Hemant Kumar Saini – författare

This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems. This book:Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities. Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems. Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things. Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum. Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem.The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering.

This reference text presents industrial and real-case scenarios of the various businesses from the edge points to the interior manufacturing units where the data is smartly generated using the Internet of Things and processed. It further discusses topics such as virtual data security, protocols for next-generation transactions, the framework of Web 4.0, and the Internet of Things in cloud grids and eco-energy.This book:Discusses automatic segregated application of enhancing the sizing of sustainable eco-energy management in cloud gridsCovers intelligent blockchain-based Internet of Things framework for sustainable secure transportation, and resdesign of blockchain with Web 4.0 architectureIllustrates non-fungible token methods for the unique identification with blockchain, and principles of confidentiality in Internet of Things eco-energyExplains the scope of intelligent and secure channels in manufacturing and logistics business sectorsIncludes the practical implications of blockchain paradigms which drive the interoperability features in end-to-end mode that aids in reducing the energy in inter-data-driven businessIt is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics, and communication engineering, computer science and engineering, information technology, and business management.

This book begins by introducing digitization in sustainable development, discussing impacts on poverty, innovation, and infrastructure in the Age of Industry 4.0, and highlighting the development of interactive AI-powered environmental sustainability green models to reform the conservative business. It further covers important topics such as integration of AI technologies with digitization, green innovation, and ethical governance frameworks to build intelligent, inclusive, and eco-conscious business ecosystems, and smart energy management systems for developing green supply chains and smart cities with advancing sustainability.Key Features:Presents the role of digitization and AI technologies in enabling sustainable development across diverse sectors and business models in the Business 4.0 landscape.Highlights AI-powered innovations such as explainable AI, fuzzy logic systems, and intelligent manufacturing for sustainable infrastructure, consumer behavior, and business transformation.Explores how accessible digital tools and small-scale digitization empower green entrepreneurship, ESG integration, and inclusive economic growth, especially in emerging economies and micro-businesses.Demonstrates how AI can strengthen cybersecurity, optimize smart transportation systems, and support ecosystem preservation through IoT, robotics, and sustainable packaging.Addresses ethical, social, and policy considerations of AI in business sustainability and anticipates future developments toward Business 5.0.The text is primarily intended for graduate students, academic researchers, and industry professionals in fields such as computer science, business studies, information systems, digital transformation, and sustainability studies.

This book provides a comprehensive exploration of the security challenges and solutions with digital sustainability in the rapidly evolving digital landscape of digital forensics. It explores the details of protecting Internet of Medical Things (IoMT) environments, where the medical data, patient data, and machine data are at high risk with the digital experiences. The book seeks to provide researchers, medical practitioners, and IT specialists with important information. It aims to set the stage for a future in which security and efficiency in IoMT smoothly blend through real-world case studies. Key themes cover IoMT-specific forensic techniques, the difficulties of striking a balance between environmental responsibility and security, and creative solutions that combine the two viewpoints.

This book provides a comprehensive examination of artificial intelligence techniques that integrate heterogeneous healthcare data to support intelligent, secure, and sustainable healthcare systems. It presents both theoretical foundations and practical methodologies for multimodal data fusion, representation learning, and decision-making using medical images, bio signals, electronic health records, wearable sensors, text, and multimedia data.Features:Illustrates analyzing and integrating multiple modalities of healthcare data, such as medical images, electronic health records, bio signals, and genomic data.Emphasizes the role of multimedia intelligence in healthcare by leveraging advanced artificial intelligence techniques to analyze diverse data formats, including text, images, audio, and video.Presents practical applications that ensure secure healthcare data management and sustainable solutions, focusing on improving patient care and enhancing diagnostics.Covers the different security mechanisms applied in multimodal and multimedia-based healthcare applications.Showcases the role of advanced artificial intelligence and machine learning methods, including privacy-preserving technologies, blockchain, and explainable artificial intelligence tailored for secure healthcare.The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.

At the intersection of cutting-edge technology and environmental stewardship lies the transformative potential of 6G. This book examines the critical relationship between advanced energy-efficient hardware, intelligent infrastructure integration, and environmental conservation, exploring how ultra-fast communication technologies can revolutionize our approach to sustainability while delivering unprecedented connectivity.From augmented reality applications promoting sustainability to intelligent transport systems, green energy solutions, and environmental conservation support, this book presents real-world case studies that illuminate 6G's practical potential. In the emerging era of generative AI, readers will discover how these technologies can work in concert to address our most pressing ecological challenges while creating new opportunities for innovation and growth.This essential resource speaks to a diverse audience of technology professionals, environmental scientists, policy makers, and forward-thinking business leaders in the fields of communication technology, environmental science, and sustainable development.

