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WO2015069320A2 - Système et procédé d'identification et de suivi mobiles dans des systèmes de localisation - Google Patents

Système et procédé d'identification et de suivi mobiles dans des systèmes de localisation Download PDF

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Publication number
WO2015069320A2
WO2015069320A2 PCT/US2014/038806 US2014038806W WO2015069320A2 WO 2015069320 A2 WO2015069320 A2 WO 2015069320A2 US 2014038806 W US2014038806 W US 2014038806W WO 2015069320 A2 WO2015069320 A2 WO 2015069320A2
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Prior art keywords
information
location
determining
signature
group
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PCT/US2014/038806
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WO2015069320A3 (fr
Inventor
Thomas B. Gravely
Martin C. Alles
Andrew E. BECK
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Commscope Technologies LLC
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Andrew LLC
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Publication of WO2015069320A3 publication Critical patent/WO2015069320A3/fr
Anticipated expiration legal-status Critical
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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/01—Determining conditions which influence positioning, e.g. radio environment, state of motion or energy consumption
    • G01S5/012—Identifying whether indoors or outdoors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0257—Hybrid positioning
    • G01S5/0263—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems
    • G01S5/0264—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems at least one of the systems being a non-radio wave positioning system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S2205/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S2205/01—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S2205/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S2205/01—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations specially adapted for specific applications
    • G01S2205/02—Indoor

Definitions

  • Wireless E91 1 calls must be located within an average accuracy range of approximately 100 meters and with latency not exceeding 30 seconds.
  • Network operators have installed wireless location systems that employ a variety of positioning technologies to establish a caller's location.
  • a serving wireless network detects the E911 call, identifies the mobile, and directly or indirectly launches a location request to the wireless location system of the serving carrier. Once a target mobile's location coordinates are determined, the location system typically sends that information through the serving network for delivery to or retrieval by the PSAP to which the network delivered the emergency call.
  • Carriers must report to federal and local agencies whether they comply with the caller location accuracy criteria. In the U.S., wireless carriers currently are permitted to perform all location accuracy compliance testing outdoors.
  • FCC Federal Communications Commission
  • Certain key performance attributes/issues of currently available in- place "macro-area" E91 1 Phase II location systems include: (a) a design that produces mobile location accuracy of approximately 50m to 100m; (b) non- autonomous operation, i.e., individual target mobiles are located only as directed by wireless networks based on 911 call initiation; (c) time delay - location of target mobile occurs within 30 seconds; and (d) significant performance degradation if target mobile is located within a structure.
  • OTT over-the-top
  • non-carrier enterprises examples include, but are not limited to, applications hosted on smartphones, supported by location capabilities resident within the mobile device itself, supported by individual non-carrier entities such as mobile device makers, application content providers, mapping services, and are not dependent whatsoever on any carrier's location facilities.
  • OTT over-the-top
  • examples include, but are not limited to, applications hosted on smartphones, supported by location capabilities resident within the mobile device itself, supported by individual non-carrier entities such as mobile device makers, application content providers, mapping services, and are not dependent whatsoever on any carrier's location facilities.
  • each of these examples lacks the basic location accuracy and response time demanded by emerging indoor-specific LBAs.
  • Figure 1 is a flow chart for determining a signature of an object according to an embodiment of the present subject matter.
  • the wireless device is tracked using the determined signature.
  • information is provided to the object.
  • Figure 2 is a flow chart for determining a signature of an object according to another embodiment of the present subject matter.
  • the wireless device is tracked using the determined signature.
  • information is provided to the object.
  • Figure 3 is a block diagram for an exemplary system for determining a signature of an object according to an embodiment of the present subject matter.
  • LBAs Large retail establishments, for instance, would like to help customers navigate within stores to the department or to specific products that they seek, independent of store staff. Many would like to track customer routes within stores where such information may be used later to facilitate product placement or advertising campaigns.
  • convention facility managers and sports complex managers envision similar services, including guiding patrons to convention booths, dining facilities, points of interest, and even to the level of individual vending machines. Retailers would like to identify and push promotional messages (on an opt-in or opt-out basis) to customers and account holders nearing or entering their establishments.
  • Some commercial property brokers and lessors envision being able to better allocate space according to tracked usage. Financial and credit organizations may wish to verify card holder physical presence at points of transaction.
  • Examples of potential users and applications include, but are not limited to:
  • the customer's mobile device pushes its ID to the store's identification and/or navigation system or is detected and ID'd by the store's system.
  • the store's system reports the ID and presence to a server, which is typically, but not necessarily, located on site.
  • the server/system pushes promotions, advertising, and/or discount information to the customer. Real-time or post- visit store trail mapping and display time analysis is also facilitated for current or later use by the store.
  • the Navigation and Targeted Promotion functionality may be utilized in combination or separately.
  • Mall/Shopping Center Targeted Promotion A customer nears a store in the mall/shopping center.
