Neuronal sensor networks

• US 20060097862A1
• Filed: 10/22/2004
• Published: 05/11/2006
• Est. Priority Date: 10/22/2004
• Status: Active Grant

• Current Assignee: HENEYWELL INTERNATIONAL INC.
• Original Assignee: Honeywell International Inc.
• Inventors: McKitterick, John B., Burne, Richard A.
• Granted Patent: US 7,429,923 B2
• Time in Patent Office: Days
• US Class Current: 340/521
• CPC Class Codes: G06N 3/02 Neural networks
• 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 69/329 in the application layer [OSI layer 7]

Abstract

A method for detecting significant events using neuronal sensor networks is provided. The method includes monitoring an environment surrounding a plurality of sensors for the presence of an event, when one or more events are detected, integrating the detected events over space and time using one or more collectors responsive to the plurality of sensors, determining when the one or more events are significant events and identifying and tracking significant events using processors responsive to the one or more collectors.

Claims

1. A system for detecting events using neuronal sensor networks, the system comprising:

a plurality of sensors that produce event detection signals when an event is detected and exceeds a minimum event threshold level;

one or more collectors adapted to receive one or more of the event detection signals and produce threshold detection signals; and

one or more processors, adapted to receive threshold detection signals from the one or more collectors;

wherein the event detection signals use a simple communication protocol.

2. The system of claim 1, wherein the sensors are deployed over a wide area.

3. The system of claim 1, wherein the one or more collectors are in close proximity to an associated subset of the plurality of sensors.

4. The system of claim 1, wherein each event detection signal provides the location of the event and strength of the event above a minimum event threshold level.

5. The system of claim 1, wherein each of the plurality of sensors comprise:

a controller that determines when an event exceeds a minimum event threshold level; and

a transmitter coupled to the controller that transmits the event detection signals.

6. The system of claim 1, wherein each of the plurality of sensors runs on ultra low power.

7. The system of claim 1, wherein each of the one or more collectors determines when a significant event occurs.

8. The system of claim 7, wherein each of the one or more collectors integrates event-detection signals over space and time to determine when a significant event occurs.

9. The system of claim 8, wherein each of the one ore more collectors transmits a threshold detection signal when a significant event is detected.

10. The system of claim 1, wherein each of the one or more processors uses threshold detection signals to track and identify significant events.

11. A method for detecting significant events using neuronal sensor networks, the method comprising:

monitoring an environment surrounding a plurality of sensors for the presence of an event;

when one or more events are detected, integrating the detected events over space and time using one or more collectors responsive to the plurality of sensors;

determining when the one or more events are significant events. and identifying and tracking significant events using processors responsive to the one or more collectors.

12. The method of claim 11, wherein monitoring an environment surrounding a plurality of sensors for the presence of an event comprises:

monitoring the surrounding environment for an event;

determining whether the strength of the event exceeds the minimum event threshold level; and

transmitting an event detection signal to a collector when the strength of the event exceeds the minimum event threshold level.

13. The method of claim 12, wherein monitoring an environment surrounding a plurality of sensors for the presence of an event comprises:

monitoring the surrounding environment for an event;

determining whether the strength of the event exceeds the minimum event threshold level; and

transmitting an event detection signal to a collector and nearby sensors when the strength of the event exceeds the minimum event threshold level.

14. The method of claim 13, wherein the sensor lowers its minimum event threshold level when it receives an event detection signal from a nearby sensor.

15. The method of claim 14, wherein the sensor lowers its minimum event threshold level for a set period of time.

16. The method of claim 12, wherein using one or more collectors responsive to the plurality of sensors to integrate detected events over space and time and detect significant events comprises:

waiting for event detection signals from nearby sensors;

integrating received event detection signals over space and time into a stored summation;

determining whether the stored summation exceeds a minimum threshold level; and

transmitting a threshold detection signal when the stored summation exceeds the minimum threshold level.

17. A method for detecting events using neuronal sensors, the method comprising:

monitoring the surrounding environment for an event;

determining whether the strength of the event exceeds the minimum event threshold level; and

transmitting an event detection signal to a collector when the strength of the event exceeds the minimum event threshold level.

18. A system for detecting events using neuronal sensor networks, the system comprising:

a plurality of sensors that produce and receive event detection signals when an event is detected;

one or more collectors wherein each collector receives event detection signals from an associated subset of the plurality of sensors and produce threshold detection signals; and

one or more processors adapted to receive threshold detection signals from the one or more collectors;

wherein the event detection signals use a simple communication protocol.

19. The system of claim 18, wherein the plurality of sensors are deployed over a wide area.

20. The system of claim 19, wherein each of the one or more collectors is in close proximity to its associated subset of sensors.

21. The system of claim 19, wherein each of the plurality of sensors will produce an event detection signal when an event exceeds a minimum event threshold level.

22. The system of claim 19, wherein the event detection signal provides the location of the sensor event and the strength of the event above a minimum event threshold level.

23. The system of claim 19, wherein each of the plurality of sensors comprise:

a controller that detects when an event exceeds a minimum event threshold level;

a transmitter coupled to the controller that transmits event detection signals; and

a receiver coupled to the controller that receives event detection signals.

24. The system of claim 19, wherein each of the plurality of sensors will lower its minimum event threshold level when it receives event detection signals from nearby sensors.

25. The system of claim 19, wherein each of the plurality of sensors run on ultra low power.

26. The system of claim 19, wherein each of the plurality of sensors runs on power obtained from the environment.

27. The system of claim 19, wherein one or more of the plurality of sensors runs on power obtained by the event that was detected.

28. The system of claim 27, wherein the event that was detected was stepping on one or more of the plurality of sensors.

29. The system of claim 19, wherein each of the one or more of collectors determine when a significant event occurs.

30. The system of claim 29, wherein each of the one or more of collectors integrate event detections signals over space and time to determine when a significant event occurs.

31. The system of claim 30, wherein each of the one or more collectors transmit a threshold detection signal when a significant event is detected.

32. The system of claim 19, wherein each of the one or more processors uses threshold detection signals to track and identify significant events.

33. A method for detecting events using sensors from neuronal sensor networks, the method comprising:

monitoring the surrounding environment for an event;

determining whether the strength of the event exceeds the minimum event threshold level; and

transmitting an event detection signal to a collector and nearby sensors when the strength of the event exceeds the minimum event threshold level.

34. The method of claim 33, wherein the neuronal sensor lowers its minimum event threshold level when it receives an event detection signal from a nearby sensor.

35. The method of claim 34, wherein the neuronal sensor lowers its minimum event threshold level for a set period of time.

36. A method for detecting significant events using collectors from neuronal sensor networks, the method comprising:

waiting for event detection signals from nearby sensors;

integrating received event detection signals over space and time into a stored summation;

determining whether the stored summation exceeds a minimum threshold level; and

transmitting a threshold detection signal when the stored summation exceeds the minimum threshold level;

wherein the event detection signals use a simple communication protocol.