Patent Publication Number: US-9854400-B2

Title: Augmenting Wi-Fi localization with auxiliary sensor information

Description:
TECHNICAL FIELD 
     The present disclosure generally relates to tracking and locating mobile devices, and in particular, to systems, methods, and devices for enabling continuity of identity for mobile devices. 
     BACKGROUND 
     In general, mobile devices connect to a network (e.g., a private network or a public network such as the Internet) via a networking device (e.g., an access point, router, switch, or the like). Typically, a mobile device is identified by an address when it uses the networking capabilities of the networking device. Device addresses, in particular media access control (MAC) addresses, are often used as proxies for the physical presence of users or even the identity of users, in part due to their persistent nature. 
     Device addresses are the basis of many tracking algorithms that promise both enhanced analytics to operators and location-based services for users. For example, the location of a mobile device can be tracked, and distinguished from other mobile devices, according to its address. 
     However, in some circumstances, the address of a mobile device is randomized in an attempt to protect the privacy of the user and purposefully frustrate tracking algorithms. As such, a mobile device that was once being tracked according to one address will appear as a new mobile device to be tracked with an unrecognized address after its address is randomized. 
     Randomization events frustrate the ability of traditional Wi-Fi localization techniques to track mobile devices according to addresses as they are no longer persistent. Randomization events also skew analytics results based on mobile device tracking by double counting mobile devices (e.g., in crowd counting scenarios) or losing the locality of mobile devices. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       So that the present disclosure can be understood by those of ordinary skill in the art, a more detailed description may be had by reference to aspects of some illustrative implementations, some of which are shown in the accompanying drawings. 
         FIG. 1  is a block diagram of an example operating environment in accordance with some implementations. 
         FIG. 2  is a block diagram of an example data network environment in accordance with some implementations. 
         FIG. 3  is a block diagram of a data processing environment in accordance with some implementations. 
         FIG. 4  is a block diagram of an example data structure for a characterization database in accordance with some implementations. 
         FIG. 5  is a representation of an implementation of maintaining continuous identity for mobile devices in accordance with some implementations. 
         FIG. 6  is a representation of another implementation of maintaining continuous identity for mobile devices in accordance with some implementations. 
         FIG. 7  is a representation of yet another implementation of maintaining continuous identity for mobile devices in accordance with some implementations. 
         FIG. 8  is a flowchart representation of a method of maintaining continuous identity for mobile devices in accordance with some implementations. 
         FIG. 9  is a block diagram of an example device in accordance with some implementations. 
     
    
    
     In accordance with common practice the various features illustrated in the drawings may not be drawn to scale. Accordingly, the dimensions of the various features may be arbitrarily expanded or reduced for clarity. In addition, some of the drawings may not depict all of the components of a given system, method or device. Finally, like reference numerals may be used to denote like features throughout the specification and figures. 
     DESCRIPTION OF EXAMPLE EMBODIMENTS 
     Numerous details are described in order to provide a thorough understanding of the example implementations shown in the drawings. However, the drawings merely show some example aspects of the present disclosure and are therefore not to be considered limiting. Those of ordinary skill in the art will appreciate that other effective aspects and/or variants do not include all of the specific details described herein. Moreover, well-known systems, methods, components, devices and circuits have not been described in exhaustive detail so as not to obscure more pertinent aspects of the example implementations described herein. 
     Overview 
     Various implementations disclosed herein include devices, systems, and methods for maintaining continuous identity for and locality of mobile devices. For example, in some implementations, a method includes: obtaining a first address for a first device; and obtaining, from one or more auxiliary sensors, auxiliary sensor information related to the first device. The method also includes determining whether the auxiliary sensor information matches information associated with a second address, where the second address was previously associated with the first device. The method further includes linking the first address with the second address for the first device, in order to continue tracking the first device when the second address is no longer detected, in response to determining that the auxiliary sensor information matches information associated with the second address. 
     In accordance with some implementations, a device includes one or more processors, a non-transitory memory, and one or more programs; the one or more programs are stored in the non-transitory memory and configured to be executed by the one or more processors and the one or more programs include instructions for performing or causing performance of any of the methods described herein. In accordance with some implementations, a non-transitory computer readable storage medium has stored therein instructions, which, when executed by one or more processors of a device, cause the device to perform or cause performance of any of the methods described herein. In accordance with some implementations, a device includes: one or more processors, a non-transitory memory, and means for performing or causing performance of any of the methods described herein. 
     Example Embodiments 
     In general, mobile devices connect to a network (e.g., a private network or a public network such as the Internet) via a networking device (e.g., an access point, router, switch, or the like). Typically, a mobile device is identified by an address when it uses the networking capabilities of the networking device. Addresses, in particular physical addresses such as media access control (MAC) addresses, are often used as proxies for the physical presence or even identity of a person (user), in part due to their persistent nature. 
