Automated asymmetric threat detection using backward tracking and behavioral analysis

• US 7,944,468 B2
• Filed: 07/05/2005
• Issued: 05/17/2011
• Est. Priority Date: 07/05/2005
• Status: Active Grant

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Inventors: Hoffman, Richard L., Taylor, Joseph A.
• Primary Examiner(s): Rao; Andy S.
• Assistant Examiner(s): Kim; Hee-Yong
• Application Number:
  US11/174,777
• Publication Number:
  US 20070011722A1
• Time in Patent Office: 2,142 Days
• Field of Search: 348/143
• US Class Current: 348/143
• CPC Class Codes: G08B 13/19608 Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
• CPC Class Codes: G08B 13/19613 Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
• CPC Class Codes: G08B 13/19656 Network used to communicate with a camera, e.g. WAN, LAN, Internet
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data

Abstract

A method and system of predictive threat detection is provided which utilizes data collected via a ubiquitous sensor network spread over a plurality of sites in an urban environment. The method includes the steps of: triggering an inquiry regarding a suspect entity at a current site in response to commission of a triggering action by the suspect entity; in response to the inquiry, compiling the data corresponding to the sites at which the suspect entity was detected by the sensor network; and analyzing the data to determine a threat status regarding the suspect entity.

Claims

1. A method of predictive threat detection utilizing data collected via a ubiquitous sensor network spread over a plurality of sites in an urban environment, the sites being classified according to site threat level, the method comprising:

a. triggering an inquiry regarding a suspect entity at a current site in response to commission of a triggering action by the suspect entity;

b. backtracking the suspect entity in response to the inquiry by collecting the data from each site at which the suspect entity was detected by the sensor network;

c. compiling a data set including a list of the sites at which the suspect entity was detected and the data corresponding thereto; and

d. comparing the list of sites included within the data set to the corresponding site threat level to determine a threat status regarding the suspect entity;

e. analyzing the data within the data set of the suspect entity to determine whether an interaction took place between the suspect entity and a subsequent entity;

f. upon determining that the interaction took place between the suspect entity and the subsequent entity, automatically repeating the backtracking, compiling, and comparing steps for the subsequent entity to determine a threat status regarding the subsequent entity;

g. analyzing the data within the data set of the subsequent entity to determine whether an interaction took place between the subsequent entity and an additional subsequent entity; and

h. upon determining that the interaction took place between the subsequent entity and the additional subsequent entity, automatically repeating the backtracking, compiling, and comparing steps for the additional subsequent entity to determine a threat status regarding the additional subsequent entity.

2. The method of claim 1 further including the step of:

reevaluating the threat status of at least one entity in response to at least one of;

the threat status of the additional subsequent entity and the data set for the additional subsequent entity.

3. The method of claim 1 wherein the interaction includes at least one of:

a physical transfer, a mental transfer, and a physical movement.

4. The method of claim 2 further including the steps of:

a. reanalyzing the data corresponding to the interaction to determine additional information regarding at least one of;

the physical transfer, the mental transfer, and the physical movement; and

b. reevaluating the threat status of at least one entity based on the additional information.

5. The method of claim 1 wherein upon collection of the data by the sensor network, the data is initially processed utilizing at least one of:

background subtraction and temporal differencing, resolving between multiple overlapping objects, classification of objects, tracking of objects, analysis of objects, and pattern matching.

6. The method of claim 5 wherein the processed data is used to derive one or more of:

an image, a movie, an object, a trace, an act, and an episode.

7. The method of claim 1 wherein additional system resources are allocated to process the data in response to the inquiry regarding the suspect entity.

8. The method of claim 1 further including the step of:

updating the site threat level of each of the respective sites at which the suspect entity was detected corresponding to the threat level of the suspect entity.

9. A method of predictive threat detection utilizing data collected via a ubiquitous sensor network spread over a plurality of sites in an urban environment, the method comprising:

a. triggering an inquiry regarding a suspect entity at a current site in response to commission of a triggering action by the suspect entity;

b. in response to the inquiry, compiling the data corresponding to the sites at which the suspect entity was detected by the sensor network; and

c. analyzing the data to determine a threat status regarding the suspect entity;

d. analyzing the data to determine whether an interaction took place between the suspect entity and a subsequent entity;

e. upon determining that the interaction took place between the suspect entity and a subsequent entity, automatically repeating the compiling and analyzing steps for the subsequent entity to determine a threat status regarding the subsequent entity;

f. reevaluating the threat status of the suspect entity in response to at least one of;

the threat status of the subsequent entity and the data set for the subsequent entity;

g. analyzing the data to determine whether an interaction took place between the subsequent entity and an additional subsequent entity; and

h. upon determining that the interaction took place between the subsequent entity and the additional subsequent entity, automatically repeating the compiling and analyzing steps for the additional subsequent entity to determine a threat status regarding the additional subsequent entity.

10. The method of claim 9 further including the step of:

reevaluating the threat status of at least one entity in response to at least one of;

the threat status of the additional subsequent entity and the data set for the additional subsequent entity.

11. The method of claim 9 wherein the analyzing step further includes:

identifying a behavior pattern of the entity based on the data.

12. The method of claim 11 wherein the threat status of the entity is reassessed based on the behavior pattern.