Proximity sensor based on local oscillator frequency

Abstract

The present invention discloses a proximity sensor based on a local oscillator frequency. The proximity sensor comprises: an integrated circuit having at least one capacitive element; and an antenna designed with an inductive element, wherein the capacitive element and the inductive element form a proximity sensor oscillating at a local oscillator (LO) frequency, wherein the integrated circuit is configured to measure a frequency deviation relative to the LO frequency, wherein the frequency deviation indicates detection of a nearby object.

Description

[0001] Priority Document

[0002] This application claims the benefit of priority to U.S. Provisional Application No. 62 / 793,265, filed on January 16, 2019, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates generally to oscillators and, more particularly, to utilizing local oscillator frequency measurements to detect environmental changes such as motion or proximity. Background Art

[0004] The Internet of Things (IoT) is the networking of physical devices, vehicles, buildings, and other items embedded with electronics, software, sensors, actuators, and network connections that enable these objects to collect and exchange data. IoT is expected to provide advanced connectivity of devices, systems, and services that go beyond machine-to-machine (M2M) communications and cover a variety of protocols, domains, and applications.

[0005] IoT can be found in a wide variety of devices, such as: heart monitoring implants; biochip transponders in farm animals; vehicles with internal sensors; automation of lighting, heating, ventilation, and air conditioning (HVAC) systems; and appliances such as washers / dryers, robot vacuums, air purifiers, ovens, or refrigerators / freezers that use Wi-Fi for remote monitoring. Typically, IoT devices incorporate wireless sensors or networks of such sensors.

[0006] Most IoT devices are wireless devices that collect data and transmit such data to a central controller. This data may include motion or proximity data detected from the immediate surroundings, among other examples. Several requirements should be met for widespread deployment of IoT devices. Such requirements include reliable communication links, low energy consumption, and low maintenance costs.

[0007] Numerous versions of proximity sensors are commercially available and disclosed in the related art. FIG. 1A shows a schematic diagram of an example of a standard infrared (IR) based proximity sensor 100. The sensor 100 includes two resistors 122 and 124, wherein the first resistor 122 has a resistance of about 250 ohms and the second resistor 124 has a resistance of about 10 kilo-ohms. A power supply 150 provides about 5 volts of power, and the sensor circuit is completed by an output terminal 160 and a ground potential 110. An IR source 130 and a photodiode 140 are placed in parallel, wherein the IR source 130 emits an IR beam that can be detected by the photodiode 140. In one embodiment, the IR source 130 and the photodiode 140 are both light emitting diodes (LEDs) and are configured as a transmitter / receiver pair. When the photodiode detects that the emitted beam is reflected from a nearby object, the intercepted IR beam reduces the resistance of the photodiode and generates an electrical signal resulting therefrom, which can be output at 160 as a signal indicating that an object is detected within a predetermined proximity range.

[0008] As another example, as shown in FIG. 1B , a proximity sensor can be based on capacitive properties. The sensor 170 includes a DC power supply 171 and a DC output 172, wherein the DC power supply 171 supplies power to an oscillator 173 to charge a capacitor. A capacitor consists of two plates, however, there is only a single capacitor plate 175 in the sensor 170. The circuit in the capacitive proximity sensor uses the supplied DC power supply 171 to generate an alternating current to measure the current in the internal AC circuit and switch the output circuit when the amount of AC current changes. The AC can only move current into and out of the internal capacitor plate 175 when there is another plate 177 nearby that can hold an opposite charge. The target that is close enough to be detected acts as another plate. If the target (e.g., an external plate 177) is close enough to the sensor 170 to be affected by the charge in the sensor's internal capacitor plate 175 through the air gap 176 that acts as a dielectric interface, it will respond by becoming oppositely charged near the sensor 170, and then the sensor 170 will be able to move a large amount of current into and out of its internal plate. The current sensor 174 is used to determine changes in current and the proximity of nearby objects.

[0009] Another example of a proximity sensor is an inductive sensor 180, as shown in FIG1C. A high-frequency magnetic field 183 is generated by a coil 182 connected to an oscillation circuit 181. When a target 184 approaches the magnetic field 183, an induced current (eddy current) flows in the target 184 due to electromagnetic induction. As the target 184 approaches the sensor 180, the induced current increases, which causes an increase in the load on the oscillation circuit 181. As a result, the oscillation weakens or stops. The sensor 180 detects the change in the oscillation state, for example, through an amplitude detection circuit, and outputs a detection signal.

[0010] Although other variations of proximity sensors exist, each requires a separate power source to provide the voltage required to detect the proximity of nearby objects. Additionally, capacitive and inductive sensors are often limited to detecting only metal or ferrous objects, and cannot detect movement of non-metallic objects or movement of the sensor itself.

[0011] Although the circuits discussed above are related to proximity sensors, similar limitations exist for motion sensors. The necessity for an independent power supply restricts devices designed for low-power use, such as IoT devices, and the limitation of detecting only metal objects is too restrictive for many IoT applications.

[0012] Some IoT devices are designed to support low-power communication protocols, such as Bluetooth Low Energy (BLE), LoRa, etc. However, IoT devices that utilize such protocols require an external power source, such as a button battery. For example, reliance on power sources is a limiting factor for electronic devices due to cost, size, lack of durability to environmental impact, and frequent replacement. Additionally, reliance on external power sources (such as batteries) requires a larger space allocation, which often poses a challenge to IoT devices designed for the smallest possible size.

