scholarly journals Smart water grid: a review and a suggestion for water quality monitoring

2021 ◽  
Author(s):  
B. Bharani Baanu ◽  
K. S. Jinesh Babu
Keyword(s):  
Water Resources ◽  
Real Time ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Quality Parameters ◽  
Smart Water ◽  
Networking Protocols ◽  
Smart Water Grid

Abstract Water is a valuable resource and an elixir of life. It is intimately linked to the living standards around the world. Reducing the water stress and conserving the resource is vital. It is the need of the hour to ameliorate the conventional water resources systems to monitor the water quantity and quality parameters continuously in real-time. Smart solutions play an important role in monitoring the system parameters and make on-site measurements. This paper focuses on Smart Water Grid, an ingenious way to monitor and preserve the quantity and quality parameters in real-time by deploying remote sensors in water distribution system. It presents a review of various sensors deployed, networking protocols used and cloud platforms employed in monitoring the water distribution system. The suitable networking protocols for the water distribution systems are suggested by analyzing various smart solutions. It also proposes an architecture for an IoT-based system to monitor the residual chlorine concentration in water distribution system. Smart Water Grid using Wireless Sensor Networks and the Internet of Things enables to monitor on-site conditions and generates alerts during abnormal conditions. It can enhance timely decision making which will help in managing valuable water resources more efficiently.

scholarly journals E-Metering and Fault Detection in Smart Water Distribution Systems using Wireless Network

2019 ◽  
Vol 8 (11) ◽  
pp. 634-639
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Rural Areas ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB

scholarly journals E-Metering and Fault Detection in Smart Water Distribution Systems using Wireless Network

2019 ◽  
Vol 8 (11) ◽  
pp. 634-639
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Rural Areas ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB

scholarly journals A Wireless Sensor Network Model for E-Metering and Fault Identification in Smart Water Distribution Systems

2019 ◽  
Vol 8 (10S) ◽  
pp. 227-232
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Distribution System ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Wireless Sensor ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB.

scholarly journals An Advanced Learning-Based Multiple Model Control Supervisor for Pumping Stations in a Smart Water Distribution System

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 887 ◽  
Author(s):  
Alexandru Predescu ◽  
Ciprian-Octavian Truică ◽  
Elena-Simona Apostol ◽  
Mariana Mocanu ◽  
Ciprian Lupu
Keyword(s):  
Machine Learning ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Metropolitan Areas ◽  
Operating Conditions ◽  
Multiple Model ◽  
Smart Water ◽  
Model Control

Water distribution is fundamental to modern society, and there are many associated challenges in the context of large metropolitan areas. A multi-domain approach is required for designing modern solutions for the existing infrastructure, including control and monitoring systems, data science and Machine Learning. Considering the large scale water distribution networks in metropolitan areas, machine and deep learning algorithms can provide improved adaptability for control applications. This paper presents a monitoring and control machine learning-based architecture for a smart water distribution system. Automated test scenarios and learning methods are proposed and designed to predict the network configuration for a modern implementation of a multiple model control supervisor with increased adaptability to changing operating conditions. The high-level processing and components for smart water distribution systems are supported by the smart meters, providing real-time data, push-based and decoupled software architectures and reactive programming.

scholarly journals Case study: a smart water grid in Singapore

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
Michael Allen ◽  
Ami Preis ◽  
Mudasser Iqbal ◽  
Andrew J. Whittle
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Quality Parameters ◽  
Supply System ◽  
System Operation ◽  
Smart Water ◽  
On Line ◽  
Software Platforms ◽  
Smart Water Grid

As aging water distribution infrastructures encounter failures with increasing frequency, there is a real need for integrated, on-line decision-support systems based on continuous in-network monitoring of hydraulic and water quality parameters. Such systems will form the basis of a Smart Water Grid, allowing water utilities to improve optimization of system operation, manage leakage control more effectively, and reduce the duration and disruption of repairs and maintenance. WaterWiSe is an integrated, end-to-end platform for real-time monitoring of water distribution systems that addresses these needs. This paper describes how WaterWiSe's sensing and software platforms have helped improve the operational efficiency of the water supply system in downtown Singapore.

scholarly journals Community-Level Resource Development and Management, Part 1: A Transferable Approach to the Analysis of Community Water Distribution System Expansion

