SYSTEM AND METHOD FOR DETERMINING DEVICE LOCATION CHARACTERISTICS USING CHANNEL STATE INFORMATION - Patent application

Abstract

Systems and methods are provided for determining device location characteristics of a wireless device, such as a smartphone. The system includes a processor configured to receive wireless signals via a plurality of wireless receivers disposed in a monitoring area. The wireless signals are transmitted by the wireless device in proximity to a subject. The wireless signals include an identifier, such as a Bluetooth identifier, corresponding to the wireless device. The processor is further configured to determine a CSI of the subject based on the received wireless signals. The processor is further configured to determine one or more device location characteristics based on the determined CSI and a body mass signature corresponding to the identifier. The one or more device location characteristics may include a relative location of the wireless device on the subject and / or a status of the associated subject.

Description

[Technical field]

[0001] The present disclosure is generally directed to systems and methods for determining device location characteristics using channel state information. [Background technology]

[0002] Contact tracing smartphone applications share wireless identification information (such as Bluetooth identifiers) with wireless receivers to assess potential close contacts. However, in some situations, an individual may accidentally pick up and carry a smartphone owned by another person. This may occur in shared work areas (such as in an office or school) where individuals are using similar smartphones. This miscarriage may lead to problems with contact tracing, since the wireless information shared by the contact tracing application corresponds to the phone's owner, not the current carrier. Previously disclosed systems have attempted to address this issue by associating identification information with a heat signature corresponding to the phone's owner. However, many sensor systems lack the high-resolution thermal sensors necessary to generate a thermal image of sufficient resolution to compare to the heat signature. Summary of the Invention [Problem to be solved by the invention]

[0003] Therefore, there is a need in the art for alternative systems and methods for ensuring that a smart phone is held by its rightful owner. [Means for solving the problem]

[0004] The present disclosure is directed to determining device location characteristics of a wireless device based on a comparison of a subject's channel state information (CSI) and a body-mass signature. The CSI describes how a wireless signal transmitted by a device propagates to multiple wireless receivers and can incorporate various effects, such as loss, phase shift, etc. Studies have shown that these effects correlate with the body mass index (BMI) of the subject through which the wireless signal passes, among other factors. The measured CSI can be aggregated and processed to determine the subject's body mass signature. Thus, if the subject's measured CSI corresponds to a known body mass signature of a particular individual, the system can infer that the subject is a particular individual. Furthermore, since the measured CSI varies depending on the relative location of the wireless device on the user (such as a front pocket or a back pocket), the CSI can be used to determine the relative location of the wireless device.

[0005] In one aspect, multiple wireless receivers, such as Bluetooth receivers, are placed in a monitoring area, such as an office space. Each wireless receiver may be placed in a sensor bundle used in a connected lighting system. As a subject carrying a wireless device moves through the monitoring area, the wireless device transmits a radio frequency (RF) wireless signal that is received by the wireless receiver. The wireless signal includes information that identifies the wireless device, such as a Bluetooth identifier. The system then calculates a CSI corresponding to the subject based on the wireless signal received by the wireless receiver. The system may then determine various device location characteristics based on the determined CSI and one or more stored body mass signatures. The stored body mass signatures may correspond to an individual or may correspond to a more general body type (e.g., tall and average BMI, short and low BMI, etc.). In one example, the system may determine whether the subject is the rightful owner of the wireless device. If not, the system may generate an alarm signal and / or reduce the functionality of the wireless device, such as by locking the wireless device. Additionally, the system may utilize the CSI to determine the relative location of a wireless device on a target.

[0006] Additionally, the aforementioned sensor bundle may include a thermopile sensor configured to capture thermal data used to supplement the CSI to determine device location characteristics. For example, thermal data of sufficient resolution may be used to estimate the location of an object and a wireless device corresponding to the object. In a further example, the thermal data may be used to determine the orientation of the object, such as the direction the object is facing. The orientation of the object may be particularly useful in determining the relative location of the wireless device (front pocket, back pocket, right pocket, left pocket, backpack, handbag, etc.). In another example, this location information may be based on commissioned layout data corresponding to multiple wireless receivers. When the wireless receivers are placed and commissioned, the commissioned layout data stores the placement of the wireless receivers.

[0007] A body mass signature used to compare with the measured CSI may be generated by the system as part of a training scheme. Similar to the monitoring areas described above, multiple wireless training receivers may be placed in a training area. The training area may be a hallway, a hallway, a stairwell, a security checkpoint, or other area where a subject will most likely be carrying a wireless device. In the training area, the wireless training receiver receives wireless training signals transmitted by the wireless device. The wireless training signals include an identifier, such as a Bluetooth identifier. The received wireless training signals are processed to determine a CSI for each transmission. The CSI is then aggregated and processed to create a body mass signature. The body mass signature is associated with an identifier such that the identifier can be used to obtain a body mass signature corresponding to the subject. The association of the body mass signature and the identifier may be stored in memory. In some examples, rather than generating a body mass signature for each expected subject, an array of stock body-mass signatures corresponding to different body types and BMIs may be stored in memory.

[0008] Further, the training sensor bundle may include a training thermopile sensor configured to capture thermal training data used to supplement the CSI to determine a body mass signature. For example, thermal training data of sufficient resolution may be used to estimate the location of an object and a wireless device corresponding to the object. In a further example, the thermal training data may be used to determine the orientation of the object, such as the direction the object is facing. The orientation of the object may be particularly useful in determining the relative location of the wireless device on the object (front pocket, back pocket, backpack, handbag, etc.). When collecting training CSI to generate a body mass signature, the training CSI corresponding to the wireless signal passing through the object is most relevant. Thus, by determining the relative location of the wireless device on the object, the thermal training data may be used to determine the importance of different aspects of the training CSI.

[0009] In many cases, the subject is a human individual carrying a wireless device, such as a smartphone, tablet computer, smart watch, smart glasses, etc. Thus, the systems and methods may be used to track the location of the subject, determine the relative location of the wireless device on the subject, and verify that the subject is the rightful owner of the wireless device. In a further example, the subject may be an animal equipped with an active wireless tracking tag. In this example, the systems and methods may be used to track the location of the animal, determine the relative location of the wireless device on the animal, and verify that the tracking tag is worn by the correct animal. This example may be further extended to inanimate objects for shipment tracking or inventory control.

