Jayashree Mohanty – författare

The application of artificial intelligence (AI) to the management and development of renewable energy sources has revolutionized the energy sector by enhancing efficiency, reliability, and scalability. With the capability to analyze weather patterns, solar radiation, and wind speeds, AI-driven technologies help ensure optimal utilization of such re-sources as solar panels and wind turbines. Artificial Intelligence for Renewable Energy Systems focuses on using AI technology to advance green energy and its management. Starting with an overview of applying AI to renewable energy management, the book follows with such real-world examples:Predictive analytics for wind turbine maintenanceIntelligent solar grid integrationVehicle-to-grid (V2G) technology for electric mobilityTaking a multidisciplinary approach, the book is a guide for academics, energy practitioners, engineers, and policymakers who are leveraging the constructive collaboration between AI and renewable energy technologies.

The application of artificial intelligence (AI) to the management and development of renewable energy sources has revolutionized the energy sector by enhancing efficiency, reliability, and scalability. With the capability to analyze weather patterns, solar radiation, and wind speeds, AI-driven technologies help ensure optimal utilization of such re-sources as solar panels and wind turbines. Artificial Intelligence for Renewable Energy Systems focuses on using AI technology to advance green energy and its management. Starting with an overview of applying AI to renewable energy management, the book follows with such real-world examples: Predictive analytics for wind turbine maintenance Intelligent solar grid integration Vehicle-to-grid (V2G) technology for electric mobility Taking a multidisciplinary approach, the book is a guide for academics, energy practitioners, engineers, and policymakers who are leveraging the constructive collaboration between AI and renewable energy technologies.

The application of artificial intelligence (AI) to the management and development of renewable energy sources has revolutionized the energy sector by enhancing efficiency, reliability, and scalability. With the capability to analyze weather patterns, solar radiation, and wind speeds, AI-driven technologies help ensure optimal utilization of such re-sources as solar panels and wind turbines. Artificial Intelligence for Renewable Energy Systems focuses on using AI technology to advance green energy and its management. Starting with an overview of applying AI to renewable energy management, the book follows with such real-world examples: Predictive analytics for wind turbine maintenance Intelligent solar grid integration Vehicle-to-grid (V2G) technology for electric mobility Taking a multidisciplinary approach, the book is a guide for academics, energy practitioners, engineers, and policymakers who are leveraging the constructive collaboration between AI and renewable energy technologies.

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 (AI), Internet of Things (IoT) systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.This book systematically examines the application of advanced technologies including AI, machine learning, IoT, 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 modeling. 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 a comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.

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 (AI), Internet of Things (IoT) systems, and emerging digital technologies to address critical challenges in hydrology, hydraulics, water quality, and smart infrastructure development.This book systematically examines the application of advanced technologies including AI, machine learning, IoT, 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 modeling. 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 a comprehensive understanding and experienced practitioners looking to implement cutting-edge solutions for sustainable water system management.