[0013] As an alternative to using batteries, power can be harvested from ambient sources such as light, motion, and electromagnetic power (including existing RF transmissions). This minimal power must be managed efficiently to implement a variety of sensors, including proximity sensors, motion sensors, etc.

[0014] In view of the above, it would be advantageous to provide a solution that can overcome the above challenges. Summary of the invention

[0015] Several exemplary embodiments of the present disclosure are summarized as follows. The purpose of this summary is to facilitate the reader to gain a basic understanding of such embodiments without completely limiting the scope of the present disclosure. The content of the invention is not a review of all contemplated embodiments, nor does it identify the important or key elements of all embodiments, nor does it illustrate the scope of any or all aspects. The purpose of the present invention is to present certain concepts of one or more embodiments in a simplified form as an introduction to the specific implementation methods described later. For convenience, the term "certain embodiments" may be used herein to refer to a single embodiment or multiple embodiments of the present disclosure.

[0016] Certain embodiments of the present disclosure include a proximity sensor based on a local oscillator frequency, comprising: an integrated circuit having at least one capacitive element; and an antenna designed with an inductive element, wherein the capacitive element and the inductive element form a proximity sensor that oscillates at a local oscillator (LO) frequency, wherein the integrated circuit is configured to measure a frequency offset relative to the LO frequency, wherein the frequency offset indicates detection of a nearby object.

[0017] Certain embodiments of the present disclosure also include a battery-free Internet of Things (IoT) tag integrated with a proximity sensor, comprising: a transmitting antenna designed to have an inductive element; and an integrated circuit having a capacitive element, wherein the inductive element and the capacitive element form a proximity sensor that oscillates at a local oscillator (LO) frequency, and wherein a frequency shift relative to the LO frequency indicates that a nearby object has been detected.

[0018] Certain embodiments of the present disclosure also include a method for detecting the approach of a nearby object, comprising: determining a local oscillator (LO) frequency of a proximity sensor; measuring a current oscillation frequency of the proximity sensor; determining a frequency offset between the LO frequency and the current oscillation frequency during a measurement window; and determining whether the frequency offset exceeds a predetermined threshold, wherein a frequency offset exceeding the predetermined threshold indicates that at least a nearby object has been detected.

[0019] Certain embodiments of the present disclosure also include a proximity sensor based on a local oscillator frequency, comprising: an antenna designed to have an inductive element; and an integrated circuit having a capacitive element; wherein the inductive element and the capacitive element form a proximity sensor that oscillates at a local oscillator (LO) frequency, wherein the integrated circuit is configured to measure a current oscillation frequency of the proximity sensor, and wherein a frequency deviation relative to the LO frequency indicates that a nearby object has been detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The subject matter of the present disclosure is specifically pointed out herein and explicitly claimed in the claims appended to the specification. The above and other features and advantages of the present disclosure will become more apparent by referring to the following detailed description in conjunction with the accompanying drawings, in which:

[0021] FIG1A is a schematic diagram of an IR proximity sensor;

[0022] FIG1B is a schematic diagram of a capacitive proximity sensor;

[0023] FIG1C is a schematic diagram of an inductive proximity sensor;

[0024] Figure 2 is a schematic diagram of an IoT tag with a proximity sensor according to an embodiment;

[0025] FIG. 3A to FIG. 3D is a diagram of an IoT tag according to various embodiments;

[0026] Figure 4 is a time series graph of LO frequency measurement results of an IoT tag according to an embodiment;

[0027] Figure 5 is the impact curve of removing a bottle of liquid placed on the IoT tag;

[0028] Figure 6 is an exemplary schematic diagram of an IoT tag according to an embodiment;

[0029] Figure 7 is a flow chart illustrating a method for detecting movement or proximity based on local oscillator frequency measurements according to an embodiment; and

[0030] Figure 8 is a network diagram illustrating an analysis system deployment according to an embodiment. DETAILED DESCRIPTION

[0031] It is important to note that the disclosed embodiments are merely examples of the many advantageous uses of the innovative teachings herein. In general, statements made in the specification of this application do not necessarily limit any of the various embodiments claimed. In addition, certain statements may apply to certain inventive features but not to other features. In general, singular elements may be plural and vice versa without loss of generality unless otherwise indicated. In the accompanying drawings, the same numbers in each figure represent the same parts.

[0032] Embodiments of the present disclosure include a method and system for determining motion or proximity based on an oscillator frequency shift of a local oscillator of an IoT tag, particularly a battery-free IoT tag.

[0033] Figure 2 is a schematic diagram of an IoT tag 200 that provides proximity and motion detection according to one embodiment. In one embodiment, the IoT tag 200 includes an integrated circuit (IC or chip) 220 and at least one antenna 210-1, 210-2 placed on an inlay 205. In one embodiment, the inlay 205 is a single-layer inlay that includes the integrated circuit 220 connected to at least one antenna 210-1, 210-2 and can be mounted on a substrate (not shown in the figure). The substrate is a single-layer material, which can be a single metal layer or any suitable integrated circuit mounting material, such as a printed circuit board (PCB), silicon, a flexible printed circuit (FPC), a low temperature co-fired ceramic (LTCC)), polyethylene terephthalate (PET), paper, etc.

[0034] In an exemplary embodiment, the IoT tag 200 includes a pair of antennas 210-1 and 210-2 etched into the inlay 205. The first antenna 210-1 is used to collect energy from ambient signals, while the second antenna 210-2 is used to transmit signals, such as BLE signals. Each antenna 210-1, 210-2 can be a type including a loop antenna, a dipole antenna with a dual-feed large loop, a transformer dual-feed, and similar configurations. It should be noted that the transmitting antenna 210-2 can also be used to collect energy. In addition, in some configurations, multiple antennas can be used to collect energy, each of which is designed to receive signals in a different frequency domain.

