| Abstract |
More than two thirds of the earth's surface is covered by water. Water might be every where, but it should never be taken for granted. The consumption of non-potable water
could be fatal. The placing, monitoring, maintenance, and distribution of water, drinkable or not, consists quite a challenge. The purity of the water is ensured by frequently
sampling analysis. However, current physical sampling-based monitoring has been proven ineffective. Various ontamination Warning Systems (CWS)s have been developed to meet the need for real-time monitoring. These systems are used to monitor water quality employing sensor technology. However, there are critical factors that there were not taken into consideration or there were not examined sufficiently, such as the denouncements of the consumers and the public health organizations which are disregarded in the majority of the deployed Contamination Warning Systems. It has been
proven that the embodiment of the human factor in the system would further enhance the credibility.
Motivated by the need to inform and take the citizens into consideration in monitoring water quality operation, we developed the QoWater system. The QoWater is a novel user-centric crowd-sourcing system that assesses the water quality in a water distribution network (WDN). The QoWater relies on the measurements collected by distributed sensors on a
WDN, as well as taking into consideration the citizens' sentiment in order to evaluate the water quality. By using QoWater client, smartphone users evaluate the quality of water based on its taste, color, appearance, pressure, as well as chemical and/or biological parameters. The user sentiment is uploaded on the QoWater server, along with their position and a timestamp. Moreover, the QoWater system informs users about potential contamination events, that have been detected close to their location. The objective of the QoWater system is to assist water providers, and regulators to detect
accidental or deliberate contaminations in real-time and reduce the spread and number of affected victims in case of contamination.
This thesis presents the QoWater system and an extensive analysis in terms of power consumption, responsiveness, and scalability. In order to obtain a preliminary evaluation of the
QoWater, we conducted a field study, in which 44 real users assessed the quality of three sources of drinkable water. The outcomes of the performance analysis and the field study
are encouraging. Power consumption and response delay are relatively low. Once more it has been proven that people are in a position to detect changes in the drinkable water quality, hence their sentiment is useful and decisive on water quality monitoring. Finally, the development of a water quality index (WQI), named Parabolic WQI (PWQI) and a power saving monitoring algorithm for sensors, called V-Trickle, are further contributions of this master thesis.
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