Adaptive beacon operation for tracking tags used in a tracking system

Abstract

a tracking tag of a tracking system (100) configured to: receive, by one or more processors (130) of the tracking tag (102, 104), a first measurement collected by one or more sensors (134) of the tracking tag (102, 104); determine, by the one or more processors (130), a degree of similarity between the first measurement and a critical value; compare, by the one or more processors (130), the degree of similarity between the first measurement and the critical value to a first threshold; modify, by the one or more processors (130), an initial time interval based on a comparison of the degree of similarity between the first measurement and the critical value to the first threshold to determine a modified time interval; and transmit, by the one or more processors (130), one or more beacon signals according to the modified time interval.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of the filing date and priority of U.S. patent application Ser. No. 17 / 988,865, filed November 17, 2022, the disclosure of which is incorporated herein by reference in its entirety. [Background technology]

[0002] background The Internet of Things (IoT) is the network interconnection of physical objects, such as products, packaging, vehicles, buildings, and the like, that have embedded electronic components for network connectivity. The embedded components enable the objects to detect others, be detected by others, collect data, and / or transmit data. In some examples, the embedded components may include tracking tags or labels attached to the physical objects. These tracking tags or labels may be passive or active. Network interconnectivity capabilities can be leveraged to track location, movement, temperature, or other information pertaining to physical objects. In many situations, this information is transmitted at periodic intervals, which requires the calculation of a payload containing this information before each transmission. These calculations utilize resources such as processing power, time, and power of the tracking tag, thereby reducing the useful life of the tracking tag. Each time a transmission is performed by the tracking tag, the tracking tag must calculate and package the payload information for transmission. This calculation utilizes resources such as processing power, time, and tracking tag power, which may reduce the tracking tag's useful life. In some instances, the tracking tag may calculate the same payload or the same payload element multiple times in a single time interval. Such an approach may create an unnecessary waste of resources and may limit the payload transmission rate for the time interval. Summary of the Invention [Means for solving the problem]

[0003] A brief overview An aspect of the present disclosure provides a method for transmitting a beacon signal from a tracking tag in a tracking system, the method including: receiving, by one or more processors of the tracking tag, a first measurement collected by one or more sensors of the tracking tag; determining, by the one or more processors, a degree of similarity between the first measurement and a critical value; comparing, by the one or more processors, the degree of similarity between the first measurement and the critical value to a first threshold; modifying, by the one or more processors, an initial time interval based on a comparison of the degree of similarity between the first measurement and the critical value to the first threshold to determine a modified time interval; and transmitting, by the one or more processors, one or more beacon signals in accordance with the modified time interval.

[0004] In one example, the method further includes receiving, by one or more processors, second measurements collected by the one or more sensors, determining, by the one or more processors, a degree of similarity between the second measurements and a critical value, comparing, by the one or more processors, the degree of similarity between the second measurements and the critical value to a first threshold, further modifying the modified time interval based on comparing the degree of similarity between the second measurements and the critical value to the first threshold, and transmitting, by the one or more processors, one or more beacon signals in accordance with the further modified time interval. In another example, the further modified time interval is the initial time interval.

[0005] In a further example, the one or more sensors include at least one temperature sensor and the critical value is temperature. In another example, the one or more sensors include at least one light sensor and the critical value indicates that the at least one light sensor is exposed to ambient light.

[0006] In another example, the modified time interval is greater than the initial time interval, and the beacon signal is transmitted at a first rate during the initial time interval and at a second rate during the modified time interval. In a further example, the modified time interval is less than the initial time interval, and the beacon signal is transmitted at a first rate during the initial time interval and at a second rate during the modified time interval.

[0007]

[0007] In one example, the method further includes generating, by one or more processors, a first beacon signal including a first payload using the first measurement, wherein the first beacon signal is transmitted according to an initial time interval.

[0008] In one example, the modified time interval cannot be greater than a maximum value. Additionally or alternatively, the modified time interval cannot be less than a minimum value.

[0009] Another aspect of the present disclosure provides a method for transmitting a beacon signal from a tracking tag in a tracking system, the method including: receiving, by one or more processors of the tracking tag, first measurements collected by one or more sensors of the tracking tag, generating, by the one or more processors, a first beacon signal including a first payload using the first measurements, receiving, by the one or more processors, second measurements collected by the one or more sensors, and determining, by the one or more processors, based on at least the second measurements, whether to use the second measurements to generate a second payload.

[0010]

[0010] In one example, the method further includes determining, by one or more processors, a degree of similarity between the first measurement and the second measurement, and comparing, by one or more processors, the degree of similarity between the first measurement and the second measurement to a second threshold, wherein determining, by one or more processors, whether to generate a second payload using the second measurement based on at least the second measurement includes determining, by one or more processors, whether to generate a second payload using the second measurement based on a comparison of the degree of similarity between the first measurement and the second measurement to a second threshold.

[0011] In another example, the method further includes generating, by the one or more processors, a second beacon signal including a second payload when a degree of similarity between the first measurement and the second measurement satisfies a second threshold. In a further example, the method further includes generating, by the one or more processors, a second beacon signal including at least a portion of the first payload when a degree of similarity between the first measurement and the second measurement does not satisfy a second threshold.

[0012]

[0012] In a further example, the method further includes comparing, by one or more processors, the second measurement to a first threshold, wherein determining, by one or more processors, whether to generate a second payload using the second measurement based on at least the second measurement includes determining, by one or more processors, whether to generate a second payload using the second measurement based on a comparison of the second measurement to the first threshold.

[0013] In another example, the method further includes generating, by the one or more processors, a second beacon signal including the second payload when the second measurement satisfies the first threshold. Additionally or alternatively, the method further includes generating, by the one or more processors, a second beacon signal including at least a portion of the first payload when the second measurement does not satisfy the first threshold.

[0014]

[0014] In a further example, determining by one or more processors whether to generate a second payload using the second measurement based on at least the second measurement includes determining by one or more processors to generate a second beacon signal including the second payload when the second measurement is received in a different time frame than the first measurement.

[0015] Another aspect of the present disclosure provides a tracking tag including one or more sensors configured to collect one or more measurements and one or more processors configured to receive a first measurement collected by the one or more sensors of the tracking tag, determine a degree of similarity between the first measurement and a critical value, compare the degree of similarity between the first measurement and the critical value to a first threshold, modify an initial time interval based on a comparison of the degree of similarity between the first measurement and the critical value to the first threshold to determine a modified time interval, and transmit one or more beacons according to the modified time interval.

