Water Distribution: An Overview
A water distribution network is a network of pipes, valves, pumps, reservoirs, storage tanks, etc., that transports water from a central treatment plant to individuals or a group of consumers to meet domestic, agricultural, or industrial needs.
The overall goal of a water distribution network is to meet the water needs of its end-user at a relevant quantity, quality, and pressure. An ideal water distribution system should fulfill all of these criteria.
Not many water distribution networks meet these requirements due to a variety of factors, some of which are:
- Inefficient distribution of water through the network
- Water losses due to pipe leakages or unauthorized use
- Machinery breakdown leading to increased expenditure
- Inefficient energy utilization due to inappropriate pump scheduling
- Water contamination at any point during the delivery process
How Artificial Intelligence can Improve Water Distribution
AI can be used to resolve several areas of challenge in water distribution.
To begin, AI can upgrade the design of monitoring and control networks as digital twins i.e. virtual replications of physical distribution networks. The AI algorithms will have the capacity to analyze statistical relationships with more refined precision and accuracy. The virtual model’s simulations can be used to inform the real-world construction of the network.
AI can also be used for the real-time monitoring of the water network to determine unaccounted water losses by calculating the difference between measurements obtained from the network and the model’s predictions at each control point. The information extracted can then be used to determine whether the water loss is due to unauthorized consumption or a pipe leakage. The value of this application of AI is that it saves time and resources wasted on deploying maintenance teams on-site to evaluate the unaccounted water loss from scratch.
The Government of India has a project that uses IoT for water distribution monitoring called “Intelligent Water Supply Network Monitoring and Control for EQuitable Distribution of WATER within a Mega city (EQWATER)”. The data is used to determine the reasons for changes in water availability in different neighborhoods.
To ensure peak functionality of all machines involved, AI can be used to automate the process of assessing for structural faults in pipes. Furthermore, AI can provide optimized response strategies in real-time to adjust to emergencies such as water scarcity, contamination events, pipe bursts, etc. AI can also reduce the incidence of crises due to equipment failure through predictive maintenance in which the algorithms use a variety of data to make recommendations on equipment maintenance and repair thus preventing problems before they arise. In this way, pipe leakages leading to water loss can be reduced.
AI can improve energy utilization and water delivery. For example, the algorithms can be used to regulate water volume in storage tanks for controlled delivery to the required areas. The water pumping schedule can be automated to optimize pump and valve schedules to reduce maintenance cost while assuring energy minimization.
Finally, AI can be used to improve the water quality in three important ways. In the first instance, it can facilitate the real-time tracing of the source of a contamination in the distribution network. In the second instance, it can be used to monitor and control the dosing of chlorine in the water network ensuring optimal delivery as necessary. In the third case, AI can improve water quality by reducing the amount of time that water spends unutilized in pipes or in the storage tanks.