INTELLIGENT ROAD ANOMALY DETECTION AND AUTOMATED REPORTING SYSTEM USING IOT AND CLOUD COMPUTING

Abstract

Deteriorating road infrastructure, particularly potholes, surface cracks, uneven pavements, and road depressions, poses severe risks to vehicular safety and contributes significantly to traffic accidents, vehicle damage, and increased maintenance costs globally. This project presents an Intelligent Road Anomaly Detection and Automated Reporting System that integrates IoT and cloud computing to enable real-time detection, precise geo-tagging, and automated multi-channel reporting of road surface anomalies. The system employs an ESP-32 microcontroller as the central processing unit, interfaced with a MEMS accelerometer for vibration-based anomaly detection, an ultrasonic sensor for road surface depth and obstacle measurement, a GPS module for precise location tagging of detected anomalies, and a keypad for user input and zone configuration. Upon detecting a road anomaly, the system simultaneously activates an LCD display for visual data presentation, a buzzer for audible alerts, a GSM module for automated SMS reporting to municipal authorities, an IoT cloud platform for real-time dashboard visualization and historical data logging, and a robotic actuator for physical anomaly marking. Battery-powered operation ensures field deployability across all road environments without dependency on external power infrastructure. Keywords: Road Anomaly Detection, Pothole Detection, IoT, ESP-32, MEMS Accelerometer, Ultrasonic Sensor, GPS, GSM, Cloud Computing, Automated Reporting, Road Safety, Smart Infrastructure, LCD, Buzzer, Robotic Actuator