In the chain of water distribution, the network is the most complex element to be analyzed and managed to deliver safe water to the users due to the vast dispersion of the potential contamination spots. For this reason, some countries, especially those most sensible to the terrorist attacks (USA, Israel, Europe) have already started research programs aimed at the development of an Online Water Quality Monitoring (OWQM) and of an Early Warning Systems (EWSs). Both of them are based on sensors installed in selected nodes of the network and are capable of quickly detecting contamination events. The implementation of EWSs paves the way to new interesting research topics, with particular reference to the technological aspects, to the employment of expert systems for the interpretation of the detected data, and to the definition of modeling tools for the design and management of the monitoring and alarm systems. The Thesis focuses on some of these aspects, with the aim of contributing to a partial systematization of the knowledge required for the design and management of the aforementioned systems. This Thesis can be divided into two parts. The former part of the Thesis (Chapters 1, 2 and 3) describes the general issues and the approach normally adopted in choosing the water parameters to be monitored. The latter part of the Thesis (Chapters 4, 5 and 6) deals with some modeling aspects regarding the design and management of EWS, introducing innovative proposals and developments. In particular, the attention is given to the issue of determining the number and the optimal location of the sensors within the network. Ultimately, the last chapter shows the technical feasibility of a smart prototype system for the early detection of biological contaminations within the network. This system will efficiently enable water utility managers to ensure a real-time adoption of water quality control procedures.

Monitoring, early detection and warning systems for contamination events in water distribution networks.

TINELLI, SILVIA
2018-03-16

Abstract

In the chain of water distribution, the network is the most complex element to be analyzed and managed to deliver safe water to the users due to the vast dispersion of the potential contamination spots. For this reason, some countries, especially those most sensible to the terrorist attacks (USA, Israel, Europe) have already started research programs aimed at the development of an Online Water Quality Monitoring (OWQM) and of an Early Warning Systems (EWSs). Both of them are based on sensors installed in selected nodes of the network and are capable of quickly detecting contamination events. The implementation of EWSs paves the way to new interesting research topics, with particular reference to the technological aspects, to the employment of expert systems for the interpretation of the detected data, and to the definition of modeling tools for the design and management of the monitoring and alarm systems. The Thesis focuses on some of these aspects, with the aim of contributing to a partial systematization of the knowledge required for the design and management of the aforementioned systems. This Thesis can be divided into two parts. The former part of the Thesis (Chapters 1, 2 and 3) describes the general issues and the approach normally adopted in choosing the water parameters to be monitored. The latter part of the Thesis (Chapters 4, 5 and 6) deals with some modeling aspects regarding the design and management of EWS, introducing innovative proposals and developments. In particular, the attention is given to the issue of determining the number and the optimal location of the sensors within the network. Ultimately, the last chapter shows the technical feasibility of a smart prototype system for the early detection of biological contaminations within the network. This system will efficiently enable water utility managers to ensure a real-time adoption of water quality control procedures.
16-mar-2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1214885
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