[0016] Another aspect of the present disclosure provides a tracking tag including one or more sensors configured to collect one or more measurements, and one or more processors configured to receive first measurements collected by the one or more sensors of the tracking tag, generate a first beacon signal including a first payload using the first measurements, receive second measurements collected by the one or more sensors, and determine, based on at least the second measurements, whether to generate a second payload using the second measurements. [Brief explanation of the drawings]

[0017] BRIEF DESCRIPTION OF THE DRAWINGS [Figure 1A] 10 illustrates various examples of object positioning according to aspects of the present technology; [Figure 1B]

[0018] FIG. 1 is a functional diagram of an example tracking system according to aspects of the present disclosure. [Figure 2]

[0019] FIG. 1 is a pictorial diagram of an example network according to an aspect of the present disclosure. [Figure 3]

[0020] FIG. 3 is a functional diagram of the example network of FIG. 2 according to an aspect of the present disclosure. [Figure 4A]

[0021] 1 illustrates an example scenario according to aspects of the present disclosure. [Figure 4B]

[0021] An example scenario according to an aspect of the present disclosure is shown. [Figure 5]

[0022] FIG. 1 is an exemplary functional diagram of a tracking tag, a reader device, and a server computing device according to aspects of the present disclosure. [Figure 6]

[0023] 1 is an exemplary representation of beacon signal timing according to an aspect of the present disclosure. [Figure 7A]

[0024] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 7B] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 7C] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 7D] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 7E] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 8]

[0025] 1 is a flowchart describing an exemplary method of interval modification according to an aspect of the present disclosure. [Figure 9A]

[0026] 1 is a flowchart describing an exemplary method of payload calculation and transmission according to an aspect of the present disclosure. [Figure 9B]1 is a flowchart describing an exemplary method of payload calculation and transmission according to an aspect of the present disclosure. [Figure 9C] 1 is a flowchart describing an exemplary method of payload calculation and transmission according to an aspect of the present disclosure. [Figure 10]

[0027] FIG. 1 is a flow diagram according to an aspect of the present disclosure. [Figure 11]

[0028] FIG. 1 is a flow diagram according to an aspect of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0018] Detailed Description overview

[0029] The present technology relates to adaptive beaconing for tracking tags in a tracking system. Such systems may utilize tracking tags to track and monitor the state of objects. Such systems may aim to ensure receipt of payload information at least once per time interval (e.g., minutes, seconds, etc.). To meet these aims, during each time interval, an item such as a tracking tag in a tracking system may transmit a beacon signal containing payload information multiple times within the time interval to ensure receipt of the information or payload of the beacon signal.

[0019]

[0030] Each time a beacon signal is transmitted by a tracking tag, the tracking tag must calculate and package the payload information for transmission. This calculation utilizes resources such as processing power, time, and tracking tag power, which may reduce the tracking tag's useful life. In some instances, the tracking tag may calculate the same payload or the same payload element multiple times in a single time interval. Such an approach may create an unnecessary waste of resources and may limit the payload transmission rate for a time interval.

[0020]

[0031] To address these shortcomings, an adaptive beaconing scheme can be used. This may involve beaconing the same payload information or payload information with the same elements and modifying the time interval based on collected measurements. The tracking system may include multiple components. The components may include one or more server computing devices, one or more readers, and one or more tracking tags. The server computing device may include a receiver module, one or more processors, and a memory with instructions and data. The reader may include a receiver module, one or more processors, and a memory with instructions and data.

[0021]

[0032] The one or more tracking tags may include one or more processors, a transmitter, one or more sensors, and a power source (e.g., one or more batteries). The sensors may include, for example, an accelerometer, a temperature sensor such as a thermometer, and / or an optical sensor (photodiode, photoresistor). The tracking tags may be configured to transmit beacons to a reader via their respective transmitters. The tracking tag's transmitters may each include an antenna coupled to the above-mentioned processor.

[0022]

[0033] A tracking system can be configured to track or monitor an object via a tracking tag. The tracking tag can be configured to transmit a beacon signal containing payload information belonging to the object. This payload information can include, for example, one or more measurements, which can be packaged in the beacon signal along with a timestamp as well as the identification information of the tracking tag. The beacon signal can be transmitted at a particular rate within a time interval. The payload information can additionally include an encryption field. The encryption field prevents an entity from accessing the payload information if the beacon signal is intercepted. The encryption field can require authentication information to access the payload information.

[0023]

[0034] At least some of the tracking tags can be configured to modify the time interval based on measurements collected by the tracking tag's sensors. This allows the tracking tag to allocate resources more efficiently by modifying transmission rates so that data containing measurements is received more frequently when needed and less frequently when redundant. To do this, the tracking tag may first collect one or more measurements using one or more sensors of the tracking tag. The measurements may be received by a processor of the tracking tag. The processor may determine a degree of similarity between the one or more measurements and a critical value. If the degree of similarity or the measurements satisfies a first threshold, the processor may modify the length of the time interval from the initial time interval to a modified time interval. The tracking tag may then transmit a beacon signal according to the modified time interval. This modification may therefore cause the tracking tag to beacon more frequently or less frequently based on the modified time interval. The processor may continue to compare the determined degree of similarity or the measurements received from the sensor to a first threshold and modify the time interval accordingly.

[0024]

[0035] In addition to or instead of changing the time interval, the tracking tag can be configured to transmit beacon signals with identical payloads or payloads with identical elements in some examples to reduce resources consumed in generating and packaging payload information for several beacon signals. Measurements collected by the sensor can be received by a processor and compared to one another. The difference between two adjacent measurements in time can be compared to a second threshold. If the difference does not meet (e.g., is less than) the second threshold, the tracking tag can transmit a beacon signal with the same payload or the same payload elements as the last transmitted beacon signal. As a result, the tracking tag can save resources that would have been used to compute a new payload.

[0025]

[0036] If the difference meets (e.g., is greater than or equal to) a second threshold, the tracking tag can compute a new payload. As an example, this new payload can contain the most recent measurements.

[0026]

[0037] In some implementations, the threshold value can be selected according to the tolerance of the system. For example, in a system in which one or more sensors are temperature sensors, the threshold value can be the uncertainty value within which the temperature measurement is reported (e.g., ±0.4 degrees above or below).

[0027]

[0038] For each subsequent measurement from the sensor, a difference determination can be made by the processor between the new measurement and the measurement contained within the payload information of the last transmitted beacon signal.

[0028]

[0039] In some examples, the time interval cannot be changed to be greater than a maximum value. In such examples, the tracking tag may be configured to calculate new payload information such that one of the reads receives new payload information in each time frame equal to the maximum value, in which case the time frame cannot be equal to the time interval.

[0029]

[0040] The features and methods described herein can provide adaptive beaconing for tracking systems, which can reduce the number of computed payloads over time when such computations become redundant and therefore unnecessary. In addition, the features described herein can allow for increased frequency of data reception over time when such information is important to the health of the system. Thus, the features described herein reduce the resources required to compute and package new payload information, which can increase the useful life of the tracking tags described herein and make the tracking system more efficient.

[0030] Example System

[0041] FIG. 1A shows examples of different objects in various environments. As shown on the left image of the figure, packages or equipment may reside on pallets in a warehouse. The pallets may be removed from a cargo truck, as shown by the "in transit" image in the center of the figure. The pallets may be moved to one or more different locations within the warehouse, such as by a forklift, as shown in the left image. The right image of the figure shows a situation in which medical equipment (e.g., wheelchairs) and supplies in boxes may be stored in an equipment room within a hospital.

[0031]

[0042] In all of these situations, whether in a warehouse, on a cargo truck, or in a hospital, the object of interest may be moving around. This may be to different aisles or rooms in a warehouse, different rooms (or possibly different floors) in a hospital, or different parts of the truck's cargo container. In the latter case, the cargo may be shifting or repositioning during transport as different packages are delivered to different locations. Knowing where an object of interest is currently located, as opposed to when such an object of interest is presumed based on an initial location, is a valuable piece of information for an office manager, warehouse manager, nurse, or attendant to have. Ideally, such people should be able to obtain the current location of a given object on their client computing device, such as a laptop, cell phone, or smartwatch.

