Data Reduction and Energy Sustenance in Multisensor Networks for Landslide Monitoring

We present extensive studies into data reduction and energy minimization in Sensor Networks for landslide detection. What started as a simple homogenous network of rainfall sensors has evolved into a complex heterogeneous network of 20 wireless probes with each probe consisting of four different types of sensors to measure rainfall, moisture, pore pressure, and movement, all of which have been in continuous operation for more than two years in the equatorial forests of Kerala, India. Each probe runs on solar power and the frequency of sensor data measurements from the probes is dynamically and adaptively throttled in real time, based on climatic conditions to minimize the total energy consumption. The probes also work together to identify who among them is sensing the maximum parameter, after which all other sensors are switched off for a predetermined duration. We present detailed analysis of data reduction and energy savings, and also relate them to the effectiveness of landslide detection. The whole system was validated by the issuance of a landslide warning in the month of July (last monsoon season), which facilitated pre-emptive action by the local government and community to prevent loss of human life.