SYSTEMS AND METHODS UTILIZING A CORRELATION ENGINE FOR SECURITY, SAFETY, AND BUSINESS PRODUCTIVITY

• US 20160240055A1
• Filed: 04/05/2016
• Published: 08/18/2016
• Est. Priority Date: 10/04/2007
• Status: Active Grant

• Current Assignee: SecureNet Solutions Group, LLC
• Original Assignee: SecureNet Solutions Group, LLC
• Inventors: Donovan, John J, Hussain, Daniar
• Granted Patent: US 9,619,984 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/0605 by facilitating the interaction with a user or administrator
• CPC Class Codes: G06F 3/0649 Lifecycle management
• CPC Class Codes: G06F 3/0685 Hybrid storage combining heterogeneous device types, e.g. hierarchical storage, hybrid arrays
• CPC Class Codes: G08B 13/19645 Multiple cameras, each having view on one of a plurality of scenes, e.g. multiple cameras for multi-room surveillance or for tracking an object by view hand-over
• CPC Class Codes: G08B 13/19656 Network used to communicate with a camera, e.g. WAN, LAN, Internet
• CPC Class Codes: G08B 13/19671 Addition of non-video data, i.e. metadata, to video stream
• CPC Class Codes: G08B 13/19693 using multiple video sources viewed on a single or compound screen
• CPC Class Codes: G08B 13/19697 Arrangements wherein non-video detectors generate an alarm themselves
• CPC Class Codes: H04L 41/0631 using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
• CPC Class Codes: H04L 41/0654 using network fault recovery ring fault isolation or reconfiguration in loop networks without recovery actions by a network management system H04L12/437
• 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: H04N 23/661 Transmitting camera control signals through networks, e.g. control via the Internet
• CPC Class Codes: H04N 23/80 Camera processing pipelines; Components thereof
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/183 for receiving images from a single remote source

Abstract

Monitoring systems and methods for use in security, safety, and business process applications utilizing a correlation engine are disclosed. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by a correlation engine, optionally by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest, or one or more critical events of interest. Finally, one or more actions are triggered based on a detection of one or more correlations of interest, one or more anomalous events, or one or more critical events of interest. Events may come from sensory devices, legacy systems, third-party systems, anonymous tips, and other data sources. The present invention may be used to increase business productivity by improving security, safety, and increasing profitability of business processes.

Claims

1. A monitoring system comprising a non-transitory, physical storage medium storing computer-readable program code, the program code executable by a hardware processor, the program code when executed by the hardware processor causing the hardware processor to execute steps comprising:

receiving sensory data about a physical environment from one or more sensors;

receiving IP data of the one or more sensors, wherein the IP data comprises at least an Internet Protocol (IP) address and a network status of at least one of the sensors;

processing the sensory data from the one or more sensors to detect one or more primitive sensory events;

normalizing the primitive sensory events into a standardized data format;

storing the normalized sensory events in an event database for later retrieval;

retrieving one or more historical normalized sensory events from the event database;

evaluating one or more historical correlations by automatically analyzing said primitive sensory events, across at least one of time and space, for one or more historical correlations among the historical normalized sensory events;

monitoring continuously and in real-time the primitive sensory events from the one or more sensors based on the one or more historical correlations to identify one or more critical events;

monitoring continuously and in real-time the network status of one or more of the sensors based on the IP data to identify one or more network failure events; and

sending one or more alerts based on at least one of said critical events and said network failure events.

2. The monitoring system of claim 1, wherein the historical correlations are calculated by applying a weighting of relative importance of the sensory data based on a quality of data produced by the sensors, wherein the primitive sensory events are weighted based at least on the quality of data produced by the sensors used to capture the sensory data.

3. The monitoring system of claim 1, wherein the critical events are determined from one or more safety procedures, and wherein the one or more alerts are sent when one or more of the safety procedures are violated.

4. The monitoring system of claim 1, wherein the one or more sensors are selected from the group consisting of a temperature probe, a pressure probe, an altitude meter, a speedometer, a revolutions per minute (RPM) meter, a blood pressure meter, a heart rate meter, a chlorine meter, a radon meter, a dust particle meter, a pollution meter, a CO₂ meter, a bacteria meter, a water meter, an electrical meter, and combinations thereof.

