This book is devoted to the issues faced by universities in the field of distance learning during and after covid as well as in digitalization times. The book devotes a lot of space to the issues of Web 3.0 in University e-learning, industry 4.0, artificial intelligence and digital equity. The aim and scope of this book is to draw a holistic picture of education before and after covid-19, the psychological effects of covid in education, using modern technologies application in education with taking into consideration sustainability development, industry 4.0 and society 5.0 aspects. The authors also raised the issue of artifical intelligence investigation in learner-instructor interaction. Highlights: To elaborate the functions of online education and numerous pedagogical strategies based on electronic learning to aid teachers and students with the tools required to succeed in the 21st century via engaging virtual experiences; To analyse tools provided by Ed-Tech firms and the effect of digital tools on maintaining the educational process in times of crisis and after pandemic; To create a roadmap for higher education institutions and provide tips regarding how to improve the effectiveness of the hybrid learning system; To understand e-learning characteristic in the era of industry 4.0 and society 5.0 and characteristics of the different web generations; And, using AI applications to improve connections and relationships between students and teachers and in education in the future. The book is both scientific and educational. It can be used at the university and by anyone interested in the topics it covers.

Electronic device usage has increased considerably in the past two decades. System configurations are continuously requiring upgrades; existing systems often become obsolete in a matter of 2–3 years. Green computing is the complete effective management of design, manufacture, use, and disposal, involving as little environmental impact as possible. This book intends to explore new and innovative ways of conserving energy, effective e-waste management, and renewable energy sources to harness and nurture a sustainable eco-friendly environment. This book: • Highlights innovative principles and practices using effective e-waste management and disposal • Explores artificial intelligence based sustainable models • Discovers alternative sources and mechanisms for minimizing environmental hazards • Highlights successful case studies in alternative sources of energy • Presents solid illustrations, mathematical equations, as well as practical in-the-field applications • Serves as a one-stop reference guide to stakeholders in the domain of green computing, e-waste management, renewable energy alternatives, green transformational leadership including theory concepts, practice and case studies • Explores cutting-edge technologies like internet of energy and artificial intelligence, especially the role of machine learning and deep learning in renewable energy and creating a sustainable ecosystem • Explores futuristic trends in renewable energy This book aims to address the increasing interest in reducing the environmental impact of energy as well as its further development and will act as a useful reference for engineers, architects, and technicians interested in and working with energy systems; scientists and engineers in developing countries; industries, manufacturers, inventors, universities, researchers, and interested consultants to explain the foundation to advanced concepts and research trends in the domain of renewable energy and sustainable computing. The content coverage of the book is organized in the form of 11 clear and thorough chapters providing a comprehensive view of the global renewable energy scenario, as well as how science and technology can play a vital role in renewable energy.

The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning, its challenges, assessment by students and their expectations, the use of tools to improve distance learning, and the functioning of e-learning in the industry 4.0 and society 5.0 eras. The book also devotes a lot of space to the issues of Web 3.0 in university e-learning, quality assurance, and knowledge management. The aim and scope of this book is to draw a holistic picture of ongoing online teaching-activities before and during the lockdown period and present the meaning and future of e-learning from students’ points of view, taking into consideration their attitudes and expectations as well as industry 4.0 and society 5.0 aspects. The book presents the approach to distance learning and how it has changed, especially during a pandemic that revolutionized education. It highlights • the function of online education and how that has changed before and during the pandemic. • how e-learning is beneficial in promoting digital citizenship. • distance learning characteristic in the era of industry 4.0 and society 5.0. • how the era of industry 4.0 treats distance learning as a desirable form of education. The book covers both scientific and educational aspects and can be useful for university-level undergraduate, postgraduate and research-grade courses and can be referred to by anyone interested in exploring the diverse aspects of distance learning.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems. Features: The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems Different use cases covered include smart health care, smart city, internet of drones, etc This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

Fully focused on addressing the missing connection between signal processing and ML. Provides one-stop guide reference for the readers. Oriented towards the material and flow with regard to general introduction, technical aspects. Comprehensively elaborates on the material with examples and.

Green Internet of Things (IoT) envisions the concept of reducing the energy consumption of IoT devices and making the environment safe. Considering this factor, this book focuses on both the theoretical and implementation aspects in green computing, next-generation networks or networks that can be utilized in providing green systems through IoT-enabling technologies, that is, the technology behind its architecture and building components. It also encompasses design concepts and related advanced computing in detail. * Highlights the elements and communication technologies in Green IoT * Discusses technologies, architecture and components surrounding Green IoT * Describes advanced computing technologies in terms of smart world, data centres and other related hardware for Green IoT * Elaborates energy-efficient Green IoT Design for real-time implementations * Covers pertinent applications in building smart cities, healthcare devices, efficient energy harvesting and so forth This short-form book is aimed at students, researchers in IoT, clean technologies, computer science and engineering cum Industry R&D researchers.