     However, in some circumstances, a randomization event occurs whereby the address of a mobile device that was being tracked according to its address is randomized. As such, the mobile device appears as if it is a new mobile device to be tracked. According to some implementations, the present disclosure provides a system and method for maintaining continuous identity for mobile devices based at least in part on auxiliary sensor information related to mobile devices and/or their users such as video data, proximity between devices, or persistent local connections between devices (e.g., BLUETOOTH links). 
       FIG. 1  is a block diagram of an example operating environment  100  in accordance with some implementations. While pertinent features are shown, those of ordinary skill in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity and so as not to obscure more pertinent aspects of the example implementations disclosed herein. To that end, as a non-limiting example, the operating environment  100  includes a plurality of access points  102 - 1 ,  102 - 2 ,  102 - 3 , and  102 - 4  (collectively referred to as “access points  102 ” herein) with coverage areas  104 - 1 ,  104 - 2 ,  104 - 3 , and  104 - 4  (collectively referred to as “coverage areas  104 ” herein), respectively. In some implementations, the access points  102  obtain addresses (e.g., media access control (MAC) addresses) for devices within the operating environment  100 . In some implementations, the access points  102  obtain characterization information (sometimes also herein called “auxiliary sensor information”) related to devices within the operating environment such as whether a device has a BLUETOOTH connection to another device, an indication of the radio system (e.g., GSM or CDMA) that the device uses, the speed, acceleration, or trajectory of the device, and/or the like. In some implementations, the access points  102  monitor the locations of devices within the operating environment  100  using Wi-Fi localization techniques. Alternatively, in some implementations, the access points  102  are switches, routers, bridges, hubs, or the like. 
     For example, an individual with a mobile device that is located within coverage area  104 - 1  can access a network (e.g., a private network or a public network such as the Internet) via access point  102 - 1 . Continuing with this example, if the individual moves into coverage area  104 - 2  with his/her mobile device, access is provided to the network via access point  102 - 2 . In some implementations, a hand-off protocol exists between the access points  102  for seamless transitions between coverage areas  104  in order to ensure uninterrupted access to the network. 
     In some implementations, the operating environment  100  also includes a plurality of sensors  112 - 1 ,  112 - 2 ,  112 - 3 , and  112 - 4  with ranges (or fields of view)  114 - 1 ,  114 - 2 ,  114 - 3 , and  114 - 4 , respectively. For example, the sensors  112  include video cameras, infrared (IR) cameras, spectral analyzers, microphones, temperature sensors, humidity sensors, motion sensors, and/or the like. In some implementations, the sensors  112  collect characterization information (sometimes also herein called “auxiliary sensor information”) associated with individuals within the operating environment  100  such as visual signatures, facial features, heat maps, distinguishing articles of clothing, color histograms, speech patterns, gait patterns, and/or the like. In some implementations, the sensors  112  monitor and track the locations of individuals within the operating environment  100  using visual localization techniques or other similar localization techniques. 
       FIG. 2  is a block diagram of an example data network environment  200  in accordance with some implementations. To that end, as a non-limiting example, the data network environment  200  includes a controller  210 , a characterization database  225 , and a network application  215 . In some implementations, the network application  215  sets parameters for the controller  210 . In some implementations, the network application supplies instructions to the controller  210 . In some implementations, the characterization database  225  correlates multiple addresses associated with a device. In some implementations, the characterization database  225  also correlates address(es) of a device with characterization information associated with the user of the device for persistent monitoring and localization purposes. In some implementations, the characterization database  225  further includes location information regarding the device and/or the user of the device. The characterization database  225  is described in more detail herein with reference to  FIG. 4 . 
     In some implementations, the controller  210  controls and facilitates the monitoring and localizing of devices within the operating network  100 . In some implementations, the controller  210  obtains addresses of devices, characterization information, and/or location information for devices within the operating network  100  from access points  102 . In some implementations, the access points  102  export addresses of devices, characterization information, and/or location information for devices within the operating network  100  to the controller  210  constantly. In some implementations, the access points  102  export addresses of devices, characterization information, and/or location information for devices within the operating network  100  to the controller  210  according to a predefined schedule (e.g., every 10, 30, 60, etc. seconds). In some implementations, the controller  210  requests addresses of devices, characterization information, and/or location information for devices within the operating network  100  from the access points  102 . 
     In some implementations, the controller  210  obtains characterization and/or location information for individuals within the operating network  100  from sensors  112 . In some implementations, the sensors  112  export characterization and/or location information for individuals within the operating network  100  to the controller  210  constantly. In some implementations, the sensors  112  export characterization and/or location information for individuals within the operating network  100  to the controller  210  according to a predefined schedule (e.g., every 10, 30, 60, etc. seconds). In some implementations, the controller  210  requests physical characterization and/or location information for individuals within the operating network  100  from the sensors  112 . 