[0010] In general, in one aspect, a system is provided for determining one or more device location characteristics of a wireless device. In one example, the wireless device is a smartphone. The system includes a processor. The processor is configured to receive wireless signals via a plurality of wireless receivers disposed in a monitoring area. According to one example, the plurality of wireless receivers are Bluetooth receivers or ultrawideband (UWB) receivers.

[0011] The wireless signal is transmitted by a wireless device in proximity to the object, the wireless signal including an identifier, the identifier corresponding to the wireless device.

[0012] The processor is further configured to determine a CSI of the target, the CSI being based on the received wireless signal.

[0013] The processor is further configured to determine one or more device location characteristics based on the determined CSI and the body mass signature. The body mass signature is associated with the identifier. In one example, the one or more device location characteristics include a relative location of the wireless device on the subject. The relative location may correspond to one of a front pocket of the subject, a back pocket of the subject, a handbag of the subject, or a backpack of the subject. In another example, the one or more device location characteristics include an associated subject status.

[0014] According to one example, the processor is further configured to generate an alarm signal. The alarm signal is generated based on a status of the associated object. According to a further example, the processor is further configured to limit one or more operational aspects of the wireless device based on the status of the associated object.

[0015] According to one example, the one or more device location characteristics are further based on commissioned layout data, the commissioned layout data corresponding to a plurality of wireless receivers.

[0016] According to one example, the processor is further configured to receive thermal monitoring data, the thermal monitoring data being collected by a thermopile monitoring sensor, the thermal monitoring sensor being disposed in the monitoring area, and in this example, the one or more device location characteristics are further based on the thermal monitoring data.

[0017] According to an example, the processor is further configured to receive a wireless training signal via a plurality of wireless training receivers disposed in the training area. The wireless training signal is transmitted by a wireless device. The wireless training signal includes an identifier. The processor is further configured to determine a training CSI based on the received wireless training signal. The processor is further configured to determine a body mass signature based on the training CSI. The processor is further configured to associate the body mass signature with the identifier.

[0018] According to one example, the processor is further configured to receive thermal training data. The thermal training data is collected by a thermopile training sensor. The thermopile training sensor is disposed in the training area. Alternatively, the processor is further configured to receive light detection and ranging (LIDAR) training data. The LIDAR training data is collected by a LIDAR training sensor. The LIDAR training sensor is disposed in the training area. In this example, the body mass signature is further based on the thermal data or the LIDAR training data.

[0019] In general, in another aspect, a method is provided for determining one or more device location characteristics of a wireless device. The method includes receiving wireless signals transmitted by a wireless device proximate to a subject via a plurality of wireless receivers disposed in a monitoring area, the wireless signals including an identifier corresponding to the wireless device. The method further includes determining a CSI of the subject based on the received wireless signals. The method further includes determining a device location characteristic based on the determined CSI and a body mass signature, the body mass signature corresponding to the identifier.

[0020] According to an example, the method may further include receiving a wireless training signal transmitted by the wireless device via a plurality of wireless training receivers disposed in the training area, the wireless training signal including the identifier. The method may further include determining a training CSI based on the received wireless training signal. The method may further include determining a body mass signature based on the training CSI. The method may further include associating the body mass signature with the identifier.

[0021] In various implementations, a processor or controller can be associated with one or more storage media (e.g., volatile and non-volatile computer memory, such as ROM, RAM, PROM, EPROM, and EEPROM, floppy disks, compact disks, optical disks, magnetic tape, Flash, OTP-ROM, SSD, HDD, etc., collectively referred to herein as "memory"). In some implementations, these storage media can be encoded with one or more programs that, when executed on one or more processors and / or controllers, perform at least a portion of the functions discussed herein. The various storage media can be fixed within a processor or controller, or can be portable such that one or more programs stored on those storage media can be loaded into a processor or controller to implement various aspects discussed herein. The term "program" or "computer program" is used herein in a generic sense to refer to any type of computer code (e.g., software or microcode) that can be employed to program one or more processors or controllers.

[0022] It should be understood that all combinations of the above-mentioned concepts and additional concepts discussed in more detail below (provided that such concepts are not mutually inconsistent) are contemplated as part of the inventive subject matter disclosed herein. In particular, all combinations of the claimed subject matter described at the end of this disclosure are contemplated as part of the inventive subject matter disclosed herein. It should also be understood that the terms explicitly employed herein, which may also appear in any disclosure incorporated by reference, should be given the meaning most consistent with the particular concepts disclosed herein.

[0023] These and other aspects of various embodiments will be apparent from and elucidated with reference to the embodiment(s) described hereinafter. [Brief description of the drawings]

[0024] In the drawings, like reference characters generally refer to the same parts throughout the different views. Also, the drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of various embodiments. [Figure 1] 1 is a probability density distribution graph of body mass index (BMI) and channel gain, according to an example. [Diagram 2] FIG. 1 is an illustration of an embodiment of a system deployed in a monitoring area, according to an example. [Diagram 3] FIG. 1 is an illustration of an aspect of a system deployed in a training area, according to an example. [Figure 4] FIG. 1 is an illustration of a database pairing identifiers with body mass signatures and thermal profiles, according to an example. [Diagram 5] FIG. 1 is a schematic illustration of an embodiment of a monitor, according to an example. [Figure 6] 1 is a flowchart of a method for determining one or more device location characteristics, according to an example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0025] The present disclosure is directed to determining device location characteristics of a wireless device based on a comparison of a subject's channel state information (CSI) and a body mass signature. The CSI represents the wireless signal transmitted by the device as it propagates to multiple wireless receivers and can reflect various effects, such as loss, phase shift, etc. Studies have shown that these effects correlate with the body mass index (BMI) of the subject through which the wireless signal passes, among other factors. The measured CSI can be aggregated and processed to determine the subject's body mass signature. Thus, if the subject's measured CSI corresponds to a known body mass signature of an individual, the system can infer that the subject is that individual. Furthermore, since the measured CSI varies depending on the relative location of the wireless device on the user (such as a front pocket or a back pocket), the CSI can be used to determine the relative location of the wireless device.