This book comprehensively covers sustainable blended learning approach in each of the STEM (science, technology, engineering and mathematics) disciplines. The book also includes the compilation of detailed concepts of blended learning ranging from definition, need, features, models, advantages and disadvantages and comparisons with traditional face-to-face learning. Sustainable blended learning in K-12 education has an immense role as foundation to learning for students in their early education. Fostering creativity and inculcating problem solving and critical thinking skills are the integral aspect of STEM education, which encourages students to pursue them to for their future careers. This book presents recent practices taken by experts at various levels to promote education in STEM. Furthermore, impact over teacher–student relationships is analyzed. Lastly, sustainable frameworks, strategies and implementation to incorporate students with additional needs are explored.

- The book will provide a foundation for researcher, scientists and educationists towards the application of advanced technologies such as IoT, AI and block chain in the area of Supply chain Management to track assets accurately and for upgrading supply chain business operations. - It will provide a multidimensional view for the masses ranging from computer science, food industry, hotel management, apparel, medical, inventory management and agriculture domain. It can be used as a reference book for higher education UG and PG students, as well as research scholars.

This book provides a clear insight about IoD and its requirements, protocols, performance improvement, evaluation methods and challenging aspects, to the readers at one place. The recent enhancement of integrating drone with the Internet of things (IoT) technology promises tremendous global development. The top applications of the Internet of Drones (IoD) are expected to be infrastructure & building monitoring, fire service systems, insurance investigations, retail fulfilment, agriculture and forensic evidence collections. Conventional drone technology is enhanced with the Internet and other emerging technologies such as cloud computing, big data, artificial intelligence and communication networks which open up for enormous opportunities like ahead for on-demand service-oriented and user-friendly IoD applications. This book presents extensive knowledge about the role of IoT and emerging technology in drone networks. It focuses on major research areas of the Internet of Drones and its related applications. It provides a strong knowledge platform towards the Internet of Drones for graduates, researchers, data scientists, educators and drone hobbyists.

The book presents recent trends and solutions to help healthcare sectors and medical staff protect themselves and others and limit the spread of the COVID-19. The book also presents the problems and challenges researchers and academics face in tackling this monumental task. Topics include: Unmanned Aerial Vehicle (UAV) or drones that can be used to detect infected people in different areas; robots used in fighting the COVID-19 by protecting workers and staff dealing with infected people; blockchain technology that secures sensitive transactions in strict confidentiality. With contributions from experts from around the world, this book aims to help those creating and honing technology to help with this global threat.

This book provides a clear insight about IoD and its requirements, protocols, performance improvement, evaluation methods and challenging aspects, to the readers at one place. The recent enhancement of integrating drone with the Internet of things (IoT) technology promises tremendous global development. The top applications of the Internet of Drones (IoD) are expected to be infrastructure & building monitoring, fire service systems, insurance investigations, retail fulfilment, agriculture and forensic evidence collections. Conventional drone technology is enhanced with the Internet and other emerging technologies such as cloud computing, big data, artificial intelligence and communication networks which open up for enormous opportunities like ahead for on-demand service-oriented and user-friendly IoD applications. This book presents extensive knowledge about the role of IoT and emerging technology in drone networks. It focuses on major research areas of the Internet of Drones and its related applications. It provides a strong knowledge platform towards the Internet of Drones for graduates, researchers, data scientists, educators and drone hobbyists.

The book presents recent trends and solutions to help healthcare sectors and medical staff protect themselves and others and limit the spread of the COVID-19. The book also presents the problems and challenges researchers and academics face in tackling this monumental task. Topics include: Unmanned Aerial Vehicle (UAV) or drones that can be used to detect infected people in different areas; robots used in fighting the COVID-19 by protecting workers and staff dealing with infected people; blockchain technology that secures sensitive transactions in strict confidentiality. With contributions from experts from around the world, this book aims to help those creating and honing technology to help with this global threat.

Comprehensive Guide to Heterogeneous Networks discusses the fundamental motivations behind this cutting-edge development, along with a brief discussion on the diverse definitions of HNs. The future of heterogeneous wireless networks (HWNs) is covered, including test cases, cost configuration, economic benefits and basic challenges. Other sections cover the topology management method in context of heterogeneous sensor nodes with diverse communication and sensing range. In addition, an outline of the pros and cons of the clustering criteria in HWSNs and taxonomy are summarized and provide futuristic research directions. Final sections discuss the future evolution of HNs and their implementations in diverse applications. This is an essential reference book for advanced students on courses in wireless communications, clinical engineering and networking. It will also be of interest to researchers, network planners, technical mangers and other professionals in these fields.

