An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution

Finding the shortest and cleanest path in cities is vital, especially metropolises. Although several algorithms some software have been introduced to manage traffic or suggest a with minimum congestion, none considers air quality deciding factor. This paper introduces novel algorithm find based on congestion quality. In proposed algorithm, city map fetched from Google Map app converted into weighted graph. Traffic data collected GPS devices, which will be available through local cloud services. The C-means clustering method used cluster congestion. Also, information pollution monitoring stations. graph weights are calculated both factors, simultaneously. problem then defined as an optimization problem, linear programming solve it. Finally, algorithm’s performance evaluated by finding Tehran, Iran different scenarios.