CA2638621A1 - An alerting system for safety, security, and business productivity having alerts weighted by attribute data - Google Patents
An alerting system for safety, security, and business productivity having alerts weighted by attribute data Download PDFInfo
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Classifications
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Abstract
The present invention is a video surveillance, storage, and alerting system having the following components. One or more surveillance cameras capture video data having attribute data, the attribute data representing importance of the surveillance cameras. One or more video analytics devices process the video data from one or more of the surveillance cameras and detect primitive video events in the video data. A
network management module monitors network status of the surveillance cameras, and the video analytics devices, and generates network events reflective of the network status of all subsystems. A correlation engine correlates two or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event. An alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine.
network management module monitors network status of the surveillance cameras, and the video analytics devices, and generates network events reflective of the network status of all subsystems. A correlation engine correlates two or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event. An alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine.
Claims (107)
1. A video surveillance, storage, and alerting system, comprising:
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices, adapted to process the video data from one or more of the surveillance cameras and to detect primitive video events in the video data;
one or more audio sensory devices for capturing audio data having attribute data, the attribute data representing importance of the audio sensory devices;
one or more audio analytics devices adapted to process the audio data from one or more of the audio sensory devices and to detect audio events in the audio data;
a video tip module for receiving video tips from one or more external sources, adapted to extract meta-data and attribute data from the video tips and to generate tip events based on the extracted meta-data and attribute data, the attribute data representing the importance of the video tips;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras, the audio data from the audio sensory devices, and the video tips from the video tip module, the hierarchy of data storage devices connected to the surveillance cameras, the audio sensory devices, and the video tip module via a network;
a hierarchical storage manager for managing storage and cascade of the video data, the audio data, and the video tips in the hierarchy of data storage devices based on the attribute data corresponding to the source of the video data, the audio data, and the video tips;
a network management module for monitoring network status of the surveillance cameras, the audio sensory devices, and the data storage devices, the network management module adapted to generate network events reflective of the network status of all subsystems;
a vehicle information module for retrieving information about a vehicle detected in the video data based on the detected vehicle's license plate, and adapted to generate vehicle events based on the information retrieved about the vehicle;
a correlation engine for correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data, tip events from the video tip module weighted by the extracted attribute data of the video tips, network events from the network management module weighted by attribute data of device corresponding to the network event, and vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices, adapted to process the video data from one or more of the surveillance cameras and to detect primitive video events in the video data;
one or more audio sensory devices for capturing audio data having attribute data, the attribute data representing importance of the audio sensory devices;
one or more audio analytics devices adapted to process the audio data from one or more of the audio sensory devices and to detect audio events in the audio data;
a video tip module for receiving video tips from one or more external sources, adapted to extract meta-data and attribute data from the video tips and to generate tip events based on the extracted meta-data and attribute data, the attribute data representing the importance of the video tips;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras, the audio data from the audio sensory devices, and the video tips from the video tip module, the hierarchy of data storage devices connected to the surveillance cameras, the audio sensory devices, and the video tip module via a network;
a hierarchical storage manager for managing storage and cascade of the video data, the audio data, and the video tips in the hierarchy of data storage devices based on the attribute data corresponding to the source of the video data, the audio data, and the video tips;
a network management module for monitoring network status of the surveillance cameras, the audio sensory devices, and the data storage devices, the network management module adapted to generate network events reflective of the network status of all subsystems;
a vehicle information module for retrieving information about a vehicle detected in the video data based on the detected vehicle's license plate, and adapted to generate vehicle events based on the information retrieved about the vehicle;
a correlation engine for correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data, tip events from the video tip module weighted by the extracted attribute data of the video tips, network events from the network management module weighted by attribute data of device corresponding to the network event, and vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
2. The video surveillance, storage, and alerting system of claim 1, further comprising:
a normalization engine for normalizing the primitive events from the video analytics devices, the audio sensory devices, the video tip module, the network management module, and the vehicle information module.
a normalization engine for normalizing the primitive events from the video analytics devices, the audio sensory devices, the video tip module, the network management module, and the vehicle information module.
3. The video surveillance, storage, and alerting system of claim 2, wherein the correlation engine further comprises:
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules; and a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules; and a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
4. The video surveillance, storage, and alerting system of claim 3, wherein the correlation engine further comprises:
a compound event detection module for detecting compound events composed of two or more primitive events.
a compound event detection module for detecting compound events composed of two or more primitive events.
5. The video surveillance, storage, and alerting system of claim 4, wherein the correlation engine further comprises:
a first event correlation module for correlating the primitive events and the compound events across time;
a second event correlation module for correlating the primitive events and the compound events across space; and a rules engine for evaluating one or more rules based on the correlation performed by the first event correlation module and the second event correlation module.
a first event correlation module for correlating the primitive events and the compound events across time;
a second event correlation module for correlating the primitive events and the compound events across space; and a rules engine for evaluating one or more rules based on the correlation performed by the first event correlation module and the second event correlation module.
6. The video surveillance, storage, and alerting system of claim 5, further comprising:
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alert engine.
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alert engine.