Sustainable UAV Ecosystems: Integrating Blockchain, Quantum, and AI for Smart Mobility and SDG Innovation provides a comprehensive examination of technologies enabling secure, intelligent, and sustainable UAV ecosystems for smart mobility and digital infrastructure. It presents theoretical foundations and practical methodologies integrating artificial intelligence, blockchain, post-quantum cryptography and cloud-edge computing for resilient UAV communications. It not only explores predictive intelligence, adaptive routing, swarm intelligence and decentralized control in autonomous aerial networks but also highlights applications in smart-city logistics, disaster response, environmental monitoring and precision agriculture. Emphasis is placed on energy-efficient operations, low-carbon mobility and sustainable UAV systems aligned with Sustainable Development Goals (SDGs).Key Features:Illustrates the design and integration of secure and sustainable UAV ecosystems, including intelligent aerial networks, smart mobility infrastructures, and autonomous drone operations.Emphasizes the role of artificial intelligence and intelligent analytics in UAV systems by leveraging advanced techniques such as predictive intelligence, adaptive routing, and swarm intelligence for cooperative aerial operations.Presents practical applications of UAV technologies in smart-city logistics, disaster response, environmental monitoring, and precision agriculture to support efficient and sustainable services.Covers cybersecurity mechanisms and post-quantum cryptographic models for protecting UAV communications, aerial networks, and decentralized drone infrastructures.Showcases the integration of blockchain, distributed cloud–edge computing, and decentralized control frameworks to enable trustworthy, scalable, and resilient UAV ecosystems.This book is suitable for senior undergraduates, graduate students, and academic researchers in computer science, artificial intelligence, aerospace engineering, robotics, communication engineering, and smart mobility systems, as well as policymakers and industry practitioners working on sustainable UAV technologies and intelligent aerial infrastructures.

mso-bidi-language: AR-SA;">This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection.

This book provides a comprehensive exploration of medical robotics and data technologies, equipping readers with insights into how these cutting-edge innovations are transforming healthcare. It bridges the gap between technological advancements and real-world applications, offering a roadmap for integrating robotics, big data, and blockchain in modern medical systems. As healthcare systems worldwide face increasing pressure to enhance efficiency, accuracy, and accessibility, emerging technologies offer groundbreaking solutions. Medical robotics has revolutionized surgical procedures, diagnostics, and patient care, while big data analytics drives predictive healthcare models, personalized treatments, and operational efficiencies. Additionally, blockchain technology ensures secure, transparent, and tamper-proof data management, addressing critical challenges in medical records, patient privacy, and interoperability. This book examines these pivotal technologies and presents a new paradigm: the convergence of big data and blockchain to empower medical robotics, enhancing precision, security, and decision-making in healthcare.

This book provides a timely and much-needed examination of how Federated and Trustworthy Artificial Intelligence (AI) can address the real-time challenges posed by climate change on cyber-physical systems (CPS) and Internet of Things (IoT) infrastructures. With extreme weather events, energy shortages, agricultural disruptions, and urban vulnerabilities on the rise, there is an urgent demand for intelligent, distributed, and resilient solutions that can safeguard critical infrastructures while ensuring sustainability and trust. The central premise of this book is that traditional centralized AI is no longer sufficient. Centralized models face serious limitations: they consume vast energy resources, expose sensitive environmental and operational data, and often collapse under communication bottlenecks during crises. In contrast, federated learning enables distributed IoT devices and CPS nodes to collaboratively train models without sharing raw data, reducing latency, preserving privacy, and improving system adaptability. Coupled with trustworthy AI principles—explainability, fairness, robustness, and transparency—this approach becomes indispensable for climate-resilient operations. This book emphasizes real-time, high-impact applications where federated and trustworthy AI are urgently required: -Smart energy grids that must dynamically balance renewable sources under fluctuating demand and unpredictable climate patterns.-Precision agriculture where IoT-enabled drones and sensors monitor soil, water, and crops under changing rainfall and temperature conditions, ensuring food security.-Disaster management systems that coordinate distributed sensors and autonomous agents for early warning, evacuation, and recovery during floods, wildfires, or storms.-Sustainable transportation networks that adapt to heatwaves, fuel constraints, and emissions targets while ensuring public safety.-Water and waste management systems that require predictive, trustworthy decision-making to remain functional during droughts and pollution spikes.

This book is intended for a technical audience with advanced learning and in-depth analysis of the latest real-world developments in the field of quantum computing. The book is focused on modeling emerging drone-based applications. The methods of developing faster drive with the new trending technology of quantum genetic heuristics, artificial intelligence, and machine-based applications are discussed. Researchers will find novel ways to secure the data and Quantum drone networks. The book examines the most promising exploratory quantum-computed drone that optimizes, secures, and dynamically analyses various sectors, including healthcare, the educational industry, finance, transportation, and manufacturing.