Integrated Road Safety System for Real-Time Waterlogging Detection and Traffic Management Using Google Maps API

Potholes, waterlogging, and possible electrical hazards have a significant impact on urban traffic safety, especially during the monsoon season. Road damage, traffic jams, car accidents, and even potentially fatal electrical leaks from damaged power lines in flooded areas are all consequences of these situations. A thorough machine learning-based method for detecting potholes in real time, determining the extent of waterlogging, and identifying electrical leaks in water is presented in this study. The device measures the risk of water accumulation, estimates pothole depth, and records road conditions using computer vision algorithms. It also finds electrical leaks in water and sends out timely alerts to reduce the risk of electrocution. Using the Google Maps API, the system automatically reroutes traffic to safer routes, reducing the amount of time that cars and pedestrians are exposed to dangerous situations. Our system provides a strong, scalable foundation for enhancing road safety and urban mobility during inclement weather by combining pothole recognition, waterlogging severity assessment, and electrical danger detection.