An IOT and Machine Learning-Enabled Integrated Intelligent Monitoring and Alert System for Landslide Detection, Conflict Avoidance, Vehicle Prioritization, and Heavy Rainfall Management in Ghat Road Sections

Landslides and vehicular conflicts in ghat road sections pose significant risks to human life and infrastructure, exacerbated by heavy rainfall and poor visibility. This paper presents an innovative IoT and machine learning-enabled system for real-time landslide detection, conflict avoidance, vehicle prioritization, and heavy rainfall management. The system integrates sensors (ADXL345 accelerometer, rain sensor, IR sensors), actuators (DC motor gates, traffic lights), and communication modules (HC-12 RF, Telegram alerts) with a machine learning model for vehicle classification. The prototype successfully detects landslides and rainfall, automates road closures, prioritizes heavy vehicles, and mitigates conflicts at sharp bends, achieving over 90% accuracy in vehicle classification and sub-second alert transmission. The system’s fail-safe design and scalability make it a viable solution for enhancing road safety in hilly regions, with potential for solar-powered operation and mobile app integration in future iterations.