[0026] FIG. 1 is a probability density distribution graph of BMI and transmission path gain. The graph includes three BMI ranges: 18.5-24.9 (classified as "normal"), 25.0-29.5 (classified as "overweight"), and 30 or more (classified as "obese"). Each range correlates to a different probability density function (PDF). The plotted PDF for each BMI range represents the relative likelihood of a gain experienced by a radio frequency (RF) signal passing through the subject. For example, if the subject is a person with a "normal" BMI, then an RF signal passing through the subject is most likely to experience a gain of about -52 dB. In a further example, if the subject is a person with an "overweight" BMI, then an RF signal passing through the subject is most likely to experience a gain of about -55 dB. As a still further example, if the subject is an individual with an "obese" BMI, then an RF signal passing through the subject will most likely experience a gain of approximately -61 dB.

[0027] Furthermore, the potential range of gain is also affected by BMI. For example, a subject with a "normal" BMI has a transmission line gain range of approximately -42 dB to -65 dB. Further, a subject with an "overweight" BMI has a transmission line gain range of approximately -50 dB to -62 dB. And, a subject with an "obese" BMI has a transmission line gain range of approximately -47 dB to -75 dB. These measurable correlations between BMI and transmission line gain allow for probabilistic prediction of a subject's identity based on the transmission line gain it imparts to the RF signal.

[0028] FIG. 2 is an illustration of a system 10 for determining one or more device location characteristics 102 of a wireless device 100 relative to a target S located in a monitoring area MA. As shown in FIG. 2, the system 10 includes four sensor bundles 400a-400d. Each of the sensor bundles 400a-400d may be embedded in or used in conjunction with a connected lighting system. Each sensor bundle 400a-400d includes a receiver (RX) 200a-200d and a thermopile sensor (Therm.) 300a-300d. In one example, the receivers 200a-200d are configured to receive wireless signals 104a1-104b6 transmitted by the wireless devices 100a, 100b, such as a Bluetooth receiver or an ultra-wideband (UWB) receiver. The wireless signals 104a1-104b6 are RF signals configured to carry identifiers 106a, 106b (not shown). The identifiers 106a, 106b represent the wireless devices 100a, 100b transmitting the wireless signals 104a1-104b6 that are received by the receivers 200a-200d. In one example, the identifiers 106a, 106b may be Bluetooth identifiers, such as Bluetooth device addresses, that are assigned to the corresponding wireless devices 100a, 100b during manufacture. The identifiers 106 may indicate an owner (e.g., a legitimate owner) of the respective wireless devices 100 represented by the identifiers 106. In an embodiment, the identifiers 106 may be linked or associated, for example in the database 150, with the owner of the respective wireless devices 100 represented by the identifiers 106.

[0029] In the example of Fig. 2, a first subject Sa holds a first wireless device 100a on the left side of his body. The first wireless device 100a is assigned a first identifier 106a. The first wireless device 100a transmits wireless signals 104a1-104a5. Each of the wireless signals 104a1-104a5 carries the first identifier 106a. Thus, the first identifier 106a allows the wireless signals 104a1-104a5 to be identified as being transmitted by the first wireless device 100a.

[0030] Further to the above example of Fig. 2, a second subject Sb holds a second wireless device 100b on the right side of his body. The second wireless device 100b is assigned a second identifier 106b. The second wireless device 100b transmits wireless signals 104b1-104b6. Each of the wireless signals 104b1-104b6 carries the second identifier 106b. Thus, the second identifier 106b allows the wireless signals 104b1-104b6 to be identified as being transmitted by the second wireless device 100b.

[0031] The sensor bundles 400a-400d further include thermopile monitoring sensors 300a-300d. Each of the thermopile monitoring sensors 300a-300d is configured to capture heat map information for a particular portion of the monitoring area MA. This heat map information may be aggregated into thermal monitoring data 124 for the entire monitoring area MA. The thermal monitoring data 124 may include an array of pixels indicative of various temperatures found within the monitoring area MA. For example, a portion of the thermal monitoring data 124 corresponding to a human subject S or an active wireless device 100 will exhibit a higher temperature than a piece of furniture. Thus, the thermal monitoring data 124 may be used to estimate the presence, location, and orientation of the subjects Sa, Sb and the wireless devices 100a, 100b within the monitoring area MA. For example, a subject S moving across a room may be assumed to be facing in the direction of its movement, so that the orientation of the subjects Sa, Sb may be determined based on the movement pattern within the monitoring area MA. In another example, the orientation of the subject S may be based on the exhaled breath seen in the thermal monitoring data 124.

[0032] In some examples, at least one of the one or more thermopile sensors 300a-300d may be a low-resolution (e.g., 3 m or higher) single pixel thermopile (SPT) sensor. In these examples, the amount of useful information provided by the thermopile sensors 300a-300d is limited. Thus, the system 10 may use alternative means, such as the commissioned layout data 128, the identifiers 164, and the CSI 108, to determine the presence and location of the objects Sa, Sb and the wireless devices 100a, 100b.

[0033] In a preferred example, at least one of the one or more thermopile monitoring sensors 300a-300d may be a multipixel thermopile (MPT) sensor. MPT sensors typically have a much higher resolution (e.g., as low as 10 centimeters) than SPT sensors and therefore can be used to determine the presence, location, and orientation of the objects Sa, Sb and the wireless devices 100a, 100b.

[0034] Each of the sensor bundles 400a-400d is communicatively coupled to the monitor 600 via any combination of wired and / or wireless connections. The monitor 600 includes a processor 125 and a memory 175 (shown in FIG. 5). The monitor 600 is configured to receive, store, and process the wireless signals 104a1-104b6 captured by the receivers 200a-200d and the thermal monitoring data 124 captured by the thermopile monitoring sensors 300a-300d. The monitor 600 may be any type of computing device, such as a desktop computer, a laptop computer, a server, etc. The monitor 600 may be located locally or remotely with respect to the monitoring area MA.

[0035] In some examples, one or more of the receivers 200a-d and / or thermopile sensors 300a-d may be discretely located away from the sensor bundles 400a-d. In these examples, the receivers 200a-d and / or thermopile monitoring sensors 300a-d may be communicatively coupled directly to the monitor 600.

