Detecting location within a network

• US 9,474,042 B1
• Filed: 03/29/2016
• Issued: 10/18/2016
• Est. Priority Date: 09/16/2015
• Status: Active Grant

• Current Assignee: Ivani, LLC
• Original Assignee: Ivani, LLC
• Inventors: Preston, Victoria, Clark, Jonathan, Barnes, Claire, Wootton, John, Wootton, Matthew, Nissman, Chris, McKinney, Justin
• Primary Examiner(s): Heiber, Shantell L
• Application Number:
  US15/084,002
• Time in Patent Office: 203 Days
• US Class Current: 1/1
• CPC Class Codes: G01V 1/001 Acoustic presence detection
• CPC Class Codes: G01V 3/12 operating with electromagnetic waves operating with millimetre waves G01V8/005
• CPC Class Codes: G11C 11/221 using ferroelectric capacitors
• CPC Class Codes: G11C 11/2257 Word-line or row circuits
• CPC Class Codes: G11C 11/2259 Cell access
• CPC Class Codes: G11C 11/2273 Reading or sensing circuits or methods
• CPC Class Codes: G11C 11/2293 Timing circuits or methods
• CPC Class Codes: G11C 11/2297 Power supply circuits
• CPC Class Codes: H04B 17/27 for locating or positioning the transmitter
• CPC Class Codes: H04B 17/318 Received signal strength
• CPC Class Codes: H04B 17/373 Predicting channel quality or other radio frequency [RF] parameters
• CPC Class Codes: H04L 1/0018 based on latency requirement
• CPC Class Codes: H04L 5/006 Quality of the received signal, e.g. BER, SNR, water filling
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/131 Protocols for games, networked simulations or virtual reality
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/30 : Services specially adapted for particular environments, situations or purposes
• CPC Class Codes: H04W 4/33 : for indoor environments, e.g. buildings
• CPC Class Codes: H04W 4/50 : Service provisioning or reconfiguring
• CPC Class Codes: H04W 4/80 : Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: H04W 52/283 : Power depending on the position of the mobile
• CPC Class Codes: H04W 64/00 : Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Systems and methods for detecting the presence of a body in a network without fiducial elements, using signal absorption, and signal forward and reflected backscatter of RF waves caused by the presence of a biological mass in a communications network.

Claims

1. A method for detecting a presence of a human comprising:

providing a first transceiver disposed at a first location within a detection area;

providing a second transceiver disposed at a second location within said detection area;

a computer server communicably coupled to said first transceiver;

said first transceiver receiving a first set of wireless signals from said second transceiver when no human is within said detection area;

said computer server receiving a first set of signal data from said first transceiver, said first set of signal data comprising data about properties of said first set of wireless signals;

said computer server creating a baseline signal profile for wireless communications from said second transceiver to said first transceiver, said baseline signal profile being based at least in part on said properties of said first set of wireless signals in said first set of signal data when no human is present in said detection area;

said first transceiver receiving a second set of wireless signals from said second transceiver;

said computer server receiving a second set of signal data from said first transceiver, said second set of signal data comprising data about properties of said second set of wireless signals; and

said computer server determining if a human is present within said detection area, said determination based at least in part on a comparison of said properties of said second set of wireless signals in said second set of wireless signal data to said baseline signal profile.

2. The method of claim 1, wherein said properties of said first set of wireless signals comprise wireless network signal protocol properties determined by said first transceiver.

3. The method of claim 2, wherein said wireless network signal protocol properties are selected from the group consisting of:

received signal strength, latency, and bit error rate.