[0035] Each antenna 210-1, 210-2 is constructed with an impedance matching structure to produce a desired impedance (labeled "210-L") at the integrated circuit interface at the desired operating frequency. It should be emphasized that the inductive element 210-L is not a dedicated inductor, but an interface-to-antenna impedance with inductive quality characteristics, because an integrated circuit interface with capacitive properties is generally required. The inductive element 210-L is shown as an inductor for discussion purposes only.

[0036] In one embodiment, at least the first antenna 210-1 is connected to a capacitive element 230. The capacitive element 230 may be a capacitor contained in the integrated circuit 220. In another embodiment, the capacitive element 230 is implemented as an integrated capacitor or a parasitic capacitor of various circuits (not shown) contained in the integrated circuit 220. Parasitic capacitance may exist at the connection between the antenna 210-1 and the integrated circuit 220, where the capacitive element 230 is located between the antenna feed line and the ground potential. Parasitic capacitance is a capacitance that is inevitably present between components of an electronic component or circuit due to proximity to each other. In yet another embodiment, the capacitive element 230 may be a capacitive interface impedance of the integrated circuit 220.

[0037] The present disclosure provides a proximity sensor 227 that provides motion and proximity sensing characteristics of the IoT tag 200, which is implemented by an inductive element 210-L and a capacitive element 230. These elements form a proximity sensor 227 that oscillates at a specific frequency, which depends on the environment. When there is no environmental interference or force on the proximity sensor, the oscillation frequency remains substantially constant. It should be noted that the sensor 227 does not have an absolute resonant frequency, and its oscillation frequency depends on the environment. In the following, the local oscillator (LO) frequency is defined as the last measured (or known) oscillation frequency of the proximity sensor 227.

[0038] The sensor 227 of the illustrated embodiment utilizes the inductance provided by the inductive element 210-L from the first antenna 210-1. The inductive element 210L is external, so the inductive sensor is affected by slight electromagnetic changes in the environment, such as the movement or approach of a nearby object or surface. Therefore, each change in inductance caused by environmental influences results in a frequency shift relative to the LO frequency of the sensor 227. Such a shift indicates the detection of the presence of a nearby object, the movement of a nearby object, the movement of the IoT tag 200 itself, or other activity in the area of ​​the IoT tag 200.

[0039] In one embodiment, the LO frequency and any offset thereof may be measured internally by the integrated circuit 220. In this way, the measured frequency may be sampled and monitored over time. Changes in the frequency may be determined to indicate events such as pickup, movement, proximity detection, etc. of an external object or person. In one embodiment, the offset may also be determined by an external analysis system, as described in detail below.

[0040] In one embodiment, the integrated circuit 220 provides the functionality of the wireless IoT device or tag 200. The integrated circuit 220 includes several functions implemented as analog circuits, digital circuits, or both. For example, the integrated circuit 220 can perform functions such as reading and writing memory, such as peripheral devices; performing simple logic operations; tracking power levels; generating and preparing transmission packets; generating cyclic redundancy check (CRC) codes; packet whitening; encrypting / decrypting and verifying packets; converting data from parallel to serial; and segmenting packet bits to the analog transmitter path for transmission.

[0041] In one embodiment, the integrated circuit 220 includes a frequency measurement circuit ( Figure 2 227 and is configured to measure the LO frequency and / or current oscillation frequency of the sensor 227. Various embodiments for measuring the LO frequency are discussed below. In one embodiment, the measurement results in a digital frequency word indicating any motion or proximity detection.

[0042] In one embodiment, the LO frequency may be measured or referenced relative to a second oscillator (not shown) connected to the integrated circuit 220. The referenced oscillator (e.g., an auxiliary oscillator) may be pre-calibrated to a certain frequency. Calibration of such oscillators may be performed using an over-the-air signal, such as described in co-pending U.S. patent application Ser. No. 15 / 994,388 assigned to a common assignee, the contents of which are incorporated herein by reference. In another embodiment, the reference signal may be uncalibrated, in which case it is known to generally produce a frequency within a specific range. In both cases, the integrated circuit 220 may detect changes in relative frequency over time.

[0043] The inductive element 210-L is integrated into the antenna 2101 and is located outside the integrated circuit 220, so the inductive element 210-L is sensitive to the pulling or frequency locking effects from external signals. Such effects may distort the frequency measurement results. Therefore, in one embodiment, a clear channel assessment (CCA) process is performed before activating the frequency measurement. CCA is a process for listening to RF transmissions on a channel to determine whether the channel is in use or available for transmission. Any signal energy detected on the channel is compared with a predetermined CCA parameter value to establish whether the channel is available for use. Additionally, outlier measurement results determined to be caused by external interference are deleted.

[0044] In one embodiment, the IoT tag 200 is battery-free and powered by harvested energy, for example, energy harvested via antennas 210-1 and 210-2. Therefore, the IoT tag 200 may not be able to perform processing tasks that require energy, such as the above-mentioned CCA process, outlier detection, and generation of pickup or move events. To this end, in one embodiment, the IoT tag 200 is connected to an analysis system that is configured to perform at least the processes of CCA, outlier detection, and generation of pickup or move events. The deployment of the analysis system can be performed in a gateway and / or a cloud computing platform, as shown in FIG. Figure 8 .