[0036] As described in more detail below, the monitor 600 uses the wireless signals 104a1-104b6 to determine the CSI 108a, 108b corresponding to each subject S, Sb. As described in connection with FIG. 1, the wireless signals 104a1-104b6 traveling through the body of the subject S, Sb experience losses. These losses correlate to the BMI of each subject S, Sb. The monitor 600 may then compare the CSI 108a, 108b of each S, Sb to the stored body mass signature 112 to determine one or more device location characteristics 102, such as a relative location 112 of the wireless device 100 or a status 114 of the associated subject. The relative location 112 indicates the location of the wireless device 100 on the subject S carrying the wireless device 100. The relative location 112 may characterize whether the wireless device 100 is carried in a front pocket, a back pocket, a right handbag, a left handbag, a backpack, etc. of the subject S. The associated object status 114 indicates whether the wireless device 100 is currently carried by a legitimate owner by comparing the CSI 108 measured for the wireless device 100 with a stored body mass signature 110 associated with the identifier 106 of the wireless device 100. The device location characteristics 102 may include additional information regarding the location of the wireless device 100. For example, the device location characteristics 102 may indicate coordinate location information, global positioning system (GPS) information, latitude and longitude values, a location within a particular building or structure, a location relative to other wireless devices 100, a location relative to aspects of a connected lighting system (such as the sensor bundle 400), changes in location over time, etc.

[0037] As shown in FIG. 2, the first wireless device 100a transmits wireless signals 104a1-104a4. Those skilled in the art will understand that this figure and description are for illustrative purposes only. The first target Sa holds the wireless device 100a in his left hand. Due to the positioning of the wireless device 100a and the first target Sa, the wireless signal 104a1 travels from the wireless device 100a to the first receiver 200a without being affected by the body of the first target Sa. Thus, the wireless signal 104a1 does not provide information that helps the monitor 600 determine the CSI 108a of the first target Sa. Conversely, both the wireless signals 104a2, 104a3 pass through the first target Sa before being captured by the second receiver 200b and the third receiver 200c, respectively. Therefore, the wireless signals 104a2, 104a3 provide information that helps the monitor 600 determine the CSI 108a of the first target Sa. The wireless signal 104a4 travels through the body of the first target Sa and then reflects off the ground as a wireless signal 104a5. The wireless signal 104a5 is then received by the third receiver 200c. Because the wireless signal 104a4 traveled through the body of the first target Sa before reflecting off the ground, the wireless signal 104a5 reflects the body-mass impact (transmission loss, reflection, scattering, delay, etc.) of the target Sa on the wireless signal 104a4. This body-mass impact allows the system 10 to determine the CSI 108a of the first target Sa. The wireless signals 104a3-104a5 illustrate an exemplary multipath transmission between the first wireless device 100a and the third receiver 200c.

[0038] As also shown in FIG. 2, the second wireless device 100b transmits wireless signals 104b1-104b4. Those skilled in the art will understand that this illustration and description are for illustrative purposes only. The second subject Sb holds the second wireless device 100ab in his right hand. Due to the positioning of the second wireless device 100b and the second subject Sb, the wireless signal 104b1 travels from the wireless device 100b to the fourth receiver 200d without being affected by the body of the second subject Sb. Thus, the wireless signal 104b1 does not provide information that helps the monitor 600 determine the CSI 108b of the second subject Sb. Conversely, both wireless signals 104b2, 104b3 pass through the second subject Sb before being captured by the third receiver 200c and the fourth receiver 200d, respectively. When passing through the second target Sb, the wireless signal 104b3 splits into a wireless signal 104b5, which is received by the third receiver 200c, and a wireless signal 104b6, which is received by the fourth receiver 200d. Thus, the wireless signals 104a5, 104a6 provide information that helps the monitor 600 determine the CSI 108b of the second target Sb. The wireless signal 104b2 travels through the body of the second target Sb and then reflects from the ground as a wireless signal 104b4. The wireless signal 104b4 then travels through the body of the second target Sb and is received by the third receiver 200c. Because the wireless signal 104b4 traveled through the body of the second target Sb before reflection and the wireless signal 104b4 traveled through the body of the second target after reflection, the wireless signal 104b4 also provides information that helps the monitor 600 determine the CSI 108b of the second target Sb.

[0039] The CSI 108 between the receiver 200 and the wireless device may be defined by Equation 1 below: TIFF2025505773000002.tif17127, where x M are the wireless signals 106 transmitted by the M wireless devices 100, and y Nis the wireless signal 106 received by the N receivers 200, and h N,M is the CSI 108 between the M wireless devices 100 and the N receivers 200, and n M is the noise experienced by the wireless signal 106 when transmitted by the M wireless devices 100. As will be described below, the system 10 may be configured to detect h N,M The CSI 108 corresponding to i receivers 200 and j wireless devices 100 may be defined by Equation 2 below: TIFF2025505773000003.tif11128, where L i is the position of the receiver 200, and P j is the position of the object S, and B j is the location of the wireless device 100. In some examples, P j and B. j is determined by analyzing the thermal monitoring data 124 collected by the thermopile monitoring sensor 300, particularly the multi-pixel thermopile array. i , P j , and B j may be used to determine whether a target S is located between the receiver 200 and the wireless device 100. If so, the wireless signal 104 captured at the receiver 200 may be used to determine the CSI 108 of the target S.

[0040] In an alternative example, the determination of the location of the receiver 200 and the location of the wireless device 100 may be determined using the commissioning layout data 128. When the receiver 200 is commissioned over the monitoring area MA, the receiver 200 may be physically located and electronically configured. As part of the commissioning process, the physical location of the receiver 200 may be stored as part of the commissioning layout data 128. For example, the commissioning layout data 128 may include or indicate location and / or position data of one or more receivers 200 located within an area (e.g., the monitoring area MA) or environment determined and identified during the commissioning process. Thus, the L i may be obtained by retrieving the position of the receiver 200 from the commissioned layout data 128. The location of the wireless device 100 may then be determined by triangulating the wireless signals 104 transmitted by the wireless device 100 and received by the receiver 200.

