Srikanta Kumar Mohapatra – 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.

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.

SIMULATION TECHNIQUES OF DIGITAL TWIN IN REAL-TIME APPLICATIONS The book gives a complete overview of implementing digital twin technology in real-time scenarios while emphasizing how this technology can be embedded with running technologies to solve all other issues. Divided into two parts with Part 1 focusing on simulated techniques in digital twin technology and Part 2 on real-time applications of digital twin technology, the book collects a significant number of important research articles from domain-specific experts. The book sheds light on the various techniques of digital twin technology that are implemented in various application areas. It emphasizes error findings and respective solutions before the actual event happens. Most of the features in the book are on the implementation of strategies in real-time applications. Various real-life experiences are taken to show the proper implementation of simulation technologies. The book shows how engineers of any technology can input their research ideas to convert to real scenarios by using replicas. Hence, the book has a collection of research articles from various engineers with expertise in different technologies from many regions of the world. It shows how to implement the embedded real-time data into technologies. Specifically, the chapters relate to the auto landing and cruising features in aerial vehicles, automated coal mining simulation strategy, the enhancement of workshop equipment, and implementation in power energy management for urban railways. This book also describes the coherent mechanism of digital twin technologies with deep neural networks and artificial intelligence. Audience Researchers, engineers, and students in computer science, software engineering and industrial engineering, will find this book to be very useful.

SIMULATION TECHNIQUES OF DIGITAL TWIN IN REAL-TIME APPLICATIONS

The book gives a complete overview of implementing digital twin technology in real-time scenarios while emphasizing how this technology can be embedded with running technologies to solve all other issues.

Divided into two parts with Part 1 focusing on simulated techniques in digital twin technology and Part 2 on real-time applications of digital twin technology, the book collects a significant number of important research articles from domain-specific experts. The book sheds light on the various techniques of digital twin technology that are implemented in various application areas. It emphasizes error findings and respective solutions before the actual event happens. Most of the features in the book are on the implementation of strategies in real-time applications. Various real-life experiences are taken to show the proper implementation of simulation technologies. The book shows how engineers of any technology can input their research ideas to convert to real scenarios by using replicas. Hence, the book has a collection of research articles from various engineers with expertise in different technologies from many regions of the world. It shows how to implement the embedded real-time data into technologies.

Specifically, the chapters relate to the auto landing and cruising features in aerial vehicles, automated coal mining simulation strategy, the enhancement of workshop equipment, and implementation in power energy management for urban railways. This book also describes the coherent mechanism of digital twin technologies with deep neural networks and artificial intelligence.

Audience

Researchers, engineers, and students in computer science, software engineering and industrial engineering, will find this book to be very useful.