       FIG. 3  is a block diagram of a data processing environment  300  in accordance with some implementations. The data processing environment  300  shown in  FIG. 3  is similar to and adapted from the data network environment  200  shown in  FIG. 2 . Elements common to  FIGS. 2 and 3  include common reference numbers, and only the differences between  FIGS. 2 and 3  are described herein for the sake of brevity. To that end, the data processing environment  300  includes the access points  102 , the sensors  112 , the controller  210 , and the characterization database  225 . According to some implementations, the controller  210  includes a monitoring module  312 , a collecting module  314 , a maintaining module  330 , a correspondence module  332 , and a linking module  334 . 
     In some implementations, the monitoring module  312  obtains addresses for devices (e.g., MAC addresses), characterization information, and/or location information from the access points  102  for devices within the coverage areas of the access points  102 . In some implementations, the collecting module  314  obtains characterization and/or location information from the sensors  112  for individuals within the ranges of the sensors  112 . 
     In some implementations, the maintaining module  330  maintains the characterization database  225  based at least in part on the information obtained from the monitoring module  312  and the collecting module  314 . In some implementations, the maintaining module  330  also establishes correspondence between one or more addresses for a device and characterization information for an individual. The maintaining module  330  is described in greater detail below with reference to  FIGS. 4 and 8 . 
     In some implementations, the correspondence module  332  determines whether the characterization information associated with a newly detected address for a device (e.g., the visual signature) matches characterization information associated with a previously detected address. In other words, the correspondence module  332  determines whether the newly detected address corresponds to a device that was previously being tracked under a different address or whether the newly detected address is associated with a device that was not previously being tracked. The correspondence module  332  is described in greater detail below with reference to  FIGS. 5-8 . 
     In some implementations, the linking module  334  links a first address for a device with a second address based on characterization information associated with the device from the access points  102  and/or characterization information associated with the individual who corresponds to the device from the sensors  112 . The linking module  334  is described in greater detail below with reference to  FIGS. 5-8 . 
       FIG. 4  is a block diagram of an example data structure for a characterization database  225  in accordance with some implementations. According to some implementations, the characterization database  225  includes a plurality of rows  410 -A,  410 -B,  410 -C,  410 -D, . . . , each of which corresponds to a unique device identified within the operating environment  100  by the controller  210 . In some implementations, the characterization database  225  is populated, updated, and maintained by the controller  210  or a component thereof (e.g., the maintaining module  330  in  FIG. 3 ). 
     As shown in  FIG. 4 , each row  410  of the characterization database  225  is characterized by the following fields: {at least one address  401 , characterization information  402 , and location information  404 }. For example, the row  410 -A is associated with the address  401 -A- 1  because the address for the device corresponding to the row  410 -A has not been randomized. 
     In another example, the row  410 -B is associated with addresses  401 -B- 1  and  401 -B- 2  because the device corresponding to the row  410 -B was initially associated with the address  401 -B- 1  before time T when its address was randomized. Continuing with this example, after time T, the device corresponding to the row  410 -B is associated with the address  401 -B- 2 . 
     In yet another example, the row  410 -C is associated with addresses  401 -C- 1 ,  401 -C- 2 , and  401 -C- 3  because the device corresponding to the row  410 -C was initially associated with the address  401 -C- 1  before time T when its address was first randomized. Continuing with this example, after time T, the device corresponding to the row  410 -C was associated with the address  401 -C- 2  until time T+1 when its address was again randomized. Further continuing with this example, after time T+1, the device corresponding to the row  410 -C is associated with the address  401 -C- 3 . 
     According to some implementations, the characterization information  402 -A includes information associated with the unique device that corresponds to the row  410 -A such as the addresses of other devices within a predefined proximity of the unique device, an indication of the existence of a connection (e.g., via BLUETOOTH) with another device, and/or the like. According to some implementations, the characterization information  402 -A includes information associated an individual who corresponds to the unique device corresponding to the row  410 -A. For example, the characterization information  402 -A includes a visual signature of a person who is carrying/using the unique device corresponding to the row  410 -A that includes, for example, one or more facial features of the person, a distinguishing article of clothing worn by the person, a heat map of the person, a color histogram corresponding to the clothing outfit of person, a voice model of a person (e.g., pitch and speech synthesis parameters such as those use for speech/speaker recognition), and/or the like. 
     According to some implementations, the characterization information  402 -A also includes a sequence of coordinates (and, optionally, associated timestamps) associated with past locations, and the present location, of the person associated with the unique device that corresponds to the row  410 -A. For example, the person is tracked within the operating environment  100  (as shown in  FIG. 100 ) based on video or audio data from the one or more sensors  112  using visual and/or auditory localization techniques. In some implementations, the coordinates are relative to the operating environment  100 . In some implementations, the coordinates are absolute geographical coordinates. According to some implementations, the location information  404 -A also includes a projected path or trajectory of the person associated with the unique device that corresponds to the row  410 -A. In some implementations, the location information  404 -A also includes the velocity and/or acceleration of the person associated with the unique device that corresponds to the row  410 -A. 
