A complex network theory approach for optimizing contamination warning sensor location in water distribution networks

TL;DR

This paper introduces a novel approach combining classical optimization and complex network theory to optimize sensor placement for contamination detection in water distribution networks, enhancing early detection and system efficiency.

Contribution

It presents a new modeling method that integrates complex network analysis with optimization techniques for sensor placement in water networks.

Findings

Improved detection efficiency in water networks.

Enhanced understanding of network vulnerabilities.

Potential for faster contamination response.

Abstract

Drinking water for human health and well-being is crucial. Accidental and intentional water contamination can pose great danger to consumers. Optimal design of a system that can quickly detect the presence of contamination in a water distribution network is very challenging for technical and operational reasons. However, on the one hand improvement in chemical and biological sensor technology has created the possibility of designing efficient contamination detection systems. On the other hand, methods and tools from complex network theory, which was primarily the domain of mathematicians and physicists, provide analytical output for engineers to design, optimize, operate, and maintain complex network systems such as power grids, water distribution networks, telecommunication systems, internet, roads, supply chains, traffic and transportation systems. In this work, we develop a new modeling approach for the optimal placement of sensors for contamination detection in a water distribution network. The approach originally combines classical optimization and complex systems theory.