Enhancing the Electrified Transportation System with the IOT Tools Placed Around a City

Abstract

Electric vehicles and smart city concepts based on IoT tools seem to be high-technology solutions that impact the transportation system, road safety, and road management sectors. In a big city where the number of vehicles is high, and the city roads are close and overlapped, road safety and vehicle management seem difficult. This is why one of the major solutions needs to use high-technology sensors based on IoT equipment and technology. In this context, this paper is exposed in order to use the benefit of the smart city, based on the IoT technology for enhancing the electric vehicle energy consumption mode, and this is by controlling the vehicle trajectory from two points in a road. The principle of the proposed work is based on the neural network concept, which uses a large database of information for making learning in order to find the optimum trajectory from various similar cars that have used the same trajectory for moving from position A to position B. The simulation was made on Matlab Simulink platform and the results were then exposed and discussed.

Keywords

• buildings
• neural network
• optimization
• power management
• storage system efficiency
• transportation sector, vehicle to sensors