     According to some implementations, the location information  404 -A includes a sequence of coordinates (and, optionally, associated timestamps) associated with past locations, and the present location, of the unique device that corresponds to the row  410 -A. For example, the unique device is tracked within the operating environment  100  (as shown in  FIG. 100 ) based data from the one or more access points  102  using Wi-Fi localization techniques. In some implementations, the coordinates are relative to the operating environment  100 . In some implementations, the coordinates are absolute geographical coordinates. According to some implementations, the location information  404 -A also includes a projected path or trajectory of the unique device that corresponds to the row  410 -A. In some implementations, the location information  404 -A also includes the velocity and/or acceleration of the unique device that corresponds to the row  410 -A. 
       FIG. 8  is a flowchart representation of a method  800  of maintaining continuous identity for mobile devices in accordance with some implementations. In various implementations, the method  800  is performed by a network controller (e.g., the network controller  210  in  FIGS. 2 and 3 ). While pertinent features are shown, those of ordinary skill in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity and so as not to obscure more pertinent aspects of the example implementations disclosed herein. To that end, briefly, in some circumstances, the method  800  includes: obtaining a first address for a first device; obtaining, from one or more auxiliary sensors, auxiliary sensor information related to the first device; determining whether the auxiliary sensor information matches information associated with a second address, where the second address was previously associated with the first device; and linking the first address with the second address for the first device, in order to continue tracking the first device when the second address is no longer detected, in response to determining that the auxiliary sensor information matches information associated with the second address. 
     To that end, as represented by block  8 - 1 , the method  800  includes obtaining a first address for a first device. In some implementations, the first device is one of a smartphone, wearable computing device, tablet, laptop, personal computer, smart home device or controller, home entertainment center, or the like. For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the monitoring module  312  in  FIG. 3 ) obtains (e.g., detects, requests, receives, and/or retrieves) an address (e.g., a MAC address) for a first device from the access points  102 . For example, the first address has not been previously recognized. In some implementations, the first address is a media access control (MAC) address. As such, the address of the device is a proxy for the person who uses/carries the device. For example, the device is being tracked for enhanced analytics purposes and/or for location-based services. 
     According to some implementations, the method  800  is triggered when the controller  210  detects a new address within the operating environment  100 . According to some implementations, the method  800  is triggered when the controller  210  detects the absence of a previously detected address. According to some implementations, the method  800  is triggered when the controller  210  contemporaneously (or near contemporaneously) detects the absence of a previously detected address and a new address within the operating environment  100  (e.g., a randomization event). 
     As represented by block  8 - 2 , the method  800  includes obtaining, from one or more auxiliary sensors, auxiliary information related to the first device. For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the monitoring module  312  and/or the collecting module  314  in  FIG. 3 ) obtains auxiliary sensor information (e.g., characterization information related to the first device or an individual carrying/using the first device) from the access points  102  and/or the sensors  112 . 
     In some implementations, the auxiliary sensor information is a visual signature associated with the person who is using or carrying the first device such as a one or more facial features, the clothing outfit of a person, a color histogram of the clothing outfit of the person, a distinguishing feature of the person, a distinguishing article of clothing worn by the person, a heat map of the person, a speech pattern of a person, a gait pattern associated with the person, and/or the like. In some implementations, the auxiliary sensor information is an address associated with another device in close proximity to the device (e.g., a second cell phone or other device that the person is carrying, a cell phone that a companion of the person is carrying, or the like). In some implementations, the auxiliary sensor information is an indication of a local connection (e.g., via BLUETOOTH) between the first device (e.g., a smartphone) and another device (e.g., a fitness band, headset, smart watch or the like). 
     In some implementations, the auxiliary sensor information includes at least one of a trajectory, speed, and acceleration of the first device or a person who corresponds with the first device. In some implementations, the trajectory, speed, and acceleration of the first device or the person helps to narrow down the pool of potential previously detected addresses that can be correlated with the newly detected address. 
     In some implementations, as represented by block  8 - 2   a , the auxiliary sensor information includes a visual signature associated with a person who corresponds with the first device. In some implementations, the visual signature includes at least one of: a heat map, one or more facial features, one or more articles of clothing, a color histogram or a gait pattern associated with the person who corresponds with the first device, and/or the like. In some implementations, the system leverages information from a network of video cameras to develop a visual signature for the person who is carrying the device. For example, the visual identifier is originally associated with the second MAC address, but when it is randomized a new correlation between the first MAC address and the visual identifier is established. 
     As shown in  FIG. 5 , at time  510 , a visual signature for a first person  502  corresponds to a MAC address 00-17-ab-5a-65-40 of a device that the first person  502  is using/carrying and a visual signature for a second person  504  corresponds to a MAC address f8-c3-29-7d-42-3d of a device that the second person  504  is using/carrying. For example, with reference to  FIG. 4 , the address  401 -A- 1  corresponds to the MAC address 00-17-ab-5a-65-40 of the device that the first person  502  is using/carrying at time  510  and the characterization information  402 -A corresponds to the visual signature for the first person  502 . Furthermore, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the MAC address f8-c3-29-7d-42-3d of device that the second person  504  is using/carrying at time  510  and the characterization information  402 -B corresponds to the visual signature for the second person  504 . 