  • the customer's mobile device pushes its ID to the mall's identification and/or navigation system or is detected and ID'd by the mall's system.
  • the mall's system reports the ID and presence to a server, which is typically, but not necessarily, located on site.
  • the server/system pushes promotions, advertising, and/or discount information and store location(s) to the customer.
  • the promotion, advertising, and/or discount information may only be for stores in the customer's vicinity.
  • Real-time or post- visit trail mapping and display time analysis is also facilitated for current or later use by the mall.
  • individual shopper mall navigation is supported on a by-store and/or by-product category and/or by-brand basis.
  • Sports or Entertainment Facility Attendee Navigation this is similar to Convention Venue-Navigation described above. Event attendees receive an optional mobile device app in advance of event or upon entry to the venue.
  • the mobile device app lists all booths, displays, seminars, dining, vending, and other facilities, and provides on-demand personal navigation to these locations.
  • the customer's mobile device pushes its ID to the store's identification and/or navigation system or is detected and ID'd by the store's system.
  • the store's system reports the ID and presence to a server which is typically, but not necessarily, located on site.
  • the server/system accesses customer account information for store personnel assignment for service and/or follow-up on past, recent, or pending purchase or account activity.
  • An identification and/or navigation system locates, ID's, and tracks and reports building tenants' movements and where, when groups of tenants gather, etc.
  • the system provides office planners, real estate managers and other authorized users with information for space planning to support functional units, meeting room placement and sizing, etc.
  • the system additionally supports person locator and personal navigation applications.
  • Emergency Location Individual - A person uses their mobile device to call 911 or other designated number/code for emergency response.
  • An indoor location system locates the caller or locates and ID's the caller. The indoor system reports/pushes this information to a macro location system, is queried by the macro system for pertinent information, or reports the information to a database from which emergency caller information is retrieved.
  • Transaction ID Verification Near-Field Location A system locates and identifies mobile devices of persons in close vicinity of and using credit and debit cards for transactions, e.g., at point-of-sale (“POS”) devices, ATMs, etc.
  • Identification and/or location Technologies for use indoors include, but are not limited to:
  • RF Ranging (which may be based on Wi-Fi access points or dedicated infrastructure);
  • Proximity Detection (which may be based on distributed antenna systems (“DAS”) antennas, Wi-Fi access points, or dedicated infrastructure);
  • DAS distributed antenna systems
  • RF Pattern Matching (which may be based on Wi-Fi access points, small cells, or dedicated infrastructure);
  • RFID radio frequency identification technology
  • Pseudolites (which may be based on ground transmitters/signal sources that emulate the signal structure of GPS satellites);
  • Sound Detection (which may be infrasonic, ultrasonic, or audible scrambled signals);
  • GPS Global Positioning System
  • GNSS Global Navigation Satellite Systems
  • GPS The U.S. GNSS system
  • GPS is commonly deployed in a variety of devices, such as handheld GPS receivers that provide latitude and longitude as well as maps for navigation.
  • GNSS other than GPS are becoming a reality, including Galileo, GLONASS, and Beidou.
  • GPS satellites in Earth orbit transmit data signals that can be received by GPS receivers located in devices such as wireless phones.
  • the position of the device is calculated using a time-based approach from the data received from multiple GPS satellites.
  • the position calculation can be made in the device itself or by a remote server to which the device transmits the received/measured GPS data.
  • GPS signals are relatively weak and signal attenuation frequently renders GPS positioning unusable if the GPS device is within a building or even under dense tree foliage.
  • Assisted-GPS in which a central server sends certain GPS almanac and ephemeris data to a GPS device via a wireless data path, can be employed as a means to reduce time-to-first-fix (“TTFF”) and to help improve overall location performance.
  • TTFF time-to-first-fix
  • IR location systems determine position of objects based on sensed presence. Each object to be tracked requires a proprietary emitter that periodically transmits an IR beacon containing a unique code. Specialized IR receivers placed throughout a facility detect the beacons and determine the position of the object based on the known location of the detecting IR receiver. Because IR signals don't penetrate opaque materials such as walls and ceilings, an IR tracking system may require multiple receivers in each room to assure full coverage of the area. Since the IR path is essentially line of sight, problems can occur if the tracked asset itself blocks the view from the IR Tag to the reader.
  • Location by means of proximity detection simply provides an indication that a mobile device has been detected within range of a sensor or receiver. If the target mobile is detected, the location system typically reports as the mobile's location the location of the detecting antenna or zone. With the exception of the special case of near- field detection, proximity detection alone may not provide indoor- navigation-level accuracy. However, a combination of proximity and other methods may achieve objective performance. Proximity detection can provide a basis for geo-fencing applications.
  • GPS/GNSS signals are so attenuated or otherwise compromised as to be unusable indoors
  • a system of local, ground-based GPS-like signal sources could be employed to overcome that handicap and be useful to GPS-equipped devices located within structures.
