Curve Monitoring and Alert System for Smart Transportation

The proposed IoT-based Smart Curve Monitoring and Alert System is designed to improve road safety through the fusion of embedded systems, machine learning and edge computing technologies. The proposed system is primarily powered by ESP32 microcontroller, continuously gathers data from an array of sensors, including accelerometers, gyroscopes and a potentiometer to set the speed limit. This collected data is then subjected to analysis by a Convolutional Neural Network (CNN) model, which has been trained to recognize driving patterns, especially when navigating curves. Here, CNN classifies the vehicle’s behavior as safe and risky, and if a risky behavior is identified, it triggers an alert and dispatches relevant data to a NodeMCU device. The NodeMCU plays a crucial role in the system by monitoring the communication tasks. It receives the alert from the ESP32, validates the vehicle’s speed against the preset limit, and, if necessary, activates a GSM module to send an immediate notification to designated guardian. To ensure real-time monitoring and awareness, all pertinent information will be displayed on the LCD screen, including the vehicle’s behavior classification, current speed, speed limit and alert status. By addressing reckless driving behaviors, particularly on curves, the system contributes significantly to safer roads and reinforces the importance of responsible driving practices.