Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Variants of the privacy-aware event detection method can include: determining measurements of a monitored space, determining values for a set of primitives from the measurements, optionally sending the primitive values to a remote event detection system, detecting an event based on the primitive values, optionally analyzing the event, and optionally notifying a user of a security threat.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: In variants, the method for data analysis can include: determining a measurement set, optionally identifying measurements of interest, selecting measurements to composite, generating composite measurements, analyzing a batch of measurements, and optionally training a policy model.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Systems and methods for implementing a threat model that classifies contextual events as threats.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: A surveillance system is coupled to a plurality of sensor data sources arranged at locations within a plurality of regions of a site under surveillance. The surveillance system accesses a threat model that identifies contextual events classified as threats. The surveillance system identifies at least one contextual event for a site in real-time by processing sensor data generated by the sensor data sources, and co-occurring contextual data for at least one of the regions. Each identified contextual event is classified as one of a threat and a non-threat by using the threat model.

Abstract: Systems and methods for augmenting real-time semantic information to a spatial rendering of a predefined space and providing a real-time situational awareness feed.

Abstract: Systems and methods for augmenting real-time semantic information to a spatial rendering of a predefined space and providing a real-time situational awareness feed.

Abstract: Systems and methods for implementing a threat model that classifies contextual events as threats.

Abstract: Systems and methods for correlating access-system primitives generated by an access control system and semantic primitives generated by a sensor data comprehension system.

Abstract: Systems and methods for augmenting real-time semantic information to a spatial rendering of a predefined space and providing a real-time situational awareness feed.

Abstract: A system and method for implementing a machine learning-based system for generating event intelligence from video image data that: collects input of the live video image data; detects coarse features within the live video image data; constructs a coarse feature mapping comprising a mapping of the one or more coarse features; receives input of the coarse feature mapping at each of a plurality of distinct sub-models; identify objects within the live video image data based on the coarse feature mapping; identify one or more activities associated with the objects within the live video image data; identify one or more interactions between at least two of the objects within the live video image data based at least on the one or more activities; composes natural language descriptions based on the one or more activities associated with the objects and the one or more interactions between the objects; and constructs an intelligence augmented live video image data.

Abstract: Systems and methods for augmenting real-time semantic information to a spatial rendering of a predefined space and providing a real-time situational awareness feed.

Abstract: A system and method for implementing a machine learning-based system for generating event intelligence from video image data that: collects input of the live video image data; detects coarse features within the live video image data; constructs a coarse feature mapping comprising a mapping of the one or more coarse features; receives input of the coarse feature mapping at each of a plurality of distinct sub-models; identify objects within the live video image data based on the coarse feature mapping; identify one or more activities associated with the objects within the live video image data; identify one or more interactions between at least two of the objects within the live video image data based at least on the one or more activities; composes natural language descriptions based on the one or more activities associated with the objects and the one or more interactions between the objects; and constructs an intelligence augmented live video image data.