Mohit Kumar – författare

Smart City Computational Paradigms: A Sustainable Approach describes the connections between state-of-the-art technologies while also providing a comprehensive overview for readers interested in advanced technologies. The smart city paradigm combines smart homes, smart healthcare, smart transportation, smart industry, smart environment, and smart energy to ensure sustainability, well-being, and comfortable living within the urban environment for the city's citizens. The book identifies challenges and proposed solutions and covers underlying theory, design techniques, classification, taxonomy, and analytical tools. Content primarily focuses on real-time applications, uncertainty solutions, and approaches with hands-on demonstrations for decision-making outcomes.This convergence of computational intelligence and IoT not only transforms data into actionable knowledge but also fosters the development of autonomous, efficient, and adaptive systems across diverse domains, ranging from smart cities to healthcare and industrial applications. The integration of computational intelligence with IoT enhances the capabilities of connected systems, making them smarter, more efficient, and better equipped to handle the complexities of the modern world.Explores the concept of the smart city, and explains how smart cities can improve sustainability, transport, and healthcareDemonstrates how computing paradigm technologies can be integrated with artificial intelligence and internet of thingsApplies inter-disciplinary themes and applications (AI, IoT, Blockchain, Decision Making, Computational Paradigm, Uncertainty) to sustainable smart citiesIncludes case studies of successful applications of the smart city computational paradigms

Harnessing Fiber-based Natural Biomaterials: For Tissue Engineering and Regeneration explores in detail the utilization of these materials in tissue engineering and regenerative medicine. The chapters cover fabrication techniques, scaffold design, cell interactions, and regenerative therapies along with their mechanical aspects. The book begins with an introduction to fundamental concepts, key challenges, and future opportunities for utilizing these materials in biomedical applications. Emphasis is placed on their characteristics and properties, fabrication strategies such as electrospinning, and 3D printing, as well as the source of biomaterials such as plant, animal, marine or microbial-derived biomaterials. A range of applications in tissue engineering and regenerative medicine are detailed, including bone, cartilage, skin, and nervous tissue. This book is a valuable reference for academic and industrial researchers, materials scientists and engineers, manufacturers, chemists, biomedical engineers, and those working in the research and development of natural-based scaffolds for tissue engineering and regenerative medicine.Presents recent developments in research on fiber-based natural biomaterials including both mechanical and biological aspects of scaffolds, for tissue engineering and regeneration and their fabrication strategiesDelves into practical aspects such as case studies, experimental protocols, and real-world examples, allowing readers to understand how to effectively utilize these fiber-based natural biomaterials in their own research or clinical practiceKey challenges and advances are discussed in detail as well as toxicological and regulatory aspects, and future aspects along with case studies

Sustainable Fiber-Based Hydrogel Composites: Multifunctional Solutions for Biomedical Challenges explores the intersection of natural fibers and hydrogel composites, addressing critical challenges in developing sustainable biomaterials for biomedical applications. Structured into seven key sections, the book outlines fabrication techniques, characterization, and multifunctional applications, along with case studies and future directions. Researchers will gain valuable insights into the mechanical and biological properties of fiber-reinforced hydrogel composites, promoting eco-friendly solutions without compromising functionality.This book will be of interest to researchers and academics in materials science, biomaterials, polymer science, composites science, and anyone with an interest in the development of sustainable biomaterials for biomedical applications.Examines natural fibers such as hemp, flax, and jute that are used in fiber-reinforced hydrogel composites for biomedical applicationsProvides detailed coverage of fabrication techniques and characterization methods for sustainable biomaterialsIncludes case studies that highlight practical applications and future trends in the field

