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

摘要

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.

主权项

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.