5. The monitoring system of claim 1, wherein the one or more legacy systems are selected from the group consisting of an access control system, a personnel system, an inventory system, a financial system, a police dispatch system, a currency system, a law enforcement database, a light control system, and combinations thereof.

6. The monitoring system of claim 1, wherein the one or more legacy systems comprise at least a personnel system, and wherein the storage medium further comprises program code, which when executed causes the hardware processor to execute steps comprising:

retrieving experience levels of personnel from the personnel system;

correlating the experience levels of personnel with the primitive sensory events; and

generating one or more alerts based on the correlation between the experience levels of personnel and the primitive sensory events.

7. The monitoring system of claim 1, wherein the storage medium further comprises program code, which when executed causes the hardware processor to execute steps comprising:

performing one or more actions based on a correlation level exceeding a predetermined threshold.

8. The monitoring system of claim 1, wherein the storage medium further comprises program code, which when executed causes the hardware processor to execute steps comprising:

generating one or more new rules based on primitive events correlated and alerts generated.

9. The monitoring system of claim 1, wherein the storage medium further comprises program code, which when executed causes the hardware processor to execute steps comprising:

receiving tip data from one or more external sources;

generating tip events based on the tip data;

correlating one or more tip events with the primitive sensory events; and

generating one or more alerts based on the correlation between the tip events and the primitive sensory events.

10. The monitoring system of claim 1, wherein the primitive sensory events are weighted based at least on one or more attribute data of the one or more sensors used to capture the sensory data.

11. The monitoring system of claim 10, wherein the attribute data comprises a quality of sensory data produced by the sensors.

12. The monitoring system of claim 10, wherein the attribute data comprises an age of the sensors used to capture the sensory data.

13. The monitoring system of claim 10, wherein the attribute data comprises a time since the sensors were last maintained.

14. The monitoring system of claim 10, wherein the attribute data comprises an integrity of the sensors used to capture the sensory data.

15. The monitoring system of claim 10, wherein the attribute data comprises a reliability of the sensors used to capture the sensory data.

16. The monitoring system of claim 10, wherein the attribute data comprises a reliability of power that is powering the sensors.

17. The monitoring system of claim 10, wherein the attribute data comprises a reliability of a transmission and a bandwidth of a communication link to the sensors.

18. The monitoring system of claim 1, wherein the storage medium further comprises program code, which when executed causes the hardware processor to execute steps comprising:

providing a graphical user interface (GUI) for a human operator to receive the one or more alerts.

19. A non-transitory, physical storage medium storing computer-readable program code, the program code executable by a hardware processor, the program code when executed by the hardware processor causing the hardware processor to execute steps comprising:

receiving sensory data about a physical environment from one or more sensors;

processing the sensory data from the one or more sensors to detect a plurality of primitive sensory events;

normalizing data corresponding to the plurality of primitive sensory events into a standardized data format;

storing the normalized data corresponding to the plurality of primitive sensory events in a memory;

retrieving the normalized data corresponding to the plurality of primitive sensory events from the memory;

automatically analyzing said normalized data corresponding to the plurality of primitive sensory events, across at least one selected from the group consisting of time and space, to identify at least one temporal or spatial correlation among the plurality of primitive sensory events;

monitoring continuously and in real-time one or more primitive sensory events from the one or more sensors to identify one or more critical events based on the at least one temporal or spatial correlation; and

sending one or more alerts based on said one or more critical events to one or more recipients.

20. A monitoring method, comprising steps of:

receiving sensory data about a physical environment from one or more sensors;

processing the sensory data from the one or more sensors to detect a plurality of primitive sensory events;

normalizing data corresponding to the plurality of primitive sensory events into a standardized data format;

storing the normalized data corresponding to the plurality of primitive sensory events in a memory;

retrieving the normalized data corresponding to the plurality of primitive sensory events from the memory;

automatically analyzing said normalized data corresponding to the plurality of primitive sensory events, across at least one selected from the group consisting of time and space, to identify at least one temporal or spatial correlation among the plurality of primitive sensory events;

monitoring continuously and in real-time one or more primitive sensory events from the one or more sensors to identify one or more critical events based on the at least one temporal or spatial correlation; and

sending one or more alerts based on said one or more critical events to one or more recipients.