[0032]

[0043] FIG. 1B is a functional diagram of tracking system 100. Tracking system 100 may include multiple tracking devices, such as tracking tags 102 and 104, and a reader device 106. Additionally, as described further below, one or more server computing devices 108 may be part of tracking system 100. A given tracking tag may be placed on or otherwise attached to or inserted within a tracked object, such as a package, a piece of equipment, a vehicle, a warehouse section, a room, or the like. Tracking tag 102 may be associated with an object such as a package, equipment, or vehicle (e.g., a forklift or an autonomous fulfillment robot that may retrieve packages from different locations in a warehouse), while tracking tag 104 may be fixed to an aisle in a warehouse or a specific room in a hospital. Thus, different tracking tags may be used depending on customer needs. As an example, different customers may have varying accuracy and “liveness” needs. For example, one customer may only want to know aisle-level accuracy daily (e.g., before a warehouse closes each day), while another customer, such as a hospital nurse, may need to know which room a piece of equipment is located in at each hour so that it can be accessed when a patient needs such equipment. Each tracking tag 102 or 104 can emit an information signal, such as a beacon signal, via an antenna, such as using transmitter 132, to communicate the data. In this regard, each tracking tag can include an identifier chip (e.g., for radio frequency (RF) identification) and / or a transmitter (e.g., an RF module configured to transmit a beacon signal using a selected frequency band and transmission protocol). In this regard, the beacon signal can transmit identifying information to enable tracking of the object. To facilitate this, each tracking tag can be embedded with a unique identifier, such as a unique MAC address or Bluetooth identifier, that can serve as a tracking tag identifier. This tracking tag identifier can be assigned to the tracking tag during a manufacturing or provisioning process (described further below).In some examples, the tracking tag 102 or 104 may include one or more processors 130 that may facilitate transmission or perform other functions as described below.

[0033]

[0044] The tracking tag's transmitter can transmit such information via radio frequency transmission in a selected frequency band using a standard or proprietary protocol. By way of example, the transmitter can utilize BLUETOOTH (e.g., BLUETOOTH Low Energy (BLE)) or 802.11 protocols within the 2.4 GHz and / or 5 GHz frequency bands. In some examples, each beacon tracking tag and each tracking tag uses the BLUETOOTH or BLE protocol.

[0034]

[0045] In some examples, the tracking tag 102 or 104 may include one or more sensors 134. In such examples, the communicated data described above may be formatted according to a selected protocol and may include one or more sensed characteristics of a given tracking tag or its environment. For example, the sensed characteristics may be temperature, location, motion, battery status, trip status, light level, and / or other detectable characteristics of the tracking tag or its environment. The one or more sensors 134 may include, for example, an accelerometer, a temperature sensor such as a thermometer, an optical sensor (e.g., a photodiode, a photoresistor), and / or other sensors capable of detecting characteristics of the tracking tag or its environment.

[0035]

[0046] The reader device 106 may be a computing device configured to detect beacon signals emitted by multiple tracking tags 102 and 104 and then store and / or transmit data related to the tracking tags. Although only one reader is shown in FIG. 1B, a system may utilize multiple readers. The reader device 106 may include one or more processors 110, memory 112, and other components typically found in a general-purpose computing device. The reader device 106 includes a receiver module 118 having an antenna and a processing section (not shown), which may include bandpass filters for frequency bands of interest, an analog-to-digital (A / D) converter, and a signal processing module for evaluating information in the received beacon signals. The processing section may also convert the received beacon signals to baseband signals before or after A / D conversion.

[0036]

[0047] The one or more processors 110 may be any conventional processor, such as a commercially available CPU or microcontroller. Alternatively, the one or more processors may be dedicated devices, such as ASICs or other hardware-based processors, such as field-programmable gate arrays (FPGAs). While FIG. 1B functionally depicts one or more processors, memory, and other elements of the reader device 106 as being within the same block, the processor, computing device, or memory may actually include multiple processors, computing devices, or memories, which may or may not be stored within the same physical housing. For example, the memory may be a hard drive, removable USB drive, or other storage medium located within a different housing than that of the reader device 106. Thus, reference to a processor or computing device should be understood to include reference to a collection of processors or computing devices or memories, which may or may not operate in parallel.

[0037]

[0048] The memory 112 stores information accessible by the one or more processors 110, including instructions 114 and data 116 that can be executed or otherwise used by the one or more processors 110. The data may include sensed characteristics from any of the tracking tags 102 and / or 104 received by the reader device 106. The memory 112 may be of any type capable of storing information accessible by the one or more processors, including computing device-readable media or other media that store data that can be read with the aid of electronic devices such as hard drives, memory cards, ROM, RAM, DVDs, or other optical disks, as well as other writable and read-only memories. The systems and methods may include different combinations of the above, whereby different portions of the instructions and data are stored on different types of media.

[0038]

[0049] Data 116 may be obtained, stored, or modified by one or more processors 110 in accordance with instructions 114. For example, claimed subject matter is not limited by any particular data structure; data may be stored in computing device registers, in a relational database, as a table with multiple different fields and records, an XML document, or a flat file. Data may also be formatted in any computing device-readable format.

[0039]

[0050] The instructions 114 may be any set of instructions that are executed by a processor directly (such as machine code) or indirectly (such as a script). For example, the instructions may be stored as computing device code on a computing device-readable medium. In this regard, the terms "instructions" and "program" may be used interchangeably herein. The instructions may be stored in object code format for direct processing by a processor or in any other computing device language, including a script or collection of independent source code modules that are interpreted on demand or pre-compiled. The functions, methods, and routines of the instructions are described in further detail below.

[0040]

[0051] In some implementations, the tracking system 100 may further include a central server, such as one or more server computing devices 108, accessible by the one or more processors 110 of the reader device 106. In some implementations, one or more tracking devices in the tracking system 100, such as the tracking tag 104, may be configured to acquire and communicate data directly with the one or more server computing devices 108. The one or more server computing devices 108 may include a receiver module 128, one or more processors 120, a memory 122, and other components typically found on a general-purpose computing device. The one or more processors 120 may be of the same or similar type as the one or more processors 110, and the memory 122 may also be of the same or similar type as the memory 112. The memory 122 stores information accessible by the one or more processors 120, including instructions 124 and 126 that may be executed or otherwise used by the one or more processors 120. The data 126 and instructions 124 may be of the same or similar type as the data 116 and instructions 114, respectively.

[0041]

[0052] After detecting the beacon signal of one or more tracking tags 102 or 104, the reader device 106 can transmit data from the tracking tags to one or more server computing devices 108 through an existing connection or over a network. Accordingly, in this case, the reader device 106 can include a transmitter module (not shown) configured for wired or wireless transmission to the server computing device. The data can be transmitted in a series of payloads (e.g., data packets) according to the methods described herein. A given payload (which can have one or more data packets) can include information pertaining to the tracking tag, the object associated with the tracking tag, and / or the surrounding environment. The information can include, for example, one or more measurements, which can be packaged in the beacon signal along with a timestamp as well as identifying information for the tracking tag. The information can additionally include an encryption field. The encryption field prevents entities from accessing the payload information if the beacon signal is intercepted. The encryption field can require authentication information to access the payload information. In one scenario, the reader device 106 may include a transceiver including both a receiver and a transmitter, which is configured to receive beacon signals from the tracking tags 102 and 104 and also to send and receive information to and from the server computing device 108.

[0042]

[0053] The server computing device 108 can be configured to track a characteristic of the tracking device for one or more alerts based on multiple conditions. The multiple conditions can include at least one condition for each characteristic, such as a minimum value, a maximum value, a threshold value, a duration, or a geofence. The conditions can be predefined or set based on user input. For example, a first alert can be set when (1) the temperature is between 0°C and above 10°C for 30 minutes, for example, and (2) the tracking device is in a tripped state, which can indicate overheating of a refrigerated package or storage compartment. A second alert can be set when (1) no motion is detected for 10 minutes, (2) two of three locations are within a geofence, and (3) the tracking device is in a tripped state, which can indicate a package is being removed for distribution. A third alert may be set when (1) a threshold amount of light is detected from inside the package and (2) the tracking device is in a tripped state, which may signal an unexpected opening or warming of the package. A fourth alert may be set when (1) a threshold amount of light is detected from inside the package and (2) two of the three locations are within the destination geofence, which may signal an opening of the package after delivery or receipt. Many other alert conditions and tracking scenarios are possible, and the above examples are not intended to be limiting.

