Novel Data Preprocessing Algorithm for WSN Lifetime Maximization in Water Pipeline Monitoring System

Wireless Sensor Networks (WSN) are widely deployed to maintain Structural Health Monitoring of Water Pipeline System (WPS). Accordingly, it is imperatively important to ensure reliable communication between sensor nodes deployed in harsh environment to allow a continuous data collection and processing. In this context, we propose and implement an energy efficient solution that enables a seamless interconnection between sensor nodes, and trusty data transmission in order to maximize the network lifetime. After a clustering step, a Data Redundancy Elimination technique is applied to remove redundant data at each cluster head. This operation is followed by a data fusion algorithm based on Dempster-Shafer evidence theory at the Base Station. This scheme is proposed with aim of reducing the size of data carried by the network and consequently save on energy consumption. This results in improved WSN lifetime and more accurate WPS systems.