     As shown in  FIG. 5 , at time  520 , a visual signature for the first person  502  still corresponds to the MAC address 00-17-ab-5a-65-40 of the device that the first person  502  is using/carrying, the visual signature for the second person  504  corresponds to a newly detected MAC address 00-28-c8-5f-a6-17 of a device that the second person  504  is using/carrying, and a visual signature for a newly detected third person  506  corresponds to a newly detected MAC address c2-4d-15-a2-67-e9 of a device that the third person  506  is using/carrying. As such, a randomization event occurred with respect to the MAC address of device that the second person  504  is using/carrying. Moreover, the MAC address f8-c3-29-7d-42-3d that was detected during time  510  is linked to the MAC address 00-28-c8-5f-a6-17 because the visual signature for the second person  504  at time  510  matches the visual signature for the second person  504  at time  520 . 
     For example, with reference to  FIG. 4 , the address  401 -A- 1  still corresponds to the MAC address 00-17-ab-5a-65-40 of the device that the first person  502  is using/carrying at time  520  and the characterization information  402 -A corresponds to the visual signature for the first person  502 . Furthermore, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the previously detected MAC address f8-29-7d-42-3d and the address  401 -B- 2  corresponds to the newly detected MAC address 00-28-c8-5f-a6-17 of device that the second person  504  is using/carrying at time  520  and the characterization information  402 -B corresponds to the visual signature for the second person  504 . Continuing with this example, the address  401 -D- 1  corresponds to the newly detected MAC address c2-4d-15-a2-67-e9 of the device that the third person  506  is using/carrying at time  520  and the characterization information  402 -D corresponds to the visual signature for the third person  506 . 
     In some implementations, as represented by block  8 - 2   b , the auxiliary sensor information includes an address of a second device within a predetermined radius (e.g., 3, 6, etc. feet) of the first device. In some implementations, when a new address exhibits similar proximity to a group as a former address (and the former address disappears), this is strong evidence that the previously detected and newly detected addresses correspond to the same device. At the very least, leveraging the temporal correlation among a group of wireless devices (and their associated addresses) can be used to dramatically reduce the search space of candidates for the new address for a newly detected device. 
     As shown in  FIG. 6 , at time  610 , a first person  602  whose device is associated with MAC address f8-29-7d-42-3d and a second person  604  whose device is associated with MAC address 00-17-ab-5a-65-40 are grouped into inter-person group  612  due to their spatial proximity to one another and in some cases their spatial proximity over time. For example, the first person  602  and the second person  604  are two friends walking close to one another. As shown in  FIG. 6 , at time  610 , a third person  606  whose device is associated with MAC address 00-28-c8-5f-a6-17 and a fourth person  608  whose device is associated with MAC address c2-4d-15-a2-67-e9 are grouped into inter-person group  614  due to their spatial proximity to one another and in some cases their spatial proximity over time. 
     For example, with reference to  FIG. 4 , the address  401 -A- 1  corresponds to the MAC address f8-29-7d-42-3d of the device that the first person  602  is using/carrying at time  610  and the characterization information  402 -A includes the MAC address 00-17-ab-5a-65-40 because of the proximity of the second person  604  to the first person  602 . Furthermore, for example, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the MAC address 00-17-ab-5a-65-40 of device that the second person  604  is using/carrying at time  610  and the characterization information  402 -B includes the MAC address f8-29-7d-42-3d because of the proximity of the first person  602  to the second person  604 . 
     As shown in  FIG. 6 , at time  620 , a first person  602  whose device is associated with MAC address f8-29-7d-42-3d and a second person  604  whose device is associated with newly detected MAC address 38-ca-2e-e7-58-0b are grouped into a new inter-person group  616  due to their spatial proximity to one another and in some cases their spatial proximity over time. As shown in  FIG. 6 , at time  620 , a third person  606  whose device is associated with MAC address 00-28-c8-5f-a6-17 and a fourth person  608  whose device is associated with MAC address c2-4d-15-a2-67-e9 are still grouped into inter-person group  614  due to their spatial proximity to one another and in some cases their spatial proximity over time. 
     As such, a randomization event occurred with respect to the MAC address of the device that the second person  604  is using/carrying. Moreover, the MAC address 00-17-ab-5a-65-40 that was detected during time  610  is linked to the MAC address 38-ca-2e-e7-58-0b because the person who the second person  604  was grouped with at time  610  (e.g., the first person  602  associated with the MAC address f8-29-7d-42-3d) is the same as at time  620 . 
