Real-Time Threshold-based Landslide Prediction System for Hilly Region using Wireless Sensor Networks

In this paper, we propose a real-time monitoring system for prediction of landslide caused by rainfall using wireless sensor networks (WSNs). In the proposed work, multiple wireless sensors together periodically monitor the environmental condition and collect related information, then transfer it to a hub. The hub then measures a landslide index based on the collected information and sends an alarm for a possible landslide to a remote cloud server in case the landslide index exceeds a predefined threshold for early landslide prevention.

[1]  Jiang Tingyao,et al.  A landslide stability calculation method based on Bayesian network , 2013, 2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA).

[2]  Richard A. Regueiro,et al.  Instability of partially saturated soil slopes due to alteration of rainfall pattern , 2012 .

[3]  T. Kavzoglu,et al.  Selecting optimal conditioning factors in shallow translational landslide susceptibility mapping using genetic algorithm , 2015 .

[4]  C. Venkatesh,et al.  Daily rainfall forecasting using artificial neural networks for early warning of landslides , 2014, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI).