Smart Water Distribution System Communication Architecture Risk Analysis Using Formal Methods

2020 ◽  
Author(s):  
Stefana Krivokuca ◽  
Branka Stojanovic ◽  
Katharina Hofer-Schmitz ◽  
Natasa Neskovic ◽  
Aleksandar Neskovic
Keyword(s):  
Risk Analysis ◽  
Formal Methods ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
System Communication ◽  
Communication Architecture ◽  
Smart Water

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 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 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.

Risk Analysis Model for Water Pipeline Leakage Based on FAHP and BPNN

2013 ◽  
Vol 441 ◽  
pp. 1093-1096
Author(s):  
Wen Zeng ◽  
Yong Ting Pan ◽  
Hong Mei Huang
Keyword(s):  
Neural Network ◽  
Risk Analysis ◽  
Bp Neural Network ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Economic Loss ◽  
Analysis Model ◽  
Initial State ◽  
Water Pipeline

Scientific analysis of the leakage of the water distribution system in city is very helpful to water supply network’s maintenance and renovation, and hence reduces negative social effect and economic loss. A leakage risk nalysis model for water distribution system was established based on fuzzy analytical hierarchy process (FAHP) and BP neural network (BPNN). This model introduces FAHP to reasonably ensure initial state of BP neural network, and uses weighted superposition to mend learning sample set of BP neural network. The water distribution system of a city in Zhejiang province P. R. China was selected to test the proposed risk analysis model, which verifise its feasibility and effectivity.

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.

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