  • Being able to deploy one's own (indoor) pseudolite positioning system, independent of GPS, could, theoretically, leverage GPS capabilities embedded in smartphones and other mobile devices to provide reliable high-accuracy indoor location.
  • pseudo-satellites pseudolites
  • small transceivers that are not GPS satellites, but that perform functions common to those satellites.
  • Pseudolites have recently gained more attention in the context of indoor location.
  • use of GPS frequencies is, for reasons that are readily understandable, highly protected and restricted by the U.S. Government.
  • An RFID location system includes RFID scanners installed throughout a facility that interrogate either active (radio transceivers) or passive tags that attach to objects.
  • Battery-powered active tags allow up to a twenty foot range between the scanner and the tags.
  • Passive tags have no batteries, but typically must be relatively close to the scanner (within inches or a few feet). Because of the limited range of passive tags, active RFID tags are the type usually found in positioning systems.
  • a centralized server stores the unique tag codes that the scanners collect and the server is able to identify and display the location of each tag according to which scanner detects a tag.
  • RFID systems determine position based only on the presence of the object in a particular area, so the accuracy of an active RFID system is dependent on the number and positioning of the scanners. Scanner repositioning may be necessitated due to changing floor layout or walls.
  • RFID systems that operate in the same frequency band as wireless LANs can pose RF interference issues with the LAN.
  • RFPM RF pattern matching
  • the mobile device to be located reports the RF characteristics of source signals, for instance from multiple cell sites, it observes at its current location, and the location system attempts to match those characteristics against a pre-established database of RF characteristics previously measured and recorded at each of many specific geographic points.
  • the location system determines as the target mobile's location the geographic point that yields the closest match of the mobile's reported RF characteristics and the pre-observed RF characteristics.
  • RFPM positioning accuracy is best in environments where the RF sources are densely deployed and poor where signal sources are sparse.
  • Devices to be located include a radio module that on a scheduled basis transmits an RF signal containing a unique identification code.
  • Sensors modified Wi-Fi access points or separate sensors installed in the area of interest receive the coded information and locate the device by means of proximity or other methods.
  • Some proprietary sensor networks calculate a device's location using measurements of signal strength or signal travel time from the tracked device to multiple sensors. Signal attenuation and multipath can negatively impact performance.
  • Wi-Fi-based sensor network tracking solutions can allow the access points to carry typical data traffic associated with Wi-Fi users, a cost advantage over dedicated (non- Wi-Fi) location systems. Since the device transmit schedule impacts battery life, the transmit schedule must be carefully managed to balance battery life against tracking and accuracy requirements.
  • the measured travel time or arrival time of mobile RF signals can be used in various ways to calculate a mobile's location and/or distance from a known reference point such as a cell tower, as is known in the art.
  • Timing-based location methods are familiar as uplink time difference of arrival (“U-TDOA”), observed time difference of arrival (“O-TDOA”), round trip time (“RTT”), timing advance (“TA”), multiple range estimation location (“MREL”), etc., and for years have been used to support "macro-area” emergency caller location and other applications. More recently, timing methods have been explored for indoor location and these development efforts continue.
  • Wi-Fi devices provides an attractive technology basis for location solutions.
  • a Wi-Fi-based solution can leverage the large base and economies of scale of installed networks and end user devices.
  • a Wi-Fi-based location system might support any type of location- aware application that involves PDAs, laptops, bar code scanners, voice-over-IP phones and other 802.11-enabled devices.
  • Proximity-oriented Wi-Fi location has been utilized for several years to support macro-area LBAs; in this usage a Wi-Fi access point ("AP") detected by a mobile device is referenced against a large (remote) database of geographic locations/addresses of APs.
  • AP Wi-Fi access point
  • Wi-Fi location has been used for location on a large-area, "macro-positioning" basis that generally yields accuracy to the level of a building or address.
  • many established vendors and startups have in the past year taken up the challenge of highly accurate indoor location using Wi-Fi access points as reference positions.
  • Wi-Fi-based RFPM for indoor positioning
  • vendors are exploring the use of other location technologies, such as timing-based position calculation using Wi-Fi access point references.
  • the video feed shows a large number of users, it may not be that easy to differentiate the movement of one particular user versus another, no matter how finely the video feed is examined in time.
  • the video feed may show only what we will hereinafter refer to as "blobs", i.e., objects that cannot be clearly characterized as person A rather than person B, but simply as a vague shape conforming to the outline of a human being when viewed from the vantage point of a video camera that is typically placed at ceiling level.
  • a video based location tracking system must have a user identification component as well as a location determining and tracking component. Since we are particularly interested in mobile device users, the identification component can occur in some interaction with the mobile, whereas the location determining and tracking component is independent of whether the user has or does not have an active mobile device in his possession. Additionally, the mobile device itself can be involved in the location determination and tracking, quite irrespective of whether there is a purely video location tracking system in operation.
