Method, apparatus, and system for wireless monitoring

Abstract

To provide a method, apparatus, and system for wireless monitoring.SOLUTION: In one example, a described method comprises: transmitting a first wireless signal from a first wireless device through a wireless multipath channel of a venue, the venue comprising a vehicle and an immediate vicinity of the vehicle; receiving a second wireless signal by a second wireless device in the venue through the wireless multipath channel, wherein the second wireless signal differs from the first wireless signal due to the wireless multipath channel and a modulation by an object undergoing a motion in the venue; obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal; and performing a monitoring task by monitoring, based on the TSCI, at least one of the vehicle, the object, or the motion of the object.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates generally to wireless monitoring. More specifically, the present disclosure relates to automatic and adaptive multi-mode wireless monitoring based on wireless channel information, power supply placement for a wireless monitoring system, enhancing vehicle security through wireless monitoring based on wireless channel information, triggering an assistant device based on wireless monitoring using wireless channel information (CI), and various power supply designs and qualifications for a wireless monitoring system or device that performs wireless monitoring. [Background technology]

[0002] With the proliferation of Internet of Things (IoT) applications, billions of home appliances, phones, smart devices, security systems, environmental sensors, vehicles, buildings, and other wirelessly connected devices will transmit data, communicate with each other and with people, and measure and track anything, anytime. In recent years, the ubiquitous deployment of wireless radio devices has made wireless sensing a key technology for measuring what is happening in our surrounding environment. Furthermore, because human activity affects wireless signal propagation, understanding and analyzing how wireless signals respond to human activity can reveal rich information about the activities around us. As more bandwidth becomes available in new generations of wireless systems, wireless sensing will enable many smart IoT applications that are currently only imagined but are possible in the near future. This is because increased bandwidth allows us to see more multipaths in rich scattering environments, such as indoors or metropolitan areas, which can be treated as hundreds of virtual antennas / sensors. Thus, wireless sensing and tracking are attracting much attention in the era of the Internet of Things. To improve the efficiency of device computation, power management, and environmental channel traffic (such as channel availability and usage) management, and to improve the sensitivity and resolution of detected events, automatic and adaptive multi-mode operation is desirable but not yet available.

[0003] Vehicle monitoring has become a critical application with the ubiquitous deployment of wireless devices in vehicles. For example, through occupant recognition, vehicle monitoring can identify pet movements and breathing (pet recognition), identify subtle movements and breathing of children (child recognition), detect movement in the trunk (unknown recognition), detect glass breakage (window breakage), and detect hit-and-run accidents. Existing methods and systems for vehicle monitoring are not completely satisfactory in terms of safety and security concerns. Vehicle monitoring requires power to operate, such as power / energy from a battery, sunlight, or other sources. By some means of energy harvesting and energy storage elements, the power / energy portion can free the device from the need for any electrical outlet (in the car or at home). By flexibly placing the device, transmitter, or receiver connected to some power source (e.g., a solar panel), the user may not need to frequently remove the device to manually recharge it, which can be applied not only to vehicle monitoring but also to other interior monitoring applications.

[0004] Digital assistant systems such as Google Home and Amazon Alexa have brought convenience to people's daily lives. Voice commands are the most common way to trigger these digital assistant systems, but they can require two or more attempts due to unsatisfactory recognition of the user's voice command or background noise. Wireless monitoring using wireless channel state information (CSI) has attracted much attention in the Internet of Things era. However, there has been no method to provide automatic assistance by utilizing both wireless monitoring and digital assistant systems. While the location of wireless monitoring devices can play an important role in providing adequate coverage, there are no existing designs for power sources for wireless monitoring devices that allow for sufficient flexibility in device location. Summary of the Invention

[0005] The present disclosure relates generally to wireless monitoring. More specifically, the present disclosure relates to automatic and adaptive multi-mode wireless monitoring based on wireless channel information, power supply placement for a wireless monitoring system, enhancing vehicle security through wireless monitoring based on wireless channel information, triggering an assistant device based on wireless monitoring using wireless channel information (CI), and various power supply designs and qualifications for a wireless monitoring system or device that performs wireless monitoring.

[0006] In one embodiment, a method is described that is implemented by a wireless monitoring system having a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory that are executed by the processor. The method includes: transmitting, using a transmitter, a wireless signal over a wireless multipath channel of a location; receiving, using a receiver, the wireless signal over the wireless multipath channel, where the wireless signal is affected by the wireless multipath channel and modulation caused by object movement within the location; obtaining a set of channel information (CI) for the wireless multipath channel based on the wireless signal; performing a monitoring task by monitoring the object and its movement based on the set of CI; determining a plurality of allowable system states of the wireless monitoring system, where each allowable system state is associated with a respective setting of at least one of the wireless signal, a series of sounding signals in the wireless signal, or the monitoring task; selecting one of the allowable system states as a system state of the wireless monitoring system based on the monitoring task; and configuring the wireless monitoring system by applying the setting associated with the selected allowable system state to the wireless monitoring system.

[0007] In another embodiment, a method for configuring a wireless monitoring system is described, the method including transmitting a wireless signal from a transmitter through a wireless multipath channel at a location, receiving the wireless signal through the wireless multipath channel, the wireless signal being affected by the wireless multipath channel and modulation by an object's movement within the location, using a processor, a memory, and a set of instructions to obtain a set of channel information (CI) for the wireless multipath channel based on the wireless signal, performing a monitoring task by monitoring the object and its movement based on the set of CIs, determining a plurality of allowable system states for the wireless monitoring system, each allowable system state being associated with a respective setting, automatically selecting one of the allowable system states as a system state of the wireless monitoring system based on the monitoring task, and configuring the wireless monitoring system by applying a setting associated with the selected allowable state to at least one of the transmitter, the receiver, the wireless signal, a series of sounding signals of the wireless signal, or the set of CIs based on the system state.

[0008] In yet another embodiment, a wireless monitoring system is described. The wireless monitoring system includes a transmitter, a receiver, and a processor. The transmitter is configured to transmit a wireless signal over a wireless multipath channel of a location. The receiver is configured to receive the wireless signal over the wireless multipath channel, the wireless signal being affected by the wireless multipath channel and modulation of an object moving within the location; obtain a set of channel information (CI) for the wireless multipath channel based on the wireless signal; and perform a monitoring task by monitoring the object and its movement based on the set of CIs. The processor is configured to determine a plurality of allowable system states of the wireless monitoring system, each allowable system state being associated with a respective setting of at least one of the wireless signal, a series of sounding signals for the wireless signal, or a monitoring task; select one of the allowable system states as a system state of the wireless monitoring system based on the monitoring task; and configure the wireless monitoring system by applying a setting associated with the selected allowable system state to at least one of the transmitter, the receiver, the wireless signal, the set of CIs, or monitoring of the object based on the system state.

[0009] In another embodiment, a wireless device of a wireless monitoring system is described. The wireless device includes: a receiver configured to receive a wireless signal transmitted by a transmitter through a wireless multipath channel of a location, the wireless signal being affected by modulation of the wireless multipath channel and an object's movement within the location; a processor communicatively coupled to the receiver; a memory communicatively coupled to the processor; and a set of instructions stored in the memory. When executed by the processor, the set of instructions causes the processor to perform a monitoring task by obtaining a set of channel information (CI) for the wireless multipath channel based on the wireless signal and monitoring the object and its movement based on the set of CI. A plurality of allowable system states are determined for the wireless monitoring system, each of the allowable system states being associated with a respective setting of at least one of the wireless signal, a set of sounding signals for the wireless signal, or a monitoring task. One of the allowable system states is selected as a system state of the wireless monitoring system based on the monitoring task. The wireless monitoring system is configured by applying a setting associated with the selected allowable system state to at least one of the transmitter, the receiver, the wireless signal, the set of CI, or monitoring of the object based on the system state.

[0010] In one embodiment, a method is described that is implemented by a wireless monitoring system having a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory that are executed by the processor, the method including: positioning and powering a transmitter at a first location within a location, positioning and powering a receiver at a second location within the location, transmitting a wireless signal from the transmitter over a wireless multipath channel of the location, receiving the wireless signal by the receiver over the wireless multipath channel, where the wireless signal is affected by the wireless multipath channel and modulation of an object moving within the location, obtaining a set of channel information (CI) for the wireless multipath channel based on the wireless signal, and monitoring the object and its movement based on the set of CI.

[0011] In another embodiment, a method for positioning and powering a wireless monitoring system is described. The method includes: positioning a transmitter at a first location within a venue, the transmitter being part of a first target device at the first location; and positioning a receiver at a second location within the venue, the receiver being part of a second target device at the second location, each of the first target device and the second target device comprising at least one of a power supply unit, a power management unit, a power transfer unit, an energy storage unit, a power generation unit, or an energy harvesting unit. The method includes powering each of the transmitter and receiver based on at least one of the unit, or respective energy harvesting units; transmitting a wireless signal from the transmitter over a wireless multipath channel of the location; receiving the wireless signal by the receiver over the wireless multipath channel, the wireless signal being affected by the wireless multipath channel and modulation of an object moving within the location; obtaining a set of channel information (CI) for the wireless multipath channel based on the wireless signal using a processor and a memory communicatively coupled to the processor and a set of instructions stored in the memory; and monitoring at least one of the object or movement of the object based on the set of CI.

[0012] In yet another embodiment, a wireless monitoring system is described. The wireless monitoring system includes a first target device, a second target device, and a processor. The first target device is disposed at a first location within a location. The first target device includes a transmitter configured to transmit a wireless signal through a wireless multipath channel of the location. The second target device is disposed at a second location within the location. The second target device includes a receiver configured to receive the wireless signal through the wireless multipath channel, the wireless signal being affected by modulation of the wireless multipath channel and an object moving within the location. Each of the first target device and the second target device includes at least one of a power supply unit, a power management unit, a power transfer unit, an energy storage unit, a power generation unit, or an energy harvesting unit for providing power to the transmitter and the receiver, respectively. The processor is configured to obtain a set of channel information (CI) for the wireless multipath channel based on the wireless signal, and monitor at least one of the object or the object's movement based on the set of CI.

[0013] In another embodiment, a wireless device of a wireless monitoring system is described. The wireless device includes a receiver, a processor communicatively coupled to the receiver, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. The receiver is configured to receive a wireless signal transmitted by a transmitter over a wireless multipath channel of a location. The wireless signal is affected by modulation of the wireless multipath channel and objects moving within the location. The transmitter is part of a first target device located at a first position in the location. The wireless device is a second target device located at a second position within the location. Each of the first target device and the second target device includes at least one of a power supply unit, a power management unit, a power transfer unit, an energy storage unit, a power generation unit, or an energy harvesting unit for providing power to the transmitter and the receiver, respectively. When executed by a processor, the set of instructions causes the processor to: perform a test procedure to determine first and second positions for placing first and second target devices, respectively, based on a criterion, wherein each of the first and second target devices is powered based on its respective position; obtain a set of channel information (CI) for the wireless multipath channel based on the wireless signal; and monitor at least one of an object or movement of the object based on the set of CI.

[0014] In one embodiment, a first wireless device of a wireless monitoring system is described. The first wireless device includes a receiver, a processor communicatively coupled to the receiver, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. The receiver is configured to receive a first wireless signal over a wireless multipath channel at a location. The location includes a vehicle and an immediate vicinity of the vehicle. The first wireless signal is received based on a transmitted wireless signal transmitted by a second wireless device of the wireless monitoring system. The first wireless signal differs from the transmitted wireless signal due to the wireless multipath channel and modulation by an object moving within the location. The set of instructions, when executed by the processor, cause the processor to obtain a time series of channel information (TSCI) of the wireless multipath channel based on the first wireless signal and perform a monitoring task by monitoring at least one of a vehicle, an object, or object movement based on the TSCI.

[0015] In another embodiment, a method for a wireless monitoring system is described. The method includes transmitting a first wireless signal from a first wireless device within a location over a wireless multipath channel of the location, the location including a vehicle and an immediate vicinity of the vehicle, receiving a second wireless signal by a second wireless device within the location over the wireless multipath channel, the second wireless signal differing from the first wireless signal due to the wireless multipath channel and modulation of the first wireless signal by an object moving within the location, obtaining, using a processor, a memory communicatively coupled to the processor and a set of instructions stored in the memory, a time series of channel information (TSCI) for the wireless multipath channel based on the second wireless signal, and performing a monitoring task by monitoring at least one of a vehicle, an object, or object movement based on the TSCI.

[0016] In yet another embodiment, a first wireless device of a wireless monitoring system is described. The first wireless device includes a transmitter, a processor communicatively coupled to the transmitter, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. When executed by the processor, the set of instructions causes the processor to generate a first wireless signal and transmit the first wireless signal through a wireless multipath channel at a location. The location includes a vehicle and an immediate vicinity of the vehicle. A second wireless signal is received by a second wireless device of the wireless monitoring system based on the first wireless signal. The second wireless signal differs from the first wireless signal due to modulation by the wireless multipath channel and an object moving at the location. A time series of channel information (TSCI) of the wireless multipath channel is obtained based on the second wireless signal. A monitoring task is performed by monitoring at least one of a vehicle, an object, or object movement based on the TSCI.

[0017] In another embodiment, a wireless monitoring system is described. The wireless monitoring system includes a first wireless device and a second wireless device. The first wireless device is configured to transmit a first wireless signal through a wireless multipath channel at a location, the location including a vehicle and an immediate vicinity of the vehicle. The second wireless device is configured to receive a second wireless signal based on the first wireless signal transmitted through the wireless multipath channel, the second wireless signal differing from the first wireless signal due to modulation by the wireless multipath channel and an object moving within the location, obtain a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal, and perform a monitoring task by monitoring at least one of a vehicle, an object, or object movement based on the TSCI, wherein the first wireless device and the second wireless device are at different locations within the vehicle.

[0018] In one embodiment, an automated assistant system is described. The automated assistant system includes a transmitter, a receiver, a processor, and an assistant device. The transmitter is configured to transmit a first wireless signal through a wireless multipath channel of a location. The receiver is configured to receive a second wireless signal through the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel being affected by the movement of an object within the location. The processor is configured to obtain a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal and monitor the movement of the object within the location based on the TSCI. The assistant device is configured to generate assistance corresponding to the object within the location based on the monitoring.

[0019] In another embodiment, a method for an automated assistant system is described. The method includes: transmitting a first wireless signal from a first wireless device within the location through a wireless multipath channel of the location; receiving a second wireless signal by a second wireless device within the location through the wireless multipath channel, the second wireless signal being different from the first wireless signal due to the wireless multipath channel being affected by movement of a person within the location; obtaining, using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory, a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal; monitoring movement of a person within the location based on the TSCI; and generating assistance to a person within the location based on a monitoring result without input from the person.

[0020] In yet another embodiment, a smart speaker is described. The smart speaker includes a receiver and a processor. The receiver is configured to receive a first wireless signal over a wireless multipath channel of a location. The first wireless signal is received based on a transmitted wireless signal transmitted by a wireless device separate from the smart speaker. The first wireless signal differs from the transmitted wireless signal due to modulation by the wireless multipath channel and an object moving within the location. The processor is configured to obtain a time series of channel information (TSCI) of the wireless multipath channel based on the first wireless signal, monitor the movement of the object within the location based on the TSCI, and generate assistance regarding the object within the location based on the monitoring and an attempt to communicate with the object.

[0021] In one embodiment, an accessory for a wireless monitoring system is described. The accessory includes at least one physical connection mechanism for attaching the accessory to at least one of a first wireless device in the wireless monitoring system or a second wireless device in the wireless monitoring system. The first wireless device is configured to transmit a first wireless signal over a wireless multipath channel of a location. The second wireless device is configured to receive a second wireless signal over the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel being affected by movement of objects within the location. The wireless monitoring system includes a processor configured to obtain a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal and monitor movement of objects within the location based on the TSCI.

[0022] In another embodiment, a wireless monitoring system is described. The wireless monitoring system includes a first wireless device, a second wireless device, a processor, and an accessory configured to attach the accessory to at least one of the first wireless device or the second wireless device, the accessory comprising at least one physical connection mechanism. The first wireless device is configured to transmit a first wireless signal through a wireless multipath channel of a location. The second wireless device is configured to receive a second wireless signal through the wireless multipath channel, the second wireless signal being different from the first wireless signal due to the wireless multipath channel being affected by the movement of objects within the location. The processor is configured to obtain a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal and monitor the movement of objects within the location based on the TSCI.

[0023] In yet another embodiment, a wireless device of a wireless monitoring system is described. The wireless device includes a processor, a memory communicatively coupled to the processor, an interface to an accessory, and at least one of a transmitter or a receiver communicatively coupled to the processor. The transmitter is configured to transmit a first wireless signal to the receiver through a wireless multipath channel of a location. The receiver is configured to receive a second wireless signal through the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel being affected by the movement of objects within the location. A time series of channel information (TSCI) of the wireless multipath channel is obtained based on the second wireless signal. The movement of objects within the location is monitored based on the TSCI. The accessory includes at least one physical connection mechanism configured to attach the accessory to the wireless device via the interface. When attached to the accessory based on the interface and the at least one physical connection mechanism, the wireless device is powered by a power cord connected to a power plug having protruding pins that are inserted into a power outlet of a power source. The accessory includes at least one of a power cord, a power plug, or a space-saving short power cord.

[0024] In one embodiment, a method for a certified wireless system is described. The method includes transmitting a wireless signal from a Type 1 device to a Type 2 device through a wireless multipath channel of a location, where the Type 1 device and the Type 2 device are heterogeneous wireless devices, receiving the wireless signal by the Type 2 device, obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the wireless signal, performing a certification test based on the TSCI for at least one certified device, which is at least one of the Type 1 device, a module of the Type 1 device, an integrated circuit (IC) of the Type 1 device, a Type 2 device, a module of the Type 2 device, or an IC of the Type 2 device, determining that each of the at least one certified device is a certified device based on a determination that respective certification criteria associated with the certified device are satisfied, and performing a task based on the TSCI using the at least one certified device to obtain the at least one certified device. The Type 2 device may transmit the TSCI (or a simplified or compressed version of the TSCI) to the Type 1 device using a wireless multipath channel (e.g., in a return packet based on a standard such as 802.11), or using another wireless channel, or over a wired network.

[0025] Another embodiment describes a qualified wireless system including: a Type 1 heterogeneous wireless device configured to transmit a wireless signal through a wireless multipath channel of a location; a Type 2 heterogeneous wireless device configured to receive the wireless signal and obtain a time series of channel information (TSCI) of the wireless multipath channel based on the wireless signal; and a processor communicatively coupled to a memory storing a set of instructions and configured to perform a qualification test based on the TSCI on at least one qualified device, the at least one qualified device being at least one of a Type 1 device, a module of the Type 1 device, an integrated circuit (IC) for the Type 1 device, a module of the Type 2 device, or an IC for the Type 2 device, to obtain the at least one qualified device; determine that each of the at least one qualified device is a qualified device based on a determination that a respective qualification criterion associated with the qualified device is satisfied; and perform tasks based on the TSCI using the at least one qualified device to obtain the at least one qualified device.

[0026] Other concepts relate to software for implementing the present disclosure for wireless monitoring in rich clutter environments. Additional novel features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following examples and accompanying drawings, or may be learned by the manufacture or operation of the examples. The novel features of the present disclosure may be realized and attained by practice or use of various aspects of the methods, instrumentalities, and combinations described in the detailed examples set forth below. [Brief explanation of the drawings]

[0027] The methods, systems, and / or devices described herein will be further explained with reference to exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These embodiments are non-limiting exemplary embodiments, and like reference numerals represent like structures throughout the several views of the drawings.

[0028] [Figure 1] 1 illustrates an example scenario in which the movement of an object is monitored and tracked, according to some embodiments of the present disclosure.

[0029] [Figure 2A] 1 illustrates a mode transition process for a wireless monitoring system according to some embodiments of the present disclosure.

[0030] [Figure 2B] 10 illustrates another mode transition process for a wireless monitoring system according to some embodiments of the present disclosure.

[0031] [Figure 3] 1 illustrates a flowchart of an exemplary method for a wireless monitoring system, according to some embodiments of the present disclosure.

[0032] [Figure 4] 10 illustrates a flowchart of another exemplary method for a wireless monitoring system, according to some embodiments of the present disclosure.

[0033] [Figure 5] 1 illustrates a system state transition process for a wireless monitoring system according to some embodiments of the present disclosure.

[0034] [Figure 6] 10 illustrates another system state transition process for a wireless monitoring system according to some embodiments of the present disclosure.

[0035] [Figure 7A] 1 illustrates several arrangements for transmitters and receivers in a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0036] [Figure 7B] 10 illustrates another arrangement for a transmitter and receiver in a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0037] [Figure 7C] 10 illustrates yet another arrangement for a transmitter and receiver in a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0038] [Figure 8] 1 illustrates a flowchart of an exemplary method for a wireless monitoring system, according to some embodiments of the present disclosure.

[0039] [Figure 9A] 1 illustrates an occupant recognition feature of a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0040] [Figure 9B] 1 illustrates a tamper recognition feature of a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0041] [Figure 10] 1 illustrates a flowchart of an exemplary method for a vehicle wireless monitoring system, according to some embodiments of the present disclosure.

[0042] [Figure 11] 1 illustrates an example state flow for a vehicle wireless monitoring system according to some embodiments of the present disclosure.

[0043] [Figure 12A] 1 illustrates exemplary functionality of an automated assistant system according to some embodiments of the present disclosure.

[0044] [Figure 12B] 1 illustrates another exemplary function of an automated assistant system according to some embodiments of the present disclosure.

[0045] [Figure 13] 1 shows a flowchart of an example method for triggering an assistant device based on wireless monitoring, according to some embodiments of the present disclosure.

[0046] [Figure 14] 1 illustrates a flowchart of an example method for wireless monitoring with a flexible power source, according to some embodiments of the present disclosure.

[0047] [Figure 15] 15A and 15B illustrate an exemplary device having a power supply design according to some embodiments of the present disclosure.

[0048] [Figure 16A] 1 illustrates an exemplary accessory for mounting a device to a wall surface, according to some embodiments of the present disclosure.

[0049] [Figure 16B] 16B illustrates an exemplary device coupled to the accessory shown in FIG. 16A according to some embodiments of the present disclosure.

[0050] [Figure 17A] 1 illustrates an exemplary accessory for attaching and connecting a device to a power outlet, according to some embodiments of the present disclosure.

[0051] [Figure 17B] 17B illustrates an exemplary device coupled to the accessory shown in FIG. 17A according to some embodiments of the present disclosure.

[0052] [Figure 18A] , [Figure 18B] 1 illustrates another exemplary device having a power supply design according to some embodiments of the present disclosure.

[0053] [Figure 19] 1 illustrates a scenario where an integrated or convertible device is utilized as a plug-in design, according to some embodiments of the present disclosure.

[0054] [Figure 20]1 illustrates a scenario where an integrated or convertible device is utilized as a desktop design, according to some embodiments of the present disclosure.

[0055] [Figure 21] 1 illustrates an exemplary device having interchangeable plugs for a power source, according to some embodiments of the present disclosure.

[0056] [Figure 22] 1 illustrates an example block diagram of a first wireless device of a wireless monitoring system, according to some embodiments of the present disclosure.

[0057] [Figure 23] 1 illustrates an example block diagram of a second wireless device of a wireless monitoring system, according to some embodiments of the present disclosure.

[0058] [Figure 24] 1 illustrates exemplary performance of motion detection based on passive infrared (PIR) sensing and WiFi sensing, according to some embodiments of the present disclosure.

[0059] [Figure 25] 1 illustrates a flowchart of an exemplary method for a certified wireless sensing system, according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0060] In the following detailed description, numerous specific details are set forth, by way of example, to provide a thorough understanding of the relevant disclosure. However, it should be apparent to those skilled in the art that the present disclosure may be practiced without such details. In other instances, well-known methods, procedures, components, and / or circuits have been described at a relatively high level, without detail, in order to avoid unnecessarily obscuring aspects of the present disclosure.

[0061] In one embodiment, the present disclosure discloses a method, apparatus, device, system, and / or software (method / apparatus / device / system / software) for a wireless monitoring system. Time-series channel information (CI) of a wireless multipath channel may be obtained (e.g., dynamically) using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. A time series of CI (TSCI) may be extracted from wireless signals (signals) transmitted between a type 1 heterogeneous wireless device (e.g., a wireless transmitter, TX) and a type 2 heterogeneous wireless device (e.g., a wireless receiver, RX) at a venue over the channel. The channel may be affected by the representations (e.g., motion, movement, representation, and / or position / pose / shape / representation changes) of objects at the venue. Objects and / or their motion characteristics and / or spatial-temporal information (STI, e.g., motion information) may be monitored based on the TSCI. Tasks may be performed based on the characteristics and / or STI. A presentation associated with the task may be generated in a user interface (UI) on the user's device. The TSCI may be a wireless signal stream. The TSCI or each CI may be pre-processed. The device may be a station (STA). The symbol "A / B" means "A and / or B" in this disclosure.

[0062] Expressions can include placement, placement of movable parts, location, position, orientation, identifiable location, area, spatial coordinates, presentation, state, expression, static representation, size, length, width, height, angle, scale, shape, curve, surface, area, volume, pose, posture, sign, body representation, dynamic representation, dynamic noun, movement, movement sequence, gesture, stretch, contraction, distortion, deformation, body representation (e.g., head, face, eyes, mouth, tongue, hair, voice, neck, limbs, arms, hands, legs, feet, muscles, moving parts), surface representation (e.g., shape, texture, material, color, electromagnetic (EM) properties, visual pattern, humidity, reflectivity, translucency, flexibility), material properties (e.g., living tissue, hair, fabric, metal, wood, leather, plastic, metallic, artificial material, solid, liquid, gas, temperature), movement, activity, behavior, change in expression, and / or any combination.

[0063] Wireless signals include transmit / receive signals, EM radiation, RF signals / transmissions, signals in licensed / unlicensed / ISM bands, band-limited signals, baseband signals, wireless / mobile / cellular communication signals, wireless / mobile / cellular network signals, mesh signals, optical signals / communications, downlink / uplink signals, unicast / multicast / broadcast signals, standard (e.g. WLAN, WWAN, WPAN, WBAN, international, national, industry, de facto, IEEE, IEEE 802, 802.11 / 15 / 16, WiFi, 802.11n / ac / ax / be, 3G / 4G / LTE / 5G / 6G / 7G / 8G, 3GPP, blue tooth, BLE, Zigbee, RFID, UWB, WiMax) compliant signals, protocol signals, standard frames, beacon / pilot / search / inquiry / acknowledge / handshake / synchronization signals, management / control / data signals, standardized wireless / cellular communication protocols, reference signals, source signals, motion probe / detection / The CI may include a sensing signal and / or a series of signals. The wireless signal may include line-of-sight (LOS) and / or non-LOS components (or paths / links). Each CI may be extracted / generated / calculated / detected at a layer of the Type 2 device (e.g., the PHY / MAC layer of the OSI model) and obtained by an application (e.g., software, firmware, driver, app, wireless monitoring software / system).

[0064] A wireless multipath channel can include: a communication channel, an analog frequency channel (e.g., analog carrier frequencies around 700 / 800 / 900 MHz, 1.8 / 1.8 / 2.4 / 3 / 5 / 6 / 27 / 60 GHz), a coded channel (e.g., CDMA), and / or a channel of a wireless network / system (e.g., WLAN, WiFi, mesh, LTE, 4G / 5G, Bluetooth, Zigbee, UWB, RFID, microwave). It can include two or more channels. The channels can be contiguous (e.g., adjacent / overlapping bands) or non-contiguous (e.g., non-overlapping WiFi channels, one at 2.4 GHz and one at 5 GHz).

[0065] The TSCI can be extracted from a wireless signal at a layer of a Type-2 device (e.g., a layer of the OSI reference model, a physical layer, a data link layer, a logical link control layer, a media access control (MAC) layer, a network layer, a transport layer, a session layer, a presentation layer, an application layer, a TCP / IP layer, an Internet layer, or a link layer). The TSCI may also be extracted from a derived signal (e.g., a baseband signal, a motion detection signal, or a motion sensing signal) derived from a wireless signal (e.g., an RF signal). It may be a (wireless) measurement detected by a communication protocol (e.g., a standardized protocol) using an existing mechanism (e.g., a wireless / cellular communication standard / network, 3G / LTE / 4G / 5G / 6G / 7G / 8G, WiFi, IEEE 802.11 / 15 / 16). The derived signal may include a packet having at least one of a preamble, a header, and a payload (e.g., for data / control / management in a wireless link / network). The TSCI may be extracted from a probe signal in a packet (e.g., a training sequence, STF, LTF, L-STF, L-LTF, L-SIG, HE-STF, HE-LTF, HE-SIG-A, HE-SIG-B, or CEF). The motion detection / sensing signal may be recognized / identified based on the probe signal. The packet may be a standard-compliance protocol frame, a management frame, a control frame, a data frame, a sounding frame, an excitation frame, an illumination frame, a null data frame, a beacon frame, a pilot frame, a probe frame, a request frame, a response frame, an association frame, a reassociation frame, a disassociation frame, an authentication frame, an action frame, a report frame, a poll frame, an announcement frame, an extension frame, an inquiry frame, an acknowledgement frame, an RTS frame, a CTS frame, a QoS frame, a CF-Poll frame, a CF-Ack frame, a block acknowledgement frame, a reference frame, a training frame, and / or a synchronization frame.

[0066] The packet may contain control data and / or motion detection probes. Data (e.g., Type 1 device IDs, parameters, characteristics, settings, control signals, commands, instructions, notifications, and broadcast-related information) may be obtained from the payload. The wireless signal may be transmitted by a Type 1 device and received by a Type 2 device. A database (e.g., in a local server, hub device, cloud server, or storage network) may be used to store TSCI, characteristics, STI, signatures, patterns, behaviors, trends, parameters, analysis, output responses, identification information, user information, device information, channel information, location (e.g., map, environment model, network, proximity device / network) information, task information, class / category information, presentation (e.g., UI) information, and / or other information.

[0067] A Type 1 / Type 2 device may include at least one of electronics, circuitry, transmitter (TX) / receiver (RX) / transceiver, RF interface, "origin satellite" / "tracker bot," unicast / multicast / broadcast device, wireless power device, power / destination device, wireless node, hub device, target device, motion detection device, sensor device, remote / wireless sensor device, wireless communication device, wireless enabled device, standard compliant device, and / or receiver. A Type 1 (or Type 2) device may be heterogeneous because, if multiple instances of a Type 1 (or Type 2) device exist, they may have different circuitry, enclosure, structure, purpose, auxiliary functionality, chips / ICs, processor, memory, software, firmware, network connectivity, antenna, brand, model, appearance, form, shape, color, material, and / or specifications. A Type 1 / Type 2 device may include an access point, a router, a mesh router, an Internet of Things (IoT) device, a wireless terminal, one or more radio / RF subsystems / radio interfaces (e.g., 2.4 GHz radio, 5 GHz radio, fronthaul radio, backhaul radio), a modem, an RF front end, an RF / radio chip or integrated circuit (IC).

