Because no two cities are alike, iAware™ City applies our behavior predictive algorithm to develop malicious intent awareness via video analytics in a manner that will address the specific needs of a city. 

Highly-scalable, iAware™ City can be adapted to municipalities of any size, from smaller communities of 100,000 residents to metropolitan cities of multiple millions.

Our patented situational understanding and intent-based analysis systems actually perform better with larger amounts of data. This translates into a remarkably-enhanced ability to identify security and safety issues from across the entire surveillance camera infrastructure, delivering real-time information that isn’t limited only to incidents, but one that is able to reliably identify malicious intent activities that may develop into active threats by means of an on-going evaluation of vehicles, traffic flow, activities, actors and objects. 

This full-scale data analysis allows iAware™ City to turn the entire municipality into a zone of awareness, even in expansive and demanding urban surroundings.

Malicious intent awareness can allow law enforcement to respond to a developing situation well before an “incident” might have been observed by other video analytic systems, both increasing the possibility of preventing a crime and intrinsically reducing the first-officers-on-site response time should an incident occur prior to their arrival. 

iAware™ City allows instant review of incident video in order to determine additional information that could be relevant to the initial investigation, such as license plate information for a vehicle that fled the scene. In such an instance, iAware™ City can utilize our ALPR technology to determine whether or not that vehicle is still in the zone of awareness and is able to direct officers to its current location, as necessary.

While improving safety by delivering greater situational awareness across the entire protected community, iAware™ City is constantly evaluating all video streams for 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 (including vehicles that have been left in unauthorized places or bags that have been left unattended) and a host of other potential threats.