7. The video surveillance, storage, and alerting system of claim 1, wherein the network management module further comprises:
a topological map module for constructing a topological map of the network, wherein the topological map includes icons for the surveillance cameras, the audio sensory devices, and the data storage devices, and wherein the icons are connected by lines representing a backbone of the network.
a topological map module for constructing a topological map of the network, wherein the topological map includes icons for the surveillance cameras, the audio sensory devices, and the data storage devices, and wherein the icons are connected by lines representing a backbone of the network.
8. The video surveillance, storage, and alerting system of claim 7, wherein the network management module further comprises:
a physical map module for constructing a physical map of the network, wherein the physical map includes icons corresponding to physical locations of the surveillance cameras, the audio sensory devices, and the data storage devices, and wherein the physical map includes at least a street map view and a satellite map view.
a physical map module for constructing a physical map of the network, wherein the physical map includes icons corresponding to physical locations of the surveillance cameras, the audio sensory devices, and the data storage devices, and wherein the physical map includes at least a street map view and a satellite map view.
9. The video surveillance, storage, and alerting system of claim 8, wherein the icons corresponding to the physical locations of the surveillance cameras have plumes indicating line-of-sight of the surveillance cameras.
10. The video surveillance, storage, and alerting system of claim 9, wherein the icons and their associated plumes indicate a network state as well as a change of network state of the surveillance cameras as determined by the network management module, and wherein the physical map shows areas of coverage as well as dark areas indicative of the network state of the surveillance cameras.
11. The video surveillance, storage, and alerting system of claim 8, wherein the icons corresponding to the physical locations of the audio sensory devices have concentric circles indicating an area of coverage of the audio sensory devices.
12. The video surveillance, storage, and alerting system of claim 1, wherein the hierarchical storage manager queries a sources table database to extract attribute data about sensory devices used to capture data being cascaded.
13. The video surveillance, storage, and alerting system of claim 12, wherein the hierarchy of data storage devices includes at least a first-tier device and a second-tier device, the first-tier device having a higher data access performance and a lower storage capacity than the second-tier device, and wherein the hierarchical storage manager cascades the video data from the first-tier device to the second-tier device based at least on importance of the video data.
14. The video surveillance, storage, and alerting system of claim 13, wherein the hierarchical storage manager further comprises:
a rules engine for determining storage locations for segments of video data based on a set of rules based on the importance of the video data; and a rules update module for updating the set of rules for segments of video data based on historical access patterns.
a rules engine for determining storage locations for segments of video data based on a set of rules based on the importance of the video data; and a rules update module for updating the set of rules for segments of video data based on historical access patterns.
15. The video surveillance, storage, and alerting system of claim 14, wherein the importance of the video data is calculated based on attribute data of the surveillance camera used to capture the video data, the primitive events detected in the video data, time period the video data was recorded, and time since the video data was last accessed.
16. The video surveillance, storage, and alerting system of claim 14, wherein the importance of the video data is calculated as a weighted average of attributes of the video data, wherein the attributes include resolution of the video data, age of the surveillance camera used to capture the video data, time since the surveillance camera was last maintained, location of the surveillance camera used to capture the video data, and primitive events detected in the video data.
17. The video surveillance, storage, and alerting system of claim 14, wherein the first-tier device is a disk array and the second-tier device is a tape array.
18. The video surveillance, storage, and alerting system of claim 1, wherein the vehicle information module further comprises:
an automatic license plate recognition engine for recognizing a license plate on the vehicle, wherein the vehicle information module generates license plate events corresponding to the recognized license plate, and wherein the vehicle information module retrieves information from a law enforcement database based on the recognized license plate.
an automatic license plate recognition engine for recognizing a license plate on the vehicle, wherein the vehicle information module generates license plate events corresponding to the recognized license plate, and wherein the vehicle information module retrieves information from a law enforcement database based on the recognized license plate.
19. The video surveillance, storage, and alerting system of claim 18, wherein the vehicle information module generates warrant events corresponding to warrant information for a registered owner of the vehicle, and wherein the correlation engine correlates warrant events from the vehicle information module with other primitive events.
20. The video surveillance, storage, and alerting system of claim 19, wherein the vehicle information module generates wanted person events corresponding to wanted person information for a registered owner of the vehicle, and wherein the correlation engine correlates wanted person events from the vehicle information module with other primitive events.
21. The video surveillance, storage, and alerting system of claim 20, wherein the vehicle information module generates stolen plate events if the license plate corresponds to a stolen plate, and wherein the correlation engine correlates stolen plate events from the vehicle information module with other primitive events.
22. The video surveillance, storage, and alerting system of claim 83, wherein the vehicle information module returns pictures of a registered owner of the vehicle, and wherein the alerting engine sends the picture of the registered owner of the vehicle to a designated destination if a wanted person event is triggered for the registered owner of the vehicle.
