The Impact of AI on Smart Cities in the Areas of Road, Transport, Traffic & Security

Statement of the Problem: A smart city is a safe & secure city for all its inhabitants. A vibrant and dynamic city is full of life and activities on its roads, streets & highways. Also, its residents require security in their homes, and workplaces. Applying AI technologies such as machine learning and deep learning on data generated from the city, such as road data, vehicles on the road, road lanes, and with the use of high precision devices such as LiDAR sensor technology and vehicle perception systems can result in powerful capabilities that capture these raw data and transform it  to extremely valuable information and data that cities, road companies, enforcement authorities and municipalities can use to learn details about road conditions, utilization, accidents and events, traffic violations, driver behaviors, and much more. Likewise, in the area of physical security, by applying AI with LiDAR sensors and people perception systems, the system can gather raw data from locations requiring high levels of security such as airports, prisons, international borders, military installations, critical infrastructures, and others leading to applications such as: perimeter protection, exit/entrance monitoring, gate access control, restricted zone enforcement, people counting, precise crowd counting, crowd management and much more. Sensor fusion between LiDAR sensors and cameras can only enhance the outcome and provide critical visual evidence of violations, intrusion, and other alert generating incidents which can also be live streamed as well as video recorded on demand.

 

Author(s): Mohamed Sadek

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