  • any of the concepts developed here and applicable to locating and tracking human users indoors may equally well be applied to humans outdoors as well as other objects in different settings. Examples of interest could include tracking poachers in a game preserve observed from drones, cars on roads, boats on a lake, train cars in a switchyard, aircraft at an airport, inventory items, etc. While certain embodiments described below are discussed with respect to a store or other particular setting, those of skill in the art will readily understand that the described techniques and principles are not limited to use in a store and are applicable to other indoor and/or outdoor settings consistent with the present disclosure.
  • the video network can generally locate a user to within a few meters, and since identity is maintained by continuously comparing the image with the reference (where "continuously” may mean “often”, “periodically” with a small amount of time between comparisons, or within other appropriate time/space constraints to as to be able to distinguish user M from other objects), this information can be very specific, even to the degree of, for example, telling the user to turn around and look for an item on a particular , shelf behind her.
  • the LE makes use of its video network to obtain characterizing pictures, for example facial pictures which are re-matched with a reference image(s) to establish identity.
  • characterizing pictures for example facial pictures which are re-matched with a reference image(s) to establish identity.
  • a very well thought out, planned, and positioned network of video cameras is needed to achieve this end.
  • Other characteristics such as size, gait, etc. are also potentially applicable to the re-identification problem.
  • temporary characteristics that generally remain fixed at least for the duration of this store visit, such as the color of the shirt or jacket worn by the user can also be used.
  • the LE can maintain separate location tracks for both objects diverging from blob AB until such time as when identity can be re-established using better positioned cameras.
  • identity can be re-established using better positioned cameras.
  • This maintenance of two separate tracks can easily be generalized to allow for multiple divergences and multiple unresolved candidate track maintenance over the short haul.
  • the LE system can maintain a large number of viable tracks for each user until these tracks can be resolved to produce the correct track.
  • the initial identification is achieved using video.
  • a case of interest is where the user M and the location determining entity LE share an application that compares stored images of the user to the images available on the video feed. If a good match is established, LE has acquired the identity of M.
  • T the non-video technology mix used to re-acquire identity
  • T could be any one of the technology types used in location as detailed earlier, or a combination of one or more of them.
  • T implicitly has some form of identity of the user.
  • This concept can even be activated and applied to users that have a currently-known identity. If such a user is the only occupant (only blob) in some sub- region S in which T places him, then the identity of this user as derived from T must match whatever identity that blob has been currently assigned. If that is not true, it must mean that the user identity has not been derived correctly. It can be noted that for each possible discrete set of measurement values in T, it is possible to define such a sub- region. Thus, the location space can be thought of as having a potentially very large number of possibly overlapping sub-regions, each of which maps to a set of observations in T. An algorithm running in the background can examine when any one of these sub- regions shows a single blob in the video imagery. At every such time, user identity can be confirmed.
  • each blob is a candidate for one of several identities. This concept is elaborated on further below.
  • T can help re-acquire identity
  • T is used to communicate to the user to raise his hand.
  • raising his hand allows the video component to fully identify the user.
  • a suggestion conveyed via T to the user such as "turn around so we can help you better,” can lead the user to perform some action which the video imagery observes in S so as to identify the user.
  • these induced user behaviors can be made local to movements or rotations of the mobile device itself. Such movements could lead to information being passed back to the LE, such as information from a MEMS
  • the application that the user has signed up for to provide location specific information may have specific user interaction built in.
  • One example of this might be where the phone displays something to the user which is taken as a signal to wave the phone. This action can then be picked up by the video network to identify the user. If MEMS (or other) data is being reported back to the LE, further verification of whether this user did in fact wave his phone will also be available.
  • a general rule that can be distilled from the above example is to observe the variation in the Wi-Fi signals associated with a particular known identity, and then to use, for example, the general principles of signal attenuation with distance to associate the proper blob, thereby associating the proper human with the Wi-Fi identity.
  • the Wi-Fi signals themselves have very poor location resolution on their own but due to the independent movement of the users, the changes in the signals can allow us to estimate what identity should go with what blob, or human-like object.
  • Variations in the signal power caused not simply by distance but by angle, as might occur where a transmitting antenna has a certain beam shape (where this shape is known by the LE) can also be matched to the movement of blobs.
  • the store may insert a few judiciously-placed
  • Wi-Fi access points into the overall identification/location/tracking system. For example, if one had such a Wi-Fi access point in a passageway of a store where the signal increases dramatically and falls away similarly with distance, every user passing through is easily matched provided the video network provides even some low grained coverage of this passage. Alternatively, if the store is crowded and many users pass through the passageway at about the same time, we would be able to limit the identity ambiguity to the number of such users; that is, we would have groups of users who match collectively to a group of identities and then sort out the individual identities at a later time using the principles discussed herein.
  • Wi-Fi signals can substitute for Wi-Fi signals and be applied towards identity discovery in a similar manner.
  • Such a technique only needs to have some form of low resolution mapping of the signals or other measurable feature in the region of interest as well as some variation with location that can be differentiated. Assume, for example, that there is a window in the store where a passing user is able to pick up some distant cellular transmitter. If the user's mobile device reports this observation of the distant transmitter to a location application, and this event of the user passing the window is observable by a video network, we once again have a means of assigning identity.
