Vision-Based Smart Pothole Detection and Alert System using ESP32

Road damage and potholes are one of the major causes of vehicle accidents and traffic disruptions. Traditional pothole detection methods rely on manual inspection, which is inefficient and time-consuming. This project proposes a Smart Pothole Detection and Alert System using ESP32 that utilizes computer vision and sensor-based detection to identify potholes and automatically control vehicle speed. In the proposed system, a web camera connected to a laptop captures road images periodically. The captured images are compared with a predefined reference image using Python-based image processing techniques. If the similarity between images falls below a threshold, the system identifies the presence of a pothole or road anomaly. The detection result is then transmitted to an ESP32 microcontroller through wireless communication. Once the ESP32 receives the signal, it activates the ultrasonic sensor (HC-SR04) to measure the depth of the pothole. Based on the measured depth, the motor speed is automatically reduced using the L293D motor driver controlling BO motors. This helps simulate a smart vehicle system that slows down when a pothole is detected. The proposed system demonstrates how computer vision, IoT, and embedded systems can be integrated to create an intelligent road safety solution.