Abhineet Anand – författare

Most events and activities in today's world are ordinarily captured using photos, videos and other multimedia content. Such content has some limitation of storing data and fetching them effectively. Three-dimensional continuous PC animation is the most proper media to simulate these occasions and activities. This book focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologies. The authors present recent advancements in multimedia systems as they relate to various application areas such as healthcare services and agriculture-related industries. The authors also discuss human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualization. They then go on to explore multimedia content adaptation for interoperable delivery. Finally, the book covers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia uses. This book is intended for computer engineers and computer scientists developing applications for multimedia and virtual reality and professionals working in object design and visualization, transformation, modelling and animation of the real world.Features:Focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologiesOffers opportunity for state-of-the-art approaches, methodologies and systems, and innovative use of multimedia-based emerging technology services in different application areasDiscusses human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualizationCovers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia usesExplores multimedia content adaptation for interoperable delivery and recent advancements in multimedia systems in context to various application areas such as healthcare services and agriculture-related fields

Most events and activities in today's world are ordinarily captured using photos, videos and other multimedia content. Such content has some limitation of storing data and fetching them effectively. Three-dimensional continuous PC animation is the most proper media to simulate these occasions and activities. This book focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologies. The authors present recent advancements in multimedia systems as they relate to various application areas such as healthcare services and agriculture-related industries. The authors also discuss human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualization. They then go on to explore multimedia content adaptation for interoperable delivery. Finally, the book covers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia uses. This book is intended for computer engineers and computer scientists developing applications for multimedia and virtual reality and professionals working in object design and visualization, transformation, modelling and animation of the real world.Features:Focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologiesOffers opportunity for state-of-the-art approaches, methodologies and systems, and innovative use of multimedia-based emerging technology services in different application areasDiscusses human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualizationCovers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia usesExplores multimedia content adaptation for interoperable delivery and recent advancements in multimedia systems in context to various application areas such as healthcare services and agriculture-related fields

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 resources as solar panels and wind turbines. They also enable precise forecasting of energy production. Additionally, AI-powered systems can facilitate real-time monitoring and predictive maintenance of renewable energy infrastructure to reduce downtime and operational costs. With AI, the renewable energy industry can overcome challenges, maximize output, and contribute significantly to global efforts in combating climate change.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 as:Predictive analytics for wind turbine maintenanceIntelligent solar grid integrationVehicle-to-grid (V2G) technology for electric mobilityIntelligent hydrogen fuel cell control.It also features global trend research, methods for data-driven forecasting, and policymaking based on advanced data analytics and visualization.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.

This edited volume presents a comprehensive exploration of modern techniques and methodologies for evaluating water quality and suitability. It bridges traditional experimental approaches with cutting-edge artificial intelligence and remote sensing tools, offering an innovative perspective on sustainable water resource management.It delves into multidisciplinary insights that combine environmental science, data analytics, and hydrological modeling. Key topics include experimental water quality analysis, GIS-based assessment, groundwater and surface water case studies, and AI applications in hydroinformatics. Readers will benefit from practical frameworks, real-world case studies, and research-driven solutions designed to address complex challenges in water suitability evaluation.This is an essential resource for researchers, academicians, environmental engineers, policymakers, and postgraduate students working in water resource management, environmental sustainability, and artificial intelligence applications. It serves as both a reference guide and an inspiration for professionals seeking to implement intelligent, data-driven, and sustainable approaches to water assessment and planning.

This edited volume presents a comprehensive exploration of modern techniques and methodologies for evaluating water quality and suitability. It bridges traditional experimental approaches with cutting-edge artificial intelligence and remote sensing tools, offering an innovative perspective on sustainable water resource management.It delves into multidisciplinary insights that combine environmental science, data analytics, and hydrological modeling. Key topics include experimental water quality analysis, GIS-based assessment, groundwater and surface water case studies, and AI applications in hydroinformatics. Readers will benefit from practical frameworks, real-world case studies, and research-driven solutions designed to address complex challenges in water suitability evaluation.This is an essential resource for researchers, academicians, environmental engineers, policymakers, and postgraduate students working in water resource management, environmental sustainability, and artificial intelligence applications. It serves as both a reference guide and an inspiration for professionals seeking to implement intelligent, data-driven, and sustainable approaches to water assessment and planning.

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.

