Systems and methods for correlating sensory events and legacy system events utilizing a correlation engine for security, safety, and business productivity
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G08B-021/00
H04L-012/24
H04W-004/00
H04L-029/08
H04W-004/70
H04L-029/06
H04L-012/26
출원번호
US-0481675
(2017-04-07)
등록번호
US-10020987
(2018-07-10)
발명자
/ 주소
Donovan, John J
Hussain, Daniar
출원인 / 주소
SecureNet Solutions Group LLC
대리인 / 주소
American Patent Agency PC
인용정보
피인용 횟수 :
0인용 특허 :
113
초록▼
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 eng
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.
대표청구항▼
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 sens
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;receiving legacy system data from one or more legacy systems;processing the sensory data from the one or more sensors to detect one or more primitive sensory events;processing the legacy system data from the one or more legacy systems to detect one or more primitive legacy events;normalizing the primitive sensory events and the primitive legacy events into a standardized data format to generate normalized sensory events and normalized legacy events;storing the normalized sensory events and the normalized legacy events in an event database for later retrieval as stored sensory events and stored legacy events;retrieving one or more stored sensory events and one or more stored legacy events from the event database;evaluating one or more historical correlations by automatically analyzing said stored sensory events and said stored legacy events, across at least one of time and space, for one or more historical correlations among the stored sensory events and the stored legacy events, wherein the historical correlations are calculated by applying a weighting of relative importance of the stored sensory events based on a quality of the sensory data;monitoring continuously and in real-time the primitive sensory events from the one or more sensors and the primitive legacy events from the one or more legacy systems 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; andsending 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 legacy system data based on a quality of data produced by the legacy systems. 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; andgenerating 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; andgenerating 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;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;receiving legacy system data from one or more legacy systems;processing the sensory data from the one or more sensors to detect one or more primitive sensory events;processing the legacy system data from the one or more legacy systems to detect one or more primitive legacy events;normalizing the primitive sensory events and the primitive legacy events into a standardized data format to generate normalized sensory events and normalized legacy events;storing the normalized sensory events and the normalized legacy events in an event database for later retrieval as stored sensory events and stored legacy events;retrieving one or more stored sensory events and one or more stored legacy events from the event database;evaluating one or more historical correlations by automatically analyzing said stored sensory events and said stored legacy events, across at least one of time and space, for one or more historical correlations among the stored sensory events and the stored legacy events, wherein the historical correlations are calculated by applying a weighting of relative importance of the stored sensory events based on a quality of sensory data;monitoring continuously and in real-time the primitive sensory events from the one or more sensors and the primitive legacy events from the one or more legacy systems 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; andsending one or more alerts based on at least one of said critical events and said network failure events. 20. A monitoring method, comprising steps of: 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;receiving legacy system data from one or more legacy systems;processing the sensory data from the one or more sensors to detect one or more primitive sensory events;processing the legacy system data from the one or more legacy systems to detect one or more primitive legacy events;normalizing the primitive sensory events and the primitive legacy events into a standardized data format to generate normalized sensory events and normalized legacy events;storing the normalized sensory events and the normalized legacy events in an event database for later retrieval as stored sensory events and stored legacy events;retrieving one or more stored sensory events and one or more stored legacy events from the event database;evaluating one or more historical correlations by automatically analyzing said stored sensory events and said stored legacy events, across at least one of time and space, for one or more historical correlations among the stored sensory events and the stored legacy events, wherein the stored sensory events are weighted based at least on one or more attribute data of the one or more sensors used to capture the stored sensory events;monitoring continuously and in real-time the primitive sensory events from the one or more sensors and the primitive legacy events from the one or more legacy systems 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; andsending one or more alerts based on at least one of said critical events and said network failure events.
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