Water Distribution Systems (WDSs) could be an easy target for accidental or intentional contamination in any city. The lack of reliable, real-time specific microbial and chemical contamination monitoring raises major public concerns as delayed detection accelerates the fast growth of the public health risk. In this context, the proposed research aims to develop, adapt and demonstrate the technical feasibility of smart Bio-Sensing & Information Management (Bio-SIM) that will effectively enable water operators to ensure smart water monitoring and quasi real-time quality control for early contamination detection and preemptive warning. Facing a lack of labeled data, numerical simulations with engineering models (EPANET-MSX) have been adopted to produce synthetic data for pattern recognition of the effect of bio-contamination on chemical and physical water parameters (e.g. pH, TOC, turbidity and free chlorine). Statistical and stochastic models enabled non-specific bio-anomaly detection, based on pattern recognition of Chlorscan data and selected parameters that can be monitored simultaneously online using multi-parameter sensors (e.g. s::can). The results were compared with laboratory model tests and numerical simulations. This paper outlines the main results of the feasibility assessment of the Bio-SIM prototype system for early bio-contamination detection, which is expected to significantly contribute to alleviating consumers’ bio/chemical contamination risks.

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