[0068] At least one of Type 1 devices, Type 2 devices, links between them, objects, characteristics, STI, motion monitoring, and tasks may be associated with an identification (ID) such as a UUID. Type 1, Type 2, or another device may acquire, store, retrieve, access, preprocess, condition, process, analyze, monitor, or apply TSCI. Type 1 and Type 2 devices may communicate network traffic on other channels (e.g., Ethernet, HDMI, USB, Bluetooth, BLE, WiFi, LTE, other networks, wireless multipath channels) in parallel with wireless signals. Type 2 devices may passively observe, monitor, or receive wireless signals from Type 1 devices on wireless multipath channels without establishing a connection (e.g., association / authentication) with or requesting service from the Type 1 device.

[0069] A transmitter (i.e., Type 1 device) can function (act as) a receiver (i.e., Type 2 device) temporarily, sporadically, continuously, repeatedly, interchangeably, alternately, simultaneously, in parallel, and / or simultaneously, and vice versa. A device may function as a Type 1 device (transmitter) and / or a Type 2 device (receiver) temporarily, sporadically, continuously, repeatedly, simultaneously, in parallel, and / or simultaneously. There may be multiple wireless nodes, each of which is a Type 1 (TX) and / or Type 2 (RX) device. TSCI may be obtained for each two nodes when exchanging / communicating wireless signals. An object's characteristics and / or STI may be monitored individually based on the TSCI or jointly based on two or more (e.g., all) TSCIs.

[0070] An object's movement may be monitored actively (in that its Type 1 device, Type 2 device, or both are wearable / associated with the object) and / or passively (in that both the Type 1 device and the Type 2 device are not wearable / associated with the object). It may be passive because the object may not be associated with a Type 1 device and / or a Type 2 device. The object (e.g., a user, an automated guided vehicle, or an AGV) may not need to carry / install any wearable / fixture (i.e., Type 1 devices and Type 2 devices are not wearable / attached equipment that the object needs to carry to perform a task). It may be active because the object may be associated with either a Type 1 device or a Type 2 device. The object may carry (or install) a wearable / attachment (e.g., a Type 1 device, a Type 2 device, or equipment communicatively coupled to either a Type 1 device or a Type 2 device).

[0071] The presentation may be visual, audio, image, video, animation, graphic presentation, text, etc. The computation of the task may be performed by a processor (or logic unit) of the Type 1 device, a processor (or logic unit) of the IC of the Type 1 device, a processor (or logic unit) of the Type 2 device, a processor of the IC of the Type 2 device, a local server, a cloud server, a data analysis subsystem, a signal analysis subsystem, and / or another processor. This work may be performed with or without a radio fingerprint or baseline (e.g., collection, processing, processing, transmission, and / or training phase / previous survey / latest survey / initial radio survey, passive indications), training, profile, trained profile, static profile, static profile, survey, initial radio survey, initial setup, installation, retraining, update, and reset).

[0072] A Type 1 device (TX device) may comprise at least one heterogeneous radio transmitter. A Type 2 device (RX device) may include at least one heterogeneous radio receiver. A Type 1 device and a Type 2 device may be co-located. A Type 1 device and a Type 2 device may be the same device. Any device may have a data processing unit / device, a computing unit / system, a network unit / system, a processor (e.g., a logic unit), a memory communicatively coupled to the processor, and a set of instructions stored in the memory to be executed by the processor. Some processors, memories, and sets of instructions may cooperate.

[0073] There may be multiple Type 1 devices interacting (e.g., communicating, exchanging signals / control / notifications / other data) with the same Type 2 device (or multiple Type 2 devices) and / or there may be multiple Type 2 devices interacting with the same Type 1 device. Multiple Type 1 / Type 2 devices may be synchronous and / or asynchronous, have the same / different window widths / sizes and / or time shifts, have the same / different synchronization start times, synchronization end times, etc. Wireless signals transmitted by multiple Type 1 devices may be sporadic, intermittent, continuous, repetitive, synchronous, simultaneous, and / or concurrent. Multiple Type 1 / Type 2 devices may operate independently and / or cooperatively. Type 1 and / or Type 2 devices may have / include heterogeneous hardware circuits (e.g., heterogeneous chips or ICs capable of generating / receiving wireless signals, extracting CI from received signals, or making CI available). They may be communicatively coupled to the same or different servers (e.g., cloud server, edge server, local server, hub device).

[0074] The operation of one device can be based on the operation, state, internal state, storage, processor, memory output, physical location, computational resources, or network of another device. Different devices may communicate directly and / or through another device / server / hub device / cloud server. A device can be associated with one or more users and have associated settings. Settings may be selected once, pre-programmed, and / or changed (e.g., adjusted, changed, modified) / varied over time. There may be additional steps in a method. Method steps and / or additional steps may be performed in the order shown or in a different order. Any steps may be performed in parallel, iteratively, or otherwise iteratively or otherwise. A user may be a human, adult, elderly adult, male, female, infant, child, baby, pet, animal, living being, machine, computer module / software, etc.

[0075] For one or more Type 1 devices interacting with one or more Type 2 devices, any processing (e.g., time domain, frequency domain) can be different for different devices. Processing can be based on location, orientation, direction, role, user-related characteristics, settings, configuration, available resources, available bandwidth, network connection, hardware, software, processor, co-processor, memory, battery life, available power, antenna, antenna type, antenna directional / unidirectional characteristics, power settings, and / or other parameters / characteristics of the device.

[0076] The wireless receiver (e.g., a Type 2 device) may receive a signal and / or another signal from the wireless transmitter (e.g., a Type 1 device). The wireless receiver may receive another signal from another wireless transmitter (e.g., a second Type 1 device). The wireless transmitter may transmit a signal and / or another signal to another wireless receiver (e.g., a second Type 2 device). The wireless transmitter, the wireless receiver, another wireless receiver, and / or another wireless transmitter may move with the object and / or another object. The other object may be tracked.

[0077] A Type 1 and / or Type 2 device may be capable of wirelessly coupling with at least two Type 2 and / or Type 1 devices. The Type 1 device may be triggered / controlled to switch / establish a wireless coupling (e.g., association, authentication) from the Type 2 device to a second Type 2 device at another location in the location. Similarly, the Type 2 device may be triggered / controlled to switch / establish a wireless coupling from the Type 1 device to a second Type 1 device at yet another location in the location. The switching may be controlled by a server (or hub device), a processor, the Type 1 device, the Type 2 device, and / or another device. The radios used before and after the switching may be different. A second wireless signal (second signal) may be transmitted through the channel between the Type 1 device and the second Type 2 device (or between the Type 2 device and the second Type 1 device). A second TSCI of the channel may be obtained from the second signal. The second signal may be the first signal. A characteristic, STI, and / or another quantity of the object may be monitored based on the second TSCI. The Type 1 and Type 2 devices may be the same. The characteristics, STIs, and / or other quantities with different timestamps may form a waveform. The waveform may be displayed in a presentation.

[0078] The wireless signal and / or another signal may have data embedded therein. The wireless signal may be a series of probe signals (e.g., repeated transmission of a probe signal, reuse of one or more probe signals). The probe signal may vary / change over time. The probe signal may be a standard-compliant signal, a protocol signal, a standardized wireless protocol signal, a control signal, a data signal, a wireless communication network signal, a cellular network signal, a WiFi signal, an LTE / 5G / 6G / 7G signal, a reference signal, a beacon signal, a motion detection signal, and / or a motion sensing signal. The probe signal may be formatted according to a wireless network standard (e.g., WiFi), a cellular network standard (e.g., LTE / 5G / 6G), or another standard. The probe signal may include a packet having a header and a payload. The probe signal may have data embedded therein. The payload may include data. The probe signal may replace a data signal. The probe signal may be embedded in a data signal. The wireless receiver, the wireless transmitter, the other wireless receiver and / or the other wireless transmitter may be associated with at least one processor, memory communicatively coupled to the respective processor, and / or a respective set of instructions stored in the memory that, when executed, cause the processor to perform any and / or all steps necessary to determine the object's STI (e.g., movement information), initial STI, initial time, direction, instantaneous position, instantaneous angle, and / or velocity.

[0079] The processor, memory, and / or set of instructions may be associated with a Type 1 device, at least one Type 2 device, an object, a device associated with the object, another device associated with the location, a cloud server, a hub device, and / or another server.

[0080] A Type 1 device can transmit a signal in a broadcast manner to at least one Type 2 device(s) over a location channel. The signal is transmitted without the Type 1 device establishing a wireless connection (e.g., association, authentication) with any Type 2 device and without the Type 2 device requesting service from the Type 1 device. A Type 1 device can transmit to a specific media access control (MAC) address common to multiple Type 2 devices. Each Type 2 device can tune its MAC address to a specific MAC address. The specific MAC address can be associated with a location. The association can be recorded in an association table in an association server (e.g., a hub device). A location can be identified by a Type 1 device, a Type 2 device, and / or another device based on the specific MAC address, a series of probe signals, and / or at least one TSCI extracted from the probe signals.

[0081] For example, a Type 2 device may be moved to a new location (e.g., from another location). A Type 1 device may be newly configured at a location such that the Type 1 and Type 2 devices are unaware of each other. During setup, the Type 1 device may be instructed / guided / triggered / controlled (e.g., using a dummy receiver, using a hardware pin configuration / connection, using a saved configuration, using a local configuration, using a remote configuration, using a downloaded configuration, using a hub device, or using a server) to send a series of probe signals to a specific MAC address. Upon powering up, the Type 2 device may scan for probe signals according to a table (e.g., stored in a designated source, server, hub device, cloud server) of MAC addresses that can be used to broadcast in different locations (e.g., different MAC addresses used for different locations such as a house, office, enclosure, floor, multi-story building, store, airport, mall, stadium, hall, station, subway, lot, region, area, district, province, city, country, continent, etc.). When the Type 2 device detects a probe signal sent to a specific MAC address, the Type 2 device may use the table to identify the location based on the MAC address.

[0082] The location of the Type 2 device may be calculated based on the specific MAC address, the series of probe signals, and / or at least one TSCI obtained by the Type 2 device from the probe signals. The calculation may be performed by the Type 2 device.

[0083] The specific MAC address may change (e.g., be adjusted, changed, modified) over time. It may change according to timetables, rules, policies, modes, conditions, circumstances, and / or changes. The specific MAC address may be selected based on MAC address availability, preselected lists, collision patterns, traffic patterns, data traffic between the Type 1 device and other devices, available bandwidth, random selection, and / or a MAC address switching plan. The specific MAC address may be the MAC address of a second wireless device (e.g., a dummy receiver or a receiver acting as a dummy receiver).

[0084] A Type 1 device may transmit a probe signal on a channel selected from a set of channels.

[0085] At least one CI for the selected channel may be obtained by each Type 2 device from a probe signal transmitted on the selected channel. The selected channel may be changed (e.g., adjusted, changed, modified) over time. The change may be according to a timetable, rule, policy, mode, condition, situation, and / or change. The selected channel may be selected based on channel availability, random selection, a preselected list, co-channel interference, inter-channel interference, channel traffic patterns, data traffic between the Type 1 device and another device, effective bandwidth associated with the channel, security criteria, channel switching plan, criteria, quality criteria, signal quality conditions, and / or considerations.

[0086] The specific MAC address and / or selected channel information can be communicated between a Type 1 device and a server (e.g., a hub device) over a network. The specific MAC address and / or selected channel information can also be communicated between a Type 2 device and a server (e.g., a hub device) over another network. A Type 2 device can communicate the specific MAC address and / or selected channel information to another Type 2 device (e.g., via a mesh network, Bluetooth, WiFi, NFC, ZigBee, etc.). The specific MAC address and / or selected channel can be selected by a server (e.g., a hub device). The specific MAC address and / or selected channel can be signaled in an announcement channel by a Type 1 device, a Type 2 device, and / or a server (e.g., a hub device). Any information can be preprocessed before being communicated.

[0087] A wireless connection (e.g., association, authentication) between a Type 1 device and another wireless device can be established (e.g., using a signal handshake). The Type 1 device can send a first handshake signal (e.g., a sounding frame, a probe signal, a request to send RTS) to the other device. The other device can respond by sending a second handshake signal (e.g., a command or a clear to send CTS) to the Type 1 device, triggering the Type 1 device to send a signal (e.g., a series of probe signals) in a broadcast manner to multiple Type 2 devices without establishing a connection with any Type 2 devices. The second handshake signal can be a response or acknowledgment (e.g., an ACK) to the first handshake signal. The second handshake signal can include data having location and / or Type 1 device information. The other device can be a dummy device with a purpose (e.g., primary purpose, secondary purpose) to establish a wireless connection with the Type 1 device, receive the first signal, and / or send the second signal. The other device can be physically attached to the Type 1 device.

[0088] In another example, another device can send a third handshake signal to a Type-1 device that triggers the Type-1 device to broadcast a signal (e.g., a series of probe signals) to multiple Type-2 devices without establishing a connection (e.g., association, authentication) with any of the Type-2 devices. The Type-1 device can respond to the third special signal by sending a fourth handshake signal to the other device. Another device can be used to trigger multiple Type-1 devices to broadcast. The triggering may be sequential, partially sequential, partially parallel, or fully parallel. The other device may have multiple radio circuits to trigger multiple transmitters in parallel. Parallel triggering can also be achieved by using at least one additional device to perform a trigger in parallel with another device (as the other device does). The other device cannot communicate (or suspend communication) with the Type-1 device after establishing a connection with it. The suspended communication may resume. The other device can enter an inactive mode, dormant mode, sleep mode, standby mode, low power mode, OFF mode, and / or power-down mode after establishing a connection with the Type-1 device. The other device may have a specific MAC address such that the Type 1 device sends signals to the specific MAC address. The Type 1 device and / or the other device may be controlled and / or coordinated by a first processor associated with the Type 1 device, a second processor associated with the other device, a third processor associated with the specified source, and / or a fourth processor associated with the other device. The first and second processors may coordinate with each other.

[0089] A first series of probe signals may be transmitted by a first antenna of the Type 1 device to at least one first Type 2 device through a first channel at a first location. A second series of probe signals may be transmitted by a second antenna of the Type 1 device to at least one second Type 2 device through a second channel at a second location. The first series of probe signals and the second series of probe signals may be different / not different. The at least one first Type 2 device may be different / not different from the at least one second Type 2 device. The first and / or second series of probe signals may be broadcast without an established connection (e.g., association, authentication) between the Type 1 device and any Type 2 device. The first and second antennas may be the same / different.

[0090] The two locations may have different sizes, shapes, and multipath characteristics. The first and second locations may overlap. The immediate areas near the first and second antennas may overlap. The first and second channels may be the same or different. For example, the first may be WiFi and the second may be LTE. Or, both may be WiFi, but the first may be 2.4 GHz WiFi and the second may be 5 GHz WiFi. Or, both may be 2.4 GHz WiFi, but with different channel numbers, SSID names, and / or WiFi settings.

[0091] Each Type 2 device can obtain at least one TSCI from each series of probe signals, where a CI is each channel between the Type 2 device and the Type 1 device. Some first Type 2 device(s) and some second Type 2 device(s) may be the same. The first and second series of probe signals may be synchronous / asynchronous. The probe signals may be transmitted with data or may be replaced by data signals. The first antenna and the second antenna may be the same.

[0092] A first series of probe signals may be transmitted at a first rate (e.g., 30 Hz). A second series of probe signals may be transmitted at a second rate (e.g., 200 Hz). The first and second rates can be the same or different. The first and / or second rates can be changed (e.g., adjusted, varied, modified) over time. The change can be according to a timetable, rule, policy, mode, condition, situation, and / or change. Any rate can be changed (e.g., adjusted, varied, modified) over time.

[0093] The first and / or second series of probe signals may be transmitted to a first MAC address and / or a second MAC address, respectively. The two MAC addresses may be the same or different. The first series of probe signals may be transmitted in a first channel. The second series of probe signals may be transmitted in a second channel. The two channels may be the same or different. The first or second MAC addresses and the first or second channels may change over time. Any changes may be in accordance with a timetable, rule, policy, mode, state, condition, and / or change.

[0094] A Type 1 device and another device may control and / or coordinate, be physically attached to, or be of / within a common device. They may be controlled by / connected to a common data processor or connected to a common bus interconnect / network / LAN / Bluetooth network / NFC network / BLE / wired network / wireless network / mesh network / mobile network / cloud. They may share common memory or be associated with a common user, user device, profile, account, identity (ID), identifier, home, residence, physical address, location, geographic coordinates, IP subnet, SSID, home device, office device, and / or manufacturing device.

[0095] Each Type 1 device may be a signal source for a respective set of Type 2 devices (i.e., it sends a respective signal (e.g., a respective series of probe signals) to a respective set of Type 2 devices). Each Type 2 device selects a Type 1 device from all Type 1 devices as its signal source. Each Type 2 device may be selected asynchronously. At least one TSCI may be obtained by each Type 2 device from a respective series of probe signals from the Type 1 device, and the TSCI is a channel between the Type 2 device and the Type 1 device.

[0096] Each Type 2 device selects a Type 1 device as its signal source from among all Type 1 devices based on identity (ID) or Type 1 / Type 2 device identifier, task to be performed, past signal sources, history (e.g., of past signal sources, the Type 1 device, another Type 1 device, each Type 2 receiver, and / or another Type 2 receiver), threshold for switching signal sources, and / or user information, account, access information, parameters, characteristics, and / or signal strength (e.g., associated with the Type 1 device and / or each Type 2 receiver).

[0097] Initially, a Type 1 device may be a signal source for each of the initial set of Type 2 devices (i.e., the Type 1 device sends a respective signal (series of probe signals) to each of the initial set of Type 2 devices). Each initial respective Type 2 device selects a Type 1 device from among all Type 1 devices as its signal source.

[0098] A signal source of a particular Type 2 device (a Type 1 device) may be changed (e.g., adjusted, altered, modified) if: (1) the time interval between two adjacent probe signals (e.g., between the current probe signal and the immediately previous probe signal, or between the next probe signal and the current probe signal) received from the current signal source of the Type 2 device exceeds a first threshold; (2) the signal strength associated with the current signal source of the Type 2 device is less than a second threshold; (3) the processed signal strength associated with the current signal source of the Type 2 device is less than a third threshold, and the signal strength is processed with a low-pass filter, a band-pass filter, a median filter, a moving average filter, a weighted average filter, a linear filter, and / or a nonlinear filter; and / or (4) the signal strength (or processed signal strength) associated with the current signal source of the Type 2 device is below a fourth threshold for a significant percentage (e.g., 70%, 80%, 90%) of the recent time window. The percentage can exceed a fifth threshold. The first, second, third, fourth and / or fifth thresholds may be time-varying.

[0099] Condition (1) can occur when a Type 1 device and a Type 2 device gradually move farther away from each other, resulting in some probe signals from the Type 1 device becoming too weak to be received by the Type 2 device. Conditions (2) through (4) can occur when the two devices move far enough away from each other that the signal strength becomes very weak.

[0100] The signal source of a Type 2 device may not change if another Type 1 device has a signal strength weaker than the current signal source by a factor (eg, 1, 1.1, 1.2, or 1.5).

[0101] If the signal source is changed (adjusted, modified, modified, etc.), a new signal source may become effective in the near future (e.g., each next time). The new signal source may be the Type 1 device with the strongest signal strength and / or processed signal strength. The current signal source and the new signal source may be the same or different.

[0102] A list of available Type 1 devices may be initialized and maintained by each Type 2 device. The list may be updated by examining signal strengths and / or processed signal strengths associated with each set of Type 1 devices. A Type 2 device may select between a first series of probe signals from a first Type 1 device and a second series of probe signals from a second Type 1 device based on their respective probe signal rates, MAC addresses, channels, characteristics / properties / statuses, tasks to be performed by the Type 2 device, the first and second series of signal strengths, and / or other considerations.

[0103] The series of probe signals may be transmitted at a constant rate (e.g., 100 Hz). The series of probe signals may be scheduled at regular intervals (e.g., 0.01 seconds for 100 Hz), although each probe signal may experience small time perturbations, possibly due to timing requirements, timing control, network control, handshaking, message passing, collision avoidance, carrier sensing, congestion, resource availability, and / or other considerations.

[0104] The rate may be changed (e.g., adjusted, modified, or amended). The change may be according to a schedule (e.g., changed hourly), a rule, a policy, a mode, a condition, and / or a change (e.g., changed whenever an event occurs). For example, the rate may normally be 100 Hz, but may be changed to 1000 Hz in demanding situations, or to 1 Hz in low power / standby situations. The probe signal may be transmitted in bursts.

[0105] The probe signal rate may vary based on the task performed by the Type 1 or Type 2 device (e.g., a task may normally require 100 Hz, temporarily 1000 Hz for 20 seconds). In one example, transmitters (Type 1 devices), receivers (Type 2 devices), and associated tasks may be adaptively (and / or dynamically) associated with classes (e.g., classes that are low priority, high priority, emergency, critical, normal, privileged, non-subscribed, subscribed, paid, and / or unpaid). The (transmitter's) rate may be adjusted for some classes (e.g., high priority classes). If the needs of that class change, the rate can be changed (e.g., adjusted, modified, modified). If the receiver has critically low power, the rate may be reduced to reduce the receiver's power consumption for responding to the probe signal. In one example, the probe signal may be used to wirelessly transfer power to the receiver (Type 2 device), and the rate may be adjusted to control the amount of power transferred to the receiver.

[0106] The rate may be changed by (or based on): a server (e.g., a hub device), a Type 1 device, and / or a Type 2 device. Control signals may be communicated between them. The server may monitor, track, predict, and / or anticipate the needs of and / or tasks performed by the Type 2 device, and control the Type 1 device to change the rate. The server may make scheduled changes to the rate according to a timetable. The server may detect an emergency and immediately change the rate. The server may detect a developing condition and gradually adjust the rate.

[0107] Characteristics and / or STI (e.g., movement information) may be monitored individually based on TSCIs associated with a particular Type 1 device and a particular Type 2 device, and / or jointly based on any TSCIs associated with a particular Type 1 device and any Type 2 device, and / or jointly based on any TSCIs associated with a particular Type 2 device and any Type 1 device, and / or globally based on any TSCIs associated with any Type 1 device and any Type 2 device. Any joint monitoring may relate to: a user, a user account, a profile, a home, a map of the location, an environmental model of the location, and / or a user history, etc.

[0108] A first channel between a Type 1 device and a Type 2 device may be different from a second channel between another Type 1 device and another Type 2 device, and the two channels may be associated with different frequency bands, bandwidths, carrier frequencies, modulations, wireless standards, coding, encryption, payload characteristics, networks, network IDs, SSIDs, network characteristics, network settings, and / or network parameters, etc.

[0109] The two channels can relate to different types of wireless systems (e.g., two of the following: WiFi, LTE, LTE-A, LTE-U, 2.5G, 3G, 3.5G, 4G, Beyond 4G, 5G, 6G, 7G, cellular network standards, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, 802.11 systems, 802.15 systems, 802.16 systems, mesh networks, Zigbee, NFC, WiMax, Bluetooth, BLE, RFID, UWB, microwave systems, radar-like systems), for example, one channel being WiFi and the other being LTE.

[0110] The two channels may be associated with similar types of wireless systems, but different networks. For example, a first channel may be associated with a WiFi network named "Pizza and Pizza" in the 2.4 GHz band with a bandwidth of 20 MHz, while a second channel may be associated with a WiFi network with an SSID of "StarBud Hotspot" in the 5 GHz band with a bandwidth of 40 MHz. The two channels may be different channels within the same network (e.g., the "StarBud Hotspot" network).

[0111] In one embodiment, the wireless monitoring system can include training a classifier for multiple events at a location based on training TSCIs associated with the multiple events. The CIs or TSCIs associated with an event can take into account / include radio samples / characteristics / fingerprints associated with the event (and / or location, environment, object, object movement, state / emotional state / mental state / condition / stage / gesture / gait / action / movement / activity / daily activity / history / event of the object, etc.).

[0112] For each of a plurality of known events occurring at a location at a respective training (e.g., survey, wirelee survey, initial wireless survey) time associated with the known event, a respective training wireless signal (e.g., a respective series of training probe signals) may be transmitted to at least one first type 2 heterogeneous wireless device through a wireless multipath channel of the location at the respective training time by an antenna of the first type 1 heterogeneous wireless device using a processor, memory, and set of instructions of the first type 1 device.

[0113] At least one respective time series of training CIs (training TSCIs) may be asynchronously acquired by each of the at least one first Type 2 device from the (respective) training signal. The CIs may be CIs of a channel between the first Type 2 device and the first Type 1 device at a training time associated with a known event. The at least one training TSCI may be preprocessed. The training may be a wireless survey (e.g., during installation of the Type 1 device and / or the Type 2 device).

[0114] For a current event occurring within a location in a current period, a current wireless signal (e.g., a series of current probe signals) may be transmitted to at least one second Type 2 heterogeneous wireless device through a channel of the location in a current period related to the current event by an antenna of the second Type 1 heterogeneous wireless device using a processor, memory, and set of instructions of the second Type 1 device.

[0115] At least one time series of current CIs (current TSCIs) may be asynchronously acquired by each of the at least one second Type-2 device from a current signal (e.g., a series of current probe signals). The CIs may be CIs of a channel between the second Type-2 device and the second Type-1 device at a current time period associated with a current event. The at least one current TSCI may be preprocessed.

[0116] A classifier may be applied by at least one second Type 2 device to classify at least one current TSCI obtained from the series of current probe signals, to classify at least a portion of a particular current TSCI, and / or to classify a combination of at least a portion of a particular current TSCI with another portion of another TSCI. The classifier may divide the TSCIs (or features / STIs or other analysis or output responses) into clusters and associate the clusters with particular events / objects / subjects / locations / movements / activities. Labels / tags may be generated for the clusters. The clusters may be stored and searched. A classifier may be applied to associate the current TSCI (or perhaps a characteristic / STI or other analysis / output response related to the current event) with: a cluster, a known / specific event, a class / category / group / grouping / list / cluster, a set of known events / subject / location / movement / activity, an unknown event, a class / category / group / grouping / list / cluster, a set of unknown events / subject / location / movement / activity, and / or another event / subject / location / movement / activity / class / category / group / grouping / list / cluster. Each TSCI may include at least one CI, each associated with a respective timestamp. Two TSCIs associated with two Type 2 devices differ by different start times, durations, stop times, amount of CIs, sampling frequencies, and sampling periods. The CIs may have different characteristics. The first and second Type 1 devices may be at the same location. They may be the same device. At least one second Type 2 device (or their location) may be a replacement for at least one first Type 2 device (or their location). The particular second Type 2 device and the particular first Type 2 device may be the same device.

[0117] The subset of first Type 2 devices and the subset of second Type 2 devices may be the same. At least one second Type 2 device and / or at least one subset of second Type 2 devices may be a subset of at least one first Type 2 device. At least one first Type 2 device and / or at least one subset of first Type 2 devices may be a replacement for a subset of at least one second Type 2 device. At least one second Type 2 device and / or at least one subset of second Type 2 devices may be a replacement for a subset of at least one first Type 2 device. At least one second Type 2 device and / or at least one subset of second Type 2 devices may be in the same respective locations as the subset of at least one first Type 2 device. At least one first Type 2 device and / or at least one subset of first Type 2 devices may be in the same respective locations as the subset of at least one second Type 2 device.

[0118] The antenna of the Type 1 device and the antenna of the second Type 1 device may be in the same location. The antenna of the at least one second Type 2 device and / or the antenna of the subset of at least one second Type 2 device may be in the same respective location as each antenna of the subset of at least one first Type 2 device. The antenna of the at least one first Type 2 device and / or the antenna of the subset of at least one first Type 2 device may be in the same respective location as each antenna of the subset of at least one second Type 2 device.

[0119] A first section of a first duration of a first TSCI and a second section of a second duration of a second TSCI may be aligned. A map between items in the first section and items in the second section may be calculated. The first section may include a first segment (e.g., a subset) of the first TSCI having a first start / end time and / or another segment (e.g., a subset) of the processed first TSCI. The processed first TSCI may be the first TSCI processed by the first operation. The second section may include a second segment (e.g., a subset) of the second TSCI having a second start time and a second end time, and another segment (e.g., a subset) of the processed second TSCI. The processed second TSCI may be the second TSCI processed by the second operation. The first operation and / or the second operation may include subsampling, resampling, interpolation, filtering, transformation, feature extraction, preprocessing, and / or other operations.

[0120] A first item in a first section may be mapped to a second item in a second section. A first item in a first section may also be mapped to another item in a second section. Another item in a first section may also be mapped to a second item in a second section. The mapping may be one-to-one, one-to-many, many-to-one, or many-to-many. At least one function of at least one of the first item in a first section of a first TSCI, another item in a first TSCI, a timestamp of the first item, a time difference of the first item, a time difference of the first item, an adjacent timestamp of the first item, an adjacent timestamp of the first item, another timestamp related to the first item, a second item in a second section of a second TSCI, another item in a second TSCI, a timestamp of the second item, a time difference of the second item, a time difference of the second item, an adjacent timestamp of the second item, and another timestamp related to the second item may satisfy at least one constraint.

[0121] One constraint may be that the difference between the timestamp of the first item and the timestamp of the second item may be bounded upper by an adaptive (and / or dynamically adjusted) upper threshold and lower by an adaptive lower threshold.

[0122] The first section may be the entire first TSCI. The second section may be the entire second TSCI. The first time duration may be equal to the second time duration. The time duration of a section of a TSCI may be determined adaptively (and / or dynamically). A provisional section of the TSCI may be calculated. A start time and an end time of a section (e.g., provisional section, section) may be determined. A section may be determined by removing the start and end portions of the provisional section. The start portion of the provisional section may be determined as follows: Iteratively, items in the provisional section with increasing timestamps may be considered as the current item, one item at a time.

[0123] At each iteration, at least one activity measure / index may be calculated and / or considered. The at least one activity measure may be associated with at least one of the following: a current item associated with the current timestamp, a past item in the provisional section with a timestamp not greater than the current timestamp, and / or a future item in the provisional section with a timestamp not less than the current timestamp. If at least one criterion (e.g., quality criterion, signal quality condition) associated with the at least one activity measure is met, the current item may be added to the beginning of the provisional section.

[0124] The at least one criterion associated with the activity measure may include at least one of the following: (a) the activity measure is less than an adaptive (dynamically adjusted) upper threshold, (b) the activity measure is greater than an adaptive lower threshold, (c) the activity measure is less than an adaptive upper threshold consecutively for at least a predetermined amount of consecutive timestamps, (d) the activity measure is greater than an adaptive lower threshold consecutively for at least another predetermined amount of consecutive timestamps, (e) the activity measure is less than an adaptive upper threshold consecutively for at least a predetermined percentage of a predetermined amount of consecutive timestamps, (f) the activity measure is greater than an adaptive lower threshold consecutively for at least another predetermined percentage of another predetermined amount of consecutive timestamps, (g) another activity measure associated with another timestamp related to the current timestamp is less than another adaptive upper threshold and greater than another adaptive lower threshold, or (h) at least one activity measure associated with at least one respective timestamp related to the current timestamp is less than a respective upper threshold and greater than a respective lower threshold. (i) the percentage of timestamps associated with the activity measures in a set of timestamps associated with the current timestamp that are less than their respective upper thresholds and greater than their respective lower thresholds exceeds a threshold; and (j) another criterion (e.g., quality criterion, signal quality condition).

