Congestion-Aware Traffic Management System using Inductive Loop Sensor

Increased urbanization has brought enormous traffic congestion that causes delays, fuel loss, and environmental pollution. Conventional traffic management systems of the Internet of Things (IoT) use static timers for signals, which are incapable of adjusting according to changing traffic conditions. The paper proposes a congestion level-based dynamic traffic management system for smoothing traffic flow and alleviating congestion. The system uses an inductive loop sensor to measure vehicle density and classifies traffic conditions as low, medium, high levels and can also be observed through the serial monitor of the mobile app anywhere at any time of any given traffic signal using the IP address using the ESP wi-fi controller. The system dynamically changes signal timings based on real-time data to give high-density lanes priority, thus decreasing bottlenecks. In addition, traffic updates are shown on the LCD screen mounted on the I2C module and sent through a Wi-Fi module, giving drivers a mobile app to choose alternative routes usually mitigating frustration for the drivers. Through this modern strategy, efficiency in traffic increases, environmental effects decrease, and smarter urban mobility solutions are provided.