Natural disasters like landslides pose significant socio-economic threats to areas whose geography favors them. This necessitates efforts to measure and monitor potential landslides are essential to ensure human safety and to protect civil infrastructure. Currently existing landslide monitoring methods and techniques are characterized by significant limitations both in technical viability (quality and frequency of data) and in terms of usability (high inferred costs, requirement of very high expertise).
In this work we present an innovative landslide monitoring system that leverages state-of-the-art IoT technologies to issue a real-time landslide warning prior to an impending landslide, facilitating evacuation and better disaster management. The system consists of a set of autonomous sensing devices equipped with a sensor suit specifically tailored for monitoring landslides. The devices take sensory measurements at frequent intervals - while operating at a very low duty cycle - and transmit them over a tree network to a data server for curation and visualization. The system follows a modular scalable architecture for ease of replication, assembly and maintenance.
This project describes the design of a prototype multimodal sensing mechanism entailing a soil water content sensor, an inertia measurement unit and a centralized gateway with a built-in algorithm capable of assessing landslide risk and generate early warnings via electronic communication as the final deliverable.
Project Details
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Project Requirements
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