[0125] The activity measure / index associated with the item at time T1 may include at least one of the following: (1) a first function of the item at time T1 and the item at time T1-D1, where D1 is a predetermined positive quantity (e.g., a fixed time offset); (2) a second function of the item at time T1 and the item at time T1+D1; (3) a third function of the item at time T1 and the item at time T2, where T2 is a predetermined quantity (e.g., a fixed initial reference time; T2 may change (e.g., adjusted, varied, modified) over time; T2 may be updated periodically; T2 may be the start of a period and T1 may be a sliding time in the period); and (4) a fourth function of the item at time T1 and other items.

[0126] At least one of the first function, the second function, the third function, and / or the fourth function may be a function (e.g., F(X, Y, ...)) with at least two arguments X and Y. The two arguments may be scalars. The function (e.g., F) may be at least one of X, Y, (XY), (YX), abs(XY), X^a, Y^b, abs(X^aY^b), (XY)^a, (X / Y), (X+a) / (Y+b), (X^a / Y^b), and ((X / Y)^ab), where a and b may be certain predetermined quantities. For example, the function may be simply abs(XY), or (XY)^2, (XY)^4. The function may be a robust function. For example, the function is (XY)^2 when abs(XY) is less than a threshold T, and (XY)+a when abs(XY) is greater than T. Alternatively, the function may be a constant when abs(XY) is greater than T. Also, when abs(Xy) is greater than T, the function may be bounded by a slowly increasing function so that outliers cannot significantly affect the results. Another example of this function may be (abs(X / Y)-a) (where a=1). In this way, when X=Y (i.e., no change or activity), the function yields a value of 0. When X is greater than Y, (X / Y) is greater than 1 (assuming X and Y are positive), and the function is positive. When X is less than Y, (X / Y) is less than 1, and the function is negative. In another example, both arguments X and Y may be n-tuples, with X = (x_1, x_2, ..., x_n) and Y = (y_1, y_2, ..., y_n). The function may be at least one of x_i, y_i, (x_i - y_i), (y_ix_i), abs(x_i - y_i), x_i^a, y_i^b, abs(x_i^a - y_i^b), (x_i - y_i)^a, (x_i / y_i), (x_i + a) / (y_i + b), (x_i^a / y_i^b), and ((x_i / y_i)^ab), where i is a component index of the n-tuples X and Y, and 1 <= i <= n. For example, the component index of x_1 is i=1, and the component index of x_2 is i=2.The function may include a sum of another function per component of at least one of x_i, y_i, (x_i-y_i), (y_ix_i), abs(x_i-y_i), x_i^a, y_i^b, abs(x_i^a-y_i^b), (x_i-y_i)^a, (x_i / y_i), (x_i+a) / (y_i +b), (x_i^a / y_i^b), and ((x_i / y_i)^ab), where i is the component index of the n-tuples X and Y. For example, the function may be in the form sum_{i=1}^n(abs(x_i / y_i)-1) / n, or sum_{i=1}^nw_i*(abs(x_i / y_i)-1), where w_i is the weight of component i.

[0127] The map may be computed using dynamic time warping (DTW). The DTW may include constraints on at least one of the map, the items of the first TSCI, the items of the second TSCI, the first duration, the second duration, the first section, and / or the second section. Suppose the i^{th} domain item is mapped to the j^{th} range item in the map. The constraints may be on the allowable combinations of i and j (constraints on the relationship between i and j). A mismatch cost between the first section of the first duration of the first TSCI and the second section of the second duration of the second TSCI may be computed.

[0128] The first section and the second section may be aligned such that a map including a plurality of links may be established between a first item of the first TSCI and a second item of the second TSCI. Each link may associate one of the first items with a first timestamp and one of the second items with a second timestamp. A mismatch cost between the aligned first section and the aligned second section may be calculated. The mismatch cost may include a function of a cost for an item between the first item and the second item associated by a particular link of the map and a link-wise cost for a link associated with the particular link of the map.

[0129] The aligned first section and the aligned second section may be represented as a first vector and a second vector, respectively, of the same vector length. The mismatch cost may include at least one of a dot product, a dot product-like measure, a correlation-based measure, a correlation indicator, a covariance-based measure, a discrimination score, a distance, a Euclidean distance, an absolute distance, an Lk distance (e.g., L1, L2,...), a weighted distance, a distance-like measure, and / or another similarity value between the first vector and the second vector. The mismatch cost may be normalized by the respective vector lengths.

[0130] A parameter derived from the mismatch cost between a first section of a first duration of a first TSCI and a second section of a second duration of a second TSCI can be modeled with a statistical distribution, and at least one of a scale parameter, a location parameter, and / or another parameter of the statistical distribution can be estimated.

[0131] The first section of the first duration of the first TSCI may be a sliding section of the first TSCI, and the second section of the second duration of the second TSCI may be a sliding section of the second TSCI.

[0132] A first sliding window may be applied to a first TSCI, and a corresponding second sliding window may be applied to a second TSCI, and the first sliding window of the first TSCI and the corresponding second sliding window of the second TSCI may be aligned.

[0133] A mismatch cost between the aligned first sliding window of the first TSCI and the corresponding aligned second sliding window of the second TSCI can be calculated, and the current event may be associated with at least one of a known event, an unknown event, and / or another event based on the mismatch cost.

[0134] The classifier may be applied to at least one of each first section of a first duration of the first TSCI and / or each second section of a second duration of the second TSCI to obtain at least one provisional classification result, each provisional classification result being associated with a respective first section and a respective second section.

[0135] The current event can be associated with at least one of a known event, an unknown event, a class / category / group / grouping / list / set of unknown events, and / or another event based on the mismatch cost. The current event can be associated with at least one of a known event, an unknown event, and / or another event based on the most numerous provisional classification results in the multiple sections of the first TSCI and the multiple sections of the corresponding second TSCI. For example, if the mismatch cost points to a specific known event for N consecutive times (e.g., N=10), the current event can be associated with the specific known event. In another example, the current event can be associated with the specific known event if the percentage of mismatch costs within the immediately preceding N consecutive times that point to the specific known event exceeds a predetermined threshold (e.g., >80%).

[0136] In another example, the current event may be associated with a known event that achieves the smallest mismatch cost the most times in time. The current event may be associated with a known event that achieves the smallest overall mismatch cost, which is a weighted average of at least one mismatch cost associated with at least one first section. The current event may be associated with a particular known event that achieves another minimum overall cost. The current event may be associated with an "unknown event" if none of the known events achieves a mismatch cost below a first threshold T1 in a sufficient percentage of at least one first section. The current event may also be associated with an "unknown event" if none of the known events achieves an overall mismatch cost below a second threshold T2. The current event may be associated with at least one of a known event, an unknown event, and / or another event based on the mismatch cost and additional mismatch cost associated with at least one additional section of the first TSCI and at least one additional section of the second TSCI. The known events may include at least one of a door closed event, a door open event, a window closed event, a window open event, a multi-state event, an on state event, an off state event, an intermediate state event, a continuous state event, a discrete state event, a person present event, a person absent event, a life present event, and / or a life absent event.

[0137] A projection for each CI may be trained using a dimensionality reduction method based on the training TSCI. The dimensionality reduction method may include at least one of principal component analysis (PCA), PCA with different kernels, independent component analysis (ICA), Fisher's linear discriminant, vector quantization, supervised learning, unsupervised learning, self-organizing maps, autoencoders, neural networks, deep neural networks, and / or another method. The projection may be applied to at least one of the training TSCI associated with at least one event and / or the current TSCI for the classifier.

[0138] A classifier for at least one event may be trained based on a projection associated with the at least one event and associated training TSCI. At least one current TSCI may be classified / categorized based on the projection and the current TSCI. The projection may be retrained using at least one of a dimensionality reduction method and another dimensionality reduction method based on at least one of the training TSCI, the at least one current TSCI before retraining the projection, and / or additional training TSCI. The other dimensionality reduction methods may include at least one of principal component analysis (PCA), PCA with different kernels, independent component analysis (ICA), Fisher's linear discriminant, vector quantization, supervised learning, unsupervised learning, self-organizing maps, autoencoders, neural networks, deep neural networks, and / or yet another method. A classifier for at least one event may be retrained based on at least one of the retrained projection, the training TSCI associated with the at least one event, and / or the at least one current TSCI. At least one current TSCI may be classified based on the retrained projections, the retrained classifier, and / or the current TSCI.

[0139] Each CI may include a vector of complex values. Each complex value may be preprocessed to provide a magnitude of the complex value. Each CI may be preprocessed to provide a vector of non-negative real numbers containing the magnitude of the corresponding complex value. Each training TSCI may be weighted in training the projection. The projection may include multiple projection components. The projection may include at least one most significant projection component. The projection may include at least one projected component that may be useful to the classifier.

[0140] Channel / Channel information / Venue / Spatia-temporal information / Motion / Object

[0141] Channel information (CI) includes signal strength, signal amplitude, signal phase, spectral power measures, modem parameters (e.g., used in connection with modulation / demodulation in digital communication systems such as WiFi, 4G / LTE, etc.), dynamic beamforming information, transfer function components, radio state (e.g., used in digital communication systems to decode digital data, baseband processing state, RF processing state, etc.), measurable variables, sensing data, layer coarse-grained / fine-grained information (e.g., physical layer, data link layer, MAC layer, etc.), digital settings, gain settings, RF filter settings, RF front-end switch settings, DC offset settings, DC correction settings, IQ correction settings, effects of the environment (e.g., location) on the radio signal during propagation, input signal (radio signal transmitted by a Type 1 device) and output signal (Type 2 signal). The CI may be associated with or include a transformation of the CI into a radio signal (received by the device), steady state behavior of the environment, a condition profile, radio channel measurements, a received signal strength indicator (RSSI), channel state information (CSI), channel impulse response (CFR), channel frequency response (CFR), characteristics of frequency components (e.g., subcarriers) in the bandwidth, channel characteristics, channel response, timestamps, auxiliary information, data, metadata, user data, account data, access data, security data, session data, status data, supervision data, home data, identification (ID), identifiers, device data, network data, proximity data, environmental data, real-time data, sensor data, stored data, encrypted data, compressed data, protected data, and / or other channel information. Each CI may be associated with a timestamp and / or a time of arrival. The CSI can equalize / restore / minimize / reduce multipath channel effects (transmission channel) and demodulate a signal similar to that transmitted by the transmitter through the multipath channel. The CI may be associated with information related to a frequency band, a frequency signature, a frequency phase, a frequency amplitude, a frequency trend, a frequency characteristic, a frequency-like characteristic, a time domain element, a frequency domain element, a time-frequency domain element, an orthogonal decomposition characteristic, and / or a non-orthogonal decomposition characteristic of a signal passing through a channel. The TSCI may be a stream of wireless signals (e.g., CIs).

[0142] The CI may be pre-processed, processed, post-processed, stored (e.g., in a local memory, portable / mobile memory, removable memory, storage network, cloud memory, in a volatile manner, in a non-volatile manner), retrieved, transmitted, and / or received. One or more modem parameters and / or radio condition parameters may be kept constant. The modem parameters may be applied to a radio subsystem. The modem parameters may represent radio conditions. A motion detection signal (e.g., a baseband signal and / or packets decoded / demodulated from the baseband signal, etc.) may be obtained by processing (e.g., downconverting) a first radio signal (e.g., an RF / WiFi / LTE / 5G signal) by the radio subsystem using the radio conditions represented by the stored modem parameters. The modem parameters / radio conditions may be updated (e.g., using previous modem parameters or previous radio conditions). Both the previous and updated modem parameters / radio conditions may be applied to a radio subsystem of a digital communication system. Both the previous and updated modem parameters / radio conditions may be compared / analyzed / processed / monitored in a task.

[0143] The channel information may also be modem parameters (e.g., stored or newly calculated) used to process the wireless signal. The wireless signal may include multiple probe signals. The same modem parameters can be used to process multiple probe signals. The same modem parameters can also be used to process multiple wireless signals. The modem parameters may include parameters indicating settings or overall configurations for operation of the radio subsystem or baseband subsystem (or both) of the wireless sensor device. The modem parameters may include one or more of gain settings, RF filter settings, RF front-end switch settings, DC offset settings, or IQ compensation settings for the radio subsystem, or digital DC correction settings, digital gain settings, and / or digital filtering settings (e.g., for the baseband subsystem). CI may also relate to information related to time, time signature, timestamp, time amplitude, time phase, time trend, and / or time characteristics of a signal. CI may be associated with information related to the time-frequency division, signature, amplitude, phase, trend, and / or characteristics of a signal. CI may relate to signal decomposition. A CI may relate to information related to direction, angle of arrival (AoA), angle of a directional antenna, and / or phase of a signal passing through a channel. A CI may relate to the attenuation pattern of a signal passing through a channel. Each CI may be associated with a Type 1 device and a Type 2 device. Each CI may be associated with an antenna of a Type 1 device and an antenna of a Type 2 device.

[0144] The CI can be obtained from communication hardware (e.g., a Type 2 device or a Type 1 device) capable of providing the CI. The communication hardware can be a WiFi-enabled chip / IC (integrated circuit), a chip compliant with 802.11 or 802.16 or other wireless / wireless standards, a next-generation WiFi-enabled chip, an LTE-enabled chip, a 5G-enabled chip, a 6G / 7G / 8G-enabled chip, a Bluetooth-enabled chip, an NFC (near field communication)-enabled chip, a BLE (Bluetooth low energy)-enabled chip, a UWB chip, or other communication chips (e.g., Zigbee, WiMax, mesh networks). The communication hardware calculates the CI and stores the CI in a buffer memory so that the CI is available for extraction. The CI can include data related to channel state information (CSI) and / or at least one matrix. The at least one matrix can be used for channel equalization, beamforming, etc. The channel can be associated with a location. Attenuation can be due to signal propagation at the location, signal propagation through / at / near the air (e.g., the air at the location), reflection, refraction, diffraction, refractive media / reflective surfaces such as walls, doors, furniture, obstacles, and / or barriers, etc. Attenuation can be due to reflections off surfaces and obstacles (e.g., reflective surfaces, obstacles) such as floors, ceilings, furniture, fixtures, objects, people, pets, etc. Each CI can be associated with a timestamp. Each CI can include N components (e.g., N frequency-domain components in CFR, N time-domain components in CIR, or N decomposed components). Each component can be associated with a component index. Each component can be a real, imaginary, or complex quantity, magnitude, phase, flag, and / or set. Each CI can include a vector or matrix of complex numbers, a set of mixed quantities, and / or a multidimensional collection of at least one complex number.

[0145] Components of the TSCI associated with a particular component index may form respective component time series associated with the respective index. The TSCI may be divided into N component time series. Each individual component time series is associated with a respective component index. Object motion characteristics / STI may be monitored based on the component time series. In one example, one or more ranges of CI components (e.g., one range from component 11 to component 23, a second range from component 44 to component 50, and a third range having only one component) may be selected based on some criteria / cost function / signal quality metric (e.g., based on signal-to-noise ratio and / or interference level) for further processing.

[0146] Component-wise characteristics of the TSCI component-feature time series may be calculated. The component-wise characteristics may be scalars (e.g., energy) or functions with domains and ranges (e.g., autocorrelation functions, transforms, inverse transforms). Object motion characteristics / STIs may be monitored based on the component-wise characteristics. Overall characteristics (e.g., aggregate characteristics) of the TSCI may be calculated based on the component-wise characteristics of each TSCI component time series. The overall characteristics may be a weighted average of the component-wise characteristics. Object motion characteristics / STIs may be monitored based on the overall characteristics. A total quantity may be a weighted average of the individual quantities.

[0147] Type 1 devices and Type 2 devices may support WiFi, WiMax, 3G / 3G Beyond, 4G / 4G Beyond, LTE, LTE-A, 5G, 6G, 7G, Bluetooth, NFC, BLE, Zigbee, UWB, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, mesh networks, proprietary wireless systems, IEEE 802.11 standards, 802.15 standards, 802.16 standards, 3GPP standards, and / or other wireless systems.

[0148] A common wireless system and / or a common wireless channel may be shared by a Type 1 transceiver and / or at least one Type 2 transceiver. The at least one Type 2 transceiver may transmit respective signals simultaneously (or: asynchronously, synchronously, sporadically, continuously, repeatedly, in parallel, simultaneously, and / or at one time) using the common wireless system and / or the common wireless channel. The Type 1 transceiver may transmit signals to the at least one Type 2 transceiver using the common wireless system and / or the common wireless channel.

[0149] Each Type 1 device and Type 2 device may have at least one transmit and receive antenna. Each CI may be associated with one of the transmit antennas of the Type 1 device and one of the receive antennas of the Type 2 device. Each pair of transmit and receive antennas may be associated with a link, path, communication path, signal hardware path, etc. For example, if a Type 1 device has M (e.g., 3) transmit antennas and a Type 2 device has N (e.g., 2) receive antennas, there may be M x N (e.g., 3 x 2 = 6) links or paths. Each link or path may be associated with a TSCI.

[0150] At least one TSCI may correspond to various antenna pairs between a Type 1 device and a Type 2 device. The Type 1 device may have at least one antenna. The Type 2 device may also have at least one antenna. Each TSCI may be associated with an antenna of the Type 1 device and an antenna of the Type 2 device. Averaging or weighted averaging across antenna links may be performed. The averaging or weighted averaging may be across at least one TSCI. The averaging may optionally be performed over a subset of the at least one TSCI corresponding to a subset of the antenna pairs.

[0151] The timestamps of some CIs of a TSCI may be irregular and may be corrected so that the corrected timestamps of the time-corrected CIs are evenly spaced in time. In the case of multiple Type 1 devices and / or multiple Type 2 devices, the corrected timestamps may be related to the same clock or different clocks. An original timestamp associated with each of the CIs may be determined. The original timestamps may not be evenly spaced in time. The original timestamps of all CIs of a particular portion of a particular TSCI in the current sliding time window may be corrected so that the corrected timestamps of the time-corrected CIs are evenly spaced in time.

[0152] Characteristics and / or STI (e.g., motion information) may include location, location coordinates, change in location, location (e.g., initial location, new location), location on map, height, horizontal position, vertical position, distance, displacement, speed, acceleration, rotational speed, rotational acceleration, direction, movement angle, orientation, direction of movement, rotation, path, deformation, translation, contraction, extension, gait, gait cycle, head movement, repetitive movement, periodic movement, pseudo-periodic movement, impulse movement, sudden movement, falling movement, transient movement, behavior, transient behavior, movement cycle, movement frequency, time trend, temporal profile, temporal characteristics, occurrence, change, temporal change, change in CI, change in frequency, change in timing, change in gait cycle, timing, start time, start time, end time, duration, movement history, movement type, movement classification, frequency, frequency spectrum, frequency characteristics, presence, absence, proximity, proximity , retreat, object identification / identifier, object composition, head movement velocity, head movement direction, mouth-related rate, eye-related rate, breathing rate, heart rate, tidal volume, breathing depth, inhalation time, exhalation time, inhalation to sweep time ratio, airflow rate, heart rate interval, heart rate variability, hand movement rate, hand movement direction, leg movement, body movement, walking speed, hand movement velocity, position characteristics, object movement-related characteristics (e.g., change in position / location), tool movement, machine movement, compound movement, and / or combination of multiple movements, event, signal statistics, signal dynamics, anomaly, movement statistics, movement parameters, motion detection indication, motion magnitude, motion phase, similarity score, distance score, Euclidean distance, weighted distance, L_1 norm, L_2 norm, L_k norm for k>2, statistical distance, correlation, correlation indicator,Autocorrelation, covariance, autocovariance, cross-covariance, inner product, Cartesian product, motion signal transformation, motion features, motion presence, motion absence, motion localization, motion discrimination, motion recognition, object presence, object absence, object entrance, object exit, object change, movement cycle, movement count, gait cycle, movement rhythm, movement deformation, gesture, handwriting, head movement, mouth movement, cardiac movement, visceral movement, motion trend, size, length, area, volume, volume, shape, morphology, tag, start / start position, end position, start / start amount, end amount, event, fall event, security The information may include security events, accident events, home events, office events, factory events, warehouse events, manufacturing events, assembly line events, maintenance events, car-related events, navigation events, tracking events, door events, door open events, door close events, window events, window open events, window closed events, repeatable events, one-time events, consumption, non-consumption, status, physical status, health status, comfort status, emotional status, mental status, other events, analysis, output response, and / or other information. Characteristics and / or STIs may be calculated / monitored based on features calculated from the CI or TSCI (e.g., feature calculation / extraction). Static segments or profiles (and / or dynamic segments / profiles) may be identified / calculated / analyzed / monitored / extracted / acquired / marked / presented / indicated / highlighted / stored / communicated based on feature analysis. Analysis may include motion detection / motion assessment / presence detection. Computational workloads may be shared among Type 1 devices, Type 2 devices, and other processors.

[0153] The Type 1 device and / or the Type 2 device may be a local device, which may be a smartphone, a smart device, a TV, a sound bar, a set-top box, an access point, a router, a repeater, a wireless signal repeater / extender, a remote control, a speaker, a fan, a refrigerator, a microwave oven, a coffee machine, a hot water pot, an appliance, a table, a chair, a light, a lamp, a door lock, a camera, a microphone, a motion sensor, a security device, a fire hydrant, a garage door switch, a power adapter, a computer, a dongle, a computer peripheral, an electronic pad, a sofa, a tile, an accessory, a home device, a vehicle device, an office device, a building equipment, a manufacturing equipment, a watch, a glass, a clock, a television, an oven, an air conditioner, an accessory, a utility, an appliance, a smart machine, a smart vehicle, an Internet of Things (IoT), a smart house, a smart office, a smart building, a smart parking lot, a smart system, and other devices.

[0154] Each Type 1 device may be associated with a respective identifier (e.g., ID). Each Type 2 device may also be associated with a respective identification (ID). The ID may include numbers, a combination of text and numbers, a name, a password, an account, an account ID, a web link, a web address, an index to some information, and / or another ID. The ID may be assigned. The ID may be assigned by hardware (e.g., hardwired, via a dongle, and / or other hardware), software, and / or firmware. The ID may be stored (e.g., in a database, in memory, in a server (e.g., a hub device), in the cloud, locally stored, remotely stored, permanently stored, or temporarily stored) and may be searched. The ID may be associated with at least one record, account, user, household, address, phone number, social security number, customer number, another ID, another identifier, timestamp, and / or collection of data. The ID and / or a portion of the ID of the Type 1 device may be made available to the Type 2 device. The ID may be used by Type 1 devices and / or Type 2 devices for registration, initialization, communication, identification, verification, detection, recognition, authentication, access control, cloud access, networking, social networking, logging, recording, cataloging, classification, tagging, association, pairing, transactions, electronic transactions, and / or intellectual property control.

[0155] The object may be a person, user, subject, passenger, child, elderly, infant, sleeping infant, infant in a vehicle, patient, worker, high value worker, expert, medical specialist, waiter, customer in a mall, traveller at an airport / train station / bus terminal / shipping terminal, staff / laborer / customer service person in a factory / mall / supermarket / office / workplace, service person in a sewer / air ventilation system / lift well, lift in a lift well, elevator, inmate, person to be tracked / monitored, animal, plant, living thing, pet, dog, cat, smartphone, phone accessory, computer, tablet, portable computer, dongle, computer accessory equipment, network equipment, WiFi equipment, IoT device, smart watch, smart glasses, smart device, speaker, key, smart key, wallet, wallet, handbag, backpack, goods, cargo, luggage, equipment, motor, machine, air conditioner, fan, air conditioning equipment, lighting fixture, movable light, television, camera, audio and / or video equipment, It can be stationery, surveillance equipment, parts, signs, tools, carts, tickets, parking passes, passes, plane tickets, credit cards, plastic cards, access cards, food packaging, utensils, tables, chairs, cleaning equipment / tools, vehicles, automobiles, cars in parking facilities, goods in a warehouse / store / supermarket / distribution center, boats, bicycles, airplanes, drones, remote controlled cars / planes / boats, robots, manufacturing equipment, assembly lines, materials / unfinished parts / robots / trolleys / transports on a factory floor, tracked objects in an airport / shopping mart / supermarket, non-objects, absence of objects, presence of objects, objects with shape, objects changing shape, shapeless objects, mass of a fluid, mass of a liquid, mass of a gas / smoke, fire, flames, electromagnetic (EM) sources, EM media, and / or other objects.

[0156] The object itself may be communicatively coupled to several networks, such as WiFi, MiFi, 3G / 4G / LTE / 5G / 6G / 7G, Bluetooth, NFC, BLE, WiMax, Zigbee, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, mesh networks, ad-hoc networks, and / or other networks. The object itself may be AC-powered and bulky, and may be moved during installation, cleaning, maintenance, renovation, etc. The object may also be placed on a mobile platform, such as a lift, pad, mobile platform, elevator, conveyor belt, robot, drone, forklift, car, boat, or vehicle. The object may have multiple parts, each with a different motion (e.g., change of location / position). For example, the object may be a person walking in front. While walking, his left and right hands may move in different directions with different instantaneous speeds, accelerations, and motions.

[0157] The wireless transmitter (e.g., a Type 1 device), the wireless receiver (e.g., a Type 2 device), another wireless transmitter, and / or another wireless receiver may travel with the object and / or another object (e.g., in a previous trip, a current trip, and / or a future trip). They may be communicatively coupled to one or more nearby devices. They may transmit TSCIs and / or information related to the TSCIs to nearby devices and / or to each other. They may be associated with nearby devices. The wireless transmitter and / or wireless receiver may be part of a small (e.g., coin-sized, cigarette-pack-sized, or even smaller) lightweight portable device. The portable device may be wirelessly coupled to the nearby device.

[0158] The nearby device may be a smartphone, an iPhone, an Android phone, a smart device, a smart appliance, a smart vehicle, a smart gadget, a smart TV, a smart refrigerator, a smart speaker, a smart watch, smart glasses, a smart pad, an iPad, a computer, a wearable computer, a notebook computer, a gateway. The nearby device may be connected to a cloud server, a local server (e.g., a hub device), and / or other servers via the Internet, a wired Internet connection, and / or a wireless Internet connection. The nearby device may be portable. The portable device, nearby devices, local server (e.g., hub device), and / or cloud server can share tasks (e.g., acquiring TSCI, determining object characteristics / STI related to object movement (e.g., position / change in position), calculating time series of power (e.g., signal strength) information, determining / calculating specific functions, searching for local extrema, classification, identifying specific values ​​of offset time, denoising, processing, simplification, cleaning, wireless smart sensing tasks, extracting CIs from signals, switching, segmenting, estimating trajectory / path / track, processing maps, processing trajectory / path / track based on environmental models / constraints / limits, correction, correction adjustment, tuning, map-based (or model-based) correction, error detection, checking for boundary hits, thresholding) and calculation and / or storage of information (e.g., TSCI). Nearby devices may not move with the object. Nearby devices can be portable / non-portable / mobile / non-mobile. Nearby devices can use battery power, solar, AC power, and / or other power sources. The nearby device may have replaceable / non-replaceable and / or rechargeable / non-rechargeable batteries. The nearby device may resemble the object. The nearby device may have the same (and / or similar) hardware and / or software as the object.The nearby devices may be smart devices, network-enabled devices, devices with connections to WiFi / 3G / 4G / 5G / 6G / Zigbee / Bluetooth / NFC / UMTS / 3GPP / GSM / EDGE / TDMA / FDMA / CDMA / WCDMA / TD-SCDMA / ad hoc networks / other networks, smart speakers, smart watches, smart clocks, smart appliances, smart machines, smart appliances, smart tools, smart vehicles, Internet of Things (IoT) devices, Internet-enabled devices, computers, portable computers, tablets, and other devices. Nearby devices and / or at least one processor associated with a wireless receiver, a wireless transmitter, another wireless receiver, another wireless transmitter, and / or a cloud server (in the cloud) may determine an initial STI for the object. Two or more of them may jointly determine initial spatio-temporal information. Two or more of them may share intermediate information in determining the initial STI (e.g., initial location).

[0159] In one example, a wireless transmitter (e.g., a Type 1 device or a tracker bot) moves with an object. The wireless transmitter can send a signal to a wireless receiver (e.g., a Type 2 device or an Origin Register) to determine the object's initial STI (e.g., initial location). The wireless transmitter can also send a signal and / or another signal to another wireless receiver (e.g., another Type 2 device or another Origin Register) to monitor the object's movement (spatio-temporal information). The wireless receiver can also receive a signal and / or another signal from the wireless transmitter and / or another wireless transmitter to monitor the object's movement. The location of the wireless receiver and / or another wireless receiver can be known. In another example, a wireless receiver (e.g., a Type 2 device or a tracker bot) can move with the object. The wireless receiver can receive a signal transmitted from the wireless transmitter (e.g., a Type 1 device or an Origin Register) to determine the object's initial spatio-temporal information (e.g., initial location). The wireless receiver may also receive a signal and / or another signal from another wireless transmitter (e.g., another Type 1 device or another origin register) for monitoring the current movement (e.g., space-time information) of the object. The wireless transmitter may also transmit a signal and / or another signal to the wireless receiver and / or another wireless receiver (e.g., another Type 2 device or another tracker bot) for monitoring the movement of the object. The location of the wireless transmitter and / or another wireless transmitter may be known.

