Virtually every city around the world today has deployed video surveillance cameras to assist with a wide range of daily operations including law enforcement, and traffic monitoring, as well as municipal resources and services management to enhance smart city safety and security. By their inherent nature, video cameras effectively increase situational awareness by putting more “eyes” on the street so city managers and first responders can see more of what is going on in their community.
In many large cities, hundreds if not thousands of cameras have been deployed, generating voluminous amounts of data and imagery – all of which needs to be effectively monitored and stored. This places a tremendous strain on manpower resources since large numbers of video cameras require large numbers of personnel to effectively monitor live events, interpret situations, and initiate appropriate action to ensure smart city safety and security. Not only does this drive-up operating cost by increasing the need for trained system operators, the physical monitoring process can be impacted by commonplace factors such as screen fatigue and everyday behaviors such as getting coffee or using the restroom.
viisights’ smart city behavioral recognition video understanding technology resolves these issues by employing advanced Artificial Intelligence and deep learning algorithms. Through contextual understanding, these algorithms transform conventional video surveillance into sources of proactive actionable intelligence. An infinitely scalable behavioral recognition video understanding technology that works with any number of cameras, viisights smart city video analytics provide a highly pragmatic, efficient, and cost-effective solution.