This book offers a rigorous and forward-looking exploration of one of the most consequential frontiers in modern computation: the use of quantum mechanics to accelerate search, optimization, learning, simulation, and secure information processing. It begins by establishing the conceptual and mathematical foundations of quantum computation, including quantum gates, circuit design, quantum parallelism, and the distinctions between classical and quantum models of information processing. It then develops the algorithmic core of the field, examining how quantum principles can be systematically translated into high-impact procedures for searching structured and unstructured spaces, solving optimization problems, and achieving provable computational advantages under realistic hardware constraints.This book:Provides a comprehensive treatment of the broader quantum ecosystem.Covers quantum cryptography and post-quantum security, error correction and fault tolerance, programming frameworks and software stacks, hardware platforms, and the emerging interface between quantum computing and machine learning.Critically engages with real-world applications in finance, logistics, pharmaceuticals, climate science, cybersecurity, and materials discovery which demonstrate the transformative reach of technology.Engages with future trajectories, commercialization, ethics, governance, and global equity.Equips readers to understand both the power and the limits of quantum computation.Designed for researchers, advanced students, engineers, and technology strategists, this volume presents quantum computing not as an abstract scientific curiosity, but as a structured computational discipline grounded in qubits, unitary gates, circuit architectures, interference engineering, and algorithmic complexity. It is an essential reference for anyone seeking to navigate the technical depth, interdisciplinary scope, and strategic significance of quantum searching and optimization in the coming computational era.

Artificial Intelligence and Data Science in Healthcare Applications provides a thorough in-depth examination of how AI and data science are transforming predictive analytics and outlier detection in every industry. With in-depth examinations of machine learning, neural networks, NLP, and ethics of AI, this book prepares readers with both theoretical principles and practical tools to create smart, scalable systems. Real-world healthcare, cybersecurity, and finance case studies exemplify real world applications, and tutorials with leading libraries serve as a starting point for implementation.Features:Offers a broad overview of both foundational and advanced topics in artificial intelligence and data science, focusing particularly on their applications in prediction and detection.Addresses the ethical implications and social impact of artificial intelligence and data science, discussing topics such as algorithmic bias, privacy, and the ethical use of predictive technologies.Discusses enhanced deep learning model to detect lung diseases from Chest-Xray.Highlights lung cancer prediction using variational autoencoders and early stopping for neural network clustering and optimal tuning.Evaluates mental well-being through wearable sensors utilizing machine learning.It will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer engineering, information technology, and biomedical engineering.

CONVERGENCE of CLOUD with AI for BIG DATA ANALYTICS This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework. Audience Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.

The book offers cutting-edge insights into AI-driven optimization algorithms and their crucial role in enhancing real-time applications within fog and Edge IoT networks and addresses current challenges and future opportunities in this rapidly evolving field. This book focuses on artificial intelligence-induced adaptive optimization algorithms in fog and Edge IoT networks. Artificial intelligence, fog, and edge computing, together with IoT, are the next generation of paradigms offering services to people to improve existing services for real-time applications. Over the past few years, there has been rigorous growth in AI-based optimization algorithms and Edge and IoT paradigms. However, despite several applications and advancements, there are still some limitations and challenges to address including security, adaptive, complex, and heterogeneous IoT networks, protocols, intelligent offloading decisions, latency, energy consumption, service allocation, and network lifetime. This volume aims to encourage industry professionals to initiate a set of architectural strategies to solve open research computation challenges. The authors achieve this by defining and exploring emerging trends in advanced optimization algorithms, AI techniques, and fog and Edge technologies for IoT applications. Solutions are also proposed to reduce the latency of real-time applications and improve other quality of service parameters using adaptive optimization algorithms in fog and Edge paradigms. The book provides information on the full potential of IoT-based intelligent computing paradigms for the development of suitable conceptual and technological solutions using adaptive optimization techniques when faced with challenges. Additionally, it presents in-depth discussions in emerging interdisciplinary themes and applications reflecting the advancements in optimization algorithms and their usage in computing paradigms. Audience Researchers, industrial engineers, and graduate/post-graduate students in software engineering, computer science, electronic and electrical engineering, data analysts, and security professionals working in the fields of intelligent computing paradigms and similar areas.

Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow’s communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications.  The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network.This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed editedbook emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.

Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow’s communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications.  The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network.This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed editedbook emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.

"Dive deep into the evolving landscape of AI with 'Towards Ethical and Socially Responsible Explainable AI'. It offers invaluable insights into creating AI systems that not only perform effectively but also uphold ethical standards and foster trust.

This book provides current state of the art along with an insight of recent research trends and open issues, challenges, and future research direction for the academician, analyzer, researcher, writers, and authors.

This book explores emerging interdisciplinary themes and applications reflecting advancements in Computational Intelligence (CI) for IoT and 5G networks.