[0160] Locations include sensing areas, rooms, houses, offices, property, workspaces, corridors, lifts, lift wells, escalators, elevators, sewers, ventilation systems, stairs, assembly areas, ducts, air ducts, pipes, enclosed spaces, enclosed structures, semi-enclosed structures, enclosed areas with at least one wall, plants, machines, engines, structures, structures with wood, structures with glass, structures with metal, structures with walls, structures with doors, structures with gaps, structures with reflective surfaces, structures with liquids, buildings, rooftops, stores, factories, assembly lines, homes, etc. Hotel rooms, museums, classrooms, schools, universities, government buildings, warehouses, garages, malls, airports, train stations, bus terminals, hubs, transportation hubs, cargo terminals, government buildings, public facilities, schools, universities, entertainment venues, recreational facilities, hospitals, pediatric / neonatal wards, nursing homes, elderly care facilities, community centers, stadiums, playgrounds, fields, basketball courts, tennis courts, soccer stadiums, baseball fields, gymnasiums, garages, shopping marts, knolls, supermarkets, manufacturing facilities, parking facilities Facilities, construction sites, mining facilities, transportation facilities, highways, roads, valleys, forests, trees, terrain, landscapes, caves, patios, land, roads, amusement parks, urban areas, rural areas, suburban areas, metropolitan areas, gardens, squares, plazas, music halls, downtown facilities, open facilities, semi-open facilities, closed areas, train platforms, train stations, distribution centers, warehouses, shops, distribution centers, storage facilities, underground spaces, spatial (e.g. above ground, space) facilities, floating facilities, caves, tunnel facilities, indoor facilities, outdoor facilities, outdoor facilities with some walls / doors / reflective barriers Areas such as facilities, open facilities, semi-open facilities, automobiles, trucks, buses, vans, containers, ships / boats, submarines, trains, trams, airplanes, vehicles, mobile platforms, caves, tunnels, pipes, channels, metropolitan areas, downtown areas with relatively tall buildings, valleys, wells, ducts, pathways, gas lines, oil pipes, water pipes, interconnecting pathways / arrays / roads / tubes / cavities / caves / pipe-like structures / voids / fluid spaces, human bodies, animal bodies, body cavities, organs, bones, teeth, soft tissue, hard tissue, rigid tissue, non-hard tissue, blood / body fluid ducts, wind ducts, air ducts, burrows, etc. The location may be an indoor space, an outdoor space, and the location may include both inside and outside spaces.For example, a location can include both the inside and outside of a building. For example, a location can be a building with one or more floors, and part of the building can be underground. The shape of the building can be, for example, round, square, rectangular, triangular, or irregular. These are just examples. The present disclosure can be used to detect events in other types of locations or spaces.

[0161] The wireless transmitter (e.g., a Type 1 device) and / or wireless receiver (e.g., a Type 2 device) may be embedded in a portable device (e.g., a module or a device having a module) that may travel with the object (e.g., in a previous travel and / or a current travel). The portable device may be communicatively coupled to the object using a wired connection (e.g., via USB, micro USB, Firewire, HDMI, serial port, parallel port, and other connectors) and / or a connection (e.g., Bluetooth, Bluetooth Low Energy (BLE), WiFi, LTE, NFC, ZigBee). The portable device may be a lightweight device. The portable device may be powered by batteries, rechargeable batteries, and / or AC power. The portable device may be very small (e.g., on the sub-millimeter and / or sub-centimeter scale) and / or small (e.g., coin-sized, card-sized, pocket-sized, or larger). The portable device may be large, bulky, and / or heavy installed machinery. Portable devices include WiFi hotspots, access points, Mobile WiFi (MiFi), dongles with USB / micro USB / Firewire / other connectors, smartphones, portable computers, computers, tablets, smart devices, Internet of Things (IoT) devices, WiFi enabled devices, LTE enabled devices, smart watches, smart glass, smart mirrors, smart antennas, smart batteries, smart lights, smart pens, smart rings, smart doors, smart windows, smart clocks, smart batteries, smart wallets, smart belts, smart handbags, smart cloth / garments, smart ornaments, smart packaging, smart paper / books / magazines / posters / printed materials / signage / displays / illuminated systems / lighting systems, smart keys / tools, smart bracelets / chains / necklaces / clothes / accessories, smart pads / cushions, smart tiles / blocks / bricks / building materials / other materials,Smart trash can / waste container, smart food carriage / storage, smart ball / racket, smart chair / sofa / bed, smart shoes / footwear / carpet / mat / shoe rack, smart gloves / handwear / ring / handwear, smart hat / cap / cosmetics / sticker / tattoo, smart mirror, smart toy, smart pill, smart cookware, smart bottle / food container, smart tool, smart device, IoT device, WiFi enabled device, network enabled device, 3G / 4G / 5G / 6G enabled device, UMTS device, 3GPP device, GSM device, EDGE device, TDMA device, FDMA device, CDMA device, WCDMA device, TD-SCDMA device, embedded device, embeddable device, air conditioner, refrigerator, heater, furnace, furniture, oven, cooking device , TV / Set Top Box (STB) / DVD Player / Audio Player / Video Player / Remote Control, Hi-Fi, Audio Device, Speaker, Lamp / Light, Wall, Door, Window, Roof, Tile / Roofing Shingle / Structure / Attic Structure / Device / Feature / Installation / Fixture, Lawn Mower / Garden Equipment / Tools / Machine Tools / Garage Tools, Garbage Can / Container, 20ft / 40ft Container, Storage Container, Factory / Production / Manufacturing Equipment, Repair Tool, Fluid Container, Machine, Installed Machine, Vehicle, Cart, Wagon, Warehouse Vehicle, Automobile, Bicycle, Motorcycle, Boat, Watercraft, Airplane, Basket / Box / Bag / Bucket / Container, Smart Plate / Cup / Bowl / Pot / Mat / Utensil / Kitchenware / Kitchen Accessories / Cabinet / Table / Chair / Tile / Light / Water Pipe / Faucet / Gas Range / Oven / Dishwasher / , etc. Portable devices may have batteries that may be replaceable, non-replaceable, rechargeable, and / or non-rechargeable. Portable devices may be charged wirelessly. The portable device may be a smart payment card. The portable device may be a payment card used in parking lots, highways, entertainment parks, or other locations / facilities requiring payment. The portable device may have an identity (ID) / identifier, as described above.

[0162] Events can be monitored based on the TSCI. Events can be object-related events such as an object (e.g., a person and / or a patient) falling, rolling, hesitating, resting, impact (e.g., a person hitting a punching bag, door, window, bed, chair, table, desk, cabinet, box, another person, animal, bird, flying, table, chair, ball, bowling ball, tennis ball, football, soccer ball, baseball, basketball, volleyball), two-body action (e.g., leaving a balloon, catching a fish, molding clay, writing a paper, person typing into a computer), moving a car in a garage, a person carrying a smartphone and walking around an airport / mall / government office / office / etc, autonomous mobile objects / machines moving around (e.g., vacuum cleaner, utility vehicle, car, drone, self-driving car), etc.

[0163] The tasks or wireless smart sensing tasks are object detection, presence detection, proximity detection, object recognition, activity recognition, object verification, object counting, daily activity monitoring, health monitor, vital signs monitoring, health condition monitoring, baby monitoring, elderly monitoring, sleep monitoring, sleep stage monitoring, gait monitoring, motion monitoring, tool detection, tool recognition, tool verification, patient detection, patient monitoring, patient verification, machine detection, machine verification, human detection, human recognition, human verification, baby detection, baby recognition, baby verification, human breathing detection, human breathing recognition, human breathing estimation, human breathing verification, human heart rate detection, human heart rate recognition, human heart rate estimation, human heart rate verification, fall detection, fall recognition, fall estimation, fall verification, emotion detection, emotion recognition, emotion estimation, emotion verification, motion detection, motion degree estimation, Motion recognition, motion estimation, motion verification, cyclic motion detection, cyclic motion estimation, cyclic motion verification, repetitive motion detection, cyclic motion recognition, repetitive motion estimation, repetitive motion verification, static motion recognition, static motion detection, static motion estimation, static motion verification, cyclostationary motion detection, cyclostationary motion recognition, cyclostationary motion estimation, cyclostationary motion verification, transient motion detection, transient motion recognition, transient motion estimation, transient motion verification, trend detection, trend recognition, trend estimation, trend verification, breathing detection, breathing recognition, breathing estimation, human biometric detection, human biometric recognition, human biometric estimation, human biometric verification, environmental informatics detection, environmental informatics recognition, environmental informatics estimation, environmental informatics verification, gait detection, gait recognition, gait estimation, gait verification, gesture detection, gesture recognition, gesture estimation, gesture verification, machine learning, supervised learning, unsupervised learning, semi-supervised learning, clustering, feature extraction, feature training, principal component analysis, eigenvalue decomposition, frequency decomposition, time decomposition,Time-Frequency Decomposition, Function Decomposition, Other Decompositions, Training, Discriminative Training, Supervised Training, Unsupervised Training, Semi-Supervised Training, Neural Networks, Sudden Motion Detection, Fall Detection, Hazard Detection, Life-Threat Detection, Regular Motion Detection, Stationary Motion Detection, Cyclostationary Motion Detection, Intrusion Detection, Suspicious Motion Detection, Security, Safety Monitoring, Navigation, Guidance, Map-Based Processing, Map-Based Correction, Model-Based Processing / Correction, Irregularity Detection, Localization, Room Sensing, Tracking, Multiple Object Tracking, Indoor Tracking, Indoor Positioning, Indoor Navigation, Energy Management, Power Transmission, Wireless Power Transmission, Object Counting, Car Tracking in Parking Garages, Device / System Activation (e.g., Security Systems, Access Systems, Alarms, Sirens, Speakers, Televisions, Entertainment Systems, Cameras, Heating / Air Conditioning (HVAC) Systems, Ventilation Systems, Lighting Systems, Gaming Systems, Coffee Machines, Cooking Appliances, Cleaning Equipment, Housekeeping Equipment), Geometric Estimation , augmented reality, wireless communication, data communication, signal broadcasting, networking, coordination, management, encryption, protection, cloud computing, other processing, and / or other tasks, which may be performed by a Type 1 device, a Type 2 device, another Type 1 device, another Type 2 device, a nearby device, a local server (such as a hub device), an edge server, a cloud server, and / or another device.This task can be based on TSCI between any pair of Type 1 and Type 2 devices. A Type 2 device can also be a Type 1 device, and vice versa. A Type 2 device can fulfill the role (e.g., functionality) of a Type 1 device temporarily, continuously, sporadically, simultaneously, and / or concurrently, and / or vice versa. The first portion of tasks may include at least one of pre-processing, processing, signal conditioning, signal processing, post-processing, sporadic / continuous / concurrent / simultaneous / dynamic / adaptive / on-demand / as needed processing, calibration, noise removal, feature extraction, coding, encryption, transformation, mapping, motion detection, motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection, vital sign estimation, vital sign recognition, periodic motion detection, periodic motion estimation, repetitive motion detection / estimation, breathing rate detection, breathing rate estimation, breathing pattern detection, breathing pattern estimation, breathing pattern recognition, heart rate detection, heart rate estimation, cardiac pattern detection, cardiac pattern estimation, cardiac pattern recognition, gesture detection, gesture estimation, gesture recognition, velocity detection, velocity estimation, object location, object tracking, navigation, acceleration estimation, acceleration detection, fall detection, change detection, intruder (and / or tampering) detection, baby detection, baby monitoring, patient monitoring, object recognition, wireless power transfer, and / or wireless charging.

[0164] The second part of the task may be a smart home task, a smart office task, a smart building task, a smart factory task (e.g., manufacturing with a machine or assembly line), a smart Internet of Things (IoT) task, a smart system task, a smart home operation, a smart office operation, a smart building operation, a smart manufacturing operation (e.g., movement of supplies / parts / raw materials to a machine / assembly line), an IoT operation, a smart system operation, turning on lights, turning off lights, controlling light in at least one of a room, area, and / or location, playing a sound clip, playing a sound clip in at least one of a room, area, and / or location, playing at least one sound clip of welcome, greeting, farewell, a first message, and / or a second message related to the first part of the task, turning on an appliance, turning off an appliance, The control may include at least one of controlling appliances in at least one of the rooms, areas, and / or locations; turning on an electrical system; turning off an electrical system; controlling an electrical system in at least one of the rooms, areas, and / or locations; turning on a security system; turning off a security system; controlling a security system in at least one of the rooms, areas, and / or locations; turning on a mechanical system; turning off a mechanical system; controlling a mechanical system in at least one of the rooms, areas, and / or locations; and / or controlling at least one of an air conditioning system, a heating system, a ventilation system, a lighting system, a heater, a stove, an entertainment system, a door, a fence, a window, a garage, a computer system, a networked device, a networked system, a home appliance, an office appliance, a lighting device, a robot (e.g., a robotic arm), a smart vehicle, a smart machine, an assembly line, a smart device, an Internet of Things (IoT) device, a smart home device, and / or a smart office device.

[0165] The tasks are to detect when the user comes home, detect when the user leaves, detect when the user moves from one room to another, detect when a window / door / garage door / blinds / curtains / panels / solar panels / sunshades are controlled / locked / unlocked / opened / closed / partially opened, detect pets, detect / monitor when the user is doing something (e.g. sleeping on the sofa, sleeping in the bedroom, running on the treadmill, cooking, sitting on the sofa, watching TV, eating in the kitchen, eating in the dining room, going up and down stairs, going out / coming back, in the bathroom), monitor / detect the location of the user / pet and do something automatically when detected (e.g. sending a message, notifying / reporting), do something to the user when a user is detected, turn on / off / dim the lights, turn on / off the music / radio / home entertainment system, turn on / off the TV / may include turning on / off / adjusting / controlling hi-fi / set-top box (STB) / home entertainment system / smart speaker / smart device, turning on / off / adjusting air conditioning system, turning on / off / adjusting ventilation system, turning on / off / adjusting heating system, adjusting / controlling curtains / light shades, turning on / off / starting computer, turning on / off / preheating / controlling coffee machine / hot water kettle, turning on / off / preheating / controlling cooker / oven / microwave / other cooking appliance, checking / adjusting temperature, checking weather forecast, checking phone message box, checking email, checking system, controlling / adjusting system, checking / controlling / arming / disarming security system / baby monitor, checking / controlling refrigerator, reporting (e.g. through speaker such as Google Home, Amazon Echo, via web page / email / messaging system / notification system).

[0166] For example, if a user arrives at home in their vehicle, the tasks may automatically detect that the user or their vehicle is approaching, open the garage door upon detection, turn on the driveway / garage lights as the user approaches the garage, turn on the air conditioner / heater / fan, etc. As the user enters the house, the tasks may automatically turn on the entrance lights, turn off the driveway / garage lights, play a greeting message to welcome the user, turn on music, turn on the radio and tune it to the user's favorite radio news channel, open the curtains / blinds, monitor the user's mood, adjust the lighting and sound environment according to the user's mood or current / impending events on the user's daily calendar (e.g., romantic lighting and music because the user is going to have dinner with his / her girlfriend in an hour), microwave the food the user prepared that morning, perform a diagnostic check of all systems in the house, check the weather forecast for tomorrow's tasks, check news of interest to the user, and update the user's calendar, to-do list, etc. Check reminders, check phone answering systems, messaging systems, email, communicate verbal reports using dialogue systems / speech synthesis, remind the user of their mother's birthday (e.g., using audible tools such as speakers, hi-fi, speech synthesis, sound, voice, music, song, sound field, background sound field, dialogue system, etc.; using visual tools such as TV / entertainment system / computer / notebook / smartpad / display / light / color / brightness / pattern, using haptic tools / virtual reality tools / gestures / tools, using smart devices / appliances / materials / furniture / fixtures, using web tools / servers / hub devices / cloud servers / fog servers / edge servers / home networks / mesh networks, using messaging tools / notification tools / communication tools / scheduling tools / email, using user interfaces / GUIs, using scents / smells / aromas / tastes, using neural tools / neural system tools, or a combination), generate reports, provide reports (e.g., using reminding tools as described above).A task may be to proactively start an air conditioner / heater / ventilation system or proactively adjust a smart thermostat temperature setting. When a user moves from the front door to the living room, the tasks may be to turn on the living room lights, open the living room curtains, open the windows, turn off the front door light behind the user, turn on the TV and set-top box, turn on the set-top box, set the TV to the user's preferred channel, adjust the appliances according to the user's preferences and conditions / states (e.g., adjust the lighting, select / play music to create a romantic atmosphere), etc.

[0167] Another example could be: When a user wakes up in the morning, the task could be to detect the user moving around in the bedroom, open the blinds / curtains, open the windows, turn off the alarm clock, adjust the room temperature profile from a night temperature profile to a day temperature profile, turn on the bedroom lights, turn on the toilet light as the user approaches the bathroom, check the radio or streaming channels, play the morning news, turn on the coffee machine, preheat water, turn off the security system, etc. When the user walks from the bedroom to the kitchen, the task could be to turn on the kitchen and hallway lights, turn off the bedroom and toilet lights, move music / messages / reminders from the bedroom to the kitchen, turn on the kitchen TV, change the TV to the morning news channel, lower the kitchen blinds, open the kitchen window to let in fresh air, unlock the back door so the user can check the back yard, adjust the kitchen temperature setting, etc. Another example could be: When the user leaves home for work, the tasks may be to detect the user's departure, say goodbye and / or have a nice day, open / close the garage door, turn on / off the garage and driveway lights, turn off / dim to save energy (only if the user fails), close / lock all windows / doors (only if the user fails), turn off appliances (especially the stove, oven, microwave), turn on / arm the home security system to protect the home against intruders, adjust the air conditioning / heating / ventilation system to an "away from home" profile to save energy, send alerts / reports / updates to the user's smartphone, etc.

[0168] The motions are classified as no motion, rest motion, motionless motion, motion, change of location / position, deterministic motion, transient motion, falling motion, repetitive motion, periodic motion, pseudo-periodic motion, periodic / repetitive motion related to breathing, periodic / repetitive motion related to heartbeat, periodic / repetitive motion related to living organisms, periodic / repetitive motion related to machines, periodic / repetitive motion related to man-made objects, periodic / repetitive motion related to nature, complex motion related to transient and periodic elements, repetitive motion, non-deterministic motion, stochastic motion, chaotic motion, random motion, complex motion with non-deterministic and deterministic elements, stationary random motion, pseudo-stationary random motion, cyclostationary random motion, non-stationary random motion, non-stationary random motion with a periodic autocorrelation function (ACF), random motion with a periodic ACF over time. motion, pseudo-stationary random motion over time, random motion where the instantaneous ACF has a pseudo-periodic / repetitive component over time, machine motion, mechanical motion, vehicle motion, drone motion, air-related motion, wind-related motion, weather-related motion, water-related motion, fluid-related motion, ground-related motion, change in magnetic properties, subsurface motion, earthquake motion, plant motion, animal motion, animal motion, human motion, normal motion, abnormal motion, dangerous motion, warning motion, suspicious motion, rain, fire, flood, tsunami, explosion, collision, imminent collision, human motion, head motion, face motion, eye motion, oral motion, tongue motion, neck motion, finger motion, hand motion, arm motion, shoulder motion, body motion, chest motion, abdominal motion, hip motion, leg motion, foot motion, body joint motion, knee motion, elbow motion, upper body motion, lower body motion, skin motion, subcutaneous motion, subcutaneous tissue motion. The motion may include at least one of blood vessel movement, venous movement, organ movement, heart movement, lung movement, stomach movement, intestinal movement, bowel movement, eating movement, breathing movement, facial expression, eye expression, mouth expression, vocal movement, singing movement, eating movement, gesture, hand gesture, arm gesture, keystroke, typing stroke, user interface gesture, man-machine interaction, gait, dance movement, coordinated movement, and / or coordinated body movement.

[0169] The heterogeneous ICs of the Type 1 device and / or any Type 2 receiver may include a low noise amplifier (LNA), a power amplifier, a transmit-receive switch, a media access controller, a baseband radio, a 2.4 GHz radio, a 3.65 GHz radio, a 4.9 GHz radio, a 5 GHz radio, a 5.9 GHz radio, a sub-6 GHz radio, a 60 GHz radio, a sub-60 GHz radio, and / or another radio. The heterogeneous IC may include a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory for execution by the processor. The IC and / or any processor may include at least one of a general purpose processor, a special purpose processor, a microprocessor, a multiprocessor, a multi-core processor, a parallel processor, a CISC processor, a RISC processor, a microcontroller, a central processing unit (CPU), a graphical processor unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), an embedded processor (e.g., ARM), a logic circuit, another programmable logic device, discrete logic, and / or a combination. Heterogeneous ICs are used in broadband networks, wireless networks, mobile networks, mesh networks, cellular networks, wireless local area networks (WLANs), wide area networks (WANs), metropolitan area networks (MANs), WLAN standards, WiFi, LTE, LTE-A, LTE-U, 802.11 standards, 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, 802.11af, 802.11ah, 802.11ax, 802.11ay, mesh networking standards 802.16, 3G, 3.5G, 4G, Beyond 4G, 4.5G, 6G, 7G, 8G, 9G, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, Bluetooth, Bluetooth Low-Energy It may support Bluetooth Low Energy (BLE), NFC, Zigbee, WiMax, and other wireless network protocols.

[0170] The processor may include a general-purpose processor, a special-purpose processor, a microprocessor, a microcontroller, an embedded processor, a digital signal processor, a central processing unit, a graphical processing unit (GPU), a multiprocessor, a multi-core processor, and / or a processor with graphics capabilities, and / or a combination thereof. The memory may be volatile, non-volatile, random-access memory (RAM), read-only memory (ROM), programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), a hard disk, flash memory, CD-ROM, DVD-ROM, magnetic storage, optical storage, organic storage, a storage system, a storage network, network storage, cloud storage, edge storage, local storage, external storage, internal storage, or any other form of non-transitory storage medium known in the art. The set of instructions (machine-executable code) corresponding to the method steps may be directly embodied in hardware, software, firmware, or a combination thereof. The set of instructions may be embedded, pre-loaded, loaded at boot time, loaded on-the-fly, loaded on-demand, pre-installed, installed, and / or downloaded.

[0171] The presentation may be visual (e.g., using a combination of sights, graphics, text, symbols, color, shade, video, animation, sound, voice, audio, etc.), graphical (e.g., using GUI, animation, video), textual (e.g., web page with text, messages, animated text), symbolic (e.g., emojis, signs, hand gestures), or mechanical (e.g., vibration, actuator movement, haptics, etc.) presentation.

[0172] Basic calculation

[0173] The computational workload associated with this method is shared among the processor, the type 1 heterogeneous wireless device, the type 2 heterogeneous wireless device, a local server (eg, a hub device), a cloud server, and other processors.

[0174] Operations, pre-processing, processing, and / or post-processing may be applied to the data (e.g., TSCI, autocorrelation, TSCI features). Operations may include pre-processing, processing, and / or post-processing. Pre-processing, processing, and / or post-processing may be operations. Operations may include pre-processing, processing, post-processing, scaling, calculating confidence coefficients, calculating line-of-sight (LOS) quantities, non-LOS calculations, and the like. Computing non-linear (NLOS) quantities, computing quantities including line-of-sight and non-linear (NLOS), computing quantities for a single link (e.g., path, communication path, link between a transmitting antenna and a receiving antenna), computing quantities including multiple links, computing functions of operands, filtering, linear filtering, nonlinear filtering, folding, grouping, energy computation, low-pass filtering, band-pass filtering, high-pass filtering, median filtering, rank filtering, quartile filtering, percentile filtering, finite impulse response (FIR) filtering, infinite impulse response (IIR) filtering, moving average (MA) filtering, autoregressive (AR) filtering, autoregressive moving average (ARMA) filtering, selective filtering, adaptive filtering, interpolation, decimation, subsampling, upsampling, resampling, time correction, time-based correction, phase correction, magnitude correction, phase cleaning, amplitude cleaning, matched filtering, enhancement, restoration, noise removal, smoothing, signal conditioning, enhancement, restoration, linear transform, nonlinear transform, inverse transform, frequency transformation, inverse frequency transformation, Fourier transform (FT), discrete-time FT (DTFT), Discrete FT (DFT), Fast FT (FFT), Wavelet Transform, Laplace Transform, Hilbert Transform, Hadamard Transform, Trigonometric Transform, Sin Transform, Cosine Transform, DCT, Power of 2 Transform, Sparse Transform, Graph Based Transform, Graph Signal Processing, Fast Transform, Transform Combined with Zero Padding, Cyclic Padding, Padding, Zero Padding, Feature Extraction, Decomposition, Projection, Orthogonal Projection, Non-Orthogonal Projection, Overprojection (oecomlee)ojecion), eigendecomposition, singular value decomposition (SVD), principle component analysis (ICA), independent component analysis (ICA), grouping, sorting, thresholding, soft thresholding, hard thresholding, clipping, soft clipping, first derivative, second derivative, higher derivative, convolution, multiplication, division, addition, subtraction, integration, maximization, minimization, least squared error, recursive least squares, constrained least squares, batch least squares, least absolute deviation, least mean squared deviation, least absolute deviation, local maximization, local minimization, cost function optimization, neural networks, recognition, labeling, training, class filtering, machine learning, supervised learning, unsupervised learning, semi-supervised learning, comparison with other TSCI, similarity score calculation, quantization, vector quantization, matching pursuit, compression, encryption, encoding, storage, transmission, normalization, time normalization, frequency domain normalization, classification, clustering, labeling, tagging, learning, detection, estimation, learning network, mapping, remapping, expansion, storage, search, transmission, reception, representation, combining, merging, splitting, tracking, monitoring, matched filtering, Kalman filtering, particle filtering, interpolation, extrapolation, histogram estimation The operations may include importance sampling, Monte Carlo sampling, compressed sensing, representation, merging, combining, dividing, scrambling, error protection, forward error correction, do nothing, time-varying processing, adjusted averaging, weighted averaging, arithmetic mean, geometric mean, harmonic mean, averaging over selected frequencies, averaging over antenna links, logical operations, permutation, combination, sorting, AND, OR, XOR, union, intersection, vector addition, vector subtraction, vector multiplication, vector division, inverse, norm, distance, and / or another operation. The operations may be pre-processing, processing, and / or post-processing. Operations may be applied jointly on multiple time series or functions.

[0175] Functions (e.g., functions of operands) can be scalar functions, vector functions, discrete functions, continuous functions, polynomial functions, properties, characteristics, magnitude, phase, exponential functions, logarithmic functions, trigonometric functions, transcendental functions, boolean functions, linear functions, algebraic functions, nonlinear functions, piecewise functions, real functions, complex functions, vector-valued functions, inverse functions, derivative functions, integral functions, circular functions, functions of other functions, one-to-one functions, one-to-many functions, many-to-one functions, many-to-many functions, zero crossings, absolute functions, index functions, mean, mode, median, range, statistics, histogram, variance, standard deviation, measure of change, expansion, dispersion, deviation, divergence, range, interquartile range, total deviation, absolute deviation, arithmetic mean, geometric mean, harmonic mean, trimmed mean, percentile, square, cube, square root, power, sine, cosine, tangent, cotangent elliptic functions, parabolic functions, hyperbolic functions, game functions, zeta functions, absolute value, threshold, limit functions, floor functions, rounding functions, sign functions, quantization, piecewise constant functions, composite functions, functions of functions, time functions processed by operations (e.g. filtering), probabilistic functions, stochastic functions, deterministic functions, periodic functions, iterative functions, transformations, frequency transforms, inverse frequency transforms, discrete time transforms, Laplace transforms, Hilbert transforms, sine transforms, cosine transforms, trigonometric transforms, wavelet transforms, integer transforms, power of two transforms, sparse transforms, projections, decompositions, principal component analysis (PCA), neural networks, feature extraction, moving functions, functions for moving windows of adjacent items in a time series, filtering functions, convolutions, mean functions, histograms, variance / standard deviation functions, statistical functions, short-time transforms, discrete transforms, Discrete Fourier Transform, Discrete Cosine Transform, Discrete Sine Transform, Hadamard Transform, Eigenvalue Decomposition, Eigenvalue, Singular Value Decomposition (SVD), Singular Value, Orthogonal Decomposition, Matching Pursuit, Sparse Transform, Arbitrary Decomposition, Graph Based Processing, Graph Based Transform, Graph Signal Processing, Classification, Class / Group / Category Identification, Labeling, Learning, Machine Learning, Detection, Estimation, Feature Extraction, Learning Networks, Feature Extraction, Noise Reduction, Signal Enhancement, Coding, Encryption, Mapping, Remapping, Vector Quantization, Low-Pass Filtering, High-Pass Filtering, Band-Pass Filtering, Matched Filtering, Kalman Filtering, Pre-Processing, Post-Processing, Particle Filtering, FIR Filtering, IIR Filtering, Autoregressive (AR) Filtering, Adaptive Filtering, First Derivative, Higher-Order Derivative, Integration, Zero Crossing, Smoothing, Median Filtering, Mode Filtering, Sampling, Random Sampling, Resampling Function, Downsampling, Downconverting, Upsampling, Upconverting, Interpolation, Extrapolation, Importance Sampling, Monte Carlo Sampling, Compressed Sensing, Statistics, These may include short-term statistics, long-term statistics, autocorrelation functions, cross-correlation functions, moment-generating functions, time averages, weighted averages, special functions, Bessel functions, error functions, complementary error functions, beta functions, gamma functions, integral functions, Gaussian functions, Poisson functions, and the like.

[0176] The steps (or each step) of this disclosure may employ machine learning, training, discriminative training, deep learning, neural networks, continuous time processing, distributed computing, distributed storage, and acceleration using GPUs / DSPs / coprocessors / multi-cores / multi-processing.

[0177] The frequency transform may include a Fourier transform, a Laplace transform, a Hadamard transform, a Hilbert transform, a sine transform, a cosine transform, a trigonometric transform, a wavelet transform, an integer transform, a power of two transform, zero-padding and combinations of transforms, a power Fourier transform with zero-padding, and / or another transform. Fast and / or approximate versions of the transforms may be performed. The transforms may be performed using floating-point and / or fixed-point arithmetic.

[0178] The inverse frequency transform may include an inverse Fourier transform, an inverse Laplace transform, an inverse Hadamard transform, an inverse Hilbert transform, an inverse sine transform, an inverse cosine transform, an inverse trigonometric transform, an inverse wavelet transform, an inverse integer transform, an inverse power of two transform, a combination of zero padding and transforms, an inverse Fourier transform with zero padding, and / or another transform. Fast and / or approximate versions of the transform may be performed. The transform may be performed using floating-point and / or fixed-point arithmetic.

[0179] Quantities / features from TSCI can be calculated. Quantities include: movement, location, map coordinates, height, speed, acceleration, movement angle, rotation, dimension, volume, time trend, one-time pattern, recurring pattern, evolving pattern, time pattern, mutually exclusive pattern, associated / correlated pattern, cause-effect, short-term / long-term correlation, tendency, slope, preference, statistics, typical behavior, atypical behavior, time trend, time profile, periodic movement, repetitive movement, repetition, tendency, change, sudden change, gradual change, frequency, transient, breathing, gait, behavior, event, suspicious event, dangerous event, warning event, warning, belief, proximity, collision, power, signal, signal power, signal strength, signal volume, received signal strength indicator (RSSI), signal amplitude, signal phase, signal frequency component, signal frequency band component, channel state information (CSI), map, time, frequency, time-period The statistics may include at least one of wavenumber, decomposition, orthogonal decomposition, non-orthogonal decomposition, tracking, respiration, palpitations, statistical parameters, cardiopulmonary statistics / analysis (e.g., output response), daily activity statistics / analysis, chronic disease statistics / analysis, medical statistics / analysis, early (or instantaneous or simultaneous or delayed) indicator / suggestion / sign / marker / verifier / detection / symptom / condition / state, biometric, baby, patient, machine, device, temperature, vehicle, parking lot, location, lift, elevator, space, road, fluid flow, home, room, office, house, building, warehouse, storage, system, ventilation, fan, pipe, duct, people, human, car, boat, truck, plane, drone, downtown, crowd, impulse event, cyclostationary, environment, vibration, material, surface, 3D, 2D, local, global, presence, and / or other measurable quantity / variable.

