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EP-3523763-B1 - IDENTIFICATIONS OF PATTERNS OF LIFE THROUGH ANALYSIS OF DEVICES WITHIN MONITORED VOLUMES

EP3523763B1EP 3523763 B1EP3523763 B1EP 3523763B1EP-3523763-B1

Inventors

  • EDUARDO, Recavarren
  • RICHARDSON, Brad
  • YANYO, Lynn

Dates

Publication Date
20260513
Application Date
20170726

Claims (15)

  1. A method for detecting and correlating patterns of entity habit between two or more unique entities through the detection of physical devices and the associated two or more unique entities within a dynamic monitored volume (300), comprising: providing a sensor associated with a processor passively monitoring data being broadcast from any of a plurality of electromagnetic spectrum emitting devices; said processor defining (304) a unique identifier for each of said electromagnetic spectrum data emitting devices; the processor analyzing received electromagnetic spectrum emitted data sets to catalog the various data sets being broadcast and the time of capture for said electromagnetic spectrum data emitting devices within said dynamic monitored volume (300); storing in a database (212) associated with a server one or more created database records within said database and presenting (216) any of said database records to a user upon user request; analyzing the electromagnetic spectrum emitted data sets, defining (304) a unique emitter identifier, logging the time when the data sets were emitted, and identifying the monitored volume or volumes (300) within which the data sets were emitted; storing the collected data on said server, and deriving analytics (404) to define patterns of entity habit on commonalities and correlations between collected data sets in the manner in which the associated two or more unique entities act and with whom they act, to create patterns and relationships between two or more previously seemingly unrelated unique entities within the dynamic monitored volume (300); and displaying (216, 316, 414) said derived patterns of entity habit between two or more unique entities and analytics associated with the collected data to a user in a visual representation.
  2. The method of claim 1, where a visual spectrum data portion of the electromagnetic spectrum data is captured by one or more of a camera, smartphone camera, or visible spectrum image capture device, wherein where the visual spectrum data captured is associated with one or more electromagnetic spectrum data emitting devices.
  3. The method of claim 1, further comprising capturing infrared data by an infrared camera or other infrared capture device, wherein the infrared data captured is associated with one or more electromagnetic spectrum data emitting devices.
  4. The method of claim 1, further comprising capturing ultraviolet data by an ultraviolet camera or other ultraviolet capture device, wherein the ultraviolet data captured is associated with one or more electromagnetic spectrum data emitting devices.
  5. The method of claim 1, further comprising capturing hyperspectral data by a hyperspectral camera or other hyperspectral capture device, wherein the hyperspectral data captured is associated with one or more electromagnetic spectrum data emitting devices.
  6. The method of claim 1, further comprising creating data structures to provide correlations between data sets, metrics, and predictions associated with each electromagnetic spectrum data emitting device within a monitored volume (300), determining points of correlation between electromagnetic spectrum emitting devices and the two or more unique entities carrying or associated with said electromagnetic spectrum data emitting devices; wherein information derived from the collected data of one or more emitters provide information about the monitored emitter(s)' previous network associations with other devices outside of any monitored volume (300).
  7. The method of claim 1, where information derived from the collected data of one or more emitters provide information about the monitored emitter(s)' previous network associations with other devices outside of any monitored volume (300).
  8. The method of claim 1, wherein: the plurality of electromagnetic spectrum emitting devices is a plurality of wireless networking protocol emitting devices; and the electromagnetic spectrum data is wireless networking protocol data.
  9. The method of claim 8, where the visual spectrum data and/or infrared data and/or ultraviolet data and/or hyperspectral data captured is associated with one or more wireless networking protocol data emitting devices.
  10. The method of claim 8, further comprising capturing acoustic pressure wave data by an acoustic pressure wave microphone or other acoustic pressure wave capture device, wherein the acoustic pressure wave data captured is associated (208) with one or more wireless networking protocol data emitting devices.
  11. The method of claim 8, further comprising creating data structures to provide correlations between data sets, metrics, and predictions associated with each wireless networking protocol data emitting device within a monitored volume (300).
  12. The method of claim 11, further comprising determining points of correlation between wireless networking protocol emitting devices and the two or more unique entities carrying and/or associated with said wireless networking protocol data emitting devices.
  13. The method of claim 8, where information derived from the collected data of one or more emitters provide information about the monitored emitters' previous network associations with other devices outside of the any monitored volume (300).
  14. The method of claim 1, where detected RF (200) or wireless communication data is associated with an object in a camera's field of view by using one or more directional antennas.
  15. The method of claim 1, for bringing two or more unique entities, within two or more monitored volumes (300), to co-location, wherein the physical devices are mobile devices or smart phones, and each unique entity is associated with a mobile device or smart phone and dynamic monitored volumes (300) are created for each unique entity; and bringing said dynamic monitored volumes (300) to coincidence in time and space by calculating whether the distance between the two or more unique entities is increasing or decreasing and sending an instruction to the devices that the one or more other unique entities is in range.