     For example, with reference to  FIG. 4 , the address  401 -A- 1  still corresponds to the MAC address f8-29-7d-42-3d of the device that the first person  602  is using/carrying at time  620  and the characterization information  402 -A includes the newly detected MAC address 38-ca-2e-e7-58-0b because of the proximity of the second person  604  to the first person  602 . Furthermore, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the previously detected MAC address 00-17-ab-5a-65-40 and the address  401 -B- 2  corresponds to the newly detected MAC address 38-ca-2e-e7-58-0b of device that the second person  604  is using/carrying at time  620  and the characterization information  402 -B includes the MAC address f8-29-7d-42-3d because of the proximity of the first person  602  to the second person  604 . 
     In some implementations, as represented by block  8 - 2   c , the second device is communicatively coupled with the first device. For example, the device is a phone which is connected (or paired) with the second device (e.g., a BLUETOOTH headset or a wearable computing device) via a local connection. In some implementations, a person may carry several devices that can be sensed, or one device may contain multiple radios that can be sensed. Examples include BLUETOOTH headphones or headsets and wearable computing devices such as iWATCH or ANDROID watches, which talk with iPHONES and ANDROID phones over BLUETOOTH, respectively. This group of personal devices will move together, and when a device has a change of MAC address from Y to the new MAC address Z for the device can be inferred by continued proximity to the same set of devices say with address X. 
     As shown in  FIG. 7 , at time  710 , a first device  702  (e.g., a smartphone) associated with MAC address f8-c3-29-7d-52-3d is connected (e.g., via BLUETOOTH) to a second device  704  (e.g., a wearable computing device such as a fitness band). As such, the first device  702  and the second device  704  are grouped into intra-person group  712  due to the spatial proximity and/or the local connection  705  between the first device  702  and the second device  704 . For example, with reference to  FIG. 4 , the address  401 -D- 1  corresponds to the MAC address f8-c3-29-7d-52-3d of the first device  702  at time  710  and the characterization information  402 -D includes an indication of the connection  705  between the first device  702  and the second device  704  and/or an address of the second device  704 . 
     As shown in  FIG. 7 , at time  710 , a third device  706  (e.g., a smartphone) associated with MAC address c2-4d-15-a2-67-e9 is connected (e.g., via BLUETOOTH) to a fourth device  708  (e.g., a wearable computing device such as a smart watch). As such, the third device  706  and the fourth device  708  are grouped into intra-person group  714  due to the spatial proximity and/or to the local connection  715  between the third device  706  and the fourth device  708 . For example, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the MAC address c2-4d-15-a2-67-e9 of the third device  706  at time  710  and the characterization information  402 -B includes an indication of the connection  715  between the third device  706  and the fourth device  708  and/or an address of the fourth device  708 . 
     As shown in  FIG. 7 , at time  720 , the first device  702  is still connected (e.g., via BLUETOOTH) to the second device  704 . As such, the first device  702  and the second device  704  are still grouped into intra-person group  712  due to the local connection  705  between the first device  702  and the second device  704 . As shown in  FIG. 7 , at time  720 , the third device  706  associated with newly detected MAC address 00-28-c8-5f-a6-17 is connected (e.g., via BLUETOOTH) to the fourth device  708 . As such, the third device  706  and the fourth device  708  are grouped into a new intra-person group  716  due to the spatial proximity and/or the local connection  715  between the third device  706  and the fourth device  708 . 
     As such, a randomization event occurred with respect to the MAC address device of third device  706 . Moreover, the MAC address c2-4d-15-a2-67-e9 that was detected during time  710  is linked to the newly detected MAC address 00-28-c8-5f-a6-17 because the local connection  715  between the third device  706  and the fourth device  708  is the same at time  710  as it is at time  720 . For example, with reference to  FIG. 4 , the address  401 -B- 1  corresponds to the MAC address c2-4d-15-a2-67-e9 of the third device  706  at time  710  and the address  401 -B- 2  corresponds to the newly detected MAC address 00-28-c8-5f-a6-17 of the third device  706  at time  720  and the characterization information  402 -B includes an indication of the connection  715  between the third device  706  and the fourth device  708  and/or an address of the fourth device  708 . 
     As represented by block  8 - 3 , the method  800  includes determining whether the auxiliary sensor information matches information associated with a second address. For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the correspondence module  332  in  FIG. 3 ) determines whether the auxiliary sensor information associated with the first address for the first device (e.g., the visual signature) matches auxiliary sensor information associated with a previously detected second address. In other words, the method  800  determines whether the first address corresponds to a device that was previously being tracked under a different address (e.g., the second address) or whether the first address is associated with a device that was not previously being tracked. 
