This book explores how technology can enhance water management by promoting transparency, sustainability, and collaborative decision-making. It highlights the potential of the Internet of Things (IoT) and blockchain technologies to address water-related challenges through secure data storage, decentralized information sharing, and real-time monitoring. Key themes include the role of blockchain in ensuring transparency in water distribution and quality, as well as how IoT devices can assist in leak detection and resource conservation. The book underscores the importance of participatory decision-making among stakeholders through effective data sharing. Additionally, it discusses challenges such as scalability and data security, offering solutions for successful implementation. Ultimately, the book advocates for the critical role of technology in achieving sustainable and efficient management of water resources.
Part I: Introduction to Water Informatics.- Water Monitoring System: A
Blockchain IoT Approach A water monitoring system based on a Blockchain
Internet of Things (IoT) approach can provide a robust and secure solution
for managing water resources. This research leverages the benefits of both
blockchain technology and IoT devices to enhance transparency, data
integrity, and efficiency in water monitoring and management.- Distribution
System in Water Quality Monitoring: Sensor Technology, Evaluation Methodology
and Results This chapter covers distribution System in Water Quality
Monitoring refers to the monitoring of water quality parameters within the
distribution network of a water supply system. This is crucial to ensure the
safety and quality of water reaching the consumers. Sensor technology,
evaluation methodology, and results play a vital role in effective water
quality monitoring. Real-Time Decision-Support System for High-Mix Low-Volume
Production Scheduling in Industry 4.0 This research proposes a real-time
decision-support system for high-mix low-volume (HMLV) production scheduling
in Industry 4.0 refers to an advanced software system that assists in making
optimal scheduling decisions for manufacturing processes involving a large
variety of products produced in small quantities.- Part II: Tracking and
Detecting Leakage Water Consumption- IoT Water Consumption Monitoring & Alert
System This chapter coverages an IoT water consumption monitoring and alert
system provides real-time tracking of water usage in households or commercial
buildings. It helps promote water conservation, detect leaks, and enable
timely interventions.- A Decision Support Tool for Water Supply System
Decentralization via Distribution Network Sectorization This study suggest a
decision support tool for water supply system decentralization via
distribution network sectorization refers to a software-based system that
assists in making informed decisions regarding the division of a water
distribution network into smaller sectors for improved management and
efficiency.- Economic Analysis of IoT and Blockchain-based Leak Detection
Systems This research conducts a cost-benefit analysis of implementing IoT
and blockchain-based leak detection systems compared to traditional methods.
Discuss factors such as installation costs, maintenance requirements,
accuracy, water savings, reduction in non-revenue water, and infrastructure
preservation to assess the economic viability of these technologies.- Part
III: Regulatory Compliance and Auditing of Water Resources Trading and
Allocation.- A Framework of Blockchain Technology in Intelligent Water
Management This study envisages Blockchain technology can provide a robust
and transparent framework for intelligent water management, enabling secure
data sharing, efficient transactions, and improved
decision-making.- Blockchain-smart contracts for sustainable project
performance: bibliometric and content analyses It explains blockchain
technology and smart contracts have the potential to enhance sustainable
project performance by providing transparency, accountability, and
efficiency.- A Lightweight Blockchain Based Framework for Underwater IoT
Developing a lightweight blockchain-based framework for Underwater Internet
of Things (IoT) involves addressing the unique challenges posed by the
underwater environment, such as limited bandwidth, high latency, and energy
constraints is the major theme of this research.- Part IV: Finding
Sustainability Through Water Informatics and Future Prospects.- Future water
quality monitoring: improving the balance between exposure and toxicity
assessments of real-world pollutant mixtures This study discusses future
water quality monitoring efforts should aim to improve the balance between
exposure and toxicity assessments of real-world pollutant
mixtures.- Implementation and Integration of Sustainability in the Water
Industry: A Systematic Research The implementation and integration of
sustainability in the water industry require a systematic research approach
to address the complex challenges and ensure long-term environmental, social,
and economic viability.- Internet of Things (IoT): Opportunities, issues and
challenges towards a smart and sustainable future The Internet of Things
(IoT) presents numerous opportunities for creating a smart and sustainable
future, but it also brings along a set of issues and challenges like
efficient resource management, environmental monitoring and sustainability
etc.
Sur Singh Rawat holds a Ph.D. in Computer Science and Engineering from Govind Ballabh Pant Engineering College, Pauri Garhwal, which is affiliated with Uttarakhand Technical University, Dehradun, India. He earned his Master of Technology degree in Information Technology from IIIT, Allahabad, India, in 2010, and his Bachelor of Technology degree in Computer Science and Information Technology from UPTU, Lucknow, in 2004. Currently, he serves as an assistant professor at JSSATE, Noida, India. His research areas include digital image processing, pattern recognition, and deep learning.
Nitima Malsa is also an assistant professor in the Department of Computer Science and Engineering at JSSATE, Noida, India. Her research interests encompass blockchain technology, machine learning, smart contracts, and cryptocurrency. She has published over 30 papers in various journals and conference proceedings, and has served as an editorial and review member for academic journals and conferences. Dr. Malsa has chaired numerous conference sessions and conducted many special sessions at international conferences. She has received funding for a project focused on blockchain technology from the CSTUP, Government of India.
Gyanendra Kumar earned his B.Tech. in Computer Engineering and Information Technology from Uttar Pradesh Technical University, Lucknow, in 2004, followed by an M.Tech. in Information Technology from J.C. Bose University of Science and Technology, YMCA, Faridabad, Haryana, in 2011. He completed his Ph.D. in Computer Engineering from the same institution in 2023. Dr. Kumar is currently an assistant professor at Manipal University Jaipur, Rajasthan. With over 18 years of academic experience across various engineering colleges and universities, he has published numerous research papers in reputable journals and conferences. Dr. Kumar serves as a reviewer for esteemed publishers such as Elsevier, Springer, MDPI, and Tech Science Press. He has been an invited speaker, session chair, and track chair at various international conferences, and is a professional member of IEEE and ACM.
Vimal Gupta obtained his B.Tech. degree in Computer Science and Engineering from Maharishi Dayanand University, Rohtak, and his M.Tech. in Computer Science and Engineering from Guru Gobind Singh Indraprastha University, New Delhi. He is currently pursuing a Ph.D. from Dr. A.P.J. Abdul Kalam Technical University, Lucknow. His research interests focus on medical image processing, data compression, and deep learning.