[0045] In some embodiments, the transmission of frequency measurements is performed using a separate transmission antenna (e.g., 210-2) that is also affected by the environment. In some embodiments, the collection antenna (e.g., 210-1) is additionally used for transmission and sensing. In the latter case, an antenna tuning circuit (not shown) can control the transmission frequency. The transmission antenna 210-2 may also be sensitive to the environment, so in one embodiment, the IoT tag 200 is configured so that the transmission process involves dynamic calibration of the tuning settings to maintain the specific frequency required for signal transmission.

[0046] During a pick-up event, the oscillation frequency of sensor 227 changes as follows: Figure 4 and Figure 5 Due to the delay in calibration and the need to charge the capacitor, a transmission failure may occur during the pick-up event itself because the transmission will be done at an uncalibrated frequency. Therefore, in one embodiment, the frequency measurement is transmitted several times to ensure a high probability of successful reception by the receiving device. In this embodiment, the frequency measurement may include a local timestamp of the time the measurement was performed rather than the time it was transmitted. In one embodiment, the determination of the accurate frequency measurement data and the associated timestamp is performed by an external analysis system.

[0047] FIG. 3A to FIG. 3D is an example diagram of an IoT tag 300 according to various embodiments. Figure 3A A first embodiment of an IoT tag 300 is shown, which includes two loop antennas 310 connected to an integrated circuit or chip (not shown in the figure, but which is placed at the antenna vertex 315 later during production). As shown, the antennas 310 are connected to test connector pads 320 and 330, which can be removed later in the production process. The loop antennas 310 have an inductive impedance at the antenna interface (as described above). Figure 2 As described in the figure) and the capacitor (not shown), as an independent component of the IoT tag 300, or as a chip part placed in 315 (not shown in the figure), see above Figure 2 As described in.

[0048] Figure 3B and Figure 3C Two embodiments of IoT tags 300 are shown with two or three circular loop antennas 310, which are further connected to an integrated circuit (not shown in the figures). Figure 3D It comprises two triangular loop antennas 310 surrounded by a circular antenna 315, each antenna being connected to an integrated circuit (not shown).

[0049] Figure 4 An example graph 400 of a time series of measurements of an oscillation frequency of a proximity sensor (227) included in an IoT tag according to an embodiment is shown. In the example shown, the initial LO frequency 405 is approximately 2353 MHz. Two pick-up events 410 and 420 can be clearly identified, i.e., events where the IoT tag itself has been picked up. During these two events, the oscillation frequency varies by approximately 1 MHz to 1.5 MHz. These changes are due to changes in the antenna inductance caused by a human hand approaching the antenna while moving. Thus, as can be determined from the above example, a proximity event is determined based on an offset relative to the LO frequency and one or more consecutive measurements of the current oscillation frequency. It should be noted that when the sensor 227 stabilizes around a new oscillation frequency (e.g., due to a new environment), such frequency is set as the (new) LO frequency.

[0050] As can be determined from the time series, the oscillation frequency not only changes during the pick events 410 and 420, it should also be noted that the frequency changes slightly before and after each pick event. It should be noted that the initial LO frequency 405 before the first pick event 410 is higher than the post-pick frequency 415. A similar frequency shift can be seen between the pre-pick frequency 415 and the post-pick frequency 425 relative to the second pick event 420. These changes are attributed to the IoT tag being set down with a slight orientation change relative to its initial position before pick up.

[0051] In the example shown, the oscillation frequency decreases by approximately 400 kHz after the first pick 410 and decreases by another 100 kHz after the second pick 420. Thus, even if no measurements were taken during the first pick event itself, e.g., due to lack of energy in the above-described harvester-based scenario, movement of the tag after pick can be detected. Such sensitive detection can be achieved based on sufficiently high resolution of the IoT tag itself, or with additional processing and averaging of multiple IoT tags using a cloud-based system, as described below, since the incremental offset in the example shown is below the resolution of the IoT tag.

[0052] However, in some cases, the change in LO frequency relative to the current oscillation frequency may be significant. Figure 5Graph 500 showing the effect of removing a bottle of liquid that has been placed on an IoT tag. The oscillation frequency 520 after the bottle is removed from the IoT tag is approximately 100 MHz higher than the initial LO frequency 510 measured before removal.

[0053] Figure 6 6 is an exemplary schematic diagram of an IoT tag 600 according to an embodiment. In the illustrated embodiment, the IoT tag 600 includes an energy harvester 601, which is coupled to a capacitor 602 (such as an on-chip capacitor), a power management unit (PMU) 603, an integrated circuit 605, and a resident memory 606. The IoT tag 600 may further include at least one collecting antenna 610 and one transmitting antenna 620. In one embodiment, one or both of the antennas 610 and 620 are printed or etched into a substrate on which the IoT tag 600 is arranged. The collecting antenna 610 is coupled to the collector 601 and is used for energy collection, and the transmitting antenna 620 is used for wireless communication to transmit frequency data of the IoT tag 600. In one embodiment, the IoT tag 600 does not include any external DC power supply, such as a battery.

[0054] In one embodiment, integrated circuit 605 implements electronic circuits (such as memory, logic, RF, etc.) to perform various functions that allow communication using a low power communication protocol. Examples of such protocols include, but are not limited to LoRa, nRF, Z Wave, EnOcean, etc. In one embodiment, the integrated circuit 605 operates using the Bluetooth Low Energy (BLE) communication protocol.

