Applied fuzzy heuristics for automation of hygienic drinking water supply system using wireless sensor networks

About 20% of communicable infectious disease is spread by drinking contaminated water. Hence, a real-time in-pipe drinking water quality system using sensor networks is proposed. The proposed prototype Drinking Water Quality Monitoring System (DWQMS) checks for parameters such as pH, temperature, turbidity, oxidation–reduction potential, conductivity, and dissolved oxygen in the drinking water supplied through pipes by the municipality in a fast and efficient manner. In the proposed work, a sensor network that is powered by solar energy is deployed inside the water pipelines to improve the network connectivity and enhance the network lifetime. The prototype designed uses an Energy Aware Multipath Routing Protocol (EAMRP) to prevent the water flow when contamination is detected in a particular pipeline region without interrupting the supply in non-contaminated regions. The key ingredients of the proposed protocol are an energy-efficient algorithm; maximizing the data correlation among sensors; shortest path routing and fast data transmission algorithm to report the water quality to the users quickly; event detection algorithms to assess the water contamination risks in pipes; and fuzzy rule descriptors to predict the water quality as desirable/acceptable/rejected for drinking with better accuracy. The simulation results show that the designed DWQMS acts as an early warning system and outperforms in terms of energy efficiency, detects the contaminants with better accuracy, increases network lifetime, and better estimates the water quality parameters. The proposed algorithms are tested in a small test bed of wireless sensor networks with 20 nodes that monitor the drinking water quality distributed in water distribution mains, which alert the consumers/houses in the water-contaminated regions.