Design and Construction of an Internet of Things-Based Landslide Early Detection System in Landslide-Prone Areas - Prasetyo, Sidik; Susanto, Rudi; Pramono, Pramono (Journal of Artificial Intelligence and Software Engineering, 2025)
Landslides are one of the natural disasters that often occur in Indonesia due to the geographical conditions dominated by mountainous and hilly areas, coupled with high rainfall. Landslides can cause huge losses and casualties due to the absence of a system that can provide real-time warnings as a preventive measure. This research aims to design and build an Internet of Things (IoT)-based landslide early detection system that is able to detect environmental conditions that have the potential for landslides in real-time. The system uses an ESP32 microcontroller as the control center connected with a rain sensor (YL-83), a tilt sensor (MPU6050), and a soil moisture sensor (Capacitive Soil Moisture). Data from the sensors is sent via RESTful API and WebSocket with WiFi connection to the monitoring website. The system is also equipped with a buzzer and RGB LED as a warning indicator if environmental conditions are detected that have the potential for landslides. For a power source, a rechargeable 18650 battery is used and combined with a Step-Up and Charger Module J5019 to maintain voltage stability. The test results conducted in the test environment obtained 40 experimental data with stable sensor readings, and all components can function properly and can display data on the monitoring website. This system offers a practical solution to support disaster mitigation in landslide-prone areas.