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Megan McWalter Richardson ◽  
Kendra V. Sharp
Keyword(s):  
Water Resources ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Distribution Networks ◽  
Community Level ◽  
Rural Tanzania ◽  
Open Source Software Package ◽  
Development And Management

Access to water is extremely important in schools around the world, where students spend most of their day. As schools expand, particularly in areas with limited water resources, it is necessary to develop and manage water resources to ensure their sustainability. In this article we describe a method of analyzing water piping distribution networks using an open-source software package that allows practitioners to model the increased demands on water distribution systems associated with school growth. The methodology was then applied to the case study of a community-level water distribution system in rural Tanzania. This method is valuable because it is both condensed and easy to follow for those in the field with or without technical backgrounds. Minimal tools are needed for practitioners to develop their own system models (only a GPS, tape measurer, bucket, stopwatch and access to a computer with the software downloaded). Overall, this condensed written resource is more accessible than others available to many practitioners and thus improves the ease of modeling for pre-planning and analysis of expansion or other water distribution system modifications.

scholarly journals A Head Formulation for the Steady-State Analysis of Water Distribution Systems Using an Explicit and Exact Expression of the Colebrook–White Equation

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1163
Author(s):  
Mengning Qiu ◽  
Avi Ostfeld
Keyword(s):  
Steady State ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Solution Method ◽  
Water Distribution System ◽  
Academic Research ◽  
Exact Expression ◽  
Contamination Source

Steady-state demand-driven water distribution system (WDS) solution is the bedrock for much research conducted in the field related to WDSs. WDSs are modeled using the Darcy–Weisbach equation with the Swamee–Jain equation. However, the Swamee–Jain equation approximates the Colebrook–White equation, errors of which are within 1% for ϵ/D∈[10−6,10−2] and Re∈[5000,108]. A formulation is presented for the solution of WDSs using the Colebrook–White equation. The correctness and efficacy of the head formulation have been demonstrated by applying it to six WDSs with the number of pipes ranges from 454 to 157,044 and the number of nodes ranges from 443 to 150,630. The addition of a physically and fundamentally more accurate WDS solution method can improve the quality of the results achieved in both academic research and industrial application, such as contamination source identification, water hammer analysis, WDS network calibration, sensor placement, and least-cost design and operation of WDSs.

scholarly journals Comparison of Searching Behaviour of Three Evolutionary Algorithms Applied to Water Distribution System Design Optimization

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 695 ◽  
Author(s):  
Weiwei Bi ◽  
Yihui Xu ◽  
Hongyu Wang
Keyword(s):  
Evolutionary Algorithms ◽  
Real Time ◽  
Distribution System ◽  
Optimization Design ◽  
Distribution Systems ◽  
Water Distribution ◽  
Optimal Solutions ◽  
Great Ability ◽  
Searching Behaviour ◽  
Run Time

Over the past few decades, various evolutionary algorithms (EAs) have been applied to the optimization design of water distribution systems (WDSs). An important research area is to compare the performance of these EAs, thereby offering guidance for the selection of the appropriate EAs for practical implementations. Such comparisons are mainly based on the final solution statistics and, hence, are unable to provide knowledge on how different EAs reach the final optimal solutions and why different EAs performed differently in identifying optimal solutions. To this end, this paper aims to compare the real-time searching behaviour of three widely used EAs, which are genetic algorithms (GAs), the differential evolution (DE) algorithm and the ant colony optimization (ACO). These three EAs are applied to five WDS benchmarking case studies with different scales and complexities, and a set of five metrics are used to measure their run-time searching quality and convergence properties. Results show that the run-time metrics can effectively reveal the underlying searching mechanisms associated with each EA, which significantly goes beyond the knowledge from the traditional end-of-run solution statistics. It is observed that the DE is able to identify better solutions if moderate and large computational budgets are allowed due to its great ability in maintaining the balance between the exploration and exploitation. However, if the computational resources are rather limited or the decision has to be made in a very short time (e.g., real-time WDS operation), the GA can be a good choice as it can always identify better solutions than the DE and ACO at the early searching stages. Based on the results, the ACO performs the worst for the five case study considered. The outcome of this study is the offer of guidance for the algorithm selection based on the available computation resources, as well as knowledge into the EA’s underlying searching behaviours.

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