[0055] The collector 601 is configured to provide multiple voltage levels to the integrated circuit 605 while maintaining a low load DC dissipation value. In an exemplary embodiment, the energy collector 601 may include a voltage multiplier (not shown) coupled to the collection antenna 610. The voltage multiplier may be a series connection of the DC outputs of multiple AC rectifier circuits, wherein all AC inputs are commonly connected to the antenna. The transmitting antenna 620 is configured as a receiving / transmitting antenna for the integrated circuit 605.

[0056] PMU 603 is coupled to capacitor 602 and is configured to regulate power to integrated circuit 605. Specifically, capacitor 602 has a very limited capacitance, so power consumption should be carefully maintained. This maintenance is performed to avoid capacitor 602 being exhausted and resetting integrated circuit 605.

[0057] In another embodiment, the PMU 603 may be further configured to provide multi-level voltage level indications to the integrated circuit 605. Such indications allow the integrated circuit 605 to determine the voltage supply status at any given moment when the capacitor 602 is charging or discharging. According to this embodiment, the PMU 603 may include a detection circuit controlled by the controller. The detection circuit includes different voltage reference threshold detectors, where only a subset of such detectors are active at a given time to perform detection.

[0058] The IoT tag 600 does not include a crystal oscillator to provide a reference clock signal. Instead, according to one embodiment, the reference clock signal used by the IoT tag 600 is generated using an over-the-air signal received from the transmit antenna 620.

[0059] The resident memory 606 is a centralized area of ​​the system IoT tag 600 that is continuously powered. Data to be retained during low power states is located in the resident memory 606. In one embodiment, the retention area is optimized to a subthreshold or near threshold voltage, such as 0.3V to 0.4V. This allows for reduced leakage of the retention cell and allows for extended retention time without data loss by dropping the capacitor voltage to a lower level.

[0060] In one embodiment, the integrated circuit 605 further includes a measurement circuit 607 configured to measure the LO frequency and the current oscillation frequency of the proximity sensor 621 (and the tag 600). Specifically, the measurement circuit 607 is configured to perform repeated measurements of the current oscillation frequency and determine the frequency deviation of the sensor 621 over time.

[0061] In one embodiment, the frequency measurement is performed by circuit 607 in IoT tag 600 using a reference oscillator (not shown) calibrated to a certain frequency. Such a reference oscillator can generate a corresponding measurement window. Measuring the LO frequency and / or the current oscillation frequency during this window is accomplished by counting the number of zero crossings of the oscillator signal occurring within the window. In an exemplary embodiment, each frequency measurement result can be a digital frequency word 640 stored in resident memory 606.

[0062] In an exemplary embodiment, the reference oscillator is calibrated to 2.4 GHz, which is the reference frequency derived from the oscillator. A measurement window can be derived from the reference oscillator, for example, with a length of 1 μs, 16 μs, 64 μs, etc. The longer the duration of the measurement window, the better its resolution. In a 1 μs window, the resolution of the frequency measurement is 1 MHz (2400 zero crossings for a 2.4 GHz reference frequency, 2401 zero crossings for a 2.401 GHz reference frequency, etc.). When a 64 μs measurement window is used, the resolution is about 15 kHz.

[0063] While longer measurement windows allow for better measurement resolution, the energy required to perform a measurement increases in direct proportion to the duration of the measurement window. Therefore, energy harvesting based on IoT tags (such as IoT tag 600) is limited in the length of measurements that a tag can perform within a given collection range.

[0064] In one embodiment, IoT tag 600 is configured to take measurements using a time window length directly related to the available energy of capacitor 602 and upload the measurement results to an analysis system, such as a cloud computing platform. The measurement results uploaded to the external analysis system can be further analyzed to determine any motion or proximity events.

[0065] For example, several subsequence measurements may be correlated or averaged to remove outliers or eliminate noise. Measurements that differ from one another (e.g., exceeding a predetermined threshold) may indicate a change in motion or proximity to the IoT tag 600. As a simple example, if a series of frequency measurements read "0000" and a new frequency measurement reads "0FFF," it may be determined that the frequency may have changed due to movement around the IoT. Determining whether the frequency has changed due to motion or movement near the IoT tag may be performed by the analysis system.

[0066] In one embodiment, the transmit antenna 620 is connected to the integrated circuit 605 via a proximity sensor 621 configured to detect frequency changes. It should be noted that the proximity sensor 621 is not necessarily a dedicated sensor, but a mechanism for detecting motion or proximity based on changes in oscillation frequency relative to the current LO frequency due to changes in motion or proximity near the IoT tag 600. For discussion purposes only, the proximity sensor 621 is shown as a discrete element.

[0067] In the example IoT tag 600, measurements and transmission of measurement data occur only when there is a predetermined threshold of harvested energy for transmission. As such, it is expected that sensor measurements from the LO cannot be made during energy harvesting. Assuming that each measurement consumes available energy at the capacitor 602, the period between measurements is related to the charging time of the capacitor or battery of the IoT tag 600, and depends on the availability, duty cycle, and strength of the excitation signal.

[0068] In an exemplary embodiment, the charging time of the capacitor 602 is measured in seconds. In this case, the IoT tag 600 may miss short-term events such as pickup events. Therefore, the IoT tag 600 is "blind" during the collection operation. Additionally, the transmission requires energy, so if each measurement result is to be transmitted separately, additional delays or "blind" intervals will be experienced during the charging time of the transmission operation. In an embodiment, the IoT tag 600 is configured to store data in a resident memory 640. Such data may include relevant frequency changes related to a predetermined number of events before a set of data is transmitted to, for example, a cloud-based system.

