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Landslide is one of the most severe natural disasters whose forecasting is of prime importance to mitigate its after-effects. Here we propose a wireless sensor network (WSN) architecture to predict the landslide for the hilly terrains. We intend to combine the technology of WSN and IoT to be able to pre-warn the local inhabitants of the coming disaster. The functional scheme will look forward to deployment of four sensor nodes using 12 geological sensors. The sensors will be used to collect the data values of an amount of rainfall, soil moisture, and angle variations. We will simulate the land displacement and moisture variations using a scaled down flume based experiment. The data collected from the sensor triplets placed in different locations will be sent to the cloud server via GSM (Global System for Mobile Communication).

We further improve upon the early warning system (EWS) using SMS-PP (Short Message Service,Point-to- Point) and SMS-CB (Short Message Service, Cell Broadcast) to pre-warn the people in the areas of increased risk of danger. With the real-time monitoring and effective early warning system in place, significant loss of life and property can be reduced.