4. The method of claim 1, further comprising:

providing a third transceiver disposed at a third location within said detection area;

said first transceiver receiving a third set of wireless signals from said third transceiver when no human is present in said detection area;

said computer server receiving a third set of signal data from said first transceiver, said third set of signal data comprising data about properties of said third set of wireless signals;

said computer server creating a second baseline signal profile for wireless communications from said third transceiver to said first transceiver, said second baseline signal profile being based at least in part on said properties of said third set of wireless signals in said third set of signal data when no human is present in said detection area;

said first transceiver receiving a fourth set of wireless signals from said third transceiver;

said computer server receiving a fourth set of signal data from said first transceiver, said fourth set of signal data comprising data about properties of said fourth set of wireless signals; and

in said computer server determining if a human is present within said detection area, said determination is based at least in part on a comparison of said properties of said fourth set of wireless signals in said fourth set of signal data to said second baseline signal profile.

5. The method of claim 1, wherein said computer server determining applies statistical methods to said second set of wireless signal data to determine the presence of a human.

6. The method of claim 1, further comprising:

said computer server continuously determining the presence or absence of a human within said detection area, said determination based at least in part on a comparison of said baseline signal profile to continuously received signal data comprising data about the properties of wireless signals received at said first transceiver from said second transceiver; and

said computer continuously updating said baseline signal profile based on said continuously received signal data if said continuously received signal data indicates the absence of a human in said detection area.

7. The method of claim 1, further comprising:

said computer server determining how many humans are present within said detection area, said determination based at least in part on a comparison of said properties of said second set of wireless signals in said second set of wireless data to said baseline signal profile.

8. The method of claim 7, further comprising:

said computer server determining a location of all humans within said detection area, said determination based at least in part on a comparison of said received second set of signal properties to said baseline signal profile.

9. The method of claim 1, further comprising:

said computer server being operatively coupled to a second system; and

only after said computer server determines a human is present in said detection area, said computer server operates said second system.

10. The method of claim 9, wherein said first transceiver and said second system are configured to communicate using an identical communication protocol.

11. The method of claim 9, wherein said second system is an electrical system.

12. The method of claim 9, wherein said second system is a lighting system.

13. The method of claim 9, wherein said second system is a heating, venting, and cooling (HVAC) system.

14. The method of claim 9, wherein said second system is a security system.

15. The method of claim 9, wherein said second system is an industrial automation system.

16. The method of claim 1, wherein said wireless communication utilizes a protocol is selected from the group consisting of:

Bluetooth™

, Bluetooth™

Low Energy, ANT, ANT+, WiFi, Zigbee, and Z-Wave.

17. The method of claim 1, wherein said wireless communications from said second transceiver to said first transceiver have a carrier frequency in the range of 850 MHz and 17.5 GHz inclusive.

18. The method of claim 1, wherein said computer server determining if a human is present within said detection area is adjusted based on machine learning comprising:

determining a first sample location of a human having a fiducial element in said detection area, said first sample location being determined based upon detecting said fiducial element;

determining a second sample location of said human in said detection area, said second sample location being determined based at least in part on a comparison of said received second set of signal data to said baseline signal profile;

comparing said first sample location and said second sample location; and

adjusting said determination of said second sample location based upon said comparing.

19. The method of claim 1, further comprising:

said computer server storing a plurality of historical data records indicative of whether a human was present in the detection area over a period of time, each of said historical data records comprising an indication of a number of humans detected in said detection area and a date and time when each of said number of humans was detected in said detection area; and

said computer server making at least some of said plurality of historical data records available to one or more external computer systems via an interface.

20. A method for detecting a presence of a human comprising:

providing a first transceiver disposed at a first location within a detection area;

providing a second transceiver disposed at a second location within said detection area;

providing a computer server communicably coupled to said first transceiver;

providing a first external system operatively coupled to said computer server;

providing a second external system operatively coupled to said computer server;

said computer server receiving from said first transceiver a set of baseline signal data comprising data about signal properties of a first set of wireless signals received by said first transceiver from said second transceiver when no human is present in said detection area;

said computer server creating a baseline signal profile for wireless communications from said second transceiver to said first transceiver, said baseline signal profile being based at least in part on said signal properties of said first set of wireless signals in said set of baseline signal data when no human is present in said detection area;