[0180] Sliding Window Algorithm

[0181] The sliding time window may have a time-varying window width. It may be smaller initially to allow for rapid acquisition and may increase over time to a steady-state size. The steady-state size may be related to the monitored frequency, repetitive motion, transient motion, and / or STI. Even in the steady state, the window size may be adaptively (and / or dynamically) changed (e.g., adjusted, varied, modified) based on battery life, power consumption, available computing power, changes in the volume of interest, the nature of the monitored motion, etc.

[0182] The time shift between two sliding time windows at adjacent time instances can be constant / variable / locally adaptive / dynamically adjusted over time. If a shorter time shift is used, any monitoring updates can be more frequent, which can be used for rapidly changing conditions, object movements, and / or objects. A longer time shift can be used for slower conditions, object movements, and / or objects.

[0183] The window width / size and / or time shift may be changed (e.g., adjusted, altered, modified) according to user requests / selections. The time shift may be changed automatically (e.g., as controlled by a processor / computer / server / hub device / cloud server) and / or adaptively (and / or dynamically).

[0184] At least one characteristic (e.g., a characteristic value or characteristic point) of a function (e.g., an autocorrelation function, an autocovariance function, a cross-correlation function, a cross-covariance function, a power spectral density, a time function, a frequency domain function, a frequency transform) may be determined (e.g., by the object tracking server, a processor, a Type 1 heterogeneous device, a Type 2 heterogeneous device, and / or another device). At least one characteristic of the function may include a maximum, a minimum, an extremum, a local maximum, a local minimum, a local extremum, a local extremum with a positive time offset, a first local extremum with a positive time offset, an nth local extremum with a positive time offset, a first local extremum with a negative time offset, a bounded maximum, a bounded minimum, a bounded extremum, a significant maximum, a significant minimum, a significant extremum, a gradient, a derivative, a higher order derivative, a maximum gradient, a minimum gradient, a local maximum gradient, a local maximum gradient with a positive time offset, a local minimum gradient, a bounded maximum gradient, a bounded minimum gradient, a maximum higher order derivative, a minimum higher order derivative, a bounded higher order derivative, a zero crossing, a zero crossing with a positive time offset, an nth zero crossing with a positive time offset, a zero crossing with a negative time offset, an nth zero crossing with a negative time offset, a bounded zero crossing, a zero crossing of a gradient, a zero crossing of a gradient of a higher order derivative, and / or other characteristics. At least one argument of the function associated with at least one characteristic of the function may be identified. A quantity (eg, spatial-temporal information of an object) may be determined based on at least one argument of the function.

[0185] Characteristics (e.g., characteristics of an object's movement at a location) can include instantaneous characteristics, short-term characteristics, recurring characteristics, recursive characteristics, history, incremental characteristics, change characteristics, deviation characteristics, phase, amplitude, degree, time characteristics, frequency characteristics, time-frequency characteristics, decomposition characteristics, orthogonal decomposition characteristics, non-orthogonal decomposition characteristics, deterministic characteristics, probability characteristics, stochastic characteristics, autocorrelation function (ACF), mean, variance, standard deviation, measure of change, spread, variance, deviation, divergence, range, interquartile range, total variation, absolute deviation, total deviation, statistics, duration, timing, trend, periodic characteristics, recurring characteristics, long-term characteristics, historical characteristics, average characteristics, recent characteristics, past characteristics, future characteristics, predicted characteristics, position, distance, height, speed, direction, velocity, acceleration, change in acceleration, angle, angular speed, change in angular velocity, of an object The change in angular acceleration includes at least one of: angular acceleration, change in angular acceleration, orientation of the object, angle of rotation, deformation of the object, shape of the object, change in shape of the object, change in size of the object, change in structure of the object, and / or change in properties of the object.

[0186] At least one local maximum and at least one local minimum of the function may be identified. At least one local signal-to-noise ratio-like (SNR-like) parameter may be calculated for each pair of adjacent local maximums and minima. The SNR-like parameter may be a function (e.g., linear, logarithmic, exponential, monotonic) of the fraction of the amount (e.g., power, magnitude) of the local maximum over the same amount of the local minimum. It may also be a function of the difference between the amount of the local maximum and the same amount of the local minimum. Significant local peaks may be identified or selected. Each significant local peak may be a local maximum with an SNR-like parameter greater than a threshold T1 and / or a local maximum with an amplitude greater than a threshold T2. At least one local minimum and at least one local minimum in the frequency domain may be identified / calculated using a persistence-based approach.

[0187] A set of selected significant local peaks may be selected from the set of identified significant local peaks based on a selection criterion (e.g., quality criteria, signal quality state). An object characteristic / STI may be calculated based on the set of selected significant local peaks and frequency values ​​associated with the set of selected significant local peaks. In one example, the selection criterion may always correspond to selecting the strongest peak in the range. The strongest peak may be selected, but non-selected peaks may still be significant (or even strong).

[0188] Unselected significant peaks may be saved and / or monitored as "reserved" peaks for use in future selections in future sliding time windows. As an example, there may be a particular peak (at a particular frequency) that appears consistently over time. Initially, even though it is significant, it may not be selected (because other peaks may become stronger). However, at a later time, the peak may become stronger and more dominant and may be selected. If it is "selected," it may be back-traced in time and deemed "selected" at an earlier time that was significant but not selected. In such a case, the back-traced peak may replace a previously selected peak at an earlier time. The replaced peak may be a relatively weak peak or a peak that appears isolated in time (i.e., appears only briefly in time).

[0189] In other instances, the selection criteria may not correspond to selecting the strongest peak in the range, but instead may consider not only the "strength" of the peak, but also the "trace" of peaks that may have occurred in the past, especially peaks that have been identified for a long time.

[0190] For example, if a finite state machine (FSM) is used, it may select the peak based on the state of the FSM. The decision threshold may be adaptively (and / or dynamically) calculated based on the state of the FSM.

[0191] The similarity score and / or component similarity score may be calculated (e.g., by a server (e.g., a hub device), a processor, a Type 1 device, a Type 2 device, a local server, a cloud server, and / or another device) based on a pair of temporally adjacent CIs of a TSCI. The pairs may be obtained from the same sliding window or two different sliding windows. The similarity score may also be based on a pair of temporally adjacent or less-adjacent CIs from two different TSCIs. The similarity score and / or component similarity score may be / include time reversal resonating strength (TRRS), correlation, cross-correlation, autocorrelation, correlation indicator, covariance, cross-covariance, autocovariance, dot product of two vectors, distance score, norm, metric, quality metric, signal quality condition, statistical property, discrimination score, neural network, deep learning network, machine learning, training, discrimination, weighted average, preprocessing, denoising, signal conditioning, filtering, time correction, time alignment, phase offset compensation, transform, component-wise operation, feature extraction, finite state machine, and / or another score. Property and / or STI may be determined / calculated based on the similarity score.

[0192] Any threshold may be predetermined, adaptively (and / or dynamically) determined, and / or determined by a finite state machine. Adaptive determination may be based on time, space, location, antenna, path, link, condition, battery life, remaining battery capacity, available power, available computational resources, available network bandwidth, etc.

[0193] A threshold applied to a test statistic to distinguish between two events (or two conditions, or two situations, or two states), A and B, may be determined. Data (e.g., CI, channel state information (CSI), power parameters) may be collected under A and / or under B in a training scenario. A trial statistic may be calculated based on the data. A distribution of the trial statistic under A may be compared to a distribution of the trial statistic under B (a reference distribution), and a threshold may be selected according to some criteria. The criteria may include maximum likelihood estimation (ML), maximum a posteriori probability (MAP), discriminative training, minimum type-1 error for a given type-2 error, minimum type-2 error for a given type-1 error, and / or other criteria (e.g., quality metric, signal quality condition). The threshold may be adjusted to achieve different sensitivities to A, B, and / or other events / conditions / situations / states. The threshold adjustment may be automatic, semi-automatic, and / or manual. Threshold adjustments may be applied once, occasionally, frequently, periodically, repeatedly, occasionally, sporadically, and / or on-demand. Threshold adjustments may be adaptive (and / or dynamically adjusted). Threshold adjustments may depend on objects, object movement / location / orientation / motion, object characteristics / STI / size / characteristics / traits / habits / behavior, location, at / at / of location, features / fixtures / furniture / barriers / materials / machines / creatures / objects / boundaries / surfaces / media, map, map constraints (or environmental model), events / states / scenes / conditions, time, timing, duration, current state, past history, user, and / or personal preference, etc.

[0194] The stopping criterion (or skip or bypass or blocking or pausing or passing or rejecting criterion) of an iterative algorithm may be that the change in the current parameter (e.g., offset value) in the update in the iteration is less than a threshold. The threshold may be 0.5, 1, 1.5, 2, or another number. The threshold may be adaptive (and / or dynamically adjusted). It may change as the iteration progresses. With respect to the offset value, the adaptive threshold may be determined based on the task, the initial specific value, the current time offset value, the regression window, the regression analysis, the regression function, the regression error, the convexity of the regression function, and / or the number of iterations.

[0195] The local extrema may be determined as a corresponding extremum of the regression function in the regression window. The local extrema may be determined based on a set of time offset values ​​and a set of associated regression function values ​​within the regression window. Each of the set of associated regression function values ​​associated with the set of time offset values ​​may be within a range from the corresponding extremum of the regression function in the regression window.

[0196] Searching for local extrema, robust search, minimization, optimization, statistical optimization, dual optimization, constraint optimization, convex optimization, global optimization, local optimization, energy minimization, linear regression, quadratic regression, higher order regression, linear programming, nonlinear programming, stochastic programming, combinatorial optimization, constraint programming, constraint satisfaction, computation of variations, optimal control, dynamic programming, mathematical programming, multiobjective optimization, multimodal optimization, disjunctive programming, space mapping, infinite dimensional optimization, heuristics, metaheuristics, convex programming, semidefinite programming, cone programming, second order cone programming, integer programming, quadratic programming, fractional programming, numerical analysis, simplex algorithm, iterative methods, gradient descent, subgradient methods, coordinate gradient methods, conjugate gradient methods, Newton's algorithm, sequential quadratic programming, interior point methods, elliptic methods, reduced gradient methods, quasi-Newton methods, simultaneous perturbation stochastic approximation, interpolation, pattern search methods, line search, non-differential optimization, genetic algorithms, evolutionary algorithms, dynamic relaxation The search for local extrema may involve an objective function, a loss function, a cost function, a utility function, a fitness function, an energy function, and / or an energy function.

[0197] The regression may be performed using a regression function to fit the sampled data (e.g., CIs, CI features, components of CIs) or another function (e.g., an autocorrelation function) in a regression window. The length of the regression window and / or the position of the regression window may be varied in at least one iteration. The regression function may be a linear function, a quadratic function, a cubic function, a polynomial function, and / or another function.

[0198] The regression analysis may minimize at least one of the following: error, aggregate error, component error, error in a projected domain, error in a selected axis, error in a selected orthogonal axis, absolute error, squared error, absolute deviation, squared deviation, higher-order error (e.g., third-order, fourth-order), robust error (e.g., squared error versus absolute error for smaller magnitude errors and for larger errors, or a first type of error for smaller magnitude errors and a second type of error for larger magnitude errors), another error, a weighted sum (or weighted average) of absolute / squared errors (e.g., in the case of a wireless transmitter with multiple antennas and a wireless receiver with multiple antennas, each pair of transmitter antenna and receiver antenna forms a link), mean absolute error, mean squared error, mean absolute deviation, and / or mean squared deviation. Errors associated with different links may have different weights. One possibility is that some links and / or some components with greater noise or lower signal quality metrics may have smaller or larger weights. (weighted sum of squared errors, weighted sum of higher-order errors, weighted sum of robust errors, weighted sum of alternative errors, absolute cost, squared cost, higher-order cost, robust cost, alternative cost, weighted sum of absolute costs, weighted sum of squared costs, weighted sum of higher-order costs, weighted sum of robust costs, and / or weighted sum of alternative costs).

[0199] The determined regression error may be an absolute error, a squared error, a higher order error, a robust error, a further error, a weighted sum of absolute errors, a weighted sum of squared errors, a weighted sum of higher order errors, a weighted sum of robust errors, and / or a weighted sum of further errors.

[0200] The time offset associated with the maximum regression error (or minimum regression error) of the regression function for a particular function within the regression window may be the updated current time offset for the iteration.

[0201] The local extrema can be searched for based on a quantity including the difference between two different errors (e.g., the difference between an absolute error and a squared error), each of which can include an absolute error, a squared error, a higher-order error, a robust error, another error, a weighted sum of absolute errors, a weighted sum of squared errors, a weighted sum of higher-order errors, a weighted sum of robust errors, and / or a weighted sum of another error.

[0202] The quantity may be compared to reference data or a reference distribution, such as an F-distribution, a central F-distribution, another statistical distribution, a threshold, a threshold associated with a probability / histogram, a threshold associated with a probability / histogram of finding a false peak, a threshold associated with an F-distribution, a threshold associated with a central F-distribution, and / or a threshold associated with another statistical distribution.

[0203] The regression window may be determined based on at least one of: a movement of the object (e.g., a change in location / position), a quantity related to the object, at least one characteristic and / or STI of the object related to the movement of the object, an estimated location of a local extremum, a noise characteristic, an estimated noise characteristic, a signal quality metric, an F-distribution, a central F-distribution, another statistical distribution, a threshold, a preset threshold, a threshold related to a probability / histogram, a threshold related to a desired probability, a threshold related to the probability of finding a false peak, a threshold related to an F-distribution, a threshold related to a central F-distribution, a threshold related to another statistical distribution, a condition that the quantity at the window center is a maximum within the regression window, a condition that only one of the local extrema of a particular function for a particular value exists for the first time within the regression window, another regression window, and / or other conditions.

[0204] The width of the regression window can be determined based on the particular local extrema to be searched for, including a first local maximum, a second local maximum, a higher-order local maximum, a first local maximum with a positive time offset, a second local maximum with a positive time offset, a higher-order local maximum with a positive time offset, a first local maximum with a negative time offset, a second local maximum with a negative time offset, a second local maximum with a negative time offset, a higher-order local maximum with a negative time offset, a first local minimum, a second local minimum, a higher-order local minimum, a first local minimum with a positive time offset, The local minimum may include a second local minimum with a positive time offset, a higher-order local minimum with a positive time offset, a first local minimum with a negative time offset, a second local minimum with a negative time offset, a higher-order local minimum with a negative time offset, a first local extremum, a second local extremum, a higher-order local extremum, a first local extremum with a positive time offset, a second local extremum with a positive time offset, a first local extremum with a negative time offset, a second local extremum with a negative time offset, and a higher-order extremum with a negative and / or negative time offset.

[0205] The current parameters (e.g., time offset value) may be initialized based on a target value, a target profile, a trend, a past trend, a current trend, a target speed, a speed profile, a target speed profile, a past speed trend, an object's motion or movement (e.g., a change in location / position), at least one characteristic and / or STI of the object associated with the object's motion, a position quantity of the object, an initial speed of the object associated with the object's motion, a predefined value, an initial width and duration of the regression window, a value based on the signal's carrier frequency, a value based on the signal's subcarrier frequency, a signal's bandwidth, an antenna's aggregate value associated with the channel, noise characteristics, a signal h metric, and / or an adaptive (and / or dynamically adjusted) value. The current time offset may be at the center, left, right, and / or another fixed relative position of the regression window.

[0206] In the presentation, information may be displayed along with a map (or environmental model) of the location. Information may include location, zone, area, region, coverage area, corrected location, approximate location, location wrt a map of the location, location wrt a segmented location, direction, route, route wrt a map and / or segmentation, trace (e.g., location within a time window such as the last 5 seconds, or the last 10 seconds, where the time window duration may be adaptively (and / or dynamically) adjusted, and the time window duration may be adaptively (and / or dynamically) adjusted for speed, acceleration), route history, approximate regions / zones along the route, history / summary of past locations, history of past locations of interest, frequently visited areas, customer traffic, herd distribution, herd behavior, herd control information, speed, acceleration, movement statistics, respiration rate, heart rate, presence / absence of movement, Presence or absence of a person, pet, or object, presence or absence of vital signs, gesture control (controlling a device using gestures), location-based gesture control, location-based operation information, identity (ID) or identifier of the object of interest (e.g., pet, person, self-guided machine / device, vehicle, drone, car, boat, bicycle, unmanned car, machine with fan, air conditioner, TV, machine with moving parts), user identification (e.g., person), user information, position / speed / acceleration / direction / movement / gesture / gesture control / movement trace, user ID or identifier, user activity, user state, user sleep / rest characteristics, user emotional state, user vital signs, location The event information may include environmental information, location weather information, earthquake, explosion, storm, rain, fire, temperature, collision, impact, vibration, events, door opening events, door slamming events, window opening events, window slamming events, fall events, combustion events, freezing events, water-related events, wind-related events, air movement events, accident events, quasi-periodic events (e.g., running on a treadmill, hopping, skipping rope, somersaults, etc.), recurring events, swarming events, vehicle events, user gestures (e.g., hand gestures, arm gestures, foot gestures, leg gestures, body gestures, head gestures, face gestures, mouth gestures, eye gestures, etc.).

[0207] Location may be two-dimensional (e.g., using two-dimensional coordinates), three-dimensional (e.g., using three-dimensional coordinates). Location may be relative (e.g., with respect to a map or environmental model) or relational (e.g., halfway between point A and point B, around a corner, upstairs, on a table, on the ceiling, on the floor, on a couch, close to point A, a distance R from point A, within a radius of R from point A, etc.). Location may be expressed in Cartesian coordinates, polar coordinates, and / or another representation.

[0208] Information (e.g., location) may be marked with at least one symbol. The symbol may change over time. The symbol may flash and / or pulsate with or without changing color / intensity. The size may change over time. The orientation of the symbol may change over time. The symbol may be a number reflecting an instantaneous quantity (e.g., user's vital signs / respiratory rate / heart rate / gesture / status / condition / action / movement, temperature, network traffic, network connectivity, device / machine status, remaining device power, device state, etc.). The rate of change, size, orientation, color, intensity, and / or symbol may reflect the respective movement. Information may be presented visually and / or verbally explained (e.g., using pre-recorded audio or speech synthesis). Information may be written in text. Information may also be presented in a mechanical manner (e.g., animated gadgets, moving parts).

[0209] The user interface (UI) device may be a smartphone (e.g., iPhone, Android phone), a tablet (e.g., iPad), a laptop (e.g., notebook computer), a personal computer (PC), a device with a graphic user interface (GUI), a smart speaker, a device with voice / sound / speaker capabilities, a virtual reality (VR) device, an augmented reality (AR) device, a smart car, an in-car display, a voice assistant, an in-car voice assistant, etc.

[0210] A map (or environmental model) may be two-dimensional, three-dimensional, and / or higher dimensional. (e.g., a time-varying 2D / 3D map / environment model). Walls, windows, doors, entrances, exits, and restricted areas may be marked on the map or model. A map may include a floor plan of a facility. A map or model may have one or more layers (overlays). A map / model may be a maintenance map / model including water pipes, gas pipes, wiring, cable runs, air ducts, crawl spaces, ceiling layouts, and / or basement layouts. A location may be segmented / subdivided / regionalized / grouped into multiple zones / areas / geographical regions / sectors / sections / territories / districts / administrative areas / sites / neighborhoods / areas / stretches / open spaces, such as bedrooms, living rooms, storage rooms, walkways, kitchens, dining rooms, foyers, garages, first floors, second floors, restrooms, offices, conference rooms, reception areas, various office areas, various warehouse areas, various facility areas, etc. The segments / areas / regions may be presented on the map / model. Different regions may be color coded. Different regions may be presented with characteristics (e.g., color, brightness, color intensity, texture, animation, blinking, blink rate, etc.) Logical segmentation of locations may be performed using at least one heterogeneous Type 2 device, or server (e.g., hub device), or cloud server, etc.

[0211] Here is an example of the disclosed system, device, and method. Stephan and his family want to install the disclosed wireless motion detection system to detect movement in their 2,000-square-foot, two-story townhouse in Seattle, Washington. Because his house is two stories, Stephan decides to use one Type 2 device (named A) and two Type 1 devices (named B and C) on the first floor. The first floor is centered around three rooms: the kitchen, dining room, and living room, with the dining room in the middle and arranged in a straight line. The kitchen and living room are on opposite sides of the house. He places a Type 2 device (A) in the dining room, one Type 1 device (B) in the kitchen, and another Type 1 device (C) in the living room. With this device installation, he specifically uses the motion detection system to partition the first floor into three zones: the dining room, the living room, and the kitchen. When motion is detected by the AB pair and the AC pair, the system analyzes the motion information and associates the motion with one of three zones.

[0212] When Stefan and his family go away for the weekend (e.g., going camping for a long weekend), Stefan turns on the motion detection system using a mobile phone app (e.g., Android phone app or iPhone app). When the system detects motion, an alert signal is sent to Stefan (e.g., SMS text message, email, push message to the mobile phone app, etc.). If Stefan pays a monthly fee (e.g., $10 / month), a service company (e.g., a security company) receives the alert signal through a wired network (e.g., broadband) or wireless network (e.g., home WiFi, LTE, 3G, 2.5G, etc.) and performs security procedures for Stefan (e.g., calling him to check the problem, sending someone to check the house, contacting the police on Stefan's behalf, etc.). Stefan loves his elderly mother and is concerned about her well-being when he is home alone. When his mother is home alone while the rest of the family is out (e.g., going to work, shopping, or on vacation), Stephan uses his mobile app to turn on the motion detection system to ensure his mother is okay. He then uses the mobile app to monitor his mother's movements around the house. When Stephan uses the mobile app to see his mother moving around the house between three areas, according to her daily routine, Stephan knows that his mother is okay. Stephan is grateful that the motion detection system can help him monitor his mother's well-being while he is away from home.

[0213] On a typical day, his mother wakes up around 7:00 AM. She plans to make breakfast in the kitchen in about 20 minutes. She then eats breakfast in the dining room for about 30 minutes. Then, she does her daily exercise in the living room before sitting on the sofa and watching her favorite TV show. The motion detection system allows Stephan to see the timing of movements in each of three areas of the house. When the movements fit into her daily routine, Stephan knows roughly that his mother should be doing well. However, if the movement pattern seems abnormal (e.g., no movement until 10:00 AM, staying in the kitchen too long, remaining motionless for long periods of time, etc.), Stephan suspects something is wrong and calls his mother to check on her. Stephan may even ask someone (e.g., family member, neighbor, paid staff member, friend, social worker, service provider) to check on his mother.

[0214] Occasionally, Stephen feels the need to reposition his Type 2 device. He simply unplugs the device from its original AC power plug and plugs it into another AC power plug. He is pleased that the wireless motion detection system is plug-and-play, and repositioning does not affect the system's operation. Once powered on, it works immediately.

[0215] On another occasion, Stephan is so convinced that our wireless motion detection system can indeed detect motion with very high accuracy and very low alerts that he can actually use the mobile app to monitor motion on the first floor. He decides to install a similar configuration (i.e., one Type 2 device and two Type 1 devices) on the second floor to monitor the bedrooms on the second floor. Again, he finds that system setup is extremely easy, as he simply needs to plug the Type 2 and Type 1 devices into AC power plugs on the second floor. No special installation is required. He can then use the same mobile app to monitor motion on the first and second floors. Each Type 2 device on the first / second floors can interact with all Type 1 devices on both the first and second floors. Stephan is happy to see that as he doubles his investment in Type 1 and Type 2 devices, he has more than double the capacity of his combined system.

[0216] According to various embodiments, each CI (CI) may include at least one of channel state information (CSI), frequency domain CSI, a frequency representation of CSI, frequency domain CSI associated with at least one subband, time domain CSI, intra-domain CSI, a channel response, a channel response estimate, a channel impulse response (CIR), a channel frequency response (CFR), channel characteristics, a channel filter response, CSI of a wireless multipath channel, information of a wireless multipath channel, a timestamp, auxiliary information, data, metadata, user data, account data, access data, security data, session data, status data, management data, family data, identity (ID), identifier, device data, network data, proximity data, environmental data, real-time data, sensor data, stored data, encrypted data, compressed data, protected data, and / or another CI. In one embodiment, the disclosed system includes hardware components (e.g., a wireless transmitter / receiver with an antenna, analog circuitry, a power supply, a processor, a memory) and corresponding software components. According to various embodiments of the present disclosure, the disclosed system includes a Bot (referred to as a Type 1 device) and an Origin (referred to as a Type 2 device) for vital signs detection and monitoring, each device comprising a transceiver, a processor, and a memory.

[0217] The disclosed system can be applied in many ways. In one example, a Type 1 device (transmitter) may be a small WiFi-enabled device placed on a table. It may also be a WiFi-enabled television (TV), set-top box (STB), smart speaker (e.g., Amazon Echo), smart refrigerator, smart microwave, mesh network router, mesh network satellite, smartphone, computer, tablet, smart plug, etc. In one example, a Type 2 (receiver) may be a WiFi-enabled device placed on a table. It may also be a WiFi-enabled television (TV), set-top box (STB), smart speaker (e.g., Amazon Echo), smart refrigerator, smart microwave, mesh network router, mesh network satellite, smartphone, computer, tablet, smart plug, etc. Type 1 and Type 2 devices may be placed in / near a conference room to count people. Type 1 and Type 2 devices may be a health monitoring system for the elderly to monitor daily activities and any signs of symptoms (e.g., dementia, Alzheimer's disease). Type 1 and Type 2 devices may be used in an infant monitor to monitor the vital signs (breathing) of living infants. Type 1 and Type 2 devices can be placed in bedrooms to monitor sleep quality and any sleep apnea. Type 1 and Type 2 devices can be placed in automobiles to monitor passenger and driver health, detect driver sleep, and detect any babies left in the car. Type 1 and Type 2 devices can be used in logistics to prevent human trafficking by monitoring people hidden in trucks and containers. Type 1 and Type 2 devices can be deployed by emergency services in disaster areas to search for victims trapped in rubble. Type 1 and Type 2 devices can be placed in an area to detect the breathing of any intruders. Non-wearable wireless respiratory monitoring has many applications.

[0218] The hardware modules may be configured to include Type 1 transceivers and / or Type 2 transceivers and may be sold / used under variable brands to design, build, and sell final commercial products. The products using the disclosed systems and / or methods may be home / office security products, sleep monitoring products, WiFi products, mesh products, TVs, STBs, entertainment systems, HiFi, speakers, home appliances, lamps, stoves, ovens, microwaves, tables, chairs, beds, shelves, tools, appliances, torches, vacuum cleaners, smoke detectors, sofas, pianos, fans, doors, windows, door / window handles, locks, smoke detection equipment, car accessories, computing devices, office supplies, air conditioners, heaters, pipes, connectors, surveillance cameras, access points, computer equipment, mobile devices, LTE devices, 3G / 4G / 5G / 6G devices, UMTS devices, 3GPP devices, GSM devices, EDGE devices, TDMA devices, FDMA devices, CDMA devices, WCDMA devices, TD-SCDMA devices, gaming devices, eyeglasses, glass panels, VR goggles, necklaces, watches, waistbands, belts, wallets, pens, hats, clothing, implantable devices, tags, parking tickets, smartphones, etc.

[0219] The summarization may include: analysis, output response, selected time window, sub-sampling, transformation, and / or projection. The presentation may include presenting at least one of a month / week / day view, simplified / detailed view, cross-sectional view, small / large form factor view, color-coded view, comparison view, summary view, video, web view, audio announcement, and another presentation related to the cyclical / recurring characteristics of the recurring motion.

[0220] A Type 1 / Type 2 device is any device that includes an antenna, a device with an antenna, a device with a housing (e.g., for a radio, antenna, data / signal processing unit, radio IC, circuitry), a device that interfaces / attaches / connects / links to another device / system / computer / phone / network / data aggregator, a device with a user interface (UI) / graphical UI / display, a device with a wireless transceiver, a device with a wireless transmitter, a device with a wireless receiver, an Internet of Things (IoT) device, a device with a wireless network, a device with both wired and wireless network capabilities, a device with a wireless integrated circuit (IC), a Wi-Fi device, a device with a Wi-Fi chip (e.g., compliant with 802.11a / b / g / n / ac / ax standards), a Wi-Fi access point (AP), a Wi-Fi client, a WiFi router, a Wi-Fi repeater, a WiFi hub, a WiFi mesh network router / hub / AP, a wireless mesh network router, an ad-hoc network device, a wireless mesh network device, a mobile device (e.g., 2G / 2.5G / 3G / 3G).5G / 4G / LTE / 5G / 6G / 7G, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA), cellular device, base station, mobile network base station, mobile network hub, mobile network compatible device, LTE device, device with LTE module, mobile module (e.g., circuit board with mobile-enabling chip (IC) such as Wi-Fi chip, LTE chip, BLE chip), device with mobile module, smartphone, companion device for smartphone (e.g., dongle, attachment, plug-in), dedicated device, plug-in device, AC-powered device, battery-powered device, device with processor / memory / instruction set, smart device / gadget / Item: A watch, stationery, pen, user interface, paper, mat, camera, television (TV), set-top box, microphone, speaker, refrigerator, oven, machine, phone, wallet, furniture, door, window, ceiling, floor, wall, table, chair, bed, nightstand, air conditioner, heater, pipe, duct, cable, carpet, decoration, gadget, USB device, plug, dongle, lamp / light, tile, ornament, bottle, vehicle, automobile, AGV, drone, robot, laptop, tablet, computer, hard disk, network card, equipment, racket, ball, shoe, wearable device, clothing, eyeglasses, hat, necklace, food, pill, small device that moves within a living being's body (e.g., blood vessels, lymph, digestive system), and / or another device. The Type 1 device and / or Type 2 device may be communicatively coupled to the Internet, another device that accesses the Internet (e.g., a smartphone), a cloud server (e.g., a hub device), an edge server, a local server, and / or storage. Type 1 and / or Type 2 devices may operate under local control, may be controlled by another device via a wired or wireless connection, may operate automatically, or may be controlled by a central system located remotely (e.g., away from the home).

[0221] In one embodiment, a Type-B device may be a transceiver that may perform as both an origin (Type-2 device, Rx device) and a bot (Type-1 device, Tx device), i.e., a Type-B device may be both a Type-1 (Tx) device and a Type-2 (Rx) device (e.g., simultaneously or alternately), such as a mesh device, mesh router, etc. In one embodiment, a Type-A device may be a transceiver that may function only as a bot (Tx device), i.e., it may be only a Type-1 device or only a Tx, such as a simple IoT device. It may have the functionality of an origin (Type-2 device, Rx device), but in some embodiment, it functions only as a bot. All Type-A and Type-B devices form a tree structure. The root may be a Type-B device that has access to a network (e.g., the Internet). For example, it may be connected to broadband service via a wired connection (e.g., Ethernet, cable modem, ADSL / HDSL modem) or a wireless connection (e.g., LTE, 3G / 4G / 5G, WiFi, Bluetooth, microwave link, satellite link, etc.). In one embodiment, all Type A devices are leaf nodes. Each Type B device may be a root node, a non-leaf node, or a leaf node.