     In some implementations, a positive match is determined as a function of at least one threshold criteria. For example, the at least one threshold criteria is satisfied when at least a predefined percentage of features of a visual signature associated with the previously detected second address match the visual signature associated with the first address for the first device. In another example, the at least one threshold criteria is satisfied when at least a predefined number of features of a visual signature associated with the previously detected second address match the visual signature associated with the first address for the first device. In yet another example, the at least one threshold is satisfied when a second device within a predefined proximity of the first address was also within the predefined proximity of the second address. In some implementations, the predefined proximity is spatial (e.g., a 3 meter radius). In some implementations, the predefined proximity is spatial-temporal, whereby the addresses follow the same path over time or have spatial proximity over time (e.g., within 3 meters for 90 seconds). In yet another example, the at least one threshold criteria is satisfied when a same local connection between a second device and the first address also existed between the second device and the second address. In some implementations, the at least one threshold criteria is adaptive. In some implementations, the positive match is determined by comparing recent histories of auxiliary sensor information (e.g., time series of the locations of the device in the past 60 seconds) related to the first and second addresses. 
     In some implementations, the first address for the device is linked to the second address when a correlation score between the auxiliary sensor information related to first address and the second address satisfies a correlation confidence threshold. In some implementations, the first address for the device is not linked to the second address when a correlation score between auxiliary sensor information related to the first address and the second address does not satisfy a correlation confidence threshold. For example, if the correlation is above X % (e.g., 80% correlation), the system continues collecting auxiliary sensor information related to the device until the accuracy threshold is satisfied. Else, in this example, the device is tracked as if it is newly discovered/tracked. In some implementations, the correlation confidence threshold is chosen based on a tradeoff between tracking and incorrect associations. For example, if it is desirable to increase the probability of tracking a user or device, a lower correlation threshold is chosen. In another example, if it is desirable to reduce the number of incorrect associations/trackings, a higher correlation threshold is chosen. 
     This approach is also robust against the addition of random time jitter between when the old MAC address disappears and the new one appears. Identification can be performed at a given instance of time, or improved performance can be achieved by tracking the MAC addresses and accumulating the probability distribution over a time duration of seconds to minutes. For example, the correlation confidence threshold is satisfied when the accumulated probability distribution over a predetermined time period (e.g., 5 minutes) exceeds a predefined confidence score. 
     If the auxiliary sensor information matches information associated with a second address, the method  800  continues to block  8 - 4 . If the auxiliary sensor information does not match information associated with a second address, the method  800  continues to block  8 - 5 . 
     As represented by block  8 - 4 , the method  800  includes linking the first address with the second address in order to continue tracking the first device when the second address is no longer detected. For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the linking module  334  in  FIG. 3 ) links the first and second addresses in the characterization database  225 . As such, in one example, after the MAC address for the device is randomized, the auxiliary sensor information indicates that the first MAC address is correlated with a previously identified second MAC address in order to continue tracking the device/person. 
     In some implementations, with reference to  FIG. 4 , rows  410  of the characterization database  225  associated with each of the first and second addresses are linked (e.g., with pointers or the like). In some implementations, with reference to  FIG. 4 , the previous address for the first device is overwritten with the newly detected address in the row  410  of the characterization database  225  associated with the first device. In some implementations, with reference to  FIG. 4 , the first and second addresses are both included in a row  410  of the characterization database  225  associated with the first device (e.g., the addresses  401 -B- 1  and  401 -B- 2  in row  410 -B). 
     As represented by block  8 - 5 , the method  800  includes linking the first address with the second address in order to initiate tracking of the first device. For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the maintaining module  330  in  FIG. 3 ) creates an entry in the characterization database  225  that correlates the first address with the auxiliary sensor information. For example, if the device is turned on for the first time in view of the system, the method  800  associates the auxiliary sensor information with the first MAC address in case it is later randomized. 
     After blocks  8 - 4  and  8 - 5 , the method  800  continues to block  8 - 1 . For example, with reference to  FIG. 3 , the controller  210  or a component thereof (e.g., the monitoring module  312  and/or the maintaining module  330  in  FIG. 3 ) monitors the addresses obtained from the access points  102  for a newly detected address. 
       FIG. 9  is a block diagram of an example of a device  900  in accordance with some implementations. For example, in some implementations, the device  900  is similar to and adapted from the network controller  210  in  FIGS. 2 and 3 . While certain specific features are illustrated, those skilled in the art will appreciate from the present disclosure that various other features have not been illustrated for the sake of brevity, and so as not to obscure more pertinent aspects of the implementations disclosed herein. To that end, as a non-limiting example, in some implementations the device  900  includes one or more processing units (CPUs)  902 , a network interface  903 , a programming (I/O) interface  905 , a memory  910 , a characterization database  225 , and one or more communication buses  904  for interconnecting these and various other components. 
     In some implementations, the one or more communication buses  904  include circuitry that interconnects and controls communications between system components. The characterization database  225  stores a plurality of rows each of which corresponds to a unique device identified within the operating environment. In some implementations, each row of the characterization database  225  is characterized by following fields: {at least one address, characterization information, and location information}. The characterization database  225  is described in more detail above with reference to  FIG. 4 . 
