Landslides are one of the major natural disasters affecting hilly and rain-prone regions, causing severe loss of life and infrastructure damage. This paper presents an IoT-based landslide early detection and prediction system using soil moisture, rain, and vibration sensors integrated with an ESP32 microcontroller. The proposed system continuously monitors environmental and geological conditions in real time and performs risk factor analysis to classify danger levels from low risk to immediate danger. Real-time data is transmitted to cloud platforms such as Thing Speak and Blynk for remote monitoring and automated alert generation. The system provides local alarms and mobile notifications for timely evacuation and disaster management. The proposed framework is low-cost, scalable, energy-efficient, and suitable for deployment in remote areas.
R.Annapoorani et al. (Thu,) studied this question.