23. A method of video surveillance, storage, and alerting, comprising the steps of:
capturing video data from one or more surveillance cameras having attribute data, the attribute data representing importance of the surveillance cameras;
capturing audio data from one or more audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
detecting primitive video events in the video data by performing image processing on the video data;
detecting audio events in the audio data by performing audio processing on the audio data;
receiving video tips from one or more external sources;
generating tip events from meta-data and attribute data extracted from the video tips, the attribute data representing importance of the video tips;
storing the video data, the audio data, and the video tips in a hierarchy of two or more data storage devices;
cascading the video data, the audio data, and the video tips from a first-level storage device to a second-level storage device based at least on importance of data, the first-tier device having a higher data access performance and a lower storage capacity than the second-tier device, the importance of the data based on attribute data corresponding to the source of the video data, the audio data, and the video tips, primitive events detected in the data, time period the data was recorded, and time since the data was last accessed;
generating network events indicative of the network status of all subsystems;
generating vehicle events based on information retrieved about a vehicle detected in the video data using the detected vehicle's license plate;
correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data, tip events from the video tip module weighted by the extracted attribute data of the video tips, network events from the network management module weighted by attribute data of device corresponding to the network event, and vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and activating one or more actions based on the correlation performed in the correlating step.
capturing video data from one or more surveillance cameras having attribute data, the attribute data representing importance of the surveillance cameras;
capturing audio data from one or more audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
detecting primitive video events in the video data by performing image processing on the video data;
detecting audio events in the audio data by performing audio processing on the audio data;
receiving video tips from one or more external sources;
generating tip events from meta-data and attribute data extracted from the video tips, the attribute data representing importance of the video tips;
storing the video data, the audio data, and the video tips in a hierarchy of two or more data storage devices;
cascading the video data, the audio data, and the video tips from a first-level storage device to a second-level storage device based at least on importance of data, the first-tier device having a higher data access performance and a lower storage capacity than the second-tier device, the importance of the data based on attribute data corresponding to the source of the video data, the audio data, and the video tips, primitive events detected in the data, time period the data was recorded, and time since the data was last accessed;
generating network events indicative of the network status of all subsystems;
generating vehicle events based on information retrieved about a vehicle detected in the video data using the detected vehicle's license plate;
correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data, tip events from the video tip module weighted by the extracted attribute data of the video tips, network events from the network management module weighted by attribute data of device corresponding to the network event, and vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and activating one or more actions based on the correlation performed in the correlating step.
24. The method of claim 23, further comprising:
recognizing a license plate on the detected vehicle;
generating license plate events corresponding to the recognized license plate containing the detected license plate;
retrieving information about the detected vehicle from a law enforcement database based on the recognized license plate;
generating warrant events corresponding to warrant information for a registered owner of the detected vehicle;
generating wanted person events corresponding to wanted person information for the registered owner of the detected vehicle;
generating stolen plate events if the license plate corresponds to a stolen plate;
normalizing the primitive video events, the audio events, the tip events, the network events, and the vehicle events;
filtering out primitive events based on a set of privacy rules;
filtering out primitive events based on a set of business rules;
detecting compound events composed of two or more primitive events, the primitive events being one or more primitive video events, audio events, tip events, network events, vehicle events, license plate events, warrant events, wanted person events, and stolen plate events;
correlating the primitive events and the compound events across time weighted by the associated attribute data;
correlating the primitive events and the compound events across space weighted by the associated attribute data;
evaluating one or more rules based on the correlation performed by the correlating steps; and activating one or more actions based on the evaluated rules.
recognizing a license plate on the detected vehicle;
generating license plate events corresponding to the recognized license plate containing the detected license plate;
retrieving information about the detected vehicle from a law enforcement database based on the recognized license plate;
generating warrant events corresponding to warrant information for a registered owner of the detected vehicle;
generating wanted person events corresponding to wanted person information for the registered owner of the detected vehicle;
generating stolen plate events if the license plate corresponds to a stolen plate;
normalizing the primitive video events, the audio events, the tip events, the network events, and the vehicle events;
filtering out primitive events based on a set of privacy rules;
filtering out primitive events based on a set of business rules;
detecting compound events composed of two or more primitive events, the primitive events being one or more primitive video events, audio events, tip events, network events, vehicle events, license plate events, warrant events, wanted person events, and stolen plate events;
correlating the primitive events and the compound events across time weighted by the associated attribute data;
correlating the primitive events and the compound events across space weighted by the associated attribute data;
evaluating one or more rules based on the correlation performed by the correlating steps; and activating one or more actions based on the evaluated rules.
25. An alerting system, comprising:
one or more sensors for capturing sensory data;
one or more processors, operatively coupled to the one or more sensors; and one or more memories, operatively coupled to the one or more processors, the one or more memories comprising program code to:
capture sensory data from the one or more sensors;
capture attribute data representing information about the sensors used to capture the sensory data;
process the sensory data from the one or more sensors to detect primitive events in the sensory data;
correlate two or more primitive events, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and perform one or more actions based on the correlation performed in the correlating step.
one or more sensors for capturing sensory data;
one or more processors, operatively coupled to the one or more sensors; and one or more memories, operatively coupled to the one or more processors, the one or more memories comprising program code to:
capture sensory data from the one or more sensors;
capture attribute data representing information about the sensors used to capture the sensory data;
process the sensory data from the one or more sensors to detect primitive events in the sensory data;
correlate two or more primitive events, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and perform one or more actions based on the correlation performed in the correlating step.
26. The alerting system of claim 25, wherein the one or more sensors are selected from the group consisting of surveillance camera, surveillance microphone, temperature probe, pressure probe, speedometer, chlorine meter, radon meter, dust particle meter, CO2 meter, water meter, electrical meter, blood pressure meter, and heart rate meter.