  • the principle incorporates the variation of the entire observable set (or parts thereof) of measurements using technique T, due to the movement of a user within a venue, and correlating that variation with observed blobs in a video system.
  • a blob in a video can be associated to an identity.
  • one immediate advantage to the LE is that if any one of the group is identified, then by observing the common or nearby location of other video observed humans (or blobs), the LE can assign that group a set of identities. So, if there were a total of "N" identities that had at some stage not yet been assigned, and this group was of size "M", where M is at most N, then even without explicit assignment of individual identity to every member of the group the LE can at least temporarily assign the M identities to the group while concerning itself with the problem of which objects to assign the remaining (N-M) identities. In other words, it simplifies the identity assignment problem.
  • the unit with connectivity to the device of interest may also see many other mobile devices that are in proximity to the unit. Thus, in R] it may see a set Si of mobile IDs. Similarly in R 2 it may see a set S of mobile IDs, and in R 3 it may see a set S 3 of mobile IDs. Since the image of interest was in each of these regions, the mobile device ID for that image must be in each of these sets. Therefore, the image of interest must be in the intersection of these sets.
  • the identity of the image in so far as it can be linked to the identity of the mobile device associated with the image, can be sequentially narrowed down by taking the intersection of set Si with set S 2 , and then the intersection of that result with S 3 and so on.
  • the identity at least in terms of the mobile device associated with the image, has been discovered.
  • the object may be one or more individual persons, a group of people, a vehicle, a unit in an inventory, etc.
  • the object may be located outside or may be located in an enclosure, such as, but not limited to, a store, a shopping mall, a sports arena, a convention hall, etc.
  • the signature of the object includes a first and a second set of information.
  • the reference identification may be a set of measureable data such as, but not limited to, a picture, a video still or video clip, a phone number of a wireless device associated with the object, a MAC address for a wireless device associated with the object, infrared map, a mobile device application, etc.
  • the reference identification for the object should be sufficient to distinguish the object from another object that is within a particular space, sub-region, etc., that is being monitored.
  • a first set of information for the object is determined using a first monitoring system.
  • the first set of information includes location information for the object.
  • a second set of information for the object is determined using a second monitoring system.
  • the second set of information includes identification information for the object, such as discussed above.
  • the second set of information is compared to the reference identification determined at block 110. If the second set of information and the reference identification match, within some predetermined tolerance level, then an identification of the object has been made.
  • the signature of the object is determined based at least in part on the first set of information and the second set of information.
  • the object is tracked based at least in part on the determined signature of the object.
  • the object is provided with a third set of information such as, but not limited to, location information, navigation information, sales promotion information, advertising information, a mobile device application, etc.
  • the first monitoring system may be, but is not limited to, a video-based system, a sound-based system, an optics-based system, etc.
  • the second monitoring system may be, but is not limited to, a local area network, a Wi-Fi network, an RF ranging system, a proximity detection system, a RF pattern matching system, an RFID system, a pseudolite system, a GPS rebroadcast system, a GNSS rebroadcast system, a sound detection system, a light modulation system, a magnetic anomaly detection system, etc.
  • the first monitoring system and the second monitoring system may be any of the preceding systems or networks.
  • the object/user is associated with a wireless device that has a mobile application/software that requires the user (or someone else) to take one or more sense maps/reference IDs of the user (e.g., pictures, infrared maps, etc.) from different angles and face views and, optionally, extended time maps of the user (e.g., video, etc.) either stationary or performing one or more specific tasks (walking, jumping, packing boxes, etc.).
  • the sense map is stored on the user's wireless device/mobile application.
  • a sensing/monitoring network takes a similar sense map of the user in a possibly different place at a later time.
  • the user's wireless device/mobile application communicates with the sensing/monitoring network and compares one or more sense maps/reference IDs with the sense map taken by the sensing/monitoring network and if the comparison is within some predetermined tolerance, an identification of the user has been determined.
  • a particular monitored space such as a store
  • the same or a different sensing/monitoring network such as, for example, a video-based system
  • the signature of the user can be ascertained by combining the determined identification of the user with the user's location.
  • the user may be tracked throughout the store (or, perhaps, beyond depending on the reach of the video-based system) by the sensing/monitoring network (or a separate tracking system) and information may be pushed to the user such as the third set of information described above.
  • the signature of the object includes a first set of information and a second set of information.
  • the object may be one or more individual persons, a group of people, a vehicle, a unit in an inventory, etc.
  • the object may be located outside or may be located in an enclosure, such as, but not limited to, a store, a shopping mall, a sports arena, a convention hall, etc.
  • the signature of the object includes a first and a second set of information.
  • a reference identification is determined for the object.
