# Human Health Impact Analysis of Contaminant in IoT-Enabled Water Distributed Networks
###### Abstract  
This paper aims to assess and analyze the health impact of consuming contaminated drinking water in a water distributed system (WDS). The analysis was based on qualitative simulation performed in two different models named hydraulic and water quality in a WDS. The computation focuses on quantitative analysis for chemically contaminated water impacts by analyzing the dose level in various locations in the water network and the mass of the substance that entered the human body. Several numerical experiments have been applied to evaluate the impact of water pollution on human life. They analyzed the impact on human life according to various factors, including the location of the injected node (pollution occurrence) and the ingested dose level. The results show a significant impact of water contaminant on human life in multiple areas in the water network, and the level of this impact changed from one location to another in WDSs based on several factors such as the location of the pollution occurrence, the contaminant concentration, and the dose level. In order to reduce the impact of this contaminant, water quality sensors have been used and deployed on the water network to help detect this contaminant. The sensors were optimally deployed based on the time-detection of water contamination and the volume of polluted water consumed. Numerical experiments were carried out to compare water pollution's impact with and without using water quality sensors. The results show that the health impact was reduced by up to 98.37% by using water quality sensors. human health analysis; water contamination; water quality model; hydraulic model; WDS; water quality sensors +
Footnote †: journal: Applied Material  
diarrhea, polio, dysentery, cholera, hepatitistis, gastric ulcers, pneumonia, and pulmonary disease [7]. Water supplies may contain various non-biological contaminants, including silica, sodium, sulfur, ammonia, and chlorine. In addition to these contaminants, microbiological contaminants in drinking water at the stage of consumption represent another problem of water quality. Poor drinking water quality significantly affects consumers' health [8]. In recent years, many developing countries have set public health goals to reduce waterborne diseases and develop safe water resources, and the situation has improved slightly. This somewhat improved situation can be further exacerbated by increased water demand and lower water availability due to population growth and economic growth. Understanding the factors that influence the quality of drinking water is also a necessary step in making the right decisions about protecting and managing the quality of drinking water [9]. In general, the quality of drinking water is affected by the variety of water sources, the treatment in predistribution water treatment plants, the water distribution system, and the containers or tanks used for water storage and household filters. However, in rural areas and small municipalities, drinking water is generally pumped directly from wells or rivers, lakes, and reservoirs without adequate treatment [10]. Therefore, the quality of water sources plays a fundamental role in determining the quality of drinking water. Protecting water source quality, which plays a crucial role in providing safe drinking water, usually requires the combined efforts of many partners, such as water managers, industrial plants, water supply, communities, and the public [11]. Evaluation of individual water quality parameters may not give a good understanding of water quality between partners with different scientific backgrounds. On the other hand, the traditional method, even by water quality experts, can also cause subjective judgments and prejudices. To solve the problems associated with characterizing and interpreting the state of water quality, various indicators of water quality have been developed to convert the levels of water quality parameters into a numerical index integrated using mathematical tools [12].