Abstract: Various embodiments described herein relate to predicting potential incident event structures based on multi-model analysis. In this regard, a potential incident event with respect to aggregated data associated with one or more data sources is identified. In response to the potential incident event, one or more potential incident event data structures are identified based at least in part on the aggregated data. Additionally, in response to the potential incident event, one or more actions are performed based at least in part on the one or more potential incident event data structures.

Abstract: A method of performing an integrity check on a plurality of video surveillance cameras includes retrieving a recent video frame from each of the plurality of video surveillance cameras, determining a integrity score for each of the recent video frames and determining which of the integrity scores failed to meet a predetermined criteria. When at least one of the integrity scores fails to meet the predetermined criteria, an integrity check report is created that includes an camera identifier along with the recent video frame for each of the plurality of video surveillance cameras that had a recent video frame with an integrity score that failed to meet the predetermined criteria. The integrity check report is displayed to a user for manual verification.

Abstract: Performance of a video system including a plurality of video cameras each configured to provide a video stream to one or more video recorders and as a monitoring station at which a user can view live and recorded video streams is evaluated. A plurality of live video streams are automatically processed to ascertain one or more live video quality metrics. A plurality of recorded video streams are automatically processed to ascertain one or more recorded video quality metrics. One or more measures of performance of the video system are automatically determined based on the one or more live video quality metrics, the one or more recorded video quality metrics. One or more underperforming components of the video system are identified based at least in part on one or more of the measures of performance of the video system.

Abstract: Various embodiments described herein relate to predicting potential incident event structures based on multi-model analysis. In this regard, a potential incident event with respect to aggregated data associated with one or more data sources is identified. In response to the potential incident event, one or more potential incident event data structures are identified based at least in part on the aggregated data. Additionally, in response to the potential incident event, one or more actions are performed based at least in part on the one or more potential incident event data structures.

Abstract: The present invention relates to a system for identifying identify of interest data structures based on a trained identity of interest model and using individual-incident data structures integrating individual identification data received from third party resources based on an incident data structure.

Abstract: A method of performing an integrity check on a plurality of video surveillance cameras includes retrieving a recent video frame from each of the plurality of video surveillance cameras, determining a integrity score for each of the recent video frames and determining which of the integrity scores failed to meet a predetermined criteria. When at least one of the integrity scores fails to meet the predetermined criteria, an integrity check report is created that includes an camera identifier along with the recent video frame for each of the plurality of video surveillance cameras that had a recent video frame with an integrity score that failed to meet the predetermined criteria. The integrity check report is displayed to a user for manual verification.