Abstract
The use of artificial intelligence and the transfer to smart cities assist in improving the mobility inside them by enhancing the traffic flow and decreasing the number of traffic accident deaths. There have been many studies to handle traffic management in urban cities by modifying the main dimensions for smart cities in mobility management and benefiting from artificial intelligence in intelligent decision-making. The use of network to build infrastructure for smart city is a major factor in successful smart city. This will enable running variety of application the use of unlimited space and data analysis using cloud edge computing. Vehicles become smart to run smartly in smart city. However, the safety of driver is the main concern and remote monitoring of driver and vehicles is the only way to have smart city without accidents. In this research, we propose a framework that analyze traffic data on time to reduce the number of accidents and safe people lives. The framework makes use of IoT devices and artificial intelligence diagnose the driver, car performance and road condition. The simulation shows that the proposed framework is great help in saving driver’s life by monitoring it remotely, great help in watching car performance to reduce cost and prevent damage to the car. In addition to that, it can be used by driver to check road status and by government to control traffic.
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Tarawneh, M., AlZyoud, F., Sharrab, Y. (2023). Artificial Intelligence Traffic Analysis Framework for Smart Cities. In: Arai, K. (eds) Intelligent Computing. SAI 2023. Lecture Notes in Networks and Systems, vol 711. Springer, Cham. https://doi.org/10.1007/978-3-031-37717-4_45
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DOI: https://doi.org/10.1007/978-3-031-37717-4_45
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