[0043]

[0054] The tracking system 100 may optionally include applications that may be installed on one or more client computing devices that enable the client computing devices to access data from the reader device 106 and / or the server computing device 108 over a network.

[0044]

[0055] 2 and 3 are pictorial and functional diagrams, respectively, of an exemplary system 200 including multiple client computing devices 220, 230, 240 and a storage system 250 connected via a network 260. System 200 also includes a tracking system 100 including tracking tags 102, 104, a reader device 106, and a server computing device 108. For purposes of clarity, only a few tags and computing devices are depicted, although a typical system may include significantly more.

[0045]

[0056] Using the client computing devices, users, such as users 222, 232, 242, can observe location data on displays, such as displays 224, 234, 244, of the respective client computing devices 220, 230, 240. As shown in Figure 3, each client computing device 220, 230, 240 may be a personal computing device intended for use by an individual user and may have all of the components typically used in connection with a personal computing device, including one or more processors (e.g., central processing units), memory (e.g., RAM and an internal hard drive) for storing data and instructions, a display, such as displays 224, 234, 244 (e.g., a monitor with a screen, a touchscreen, a head-mounted display, a smartwatch display, a projector, a television, or other device operable to display information), and user input devices 226, 236, 246 (e.g., one or more of a mouse, a keyboard, a touchscreen, and / or a microphone). The client computing device may also include speakers, network interface devices, and all of the components used to connect these elements together.

[0046]

[0057] Client computing devices 220, 230, and 240 may each comprise a full-sized personal computing device, although the client computing devices may alternatively comprise mobile computing devices capable of wirelessly exchanging data with a server over a network such as the Internet. By way of example only, client computing device 220 may be a mobile phone, or may be a device such as a wireless-enabled PDA, tablet PC, wearable computing device or system (e.g., a smart watch or head-mounted display), or notebook capable of obtaining information over the Internet or other network. By way of example, a user may input information by using a small keyboard, keypad, or microphone, by using visual signals (gestures) from a camera or other sensor, or by using a touchscreen.

[0047]

[0058] Similar to memory 112, storage system 250 may be any type of computerized storage capable of storing information accessible by one or more server computing devices 108, such as a hard drive, memory card, ROM, RAM, DVD, CD-ROM, writable and read-only memory, etc. In addition, storage system 250 may include a distributed storage system in which data is stored on multiple different storage devices that may be physically located in the same or different geographic locations. Storage system 250 may be connected to the computing devices via network 260 as shown in FIG. 2 and / or may be directly connected to or embedded within any of client computing devices 220, 230, 240. Storage system 250 may store information about the tracking tags, including, for example, location, status (e.g., activated and at what time), identifier, last update, sensor data (e.g., temperature readings), information about the object to which the tracking tag is attached (e.g., manufacturing data), etc. In this regard, the information may be determined from received beacon signals provided to and updated by one or more server computing devices 108 and / or any of the client computing devices 220, 230, 240 to the storage system 250.

[0048]

[0059] FIG. 4A illustrates an example system 400 having several tracking tags positioned in various locations in a building (e.g., a hospital). In this example, along one side of a hallway 404, there may be several rooms 402A, 402B, 402C, and 402D, such as patient rooms. On the other side of the hallway 404, there is another room 408, which may be a conference room, common area, rehabilitation facility, or the like, as well as a storage room 406, such as for storing equipment or supplies. One or more tracking tags 410 corresponding to tracking tag 102 or 104 may be positioned within each room, including the hallway. Each tracking tag 410 may be fixed to a location within the room and may be configured to emit a beacon signal 412 (e.g., an RF signal within a selected frequency band according to a particular communication protocol). While the beacon signal 412 may be directional, this is not required; the beacon signal may be transmitted in all directions, for example, from tracking tags 410 positioned on a ceiling, a pillar, or a floor. In some implementations, the tracking tag 410 can be configured to emit a beacon signal along with information related to its environment (eg, temperature, humidity, etc.).

[0049]

[0060] Tracking tag 414 may correspond to tracking tag 102 or 104 when placed on various objects (e.g., the furniture shown in storage room 406 or the wheelchair case shown in room 402A). Also, in some examples, tracking tags can be configured to emit beacon signals that carry information related to the object to which the tracking tag is applied (e.g., temperature, motion information, object details, and / or other detectable characteristics of the tracking device or its environment). Reader devices 416 (which may be configured the same as or similar to reader device 106) can be found in various locations within a building, such as in patient rooms, storage rooms, hallways, or other locations. Note that even when transmitted omnidirectionally, the beacon signal from a given tracking tag may be attenuated in a non-uniform manner due to the presence of walls, furniture, floors / ceilings, equipment, etc.

[0050]

[0061] FIG. 4B shows another example of a system 420 having several fixed tracking tags positioned along different aisles in a warehouse environment. In this example, several aisles 422A, 422B, 422C, and 422D are present, although more (or fewer) aisles may be present, and the aisles may be configured in configurations other than those shown. Here, fixed tracking tags 424 are located at different locations in the aisles, such as along the end caps of the aisles, along the ceiling (or floor), on shelves, on storage lockers, on cabinets, or elsewhere along the aisles. As in FIG. 4A, fixed tracking tags 426 are located on or otherwise associated with different objects, such as pallets of equipment or forklifts that retrieve items from that location in the warehouse. As mentioned above, the fixed tracking tags are configured to transmit beacon signals that can be detected by one or more reader devices 428 (which may be configured the same as or similar to reader device 106).

[0051]

[0062] 5, tracking tag 102 can transmit beacon signals 510A, 510B that can be received by reader devices 106A, 106B (which can be configured the same as or similar to reader device 106). Each reader device can then transmit data 520A, 520B to server computing device 108. As discussed above, this data can provide information about the beacon signal 510A, 510B received from tracking tag 102. Such information can include a tracking tag identifier, status information (e.g., whether the tracking tag is moving or is moving, temperature measurements, whether certain thresholds have been met, etc.), etc. Thus, in this example, each of reader devices 106A, 106B is located within the effective range of tracking tag 102.

[0052]

[0063] To determine the location of a given tracking tag, the system can use signal strength information obtained from the beacon signals of one or more tracking tags. A series of beacon signals can be ramped at different power levels (a ramped sequence). By evaluating the received beacon signal in terms of its transmitted power, the system can determine the room or other location in which a given tracking tag is located. From this, the system can determine the location of a given tracking tag (and therefore its corresponding object) with an appropriate degree of certainty, such as by triangulating its location in relation to associated tracking tags.

[0053] Example Methods

[0064] As described above, a tracking system can be configured to track or monitor objects via tracking tags. Beacon signals can be transmitted at a specific rate within a time interval to meet certain performance standards. For example, a tracking system may require that a beacon signal transmitted by a tracking tag be received by at least one of the readers a minimum of once during each time interval. For example, a tracking system may utilize time intervals (e.g., 1 ms, 5 ms, 1 minute, 5 minutes, etc.). To meet the above requirements, tracking tags in the system can transmit beacon signals at a specific rate during each time interval. For example, referring to FIG. 6, a tracking tag can transmit B1, B2, B3, and B4 at multiple different times during a time interval spanning T0 to T1. In such an example, a time interval may be 1 minute with a 25% chance of reception by one of the readers. In this regard, a tracking tag may be required to transmit beacon signals at a rate of at least four times per time interval or at least four times per minute to ensure that at least one of the beacon signals is received by at least one of the readers.

