iAware Enterprise applies our behavior predictive algorithm to develop malicious intent awareness via concurrent video analytics of multi-location corporate environments, providing real-time capabilities to identify activities that may develop into active threats.
The advanced capabilities of our AI driven system allow iAware Enterprise to analyze consolidated video analytics from multiple campuses across an enterprise in a single security center, reducing the number of monitoring personnel required by eliminating the need for continuous human monitoring.
iAware Enterprise evaluates all video streams concurrently to identify and respond to gun detection, knife detection, dispute detection, panic detection, anomaly detection (identifying abnormal behavior which might otherwise go unnoticed, such as wrong direction detection for vehicles and actors), specific movement detection (such as line crossing, loitering, person running, etc), unattended object detection and a host of other potential threats.
Automatic license plate recognition provides real-time recognition of license plates from surveillance video with ease, and delivers an alert the instant a targeted plate is identified attempting to enter any corporate property.
For non-targeted plates, a simple search allows security personnel to review suspicious activity and receive a comprehensive report of vehicle activity that includes every time that vehicle drove past any camera in the corporate camera network. Facial recognition provides positive identification of on-site actors from a database of authorized individuals entered into the system (both employees and visitors). The system identifies the image, description and location of any non-registered or watch-listed persons who have entered the zone of awareness and immediately alerts corporate security or law enforcement.
The system’s AI-driven deep learning algorithms are continuously evaluating and categorizing video data, adding recognition criteria to identify behaviors or events that do not match the typical profile of activity for a specific area. This augments any rules-driven responses with a continuously improving data set of evaluation criteria. This approach makes the entire enterprise a zone of awareness, enhancing the safety and security of everyone, wherever they may be across the enterprise facilities.
