Current - Issue

Poor Road conditions caused by potholes and speed bumps are among the major factors responsible for vehicle damage, traffic congestion, passenger discomfort, and road accidents in modern transportation systems. Traditional methods for monitoring and inspecting roads depend mostly on human monitoring and crowd reporting, making them time consuming, laborious, and inefficient methods for timely road analysis. This paper describes a Smart Pothole Detection and Vehicle Control System, combining computer vision, image processing, embedded systems, and intelligent vehicles for road anomaly detection and monitoring. In the proposed model, a 1080p HD camera, as well as OpenCV image processing, have been used for continuous road surface analysis and detecting potholes or uneven roads. A Raspberry Pi Pico W microcontroller is used as the control center, supporting detection, monitoring, and adaptive vehicle response operations based on detected road conditions. The developed smart system provides GPS alerts, Telegram notifications, and real-time dashboards as additional options for more convenient monitoring. This study offers an effective solution to intelligent transportation systems as well as applications in smart road monitoring and autonomous vehicles in the future.