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Towards Sustainable Water Supply: Schematic Development of Big Data Collection using Internet of Things (IoT)


Water supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands of treatment facilities and appurtenances. This enormous set-up is currently operated by more than 170,000 public water systems. Sustainability of the water supply system faces several imminent challenges such as: 1) increasing water main breaks, 2) decreasing fresh water resources, 3) untraceable non-revenue water use, and 4) increasing water demands.

However, current water supply management practices are not capable of providing fundamental solutions to the issues identified above. Big Data is a new technical concept to collect massive amounts of relevant data from sensors installed to monitor structural condition, usage, and system performance. This Big Data concept can be realized by deploying Internet of Things (IoT) technology throughout the water supply infrastructure and consumers usage. This paper presents a schematic development of IoT application for Big Data collection through a myriad of water clients. The scheme consists of downstream and upstream data collection using Wireless Sensor Network (WSN) technologies connecting to IoT.

Downstream data shall provide water usage and performance data to clients and upstream data is similar to traditional SCADA and Automated Meter Reading (AMR) systems. Ultimately, all data will be converged to build a Big Data collection system where data mining identifies 1) local and system performances including pressure and flow, 2) non-revenue and illegitimate water consumption, and 3) locations and quantity of water breaks and water losses. The goal of this development is to enable both utilities and consumers to proactively manage their water usage and achieve higher levels of sustainability in water supply.


Figure 1.AMRsystem using GSM modem system

Figure 1.AMRsystem using GSM modem system

AMR technology has followed steps of IT development in networking technology. In the beginning of AMR development, the network system was not free of wired connection, short-range network such as radio frequency (RF), drive-by data collection, and connection of power source. Recent development of AMR uses advanced network technologies such as Wi-Fi, GSM modem, and power line communication. Figure 1 illustrates an existing AMR system using GSM modem system.


Figure 2. Internet of Things Schematic Showing the End Users and Application Areas Based on Data

Figure 2. Internet of Things Schematic Showing the End Users and Application Areas Based on Data

A fundamental difference of IoT comparing to existing technologies such as AMR or condition monitoring system is that IoT extends its data utilization beyond independently operating utility billing system or water leak detection warning. Big Data integrates the data and seeks mutual benefits for multiple stakeholders including water utility owner and customers through easy access facilitated by Internet operated via individual’s smart phone or computer. Figure 2 illustrates a schematic and holistic view of IoT application development.

Figure 3. Service Level vs. Development Level of IoT Application

Figure 3. Service Level vs. Development Level of IoT Application

Early development of network connections of things was already utilized in many areas. For example, pressure monitoring sensors were installed in petroleum pipeline to prevent theft, vandalism, leak and rupture. Pore-water pressure sensors were installed to set an automatic alarm prior to land sliding. This early development of above sensors and its application are limited only to collect specific data. Figure 3 shows co-relationship between expected service levels as IoT technology develops. IoT must have an intelligent function that automates decision making without human interference.


Figure 5. Indicators for Pipe Condition Assessment

Figure 5. Indicators for Pipe Condition Assessment

Many previous studies developed asset management frameworks, data collection, and failure prediction models. Pipe condition assessment is typically the second step of asset management followed by asset inventory. Pipeline condition assessment becomes baseline for various decisions made towards enhancement of sustainability. However, the industry severely experiences lack of adequate data collection and sensor technologies which is fundamental for an effective pipe condition assessment. Vairavamoorthy et al. proposes various indicators for the pipe condition assessment as shown in Figure 5. Other studies also proposed similar set of indicators. Limited access to this kind of data is one of the major challenges that warrant installing sensors to capture condition data from the buried pipes.


The concept of sustainability is well understood and attracts many industry practitioners and policy makers. However, practical and definite implementations that enhance sustainability are not easy. This paper describes a conceptual development of IoT and Big Data in the context of water supply systems highlighting its advantages and limitations. The paper advocates implementing IoT and Big Data technology for saving water resources and energy.

It is an imperative task to reduce several billion gallons of treated water loss. Most of public water supply system maintenance is performed in a reactive manner rather than proactive. This new technology will provide a possible solution to make the industry more proactive. Data is generated from sensors installed in each device, which is called IoT, and transferred through Internet network system. Application of IoT consists of smart sensors capturing water data and sophisticated data analysis to retrieve any useful information to enhance sustainability through virtual data platform and control system.

Therefore, two technologies, IoT and Big Data, should be effectively and efficiently integrated. Three main benefits in the water supply system are: 1) automated system condition monitoring including leak detection; 2) optimizing water supply, production, and energy consumption; and 3) optimizing water consumption. Although the technology seems not available for water supply system at this moment, IoT and Big Data will be key technical components to build smart and sustainable urban infrastructures.

Source: Indiana University
Authors: Dan Kooa | Kalyan Piratla B | John Matthews

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