27. The alerting system of claim 25, further comprising program code to:
filter out primitive events based on a set of privacy rules.
filter out primitive events based on a set of privacy rules.
28. The alerting system of claim 25, further comprising program code to:
detect compound events composed of two or more primitive events.
detect compound events composed of two or more primitive events.
29. The alerting system of claim 28, further comprising program code to:
time correlate the primitive events and the compound events across time;
space correlate the primitive events and the compound events across space; and evaluate one or more rules based on the correlation performed in the time correlating step and the space correlating step.
time correlate the primitive events and the compound events across time;
space correlate the primitive events and the compound events across space; and evaluate one or more rules based on the correlation performed in the time correlating step and the space correlating step.
30. The alerting system of claim 29, further comprising program code to:
generate one or more new rules based on the primitive events correlated in the correlating step and the actions performed in the action step.
generate one or more new rules based on the primitive events correlated in the correlating step and the actions performed in the action step.
31. The alerting system of claim 25, further comprising program code to:
receive tip data from one or more external sources;
determine attribute data for the tip data, the attribute data representing the reliability of the source of the tip data; and generate tip events based on the tip data and the attribute data.
receive tip data from one or more external sources;
determine attribute data for the tip data, the attribute data representing the reliability of the source of the tip data; and generate tip events based on the tip data and the attribute data.
32. The alerting system of claim 25, further comprising:
a hierarchy of two or more data storage devices for storing the sensory data from the one or more sensors, wherein the hierarchy of data storage devices is connected to the one or more sensors via a network.
a hierarchy of two or more data storage devices for storing the sensory data from the one or more sensors, wherein the hierarchy of data storage devices is connected to the one or more sensors via a network.
33. The alerting system of claim 32, further comprising program code to:
manage storage and cascade of the sensory data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the sensory data.
manage storage and cascade of the sensory data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the sensory data.
34. The alerting system of claim 32, wherein the hierarchy of data storage devices includes at least a first-tier device and a second-tier device, the first-tier device having a higher data access performance and a lower storage capacity than the second-tier device.
35. The alerting system of claim 33, further comprising program code to:
determine storage locations for segments of sensory data based on a set of rules based on the importance of the sensory data; and update the set of rules for segments of sensory data based on historical access patterns.
determine storage locations for segments of sensory data based on a set of rules based on the importance of the sensory data; and update the set of rules for segments of sensory data based on historical access patterns.
36. The alerting system of claim 25, further comprising program code to:
monitor network status of the one or more sensors; and generate network events reflective of the network status of the one or more sensors.
monitor network status of the one or more sensors; and generate network events reflective of the network status of the one or more sensors.
37. The alerting system of claim 25, further comprising program code to:
retrieve information about a vehicle detected in the sensory data based on the detected vehicle's license plate; and generate vehicle events based on the information retrieved about the vehicle.
retrieve information about a vehicle detected in the sensory data based on the detected vehicle's license plate; and generate vehicle events based on the information retrieved about the vehicle.
38. The alerting system of claim 37, further comprising program code to:
recognize a license plate on the vehicle;
generate license plate events corresponding to the recognized license plate;
and retrieve information from a law enforcement database based on the recognized license plate.
recognize a license plate on the vehicle;
generate license plate events corresponding to the recognized license plate;
and retrieve information from a law enforcement database based on the recognized license plate.
39. The alerting system of claim 38, further comprising program code to:
generate warrant events corresponding to warrant information for a registered owner of the vehicle; and correlate warrant events with other primitive events.
generate warrant events corresponding to warrant information for a registered owner of the vehicle; and correlate warrant events with other primitive events.
40. The alerting system of claim 38, further comprising program code to:
generate wanted person events corresponding to wanted person information for a registered owner of the vehicle; and correlate wanted person events with other primitive events.
generate wanted person events corresponding to wanted person information for a registered owner of the vehicle; and correlate wanted person events with other primitive events.
41. The alerting system of claim 38, further comprising program code to:
generate stolen plate events if the license plate corresponds to a stolen plate; and correlate stolen plate events with other primitive events.
generate stolen plate events if the license plate corresponds to a stolen plate; and correlate stolen plate events with other primitive events.
42. The alerting system of claim 38, further comprising program code to:
retrieve pictures of a registered owner of the vehicle; and send the picture of the registered owner of the vehicle to a designated destination if a wanted person event is triggered for the registered owner of the vehicle.
retrieve pictures of a registered owner of the vehicle; and send the picture of the registered owner of the vehicle to a designated destination if a wanted person event is triggered for the registered owner of the vehicle.