said computer server receiving from said first transceiver a first set of sample signal data comprising data about signal properties of a second set of wireless signals received by said first transceiver from said second transceiver when a human is present in said detection area;

said computer server creating a first sample signal profile for wireless communications from said second transceiver to said first transceiver said first sample signal profile being based at least in part on said signal properties of said second set of wireless signals in said first sample signal data when a human is present in said detection area;

said computer server receiving from said first transceiver a second set of sample signal data comprising data about signal properties of a third set of wireless signals received by said first transceiver from said second transceiver when a human is present in said detection area;

said computer server creating a second sample signal profile for wireless communications from said second transceiver to said first transceiver said second sample signal profile being based at least in part on said signal properties of said third set of wireless signals in said second set of sample signal data when a human is present in said detection area;

said computer server receiving from said first transceiver a third set of sample signal data comprising data about signal properties of a fourth set of wireless signals received by said first transceiver from said second transceiver when a human is present in said detection area;

said computer server determining to operate said first external system based upon said computer server determining that said data about signal properties of said fourth set of wireless signals in said third set of sample signal data corresponds to said first sample signal profile;

said computer server determining not to operate said second external system based upon said computer server determining that said data about signal properties of said fourth set of wireless signals in said third set of sample signal data does not correspond to said second sample signal profile.

21. The method of claim 20, wherein at least one of said computer server determining to operate said first external system or said computer server determining not to operate said second external system is adjusted based on machine learning comprising:

determining a first sample location of a human having a fiducial element in said detection area, said first sample location being determined based upon detecting said fiducial element;

determining a second sample location of said human in said detection area, said second sample location being determined based at least in part on a comparison of said received second set of sample signal data to said baseline signal profile;

comparing said first sample location and said second sample location; and

adjusting said determination of said second sample location based upon said comparing.

22. The method of claim 20, wherein said signal properties of said second set of wireless signals in said first sample signal data comprises properties selected from the group consisting of:

received signal strength, latency, and bit error rate.

23. The method of claim 20, wherein:

said computer server creating said first sample signal profile comprises applying statistical methods to said first set of sample signal data; and

said computer server creating said second sample signal profile comprises applying statistical methods to said second set of sample signal data.

24. The method of claim 20, further comprising:

said computer server continuously receiving from said first transceiver additional sets of baseline signal data comprising property data about the signal properties of a second set of wireless signals received by said first transceiver from said second transceiver, and said computer server updating said baseline signal profile based on said continuously received additional sets of baseline signal data when said continuously received sets of baseline signal data indicate the absence of a human in said detection area.

25. The method of claim 20, further comprising:

said computer server determining how many humans are present in said detection area based at least in part on a comparison of said third set of sample signal data to said baseline signal profile.

26. The method of claim 25, further comprising:

said computer server determining a location of all humans present in said detection area, said determination based at least in part on a comparison of said third set of sample signal data to said baseline signal profile.

27. The method of claim 21, wherein:

said computer server operates said first external system even if said signal properties of said fourth set of wireless signals in said third set of sample baseline signal data corresponds to said second sample baseline signal profile.

28. The method of claim 21, wherein:

said computer server operates said second external system only if said signal properties of said fourth set of wireless signals in said third set of sample baseline data corresponds to said second sample baseline signal profile.

29. The method of claim 21, wherein said wireless communications from said second transceiver to said first transceiver have a carrier frequency in the range of 850 MHz and 17.5 GHz inclusive.

30. The method of claim 21, further comprising:

said computer server storing a plurality of historical data records indicative of whether a human was present in the detection area over a period of time, each of said historical data records comprising an indication of a number of humans detected in said detection area and a date and time of when each of said number of humans was detected in said detection area; and

said computer server making at least some of said plurality of historical data records available to one or more external computer systems via an interface.