[0041] Furthermore, the CSI 108 can also be described by the following Equation 3: TIFF2025505773000004.tif9129 Here, BM j is the body mass effect of the jth subject S, and d i,j is the distance from the i-th receiver 200 to the j-th wireless device 100. Therefore, h i,j The probability density function of may be defined as follows in Equation 4: TIFF2025505773000005.tif8116

[0042] When the wireless device 100 is picked up by a subject S and carried through a monitoring area MA, the system 10 can infer the body mass effect BM of the subject S from the time series data of the wireless signal 104 captured by the receiver 200. The probability that the rightful owner is carrying the wireless device 100 can be determined by the following Equations 5 and 6: TIFF2025505773000006.tif9119TIFF2025505773000007.tif8126

[0043] Thus, the CSI 108 between the K different receivers 200 and the wireless device 100 may be combined. From the combined CSI 108, a total body mass effect BM of the subject may be determined. The total body mass effect BM of the subject may then be compared to a stored body mass signature 110 associated with the identifier 106 embedded in the wireless signal 104. Based on this comparison, the system 10 determines a status 114 of the associated subject of the wireless device 100.

[0044] In some examples, the determination of the status 114 of the associated object may be aided by the stored body mass signature 110 and the stored thermal profile 130 corresponding to the identifier 106. The thermal profile 130 represents the thermal characteristics of the particular object S associated with the identifier 106. If the object S is a human, a non-human animal, or a powered device (such as a robot), the object S generates heat in a pattern that is unique to the physical characteristics of the object S. These thermal profiles 130 may be used to identify the object S. The thermal profile 130 may include feature data such as cluster area, peak temperature, etc. The cluster area is defined by a group of pixels of similar temperature in the thermal profile 130. If the object S is a human, a group of pixels that are close to the human body temperature can be used to define the overall shape of the object S. Similarly, the peak temperature captures the highest temperature of a particular pixel over time. Various different types of objects S may have different peak temperatures. For example, a pixel corresponding to a human will likely have a different peak temperature than a pixel corresponding to a non-human powered device. The system 10 may compare the thermal monitoring data 124 captured by the thermopile monitoring sensor 300 to the thermal profile 130 to determine the status 114 of the associated object.

[0045] If the associated object status 114 indicates that the object S is the rightful owner of the wireless device 100, typically no further action is required. However, if the associated object status 114 indicates that the wireless device 100 is carried by an object S other than the rightful owner, the monitor 600 may generate one or more responses. In one example, the response may be that the wireless device 100 generates an alarm signal 116. The alarm signal 116 may be embodied in a number of different ways. For example, the alarm signal 116 may trigger the monitor 600 and / or the wireless device 100 to provide visual or audio notification(s). Additionally, the alarm signal 116 may be transmitted to a remote monitoring device to inform a remote individual that the wireless device 100 in the monitoring area MA is carried by a non-owner object S.

[0046] In another example, the response may be to generate a limit operation signal 132 by the monitor. The limit operation signal 132 is configured to limit one or more operational aspects 118 of the wireless device 100 if the system 10 learns that the wireless device 100 is carried by a subject S other than the legitimate owner. In one example, the limit operation signal 132 locks the user interface (e.g., touch screen) of the wireless device 100. In another example, the limit operation signal 132 restricts access to certain sensitive applications and / or files, such as banking applications, email applications, texting applications, etc. In another example, the limit operation signal 132 may restrict use of certain hardware of the wireless device 100, such as the camera, speaker, or microphone.

[0047] In some examples, the CSI 108 is used to determine the relative location 112 of the wireless device 100 on the subject S. In one example, the relative location 112 of the wireless device 100 may be determined by analyzing the CSI 108 to determine which wireless signals 104 experience loss due to body mass effects. For example, if the CSI 108 indicates that there is no body mass effect on the wireless signals 104 captured by the first receiver 200 to the back of the subject S, but also indicates that there is a large body mass effect on the wireless signals 104 captured by the second receiver to the front of the subject S, the system 10 may determine that the wireless device 100 is in the back pocket of the subject S. This determination may be aided by analyzing the thermal monitoring data 124 to determine the orientation of the subject S, i.e., determining which way the subject is facing. For example, the subject S may be assumed to be facing in its direction of movement, and thus the orientation of the subject S may be determined based on the pattern of movement within the monitoring area MA. In another example, the orientation of the subject S may be based on the breath detected in the thermal monitoring data 124, since the subject S is presumed to be facing in the direction of its breath.

[0048] In the example of FIG. 2, each wireless device 100 includes a single antenna configured to transmit the wireless signal 104. However, in some further examples, each wireless device 100 may include two or more antennas. For example, if the wireless device 100a is embodied as a smartphone, the wireless device 100a may include a first antenna positioned on the front side of the smartphone configured to transmit the wireless signal 104a1 and a second antenna positioned on the back side of the smartphone configured to transmit the wireless signal 104a2. The wireless signals 104a1, 104a2 are captured by the wireless receiver 200. The processor 125 may then analyze the wireless signals 104a1, 104a2 to determine the orientation of the smartphone. For example, if the wireless signal 104a1 is received by the wireless receiver 200 after the wireless signal 104a2, then the back side of the smartphone is likely facing the wireless receiver 200. With this knowledge, the processor 125 may analyze the thermal monitoring data 124 to determine which antenna is facing the target S. The system 10 may then select an antenna facing the subject S to determine a CSI 108 corresponding to the subject S. Utilizing an antenna facing the subject S maximizes the influence of the subject S's body on the transmitted wireless signal 104, and therefore also maximizes the influence of the subject S's body on the CSI 108 derived from the transmission and reception of the wireless signal 104.

[0049] 3 is an illustration of further aspects of the system 10. These aspects are directed to determining a body mass signature 110 of a subject S located in a training area TA based on a training CSI 122. The training area TA is preferably a highly trafficked area in which the subject S will be carrying a corresponding wireless device 100. For example, if the monitoring area MA comprises a portion of an office building, the training area TA may be a hallway, a corridor, a staircase, a security checkpoint, a hallway, a lobby, an elevator, or a break room.