43. An alerting system, comprising:
one or more sensors for capturing sensory data having attribute data, the attribute data representing information about the sensors used to capture the sensory data;
one or more data processing units, adapted to process the sensory data from one or more of the sensors and to detect primitive events in the sensory data;
a correlation engine for correlating two or more primitive events from the data processing units, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more sensors for capturing sensory data having attribute data, the attribute data representing information about the sensors used to capture the sensory data;
one or more data processing units, adapted to process the sensory data from one or more of the sensors and to detect primitive events in the sensory data;
a correlation engine for correlating two or more primitive events from the data processing units, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
44. A method of alerting, comprising the steps of:
capturing sensory data from one or more sensors;
capturing attribute data, the attribute data representing information about the sensors used to capture the sensory data;
processing the sensory data from the sensors to detect primitive events in the sensory data;
correlating two or more primitive events, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and sending one or more alerts based on the correlation performed in the correlating step.
capturing sensory data from one or more sensors;
capturing attribute data, the attribute data representing information about the sensors used to capture the sensory data;
processing the sensory data from the sensors to detect primitive events in the sensory data;
correlating two or more primitive events, the primitive events weighted by the attribute data of the sensors used to capture the sensory data; and sending one or more alerts based on the correlation performed in the correlating step.
45. A video surveillance, storage, and alerting system, comprising:
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices, adapted to process the video data from one or more of the surveillance cameras and to detect primitive video events in the video data;
a network management module for monitoring network status of the surveillance cameras, and the video analytics devices, the network management module adapted to generate network events reflective of the network status of all subsystems;
a correlation engine for correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices, adapted to process the video data from one or more of the surveillance cameras and to detect primitive video events in the video data;
a network management module for monitoring network status of the surveillance cameras, and the video analytics devices, the network management module adapted to generate network events reflective of the network status of all subsystems;
a correlation engine for correlating two or more primitive events, the primitive events being one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
46. The video surveillance, storage, and alerting system of claim 45, further comprising:
a normalization engine for normalizing the primitive events from the video analytics devices and the network management module.
a normalization engine for normalizing the primitive events from the video analytics devices and the network management module.
47. The video surveillance, storage, and alerting system of claim 45, wherein the correlation engine further comprises:
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules.
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules.
48. The video surveillance, storage, and alerting system of claim 45, wherein the correlation engine further comprises:
a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
49. The video surveillance, storage, and alerting system of claim 45, wherein the correlation engine further comprises:
a compound event detection module for detecting compound events composed of two or more primitive events.
a compound event detection module for detecting compound events composed of two or more primitive events.
50. The video surveillance, storage, and alerting system of claim 49, wherein the correlation engine further comprises:
an event correlation module for correlating the primitive events and the compound events across time.
an event correlation module for correlating the primitive events and the compound events across time.
51. The video surveillance, storage, and alerting system of claim 49, wherein the correlation engine further comprises:
an event correlation module for correlating the primitive events and the compound events across space.
an event correlation module for correlating the primitive events and the compound events across space.
52. The video surveillance, storage, and alerting system of claim 45, wherein the correlation engine further comprises:
a rules engine for evaluating one or more rules based on the correlation performed by the correlation engine.
a rules engine for evaluating one or more rules based on the correlation performed by the correlation engine.
53. The video surveillance, storage, and alerting system of claim 45, further comprising:
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alert engine.
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alert engine.
54. A method of video surveillance, storage, and alerting, comprising the steps of:
capturing video data from one or more surveillance cameras having attribute data, the attribute data representing importance of the surveillance cameras;
processing the video data from one or more of the surveillance cameras to detect primitive video events in the video data;
monitoring network status of the surveillance cameras;
generating network events reflective of the network status of all subsystems;
correlating two or more primitive video events weighted by the attribute data of the surveillance cameras used to capture the video data and network events weighted by attribute data of device corresponding to the network event;
generating one or more alerts to one or more persons; and performing one or more actions based on the correlation performed in the correlating step.
capturing video data from one or more surveillance cameras having attribute data, the attribute data representing importance of the surveillance cameras;
processing the video data from one or more of the surveillance cameras to detect primitive video events in the video data;
monitoring network status of the surveillance cameras;
generating network events reflective of the network status of all subsystems;
correlating two or more primitive video events weighted by the attribute data of the surveillance cameras used to capture the video data and network events weighted by attribute data of device corresponding to the network event;
generating one or more alerts to one or more persons; and performing one or more actions based on the correlation performed in the correlating step.
55. The method of claim 54, further comprising:
normalizing the primitive video events and the primitive network events.
normalizing the primitive video events and the primitive network events.
56. The method of claim 54, further comprising:
filtering out primitive events based on a set of privacy rules.
filtering out primitive events based on a set of privacy rules.
57. The method of claim 54, further comprising:
out primitive events based on a set of business rules.
out primitive events based on a set of business rules.
58. The method of claim 54, further comprising:
detecting compound events composed of two or more primitive events.
detecting compound events composed of two or more primitive events.
59. The method of claim 54, further comprising:
correlating the primitive events and the compound events across time.
correlating the primitive events and the compound events across time.
60. The method of claim 54, further comprising:
correlating the primitive events and the compound events across space.
correlating the primitive events and the compound events across space.
61. The method of claim 54, further comprising:
evaluating one or more rules based on the correlation performed by in the correlating step.
evaluating one or more rules based on the correlation performed by in the correlating step.
62. The method of claim 54, further comprising:
generating one or more new rules based on the primitive events correlated in the correlating step and the alerts generated in the alerting step.
generating one or more new rules based on the primitive events correlated in the correlating step and the alerts generated in the alerting step.