[0222] The Type 1 device (transmitter, or Tx) and Type 2 device (receiver, or Rx) may be on the same device (e.g., RF chip / IC), or simply on the same device. The device may operate in high frequency bands such as 28 GHz, 60 GHz, 77 GHz, etc. The RF chip may have dedicated Tx antennas (e.g., 32 antennas) and dedicated Rx antennas (e.g., another 32 antennas).

[0223] One transmit antenna can transmit a radio signal (e.g., a series of probe signals, perhaps at 100 Hz). Alternatively, all Tx antennas can be used to transmit radio signals with beamforming (at Tx), so that the radio signals are focused in a particular direction (e.g., for energy efficiency, or to boost the signal-to-noise ratio in that direction, or low-power operation when "scanning" in that direction, or low-power operation when an object is known to be in that direction).

[0224] The radio signal hits an object (e.g., a living human lying on a bed 4 feet away from the Tx / Rx antennas, breathing and heartbeat) within a location (e.g., a room). Object movement (e.g., lung movement according to breathing rate, or blood vessel movement according to heartbeat) can affect / modulate the radio signal. All Rx antennas can be used to receive the radio signal.

[0225] Beamforming (at the Rx and / or Tx) may be applied (digitally) to "scan" different directions. Many directions may be scanned or monitored simultaneously. Along with beamforming, a "sector" (e.g., direction, orientation, azimuth, bearing, zone, region, segment) may be defined relative to the Type 2 device (e.g., relative to the center position of the antenna array). For each probing signal (e.g., pulse, ACK, control packet, etc.), channel information or CI (e.g., channel impulse response / CIR, CSI, CFR) is obtained / calculated (e.g., from the RF chip) for each sector. For respiration detection, CIR can be collected over a sliding window (e.g., 30 seconds; a 100 Hz ringing / probing rate could have 3000 CIRs over 30 seconds).

[0226] A CIR can have many taps (e.g., N1 components / tap). Each tap may be associated with a time lag, or time-of-fright (e.g., the time it takes to hit and back a person 4 feet away). When breathing in a certain direction at a certain distance (e.g., 4 feet), one can find the CIR in the "certain direction" and then find the tap corresponding to the "certain distance." Respiration rate and heart rate can then be calculated from that tap of that CIR.

[0227] Each tap within a sliding window (e.g., a 30-second window of "component time series") can be considered a time function (e.g., a "tap function," "component time series"). Each tap function can be examined in search of strong periodic behavior (e.g., corresponding perhaps to breathing in the range 10 bpm to 40 bpm).

[0228] A Type 1 device and / or a Type 2 device can have external connections / links and / or internal connections / links. An external connection (e.g., connection 1110) can be associated with 2G / 2.5G / 3G / 3.5G / 4G / LTE / 5G / 6G / 7G / NBIoT, UWB, WiMax, Zigbee, 802.16, etc. The internal connections (e.g., 1114A and 1114B, 1116, 1118, 1120) can be associated with WiFi, IEEE802.11 standards, 802.11a / b / g / n / ac / ad / af / ag / ah / ai / aj / aq / ax / ay, Bluetooth 1.0 / 1.1 / 1.2 / 2.0 / 2.1 / 3.0 / 4.0 / 4.1 / 4.2 / 5, BLE, mesh networking, and IEEE802.16 / 1 / 1a / 1b / 2 / 2a / a / b / c / d / e / f / g / h / i / j / k / l / m / n / o / p / standards.

[0229] Type 1 devices and / or Type 2 devices are powered by batteries (e.g., AA batteries, AAA batteries, coin cell batteries, button cell batteries, small batteries, battery banks, power banks, car batteries, hybrid batteries, vehicle batteries, container batteries, non-rechargeable batteries, rechargeable batteries, NiCd batteries, NiMH batteries, lithium ion batteries, zinc carbon batteries, zinc chloride batteries, lead acid batteries, alkaline batteries, batteries with wireless chargers, smart batteries, solar batteries, boat batteries, plain batteries, other batteries, temporary energy storage devices, capacitors, flywheels).

[0230] Any device may be powered by DC or direct current (e.g., from batteries, generators, power converters, solar panels, rectifiers, DC-DC converters as described above, at various voltages such as 1.2V, 1.5V, 3V, 5V, 6V, 9V, 12V, 24V, 40V, 42V, 48V, 110V, 220V, 380V, etc.) and therefore may have a DC connector or connectors with at least one pin for DC power.

[0231] Any device may be powered by AC or alternating current (e.g., from a domestic wall outlet, a transformer, an inverter, shore power, or various voltages such as 100V, 110V, 120V, 100-127V, 200V, 220V, 230V, 240V, 220-240V, 100-240V, 250V, 380V, 50Hz, 60Hz, etc.) and therefore may have an AC connector or connectors with at least one pin for AC power. Type 1 devices and / or Type 2 devices may be located (e.g., installed, positioned, moved) within or outside a location.

[0232] For example, in a vehicle (e.g., an automobile, truck, lorry, bus, specialty vehicle, tractor, excavator, drilling machine, teleporter, bulldozer, crane, forklift, electric vehicle, AGV, emergency vehicle, cargo, freight car, trailer, container, boat, ferry, ship, submarine, aircraft, airship, lift, monorail, train, electric railcar, rail car, rail car, etc.), the Type 1 device and / or Type 2 device may be an embedded device embedded in the vehicle or an add-on device (e.g., an aftermarket device) plugged into a port within the vehicle (e.g., an OBD port / socket, a USB port / socket, an accessory port / socket, a 12V auxiliary power outlet, and / or a 12V cigarette lighter port / socket).

[0233] For example, one device (e.g., a Type 2 device) may be plugged into a 12V cigarette lighter / accessory port or an OBD port or a USB port (e.g., of a car / truck / vehicle), and the other device (e.g., a Type 1 device) may be plugged into a 12V cigarette lighter / accessory port or an OBD port or a USB port (e.g., of a car / truck / vehicle). The OBD port and / or USB port may provide power, signaling, and / or networking (of the car / truck / vehicle). The two devices may jointly monitor passengers, including children / babies, in the vehicle. They may be used to count passengers, recognize the driver, and detect the presence of passengers in specific seats / positions within the vehicle.

[0234] In another embodiment, one device may be plugged into a 12V cigarette lighter / accessory port or OBD port or USB port of a car / truck / vehicle, while the other device may be plugged into a 12V cigarette lighter / accessory port or OBD port or USB port of another car / truck / vehicle.

[0235] In another example, many devices of the same Type A (e.g., Type 1 or Type 2) may exist in many heterogeneous vehicles / portable devices / smart gadgets (e.g., automated guided vehicles / AGVs, shopping / luggage / mobile carts, parking tickets, golf carts, bicycles, smartphones, tablets, cameras, recording devices, smartwatches, roller skates, shoes, jackets, goggles, hats, eyewear, wearables, Segways, scooters, baggage tags, cleaning machines, vacuum cleaners, pet tags / collars / wearables / implants), each of which may be plugged into the vehicle's 12V accessory port / OBD port / USB port or embedded in the vehicle. There may also be one or more other Type B devices (e.g., if A is Type 2, then B is Type 1, and if A is Type 1, then B is Type 2) installed in locations such as gas stations, streetlights, street corners, tunnels, multi-story parking lots, and scattered locations covering a large area such as factories, stadiums, train stations, shopping malls, and construction sites. Type A devices can be located, tracked, or monitored based on TSCI.

[0236] The area / location may not have local connectivity such as broadband service, Wi-Fi, etc. Type 1 and / or Type 2 devices may be portable. Type 1 and / or Type 2 devices may support plug and play.

[0237] Pairwise wireless links can be established between many pairs of devices, forming a tree structure. In each pair (and associated link), a device (the second device) may be a non-leaf (Type B). The other device (the first device) may be a leaf (Type A or Type B) or a non-leaf (Type B). In the link, the first device acts as a bot (Type 1 device or transmitting device) to transmit a wireless signal (e.g., a probe signal) to the second device over a wireless multipath channel. The second device can act as an origin (Type 2 device or Rx device) to receive the wireless signal, obtain TSCI, and calculate a "link analysis" based on the TSCI.

[0238] FIG. 1 illustrates an exemplary scenario in which object movement is detected based on channel state information within a location, according to one embodiment of the present disclosure. For example, as shown in FIG. 1, in a two-bedroom apartment 100, an origin 101 may be located in the living area 102, a bot 1 110 may be located in the bedroom 1 area 112, and a bot 2 120 may be located in the dining room area 122. Each of bot 1 110 and bot 2 120 may transmit a wireless signal to the origin 101, which may acquire channel information of a wireless multipath channel based on the wireless signal. The origin 101 may calculate motion information based on the channel information and detect object movement / activity based on the motion information, either by itself or through a third device such as a motion detector. That is, the origin 101 may detect object movement / activity based on the wireless signals transmitted by bot 1 110 and / or bot 2 120, either by itself or through a third device such as a motion detector.

[0239] If object movement / activity is detected based on wireless signals transmitted by both Bot1 110 and Bot2 120, the activity / movement or object (e.g., person / user) may be located in the living room area 102. If object movement / activity is detected based only on wireless signals transmitted by Bot1 110, the activity / movement or object (e.g., person / user) may be located in the bedroom 1 area 112. If object movement / activity is detected based only on wireless signals transmitted by Bot2 120, the activity / movement or object (e.g., person / user) may be located in the dining room area 122. If object movement / activity cannot be detected based on wireless signals transmitted by either Bot1 110 or Bot2 120, it can be determined that no one or object is located in the apartment 100. The corresponding area in which the activity / movement / person / user was detected may be marked with a predetermined pattern.

[0240] In some embodiments, the bot and origin of a wireless monitoring system may be located in different locations, for example, based on the location of a power source and / or the location of the object being monitored. For example, in a vehicle wireless monitoring system including a bot (or transmitter) and an origin (or receiver), each of the transmitter and receiver may be located in different locations within the vehicle or in different locations on the vehicle.

[0241] In some embodiments, bots and origins may also be utilized in wireless monitoring systems, sometimes referred to as car presence detection (CPD) systems or vehicle wireless monitoring systems, to monitor objects or detect events related to vehicles.

[0242] In some embodiments, bots and origins may also be utilized in a wireless monitoring system to monitor objects or detect events to trigger an assistant device or digital assistant system, such as a smart speaker or a smart assistant such as Google Home or Amazon Alexa. Results from the wireless monitoring system may automatically trigger and / or adjust the operation of the digital assistant system, for example, turning on or adjusting the operation of the digital assistant system upon motion detection, motion loss, motion location, etc. The wireless monitoring system together with the assistant device may be referred to as an automated assistant system.

[0243] The wireless monitoring system, including the bot and origin, can enter various operating modes, such as an inactive mode, a dormant mode, a sleep mode, a standby mode, a low-power mode, an off mode, and / or a power-down mode. Exemplary transitions between system operating modes are shown in FIGS. 2A and 2B. As shown in FIG. 2A, the system can initially operate in mode 1 using parameter P1. Upon some trigger event T12, the system can transition to operating mode 2 using parameter P2. Then, upon another trigger event T21, the system can return to operating mode 1. As shown in FIG. 2B, another operating mode 3 with parameter P3 may exist. In one embodiment, the system currently operates in mode 2. Upon some trigger event T23, the system can transition to operating mode 3. Then, upon another trigger event T31, the system can return to operating mode 1.

[0244] FIG. 3 illustrates a flowchart of an exemplary method 300 of a wireless monitoring system according to some embodiments of the present disclosure. In operation 302, a transmitter, e.g., on a bot, transmits a wireless signal through a wireless multipath channel of a location. In operation 304, a receiver, e.g., on an origin, receives the wireless signal affected by the wireless multipath channel and modulation of an object moving within the location. In operation 306, a set of channel information (CI) for the wireless multipath channel is obtained based on the wireless signal. In operation 308, a monitoring task for monitoring the object and its movement is executed based on the set of CI. In operation 310, multiple allowable system states of the wireless monitoring system are determined. Each allowable system state is associated with a respective setting of at least one of the wireless signal, a set of sounding signals in the wireless signal, or a monitoring task. In operation 312, one of the allowable system states is selected as a system state of the wireless monitoring system based on the monitoring task. In operation 314, the wireless monitoring system is configured by applying a setting associated with the selected allowable system state to the wireless monitoring system. The order of the operations in FIG. 3 may be changed according to various embodiments of the present disclosure.

[0245] FIG. 4 shows a flowchart of another exemplary method 400 of a wireless monitoring system according to some embodiments of the present disclosure. At operation 402, a set of channel information (CI) for a wireless multipath channel within a location is obtained based on a wireless signal affected by modulation of the wireless multipath channel and an object moving within the location. At operation 404, a monitoring task is executed to monitor objects and object movement based on the set of CIs. At operation 406, a plurality of allowable system states for the wireless monitoring system are determined. Each allowable system state is associated with a respective setting. At operation 408, one of the allowable system states is automatically selected as a system state for the wireless monitoring system based on the monitoring task. At operation 410, the wireless monitoring system is configured by applying the setting associated with the selected allowable system state to the wireless monitoring system. Optionally, at operation 412, the system state is changed to a first state associated with a normal sounding rate associated with the monitoring task. Optionally, at operation 414, the system state is changed to a second state associated with a sounding rate higher than the normal sounding rate, if required by the monitoring task. Optionally, in operation 416, the system state is changed to a third state associated with a sounding rate lower than the normal sounding rate to conserve power. The order of the operations in FIG. 4 may be changed according to various embodiments of the present disclosure.

[0246] Humanoid mannequins can mimic human activity as test subjects for WiFi sensing. Wireless sensing has brought many benefits to people's daily lives. However, involving human subjects in testing for wireless sensing and monitoring applications can pose potential health risks or inconvenience / dependence, as the testing and regulatory processes can be lengthy and expensive. Liability issues may also exist due to potential workplace injuries. Replicable, reproducible, and scalable testing processes are highly necessary because they can shorten product development and commercialization times and create standardized testing protocols for the wireless sensing industry.

[0247] There are examples of using a substitute subject for testing, such as Specific Absorption Rate (SAR) testing, which is a radio frequency (RF) dosimetric quantification of the magnitude and distribution of absorbed electromagnetic energy within a biological object exposed to an RF field.

[0248] A specific anthropomorphic manikin (SAM) is a phantom constructed from specific materials that simulate the dielectric properties of the human body. The electrical conductivity and permittivity of the human body are mimicked with solutions of sugar, salt, water, and other ingredients. Different solutions can be used for different frequencies, e.g., Wi-Fi or 5G.

[0249] From the perspective of the human body, SAMs can mimic radiation absorption, and the radiation absorbed dose can be used to estimate the effects on the human body. However, from the perspective of wireless sensing, if humans and pets are similar in size and shape, the absorption of SAMs can mimic the real interaction with wireless signals (such as WiFi multipath), and they could potentially be used as test subjects in WiFi sensing tests instead of human subjects.

[0250] An exemplary approach using a permuted test subject is described below. First, a radio frequency band of interest can be selected, such as the WiFi 5 GHz band (5.250-5.350 GHz, 5.470-5.725 GHz). Second, a SAM is used in this frequency band. The high-frequency response of a material can be expressed as a complex permittivity. Shapes of different sizes can be tested, such as human adults, children, infants, pets, etc. They can be stationary or have moving parts (knees) or active moving parts controlled by robotic means (e.g., chest movement). In one embodiment, materials (e.g., paints or fillers) can be added to a mannequin for customization. Humanoid robots, or robotic parts in some approaches, can be utilized. SAMs can be from the fashion, automotive, or medical industries.

[0251] The wireless monitoring system may be in any one of a plurality of allowable system states, each associated with a respective setting of at least one of a wireless signal, a set of sounding signals on the wireless signal, or a monitoring task. At a given time, the system operates in a system state selected from the allowable system states. For example, FIG. 5 illustrates a process of system state transitions for a wireless monitoring system according to some embodiments of the present disclosure. The wireless monitoring system associated with FIG. 5 can operate in different system states, where each system state corresponds to a sounding signal at a different frequency.

[0252] In one embodiment, the wireless monitoring system of FIG. 5 may be utilized to monitor human health, for example, by performing daily activity, sleep monitoring, and / or fall detection. The wireless monitoring system may have a default state with a sounding signal at a frequency of 1 Hz to search for movement or respiratory activity. This default frequency is selected to have good performance, e.g., a sufficiently high detection rate, when no one is home, or when the system is expected to experience the most frequent conditions.

[0253] When a trigger event occurs, the system transitions from one state to another. For example, if a large movement is detected and certain criteria are met, the system changes its sounding signal frequency to X3 Hz and enters another state, where X3 > X1. In this new state, the system can wait to detect falls in addition to motion and breathing detection.

[0254] Once a certain timeout condition is met, for example, after a predetermined period without a fall accident detection, the system returns to the default state with an X1 Hz sounding signal. When the system engine is in the sleep stage, the system can either remain in the default X1 Hz state or switch to the X2 Hz state, as shown in FIG. 5, where X2>X1. The X1 Hz state allows the system to perform normal sleep monitoring using an X1 Hz sounding signal, and sleep apnea can only be detected if it persists beyond a first period T1. The X2 Hz state allows the system to perform normal sleep monitoring using an X2 Hz sounding signal, and sleep apnea can be detected whenever it persists beyond a second period T2, where T2 is shorter than T1. If a large movement or movement pattern is detected (e.g., rolling toward the edge of the bed), the system switches to the X3 Hz state and waits for a fall from the bed, where X3>X2.

[0255] In some embodiments, the system can use the X3 Hz sounding signal as a default and constant frequency, which prevents frequency switching upon any trigger event. When a trigger event occurs, the system engine can perform downsampling and use the X1 Hz component for motion and respiration detection.

[0256] FIG. 6 illustrates another system state transition process for a wireless monitoring system according to some embodiments of the present disclosure. The wireless monitoring system associated with FIG. 6 can operate in different system states, where each system state corresponds to a sounding signal at a different frequency. In one embodiment, the wireless monitoring system of FIG. 6 can be utilized to detect the presence of objects and / or monitor the movement of objects within a home or space. For example, the system can be a home monitoring or public space monitoring system to ensure safety.

[0257] The system according to FIG. 6 may have a default state with a sounding signal frequency of Y1 Hz to detect motion within a space. When motion is detected, the system sends an alert. After motion ceases, the system can remain in the Y1 Hz state for breath detection, or switch to the Y2 Hz state for finer resolution or a shorter apnea window, where Y2 > Y1. In one embodiment, the Y2 Hz state allows the system to perform wireless surveillance using the Y2 Hz sounding signal to detect motion in scenarios where an intruder is stationary but intends to remain in the space, or in a mall, museum, or public restroom after closing for the day. When a certain timeout condition is met, for example, after a predetermined period of no motion detection, the system returns to the initial state with the Y1 Hz sounding signal.

[0258] In other embodiments, instead of having a single default state, the system can be designed to alternate between multiple states. For example, the system in Figure 6 stays in the Y1Hz state for S1 seconds, then switches to the Y2Hz state for S2 seconds, and then back to Y1Hz.

[0259] 7A-7C are diagrams illustrating different arrangements for a transmitter and receiver in a vehicle wireless monitoring system according to some embodiments of the present disclosure. As shown in FIG. 7A, a vehicle wireless monitoring system can be used to monitor and track an object (e.g., an infant or child 750) in a car 701. In the example shown in FIG. 7A, the wireless receiver of the vehicle wireless monitoring system can be located in a position 710 in front of the driver's seat of the car 701. In some embodiments, the wireless receiver can function as a hub for a smart car telematics monitor or other in-vehicle devices. In some embodiments, the wireless receiver includes a processor or wireless AI engine and can connect to a cloud server based on LTE or 5G.

[0260] In the example shown in FIG. 7A , a wireless transmitter for a vehicle wireless monitoring system may be located at location 720 on the dashboard or front-end window of a car 701. In some embodiments, the wireless transmitter can function as a high-quality car front dash cam for recording streaming video, for example, upon request from a wireless AI engine in the wireless receiver. In some embodiments, the wireless transmitter located at location 720 can connect to the wireless receiver located at location 710 and perform in-car wireless sensing based on Wi-Fi signals. In some embodiments, the wireless transmitter is plugged into a 12V outlet in the car 701 for charging. In some embodiments, the wireless transmitter is hardwired to the battery box of the car 701 for charging.

[0261] FIG. 7B illustrates another location for a transmitter and receiver in a vehicle wireless monitoring system, according to some embodiments of the present disclosure. In the example shown in FIG. 7B , the wireless receiver of the vehicle wireless monitoring system is still located in position 710 in front of the driver's seat of the car 701, while the wireless transmitter of the vehicle wireless monitoring system may be located in position 721 or position 722, which may be located in a location where a 12V outlet is available. If the wireless AI engine in the wireless receiver can only host one transmitter for Wi-Fi sensing, it can select one of positions 721 and 722 to locate the wireless transmitter. In some embodiments, the wireless transmitter in this case could be a high-speed USB-C charger that plugs into the car's 12V outlet and is equipped with a battery. In some embodiments, the wireless transmitter located in position 721 or position 722 can connect to the wireless receiver located in position 710 to perform in-car wireless sensing and monitoring.

[0262] FIG. 7C illustrates yet another location for a transmitter and receiver in a vehicle wireless monitoring system, according to some embodiments of the present disclosure. While the wireless receiver of the vehicle wireless monitoring system is still located in location 710 in front of the driver's seat of the car 701 in the example shown in FIG. 7C , the wireless transmitter of the vehicle wireless monitoring system could be located in location 723 or location 724, where the infant or child 750 is within line of sight of the wireless transmitter and wireless receiver. If the wireless AI engine in the wireless receiver can only host one transmitter for Wi-Fi sensing, it can select one of locations 723 and 724 to locate the wireless transmitter. In some embodiments, the wireless transmitter in this case may be a dedicated transmitter with a battery therein and / or a solar panel for recharging the transmitter. In some embodiments, the wireless transmitter is attached to a window of the car 701 by a suction cup. The suction cup allows the wireless transmitter to be attached to various and flexible locations on the car 701. In some embodiments, the wireless transmitter located in location 723 or location 724 can connect to the wireless receiver located in location 710 to perform in-car wireless sensing and monitoring. In very rare cases, users may need to unplug the wireless transmitter to recharge it via the USB port, in which case they will get a low battery notification from the app on the transmitter.

[0263] FIG. 8 illustrates a flowchart of an example method 800 of a wireless monitoring system according to some embodiments of the present disclosure. In operation 802, a transmitter of the wireless monitoring system, e.g., on a bot, is placed at a first location within a location and powered on. In operation 804, a receiver of the wireless monitoring system, e.g., on an origin, is placed at a second location within the location and powered on. In operation 806, a wireless signal is transmitted from the transmitter through a wireless multipath channel of the location. In operation 808, the wireless signal is received by the receiver via the wireless multipath channel. The wireless signal is affected by the wireless multipath channel and modulation of objects moving within the location. In operation 810, a set of wireless multipath channel information (CI) is obtained based on the wireless signal. In operation 812, objects and their movements are monitored based on the set of CIs. The order of the operations in FIG. 8 can be changed according to various embodiments of the present disclosure.

[0264] In one example of a vehicle wireless monitoring system, security and safety functions can operate simultaneously. For security concerns, the system can monitor the interior of the automobile via wireless sensing (or cameras). For safety concerns, the system can monitor the exterior of the automobile via cameras, radar, lidar, etc. while driving (in case of a traffic accident) and while parked (in case of a hit-and-run). For safety concerns, the system can monitor the automobile itself, for example, via sensors, gyros, or accelerometers in either the transmitter or receiver of the wireless device. When parked, the system can monitor the automobile to detect any events such as broken windows, burglaries, hit-and-runs, etc.

[0265] In another embodiment, each time the car is turned off, the system can perform WiFi sensing to check for any movement or breathing signals to see if a child or pet has been left unattended. The system may send an alarm notification to the user if such an event is detected or if the car transitions to deep sleep mode. When the car is parked in deep sleep mode, if the car is hit by another vehicle, or if a car window is broken, the system can wake up again and perform WiFi sensing again to check for a break-in event. If the transmitter is a dash cam, it can also wake up and record video for a certain period of time. This idea can be extended to other indoor wireless monitoring scenarios.

[0266] In another example, a smart device such as a smart speaker or virtual assistant artificial intelligence (AI) may be triggered by some event detected by a wireless monitoring system, such as by Mimamori or other health monitoring and security applications. For example, Alexa may be triggered by fall down detection without anyone having to ask Alexa first. Below are some example scenarios when smart speaker Alexa may be triggered by wireless monitoring.

[0267] Scenario 1 (Motion detected during security mode) 1. Alexa: Hey, Steve, is that you? Can you tell me your three passwords? 2a. Steve (homeowner): Dog, eating, pizza. 3a.Alexa: Come back, Steve. Enter Mimamori mode.

[0268] Scenario 2 (Motion detected during security mode): 1. Alexa: Hey Steve, is that you? Can you tell me your three passwords? 2b. Intruder: What? I don't know. Open Sesame 3b. Alexa: Intruder! Intruder! I've taken your photo and sent it to the owner and the CSP security center. Get out now! (Alert and / or send photo to CSP and Steve) 4b. Alexa: I see you're still there. You just entered the living room. I'm calling the police. Get out now. (Send additional alerts / photos to CSP and Steve)

[0269] Scenario 3 (Detecting Steve waking up in Mimamori mode) 1. Alexa: Good morning, Steve. Last night's sleep score was 49. Try taking a nap today. Would you like today's news or weather first? 2a. Steve: The weather. 3a.Alexa: What's the weather like today? 2b.Steve:…

[0270] Scenario 4 (No motion detected for some time or a fall detected) 3b.Alexa: Steve, are you OK? Do you want help? 4b. Steve: (quiet) 5. Alexa: Your caregiver has notified you to call. If you don't answer, she'll be on her way. (Activates security cameras)

[0271] Scenario 5 (sudden movement detected inside the vehicle) 1. Alexa: Steve, what's wrong? Should I call 911 or roadside assistance? 2a. Steve: (quiet for a moment) 3a. Alexa: You didn't respond in time. To be safe, we'll call 911 unless you say something before 10 seconds. 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, call 911. 4a. Alexa: I called 911. An ambulance is coming to help you. (Activates security cameras)

[0272] Scenario 6 (sudden movement detected inside the vehicle) 1. Alexa: Steve, what's wrong? Should I call 911 or roadside assistance? 2b. Steve: I'm stuck in the snow. I need roadside assistance. 3b. Alexa: You asked to call Roadside Assistance. Is that OK? Say yes or no. 4b. Steve: Yes. 5b. Alexa: I called Roadside Assistance. A tow truck will come to your aid. (Activates security cameras)

[0273] Scenario 7 (sudden movement detected inside the vehicle) 1. Alexa: Steve, what's up? Should I call 911 or roadside assistance? 2c.Steve: No, it's okay. 3c. Alexa: You said it was okay. Is that okay? Say yes or no. 4c.Steve: Yes. 5c.Alexa: That's great to hear. Drive safely, Steve.

[0274] FIG. 9A illustrates an occupant recognition function of a vehicle wireless monitoring system according to some embodiments of the present disclosure. As shown in FIG. 9A , the vehicle wireless monitoring system can be used to monitor and track an object associated with a vehicle 901. The object can be any one of a driver 902 in the vehicle 901, an infant or child 903 in the vehicle 901, a pet 904 in the vehicle 901, an unknown object 905 in the vehicle 901, etc. For example, based on wireless signals transmitted between a bot(s) and an origin(s) of the vehicle wireless monitoring system, the system can identify the movement of an object within the vehicle 901 (e.g., in the front seat 911, back seat 912, trunk 913 of the vehicle 901) or the movement of an object in the vicinity of the vehicle 901. In one embodiment, the system can identify the movements, gestures, and / or breathing of the driver 902 in the front seat 911 of the vehicle 901. In another embodiment, the system can identify the subtle movements and breathing of an infant or child 903 in the back seat 912 of the vehicle 901. In yet another embodiment, the system can identify the movement and breathing of a dog 904 in the back seat 912 of a car 901. In another embodiment, the system can identify the movement of an unknown object 905 in the trunk 913 of the car 901.

[0275] FIG. 9B illustrates vandalism recognition capabilities of a vehicle wireless monitoring system according to some embodiments of the present disclosure. As shown in FIG. 9B , the vehicle wireless monitoring system can be used to monitor and detect events related to a car 901. The event may be any one of a broken window 905, a hit-and-run 906, or some other abnormal behavior of the car 901. For example, based on wireless signals transmitted between a bot and an origin of the vehicle wireless monitoring system, the system can identify vandalism, vibrations, or other abnormal behavior of the car 901, which may indicate an event or accident. In one embodiment, the system can detect a broken window 905 at a passenger-side window 924 in the rear of the car 901. In another embodiment, the system can detect a hit-and-run accident 906 based on detecting abnormal vandalism or behavior at a front corner 922 and / or a rear corner 926 of the car 901.

[0276] In some embodiments, the origin of the vehicle wireless monitoring system may be a wireless receiver that functions as a hub for a smart car telematics monitor or other in-vehicle devices. In some embodiments, the wireless receiver includes a processor or wireless AI engine and can connect to a cloud server based on LTE or 5G. In some embodiments, the bot of the vehicle wireless monitoring system may be a wireless transmitter that functions, for example, as a high-quality car front dash cam for recording streaming video in response to requests from the wireless AI engine of the wireless receiver. In some embodiments, the bot of the vehicle wireless monitoring system may be a high-speed USB-C charger that plugs into a car's 12V outlet and is equipped with a battery. In some embodiments, the bot of the vehicle wireless monitoring system may be a dedicated transmitter with an internal battery and / or a solar panel for recharging the transmitter. In some embodiments, the wireless transmitter is attached to the window of the vehicle 901 by a suction cup. In some embodiments, the wireless transmitter is wirelessly connected to the wireless receiver to perform in-vehicle wireless sensing and monitoring.

[0277] FIG. 10 illustrates a flowchart of an exemplary method 1000 of a vehicle wireless monitoring system according to some embodiments of the present disclosure. At operation 1002, a first wireless signal is transmitted from a first wireless device through a wireless multipath channel at a location. The location includes the vehicle and the vehicle's immediate vicinity. For example, the location includes a vicinity area around the vehicle, where object movement may affect the wireless signal transmitted from the vehicle's base to the origin of the vehicle wireless monitoring system. This ensures detection and monitoring of any objects or events in the vehicle's vicinity, not just those inside the vehicle. At operation 1004, a second wireless signal is received by a second wireless device through the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel and modulation of the first wireless signal by objects moving within the location. At operation 1006, a time series of channel information (TSCI) of the wireless multipath channel is obtained based on the second wireless signal using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. In operation 1008, a monitoring task is performed by monitoring at least one of a vehicle, an object, or object movement based on the TSCI. The order of the operations in FIG. 10 may be changed according to various embodiments of the present disclosure.