Description

COPYRIGHT NOTICE A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction of the patent document or the patent disclosure, as it appears in the European Patent Office patent file or records, but otherwise reserves all copyright rights whatsoever. CLAIM TO PRIORITY: This application claims under 35 U.S.C. § 120, the benefit of the Provisional Application 62/369,265, filed 08/01/2016, Titled "Dignus Application and Facilitated Meetings". BACKGROUND Since 2007, a large proportion of human beings in the world have adopted the use of smart phones which they carry on their person as part of their daily routine. These smart phones have associated signatures and unique identifiers that, due to the constant proximity to the users who carry them, have become part of individual's personal identifiable information. Over the last several years, the use of smart phones has been augmented by networked wearable smart devices, and other portable networked communication devices used by an ever-growing proportion of the world's population. Wearable devices are usually smart watches or similar. Portable devices include laptop computers, tablet computers, Bluetooth enabled cars, etc. These wearable or portable devices are frequently networked with each other, and are increasingly exchanging data with other devices and systems known as the Internet of Things (IoT). Each of these devices has a uniquely identifiable signature. Moreover, as people tend to keep a radio frequency (RF)-emitting device for years, the unique identifiers associated with these RF-emitting devices has effectively become an enduring and consistent uniquely identifiable RF signature associated with the person that carries them. These RF signatures can be detected, measured, and used to identify an individual. This information can be used in environments where security is a concern. It is the Freya system which refers to the hardware, software, and user interaction that comprise the system for monitoring defined volumes through detecting and capturing emissions and reflections from the electromagnetic spectrum, including the Radio Frequency (RF) spectrum, human-visible spectrum, infrared spectrum, ultraviolet spectrum, hyperspectral range, and acoustic pressure waves. The Freya system also comprises recording the captured emissions and reflections, creating one or more databases composed of the recorded multispectral information, and providing detailed analytics derived from the overlay of RF spectrum and/or video data, and/or acoustic waves from said one or more created databases. Once the Freya system collects and stores this RF information into one or more defined databases, analytics can be drawn to provide significant intelligence about those emitters and associated humans present within the monitored volume. Freya provides unique identifiers for detected emitters; insights into the current network relationships between emitters, past and current; human relational networks within the monitored volume; and previous emitter locations prior to detection by the Freya system. Document CA2390352C describes a system for monitoring traffic including a population of users bearing a multiplicity of mobile communication devices, and methods useful for monitoring traffic, the system including a mobile communication network interface receiving, from at least one communication network serving the multiplicity of mobile communication devices, and storing, location information characterizing at least some of the multiplicity of mobile communication devices, and a traffic monitor operative to compute at least one traffic-characterizing parameter on the basis of the location information. BRIEF DESCRIPTION OF THE DRAWINGS Certain illustrative embodiments illustrating organization and method of operation, together with objects and advantages may be best understood by reference to the detailed description that follows taken in conjunction with the accompanying drawings in which: FIGURE 1 is a flow diagram of the application logic flow for device location and meeting consistent with certain embodiments of the present invention.FIGURE 2 is a view of the process flow for correlating video derived information with RF, infrared, and/or visible spectrum data forming multispectral data creation consistent with certain embodiments of the present invention.FIGURE 3 is a view of the process flow for creating unique identifiers for unknown RF and other spectrum emitters in a monitored volume consistent with certain embodiments of the present invention.FIGURE 4 is a view of the process flow for analyzing all collected monitoring and defining patterns of life for devices within a monitored volume for all spectra in which devices emit information, and providing metrics, predictions, and recommendations to a user consistent with certain embodiments of the present invent