63. An audio surveillance, storage, and alerting system, comprising:
one or more audio sensory devices for capturing audio data having attribute data, the attribute data representing importance of the audio sensory devices;
one or more audio analytics devices adapted to process the audio data from one or more of the audio sensory devices and to detect audio events in the audio data;
a network management module for monitoring network status of the audio sensory devices, the network management module adapted to generate network events reflective of the network status of the audio sensory devices;
a correlation engine for correlating two or more primitive events, the primitive events being one or more audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data and network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more audio sensory devices for capturing audio data having attribute data, the attribute data representing importance of the audio sensory devices;
one or more audio analytics devices adapted to process the audio data from one or more of the audio sensory devices and to detect audio events in the audio data;
a network management module for monitoring network status of the audio sensory devices, the network management module adapted to generate network events reflective of the network status of the audio sensory devices;
a correlation engine for correlating two or more primitive events, the primitive events being one or more audio events from the audio analytics devices weighted by the attribute data of the audio devices used to capture the audio data and network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
64. The audio surveillance, storage, and alerting system of claim 63, further comprising:
a normalization engine for normalizing the primitive events from the audio analytics devices and the network management module.
a normalization engine for normalizing the primitive events from the audio analytics devices and the network management module.
65. The audio surveillance, storage, and alerting system of claim 64, wherein the correlation engine further comprises:
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules.
a privacy filter for filtering out primitive events normalized by the normalization engine based on a set of privacy rules.
66. The audio surveillance, storage, and alerting system of claim 64, wherein the correlation engine further comprises:
a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
a business filter for filtering out primitive events normalized by the normalization engine based on a set of business rules.
67. The audio surveillance, storage, and alerting system of claim 63, wherein the correlation engine further comprises:
a compound event detection module for detecting compound events composed of two or more primitive events.
a compound event detection module for detecting compound events composed of two or more primitive events.
68. The audio surveillance, storage, and alerting system of claim 67, wherein the correlation engine further comprises:
an event correlation module for correlating the primitive events and the compound events across time.
an event correlation module for correlating the primitive events and the compound events across time.
69. The audio surveillance, storage, and alerting system of claim 67, wherein the correlation engine further comprises:
an event correlation module for correlating the primitive events and the compound events across space.
an event correlation module for correlating the primitive events and the compound events across space.
70. The audio surveillance, storage, and alerting system of claim 69, wherein the correlation engine further comprises:
a rules engine for evaluating one or more rules based on the correlation performed by the event correlation module.
a rules engine for evaluating one or more rules based on the correlation performed by the event correlation module.
71. The audio surveillance, storage, and alerting system of claim 63, further comprising:
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alerting engine.
a learning engine for generating one or more new rules based on the primitive events correlated by the correlation engine and the alerts generated by the alerting engine.
72. The audio surveillance, storage, and alerting system of claim 63, wherein the network management module further comprises:
a physical map module for constructing a physical map of the network including icons corresponding to physical locations of the audio sensory devices, the icons having concentric circles indicating an area of coverage of the audio sensory devices.
a physical map module for constructing a physical map of the network including icons corresponding to physical locations of the audio sensory devices, the icons having concentric circles indicating an area of coverage of the audio sensory devices.
73. The audio surveillance, storage, and alerting system of claim 63, further comprising:
a hierarchy of two or more data storage devices for storing the audio data from the audio sensory devices, the hierarchy of data storage devices connected to the audio sensory devices via a network.
a hierarchy of two or more data storage devices for storing the audio data from the audio sensory devices, the hierarchy of data storage devices connected to the audio sensory devices via a network.
74. The audio surveillance, storage, and alerting system of claim 73, further comprising:
a hierarchical storage manager for managing storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
a hierarchical storage manager for managing storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
75. The audio surveillance, storage, and alerting system of claim 74, wherein the hierarchical storage manager queries a sources table database to extract attribute data about sensory devices used to capture data being cascaded.
76. The audio surveillance, storage, and alerting system of claim 73, wherein the hierarchy of data storage devices includes at least a first-tier device and a second-tier device, the first-tier device having a higher data access performance and a lower storage capacity than the second-tier device.
77. The audio surveillance, storage, and alerting system of claim 74, wherein the hierarchical storage manager cascades the audio data from the first-tier device to the second-tier device based at least on importance of the audio data.
78. The audio surveillance, storage, and alerting system of claim 74, wherein the hierarchical storage manager further comprises:
a rules engine for determining storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and a rules update module for updating the set of rules for segments of audio data based on historical access patterns.
a rules engine for determining storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and a rules update module for updating the set of rules for segments of audio data based on historical access patterns.
79. The audio surveillance, storage, and alerting system of claim 77, wherein the importance of the audio data is calculated based on attribute data of the sensory device used to capture the audio data, the events detected in the audio data, time period the audio data was recorded, and time since the audio data was last accessed.
80. The audio surveillance, storage, and alerting system of claim 79, wherein the importance of the audio data is calculated as a weighted average of attributes of the audio data, and wherein the attributes include resolution of the audio data, age of the sensory device used to capture the audio data, time since the sensory device was last maintained, location of the sensory device used to capture the audio data, and primitive events detected in the audio data.
81. The audio surveillance, storage, and alerting system of claim 73, wherein the first-tier device is a disk array and the second-tier device is a tape array.
