An IoT-Enabled Early Warning System for Landslides and Acid Rain Through Rainfall and pH Monitoring

• Phu Nguyen Van,
• Phuc Dao Anh,
• Dat Nguyen Tien,
• Minh Nguyen Viet,
• Mai Huong Nguyen Thi,
• Kien Do Trung,
• Thanh Pham Van,

Vol. 19, No. 11, November 30, 2025
10.3837/tiis.2025.11.007, Download Paper (Free):

• IoT-based monitoring
• rainfall measurement
• environmental monitoring
• landslide early warning system
• acid detetion
• tipping bucket rain gauge

Abstract

This study proposes an IoT-based system to monitor rainfall intensity and rainwater pH levels, aiming to address environmental challenges such as landslides and acid rain. The system integrates tipping bucket rain gauges and DFRobot pH sensors with the LILYGO T-SIM7600 G-H ESP32 module to enable real-time data collection, processing, and wireless transmission. By leveraging IoT technologies, the system facilitates automated alerts through SMS, including GPS coordinates, to notify users of critical environmental thresholds. Data visualization and analysis are achieved via the ThingSpeak platform, providing intuitive real-time insights. The system's innovative design combines affordability, scalability, and compactness, making it suitable for diverse applications, especially in resource-constrained regions. Key features include the accurate measurement of rainfall and pH, reliable cloud-based data transmission, and prompt alert mechanisms. Compared to traditional monitoring methods, the proposed solution overcomes limitations such as delayed data availability and high maintenance costs, while also expanding functionality to include pH monitoring. This comprehensive approach enhances early warning capabilities, aiding in proactive disaster risk management and environmental protection. The findings contribute significantly to the field of environmental monitoring, laying the foundation for further advancements in integrated IoT-based solutions for climate resilience.

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