Autonomous Monitoring of River Level with Real Time Event Prediction

Abstract

Observation of water level at various river sites could provide valuable insight about probable disaster in advance to initiate disaster management protocol as early as possible. We have developed an autonomous remote river water level monitoring network with event prediction algorithm at the server while maintaining a substantially low manufacturing cost. The WSN is comprised of several chosen sites based on their statistics with intelligent sensors for water level measurement. The sensors are autonomous in nature to account for any disturbance in node environment and also within the network. The real time data are transmitted to a remote server through GPRS for further processing. Server extracts information and simulates various real time parameters such as water level rise rate, time remaining to exceed the critical level for a particular site etc. A prediction algorithm running on the server side predicts the measured level values for each node over a period of time. A prototype system is implemented with six nodes at different points and has yielded satisfactory results.