Kelani, Muhammad Arif Khumaini and Abd. Rahman, Faridah and Gunawan, Teddy Surya and Kartiwi, Mira and Harun, Harlisya and Abdul Kadir, Kusyairi (2025) Design and implementation of a low-cost IoT based landslide monitoring and early warning system using ESP32 and Blynk cloud platform. In: 2025 IEEE 11th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA), 10-11 September 2025, KUALA LUMPUR MALAYSIA.
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Abstract
Landslides are among the most devastating natural disasters, often resulting in significant loss of life, infrastructure damage, and environmental degradation. This paper presents the design and development of a low-cost, realtime Internet of Things (IoT)-based landslide monitoring and early warning system, utilizing the ESP32-WROVER-E microcontroller, YL-69 soil moisture sensor, and MPU6050 accelerometer-gyroscope. The system transmits environmental data wirelessly to the Blynk cloud platform, enabling remote monitoring and immediate alert dissemination via a mobile application. Calibration of the soil moisture sensor using piecewise linear regression significantly reduced measurement errors, achieving an accuracy within ±5% of actual volumetric water content. The MPU6050 effectively detected slope inclinations, classifying them into normal, warning, and danger zones with high reliability. Real-time tests under simulated landslide conditions demonstrated the system’s ability to issue timely alerts through push notifications and email, offering scalable deployment in disaster-prone regions. Unlike conventional geotechnical instruments, this system provides portability, energy efficiency, and minimal maintenance requirements. With potential for integration of additional sensors and AI-driven predictive analytics, the proposed solution advances the field of disaster risk reduction. It enhances community resilience through accessible, real-time landslide monitoring technology.
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