[0069] As described above, when measuring frequency offset values ​​relative to a reference oscillator, the measurement is affected by changes and variability of the reference. The stability of the reference oscillator is affected by various temperature changes and phase noise (PN) introduced into the measurement. By using an analysis system, PN can be averaged using longer measurements and / or averaging consecutive measurements. The analysis system can additionally compensate for certain factors, such as temperature effects, for example by retrieving data from a temperature sensor and applying appropriate corrections to the measurement results.

[0070] In one embodiment, the reference oscillator is configured to be minimally affected by the environment compared to the wandering frequency. For example, the reference oscillator may be implemented as: an internal ring oscillator; an internal LC oscillator, where the inductor L is located inside the chip and is therefore not affected by the environment; or an LC oscillator with an external inductor, which is not designed as an antenna and is relatively less affected by electromagnetic changes in the environment. It should be noted that the external inductor may have a better quality factor than the internal inductor, and therefore consumes less power than the LC oscillator with the internal inductor.

[0071] It should also be noted that the reference oscillator can either be dynamically calibrated on its own or it can be free running. When the reference oscillator is not calibrated, the operating range of the reference oscillator is known. In either case, the differential change in the frequency measurement can be accurately detected.

[0072] Figure 7 700 is an exemplary flow chart showing a method for detecting movement or approach using a proximity sensor such as an IoT tag according to an embodiment. The structure of the proximity sensor is as described above.

[0073] S710, measure the LO frequency. The LO frequency varies with the inductor element 210-L and the capacitor element 230 (both as Figure 2 The LO frequency depends on the environment and remains substantially constant when there are no environmental disturbances or forces acting on the proximity sensor. Each change in inductance due to the environment results in a frequency shift relative to the LO frequency. The measurement produces frequency measurement data that can be stored in resident memory.

[0074] S720, perform one or more continuous measurements of the current oscillation frequency of the sensor over the measurement window. In one embodiment, the measurement results are averaged as at least one of a mean, a median, a standard deviation, and a similar calculation of an average frequency value. The average measurement result can be determined based on a set time period (e.g., an average value of the frequency measured within 1 second), based on the number of measurements performed (e.g., after ten measurements are performed), etc. When the IoT tag is powered by harvested energy, the number of measurements can be based on the available power, so the time period for performing 10 measurements can vary depending on the storage and available power of the IoT tag.

[0075] S730, determining the frequency offset between the LO frequency and the continuous measurement, and determining whether the offset exceeds a predetermined threshold. The threshold can be either static or dynamic and based on environmental parameters. For example, the threshold can be adjusted based on the determined current operating temperature of the IoT tag.

[0076] S740, in one embodiment, the frequency measurement data is transmitted to an external analysis system located outside the IoT tag. In a certain embodiment, each measurement result is transmitted to the external analysis system. While this ensures accurate data, it requires additional energy, which may not always be available. In another embodiment, only the calculated average measurement result is transmitted. In another embodiment, only the measurement results that have been determined to exceed a predetermined threshold are transmitted to the external analysis system. The latter two embodiments require less transmission power than the first embodiment, but introduce delays when transmitting the data to the cloud-based system. In another embodiment, the number of transmissions can be adjusted based on the available power. In another embodiment, all LO frequency measurements are sent to the analysis system, and the determination of frequency offset and pickup / proximity events is determined by the analysis system.

[0077] In some embodiments, when the antenna is configured to increase the Q factor and save current using an external inductor, the transmission of the frequency measurement results is performed using a transmitting antenna that is also affected by the environment. In some embodiments, the same LO and antenna are used for transmission and sensing. In the latter case, the LO has an antenna tuning circuit configured to control the transmission frequency. In this case, the tuning setting should be set to a specific consistent value during the measurement. This may be different from the tuning value used for transmission. The value should remain consistent to allow the cloud-based system to accurately compare the measurement results. In some cases, such as when there are several external interferences at one frequency, the oscillator measurement is performed using different tuning frequencies. In such cases, the IoT tag should transmit not only the LO measurement value to the cloud-based system, but also the antenna tuning setting used during the measurement.

[0078] Transmitting antennas are also sensitive to their environment, so the transmission process usually involves dynamic calibration of the tuning setup to maintain a specific frequency. During a pick-up event, the frequency changes rapidly, as shown in Figure 4 and Figure 5 Due to the delay in calibration and the need to charge the capacitor, the transmission may fail during the pick-up event itself because the transmission will be performed at an uncalibrated frequency. Therefore, in one embodiment, the measurement data is transmitted several times to ensure an increased probability of successfully receiving the measurement data. In this embodiment, the frequency measurement includes a local timestamp of the time the measurement was completed rather than the time it was transmitted.

[0079] Figure 8 FIG. 8 is a network diagram 800 illustrating a deployment of an analysis system 810 according to an embodiment. Figure 8 As shown, IoT tag 820 is connected to gateway 830, which is further connected to cloud computing platform 840. Gateway 830 is a device configured to connect to IoT tag 820 (e.g., via BLE connection) and cloud computing platform 840 (e.g., via Wi-Fi or Ethernet connection). Please refer to the above for details on the operation of IoT tag 820.

[0080] The analysis system 810 may be installed in the gateway 830 or integrated in the cloud computing platform 840. The IoT tag 820 is a passive device that harvests energy from ambient sources and is configured to operate with minimal power requirements, so any analysis performed on the data collected by the IoT tag 820 (including frequency change and deviation analysis) can be offloaded to the analysis system 810.

[0081] In one embodiment, the gateway 830 is configured to perform energy-c (not shown), wherein the frequency measurements and their changes can be transmitted to the cloud-based analysis system 810. The analysis system 810 is configured to analyze the frequency measurement time series.

