Design and Development of an IoT-Based Ground Vibration Monitoring System with Landslide Potential Classification Using SVMDesign and Development of an IoT-Based Ground Vibration Monitoring System with Landslide Potential Classification Using SVM - Pratama, Ridho; Tanjung, Mahardika Abdi Prawira (Marqcha Institute, 2026)
Landslides are natural disasters that can cause casualties, environmental damage, and infrastructure losses. One challenge in landslide mitigation is the limited availability of monitoring systems that can provide fast, real-time, and interpretable information about ground conditions. This study aims to design and develop an Internet of Things (IoT)-based ground vibration monitoring system with landslide potential classification using Support Vector Machine (SVM). The system uses an MPU6050 sensor to acquire ground vibration data and an ESP8266 microcontroller to transmit data through a Wi-Fi network to a server. The collected data are processed through preprocessing, windowing, feature extraction, and standardization before being classified into three condition categories: Safe, Alert, and Danger. The classification results are displayed on an LCD, visualized through a web dashboard, and used to activate a relay as a warning mechanism when a dangerous condition is detected. The testing results show reliable data transmission with a 100% delivery success rate in the observed test and an average latency of approximately 0.3 seconds. The SVM model achieved 99.79% accuracy, with high precision, recall, and F1-score for all classes. Therefore, the proposed prototype can support ground vibration monitoring and early landslide warning efforts more effectively.