[0050] FIG. 3 illustrates two training sensor bundles 450a, 450b communicatively coupled to the monitor 600 via any combination of wired and / or wireless connections. Each training sensor bundle 450a, 450b includes a corresponding training receiver (Rx) 250a, 250b, a corresponding thermopile training sensor (Therm.) 350a, 350b, and a corresponding light detection and ranging (LIDAR) training sensor (LIDAR) 650a, 650b. Each of the training sensor bundles 450a, 450b may be embedded in or used with a connected lighting system. The training receivers 250a, 250b are configured to receive wireless training signals 120a1-120a4 transmitted by the wireless device 100. In some examples, the wireless training signals 120a1-120a4 are the same as the wireless signal 104 illustrated in FIG. 2. Wireless signals 120a1-120a4 are RF signals configured to carry identifier 106 (not shown). Identifier 106 represents wireless device 100 transmitting wireless training signals 120a1-120a4 that are received by receivers 250a, 250b. As with the example of Figure 2, identifier 106 may be a Bluetooth identifier, such as a Bluetooth device address, that is assigned to wireless device 100 during manufacture.

[0051] As also shown in FIG. 3, the wireless device 100 transmits wireless signals 104a1-104a4. Those skilled in the art will appreciate that this illustration and description are for illustrative purposes only. The subject S holds the wireless device 100 in his left hand. Due to the positioning of the wireless device 100 and the subject S, the wireless training signal 120a3 travels from the wireless device 100 to the first training receiver 250a without being affected by the body of the subject S. Furthermore, the wireless training signal 120a2 is reflected by the floor as the wireless training signal 120a6 without passing through the body of the subject S. Thus, the wireless training signals 120a2, 120a3, 120a6 do not provide information that helps the monitor 600 determine the training CSI 122 of the subject S. Conversely, both the wireless signals 120a1, 120a4 pass through the subject S before being captured by the second training receiver 200b. Wireless training signal 120a1 is reflected off the floor as wireless training signal 120a5 before being captured by second training receiver 250b. Thus, wireless training signals 120a1, 120a4, 120a5 provide information that helps monitor 600 determine training CSI 122 of subject S.

[0052] The sensor training bundle 450a, 450b further includes a thermopile training sensor 350a, 350b. The thermopile training sensor 350a, 350b is configured to capture thermal training data 126 of the training area TA. The thermal training data 126 may be used to estimate the presence and location of the object S and the wireless device 100. The thermal training data 126 may also be used to estimate the orientation of the object S. In a further example, the thermal training data 126 may be used to derive a thermal profile 130 of the object S. The thermal profile 130 may include characteristics such as cluster area, peak temperature, etc. The thermal profile 130 may be associated with the identifier 106 of the wireless device 100. In a preferred example, at least one of the thermopile training sensors 350a, 350b may be an MPT sensor.

[0053] The sensor training bundles 450a, 450b further include LIDAR training sensors 650a, 650b. The LIDAR training sensors 650a, 650b are configured to capture LIDAR Training Data 134. The LIDAR Training Data 134 may be a point cloud that maps aspects of a training area (TA) that includes a target S. Similar to the thermal training data 126, the LIDAR Training Data 134 may be used to estimate an orientation of the target S.

[0054] Once the monitor 600 acquires the wireless training signals 120a1-120a6, the system 10 may determine the training CSI 122 according to Equation 1. The system may then generate a body mass signature 110 of the subject S according to Equations 2-6. The body mass signature 110 is associated with the identifier 106 of the wireless device 100.

[0055] 4 illustrates a Database 150 that stores relationships between associated Identifiers 106 (such as Bluetooth Identifiers) and Body-Mass Signatures 110. When a subject S carrying a wireless device 100 is under analysis, the system 10 extracts the Identifier 106 from a wireless signal 104 transmitted by the wireless device 100. Using the Identifier 106, the system 10 can obtain a Body-Mass Signature 110, derived from a training CSI 124, for comparison with the CSI 108 of the subject S carrying the wireless device 100 to determine the status 114 of the associated subject. In some examples, the Body-Mass Signature 110 is not derived directly from the training CSI 124, but is a more general Body-Mass Signature 110 corresponding to a particular body-type and / or characteristics (e.g., tall and average BMI, short and low BMI, etc.).

[0056] In some examples, the database 150 also stores a relationship between the associated identifier 106 and a thermal profile 130. The thermal profile 130 represents the thermal characteristics of a particular object S that is associated with the identifier 106 as a result of the training process. For example, if the object S is a human, a non-human animal, or a moving device (such as a robot), the object S generates heat in a pattern that is specific to the physical characteristics of the object S. This pattern may be captured as a thermal profile 130 during training. In this example, the status 114 of the associated object may further depend on a comparison of the thermal profile 130 associated with the extracted identifier 106 to the captured thermal monitoring data 124.

[0057] In some examples, the system 10 and / or monitor 600 may periodically or continuously update the database 150. These updates may correspond to a new object S passing through the transition area TA. As part of these updates, new entries may be added to the database 150 that associate identifiers 106 with body mass signatures 110 and / or thermal profiles 130. These new entries may be added if the system 10 recognizes an identifier 106 or body mass signature 110 that is not found in the current database. Additionally, in some examples, existing entries may be updated to modify the body mass signature 100 or thermal profile 130 associated with a particular identifier 106.

[0058] 5 is a schematic diagram of an embodiment of a monitor 600. The monitor 600 includes a processor 125, a memory 175, and a transceiver (TxRx) 650. The monitor 600 uses the transceiver 650 to receive Wireless Signals 104, Wireless Training Signals 120, Thermal Monitoring Data 124, and Thermal Training Data 126. The processor 125 extracts Identifiers 106 from the wireless training signals 120. The processor 125 determines Training CSIs 122 based on the wireless training signals 120 and / or the thermal training data 126. The processor 125 then determines Body-Mass Signatures 110 for each Identifier 106 based on the Training CSIs 122. The processor 125 may also generate Thermal Profiles 130 based on the thermal training data and based on each identifier 106. The processor 125 stores the associated identifiers 106, body mass signatures 110, and thermal profiles in a Database 150.

