Optimized traffic control and data processing using IoT

Abstract

The development of the Internet of Things facilitates various dimensionalities in a home, industrial and business applications. The integration of sensors and smart objects with accessible infrastructure makes the efficient data processing and decreases the human resource, operating time. The novel smart traffic control framework is proposed using local traffic smart server and remote cloud server to improve the traffic signal processing time that reduces the vehicles’ waiting time, congestion and pollution at the roadway intersection. This approach is also capturing the vehicle’s transition that is used to track high-speed vehicles. Optimized regression algorithm is proposed to collect multi-path data and compute single-point nifty decision using waiting vehicle density at four-direction roadway intersection. The sensor data is processed using regression algorithm and take the decision to change the lamp onset. The case study implementation has been demonstrated for four-direction roadway by considering the existing infrastructure with Arduino Uno kit and evaluated the smart traffic framework by comparing with normal traffic system. The results prove that proposed framework smooth the progress of hassle-free travel by reducing the waiting time for the green lamp onset, and also can be use the recorded vehicles images to track the high-speed vehicles.