[0082] In one embodiment, the IoT tag 820 is powered on and off depending on energy conditions. Due to power requirements, such tags cannot robustly track measurement time series independently, but are still useful when coupled with a gateway 830 or a cloud-based platform 840. Another advantage of the analysis system 810 external to the IoT tag 800 itself is that the analysis system 810 can be configured to receive data points from multiple IoT tags. In one embodiment, the cloud computing platform 840 is configured to analyze the data of many co-located tags together to determine a common conclusion about the surrounding environment. In the event that the measurement results are noisy, the cloud computing platform 840 can additionally average and filter out the noise.

[0083] Gateway 830 may be any computing device, such as a smart phone, tablet computer, personal computer, router, etc.

[0084] Based on the received data, the analysis system 810 can perform various forms of analysis, compensate for drift, and perform noise filtering / averaging to be able to detect pickup or movement effects. In one embodiment, the analysis system 810 is configured to receive measurement data of multiple tags, especially co-located tags. In some cases, the analysis system determines which tags are co-located based on a priori information or based on receiving data from the same gateway (usually, the range of the gateway to the tags is limited to a few meters).

[0085] In one embodiment, the analysis system 810 is configured to infer co-location based on correlating measurement data from different IoT tags. In embodiments where the energy source of the IoT tags is non-static, the analysis system 810 deployed in the cloud computing platform 840 is configured to detect when several tags become powered together.

[0086] In one embodiment, the transmission of data is based on the power source that is also responsible for the pickup event. For example, a person approaches multiple tags with a smartphone that is used as a harvesting power source. The tags become energized together and begin transmitting to a cloud-based system. As the person moves closer to the tags, the LO frequency of each tag is affected. If the person picks up a single tag, the frequency of that tag changes more than the other tags. When the person puts down the tag and begins to move away, the frequency value after the drop is slightly different than the frequency value before the pickup because the tag orientation may have changed, as shown in FIG. Figure 4 . For the remaining tags, the frequency after being put down does not change. As the person continues to move away, all tags will stop transmitting when the energy is exhausted. Each of these sequences of events can be transmitted and analyzed by the analysis system 810 based on the frequency measurement data. In one embodiment, the analysis system 810 is configured to consider available per-tag test data from different stages of the tag's history.

[0087] In the various embodiments of the present disclosure, it can be implemented as hardware, firmware, software or any combination thereof. In addition, the software is preferably implemented as an application program tangibly embodied in a program storage unit or a computer-readable medium composed of components or certain devices and / or device combinations. The application program can be uploaded to a machine including any applicable architecture and executed by it. Preferably, the machine is implemented on a computer platform with hardware such as one or more central processing units ("CPU"), memory and input / output interfaces. The computer platform may also include an operating system and microinstruction codes. The various processes and functions described herein may be a part of the microinstruction code executable by the CPU or a part of the application program or any combination thereof, regardless of whether such a computer or processor is explicitly shown. In addition, various other peripheral units may be connected to the computer platform, such as an additional data storage unit and a printing unit. In addition, a non-temporary computer-readable medium is any computer-readable medium other than a temporary propagation signal.

[0088] As used herein, the phrase "at least one" followed by a list of items means that any one of the listed items may be used alone, or any combination of two or more of the listed items may be used. For example, if a system is described as including "at least one of A, B, and C," the system may include A alone; B alone; C alone; A and B combined; B and C combined; A and C combined; A, B, and C combined.

[0089] All examples and conditional language cited herein are intended for teaching purposes to help the reader understand the principles of the disclosed embodiments and the concepts contributed by the inventors to promote the art, and should be interpreted as not being limited to these specifically cited examples and conditions. Moreover, all statements herein referring to the principles, viewpoints, and embodiments of the disclosed embodiments and their specific examples are intended to cover equivalent schemes of their structures and functions. In addition, it is also intended to include currently known equivalent schemes and equivalent schemes developed in the future, that is, regardless of the structure, including any elements developed to perform the same function.

Claims

1. A proximity sensor based on a local oscillator frequency, comprising: an integrated circuit having at least one capacitive element; Antennas designed with inductive elements; as well as Inlays including integrated circuits and antennas; Wherein the capacitive element and the inductive element form a proximity sensor that oscillates at a local oscillator frequency, wherein the integrated circuit is configured to measure a frequency shift relative to the local oscillator frequency, wherein the frequency shift indicates detection of a nearby object.

2. The proximity sensor according to claim 1, wherein: The local oscillator frequency is within the communication signal range specified by the Bluetooth low energy standard.

3. The proximity sensor according to claim 1, wherein: The inductive element is at least an inductive interface impedance, and wherein the antenna is configured with an impedance matching structure to generate the inductance required for the local oscillator frequency.

4. The proximity sensor according to claim 1, wherein: When there is no environmental interference acting on the proximity sensor, the local oscillator frequency remains substantially constant, and wherein the local oscillator frequency is the last measured oscillation frequency of the proximity sensor.

5. The proximity sensor according to claim 1, wherein: The capacitive element is any one of the following: a capacitive interface impedance, a dedicated capacitor coupled to the integrated circuit, and a parasitic capacitance of one or more circuits included in the integrated circuit.

6. The proximity sensor according to claim 1, wherein: The frequency offset is a digital word, and wherein the digital word is transmitted through the antenna to an external analysis system.