[0278] In one embodiment, whenever a vehicle is turned off, a vehicle wireless monitoring system, such as a CPD system, performs WiFi sensing to look for any movement or breathing signals inside the vehicle. In most cases, this double-checks to determine if a child or pet has been unintentionally left inside the vehicle. If such an event or similar event is detected, the system sends a warning notification to the user. The system then goes into deep sleep mode.

[0279] In another embodiment, when the car is parked and the system is in deep sleep mode, an accident or event may occur. For example, if the car is hit by another car or its window is broken, the system automatically restarts. The system performs WiFi sensing again to check for any interruption events. If the bot or origin is connected to or coupled to a car camera (e.g., a dash camera or monitor), the camera also wakes up to record video for a predetermined period of time, e.g., 10 seconds. If such an event is detected, the system sends a warning notification to the user. The system then transitions back to deep sleep mode.

[0280] FIG. 11 illustrates an example state flow 1100 of a vehicle radio monitoring system, e.g., a car presence detection (CPD) system, according to some embodiments of the present disclosure. For example, in phase A, a user turns on the car engine to start the car, and in phase B, the user turns off the car engine and stops the car. Thus, the car is on from phase A to phase B, and the car is off from phase B to the next phase A. When the car is on, the vehicle radio monitoring system can be in a car on state 1101 to detect any abnormal activity in the trunk or outside the car. When the car is off, the vehicle radio monitoring system can enter other states in various scenarios. While a CPD system typically performs car presence detection after the car engine is turned off, as described below, in some embodiments, the CPD system can also perform car presence detection before the car engine is turned off.

[0281] In the example shown in FIG. 11 , during Phase B, the vehicle wireless monitoring system enters a first state 1110 to perform CPD sensing when the vehicle is off but the user (owner or driver) is still near the vehicle. During first state 1110, the system does not send any alerts to the user, even if motion 1112 is detected. This sensing-but-not-alerting state 1110 can persist for a predetermined period of time or until the level of motion in and / or around the vehicle falls below a predetermined threshold. The period and threshold may also be dynamically adjusted based on the number or frequency of events detected during state 1110.

[0282] The system then enters a second state 1120 to perform CPD sensing when the vehicle is off and the user (owner or driver) is not near the vehicle. During the second state 1120, the system alerts the user whenever motion 1122, 1124, 1126 is detected, and also alerts the user whenever any breathing 1125 is detected. Sensing involving the alert state 1120 can continue for a predetermined period of time or until the level of motion in and / or around the vehicle falls below a predetermined threshold. The period and threshold may also be dynamically adjusted based on the number or frequency of events detected during state 1120.

[0283] The system then enters a third state 1130 during phase C, where the car is off and the CPD system enters deep sleep mode. During third state 1130, the CPD system can be awakened, for example, during phase D, by an abnormal event, such as a collision, a broken window, etc., to again enter second state 1120 and perform CPD sensing with an alert when the car is off and the user (owner or driver) is not near the car. In this case, in response to detected motion 1128, the system sends an alert to the user during second state 1120. Then, again, the system enters third state 1130 during phase C, where the car is off and the CPD system again enters deep sleep mode. Finally, when the user turns the car engine back on, the system again enters car-on state 1101.

[0284] FIG. 12A illustrates exemplary functionality of an automated assistant system according to some embodiments of the present disclosure. As shown in FIG. 12A , the automated assistant system can be used to detect and monitor individuals entering a home 1200. The individuals may be unauthorized users, such as intruders or thieves, or legitimate users, such as the home owner or resident. For example, based on wireless signals transmitted between the bots 1210, 1220, and 1230 of the automated assistant system and the origin 1201, the system can identify the movement of an object 1250 entering the home 1200. In one embodiment, the system includes an assistant device 1205 communicatively coupled to the origin 1201. The assistant device 1205 may or may not be physically coupled to the origin 1201.

[0285] Based on the detection and / or monitoring of object movement, the assistant device 1205 can attempt to communicate with the object (person 1250) and / or can automatically generate assistance based on the communication (or communication attempt). In one embodiment, after the assistant device 1205 determines that the person 1250 is the homeowner based on the communication, the assistant device 1205 can automatically turn on the lights in the home. In another embodiment, after the assistant device 1205 determines that the person 1250 is an intruder based on the communication, the assistant device 1205 can automatically turn on an alarm and / or call 911 or other predetermined number to request help.

[0286] FIG. 12B illustrates another exemplary function of the automated assistant system according to some embodiments of the present disclosure. As shown in FIG. 12B, the automated assistant system may also be used to detect and monitor sudden movements of a person within the house 1200, such as a fall. The person 1260 may be the owner of the house or a resident of the house. For example, based on wireless signals transmitted between the bots 1210, 1220, and 1230 of the automated assistant system and the origin 1201, the system can identify that the person 1260 has fallen. Based on the detection of the fall, the assistant device 1205 can attempt to communicate with the person 1260 and / or automatically generate assistance based on the communication. In one embodiment, after the assistant device 1205 determines that the person 1260 does not need assistance based on the communication, the assistant device 1205 can turn on more lights or adjust the temperature in the house based on predetermined settings. In another embodiment, after the assistant device 1205 determines, based on the communication, that the person 1260 has collapsed and / or needs immediate help, the assistant device 1205 can automatically call 911 or other predetermined number for help.

[0287] FIG. 13 shows a flowchart of an example method 1300 for triggering an assistant device based on wireless monitoring, according to some embodiments of the present disclosure. At operation 1302, a first wireless signal is transmitted from a first wireless device within a location through a wireless multipath channel of the location. At operation 1304, a second wireless signal is received by a second wireless device through the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel being affected by the movement of a person within the location. At operation 1306, a time series of channel information (TSCI) of the wireless multipath channel is obtained based on the second wireless signal using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. At operation 1308, the movement of the person within the location is monitored based on the TSCI. At operation 1310, assistance to the person within the location is generated based on the monitoring without input from the person. The order of the operations in FIG. 13 can be changed according to various embodiments of the present disclosure.

[0288] In one example, a smart device such as a smart speaker or virtual assistant artificial intelligence (AI) may be triggered by some event detected by the wireless monitoring system disclosed herein. In one embodiment, the wireless monitoring system may include Origin Wireless's Mimamori or other health monitoring and security applications.

[0289] In some embodiments, the wireless monitoring system may be integrated into a smart speaker, such as an Amazon Echo or Amazon Alexa. In some embodiments, motion monitoring may be a skill on the smart speaker that interfaces with the wireless monitoring system. The wireless monitoring system may monitor motion and communicate analytics directly to the smart speaker. In some embodiments, the wireless monitoring system may monitor motion and send Level 1 analytics to the device, which may be a local or cloud device that performs additional processing and sends some Level 2 analytics to the smart speaker.

[0290] In some embodiments, a user provides verbal commands to a smart speaker, which forwards the commands to a wireless monitoring system. The wireless monitoring system can use wireless sensing to monitor the user's movements and refine the user's commands. Based on the detected user movements, the wireless monitoring system can adjust system parameters or perform auxiliary actions, such as "change the volume," "play the next song," "repeat the current song," or "turn on the lights."

[0291] FIG. 14 illustrates a flowchart of an example method 1400 for wireless monitoring with a flexible power source, according to some embodiments of the present disclosure. At operation 1402, a first wireless signal is transmitted from a first wireless device through a wireless multipath channel of a location. At operation 1404, a second wireless signal is received by a second wireless device through the wireless multipath channel. The second wireless signal differs from the first wireless signal due to the wireless multipath channel being affected by the movement of objects within the location. At operation 1406, a time series of channel information (TSCI) of the wireless multipath channel is obtained based on the second wireless signal, for example, using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. At operation 1408, the movement of objects within the location is monitored based on the TSCI. At least one of the first wireless device or the second wireless device is attached to a power accessory. The order of the operations in FIG. 14 can be changed according to various embodiments of the present disclosure.

[0292] Some embodiments relate to the design / plugs / mounts / transformers / accessories of Type 1 and Type 2 devices. In one embodiment, a Type 1 or Type 2 device has a desktop design (rests on a surface with a power cord) or a plug-in design (built-in plug, with transformer). In one embodiment, there is an accessory (no power) that helps the desktop design be wall-mounted. There is no electrical connection to the Type 1 or Type 2 device. The accessory has a power-transformer, prongs, and a connector to the Type 1 or Type 2 device. In another embodiment, the Type 1 or Type 2 device has an integrated (or convertible) design so that it can be placed on a desktop and plugged into a wall outlet. It has retractable prongs, a built-in transformer, and a power cable socket (a power cable that connects to a wall power socket). In another embodiment, the Type 1 or Type 2 device has an interchangeable plug (with an international plug / pin configuration).

[0293] 15A and 15B illustrate an exemplary device 1500 having a power supply design according to some embodiments of the present disclosure. The device 1500 shown in FIGS. 15A and 15B corresponds to a desktop design of a Type 1 or Type 2 device. That is, the device 1500 may be either a bot or an origin. The device 1500 may be placed on a surface such as a desk and has an interface 1510 for connecting to a power cord for power supply.

[0294] 16A illustrates an example accessory 1601 for mounting a device to a wall surface, according to some embodiments of the present disclosure. FIG. 16B illustrates an example device 1600 coupled to the accessory 1601 shown in FIG. 16A, according to some embodiments of the present disclosure. In some embodiments, the device 1600 can correspond to a Type 1 or Type 2 device, i.e., a desktop design for a bot or origin. In some embodiments, the device 1600 corresponds to an intelligent virtual assistant (IVA) or intelligent personal assistant (IPA), such as a smart speaker, and includes a bot or origin.

[0295] The accessory 1601 in this embodiment can help the desktop design 1600 be wall-mounted. The accessory 1601 does not provide power and does not have a power interface. As such, the accessory 1601 has no electrical coupling to the device 1600. As shown in FIG. 16B, the device 1600 may be powered via a power cord 1610.

[0296] 17A illustrates an example accessory 1701 for attaching and connecting a device to a power outlet, according to some embodiments of the present disclosure. FIG. 17B illustrates an example device 1700 coupled to the accessory 1701 shown in FIG. 17A, according to some embodiments of the present disclosure. In some embodiments, the device 1700 can correspond to a Type 1 or Type 2 device, i.e., a desktop design for a bot or origin. In some embodiments, the device 1700 corresponds to an intelligent virtual assistant (IVA) or intelligent personal assistant (IPA), such as a smart speaker, and comprises a bot or origin.

[0297] Accessory 1701 in this embodiment has a functional portion 1702 and a frame portion 1703. Frame portion 1703 can fit over and hold a device (e.g., device 1700), while portion 1702 can include a power plug or prongs that plug into a power outlet for power, an internal power transformer, and / or a connector for electrically connecting the device to a power outlet to power the device.

[0298] 18A and 18B illustrate another exemplary device 1800 with a power supply design, according to some embodiments of the present disclosure. The device 1800 shown in FIGS. 18A and 18B corresponds to a plug-in design for a Type 1 or Type 2 device. That is, the device 1800 may be either a bot or an origin. The device 1800 can be plugged into an outlet, such as a wall outlet, via a power supply plug 1810. Additionally, as shown in FIG. 18B, the plug 1810 is foldable, allowing the device 1800 to be converted into a desktop design for resting on a surface. In some embodiments, the device 1800 includes both a built-in plug and a power transformer.

[0299] In some embodiments, a Type 1 or Type 2 device can have an integrated or convertible design so that it can sit on a surface and plug into a wall power outlet. It can have retractable prongs, a built-in power transformer, and an interface for a power cable to connect to a wall power socket. That is, a Type 1 or Type 2 device can be available as either a plug-in design or a desktop design.

[0300] 19 illustrates a scenario in which an integrated or convertible device 1800, according to some embodiments of the present disclosure, is utilized as a plug-in design. As shown in FIG. 19, when utilized as a plug-in design, prongs or pins 1810 of device 1800 are unfolded and extended into a socket on a wall 1900 to power device 1800. In this scenario, device 1800 does not need to have any cable accessories to form an origin or bot.

[0301] 20 illustrates a scenario in which an integrated or convertible device 1800 according to some embodiments of the present disclosure is utilized as a desktop design. As shown in FIG. 20, when utilized as a desktop design, the prongs or pins 1810 of the device 1800 are folded within the device 1800 and are not used. The device 1800 is sitting on a desk 2000 and is powered by cable accessories including, for example, an AC / DC adapter 1820 and a power cable 1830. In this scenario, the device 1800, together with the AC / DC adapter 1820 and the power cable 1830, forms an origin or bot.

[0302] In some embodiments, a mechanism can be configured to set one of the power inputs to have a higher priority to prevent both pin 1810 and power cable 1830 from being inserted into a power outlet. That way, when both pin 1810 and power cable 1830 are inserted or plugged in, the higher priority power input (e.g., pin 1810) can trigger a block, preventing the other power input (e.g., power cable 1830) from being electrically connected for double charging.

[0303] FIG. 21 illustrates an exemplary device 2100 with an interchangeable plug for power delivery, according to some embodiments of the present disclosure. The device 2100 shown in FIG. 21 corresponds to a plug-in design for a Type 1 or Type 2 device. That is, the device 2100 may be a bot or an origin. As shown in FIG. 21, the plug of the device 2100 may be modified to one of other plug / pin configurations 2110, 2120, 2130, 2140, 2150 to fit different sockets for power delivery.

[0304] 22 illustrates an exemplary block diagram of a first wireless device, e.g., a bot 2200, of a wireless monitoring system, according to one embodiment of the present disclosure. The bot 2200 is an example of a device that can be configured to implement various methods described herein. As shown in FIG. 22, the bot 2200 includes a housing 2240 that houses a processor 2202, a memory 2204, a transceiver 2210 including a transmitter 2212 and a receiver 2214, a synchronization controller 2206, a power module 2208, and an optional carrier component 2220 and a wireless signal generator 2222.

[0305] In this embodiment, processor 2202 controls the basic operations of bot 2200 and may include one or more processing circuits or modules, such as a central processing unit (CPU) and / or any combination of general-purpose microprocessors, microcontrollers, digital signal processors (DSPs), field programmable gate arrays (FPGAs), programmable logic devices (PLDs), controllers, state machines, gate logic, discrete hardware components, dedicated hardware finite state machines, or any other suitable circuits, devices and / or structures capable of performing arithmetic or other manipulation of data.

[0306] The memory 2204, which may include both read-only memory (ROM) and random access memory (RAM), can provide instructions and data to the processor 2202. A portion of the memory 2204 may also include non-volatile random access memory (NVRAM). The processor 2202 typically performs logical and arithmetic operations based on program instructions stored in the memory 2204. The instructions (also known as software) stored in the memory 2204 can be executed by the processor 2202 to perform the methods described herein. The processor 2202 and the memory 2204 together form a processing system that stores and executes software. As used herein, "software" refers to any type of instructions, whether referred to as software, firmware, middleware, microcode, or the like, that can configure a machine or device to perform one or more desired functions or processes. The instructions may include code (e.g., code in source code format, binary code format, executable code format, or any other suitable format). When executed by one or more processors, the instructions cause the processing system to perform various functions described herein.

[0307] The transceiver 2210, including the transmitter 2212 and the receiver 2214, enables the bot 2200 to transmit and receive data to and from a remote device (e.g., the origin or another bot). The antenna 2250 is typically mounted on the housing 2240 and electrically coupled to the transceiver 2210. In various embodiments, the bot 2200 includes multiple transmitters, multiple receivers, and multiple transceivers (not shown). In one embodiment, the antenna 2250 is replaced with a multi-antenna array 2250 capable of forming multiple beams, each pointing in a separate direction. The transmitter 2212 can be configured to wirelessly transmit signals having various types or functions, and such signals are generated by the processor 2202. Similarly, the receiver 2214 is configured to receive wireless signals having different types or functions, and the processor 2202 is configured to process multiple different types of signals.

[0308] In this embodiment, the bot 2200 can function as bot 1 110 or bot 2 120 in FIG. 1 to detect object movement within a location. For example, the wireless signal generator 2222 can generate and transmit a wireless signal via the transmitter 2212 through a wireless multipath channel affected by the movement of an object within the location. The wireless signal carries channel information. Because the channel was affected by the movement, the channel information includes motion information that can represent the movement of the object. In this manner, movement can be indicated and detected based on the wireless signal. The generation of the wireless signal by the wireless signal generator 2222 can be based on a request for motion detection from another device, such as an origin, or based on a pre-configuration of the system. That is, the bot 2200 may or may not know that the transmitted wireless signal will be used to detect movement.

[0309] The synchronization controller 2206 in this example may be configured to control the operation of the bot 2200 to be synchronized or asynchronous with another device, for example, an origin or another bot. In one embodiment, the synchronization controller 2206 may control the bot 2200 to synchronize with an origin that receives a wireless signal transmitted by the bot 2200. In another embodiment, the synchronization controller 2206 may control the bot 2200 to transmit a wireless signal asynchronously with the other bots. In another embodiment, the bot 2200 and each of the other bots may transmit a wireless signal individually and asynchronously.

[0310] The carrier configuration unit 2220 is an optional component in the bot 2200 for configuring transmission resources, e.g., time and carrier, for transmitting the wireless signal generated by the wireless signal generator 2222. In one embodiment, each CI in the time series of CIs has one or more components, each corresponding to a carrier or subcarrier for the transmission of the wireless signal. Motion detection can be based on motion detection with respect to any one or any combination of the components.

[0311] The power module 2208 can include a power source, such as one or more batteries, and a power regulator that provides controlled power to each of the above-mentioned modules of Figure 22. In some embodiments, if the bot 2200 is coupled to a dedicated external power source (e.g., a wall power outlet), the power module 2208 can include a transformer and a power regulator.

[0312] The various modules described above are coupled to one another by a bus system 2230. The bus system 2230 may include a data bus and, for example, a power bus, a control signal bus, and / or a status signal bus in addition to the data bus. It will be appreciated that the modules of the bot 2200 may be operably coupled to one another using any suitable technology and medium.

[0313] While a number of separate modules or components are shown in Figure 22, those skilled in the art will appreciate that one or more of the modules may be combined or commonly implemented. For example, processor 2202 may perform the functions described above with respect to processor 2202 as well as the functions described above with respect to wireless signal generator 2222. Conversely, each of the modules shown in Figure 22 may be implemented using multiple separate parts or elements.

[0314] FIG. 23 illustrates an exemplary block diagram of a second wireless device, e.g., origin 2300, of a wireless monitoring system, in accordance with one embodiment of the present disclosure. Origin 2300 is an example of a device that can be configured to implement various methods described herein. In this example, origin 2300 functions as origin 101 of FIG. 1 for detecting object motion within a location. As shown in FIG. 23 , origin 2300 includes a housing 2340 that houses a processor 2302, a memory 2304, a transceiver 2310 including a transmitter 2312 and a receiver 2314, a power module 2308, a synchronization controller 2306, a channel information extractor 2320, and optionally, a motion detector 2322.

[0315] In this embodiment, processor 2302, memory 2304, transceiver 2310, and power module 2308 operate similarly to processor 302, memory 304, transceiver 310, and power module 308 in bot 2200. Antenna 2350 or multi-antenna array 2350 is typically mounted in housing 2340 and electrically coupled to transceiver 2310.

[0316] The origin 2300 may be a second wireless device having a different type from the first wireless device (e.g., the bot 2200). Specifically, a channel information extractor 2320 in the origin 2300 is configured to receive a wireless signal through a wireless multipath channel affected by the movement of an object within a location and obtain a time series of channel information (CI) of the wireless multipath channel based on the wireless signal. The channel information extractor 2320 may send the extracted CI to an optional motion detector 2322, or a motion detector external to the origin 2300, for detecting the movement of an object within the location.

[0317] The motion detector 2322 is an optional element within the origin 2300. In one embodiment, it is within the origin 2300, as shown in FIG. 23 . In another embodiment, it is external to the origin 2300 and resides in another device, which may be a bot, another origin, a cloud server, a fog server, a local server, or an edge server. The optional motion detector 2322 can be configured to detect the movement of objects within a location based on motion information associated with the object's movement. The motion information associated with the first and second wireless devices is calculated based on the time series of CIs by the motion detector 2322 or another motion detector external to the origin 2300.

[0318] The synchronization controller 2306 in this example may be configured to control the operation of the origin 2300 to be synchronized or not synchronized with another device, such as a bot, another origin, or an independent motion detector. In one embodiment, the synchronization controller 2306 may control the origin 2300 to be synchronized with a bot transmitting a wireless signal. In another embodiment, the synchronization controller 2306 may control the origin 2300 to receive wireless signals asynchronously with other origins. In another embodiment, the origin 2300 and the other origins may each receive wireless signals separately and asynchronously. In one embodiment, the optional motion detector 2322, or a motion detector external to the origin 2300, is configured to asynchronously calculate respective heterogeneous motion information related to the object's motion based on respective time series of the CIs.

[0319] The various modules described above are coupled together by a bus system 2330. The bus system 2330 may include a data bus and, for example, a power bus, a control signal bus, and / or a status signal bus in addition to the data bus. It will be appreciated that the modules of origin 2300 may be operatively coupled to each other using any suitable technology and medium.

[0320] While a number of separate modules or components are shown in Figure 23, those skilled in the art will appreciate that one or more of the modules may be combined or commonly implemented. For example, processor 2302 may implement the functionality described above with respect to processor 2302 as well as the functionality described above with respect to channel information extractor 2320. Conversely, each of the modules shown in Figure 23 may be implemented using multiple separate parts or elements.

[0321] In one embodiment, in addition to the bot 2200 and the origin 2300, the system may also include a third wireless device (e.g., another bot) configured to transmit an additional, disparate wireless signal through an additional wireless multipath channel affected by the movement of objects within the location, and a fourth wireless device (e.g., another origin) having a different type from the third wireless device. The fourth wireless device may be configured to receive the additional, disparate wireless signal through the additional wireless multipath channel affected by the movement of objects within the location and to obtain a time series of additional channel information (CI) for the additional wireless multipath channel based on the additional disparate wireless signal. The additional CI for the additional wireless multipath channel may be associated with a different protocol or configuration than that associated with the CI for the wireless multipath channel. For example, the wireless multipath channel may be associated with LTE and the additional wireless multipath channel may be associated with Wi-Fi. In this case, optional motion detector 2322 or a motion detector external to origin 2300 is configured to detect motion of objects within the location based on both motion information associated with the first and second wireless devices and additional motion information associated with the third and fourth wireless devices calculated by the motion detector and at least one of the fourth wireless device based on a time series of additional CIs.

[0322] In some embodiments, the present disclosure discloses how to qualify a wireless system to achieve wireless sensing and how to distribute wireless sensing capabilities for IoT in a wireless mesh network (WMN).

[0323] An example of a wireless sensing system is one that utilizes WiFi channel state information (CSI), as WiFi is one of the most popular wireless technologies today. 802.11 sensing, or WiFi sensing, is the use of 802.11 signals to sense (e.g., detect) events / changes in the surroundings, which can be exploited using signal processing and machine learning.

[0324] In one embodiment, a wireless transmitter (Tx) transmits an 802.11 signal to a wireless receiver (Rx) within a multipath-rich venue. The 802.11 signal bounces back and forth within the venue, creating numerous multipaths. While undesirable for communication, the 802.11 signal bounces effectively "scan" or "sense" the venue. By monitoring the multipaths (e.g., via CSI), the disclosed system can detect target events and changes within the venue. The disclosed motion detection method does not require line-of-sight (LOS) between the transmitter and receiver and can function in both LOS and non-LOS (NLOS) situations. In most cases, the transmitter and receiver do not need to be wearable devices. This provides new functionality for 802.11-enabled devices (e.g., TVs, speakers, routers, IoT devices) and facilities (stadiums, halls, rooms, warehouses, factories) and opens new industry-wide business opportunities for all 802.11-related companies (parts / devices / services). The disclosed system does not require dedicated hardware.

[0325] Passive infrared (PIR) motion sensors only work in line-of-sight (LOS) scenarios and do not support machine learning. They require many PIR sensors (e.g., six) to cover an entire home. Video cameras based on motion sensing only work in line-of-sight scenarios and are memory- and computation-intensive. Video surveillance or recording violates human privacy. In contrast, 802.11 sensing can work in both line-of-sight and non-line-of-sight scenarios, requires only one transmitter and receiver pair to cover an entire home, can support machine learning, and has much lower memory and computation requirements than video cameras based on motion sensing. Furthermore, there is no privacy-violating video in 802.11 sensing.

[0326] 802.11 sensing can be applied to many scenarios, such as intruder detection, security, motion detection for smart IoT, sleep monitoring, health, respiratory monitoring for care, smart factory, indoor GPS companion, localization / tracking for traffic planning, elderly, accident detection, fall detection for care, smart car, child detection in hot cars to prevent accidents, conference room, convenience, presence / proximity detection for smart IoT, user identification, personalization, human identification for smart IoT, smart office, and gesture recognition for activity recognition for user interfaces. Many of these applications do not require wearable devices, can operate in contactless mode, and do not require video or line-of-sight requirements.

[0327] 802.11 sensing can create business opportunities for service providers, device manufacturers (e.g., manufacturers of smart home / IoT devices, consumer electronics, computing devices, home appliances, lighting, and accessories), and component providers. For example, the disclosed methods can enable smart device manufacturers to offer a new wave of "802.11 sensing" services, firmware, software, and / or devices in traditional modes (e.g., broadband, mobile, streaming, cable) or new modes (e.g., smart device manufacturers) related to daily life, safety, lifestyle, convenience, personalization, caregiving, digital health, and more.

[0328] Figure 24 shows exemplary performance of motion detection based on passive infrared (PIR) sensing and WiFi sensing, according to some embodiments of the present disclosure. In a test house covered by six professionally installed PIRs and 802.11 Tx / Rx pairs, 802.11 motion sensing performs better than PIR in a long-term side-by-side comparison. As shown in Figure 24, PIR sensing and 802.11 sensing have similar false alarm rates, but 802.11 sensing has a better detection rate than PIR sensing.

[0329] In a multi-night side-by-side comparison with other respiratory sensors (pressure sensors, radar sensors, and PSG as ground truth), 802.11 respiratory monitoring (non-contact) outperforms pressure sensors and radar sensors in terms of stage (awake / REM / NREM) detection speed and median (abs) error. 802.11 tracking (tracking based on 802.11 signals) demonstrated high tracking accuracy in walking experiments along paths within buildings, with mean (abs) tracking error of less than 20-30 cm in NLOS operation.

[0330] The bouncing of 802.11 signals creates multipaths that effectively scan or sense the environment, including any object motion, events, and changes. The multipaths can be captured in channel state information (CSI). In 802.11 sensing, various signal processing / machine learning algorithms and systems can be applied to acquire and analyze CSI to accomplish various tasks related to motion / events / changes, such as motion detection by detecting changes in CSI, breathing detection by detecting periodic behavior in CSI, and localization through CSI recognition. Standardization may be required for systems regarding CSI generation, timing, accuracy, consistency, protocols, etc. Interfaces may also be standardized. Some 802.11 sensing demos use periodic probing / CSI generation at 1 / 10 / 100 / 1000 Hz, with a sounding overhead of less than 0.1% of the available data bandwidth at 10 Hz. The protocol may be determined to control the consistency, accuracy, and format of the CSI, the generation of the CSI, the repetition rate, the accuracy of the timing, the antenna selection for 802.11 sensing, and probing.

[0331] Using standardized wireless sensing, devices from different manufacturers and different service providers can communicate with each other to estimate CSI for wireless sensing at a location based on a certification process as described herein. A database of certified devices is maintained to include devices that are already certified to estimate CSI and perform wireless sensing based on the CSI. Each certified device in the database has access to information related to other certified devices in the database.

[0332] In one example, when the wireless environment of a location becomes more complex, for example, due to more people entering the location, a qualification test may be performed on a new device in the location to add more qualified devices to improve wireless sensing accuracy. The requirement test may be performed based on qualification criteria associated with the new device and one or more CSI samples obtained using a qualified device in the database. For example, if the CSI obtained from wireless signals transmitted between the new device and a qualified device is good or sufficiently better than a predetermined threshold, the new device is determined to be qualified. In another example, the new device is determined to be qualified when two CSIs obtained from wireless signals transmitted at two different times between the new device and a qualified device are sufficiently close, for example, when a similarity score between the two CSIs is greater than a first threshold or a distance score between the two CSIs is less than a second threshold.

[0333] FIG. 25 shows a flowchart of an example method 2500 of a certified wireless sensing system according to some embodiments of the present disclosure. At operation 2502, a wireless signal is transmitted by a Type 1 device through a wireless multipath channel at a location. At operation 2504, the wireless signal is received by a Type 2 device. At operation 2506, a time series of channel information (CI) of the wireless multipath channel is obtained based on the wireless signal. At operation 2508, a certification test is performed based on the TSCI for a device to be certified that is associated with the Type 1 or Type 2 device. At operation 2510, when the certification criteria are met, the device to be certified is determined to be a certified device. At operation 2512, a task is performed based on the TSCI using the certified device. The device to be certified may be a previously or currently certified device that requires recertification. For example, a certified device may be recertified (1) after a power-off cycle, or (2) after any wireless network disruption / failure / traffic condition / jam occurs, or (3) after an Internet disruption / failure / traffic condition / jam occurs, or (4) upon receiving a request / command / control from a device (such as some Type 1 devices, some Type 2 devices, some devices at a location, some servers, or some user devices), or (5) periodically, regularly, sporadically, irregularly, requesting, or in any condition, or (6) upon a task change (e.g., task start, task end, new task, multiple simultaneous tasks, task modification, arbitrary event, time event, scheduled event, planned event, timeout). Multiple devices to be given certification may be certified simultaneously, simultaneously, independently, dependently, cooperatively, individually, or jointly.

[0334] At operation 2514, the device to be certified is registered as a certified device for the task associated with the test or standard. At operation 2516, a database of certified devices is updated with the certified device, location, or task. At operation 2518, additional TSCI is obtained through signaling between the certified device and additional certified devices. At operation 2520, the signaling is configured according to a protocol, standard, or signaling requirement. At operation 2522, a query by the additional certified device is used to obtain information about the certified device from the database. At operation 2524, another task is performed based on the additional TSCI using the certified device or the additional certified device. The order of the operations in FIG. 25 may be changed in various embodiments of the disclosure.

[0335] If the CSI meets the criteria, the device may be "certified." A certified wireless system may be a standard-compliant wireless system or a system that operates in a manner defined by a standard. For example, a Type 2 device is certified (e.g., compliant with a standard or meets the requirements of a standard such as WiFi, 4G / 5G / 6G / 7G / 8G) if the first CI and second CI are "close" to each other when there is no change in location (e.g., no object movement). A Type 1 device may be a transmitter (Tx, or "bot"). A Type 2 device may be a receiver (Rx, or "origin"). A Type 1 device may be a Type 2 device, or vice versa.

[0336] The following numbered sections provide examples for configuring a wireless monitoring system by selecting and / or setting a system state from several allowable system states.