This edited volume presents a comprehensive exploration of smart and sustainable water management, combining urban hydrology, digital innovation, cybersecurity, and climate resilience. It covers rainwater harvesting, stormwater control, wastewater management, wetlands, aquifer recharge, and field-based environmental investigations alongside advanced themes such as IoT-enabled monitoring, AI-driven predictive modelling, blockchain governance, homomorphic encryption, and SCADA security. Blending practical case studies with emerging technologies, the book offers a multidisciplinary resource that connects engineering, data science, policy, and environmental management within a single reference framework.The book integrates traditional water management practices with cutting-edge tools including smart sensors, machine learning, MNDWI-based impact assessment, bioimpedance water quality systems, and blockchain-enabled governance. Dedicated chapters address cybersecurity risks in water infrastructure and privacy-preserving IoT architectures. Real-world field studies from India provide applied insights, while predictive analytics and climate-resilient strategies support forward planning. Readers gain technical depth, implementation perspectives, and policy alignment guidance in one cohesive volume.This book is designed for environmental engineers, urban planners, water utility professionals, cybersecurity specialists, policymakers, researchers, and postgraduate students in civil engineering, data science, environmental studies, and smart infrastructure domains. It also supports smart city teams and sustainability practitioners seeking integrated digital water solutions.

This book is a comprehensive exploration of bio-inspired optimization techniques and their potential applications in healthcare. Bio-Inspired Optimization for Medical Data Mining is a groundbreaking book that delves into the convergence of nature’s ingenious algorithms and cutting-edge healthcare technology. Through a comprehensive exploration of state-of-the-art algorithms and practical case studies, readers gain unparalleled insights into optimizing medical data processing, enabling more precise diagnosis, optimizing treatment plans, and ultimately advancing the field of healthcare. Organized into 15 chapters, readers learn about the theoretical foundation of pragmatic implementation strategies and actionable advice. In addition, it addresses current developments in molecular subtyping and how they can enhance clinical care. By bridging the gap between cutting-edge technology and critical healthcare challenges, this book is a pivotal contribution, providing a roadmap for leveraging nature-inspired algorithms. In this book, the reader will discover Cutting-edge bio-inspired algorithms designed to optimize medical data processing, providing efficient and accurate solutions for complex healthcare challenges;How bio-inspired optimization can fine-tune diagnostic accuracy, leading to better patient outcomes and improved medical decision-making;How bio-inspired optimization propels healthcare into a new era, unlocking transformative solutions for medical data analysis;Practical insights and actionable advice on implementing bio-inspired optimization techniques and equipping effective real-world medical data scenarios;Compelling case studies illustrating how bio-inspired optimization has made a significant impact in the medical field, inspiring similar success stories. Audience This book is designed for a wide-ranging audience, including medical professionals, healthcare researchers, data scientists, and technology enthusiasts.

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.

This book provides in-depth explanations and discussions of the latest applications of Artificial Intelligence (AI), machine learning, and the Internet of Medicine, offering readers the cutting edge on this rapidly growing technology that has the potential to transform healthcare and improve patient outcomes. Over the past five years, there have been significant advances in healthcare through the use of artificial intelligence (AI) and machine learning (ML) technologies. AI and machine learning in medical imaging has significantly improved the accuracy and speed of medical imaging analysis, accelerated the drug discovery process by identifying potential drug targets and predicting the efficacy and safety of new drugs, and enabled personalized medicine by analyzing large amounts of patient data to identify individualized treatment plans based on a patient’s genetic makeup and medical history. Internet of Medicine (IoM) refers to the integration of the Internet of Things (IoT) and connected medical devices with healthcare systems and processes to enable remote monitoring, diagnosis, and treatment of patients. IoM is a subset of the larger Internet of Things concept, which involves the connection of everyday devices and appliances to the internet for various purposes. IoM has the potential to revolutionize healthcare by improving patient outcomes, reducing costs, and increasing efficiency. Some of the specific applications of IoM include remote patient monitoring, real-time data analysis, predictive analytics, smart hospitals, and personalized medicine.

The metaverse is becoming an increasingly popular space for a number of industries, including gaming, healthcare, education, and social media. As the use of this technology grows, so do concerns about data management and privacy. This book is a discussion and analysis of this technology and the methods needed to construct and improve distributed systems in the metaverse. It discusses the creation of large-scale algorithms and protocols aimed at furthering interactions in immersive virtual environments. Through a clear explanation of the dependence on more efficient, secure, and distributed systems to support the Metaverse, this book will discuss how data can be synchronized and securely stored across different platforms, allowing for real-time interconnectivity with relatively low delay in transfer. The book also takes a closer look at security and privacy concerns in distributed metaverse systems, including privacy -reserving methods, decentralized identity solutions, and sustainable methods of authentication. Providing case studies, simulation results, and real examples, this book offers a theoretical background with practical guidelines, enabling readers to face the problems and seize the potential of distributed systems in the metaverse.