  • the reference identification may be a set of measureable data such as, but not limited to, a picture, a video still or video clip, a phone number of a wireless device associated with the object, a MAC address for a wireless device associated with the object, infrared map, a mobile device application, etc.
  • the reference identification for the object should be sufficient to distinguish the object from another object that is within a particular space, sub-region, etc., that is being monitored.
  • the first set of information for the object is determined using a first monitoring system.
  • the first set of information includes location information for the object.
  • a second set of information for the object is determined using a second monitoring system where the second set of information includes a first and a second portion.
  • the second set of information includes identification information for the object, such as discussed above. The first portion of the second set of information for the object is determined from a second monitoring system and the second portion of the second set of information is determined from a third monitoring system.
  • the first and second portions of the second set of information are each individually compared with the reference identification determined at block 210.
  • either the first or the second portion of the second set of information is selected based on the comparison.
  • the selection is based on which of the first and second portion more closely matches the reference identification.
  • the "closeness" matching may be based on which set of data of the first and second portions has fewer deviations from the reference identification set of data.
  • the matching may be based on which set of data of the first and second portions is within some predetermined tolerance level.
  • the signature of the object is determined based at least in part on the first set of information and the selected portion of the second set of information.
  • the object is tracked based at least in part on the determined signature of the object.
  • the object is provided with a third set of information such as, but not limited to, location information, navigation information, sales promotion information, advertising information, a mobile device application, etc.
  • the first monitoring system may be, but is not limited to, a video-based system, a sound-based system, an optics- based system, etc.
  • the second monitoring system may be, but is not limited to, a local area network, a Wi-Fi network, an RF ranging system, a proximity detection system, a RF pattern matching system, an RFID system, a pseudolite system, a GPS rebroadcast system, a GNSS rebroadcast system, a sound detection system, a light modulation system, a magnetic anomaly detection system, etc.
  • the first monitoring system and the second monitoring system may be any of the preceding systems or networks.
  • a block diagram 300 is depicted for a system 303 for determining a signature of an object 301 according to an embodiment of the present subject matter.
  • the signature of the object includes a first set of information and a second set of information.
  • the object may be one or more individual persons, a group of people, a vehicle, a unit in an inventory, etc.
  • the object is located in a location space 302 which may be located outside or in an enclosure, such as, but not limited to, a store, a shopping mall, a sports arena, a convention hall, etc.
  • the signature of the object includes a first and a second set of information.
  • the system 303 includes a first monitoring system 321 having at least a first sensor 322 and a second monitoring system 331 having at least a second sensor 332.
  • First monitoring system 321 determines the first set of information for the object 301.
  • Second monitoring system 322 determines the second set of information for the object 301.
  • the first monitoring system may be, but is not limited to, a video-based system, a sound-based system, an optics-based system, etc.
  • the first sensor 322 may be a video camera that may be part of a video camera network which covers location space 302 which may be part of a larger space in which object 301 is to be monitored and/or tracked.
  • the second monitoring system may be, but is not limited to, a local area network, a Wi-Fi network, an RF ranging system, a proximity detection system, a RF pattern matching system, an RFID system, a pseudolite system, a GPS rebroadcast system, a GNSS rebroadcast system, a sound detection system, a light modulation system, a magnetic anomaly detection system, etc.
  • the second sensor 332 may be a Wi-Fi access point that may be part of a Wi-Fi network which covers location space 302 which may be part of a larger space in which object 301 is to be monitored and/or tracked.
  • the first monitoring system and the second monitoring system may be any of the preceding systems or networks.
  • system 303 includes circuitry and/or software and/or a memory device 311 for storing a reference identification for the object 301.
  • System 303 also includes a processor 380.
  • Processor 380 includes a comparator for comparing the second set of information with the reference identification in device 311, circuitry /device and/or software for determining the signature of the object 301 based at least in part on the first set of information and the second set of information, circuitry/device and/or software for tracking the object 301 based at least in part on the determined signature of the object, and circuitry/device and/or software for providing a third set of information to the object 301.
  • the third set of information may be, but is not limited to, one or more of location information, navigation information, sales promotion information, advertising information, and a mobile device application.
  • MLDC Mobile Location by Dynamic Clustering
  • the MLDC system is used to determine a location of a mobile device associated with an object using network measurement reports or similar information (which may include calibration data), clustering the information and comparing it with information received from the object's mobile device, and determining a location of the object/mobile device based on the comparison.
  • an MLDC system places a mobile device associated with an object in some region ⁇ x,y,z ⁇ of location space.
  • a video-based monitoring system such as a video camera network (“VCN"), shows only one object in the ⁇ x,y,z ⁇ region where that object has coordinates (xv,yv,zv).
  • VCN video camera network
  • the MLDC system uses the (xv,yv,zv) coordinates as the location estimate of the object.
  • a system such as system 303 in Figure 3, uses a first type of observation system to locate and track an object, and a second type of observation system to refme the location estimate from the first type of system, where the second type of observation system on its own is incapable of tracking the user.