[0054]

[0065] In some examples, tracking tags can use adaptive beaconing to improve the usefulness of information provided by reader devices to server computing devices. In this regard, time intervals can be adjusted when certain conditions are met. In the simplest manner depicted in FIG. 7A , timing intervals can be modified based on a comparison to a threshold. For example, in block 710, one or more sensors 134 of tracking tags 102 or 104 can collect one or more measurements (M). In block 720, one or more processors 130 can determine whether the one or more measurements satisfy a first threshold. For example, one or more processors 130 can determine that the one or more measurements satisfy the first threshold if the one or more measurements are greater than or equal to the first threshold or less than or equal to the first threshold. If the one or more processors 130 determine that the one or more measurements satisfy the first threshold in block 720, then the one or more processors 130 may modify the time interval in block 730A. If the one or more processors 130 determine that the one or more measurements do not exceed the first threshold, then the one or more processors 130 may not modify the time interval in block 730B. Following blocks 730A and 730B, the transmitter 132 of the tracking tag 102 or 104 may transmit a beacon signal in block 740 according to a time interval corresponding to the modified time interval in block 730A or the unmodified time interval in block 730B.

[0055]

[0066] This can be particularly useful when monitoring temperature-dependent foods or items. In this regard, the sensor may be a temperature sensor and the threshold value is an undesirable temperature. In one example involving an asset such as frozen food, the undesirable temperature may be at or slightly below the melting point of the frozen item. When the temperature sensor detects a reading above the melting point, the tracking tag's time interval is decreased, thereby allowing the tracking tag to beacon relatively frequently. The decreased time interval and relatively frequent beaconing allows for increased receipt of temperature measurements at or around the melting point. This increased monitoring may be desirable, for example, to ensure that the frozen food can return to a relatively cool temperature and to determine how long the frozen food has remained at or around the melting point. If the temperature returns to a temperature below the melting point, the time interval may be increased or returned to its initial value. In this regard, the tracking tag would beacon relatively less frequently since close monitoring is no longer necessary. A similar approach can be employed for items that need to be maintained within a given temperature range (eg, not too warm or too cold).

[0056]

[0067] In another example, the method described above can be used to determine when to extend the battery life of a tracking tag when it is no longer needed to track an object. In this regard, the object to which the tracking tag is attached may be an item contained within a box for shipping. The sensor may be a light sensor, and the first threshold value may be a value that signals that the box has been opened (e.g., exposed to ambient light). The box may be opened when the asset reaches its desired location, meaning that the tracking tag may no longer be needed after the object is unpacked. When the light sensor detects that the box has been opened, the tracking tag's time interval is decreased, allowing the tracking tag to beacon relatively frequently. This allows the tracking tag to extend its remaining battery life since it is no longer needed to track the object.

[0057]

[0068] However, in some instances, a relatively complex scheme may be used to determine whether a threshold is met rather than directly using one or more measurements. Figure 10 is an example method 1000 for adapting a beacon signal generated by a tracking tag in a tracking system that may be executed by one or more processors, such as, for example, processor 130 of one or more tracking tags 102 or 104. In block 1010, one or more processors of the tracking tag receive first measurements collected by one or more sensors of the tracking tag. To do this, the tracking tag may first collect one or more measurements by using one or more sensors of the tracking tag. The measurements may be received by the processor of the tracking tag. For example, the sensor may be a temperature sensor that may be used to monitor objects, such as food or items, that have temperature dependency.

[0058]

[0069] In block 1020, the measurement can be compared to a critical value to determine a degree of similarity (DOS). The critical value may represent some important reference value, such as the melting point of the item to which the tracking tag is attached. For example, in the case of frozen food, the critical value may be an undesirable temperature, such as the melting point of the frozen food. The degree of similarity may be a percentage or difference in value between the critical value and the measurement. In this regard, the degree of similarity represents the degree to which the measurement approaches the critical value.

[0059]

[0070] At block 1030, the degree of similarity between the first measurement and the critical value may be compared to a first threshold. In this regard, one or more processors 130 may determine whether the one or more measurements satisfy the first threshold. Referring again to the frozen food example, this first threshold may represent a percentage to be compared to the degree of similarity. In this example, comparing the degree of similarity to the first threshold may indicate that the temperature is approaching a critical value, such as the melting point.

[0060]

[0071] At block 1040, the initial time interval can be modified based on a comparison of the degree of similarity between the first measurement and the critical value to a first threshold to determine a modified time interval. This modification can involve, for example, increasing or decreasing the time interval depending on the circumstances of the comparison. For example, if the measurement meets, e.g., equals or exceeds, the first threshold, the processor can modify the length of the time interval from the initial time interval to a modified time interval. This modification can cause the tracking tag to beacon more frequently or less frequently based on the modified time interval. This can allow the tracking tag to better allocate resources by changing its transmission rate so that data comprising measurements is received more frequently when needed and less frequently when redundant.

[0061]

[0072] At block 1050, one or more beacon signals are transmitted according to the modified time interval. For example, referring to the frozen food example, the tracking tag's time interval may be decreased, thereby causing the tracking tag to beacon relatively frequently. The decreased time interval or more frequent beaconing allows for increased receipt of temperature measurements at or around the melting point. This increased monitoring may be desirable, for example, to ensure that the frozen food returns to a relatively cool temperature in a desired amount of time and to determine the amount of time the frozen food has remained at or around the melting point.

[0062]

[0073] Additionally or alternatively, in some examples, rather than a single critical value, the tracking tag may use multiple different critical values. In such examples, the item may be a refrigerated item, such as food that is refrigerated but not necessarily frozen. Refrigerated items may be affected by exposure to relatively high ambient temperatures over a period of time, e.g., their temperature may increase by a large amount. In this regard, the core temperature of a refrigerated item may begin to rise when exposed to warm air, but it may take some period of time for the core temperature to increase by a sufficient amount to create concern (e.g., approaching unusable status or exceeding some desired freshness threshold). For example, the core temperature of a refrigerated item may be expected to warm to an undesirable temperature after exposure to a first ambient temperature for at least a first period of time, or after exposure to a second ambient temperature for a second period of time, etc. (e.g., 20 minutes at 10°C, 15 minutes at 15°C, 5 minutes at 20°C, etc.). In this regard, the memory 112 of one or more processors 110 of the tracking tag 102 or 104 may contain data identifying threshold time periods and corresponding temperatures. In this regard, rather than a single critical value, the tracking tag may utilize a set of critical values ​​(i.e., a combination of threshold time periods and corresponding ambient temperatures). In this example, the one or more measurements may include both one or more ambient temperature measurements and one or more timestamps. The one or more ambient temperature measurements may be collected on an exterior surface of the refrigerated item. The exterior surface may correspond to the location of the tracking tag. Furthermore, in this example, the degree of similarity may be (1) a percentage or difference in value between each of the ambient temperatures in the set of critical values ​​and the one or more measurements, and (2) a percentage or difference in value between each of the time periods in the set of critical values ​​and the amount of time the ambient temperature remained at each measured temperature. The amount of time the ambient temperature remained at each measured temperature may be determined based on the timestamps of the one or more measurements. In this example, the first threshold may be a percentage to be compared with one or more degrees of similarity.Thus, a comparison of each degree of similarity to the first threshold may indicate that the refrigerated item has remained at ambient temperature for a period of time such that the core temperature of the refrigerated item is likely approaching an undesirable core temperature, as in the example above.

