SYSTEM AND METHOD FOR EVENT DETECTION AND CORRELATION FROM MOVING OBJECT SENSOR DATA

• US 20130111012A1
• Filed: 10/31/2011
• Published: 05/02/2013
• Est. Priority Date: 10/31/2011
• Status: Active Grant

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Inventors: Gupta, Chetan Kumar, Mehta, Abhay, Wang, Song
• Granted Patent: US 9,262,294 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/3013 where the computing system is an embedded system, i.e. a combination of hardware and software dedicated to perform a certain function in mobile devices, printers, automotive or aircraft systems testing or monitoring of control systems or parts thereof G05B23/02
• CPC Class Codes: G06F 11/3058 Monitoring arrangements for monitoring environmental properties or parameters of the computing system or of the computing system component, e.g. monitoring of power, currents, temperature, humidity, position, vibrations thermal management in cooling arrangements of a computing system G06F1/206
• CPC Class Codes: G06F 11/328 Computer systems status display G06F11/327 takes precedence

Abstract

An exemplary embodiment of the present techniques may detect and correlate events from moving object sensor data by receiving data from a sensor. The data received from the sensor may be mapped, and events may be detected based on the mapped sensor data. Events from the mapped sensor data may be correlated online.

Claims

1. A system for event detection and correlation from moving object sensor data, the system comprising:

a processor that is adapted to execute stored instructions; and

a memory device that stores instructions, the memory device comprising processor-executable code, that when executed by the processor, is adapted to;

receive data from a sensor attached to a moving object;

map the data received from the sensor;

detect events based on the mapped sensor data; and

correlate the events online.

2. The system recited in claim 1, wherein the memory device includes processor-executable code adapted to correlate the events online using a hierarchical neighborhood tree.

3. The system recited in claim 1, wherein the memory device includes processor-executable code adapted to map the data received from the sensor by computing quantities related to each moving object and each segment from the data received across a network.

4. The system recited in claim 1, wherein the memory device includes processor-executable code adapted to detect events based on the mapped sensor data, the events including skyline events, static sensor anomaly events, or dynamic sensor anomaly events.

5. The system recited in claim 1, wherein the memory device includes processor-executable code adapted to detect events based on the mapped sensor data by discovering rules corresponding to the events.

6. The system recited in claim 1, wherein a static sensor anomaly event is described using an exponentially weighted moving average or Haar wavelets.

7. The system recited in claim 1, wherein the moving object is a vehicle and the segment is a roadway, or the moving object is an aircraft and the segment is a defined amount of airspace.

8. A method of event detection and correlation from moving object sensor data, the method comprising:

receiving data from a sensor;

mapping the data received from the sensor;

detecting events based on the mapped sensor data; and

correlating the events online.

9. The method recited in claim 8, comprising correlating the events online using a hierarchical neighborhood tree.

10. The method recited in claim 8, wherein receiving data from a sensor includes receiving a position report from a sensor across a network.

11. The method recited in claim 8, comprising detecting events based on the mapped sensor data at various levels of abstraction or across multiple segments.

12. The method recited in claim 8, wherein detecting events based on the mapped sensor data includes detecting static sensor anomaly events, dynamic sensor anomaly events, or skyline events based on the mapped sensor data.

13. The method recited in claim 8, wherein a static sensor anomaly event is described using an exponentially weighted moving average or Haar wavelets.

14. The method recited in claim 8, wherein a dynamic sensor anomaly event is detected by using an efficient indexing scheme over the dynamic sensor data.

15. A non-transitory, computer-readable medium, comprising code configured to direct a processor to:

receive data from a sensor;

map the data received from the sensor;

detect events based on the mapped sensor data; and

correlate the events online.

16. The non-transitory, computer-readable medium recited in claim 15, comprising correlating the events online using a hierarchical neighborhood tree.

17. The non-transitory, computer-readable medium recited in claim 15, wherein receiving data from a sensor includes receiving a position report from a sensor across a network.

18. The non-transitory, computer-readable medium recited in claim 15, wherein detecting events based on the mapped sensor data includes detecting static sensor anomaly events, dynamic sensor anomaly events, or skyline events based on the mapped sensor data.

19. The non-transitory, computer-readable medium recited in claim 15, wherein a static sensor anomaly event is described using an exponentially weighted moving average or Haar wavelets.

20. The non-transitory, computer-readable medium recited in claim 15, comprising discovering rules corresponding to the events after the events are detected.