  • system 303 uses Wi-Fi information to locate a user and then refines that location estimate using a VCN, where the VCN on its own cannot track the user.
  • the MLDC system uses Wi-Fi data to place an object's mobile device in some region ⁇ x,y,z ⁇ of location space.
  • Data from a VCN shows only one object in the ⁇ x,y,z ⁇ region where that object has coordinates (xv,yv,zv).
  • the MLDC system uses the (xv,yv,zv) coordinates as its location estimate of the object.
  • the VCN on its own can only tell how many objects (e.g., blobs, human like images) exist in one or more regions of the location space. The VCN cannot provide the identity of the object.
  • a VCN cannot provide continuous coverage over the locatable region (e.g., if the region includes an area which is out of range of the video cameras in the VCN), a situation may arise where the VCN cannot track an object.
  • the MLDC may be able to track the object where the VCN cannot, and where both the MLDC and the VCN are capable of tracking the object, the MLDC may use information from the VCN to improve its location estimate of the object.
  • algorithm A could be a generic "blob-following" algorithm.
  • algorithm A fails and cannot recover. Any entry into a non- VCN-covered region is a potential failure point.
  • the tracking of the object was being undertaken in conjunction with and MLDC system or any other location/tracking scheme using, e.g., Wi-Fi or other RF signals, the latter technique could track the object into and out of the region R. After the object has cleared region R, the latter technique could then pass tracking control back to the VCN.
  • Such a scheme would have the potential to utilize the VCN while not exhibiting complete failure points in the location space.
  • a region in a 2-D or 3-D space may be calibrated where the space has one or more distinguishing features ⁇ F ⁇ with known co-ordinates and where a mobile device being calibrated has no knowledge of ground truth (i.e., where exactly it is in space).
  • the desired calibration data will include an observation set (i.e., measurements at a mobile device of whatever type) at a set of locations. These observations are assumed to be a function of the (x,y,z) coordinates of the 2-D or 3-D space and may sometimes be dependent on the first or higher derivatives with respect to time of the (x,y,z) coordinates, representing velocity, acceleration, etc.
  • a mobile device in the space records observation data and stores the observation data along with a time stamp. Any arbitrary form of motion of the mobile is permissible in order to obtain the observation data.
  • a VCN may observe and record the motion of the mobile device.
  • the VCN uses a clock with some known relationship to the clock used by the mobile device. On completion of the movement of the mobile device through the space, corresponding instants of time from the VCN and the mobile observation record are matched. Given the video record, the set ⁇ F ⁇ can permit accurate calculation of the (x,y,z) coordinates of the mobile device. Successive frames also permit the calculation of higher derivatives representing velocity and acceleration. Now the mobile location and higher derivatives can be matched to the observations. Calibration is achieved.
  • Embodiments of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them.
  • Embodiments of the subject matter described in this specification can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a tangible program carrier for execution by, or to control the operation of, data processing apparatus.
  • the tangible program carrier can be a computer readable medium.
  • the computer readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, or a combination of one or more of them.
  • processor encompasses all apparatus, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers.
  • the processor can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them.
  • a computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and it can be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
  • a computer program does not necessarily correspond to a file in a file system.
  • a program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code).
  • a computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
  • FPGA field programmable gate array
  • ASIC application specific integrated circuit
  • processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer.
  • a processor will receive instructions and data from a read only memory or a random access memory or both.
  • the essential elements of a computer are a processor for performing instructions and one or more data memory devices for storing instructions and data.
  • a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks.
  • mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks.
  • a computer need not have such devices.
  • a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant ("PDA”), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, to name just a few.
  • PDA personal digital assistant
  • GPS Global Positioning System
  • Computer readable media suitable for storing computer program instructions and data include all forms data memory including non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto optical disks; and CD ROM and DVD- ROM disks.
  • semiconductor memory devices e.g., EPROM, EEPROM, and flash memory devices
  • magnetic disks e.g., internal hard disks or removable disks
  • magneto optical disks e.g., CD ROM and DVD- ROM disks.
  • the processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
  • embodiments of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a cathode ray tube (CRT) or liquid crystal display (LCD) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer.
  • a display device e.g., a cathode ray tube (CRT) or liquid crystal display (LCD) monitor
  • keyboard and a pointing device e.g., a mouse or a trackball
  • Other kinds of devices can be used to provide for interaction with a user as well; for example, input from the user can be received in any form, including acoustic, speech, or tactile input.
  • Embodiments of the subject matter described in this specification can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described is this specification, or any combination of one or more such back end, middleware, or front end components.
  • the components of the system can be interconnected by any form or medium of digital data communication, e.g., a
  • Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet.
  • LAN local area network
  • WAN wide area network
  • the computing system can include clients and servers.
  • a client and server are generally remote from each other and typically interact through a
  • client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

L'invention concerne des systèmes et des procédés permettant de déterminer une signature d'un objet tel qu'une personne, un groupe de personnes, un véhicule, un article en stock, etc. Dans un mode de réalisation, un ID de référence est déterminé pour un objet, un emplacement et une identification sont déterminés pour l'objet, et une signature de l'objet est déterminée à partir de l'emplacement et de l'identification déterminés de l'objet.