XAI Based Intelligent Systems for Society 5.0 focuses on the development and analysis of Explainable Artificial Intelligence (XAI)-based models and intelligent systems that can be utilized for Society 5.0—characterized by a knowledge intensive, data driven, and non-monetary society. The book delves into the issues of transparency, explainability, data fusion, and interpretability, which are significant for the development of a super smart society and are addressed through XAI-based models and techniques. XAI-based deep learning models, fuzzy and hybrid intelligent systems, expert systems, and intrinsic explainable models in the context of Society 5.0 are presented in detail.The book also addresses—using XAI-based intelligent techniques—the privacy issues intrinsic in storing huge amounts of data or information in virtual space. The concept of Responsible AI, which is at the core of the future direction of XAI for Society 5.0, is also explored in this book. Finally, the application areas of XAI, including relevant case studies, are presented in the concluding chapter. This book serves as a valuable resource for graduate/post graduate students, academicians, analysts, computer scientists, engineers, researchers, professionals, and other personnel working in the area of artificial intelligence, machine learning, and intelligent systems, who are interested in creating a people-centric smart society.

Cyber-Physical Systems (CPS) integrate computing and communication capabilities by monitoring and controlling the physical systems via embedded hardware and computers. This book brings together new and futuristic findings on IoT, Cyber Physical Systems and Robotics leading towards Automation and solving issues of various critical applications in Real-time. The book initially overviews the concepts of IoT, IIoT and Cyber Physical Systems followed by various critical applications and discusses the latest designs and developments that provide common solutions for the convergence of technologies. In addition, the book specifies methodologies, algorithms and other relevant architectures in various fields that include Automation, Robotics, Smart Agriculture and Industry 4.0. The book is intended for practitioners, enterprise representatives, scientists, students and Ph.D Scholars in hopes of steering research further towards cyber physical systems design and development and implementation across various domains. Additionally, this book can be used as a secondary reference, or rather one-stop guide, by professionals for real-life implementation of cyber physical systems. The book highlights: * A Critical Coverage of various domains: IoT, Cyber Physical Systems, Industry 4.0, Smart Automation and related critical applications. * Advanced elaborations for target audiences to understand the conceptual methodology and future directions of cyber physical systems and IoT. * An approach towards Research Orientations to enable researchers to point out areas and scope for implementation of Cyber Physical Systems in several domains for better productivity.

Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient's life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world. Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world. Key Features: Highlights the importance and applications of Swarm Intelligence and Evolutionary Algorithms in Healthcare industry. Elaborates Swarm Intelligence and Evolutionary Algorithms for Cancer Detection. In-depth coverage of computational methodologies, approaches and techniques based on Swarm Intelligence and Evolutionary Algorithms for detecting Brain Tumour including deep learning to optimize brain tumor diagnosis. Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms. Focuses on applying Swarm Intelligence and Evolutionary Algorithms for Heart Disease detection and diagnosis. Comprehensively covers the role of Swarm Intelligence and Evolutionary Algorithms for Drug Design and Discovery. The book will play a significant role for Researchers, Medical Practitioners, Healthcare Professionals and Industrial Healthcare Research and Development wings to conduct advanced research in Healthcare using Swarm Intelligence and Evolutionary Algorithms techniques.

With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges.  The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.

This book discovers what it will take to reindustrialize the previous industrial powerhouses in order to offset the advantages of cheap labor suppliers dominating the industrial sector by exploring the current situation of the production, processing, and manufacturing industries. The Internet of Things (IoT), Big Data, Cyber-Physical Systems (CPS), and Cloud Computing, Cyber Security, Cobotics, Automation, AI, 3D Printing and Additive Manufacturing, SDN, Blockchain technologies are outlined in this unique and comprehensive book, which has true potential for professionals, researchers, policymakers, and book users. New Horizons for Industry 4.0 in Modern Business encompass trends in business and technology globally that may completely alter how manufacturing and production are conducted. What you will discover: Learn about the Industrial Internet of Things and the Industrial Internet. Learn about the technologies that must develop to support Industry 4.0 and what is being done right now to make that happen. In this book, the topic of Industry 4.0 is covered in detail, and it even moves on to concepts of Digital Twins to boost output and create Industrial Internet of Things. With the development of new digital industrial technology, or "Industry 4.0," it is now feasible to collect and analyze data from many machines, resulting in processes that are quicker, more adaptable, and more efficient, producing things of higher quality while spending less money. The manufacturing revolution will boost productivity, alter economics, promote industrial development, and alter workforce demographics, ultimately altering the competitiveness of businesses and areas. Although advanced digital technology is being employed in manufacturing, Industry 4.0 will completely change how things are done. Greater production efficiencies will result, and conventional connections between suppliers, manufacturers, and consumers-as well as between people and machines-will shift. Industry 4.0 is changing the business process. This disruptive technology is radically changing the way businesses/manufacturing is conducted. It will give machines that little bit of intuition with the help of robotics, 3D printing, artificial intelligence, augmented reality, and virtual reality-that will help them do mindless and repetitive jobs without human intervention, allowing humans to focus more on their core competencies.