[0059] The processor 125 then determines Device Location Properties 102 of the wireless device 100. The processor 125 first determines the CSI 108 based on the wireless signals 104. The CSI 108 may also be determined based on the thermal monitoring data 124 and the commissioned layout data 128. The processor may then determine the Device Location Properties 102 based on the CSI 108 and a body mass signature 110 corresponding to an identifier 106 embedded in the wireless signals 104 used to derive the CSI 108. The Device Location Properties 102 may also be based on the thermal monitoring data 124 and a thermal profile 130 corresponding to the identifier 106. The Device Location Properties 102 may include (1) a Relative Location 112 of the wireless device 100 on the object S, and (2) a Rightful Owner Status 114 of the associated object. The processor 125 may then generate an Alarm Signal 116 based on the status 114 of the associated object. The processor 125 may also generate a Limit Operation Signal 132 configured to limit one or more Operational Aspects 118 of the wireless device 100.

[0060] 6, a method 500 for determining one or more device location characteristics of a wireless device is provided. The method 500 includes receiving 502 a wireless signal transmitted by a wireless device in proximity to a subject via a plurality of wireless receivers disposed in a monitoring area. The wireless signal includes an identifier, such as a Bluetooth identifier, corresponding to the wireless device. The wireless signal may be transmitted by a smartphone in the subject's front or back pocket. In this example, the subject is a human, but in alternative examples, the subject may be a non-human animal or device, such as a robot.

[0061] The method 500 further includes determining 504 a CSI of the subject based on the received wireless signals. The CSI is determined by comparing the wireless signals transmitted by the wireless device and the wireless signals received by the receiver. In this example, the CSI represents the body mass effect of the subject carrying the wireless device on the wireless signals. Thus, the CSI serves as an identifier of the subject carrying the device. In some examples, the CSI is determined based on the selected wireless signals determined to be transmitted through the subject's body. This determination may be made through analysis of thermal monitoring data collected by a thermopile monitoring sensor.

[0062] The method 500 further includes determining 506 a device location characteristic based on the determined CSI and a body mass signature, the body mass signature being associated with the identifier. The body mass signature is a representation of the object's body's effect on the wireless signal. Thus, by comparing the determined CSI and the body mass signature, a number of device location characteristics may be determined. In one example, the status of the associated object of the wireless device may be determined. The status of the associated object indicates whether the wireless device is currently carried by a legitimate owner. In another example, the relative location of the wireless device on the object (front pocket, back pocket, handbag, backpack, etc.) is determined.

[0063] According to an example, and still referring to FIG. 6 , the method 500 may further include receiving 508 a wireless training signal transmitted by the wireless device via a plurality of wireless training receivers disposed in the training area. The wireless training signal includes an identifier. The wireless training signal may be equivalent to the wireless signals described above. The training area may be a hallway, a corridor, a stairwell, a security checkpoint, or other area where subjects will most likely carry a wireless device. The training area is used to generate body mass signatures of subjects moving through the training area and to associate the body mass signatures with identifiers transmitted by the wireless devices carried by the corresponding subjects.

[0064] The method 500 may further include determining 510 a training CSI based on the received wireless training signals. Similar to the CSI described above, the training CSI represents a body mass effect of a subject carrying a wireless device on the wireless training signals. The training CSI may be determined based on a selected wireless training signal determined to be transmitted through the subject's body. This determination may be made through analysis of thermal training data collected by the thermopile training sensor.

[0065] Method 500 may further include determining 512 a body mass signature based on the training CSI. The body mass signature may be an aggregate of the training CSI corresponding to the most relevant wireless training signals, i.e., the wireless training signals traveling through the subject's body.

[0066] The method 500 may further include associating the body mass signature with an identifier 514. This association of the body mass signature and the identifier may be stored in a database for retrieval during monitoring.

[0067] As defined and used herein, all definitions should be understood to govern dictionary definitions, definitions in documents incorporated by reference, and / or ordinary meanings of the defined terms.

[0068] The indefinite articles "a" and "an," as used in the specification and claims, unless clearly indicated otherwise, should be understood to mean "at least one."

[0069] The term "and / or" as used in the specification and claims should be understood to mean "either or both" of the elements so conjoined, i.e., elements that are conjunctive in some cases and disjunctive in other cases. Multiple elements listed with "and / or" should be construed in the same manner, i.e., "one or more" of the elements so conjoined. Other elements other than the elements specifically identified by the "and / or" clause may be optionally present, whether related or unrelated to those elements specifically identified.

[0070] As used in the specification and claims, "or" should be understood to have the same meaning as "and / or" as defined above. For example, when separating items in a list, "or" or "and / or" shall be interpreted as inclusive, i.e., including at least one, but also including more than one of an element or list of elements, and optionally additional unlisted items. Only terms such as "only one of" or "exactly one of," or when used in the claims, "consisting of," where the contrary is clearly indicated, refer to the inclusion of exactly one of an element or list of elements. In general, the term "or," as used herein, shall be interpreted as indicating exclusive alternatives (i.e., "one or the other, but not both") only when preceding terms of exclusivity, such as "any of," "one of," "only one of," or "exactly one of."

[0071] As used in this specification and claims, the phrase "at least one" referring to a list of one or more elements should be understood to mean at least one selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each element specifically listed in the list of elements, and not excluding any combinations of elements in the list of elements. This definition also allows that elements other than the elements specifically identified in the list of elements to which the phrase "at least one" refers can optionally be present, whether related or unrelated to those elements specifically identified.

[0072] It should also be understood that, unless expressly indicated to the contrary, in any method claimed herein that includes two or more steps or actions, the order of the method steps or actions is not necessarily limited to the order in which the method steps or actions are recited.

[0073] In the claims and in the above specification, all transitional phrases such as "comprising," "including," "carrying," "having," "containing," "involving," "holding," "consisting of," and the like, are to be understood to be open-ended, i.e., meaning including but not limited to. Only transitional phrases such as "consisting of" and "consisting essentially of" are closed or semi-closed transitional phrases, respectively.

[0074] The above examples of the described subject matter can be implemented in any of numerous ways. For example, some aspects can be implemented using hardware, software, or a combination thereof. If any aspects are implemented at least in part in software, the software code can be executed on any suitable processor or collection of processors, whether provided on a single device or computer, or distributed among multiple devices / computers.