[0337] Item 1. A method of configuring a wireless monitoring system, comprising: transmitting a wireless signal from a type 1 disparate wireless device through a wireless multipath channel at a location; receiving a wireless signal from a type 2 disparate wireless device through the wireless multipath channel, the received wireless signal differing from the transmitted wireless signal due to the wireless multipath channel at the location and modulation of the wireless signal by an object moving within the location; using a processor, memory, and a set of instructions, obtaining a set of channel information (CI) for the wireless multipath channel based on the received wireless signal; performing a monitoring task by monitoring the object and its movement based on the set of CI; and determining several allowable system states of the wireless monitoring system, wherein each allowable system state is determined based on the wireless signal, signaling within the wireless signal, a sequence of sounding signals within the wireless signal, timing of the sounding signals within the wireless signal, sounding of the sounding signals, and the like. determining a setting associated with at least one of a receiving frequency of the wireless signal, a frame type of the wireless signal, a field of a frame type of the wireless signal, generation of the wireless signal by the Type 1 device, transmission of the wireless signal by the Type 1 device, reception of the wireless signal by the Type 2 device, processing of the wireless signal by the Type 2 device, coordination of the Type 1 device and the Type 2 device with respect to the transmission of the wireless signal, coordination with other devices with respect to the transmission of the wireless signal, the set of CIs, obtaining the set of CIs for the wireless multipath channel based on the received wireless signal, the monitoring task for the object, customizing the monitoring task, operation of the monitoring task, and operation for monitoring the object based on the CI; selecting a system state to be one of the allowable system states based on the monitoring task; and configuring the wireless monitoring system by applying the setting associated with the selected allowable system state to the wireless monitoring system.

[0338] Clause 2. A method of configuring a wireless monitoring system as recited in clause 1, further comprising automatically selecting the system state, the selected acceptable system state, based on at least one of negotiation, handshake, coordination between at least two of a Type 1 device, a Type 2 device, a server, another Type 1 device, or another Type 2 device, at least one of monitoring task constraints, requirements, and conditions, at least one of commands, requirements, coordination, and server plans, test procedures, or optimization criteria.

[0339] Clause 3. A method of configuring a wireless monitoring system as recited in clause 1, further comprising: performing a test procedure associated with a monitoring task; transmitting a test wireless signal from a test type 1 disparate wireless device through a test wireless multipath channel at a test location; receiving the test wireless signal at a test type 2 disparate wireless device through the test wireless multipath channel, the received test wireless signal differing from the transmitted test wireless signal due to the test wireless multipath channel at the test location and a modulation of the test wireless signal by a test object performing a test movement at the test location; obtaining, using a test processor, a test memory, and a set of testing instructions, test channel information (CI) for the test wireless multipath channel based on the received test wireless signal; performing a test procedure by monitoring the test object and the test movement of the test object based on the set of test CIs; and automatically selecting a system state to be a selected allowable system state based on the test procedure.

[0340] Clause 4. A method of configuring a wireless monitoring system as described in clause 3, wherein the test Type 1 devices include at least one of the Type 1 device, another Type 1 device, the Type 2 device, another Type 2 device, and another wireless device; the test Type 2 devices include at least one of the Type 1 device, another Type 1 device, the Type 2 device, another Type 2 device, and another Type 2 device; and the test location includes the location, the location under a test condition, the location under at least one candidate operating condition, the location under at least one candidate manifestation, and at least one candidate manifestation. a location including at least one of the locations in a representation of at least one target to be monitored in a monitoring task, the location not including an object, the location having at least one of the object or a test object similar to the object, the location having the object or test object in a representation of at least one target to be monitored in a monitoring task, and the location having the object or test object performing the movement of at least one target to be monitored in the monitoring task, and further comprising: placing a test Type 1 device at at least one candidate position within the test location, one of the candidate positions being the position of the Type 1 device; placing a test Type 2 device at at least one candidate position within the test location, one of the candidate positions being the position of the Type 1 device; placing the test Type 1 device in at least one candidate direction within the test location, one of the candidate directions being a direction of the Type 1 device; and placing the test Type 2 device in at least one candidate direction within the test location, one of the candidate directions being a direction of the Type 2 device.

[0341] Clause 5. A method of configuring a wireless monitoring system according to clause 3, wherein the test objects include the object, the object performing the movement, the object performing at least one target movement to be monitored in a monitoring task, a test object similar to the object, a test object with a similar radio footprint to the object, a test object having a similar radio signature to the object, a test object having a similar radio signature for CI to the object, a test object having a similar CI to the object, a test object having a similar physical appearance to the object, a test object having a similar physical structure to the object, a test object having similar moving parts to the object, a test object capable of performing a movement similar to the object, a test object performing the movement, and a test object to be monitored in a monitoring task. a test object performing at least one target movement corresponding to the movement of the object, the test movement further comprising at least one of the movement of the object, a test movement similar to the movement of the object, a portion of the movement of the object, a partial test movement similar to the portion of the movement of the object, the movement of a portion of the object, a partial test movement similar to the movement of the portion of the object, the movement of a moving part of the object, a test movement of at least one moving part similar to the movement of a corresponding moving part of the object, a portion of the movement of a moving part of the object, a partial test movement similar to the portion of the movement of a corresponding moving part, the movement of a moving part of a portion of the object, a test movement of at least one moving part similar to the movement of a corresponding moving part of the object, and a target movement monitored in a monitoring task.

[0342] Clause 6. A method of configuring a wireless monitoring system as recited in clause 3, wherein the test wireless signals further include at least one candidate wireless signal, one of the candidate wireless signals being the wireless signal, each candidate wireless signal being associated with at least one of: at least one transmit antenna, at least one receive antenna, carrier frequency, modulation, signal constellation, signal bandwidth, frequency band, frequency aggregation, frequency hopping, signaling, signal format, protocol, standard, sequence of sounding signals, sounding signal selection, sounding frequency, sounding rate, sounding duration, sounding timing, sounding timing regularity, management frame, control frame, data frame, management package, control packet, data packet, frame control field, field of frame, frame header, frame body.

[0343] Clause 7. The method of configuring a wireless monitoring system of clause 3, further comprising automatically selecting the system state to be the selected acceptable system state based on an optimization criterion associated with the test procedure and monitoring of the test object based on the set of incident CIs.

[0344] Clause 8. A method of configuring a wireless monitoring system as recited in clause 1, wherein the wireless signals include a set of sounding signals based on a protocol, and wherein each allowable system state and its associated configuration relates to at least one of timing, progression, speed, sounding rate, sounding cadence, signal strength, signal modulation, carrier frequency, frequency band, frequency bandwidth, frequency hopping, transmit antennas, receive antennas, sounding signal selection, CI selection, monitoring functionality, functionality level, and functional parameters of at least one of: Type 1 devices, Type 2 devices, coordination of Type 1 and Type 2 devices, set of sounding signals, set of CIs, and said monitoring of said object.

[0345] Clause 9. A method of configuring a wireless monitoring system as described in clause 1, applying a configuration by configuring at least one of the Type 1 device, the Type 2 device, the other device, an integrated circuit (IC) in the Type 1 device, an IC in the Type 2 device, an IC in the other device, coordination between the Type 1 device and either the Type 2 device or the other device, a wireless signal, signaling in a wireless signal, a sounding signal in a wireless signal, timing or sounding frequency of a sounding signal, the transmission, the reception, the generation or the processing of the wireless signal based on the system state, the set of CIs, the acquisition of a set of CIs, and the monitoring of the object.

[0346] Clause 10. The method of configuring a wireless monitoring system of clause 9, further comprising indirectly configuring the Type 1 device by configuring the Type 2 device.

[0347] Clause 11. A method of configuring the wireless monitoring system of clause 10, wherein the wireless signals include a series of sounding signals in response to a series of trigger wireless signals from the Type 2 device based on a protocol, each sounding signal being a trigger response to a trigger signal from the Type 2 device based on a protocol, and wherein configuring the series of trigger signals to be transmitted by the Type 2 device indirectly configures transmission of at least one of a trigger response, a series of sounding signals, and a series of sounding signals from the Type 1 device.

[0348] Clause 12. The method of the wireless monitoring system of clause 11, wherein at least one of the timing, progression, rate, sounding rate, sounding cadence, signal strength, signal modulation, carrier frequency, frequency band, frequency bandwidth, frequency hopping, antenna and sounding signal selection of the series of sounding signals of the Type 1 device is indirectly configured by configuring at least one of the timing, sounding rate, sounding cadence, signal strength, signal modulation, carrier frequency, frequency band, frequency bandwidth, frequency hopping, antenna and sounding signal selection of the series of trigger signals transmitted by the Type 2 device.

[0349] Item 13. How to configure the wireless monitoring system of Item 9, indirectly configuring a Type 2 device by configuring a Type 1 device:

[0350] Clause 14. A method of configuring the wireless monitoring system of clause 13, wherein the wireless signals include a series of sounding signals, and indirectly configuring the Type 2 device, the extraction of the set of CIs from the received wireless signals, and at least one of the set of CIs, by configuring at least one of the timing, sounding rate, sounding cadence, signal strength, signal modulation, carrier frequency, frequency band, frequency bandwidth, frequency hopping, antenna, and sounding signal selection of the Type 1 device.

[0351] Clause 15. A method of configuring a wireless monitoring system as recited in clause 1, further comprising at least one of changing the system state to another of the allowable system states or updating a setting associated with a particular allowable system state based on a change in at least one of the Type 1 device, the Type 2 device, the wireless signal, the signaling, the sounding signal, the timing, the sounding frequency, the frame type, the fields, the generating, the transmitting, the receiving, the processing, the adjusting, the set of CIs, the obtaining, the customizing, the computing, the wireless multipath channel, and the location.

[0352] Item 16. A method of configuring a wireless monitoring system according to item 15, comprising: a finite state machine (FSM), a trigger for a state transition of the FSM, a criterion, an event, a condition, a schedule, a request, a requirement, an optimization, a goal, an operation, a discovery, a sensor reading, a state change, a trigger from another device, a timeout, a timing, monitoring functionality, a functionality requirement, a computational requirement, a memory requirement, a sounding requirement, a function setting, a sensitivity setting, a resolution setting, a detection, a recognition, monitoring, a monitoring condition, a monitoring state, a monitoring situation, a monitoring amount, a shared resource, a shared resource constraint, a resource management, a network congestion of the wireless multipath channel, an interference of the wireless multipath channel, another sensor, another sensor of the type 1 device, another sensor of the type 2 device, a power management, a thermal management, a computational management, a memory management, a power-on, a power-off, a power efficiency consideration, a thermal consideration. , network considerations, wireless multipath channel traffic considerations, usage considerations, user considerations, power saving, heat reduction, traffic congestion, traffic optimization, a new state of the monitoring task, a new stage of the monitoring task, a change in the monitoring task, a change in the object, an appearance of the object, a disappearance of the object, a change in the object's movement, a change in the location, a change in the wireless multipath channel, a change in the Type 1 device, a change in the Type 2 device, a status of the location, a status of the wireless multipath channel, a status of the Type 1 device, a status of the Type 2 device, a new movement of the object being monitored, a new monitoring task, or a new object being monitored.

[0353] Clause 17. A method of configuring a wireless monitoring system as described in clause 15, wherein the wireless signals include a series of protocol-based sounding signals, a sounding rate associated with the series of sounding signals, the method further comprising: changing the system state to a first state associated with a normal sounding rate associated with a monitoring task; when the monitoring task becomes required, changing the system state to a second state associated with a sounding rate higher than the normal rate; and changing the system state to a third state associated with a sounding rate lower than the normal rate to conserve power.

[0354] Clause 18. A method of configuring a wireless monitoring system as described in clause 15, further comprising: executing a first set of at least one monitoring task, where executing any monitoring task includes monitoring each object and corresponding movement of each of the objects based on the set of CIs; selecting the system state to a first state based on the first set of monitoring tasks; executing a second set of at least one monitoring task rather than the first set of monitoring tasks; and changing the system state from the first state to a second state based on the second set of monitoring tasks.

[0355] Clause 19. The method of configuring a wireless monitoring system of clause 18, wherein there are two or more monitoring tasks, including a default task and at least one on-demand task, and further comprising selecting the system state to a first state associated with a first setting associated with a default monitoring task, changing the system state to a second state associated with a second setting associated with an on-demand task, and changing the system state back to the first state after the on-demand task.

[0356] Item 20. A method of configuring a wireless monitoring system, comprising: transmitting a wireless signal from a Type 1 disparate wireless device through a wireless multipath channel of a location; receiving the wireless signal through the wireless multipath channel by a Type 2 disparate wireless device, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless multipath channel of the location and modulation of the wireless signal by an object moving within the location; using a processor, memory, and a set of instructions, obtaining a set of channel information (CI) for the wireless multipath channel based on the received wireless signal; and performing a monitoring task by monitoring the object and the movement of the object based on the set of CI; and configuring the wireless monitoring system, each permissible system state associated with a respective configuration. determining several acceptable system states; automatically selecting a system state to be one of the acceptable system states based on the monitoring task; and applying the settings associated with the selected acceptable system state to at least one of the Type 1 device, the Type 2 device, another Type 1 device, another Type 2 device, a server, a user device, an integrated circuit (IC) of a device, coordination between at least two devices, the wireless signal, signaling in the wireless signal, a series of sounding signals within the wireless signal, timing or sounding frequency of the sounding signal, the transmission, receiving, generating or processing the wireless signal based on the system state, the set of CIs, obtaining the set of CIs, and the monitoring of the object.

[0357] Clause 21. A method of configuring a wireless monitoring system according to clause 20, wherein the system state is automatically selected to be the selected acceptable system state based on at least one of negotiation, handshake, coordination between at least two of the Type 1 device, the Type 2 device, a server, other Type 1 devices, or other Type 2 devices, at least one of the monitoring task constraints, requirements and states, at least one of commands, requirements, coordination and server plans, test procedures, or optimization criteria.

[0358] Clause 22. A method of configuring a wireless monitoring system as described in clause 20, comprising: executing a test procedure associated with a monitoring task; transmitting a test wireless signal from a test type 1 disparate wireless device over a test wireless multipath channel of a test location; receiving the test wireless signal at a test type 2 disparate wireless device over the test wireless multipath channel, the received test wireless signal differing from the transmitted test wireless signal by the test wireless multipath channel of the test location and a modulation of the test wireless signal by a test object performing a test movement at the test location; obtaining, using a test processor, a test memory, and a set of test instructions, a set of test channel information (CI) for the test wireless multipath channel based on the received test wireless signal; performing the test procedure by monitoring the test object and its test movement based on the set of test CIs; and selecting the system state to be the selected allowable system state automatically based on the test procedure and an associated optimization criterion.

[0359] Clause 23. A method of configuring a wireless monitoring system as defined in clause 20, wherein the wireless signals include a series of protocol-based sounding signals, and a sounding rate associated with the series of sounding signals, the method comprising at least one of changing the system state to a first state associated with a normal sounding rate associated with...

Claims

1. a first wireless device of a wireless monitoring system, a receiver configured to receive at least one wireless signal over a wireless multipath channel at a location, the receiver comprising: the location includes a vehicle and the immediate vicinity of the vehicle; a receiver for receiving any received radio signals based on a respective transmitted radio signal transmitted by a second wireless device of the wireless monitoring system; a processor communicatively coupled to the receiver; a memory communicatively coupled to the processor; A set of instructions stored in the memory that, when executed by the processor, causes the processor to, after the vehicle is turned off: obtaining a first time series of channel information (TSCI) of the wireless multipath channel based on a first received wireless signal received after the vehicle is turned off; performing a first monitoring task of detecting the presence of the child in the vehicle by detecting a child's movement or the child's breathing based on the first TSCI, the first monitoring task comprising at least: calculating a motion analysis based on the first TSCI; detecting the motion when the motion analysis exceeds a first threshold; calculating a breath analysis based on the first TSCI; detecting the child's breathing when the breath analysis exceeds a second threshold; performing the first monitoring task by detecting the presence of the child when the movement analysis exceeds the first threshold or the respiration analysis exceeds the second threshold; communicating a first alert notification to a user when the child is detected; stopping the first monitoring task while the vehicle is off and entering a low power consumption mode; waking up from the low power mode while the vehicle is off, triggered by abnormal movement of the vehicle; acquiring a second TSCI of the wireless multipath channel based on a second received wireless signal after startup; performing a second monitoring task for detecting a security event by detecting an interruption event based on the second TSCI while the vehicle is off, the second monitoring task comprising at least: calculating a change analysis based on the second TSCI; detecting the interrupt event when the change analysis exceeds a third threshold, thereby performing the second monitoring task; communicating a second alert notification to the user when the interruption event is detected; a set of instructions that cause the second monitoring task to stop while the vehicle is off and enter the low power mode; a first wireless device including:

2. 10. The first wireless device of claim 1, The set of instructions, when executed by the processor, cause the processor to further monitor at least one of an interior space, an exterior space, or a structure of the vehicle based on the TSCI; the interior space includes at least one of a passenger compartment, a trunk, a hood, a storage space, a compartment, a trailer, a container, a cargo hold, a gas tank, a fuel tank, or an oil bag; the exterior space includes at least one of a garage, a parking facility where a vehicle stops and parks, or an area around the vehicle where other vehicles can approach, stop, and park; The first wireless device, wherein the structure includes at least one of a chassis, a body, a light, a window, a door, a tailgate, a bumper, a wheel, or an engine of a vehicle.

3. 3. The first wireless device of claim 2, wherein the set of instructions, when executed by the processor, causes the processor to: The first wireless device further performs at least one of presence detection, child presence detection, pet presence detection, detection of children left behind by parents after the car engine is turned off, motion detection, window breakage detection, vibration detection, foreign object detection, breath detection, heart rate detection, driver recognition, driver attention monitoring, driver alertness monitoring, driver drowsiness detection, vehicle customization based on driver recognition, passenger recognition, passenger location, passenger number counting, security monitoring, intrusion detection, intruder detection, intruder presence detection, detection of outsiders reaching the vehicle interior through an opening, exterior monitoring, pedestrian detection, cyclist detection, blind spot monitoring, or proximity detection.

4. 4. The first wireless device of claim 3, wherein the set of instructions, when executed by the processor, further causes the processor to: calculating at least one spatio-temporal information (STI) of at least one of the vehicle, the object, or the movement of the object based on the TSCI; and monitoring the vehicle, the object, or the movement of the object based on the at least one STI, wherein the STI includes at least one of presence, count, motion intensity, distance, speed, acceleration, angle, motion statistics, motion localization, motion classification, gesture, action, motion trend, head movement, motion rhythm, motion period, repetition period, period frequency, breathing statistics, heart rate statistics, breathing rate, heart rate, blink, driver event, passenger event, entrance event, exit event, window event, door event, driver drowsiness event, driver distraction event, fall event, security event, accidental event, physical state, health state, or mental state.

5. 5. The first wireless device of claim 4, wherein the set of instructions, when executed by the processor, further causes the processor to: calculating an analysis based on the at least one STI; monitoring the vehicle, the object, or the movement of the object based on the analysis; and computing the analysis further comprising: treating the at least one shallow trench isolation; analyzing the at least one shallow trench isolation; thresholding the at least one STI based on a threshold value; classifying the at least one STI based on at least one of a classifier or a neural network using input including the at least one STI; or calculating at least one of a degree of movement, a change, an indication, an occurrence of an event, a security event, an identification, a trend, a sleep state, a driver's alertness, a driver's state, a gesture, a duration, a count, a location, an irregularity, a deviation, or an alert based on the at least one STI.

6. 5. The first wireless device of claim 4, wherein calculating the at least one STI comprises: Calculating a time series of the TSCI features; and calculating a time series threshold indicator (STI) based on the time series of TSCI features, each feature comprising: the first wireless device comprising at least one of a scalar, a vector, a matrix, a magnitude of a CI, a phase of a CI, a magnitude squared of a CI, a function of a sliding window of a CI, a component of a CI, a correlation, an autocorrelation, an autocorrelation function (ACF), a correlation between two windows of a CI aligned using dynamic time warping (DTW), a local maximum, a local minimum, a zero crossing, a dot product, a time-reversed resonance strength (TRRS), a distance score, a Euclidean distance, an absolute distance, a moving average, a weighted average, a variance, a fluctuation, a derivative, a variability, a deviation, a divergence, an entropy, a fluctuation measure, a regularity measure, a similarity measure, a similarity score, a transform, a frequency spectrum, a spectral feature, a spectral analysis, an inverse transform, a frequency transform, zero padding, a repetition, a periodicity, a spurt, a suddenness, a repetition, a frequency, a rate, a period, a timing, a duration, a variation, a feature extraction, a decomposition, a dimensionality reduction, a projection, an eigenvalue decomposition, or a principal component analysis (PCA).

7. 2. The first wireless device of claim 1, wherein the TSCI comprises: The first wireless device is preprocessed based on at least one of filtering, interpolation, decimation, resampling, time correction, noise removal, smoothing, signal conditioning, phase correction, magnitude correction, phase cleaning, magnitude cleaning, enhancement, spectral analysis, inverse transform, or frequency transform.

8. 2. The first wireless device of claim 1, wherein the set of instructions, when executed by the processor, further causes the processor to: generating a response based on the TSCI-based radio monitoring, the response comprising: The first wireless device includes at least one of warning, presentation, driver alertness measurement, audiovisual control, audio volume control, playing upbeat music, playing warning messages, driver interaction, fresh air control, temperature control, window control, climate control, lighting control, seat customization, mirror control, speed control, acceleration, deceleration, accident avoidance, or emergency stop.

9. 2. The first wireless device of claim 1, wherein the set of instructions, when executed by the processor, further causes the processor to: pre-processing the TSCI; Computing a time series of features of the TSCI, each feature being a feature of a first sliding time window of the pre-processed TSCI; calculating a time series of STIs based on the time series of features, each STI corresponding to a second sliding time window of the time series of features; calculating a time series of analyses based on the time series of STIs, each analysis corresponding to a third sliding time window of the time series of STIs; monitoring at least one of the vehicle, object, or the movement of the object based on at least one of the feature time series, the STI time series, or the analysis time series; generating a response based on the monitoring.

10. 3. The first wireless device of claim 2, wherein the set of instructions, when executed by the processor, further causes the processor to perform security monitoring of the vehicle based on the TSCI, the security monitoring comprising: Detecting suspicious activity in the external space, detecting a person approaching the vehicle, detecting a person in the external space looking into the vehicle through a window, detecting a person in the external space damaging the vehicle, detecting a person in the external space forcibly opening a door or window of the vehicle; Detecting suspicious activity in the interior space, detecting outsiders reaching the interior of the vehicle through windows, intrusion detection, intruder tracking, detecting the presence of children in the back seat, detecting the presence of pets, The first wireless device includes at least one of: detecting a window being broken while parking; detecting a door being opened while parking; detecting a hit and run while parking; detecting a collision; or detecting structural damage.

11. 3. The first wireless device of claim 2, wherein the set of instructions, when executed by the processor, further causes the processor to monitor a driver and passengers of the vehicle based on the TSCI, wherein monitoring the driver and passengers includes: Driver monitoring, driver presence detection, driver identification, driver activity monitoring, driver vital signs monitoring, driver respiration monitoring, driver heart rate monitoring, driver alertness monitoring, driver distraction detection, driver entering the vehicle, driver exiting the vehicle, Passenger monitoring, passenger presence detection, infant detection, child detection, pet detection, passenger location, passenger counting, passenger recognition, passenger activity monitoring, passenger respiration monitoring, passenger heart rate monitoring, passenger vital signs monitoring, passenger sleep detection, passenger entering the vehicle, passenger exiting the vehicle, or monitoring driver and passenger interactions.

12. 2. The first wireless device of claim 1, wherein the set of instructions, when executed by the processor, causes the processor to: suspending at least one of the first monitoring task and the second monitoring task when a low activity state is determined in at least one of the first monitoring task and the second monitoring task; Entering low power mode; waking up from said low power mode triggered by a signal; resuming the at least one of the first monitoring task and the second monitoring task; if the low activity state is again determined in the at least one of the first monitoring task and the second monitoring task, again pausing the at least one of the first monitoring task and the second monitoring task; and re-entering the low power mode.

13. 10. The first wireless device of claim 1, The set of instructions, when executed by the processor, causes the processor to: Associating an event of the vehicle with a characteristic of the TSCI, the event including at least one of a safety monitoring event, a security monitoring event, a vehicle structural integrity monitoring event, a driver monitoring event, a passenger monitoring event, or an intruder monitoring event; and detecting the event in the vehicle by recognizing the feature of the TSCI, the event being: the first wireless device including at least one of an open window, a closed window, a broken window, an open door, a closed door, an unlocked door, a deformed door, an unauthorized door opening, a driver presence, a driver movement, a driver drowsiness, a distracted driver, a passenger presence, a passenger movement, an intruder presence, an intruder movement, a collision, a vehicle obstruction, an infant left in a vehicle, a child left in a vehicle, a pet left in a vehicle, a person walking by, a person peering through a window of the vehicle, another vehicle too close, breathing detected in the vehicle, or movement detected in the vehicle.

14. 10. The first wireless device of claim 9, wherein the set of instructions, when executed by the processor, causes the processor to: Associating an event of the vehicle with at least one feature of the TSCI, the feature time series, the STI time series, or the analysis time series, wherein the event comprises at least one of a safety event, a security event, a vehicle structural integrity event, a driver event, a passenger event, or an intruder event; Detecting the event in the vehicle by recognizing the feature of the TSCI; training a model of the event based on at least one of a training TSCI of a training wireless multipath channel at a training location, a time series of training features calculated based on the training TSCI, a time series of training STIs calculated based on the training features, or a time series of training analyses calculated based on the training STIs; the training TSCI is obtained from a training wireless signal transmitted from a training wireless device within the training location to another training wireless device within the training location during a training period; The first wireless device, wherein the event is detected based on the model and at least one of the TSCI, the feature time series, the STI time series, or the analysis time series.

15. 2. The first wireless device of claim 1, wherein the set of instructions, when executed by the processor, causes the first monitoring task and the second monitoring task to start, stop, or pause at least one subtask of the first monitoring task and the second monitoring task. Arming or disarming said wireless monitoring system; the parked or unparked status of said vehicle; the stopped or moving status of said vehicle; turning the vehicle's engine on or off; turning the vehicle's headlights on or off; a brake release or brake depression by the driver of the vehicle; opening or closing at least one of a driver's door, a passenger's door, a vehicle trunk door, a window, a vehicle hood cover, a cargo door, a trailer door, a container door, a storage space door, or a fuel tank cover; the driver's entry and exit in relation to the opening and closing of the driver's door; Passengers entering and exiting the vehicle by opening and closing the passenger door, The driver's smartphone entry and exit, The passenger's smartphone entry and exit, Whether there are paired devices, Pairing or unpairing a previously paired device; interaction with parts of the vehicle; a lack of movement within the vehicle for a period of time; or and a presence of motion within the vehicle for a period of time.

16. 2. The first wireless device of claim 1, wherein at least one of the first wireless device or the second wireless device is physically attached to or supported by the vehicle based on at least one of a USB port, a cigarette lighter port, an OBD port, an Ethernet point, a network point, or a mounting portion of the first or second wireless device; the first wireless device and the second wireless device are at different locations within the vehicle; At least one of the first wireless device or the second wireless device is factory-installed or integrated into a vehicle subsystem of the vehicle.

17. 10. The first wireless device of claim 1, wherein at least one of the first wireless device or the second wireless device is communicatively coupled to or powered by the vehicle based on at least one of a USB port, a cigarette lighter port, an OBD port, an Ethernet point, a network point, a vehicle network, a vehicle WiFi system, a vehicle Bluetooth system, a vehicle BLE system, a vehicle Zigbee system, a vehicle communication system, an in-vehicle electronic subsystem, hardwiring, or a mounting point for the first or second wireless device; The first wireless device and the second wireless device are in the same location within the vehicle.

18. 10. The first wireless device of claim 1, wherein the receiver is further configured to receive additional wireless signals via additional wireless multipath channels at the location; the additional wireless signal is received based on an additional transmitted wireless signal transmitted by an additional wireless device of the wireless monitoring system; the additional wireless signal differs from the additional transmitted wireless signal due to the additional multipath channel and modulation due to the movement of objects at the location; The set of instructions, when executed by the processor, causes the processor to: obtaining an additional TSCI of the additional wireless multipath channel based on the additional wireless signal; independently performing at least one of the first monitoring task and the second monitoring task by monitoring at least one of the vehicle, the object, or the movement of the object based on the additional TSCI; and jointly performing at least one of the first monitoring task and the second monitoring task by monitoring at least one of the vehicle, the object, or the movement of the object based jointly on the TSCI and the additional TSCI.

19. 10. The first wireless device of claim 1, wherein an additional wireless device in the location is: receiving a second wireless signal over the wireless multipath channel at the location, the second wireless signal being received based on the transmitted wireless signal and different from the transmitted wireless signal due to different modulations caused by the wireless multipath channel and the motion of objects within the location; obtaining additional TSCI of the wireless multipath channel based on the second wireless signal; independently performing at least one of the first monitoring task and the second monitoring task by monitoring at least one of the vehicle, the object, or the movement of the object based on the additional TSCI; The at least one of the first monitoring task and the second monitoring task is jointly performed by monitoring at least one of the vehicle, the object, or the movement of the object based jointly on the TSCI and the additional TSCI.

20. 1. A method of a wireless monitoring system over a wireless multipath channel of a location, the location including a vehicle and a vicinity of the vehicle, the method comprising, after the vehicle is turned off, transmitting a separate wireless signal from a first wireless device within the location over the wireless multipath channel of the location; receiving at least one wireless signal by a second wireless device within the location via the wireless multipath channel; obtaining, using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory, a first time series of channel information (TSCI) for the wireless multipath channel based on the at least one wireless signal; performing a first monitoring task of detecting the presence of the child in the vehicle by detecting a child's movement or the child's breathing based on the first TSCI, the first monitoring task comprising at least: calculating a motion analysis based on the first TSCI; detecting the motion when the motion analysis exceeds a first threshold; calculating a breath analysis based on the first TSCI; detecting the child's breathing when the breath analysis exceeds a second threshold; performing the first monitoring task by detecting the presence of the child when the movement analysis exceeds the first threshold or the respiration analysis exceeds the second threshold; communicating a first alert notification to a user when the child is detected; stopping the first monitoring task while the vehicle is off and entering a low power consumption mode; waking up from the low power mode while the vehicle is off, triggered by abnormal movement of the vehicle; acquiring a second TSCI of the wireless multipath channel based on a second received wireless signal after startup; performing a second monitoring task for detecting a security event by detecting an intrusion event based on the second TSCI while the vehicle is off, the second monitoring task comprising at least: calculating a change analysis based on the second TSCI; detecting the intrusion event when the modification analysis exceeds a third threshold, thereby performing the second monitoring task; communicating a second alert notification to the user when the intrusion event is detected; stopping the second monitoring task while the vehicle is off and entering the low power mode.

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