[0063]

[0074] 8 shows an example visual representation of the interval modification described above. At block 810, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more measurements. At block 812, one or more processors 130 may determine a degree of similarity between the one or more measurements and a critical value. At block 820, the one or more processors 130 may determine whether the degree of similarity satisfies a first threshold. For example, the one or more processors 130 may determine that the degree of similarity satisfies the first threshold if the degree of similarity is equal to or greater than the first threshold. If the one or more processors 130 determine that the degree of similarity exceeds the first threshold, then at block 830A, the one or more processors 130 may modify the time interval. If the one or more processors 130 determine that the degree of similarity does not meet the first threshold, then in block 830B, the one or more processors may not change the time interval. Following blocks 830A and 830B, in block 840, the transmitter 132 of the tracking tag 102 or 104 may transmit a beacon signal according to the changed or unchanged time interval.

[0064]

[0075] The processor may continue to receive measurements from the sensors and further modify the time interval accordingly. However, in some examples, if the measurements or degree of similarity no longer satisfy the first threshold, the tracking tag may adjust the modified time interval back to the initial time interval. FIG. 7B illustrates another example method of interval modification. At block 710, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more measurements. At block 721, the one or more processors 130 may determine whether the one or more measurements or degree of similarity satisfy the first threshold. For example, the one or more processors 130 may determine that the one or more measurements or degree of similarity satisfy the first threshold if the one or more measurements or degree of similarity are greater than or equal to the first threshold or less than or equal to the first threshold, e.g., as described above. If the one or more processors 130 determine that the one or more measurements or degrees of similarity satisfy the first threshold in block 721, then the one or more processors 130 may change the time interval in block 730A. If the one or more processors 130 determine that the one or more measurements or degrees of similarity do not satisfy the first threshold in block 721, then the one or more processors 130 may determine whether the current time interval is equal to the initial time interval in block 722. If the current time interval is equal to the initial time interval, then the one or more processors 130 may not change the time interval in block 730B. If the current time interval is not equal to the initial time interval, then the one or more processors 130 may change the time interval to the initial time interval in block 730C. Following blocks 730A, 730B, and 730C, in block 740, the transmitter 132 of the tracking tag 102 or 104 can transmit a beacon signal according to the time interval.

[0065]

[0076] Referring again to the frozen food example, if the temperature returns to some point below the melting point (i.e., the degree of similarity or one or more measurements no longer meet the first threshold), the time interval can return to its initial value. In this regard, the tracking tag would beacon less frequently since close monitoring is no longer required. A similar approach can be employed for items that need to be maintained within a given temperature range (e.g., not too warm or too cold).

[0066]

[0077] Similarly, referring again to the ambient lighting and battery example, if the box is opened but subsequently closed, the time interval may return to its initial value. In this regard, the tracking tag may be particularly useful in situations where the box is opened while the tracking tag is not in its desired location, resulting in the tracking tag beaconing relatively infrequently since there is no need to extend its remaining battery life.

[0067]

[0078] In some implementations, the one or more processors 130 may modify the time interval to increase the frequency of the beacon signal when one or more measurements or measures of similarity satisfy a threshold. In some implementations, the one or more processors 130 may modify the time interval to decrease the frequency of the beacon signal when one or more measurements or measures of similarity do not satisfy a threshold. FIG. 7C illustrates another example method of interval modification. At block 710, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more measurements. At block 720, the one or more processors 130 may determine whether the one or more measurements or measures of similarity satisfy a first threshold. The one or more processors 130 may determine that the one or more measurements or measures of similarity satisfy the first threshold, for example, if the one or more measurements or measures of similarity are greater than or equal to the first threshold or less than or equal to the first threshold. If the one or more processors 130 determine that the one or more measurements or degrees of similarity satisfy the first threshold, then in block 732A, the one or more processors 130 may decrease the time interval. If the one or more processors 130 determine that the one or more measurements or degrees of similarity do not satisfy the first threshold, then in block 732B, the one or more processors 130 may increase the time interval. Continuing with blocks 732A and 732B, in block 740, the transmitter 132 of the tracking tag 102 or 104 may transmit a beacon signal according to the time interval.

[0068]

[0079] Referring again to the frozen food example, if the temperature returns to some point below the melting point (i.e., the degree of similarity or one or more measurements no longer meet the first threshold), the time interval can be increased again. In this regard, the tracking tag would beacon at a relatively low frequency since close monitoring is no longer required. A similar approach can be employed for items that need to be maintained within a given temperature range (e.g., not too warm or too cold).

[0069]

[0080] Similarly, referring again to the example of ambient lighting and batteries, if the box is opened but subsequently closed, the time interval can be increased. In this regard, the tracking tag may be particularly useful in situations where the box is opened while the tracking tag is not in its desired location, as it will beacon relatively infrequently since it is not necessary to extend its remaining battery life.

[0070]

[0081] In some examples, the time interval cannot be changed beyond a maximum value to ensure that a beacon signal is received at least once within a time interval equal to the maximum value. For example, the maximum value is 10 minutes, and the time interval cannot be changed beyond this to ensure that a beacon signal is received at least once every 10 minutes. FIG. 7D shows another example method of interval change. At block 710, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more measurements. At block 721, the one or more processors 130 may determine whether the degree of similarity or the one or more measurements meet a first threshold. For example, the one or more processors 130 may determine that the degree of similarity or the one or more measurements meet the first threshold if, for example, the degree of similarity is greater than or equal to the first threshold or less than or equal to the first threshold. If the one or more processors 130 determine that the degree of similarity or one or more measures meet the first threshold, then in block 732A, the one or more processors 130 may decrease the time interval. If the one or more processors 130 determine that the degree of similarity or one or more measures does not meet the first threshold, then in block 732B, the one or more processors 130 may increase the time interval. Then, in block 734, the one or more processors 130 may determine whether the time interval exceeds a maximum value. If the one or more processors 130 determine that the time interval exceeds the maximum value, then in block 736, the one or more processors 130 may change the time interval to the maximum value. If the one or more processors 130 determine that the time interval is less than the maximum value, following blocks 732A and 736, in block 740, the transmitter 132 of the tracking tag 102 or 104 may transmit a beacon signal according to the modified time interval.Such a scheme can not only ensure that the beacon signal is received at least once within a time interval equal to its maximum value, but at the same time avoid unnecessary waste of the tracking tag's battery caused by transmitting the beacon signal too frequently.

[0071]

[0082] In some examples, the time interval cannot be changed to be less than a minimum value. FIG. 7E shows another example method of interval change. In block 710, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more measurements. In block 721, the one or more processors 130 may determine whether the degree of similarity or the one or more measurements meet a first threshold. The one or more processors 130 may determine that the degree of similarity or the one or more measurements meet the first threshold if, for example, the degree of similarity or the one or more measurements are greater than or equal to the first threshold or less than or equal to the first threshold. If the one or more processors 130 determine that the degree of similarity or the one or more measurements do not meet the first threshold, then in block 732B, the one or more processors 130 may increase the time interval. If the one or more processors 130 determine that the degree of similarity or one or more measures meets the first threshold, then in block 732A, the one or more processors 130 may decrease the time interval. Then, in block 735, the one or more processors 130 may determine whether the time interval is less than a minimum value. If the one or more processors 130 determine that the time interval is less than the minimum value, then in block 737, the one or more processors 130 may change the time interval to the minimum value. If the one or more processors 130 determine that the time interval is greater than the minimum value, following blocks 732A and 737, then in block 740, the transmitter 132 of the tracking tag 102 or 104 may transmit a beacon signal according to the changed time interval. This scheme may allow the battery life of the tracking tag 102 or 104 to be preserved for at least a minimum amount of time.