7. The proximity sensor according to claim 1, wherein: The integrated circuit is further configured as: The frequency offset is measured during a measurement window based on the local oscillator frequency and one or more consecutive measurements of a current oscillation frequency of the proximity sensor.

8. The proximity sensor according to claim 1, wherein: The shift in the local oscillator frequency indicative of a detection of a nearby object is at least an initial increase in the local oscillator frequency by a threshold amount over a previous local oscillator frequency.

9. The proximity sensor according to claim 1, wherein: The excursion in the local oscillator frequency indicative of detection of a nearby object is at least an initial increase in the local oscillator frequency above a previous local oscillator frequency by a threshold amount, followed by a decrease in the local oscillator frequency below the previous local oscillator frequency.

10. The proximity sensor according to claim 1, wherein: The shift in the local oscillator frequency indicating detection of a nearby object is a result of a change in the inductance of the inductive element due to environmental effects caused by the nearby object.

11. The proximity sensor according to claim 1, wherein: The frequency shift is additionally indicative of at least one of: motion of a nearby object, motion of a proximity sensor, and proximity of a nearby object.

12. A battery-free IoT tag integrated with a proximity sensor, comprising: A transmitting antenna designed to have an inductive element; An integrated circuit having a capacitive element; Inlays including integrated circuits and antennas; a harvesting antenna connected to a harvester, wherein the harvester is configured to harvest energy from ambient signals; and accumulators, used to store the collected energy; Wherein the inductive element and the capacitive element form a proximity sensor that oscillates at a local oscillator frequency, and wherein a frequency deviation relative to the local oscillator frequency indicates detection of a nearby object.

13. The battery-free IoT tag according to claim 12, wherein: The inlay is a single-layer inlay, and the collecting antenna is disposed within the single-layer inlay.

14. The battery-free IoT tag according to claim 12, wherein: The battery-free IoT tag further comprises a reference oscillator, and wherein the integrated circuit is further configured to measure at least one current oscillation frequency using the reference oscillator.

15. The battery-free IoT tag according to claim 12, wherein: The inductive element is at least an inductive interface impedance, and wherein the transmitting antenna is configured with an impedance matching structure to generate the inductance required for the local oscillator frequency.

16. The battery-free IoT tag according to claim 15, wherein: When there is no environmental interference acting on the proximity sensor, the local oscillator frequency remains substantially constant, wherein the local oscillator frequency is the last measured oscillation frequency of the proximity sensor.

17. The battery-free IoT tag according to claim 12, wherein: The capacitive element is any one of the following: a capacitive interface impedance, a dedicated capacitor coupled to the integrated circuit, and a parasitic capacitance of one or more circuits included in the integrated circuit.

18. The battery-free IoT tag according to claim 12, wherein: The integrated circuit is further configured as: determining a digital word corresponding to a currently measured oscillation frequency of the proximity sensor; and The digital word is transmitted to an external analysis system via the transmission antenna.

19. The battery-free IoT tag according to claim 18, wherein: The frequency offset is determined by the external analysis system based on the local oscillator frequency and one or more consecutive measurements of a current oscillation frequency of the proximity sensor.

20. The battery-free IoT tag according to claim 12, wherein: The frequency shift is additionally indicative of at least one of: motion of a nearby object, motion of a proximity sensor, and proximity of a nearby object.

21. A method for detecting the proximity of a nearby object by a proximity sensor based on a local oscillator frequency, the proximity sensor comprising: An antenna designed to have an inductive element; An integrated circuit having a capacitive element; as well as an inlay comprising the integrated circuit and the antenna; wherein the inductive element and the capacitive element form a proximity sensor oscillating at a local oscillator frequency; The method comprises: determining a local oscillator frequency of the proximity sensor; measuring a current oscillation frequency of the proximity sensor; determining a frequency offset between the local oscillator frequency and the current oscillation frequency during a measurement window; and A determination is made as to whether the frequency shift exceeds a predetermined threshold, wherein a frequency shift exceeding the predetermined threshold indicates at least detection of a nearby object.

22. The method according to claim 21, wherein: When there are no environmental disturbances or forces acting on the proximity sensor, the local oscillator frequency remains substantially constant.

23. A proximity sensor based on a local oscillator frequency, comprising: An antenna designed to have an inductive element; an integrated circuit having a capacitive element, wherein the integrated circuit is configured to: determine a digital word corresponding to the measured current oscillation frequency and transmit the digital word via the antenna to an external analysis system, wherein the frequency offset is determined by the external analysis system; and an inlay comprising the integrated circuit and the antenna; wherein the inductive element and the capacitive element form a proximity sensor that oscillates at a local oscillator frequency, wherein the integrated circuit is configured to measure a current oscillation frequency of the proximity sensor, and wherein a frequency deviation relative to the local oscillator frequency indicates detection of a nearby object.

24. The proximity sensor according to claim 23, wherein: The frequency offset is determined by the external analysis system based on the local oscillator frequency and one or more consecutive measurements of a current oscillation frequency of the proximity sensor.

25. The proximity sensor of claim 23, wherein: When there is no environmental interference acting on the proximity sensor, the local oscillator frequency remains substantially constant, wherein the local oscillator frequency is the last measured oscillation frequency of the proximity sensor.

26. The proximity sensor of claim 23, wherein: The local oscillator frequency has a wandering frequency that depends on environmental disturbances acting on the proximity sensor.

27. The proximity sensor of claim 23, wherein: The capacitive element is any one of the following: a capacitive interface impedance, a dedicated capacitor coupled to the integrated circuit, and a parasitic capacitance of one or more circuits included in the integrated circuit.

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