Smart Water Technology for Sustainable Management in Modern Cities

• #1. Foundations of Smart Water and Artificial Intelligence Technologies
• #2. Challenges and Opportunities in Implementing AI for Smart Water
• #3. Water Quality Monitoring and Control With AI
• #4. Real-Time Water Quality Monitoring: Use of AI Sensors and Algorithms for Real-Time Monitoring of Water
• #5. The Critical Role of Water Quality: Health Impacts, Contaminants, and Sustainable Solutions for Environmental and Human Well-being
• #6. Applying the Water Sensitive City Index in a House of Quality Framework to Enhance Urban Water Governance and Sustainability: Evaluating Smart Water Cities
• #7. Water Demand Forecast and Efficient Supply Management
• #8. Optimising Water Use Through Smart Models and Artificial Intelligence
• #9. Precision Agriculture and AI-Driven Resource Optimization for Sustainable Land and Resource Management
• #10. Innovations and Efficiency in Wastewater Treatment Using Artificial Intelligence
• #11. An Optimal Method of Assessing the Quality of Water Using Integrated AI and Blockchain Methodology
• #12. Artificial Intelligence and Applications in Drinking Water Management
• #13. AI Applications in Drinking-Water Management
• #14. Integrating AI in Green and Blue Infrastructure for Sustainable Smart Cities

Jorge Ruiz-Vanoye is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the Secretaria de Ciencia, Humanidades, Tecnología e Innovación program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). Additionally, he holds the title of Lecturer-level Researcher for the Agency for the Quality of the University System of Catalonia (Generalitat de Catalunya). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.

Ocotlán Díaz-Parra is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the Secretaria de Ciencia, Humanidades, Tecnología e Innovación program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.