[0072]

[0083] In addition to or instead of varying the time interval, the tracking tag may be configured to transmit beacon signals having the same payload or payloads with the same elements in some examples to reduce resources consumed in generating and packaging payload information for several beacon signals. FIG. 11 is an example method 1100 for adapting beacon signals generated by a tracking tag within a tracking system that may be executed by one or more processors, such as, for example, processor 130 of tracking tag 102 or 104. In block 1110, the one or more processors of the tracking tag first receive first measurements collected by one or more sensors of the tracking tag. To do this, the tracking tag may first collect one or more measurements using one or more sensors of the tracking tag. The measurements may be received by the processor of the tracking tag. For example, the sensor may be a temperature sensor that may be used to monitor an object, such as food or an item, that has temperature dependency.

[0073]

[0084] In block 1120, one or more processors of the tracking tag can use the first measurement to generate a first payload. The first payload can include information such as the first measurement, which can be packaged in a beacon signal with a timestamp as well as the tracking tag's identification information. The payload information can additionally include an encryption field. The encryption field prevents an entity from accessing the payload information if the beacon signal is intercepted.

[0074]

[0085] In block 1130, the one or more processors of the tracking tag receive second measurements collected by one or more sensors of the tracking tag, the second measurements collected by the one or more sensors of the tracking tag and received by the one or more processors in a manner similar to the first measurements.

[0075]

[0086] At block 1140, the one or more processors may determine whether to generate a second payload using the second measurement based on at least the second measurement. In some examples, the first and second measurements collected by one or more sensors may be received by a processor and compared to each other to determine whether to generate a second payload. The degree of similarity between two adjacent measurements in time may be compared by the one or more processors to a second threshold. For example, the degree of similarity may be a percentage or a difference in value. In some implementations, the second threshold may be selected according to a system tolerance. For example, in a system in which one or more sensors are temperature sensors, the second threshold may be an uncertainty value within which the temperature measurement is reported (e.g., ±0.4 degrees or more or less).

[0076]

[0087] If the difference does not meet (e.g., is less than) the second threshold, the tracking tag can transmit a beacon signal containing the same payload from the last transmitted beacon signal or at least the same portion of a previously transmitted payload. This allows the tracking tag to conserve resources that would have been used to compute a new payload. If the difference meets (e.g., is greater than or equal to) the second threshold, the tracking tag can compute a new payload. As an example, this new payload can contain the most recent measurements.

[0077]

[0088] In some examples, to determine whether to generate a second payload, the one or more processors can determine a degree of similarity between the second measurement and a critical value. The degree of similarity between the second measurement and the critical value can then be compared by the one or more processors to a first threshold. Alternatively, the one or more second measurements can be compared to the first threshold. The first threshold can be a value utilized in modifying the time interval, as described above. If the degree of similarity between the second measurement and the critical value or the second measurement satisfies the first threshold, the one or more processors can generate a second payload using the second measurement.

[0078]

[0089] Depending on the degree of similarity between the second measurement and the critical value or if the second measurement does not meet the first threshold, the tracking tag can transmit a beacon signal containing the same payload from the last transmitted beacon signal or at least the same portion of a previously transmitted payload, thereby generating and transmitting a new payload when the collected measurements approach or meet the value of interest.

[0079]

[0090] 9A shows an example visual representation of payload calculation and transmission. At block 910, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more first measurements. At block 920, one or more processors 130 may calculate a first payload using the one or more first measurements. At block 930, a transmitter 132 of the tracking tag 102 or 104 may transmit the first payload. At block 940, one or more sensors 134 of the tracking tag 102 or 104 may collect one or more second measurements. At block 950, the one or more processors 130 may determine a degree of similarity between the one or more first measurements and the one or more second measurements. At block 960, the one or more processors 130 may determine whether the degree of similarity satisfies a second threshold. If the one or more processors 130 determine that the degree of similarity meets the second threshold, then the one or more processors 130 may compute a second payload in block 970. Then, in block 980A, the transmitter 132 of the tracking tag 102 or 104 may transmit the second payload. If the one or more processors 130 determine that the degree of similarity does not meet the second threshold, then in block 980B, the transmitter 132 of the tracking tag 102 or 104 may transmit at least a portion of the first payload.

[0080]

[0091] In some implementations, the tracking tag can be configured to calculate a new payload if the one or more second measurements satisfy the first threshold described above. FIG. 9B shows another example method of payload calculation and transmission. At block 910, one or more sensors 134 of the tracking tag 102 or 104 can collect one or more first measurements. At block 920, one or more processors 130 can calculate the first payload. At block 930, the transmitter 132 of the tracking tag 102 or 104 can transmit the first payload. At block 940, one or more sensors 134 of the tracking tag 102 or 104 can collect one or more second measurements. At block 942, the one or more processors 130 can determine whether the one or more measurements satisfy the first threshold. If the one or more processors 130 determine that the one or more second measurements satisfy the first threshold, then the one or more processors 130 may compute a second payload in block 970. The transmitter 132 of the tracking tag 102 or 104 may then transmit the second payload in block 980A.

[0081]

[0092] If the one or more processors 130 determine that the one or more second measurements do not satisfy the first threshold, then in block 950, the one or more processors 130 may determine a degree of similarity between the one or more first and second measurements. In block 960, the one or more processors 130 may determine whether the degree of similarity satisfies a second threshold. If the one or more processors 130 determine that the degree of similarity satisfies the second threshold, then in block 970, the one or more processors 130 may compute a second payload. Then, in block 980A, the transmitter 132 of the tracking tag 102 or 104 may transmit the second payload. If the one or more processors 130 determine that the degree of similarity does not satisfy the second threshold, then in block 980B, the transmitter 132 of the tracking tag 102 or 104 may transmit at least a portion of the first payload.

[0082]

[0093] In some implementations, the tracking tag can be configured to calculate a new payload if the degree of similarity between the one or more second measurements and the critical value satisfies the first threshold described above. FIG. 9C illustrates another exemplary method of payload calculation and transmission. At block 910, one or more sensors 134 of the tracking tag 102 or 104 can collect one or more first measurements. At block 920, one or more processors 130 can calculate the first payload. At block 930, the transmitter 132 of the tracking tag 102 or 104 can transmit the first payload. At block 940, one or more sensors 134 of the tracking tag 102 or 104 can collect one or more second measurements. At block 944, the one or more processors 130 can determine the degree of similarity between the one or more second measurements and the critical value. In block 948, the one or more processors 130 may determine whether the degree of similarity between the one or more first measurements and the critical value satisfies a first threshold. If the one or more processors 130 determine that the degree of similarity between the one or more second measurements and the critical value satisfies the first threshold, then in block 970, the one or more processors 130 may compute a second payload. Then, in block 980A, the transmitter 132 of the tracking tag 102 or 104 may transmit the second payload.

[0083]

[0094] If the one or more processors 130 determine that the degree of similarity between the one or more second measurements and the critical value does not satisfy the first threshold, then in block 950, the one or more processors 130 may determine the degree of similarity between the one or more first measurements and the one or more second measurements. In block 960, the one or more processors 130 may determine whether the degree of similarity between the one or more first measurements and the one or more second measurements satisfies a second threshold. If the one or more processors 130 determine that the degree of similarity between the one or more first measurements and the one or more second measurements satisfies the second threshold, then in block 970, the one or more processors 130 may compute a second payload. Then, in block 980A, the transmitter 132 of the tracking tag 102 or 104 may transmit the second payload. If the one or more processors 130 determine that the degree of similarity between the one or more first measurements and the one or more second measurements does not satisfy the second threshold, then in block 980B, the transmitter 132 of the tracking tag 102 or 104 may transmit at least a portion of the first payload.

