Multi-Agent-Based Modeling for Underground Pipe Health and Water Quality Monitoring for Supplying Quality Water

Multi-Agent-Based Modeling for Underground Pipe Health and Water Quality Monitoring for Supplying Quality Water

Lakshmi Kanthan Narayanan (Chennai Institute of Technology, Chennai, India), Suresh Sankaranarayanan (SRM Institute of Science and Technology, India), Joel J. P. C. Rodrigues (Federal University of Piaui (UFPI), Brazil & Instituto de Telecomunicações, Portugal) and Pascal Lorenz (Université de Haute-Alsace, France)
Copyright: © 2020 |Pages: 28
DOI: 10.4018/IJIIT.2020070103


This article discusses distributed monitoring through the deployment of various multiagents in the IoT-Fog-based water distribution network (WDN). This will ensure the right amount of water supplied with respect to demand forecasted to residents. In addition, underground pipe health is also monitored by means of a multiagent based on hydraulic parameters supplying water forecasted with minimal losses which would minimize the operational and material cost involved in recovery or repair. Lastly, there are agents deployed towards leakage monitoring and anti-theft detection of water. The multiagents act upon various parameters of hydrology and analysis is based on the data acquired by the various sensors deployed in the water distribution network which perform partial automation of the disconnection of the supply during extreme critical conditions.
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1. Introduction

Water and its resources are exposed to contamination and get polluted due to rapid growth in industrialization, population and urbanization. The rate of consumption of water and the rate at which the resources are getting polluted is alarming the entire world, which has already led to ‘Day Zero’ in many countries. The sustainability in water supply has gained much importance in meeting the urban demand in which the usage of water for domestic purpose play a vital role. The people residing in Netherland and United States (US) utilize nearly more than half of the water supplied for household usage.

The drastic change in Climatic condition will also affect the water quality and also lead to scarcity of resource. This will also result in the increase of people affected by water- borne disease globally. The other reasons for the diminishing in the quality level of drinking water supplied through the water distribution system are due to breakdown in pipes, erosion of pipes and reaction with pipe materials. It has become essential to resolve these issues through technology and also it is the need of the hour to come up with a system that provides an optimal and flexible solution.

The total consumption of water for various utilization in household differs significantly between families based on the size of the family, habitation and lifestyle (Smith and Ali, 2006). It is also essential to have a detailed knowledge and better understanding about the requirements of the consumers (Shove, 2003).

Figure 1 displays various water borne diseases and also about the percentage of people affected by it. Figure 2 describes the population around the globe lacking access to safe water.

Computer Science is the origin of Multi-agent systems which is widely used in almost all fields of engineering for different applications using IoT and it is tough to find a global definition for multi-agent system (Berger, 2004).

The widely accepted definition is “A computer system resides in an environment which is capable of performing autonomous action in order to satisfy the design goals” (Abbas et al., 2015, Woolridge, 2009).

These agents are classified on the basis of goal-directed and reactive behavior (Son, 2015). Figure 3 illustrates about a simple multi agent system.

Figure 1.

Various types of waterborne diseases (Ameer, 2017)

Figure 2.

World’s population lacks in access to safe water


Since the multi agent system has a diverse nature and can be applied to ‘n’ number of applications, it is very hard to define a system on the basis of their applications. Based on the operations they perform, the agents are classified as control agents, communication agents, decision making agent and data acquisition agents (Bousquet and Page, 2004).

The evolution of Internet of Things (IoT) has made a dramatic turnaround in almost all the fields of applications such as inventory managements, engineering, health care, data science, research, defense, cruise control in ships and airplanes, automation, business analytics etc. It enables the luxury of performing, controlling, monitoring and reporting action sitting at any corner of the world. IoT has made the response and performance time of action to a greatest level of improvement in terms of time and accuracy.

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