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Full Description
Integrated Smart Technologies for Sustainable Water Systems using Computer Applications presents a comprehensive exploration of how cutting-edge computational technologies are revolutionizing water resource management. This multidisciplinary guide demonstrates the practical integration of artificial intelligence, IoT systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.
The book systematically examines the application of advanced technologies including Artificial Intelligence, Machine Learning, Internet of Things, Blockchain, Cloud and Edge Computing, and Geographic Information Systems across diverse water management scenarios. Through theoretical models, algorithmic approaches, and real-world case studies from both developed and developing countries, it illustrates key findings in AI-driven water demand and quality predictions, IoT-enabled real-time distribution network monitoring, blockchain applications for transparent water resource transactions, intelligent flood forecasting systems, automated irrigation methods, wastewater treatment automation, and digital twin development for dynamic infrastructure modelling. The work uniquely incorporates emerging concepts such as explainable AI, climate resilience frameworks, and digital twin technologies, positioning it at the forefront of current industry and academic research trends.
This essential resource is designed for researchers, industry professionals, software developers, educators, and students specializing in water resource management and sustainable technology applications. The content balances foundational insights with advanced methodologies, making it equally valuable for newcomers seeking comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.
Contents
1. Computer-Aided RSM and Kinetic Modelling of Phenol Removal from Arsenic-Selenium Co-Contaminated Water Using Filtrasorb Activated Carbon 2. Responsible AI in Action: Trends for Ethical and Sustainable Smart Technology 3. IoT and Wireless Sensor Networks for Real-Time Water 4. Smart Technologies for Water Quality Prediction with AI and ML 5. Blockchain for Secure and Transparent Water Resource ManagementWastewater Following Membrane-based Method 6. Digital Twin Modelling for Water Distribution Network 7. Flood Prediction Using Machine Learning Techniques 8. Smart Irrigation & Precision Agriculture for Water Resource Management: Sensor-Driven Irrigation, Crop Water-Use Optimization, and Decision Support 9. AI-Based Flood Prediction and Early Warning Systems 10. Smart Irrigation systems based on IoT and Remote Sensing 11. An IoT-Integrated Smart Irrigation System with Machine Learning for Water Conservation in Precision Agriculture 12. Urban Drainage and Wastewater Systems to Automation 13. Efficient Water Quality Assessment: Synergistic Integration of Computer Vision and Machine Learning 14. Cybersecurity in Smart Water Systems 15. Water Quality Monitoring with Computer Vision and ML 16. Scalable ML deployment strategies: Case study on water management, print ,and logistics
