الفهرس 
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Abstract
Water is vital for human survival, health and dignity. It is a fundamental resource for human and economic development. Nevertheless, it is considered one of the poorest managed natural resources. It is estimated that water distribution networks lose around 40% of the pumped water through the network due to physical and apparent losses in a phenomenon known as Non-Revenue Water (NRW). Expanding water networks without addressing water losses will only lead to a cycle of waste and inefficiency. Also, high rates of Non-Revenue Water (NRW) is closely related to poor energy efficiency as water transported in networks is loaded with energy through the distribution and treatment processes. Therefore, reducing NRW is important to overall efficiency and financial sustainability, since it provides additional revenues and reduces costs.
One of the other hand, smart water networks using ICT technologies are becoming a real critical pursuit for utility owners around the world in order to face the increasing water demand with the old-ageing infrastructure. Through continuous monitoring of Water Distribution network (WDN), utility companies can get prompt identification for critical events such as leaks and bursts, leading to reduction of Non-Revenue Water (NRW) losses.
In this thesis, we investigate the use of wireless sensor network (WSN) and internet of things (IoT) technologies for continuous monitoring of the hydraulic status of water distribution networks. Most of the existing literature assumes the continuous water supply network with 24 hours of feeding. We focus our investigation of intermittent water distribution networks, which are prevalent in many developing countries due to the limited supply and hydraulic capacity of the network. We present a tailored WSN system for monitoring of intermittent WDN, which optimize the operation of the embedded pressure sensors and wireless transmission. We also propose an adaptive Kalman filter approach to leakage and burst detection in intermittent water distribution network from the time-series data analysis of the measured pressure data.
We validate the performance results of the proposed system using simulated and real measurement data from a case study of a pilot intermittent supplied district meter area (DMA) in Hurghada, Egypt.