82. The audio surveillance, storage, and alerting system of claim 63, further comprising:
an audio tip module for receiving audio tips from one or more external sources via telephone or Internet, adapted to extract meta-data and attribute data from the audio tips and to generate tip events based on the extracted meta-data, the attribute data representing an importance of the audio tips.
an audio tip module for receiving audio tips from one or more external sources via telephone or Internet, adapted to extract meta-data and attribute data from the audio tips and to generate tip events based on the extracted meta-data, the attribute data representing an importance of the audio tips.
83. A method of audio surveillance, storage, and alerting, comprising the steps of:
capturing audio data from one or more audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
processing the audio data from one or more of the audio sensory devices to detect audio events in the audio data;
monitoring network status of the audio sensory devices to generate network events reflective of the network status of the audio sensory devices;
correlating two or more primitive events, the primitive events being one or more audio events weighted by the attribute data of the audio devices used to capture the audio data and network events weighted by attribute data of device corresponding to the network event; and performing one or more actions based on the correlation performed in the correlating step.
capturing audio data from one or more audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
processing the audio data from one or more of the audio sensory devices to detect audio events in the audio data;
monitoring network status of the audio sensory devices to generate network events reflective of the network status of the audio sensory devices;
correlating two or more primitive events, the primitive events being one or more audio events weighted by the attribute data of the audio devices used to capture the audio data and network events weighted by attribute data of device corresponding to the network event; and performing one or more actions based on the correlation performed in the correlating step.
84. The method of claim 83, further comprising:
filtering out primitive events based on a set of privacy rules.
filtering out primitive events based on a set of privacy rules.
85. The method of claim 83, further comprising:
filtering out primitive events based on a set of business rules.
filtering out primitive events based on a set of business rules.
86. The method of claim 83, further comprising:
detecting compound events composed of two or more primitive events.
detecting compound events composed of two or more primitive events.
87. The method of claim 86, further comprising:
correlating the primitive events and the compound events across time.
correlating the primitive events and the compound events across time.
88. The method of claim 86, further comprising:
correlating the primitive events and the compound events across space.
correlating the primitive events and the compound events across space.
89. The method of claim 83, further comprising:
evaluating one or more rules based on the correlation performed in the correlating step.
evaluating one or more rules based on the correlation performed in the correlating step.
90. The method of claim 86, further comprising:
generating one or more new rules based on the correlated primitive events and the generated alerts.
generating one or more new rules based on the correlated primitive events and the generated alerts.
91. The method of claim 83, further comprising:
displaying a physical map of the network including icons corresponding to physical locations of the audio sensory devices, the icons having concentric circles indicating an area of coverage of the audio sensory devices.
displaying a physical map of the network including icons corresponding to physical locations of the audio sensory devices, the icons having concentric circles indicating an area of coverage of the audio sensory devices.
92. The method of claim 83, further comprising:
storing the audio data from the audio sensory devices in a hierarchy of two or more data storage devices, the hierarchy of data storage devices connected to the audio sensory devices via a network.
storing the audio data from the audio sensory devices in a hierarchy of two or more data storage devices, the hierarchy of data storage devices connected to the audio sensory devices via a network.
93. The method of claim 92, further comprising:
managing storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
managing storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
94. The method of claim 92, further comprising:
determining storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and updating the set of rules for segments of audio data based on historical access patterns.
determining storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and updating the set of rules for segments of audio data based on historical access patterns.
95. The method of claim 83, further comprising:
receiving audio tips from one or more external sources via telephone or Internet;
extracting meta-data and attribute data from the audio tips, the attribute data representing an importance of the audio tips; and generating tip events based on the extracted meta-data.
receiving audio tips from one or more external sources via telephone or Internet;
extracting meta-data and attribute data from the audio tips, the attribute data representing an importance of the audio tips; and generating tip events based on the extracted meta-data.
96. An audio surveillance, storage, and alerting system, comprising:
one or more audio sensory devices;
one or more processors; and one or more memories, operatively coupled to one or more of the processors, and storing program code, which when executed causes one or more of the processors to:
capture audio data from one or more of the audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
process the audio data from one or more of the audio sensory devices to detect audio events in the audio data;
monitor network status of the audio sensory devices to generate network events reflective of the network status of the audio sensory devices;
correlate two or more primitive events, the primitive events being one or more audio events weighted by the attribute data of the audio devices used to capture the audio data and network events weighted by attribute data of device corresponding to the network event; and perform one or more actions based on the correlation performed in the correlating step.
one or more audio sensory devices;
one or more processors; and one or more memories, operatively coupled to one or more of the processors, and storing program code, which when executed causes one or more of the processors to:
capture audio data from one or more of the audio sensory devices having attribute data, the attribute data representing importance of the audio sensory devices;
process the audio data from one or more of the audio sensory devices to detect audio events in the audio data;
monitor network status of the audio sensory devices to generate network events reflective of the network status of the audio sensory devices;
correlate two or more primitive events, the primitive events being one or more audio events weighted by the attribute data of the audio devices used to capture the audio data and network events weighted by attribute data of device corresponding to the network event; and perform one or more actions based on the correlation performed in the correlating step.
