Abstract: Landslides pose significant threats to lives, infrastructure, and the environment. Detecting and monitoring landslides in real-time is crucial for early warning and mitigation efforts. In recent years, advancements in Internet of Things (IoT) technology have paved the way for innovative solutions in disaster management. This project proposes an IoT-based Landslide Detection and Monitoring System designed to provide timely alerts and comprehensive data for effective response and risk reduction. The system integrates various sensors such as accelerometers, inclinometers, and moisture sensors deployed in landslide-prone areas to continuously monitor ground movement, slope stability, and soil conditions. These sensors are connected to a central IoT gateway, which collects, processes, and analyzes the data in real-time. Machine learning algorithms are employed to detect patterns indicative of potential landslide events, enhancing the system's predictive capabilities.
Keywords: IoT (Internet of Things), Landslide Detection, Landslide Monitoring, Real-time Data, Cloud-based Platform, Early Warning System,Risk Assessment, Emergency Response, Alert.
Cite:
Vishakha Sadare, Tanjila Nadaf, Shalani Kumari, Prof. P. P. Belgali,"IOT BASED LANDSLIDING DETECTION AND MONITORING", IJIREEICE International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 12, no. 3, 2024, Crossref https://doi.org/10.17148//IJIREEICE.2024.12314.
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