[0075] The present disclosure may be implemented as a system, method, and / or computer program product at any possible level of technical detail. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions for causing a processor to execute aspects of the present disclosure.

[0076] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: portable computer diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or Flash memories), static random access memories (SRAMs), portable compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or raised structures in grooves on which instructions are recorded, and suitable combinations of the above. As used herein, computer-readable storage media is not to be construed as being ephemeral signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or electrical signals transmitted through wires.

[0077] The computer-readable program instructions described herein can be downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network, or from a computer-readable storage medium to the respective computing / processing device. The network can include copper transmission cables, optical transmission fiber, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing / processing device.

[0078] The computer readable program instructions for carrying out the operations of the present disclosure can be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, configuration data for an integrated circuit, or source or object code written in any combination of one or more programming languages, including object oriented programming languages ​​such as Smalltalk, C++, procedural programming languages ​​such as the "C" programming language, or similar programming languages. The computer readable program instructions can be executed entirely on the user's computer, partially on the user's computer, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server, as a standalone software package. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (e.g., through the Internet using an Internet Service Provider). In some examples, electronic circuitry, including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), can execute computer readable program instructions by individualizing the electronic circuitry using state information of the computer readable program instructions to perform aspects of the present disclosure.

[0079] Aspects of the present disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to examples of the present disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0080] Computer readable program instructions can be provided to a processor of a special purpose computer, or other programmable data processing apparatus, to manufacture a machine, such that the instructions, executing via the processor of the computer or other programmable data processing apparatus, can generate means for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. Computer readable program instructions can also be stored on a computer readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer readable storage medium on which the instructions are stored can include an article of manufacture including instructions that perform aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0081] Furthermore, the computer readable program instructions may be loaded onto a computer, other programmable data processing apparatus, or other device to cause the computer, other programmable data processing apparatus, or other device to perform a series of operational steps to create a computer-implemented process, such that the instructions executing on the computer, other programmable data processing apparatus, or other device perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0082] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various examples of the disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the figures. For example, two blocks shown in succession may in fact be executed substantially simultaneously, or the blocks may possibly be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a dedicated hardware-based system that executes the specified functions or acts, or executes a combination of dedicated hardware and computer instructions.

[0083] Other implementations are within the scope of the following claims and other claims to which the applicant may be entitled.

[0084] While various examples have been described and illustrated herein, those skilled in the art will readily envision various other means and / or structures for performing the functions described herein and / or obtaining the results and / or one or more advantages thereof, and each such variation and / or modification is deemed to be within the scope of the examples described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are intended to be exemplary, and that the actual parameters, dimensions, materials, and / or configurations will depend on the particular application or applications for which the teachings are used. Those skilled in the art will recognize or be able to ascertain using no more than routine experimentation many equivalents to the specific examples described herein. Thus, the above examples are presented by way of example only, and it should be understood that, within the scope of the appended claims and their equivalents, examples other than those specifically described and claimed may be practiced. Examples of the present disclosure are directed to each individual feature, system, article, material, kit, and / or method described herein.

Claims

1. 1. A system for determining one or more device location characteristics of a wireless device, the system comprising: receiving, via a plurality of wireless receivers disposed in a monitoring area, a wireless signal transmitted by a wireless device proximate to the subject, the wireless signal including an identifier corresponding to the wireless device; determining channel state information (CSI) of the target based on the received wireless signals; and determining one or more device location characteristics based on the determined CSI and a body mass signature, the body mass signature associated with the identifier, the body mass signature corresponding to one or more subject body mass indices; 23. A system comprising: a processor configured to:

2. The system of claim 1 , wherein one or more device location characteristics include a relative location of the wireless device on the object.

3. The system of claim 2 , wherein the relative location corresponds to one of a front pocket of the object, a back pocket of the object, a handbag of the object, or a backpack of the object.

4. The system of claim 1 , wherein one or more device location characteristics include an associated object status indicating whether the object with the wireless device is an owner of the wireless device.

5. The system of claim 4 , wherein the processor is configured to generate an alarm signal based on a status of the associated object.

6. The system of claim 4 , wherein the processor is configured to limit one or more operational aspects of the wireless device based on a status of the associated object.

7. The system of claim 1 , wherein the plurality of wireless receivers are Bluetooth receivers or ultra-wide band receivers.

8. The processor, receiving, via a plurality of wireless training receivers disposed in a training area, a wireless training signal transmitted by a wireless device, the wireless training signal including an identifier; determining a training CSI based on the received wireless training signal; determining a body mass signature based on the training CSI; and associating the body mass signature with the identifier of the wireless training signal; The system of claim 1 configured to:

9. 10. The system of claim 8, wherein the processor is configured to receive thermal training data collected by a thermopile training sensor disposed in the training area or light detection and ranging (LIDAR) training data collected by a LIDAR training sensor disposed in the training area.

10. The system of claim 9 , wherein the body mass signature is further based on the thermal training data or the LIDAR training data.

11. The system of claim 1 , wherein the one or more device location characteristics are further based on commissioned layout data corresponding to the plurality of wireless receivers.

12. The system of claim 1 , wherein the processor is configured to receive thermal monitoring data collected by a thermopile monitoring sensor disposed in the monitoring area.

13. The system of claim 12 , wherein one or more device location characteristics are further based on the thermal monitoring data.

14. 1. A method for determining one or more device location characteristics of a wireless device, the method comprising: receiving, via a plurality of wireless receivers disposed in a monitoring area, a wireless signal transmitted by a wireless device in proximity to a subject, the wireless signal including an identifier corresponding to the wireless device; determining target channel state information (CSI) based on the received wireless signals; determining a device location characteristic based on the determined CSI and a body mass signature, the body mass signature associated with the identifier, the body mass signature corresponding to one or more subject body mass indices; A method comprising:

15. The method comprises: receiving, via a plurality of wireless training receivers disposed in a training area, a wireless training signal transmitted by a wireless device, the wireless training signal including an identifier; determining a training CSI based on the received wireless training signal; determining a body mass signature corresponding to the identifier based on the training CSI; associating the body mass signature with the identifier of the wireless training signal; A method comprising:

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