[0084]

[0095] For each subsequent measurement or measurements from the sensor, a determination of the degree of similarity may be made by the processor between the new measurement or measurements and the measurement or measurements contained within the payload information of the last transmitted beacon signal.

[0085]

[0096] In some examples, a new payload can be calculated at least once in a time frame. The time frame can correspond to the maximum value of the time interval described above. In such examples, the tracking tag can be configured to calculate new payload information such that one of the readers receives new payload information in each time frame equal to the maximum value; in this case, the time frame cannot be equal to the time interval. For example, if the maximum value is 10 minutes, a new payload would need to be calculated such that a new measurement is received at least every 10 minutes. For example, if a second measurement is obtained in a different or subsequent time frame than the first measurement, one or more processors in the tracking tag can calculate a new payload using the second measurement. In this example, the degree of similarity need not actually meet the second threshold to calculate a new payload. Of course, other maximum values ​​for time intervals greater than or less than 10 minutes can also be used, depending on the needs of the tracking system.

[0086]

[0097] The features and methods described herein can provide adaptive beaconing for tracking systems, which can reduce the number of payloads computed over time when such computations become redundant and therefore unnecessary. In addition, the features described herein can allow for increased frequency of data reception over time when such information is important to the health of the system. Thus, the features described herein can calculate and package new payload information, thereby increasing the useful life of the tracking tags described herein and reducing the resources required to make the tracking system more efficient.

[0087]

[0098] Unless otherwise stated, the above-described alternatives are not mutually exclusive and may be implemented in various combinations to realize their inherent advantages. Because these and other variations and combinations of the above-described features may be utilized without departing from the subject matter defined by the claims, the above description of the embodiments should be construed as illustrative and not limiting of the subject matter defined by the claims. Additionally, example clauses described herein, as well as clauses expressed as "such as," "including," and similar expressions, should not be construed as limiting the subject matter of the claims to any particular example; rather, the example is intended to illustrate only one of many possible embodiments. Furthermore, the same reference symbols in different drawings may identify the same or similar elements.

Claims

1. 1. A method for transmitting a beacon signal from a tracking tag in a tracking system, comprising: receiving, by one or more processors of the tracking tag, first measurements collected by one or more sensors of the tracking tag; determining, by the one or more processors, a degree of similarity between the first measurement and a critical value; comparing, by the one or more processors, the degree of similarity between the first measurement and the critical value to a first threshold; modifying, by the one or more processors, an initial time interval based on the comparison of the degree of similarity between the first measurement and the critical value to the first threshold value to determine a modified time interval; transmitting, by the one or more processors, one or more beacon signals according to the modified time intervals; A method having the following.

2. receiving, by the one or more processors, second measurements collected by the one or more sensors; determining, by the one or more processors, a degree of similarity between the second measurement and the critical value; comparing, by the one or more processors, the degree of similarity between the second measurement and the critical value to the first threshold; further modifying the modified time interval based on the comparison of the degree of similarity between the second measurement and the critical value to the first threshold value; transmitting, by the one or more processors, one or more beacon signals according to the further modified time intervals; The method of claim 1 further comprising:

3. The method of claim 2 , wherein the further modified time interval is the initial time interval.

4. the one or more sensors include at least one temperature sensor; The method of claim 1 , wherein the critical value is a temperature.

5. the one or more sensors include at least one optical sensor; The method of claim 1 , wherein the critical value indicates that the at least one light sensor is exposed to ambient light.

6. the modified time interval is greater than the initial time interval; 2. The method of claim 1, wherein beacon signals are transmitted at a first rate during the initial time interval and at a second rate during the modified time interval.

7. the modified time interval is less than the initial time interval; 2. The method of claim 1, wherein beacon signals are transmitted at a first rate during the initial time interval and at a second rate during the modified time interval.

8. 2. The method of claim 1, further comprising generating, by the one or more processors, a first beacon signal including a first payload using the first measurement, the first beacon signal being transmitted according to the initial time interval.

9. The method of claim 1 , wherein the modified time interval cannot exceed a maximum value.

10. The method of claim 1 , wherein the modified time interval cannot be less than a minimum value.

11. 1. A method for transmitting a beacon signal from a tracking tag in a tracking system, comprising: receiving, by one or more processors of the tracking tag, first measurements collected by one or more sensors of the tracking tag; generating, by the one or more processors, a first beacon signal including a first payload using the first measurement; receiving, by the one or more processors, second measurements collected by the one or more sensors; determining, by the one or more processors, based on at least the second measurements, whether to generate a second payload using the second measurements; A method having the following.

12. determining, by the one or more processors, a degree of similarity between the first measurement and the second measurement; comparing, by the one or more processors, the degree of similarity between the first measurement and the second measurement to a second threshold; and Determining, by the one or more processors, whether to generate the second payload using the second measurement based on at least the second measurement, includes:

12. The method of claim 11, further comprising determining, by the one or more processors, whether to use the second measurement to generate the second payload based on the comparison of the degree of similarity between the first measurement and the second measurement to the second threshold.

13. 13. The method of claim 12, further comprising generating, by the one or more processors, a second beacon signal including the second payload when the degree of similarity between the first measurement and the second measurement satisfies the second threshold.

14. 13. The method of claim 12, further comprising generating, by the one or more processors, a second beacon signal including at least a portion of the first payload when the degree of similarity between the first measurement and the second measurement does not satisfy the second threshold.

15. further comprising comparing, by the one or more processors, the second measurement to a first threshold; Determining, by the one or more processors, whether to generate the second payload using the second measurement based on at least the second measurement, includes:

12. The method of claim 11, further comprising determining, by the one or more processors, whether to generate the second payload using the second measurement based on the comparison of the second measurement to the first threshold.

16. 16. The method of claim 15, further comprising generating, by the one or more processors, a second beacon signal including the second payload when the second measurement satisfies the first threshold.

17. 16. The method of claim 15, further comprising generating, by the one or more processors, a second beacon signal including at least a portion of the first payload when the second measurement does not satisfy the first threshold.

18. Determining, by the one or more processors, whether to generate the second payload using the second measurement based on at least the second measurement, includes:

12. The method of claim 11, comprising determining, by the one or more processors, to generate a second beacon signal including the second payload when the second measurement is received in a different time frame than the first measurement.

19. a tracking tag, one or more sensors configured to collect one or more measurements; one or more processors; In a tracking tag having the one or more processors receiving first measurements collected by one or more sensors of the tracking tag; determining a degree of similarity between the first measurement and a critical value; comparing the degree of similarity between the first measurement and the critical value to a first threshold; modifying an initial time interval based on the comparison of the degree of similarity between the first measurement and the critical value to the first threshold value to determine a modified time interval; transmitting one or more beacon signals according to the modified time intervals. A tracking tag is configured as follows:

20. a tracking tag, one or more sensors configured to collect one or more measurements; one or more processors; In a tracking tag having the one or more processors receiving first measurements collected by one or more sensors of the tracking tag; generating a first beacon signal including a first payload using the first measurement; receiving second measurements collected by the one or more sensors; determining whether to generate a second payload using the second measurement based on at least the second measurement; A tracking tag is configured as follows:

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