AI can process more video simultaneously to look for anomalies
The rapid spread of the use of video analytics in surveillance systems is due to a combination of technological and operational factors that are driving this well-established trend in the security market. The market today offers the possibility of executing complex algorithms with hardware devices of very limited size and price. This favors the evolution and availability of advanced video analysis algorithms based on artificial intelligence (AI). Many operators of physical casinos have opted for this technology to keep their facilities much more secure.
In an environment where the number of cameras has increased exponentially, video recordings generate huge image archives. Human resources are scarce and costly, and process automation is crucial for optimizing security and business operations. In addition, there is a growing appetite for data of all kinds to help improve business intelligence applications and smart city initiatives.
The result is, as is already being experienced in the casino industry, an explosion of interest, supply, and promotion of a multitude of AI-based video analytics. With AI implemented in cameras, you can have better detection of motion, perception of tampering, camera failure or tampering attempts, intrusion detection, and the location of a person running in a certain direction.
AI also provides several other features, such as abandoned objects. This reveals if an object is not part of the normal scenario in the casino and/or has been unattended for a certain period of time. The same goes for the deleted object, as it discovers if objects have been removed from the scene.
This solution is installed in strategic places in the casino such as corridors, cash registers, common areas, pantry, or archive areas. The objective is to be able to observe each area and thus visualize what visitors and customers are doing in your business, verifying the images through the video gateway if appropriate.