PCT/US2014/038806 2013-05-31 2014-05-20 Système et procédé d'identification et de suivi mobiles dans des systèmes de localisation Ceased WO2015069320A2 (fr)

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EP3169121A1 (fr) * 2015-11-16 2017-05-17 Accenture Global Solutions Limited Analyse de signal de réseau de télécommunication pour mettre en correspondance un identifiant cellulaire de dispositif mobile au moyen d'un identifiant de réseau d'un dispositif mobile
CN107889215A (zh) * 2017-12-01 2018-04-06 重庆邮电大学 基于标识管理的多级定位方法及系统
CN110109087A (zh) * 2019-05-07 2019-08-09 中国科学院声学研究所 一种声纳不规则探测范围显示方法及系统
JPWO2020240690A1 (fr) * 2019-05-28 2020-12-03
EP3771995A1 (fr) * 2019-07-31 2021-02-03 Palantir Technologies Inc. Détermination de géolocalisations d'objets sur la base de sources de données hétérogènes
EP3771994A1 (fr) * 2019-07-31 2021-02-03 Palantir Technologies Inc. Détermination de géolocalisations d`entités composites sur la base de sources de données hétérogènes
WO2021142017A1 (fr) * 2020-01-06 2021-07-15 Misapplied Sciences, Inc. Système d'informations de pôle de transport
WO2025159665A1 (fr) * 2024-01-23 2025-07-31 Telefonaktiebolaget Lm Ericsson (Publ) Appareil, procédé de détection et d'identification d'un objet

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EP3169121A1 (fr) * 2015-11-16 2017-05-17 Accenture Global Solutions Limited Analyse de signal de réseau de télécommunication pour mettre en correspondance un identifiant cellulaire de dispositif mobile au moyen d'un identifiant de réseau d'un dispositif mobile
CN109691193B (zh) * 2015-11-16 2021-02-09 埃森哲环球解决方案有限公司 用于对标识符进行匹配的方法和系统
US9973889B2 (en) 2015-11-16 2018-05-15 Accenture Global Solutions Limited Telecommunication network signal analysis for matching a mobile device cellular identifier with a mobile device network identifier
CN109691193A (zh) * 2015-11-16 2019-04-26 埃森哲环球解决方案有限公司 用于将移动设备蜂窝标识符与移动设备网络标识符进行匹配的电信网络信号分析
CN107889215B (zh) * 2017-12-01 2020-08-18 重庆邮电大学 基于标识管理的多级定位方法及系统
CN107889215A (zh) * 2017-12-01 2018-04-06 重庆邮电大学 基于标识管理的多级定位方法及系统
CN110109087A (zh) * 2019-05-07 2019-08-09 中国科学院声学研究所 一种声纳不规则探测范围显示方法及系统
JPWO2020240690A1 (fr) * 2019-05-28 2020-12-03
WO2020240690A1 (fr) * 2019-05-28 2020-12-03 日本電信電話株式会社 Système d'analyse de données et procédé d'analyse de données
JP7422755B2 (ja) 2019-05-28 2024-01-26 日本電信電話株式会社 データ解析システム、およびデータ解析方法
EP3771995A1 (fr) * 2019-07-31 2021-02-03 Palantir Technologies Inc. Détermination de géolocalisations d'objets sur la base de sources de données hétérogènes
US11586660B2 (en) 2019-07-31 2023-02-21 Palantir Technologies Inc. Determining object geolocations based on heterogeneous data sources
EP3771994A1 (fr) * 2019-07-31 2021-02-03 Palantir Technologies Inc. Détermination de géolocalisations d`entités composites sur la base de sources de données hétérogènes
EP4343577A1 (fr) * 2019-07-31 2024-03-27 Palantir Technologies Inc. Détermination de géolocalisations d'objets sur la base de sources de données hétérogènes
US11966430B2 (en) 2019-07-31 2024-04-23 Palantir Technologies Inc. Determining geolocations of composite entities based on heterogeneous data sources
US12111862B2 (en) 2019-07-31 2024-10-08 Palantir Technologies Inc. Determining object geolocations based on heterogeneous data sources
US12361045B2 (en) 2019-07-31 2025-07-15 Palantir Technologies Inc. Determining geolocations of composite entities based on heterogeneous data sources
WO2021142017A1 (fr) * 2020-01-06 2021-07-15 Misapplied Sciences, Inc. Système d'informations de pôle de transport
US11315526B2 (en) 2020-01-06 2022-04-26 Misapplied Sciences, Inc. Transportation hub information system
WO2025159665A1 (fr) * 2024-01-23 2025-07-31 Telefonaktiebolaget Lm Ericsson (Publ) Appareil, procédé de détection et d'identification d'un objet

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