     The memory  910  includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices. In some implementations, the memory  910  includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. The memory  910  optionally includes one or more storage devices remotely located from the one or more CPUs  902 . The memory  910  comprises a non-transitory computer readable storage medium. In some implementations, the memory  910  or the non-transitory computer readable storage medium of the memory  910  stores the following programs, modules and data structures, or a subset thereof including an optional operating system  920 , a monitoring module  930 , a collecting module  932 , a maintaining module  934 , a correspondence module  936 , and a linking module  938 . 
     The operating system  920  includes procedures for handling various basic system services and for performing hardware dependent tasks. 
     In some implementations, the monitoring module  930  is configured to obtain addresses, characterization information, and/or location information from networking devices (e.g., the access points  102  in  FIG. 1 ) for devices (e.g., smartphone, wearable computing device, tablet, laptop, personal computer, smart home device or controller, home entertainment center, or the like) within the coverage areas of the networking devices. To that end, in various implementations, the monitoring module  930  includes instructions and/or logic  931   a , and heuristics and metadata  931   b . According to some implementations, the monitoring module  930  is similar to and adapted from the monitoring module  312  in  FIG. 3 . 
     In some implementations, the collecting module  932  is configured to obtain characterization and/or location information from auxiliary sensors (e.g., the sensors  112  in  FIG. 1 ) for individuals within the ranges of the auxiliary sensors. To that end, in various implementations, the collecting module  932  includes instructions and/or logic  933   a , and heuristics and metadata  933   b . According to some implementations, the collecting module  932  is similar to and adapted from the collecting module  314  in  FIG. 3 . 
     In some implementations, the maintaining module  934  is configured to maintain characterization database  225  based at least in part on the information obtained from the monitoring module  930  and/or the collecting module  932 . To that end, in various implementations, the maintaining module  934  includes instructions and/or logic  935   a , and heuristics and metadata  935   b . According to some implementations, the maintaining module  934  is similar to and adapted from the maintaining module  330  in  FIG. 3 . 
     In some implementations, the correspondence module  936  is configured to determine whether the characterization information associated with a newly detected address for a device (e.g., the visual signature) matches characterization information associated with a previously detected address. To that end, in various implementations, the correspondence module  936  includes instructions and/or logic  937   a , and heuristics and metadata  937   b.  According to some implementations, the correspondence module  936  is similar to and adapted from the correspondence module  332  in  FIG. 3 . 
     In some implementations, the linking module  938  is configured to link first address for a device with a second address within the characterization database  225  based on characterization information associated with the device and/or characterization information associated with the individual who corresponds to the device. To that end, in various implementations, the linking module  938  includes instructions and/or logic  939   a , and heuristics and metadata  939   b . According to some implementations, the linking module  938  is similar to and adapted from the linking module  334  in  FIG. 3 . 
     Although the monitoring module  930 , the collecting module  932 , the maintaining module  934 , the correspondence module  936 , and the linking module  938  are shown as residing on a single device (i.e., the device  900 ), it should be understood that in other implementations, any combination of the monitoring module  930 , the collecting module  932 , the maintaining module  934 , the correspondence module  936 , and the linking module  938  reside in separate computing devices. For example, each of the monitoring module  930 , the collecting module  932 , the maintaining module  934 , the correspondence module  936 , and the linking module  938  reside on a separate device. 
     Moreover,  FIG. 9  is intended more as functional description of the various features which be present in a particular embodiment as opposed to a structural schematic of the implementations described herein. As recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated. For example, some functional modules shown separately in  FIG. 9  could be implemented in a single module and the various functions of single functional blocks could be implemented by one or more functional blocks in various implementations. The actual number of modules and the division of particular functions and how features are allocated among them will vary from one embodiment to another and, in some implementations, depends in part on the particular combination of hardware, software, and/or firmware chosen for a particular embodiment. 
     While various aspects of implementations within the scope of the appended claims are described above, it should be apparent that the various features of implementations described above may be embodied in a wide variety of forms and that any specific structure and/or function described above is merely illustrative. Based on the present disclosure one skilled in the art should appreciate that an aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method may be practiced using any number of the aspects set forth herein. In addition, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to or other than one or more of the aspects set forth herein. 
     It will also be understood that, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first sensor could be termed a second sensor, and, similarly, a second sensor could be termed a first sensor, which changing the meaning of the description, so long as all occurrences of the “first sensor” are renamed consistently and all occurrences of the “second sensor” are renamed consistently. The first sensor and the second sensor are both sensors, but they are not the same sensor. 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the claims. As used in the description of the embodiments and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in accordance with a determination” or “in response to detecting,” that a stated condition precedent is true, depending on the context. Similarly, the phrase “if it is determined [that a stated condition precedent is true]” or “if [a stated condition precedent is true]” or “when [a stated condition precedent is true]” may be construed to mean “upon determining” or “in response to determining” or “in accordance with a determination” or “upon detecting” or “in response to detecting” that the stated condition precedent is true, depending on the context.