This book provides detail on applying Internet of Things (IoT) and Internet of Everything (IoE) in smart cities and their design aspects related to physical and network layer models. The authors explore the possibilities of utilizing communication technologies like multi-input multi-output (MIMO), narrow-band IoT (NB-IoT), ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC) for successful implementation of the IoT/IoE. The authors also address the development and advancement in cloud computing to support IoT and IoE. Research on the challenges and future predictions for efficiently implementing and exploring the benefits of smart cities are also explored. The book pertains to researchers, academics, and professionals in the field. Discusses the applicability of Internet of Things (IoT) and Internet of Everything (IoE) for smart cities; Addresses different protocols, networks, and technologies related to the implementation of IoT and IoE for smart cities; Provides a detailed overview on the physical and network layer design and signal processing algorithms related to IoT and IoE.

This book presents recent technologies that explore artificial intelligence (AI) and its scope in Internet of Things (IoT) enabled areas for productivity and the betterment of society. The book aims at targeting audiences of several disciplines to share research, suggest solutions, and future trends in the field of AI using IoT. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both aspects to give a holistic understanding of the AI paradigm for IoT. The book focuses on timely topics related to the field of AI enabled IoT applications at large. The book consists of four major parts: fundamentals, theoretical discussion, critical applications, and the learning algorithms. These contents shall include the basics, types, tools, and techniques of AI. Finally, applications of AI enabled IoT in several areas are presented including health, security, climate change, agricultural engineering, bioinformatics, biomedicine, smart applications, natural language processing, social and economic implications of AI enabled IoT, as well as robotics, sustainability, risk management, seismic data processing, smart grid management, text analysis, security, privacy, and ethics.

This book presents the Fifth International Conference on Safety and Security with IoT (SaSeIoT 2021), which took place online. The conference aims to explore not only IoT and its related critical applications but also IoT towards Security and Safety. The conference solicits original and inspiring research contributions from experts, researchers, designers, and practitioners in academia, industry and related fields and provides a common platform to share knowledge, experience and best practices in various domains of IoT.

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images.

This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physician's and doctor's medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system. Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas; Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer; Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.

This book provides detail on applying Internet of Things (IoT) and Internet of Everything (IoE) in smart cities and their design aspects related to physical and network layer models. The authors explore the possibilities of utilizing communication technologies like multi-input multi-output (MIMO), narrow-band IoT (NB-IoT), ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC) for successful implementation of the IoT/IoE. The authors also address the development and advancement in cloud computing to support IoT and IoE. Research on the challenges and future predictions for efficiently implementing and exploring the benefits of smart cities are also explored. The book pertains to researchers, academics, and professionals in the field. Discusses the applicability of Internet of Things (IoT) and Internet of Everything (IoE) for smart cities; Addresses different protocols, networks, and technologies related to the implementation of IoT and IoE for smart cities; Provides a detailed overview on the physical and network layer design and signal processing algorithms related to IoT and IoE.

This book presents recent technologies that explore artificial intelligence (AI) and its scope in Internet of Things (IoT) enabled areas for productivity and the betterment of society. The book aims at targeting audiences of several disciplines to share research, suggest solutions, and future trends in the field of AI using IoT. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both aspects to give a holistic understanding of the AI paradigm for IoT. The book focuses on timely topics related to the field of AI enabled IoT applications at large. The book consists of four major parts: fundamentals, theoretical discussion, critical applications, and the learning algorithms. These contents shall include the basics, types, tools, and techniques of AI. Finally, applications of AI enabled IoT in several areas are presented including health, security, climate change, agricultural engineering, bioinformatics, biomedicine, smart applications, natural language processing, social and economic implications of AI enabled IoT, as well as robotics, sustainability, risk management, seismic data processing, smart grid management, text analysis, security, privacy, and ethics.