Machine learning Smart Traffic Prediction and Congestion Reduction

Abstract

Smart traffic congestion reduction is useful for reducing the traffic in a highly congested area. To prevent heavy traffic Internet of things is implemented through a small device called a sensor, this technology is called smart traffic. A small device is placed near the roadside street post to detect the vehicle count. Smart traffic works by collecting the various signals like WiFi, Bluetooth, ZigBee from various electronic gadgets like a smartphone, smartwatch, smart band, tablet. The MAC address from each vehicle is collected as input information and stored in a cloud platform. Analyze and calculate the collected data set and performed it under machine learning prediction algorithms to get a better accuracy result to avoid traffic congestion. The logistic regression algorithm gives a 91% of accuracy level in traffic. It gives the shortest route to reach the destination without any hurdles. Results are reduced the traveling time, noise pollution, carbon dioxide emission, reach the destination on correct time and also save the fuel.