97. The system of claim 96, further comprising program code to:
detect compound events composed of two or more primitive events.
detect compound events composed of two or more primitive events.
98. The system of claim 96, further comprising program code to:
correlate the primitive events and the compound events across time.
correlate the primitive events and the compound events across time.
99. The system of claim 96, further comprising program code to:
correlate the primitive events and the compound events across space.
correlate the primitive events and the compound events across space.
100. The system of claim 96, further comprising program code to:
generate one or more new rules based on the correlated primitive events and the generated alerts.
generate one or more new rules based on the correlated primitive events and the generated alerts.
101. The system of claim 96, further comprising:
a hierarchy of two or more data storage devices, the hierarchy of data storage devices connected to the audio sensory devices via a network, wherein one or more of the memories store program code to:
store the audio data from the audio sensory devices in the hierarchy of data storage devices.
a hierarchy of two or more data storage devices, the hierarchy of data storage devices connected to the audio sensory devices via a network, wherein one or more of the memories store program code to:
store the audio data from the audio sensory devices in the hierarchy of data storage devices.
102. The system of claim 101, further comprising program code to:
manage storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
manage storage and cascade of the audio data in the hierarchy of data storage devices based on the attribute data corresponding to the source of the audio data.
103. The system of claim 101, further comprising program code to:
determine storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and update the set of rules for segments of audio data based on historical access patterns.
determine storage locations for segments of audio data based on a set of rules based on the importance of the audio data; and update the set of rules for segments of audio data based on historical access patterns.
104. The system of claim 96, further comprising program code to:
receive audio tips from one or more external sources via telephone or Internet;
extract meta-data and attribute data from the audio tips, the attribute data represents an importance of the audio tips; and generate tip events based on the extracted meta-data.
receive audio tips from one or more external sources via telephone or Internet;
extract meta-data and attribute data from the audio tips, the attribute data represents an importance of the audio tips; and generate tip events based on the extracted meta-data.
105. A video surveillance, storage, and alerting system, comprising:
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
a video tip module for receiving video tips from one or more external sources, adapted to extract meta-data and attribute data from the video tips and to generate tip events based on the extracted meta-data and attribute data, the attribute data representing the importance of the video tips;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras and the video tips from the video tip module, the hierarchy of data storage devices connected to the surveillance cameras and to the video tip module via a network;
a hierarchical storage manager for managing storage and cascade of the video data and the video tips in the hierarchy of data storage devices based on the attribute data corresponding to a source of the video data and a source of the video tips;
and an alerting engine for generating one or more alerts and performing one or more actions based on the cascade performed by the hierarchical storage manager.
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
a video tip module for receiving video tips from one or more external sources, adapted to extract meta-data and attribute data from the video tips and to generate tip events based on the extracted meta-data and attribute data, the attribute data representing the importance of the video tips;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras and the video tips from the video tip module, the hierarchy of data storage devices connected to the surveillance cameras and to the video tip module via a network;
a hierarchical storage manager for managing storage and cascade of the video data and the video tips in the hierarchy of data storage devices based on the attribute data corresponding to a source of the video data and a source of the video tips;
and an alerting engine for generating one or more alerts and performing one or more actions based on the cascade performed by the hierarchical storage manager.
106. A video surveillance, storage, and alerting system, comprising:
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices adapted to process the video data from one or more of the surveillance cameras to detect primitive video events in the video data;
a vehicle information module for retrieving information about a vehicle detected in the video data based on the detected vehicle's license plate, and adapted to generate vehicle events based on the information retrieved about the vehicle;
a correlation engine for correlating one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data and one or more vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
one or more video analytics devices adapted to process the video data from one or more of the surveillance cameras to detect primitive video events in the video data;
a vehicle information module for retrieving information about a vehicle detected in the video data based on the detected vehicle's license plate, and adapted to generate vehicle events based on the information retrieved about the vehicle;
a correlation engine for correlating one or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data and one or more vehicle events from the vehicle information module weighted by the information retrieved about the vehicle; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
107. A video surveillance, storage, and alerting system, comprising:
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras, the hierarchy of data storage devices connected to the surveillance cameras via a network;
a network management module for monitoring network status of the surveillance cameras and the data storage devices, the network management module adapted to generate network events reflective of the network status of the surveillance cameras and the data storage devices;
a correlation engine for correlating two or more network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
one or more surveillance cameras for capturing video data having attribute data, the attribute data representing importance of the surveillance cameras;
a hierarchy of two or more data storage devices for storing the video data from the surveillance cameras, the hierarchy of data storage devices connected to the surveillance cameras via a network;
a network management module for monitoring network status of the surveillance cameras and the data storage devices, the network management module adapted to generate network events reflective of the network status of the surveillance cameras and the data storage devices;
a correlation engine for correlating two or more network events from the network management module weighted by attribute data of device corresponding to the network event; and an alerting engine for generating one or more alerts and performing one or more actions based on the correlation performed by the correlation engine.
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| US11/867,575 | 2007-10-04 |
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| CA2638621A1 true CA2638621A1 (en) | 2008-11-26 |
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| EP (1) | EP2046040B1 (en) |
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| US10862744B2 (en) | 2020-12-08 |
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| US20170207949A1 (en) | 2017-07-20 |
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