Saravanan Krishnan - Böcker

Handbook of Research on Blockchain Technology presents the latest information on the adaptation and implementation of Blockchain technologies in real world business, scientific, healthcare and biomedical applications. The book's editors present the rapid advancements in existing business models by applying Blockchain techniques. Novel architectural solutions in the deployment of Blockchain comprise the core aspects of this book. Several use cases with IoT, biomedical engineering, and smart cities are also incorporated. As Blockchain is a relatively new technology that exploits decentralized networks and is used in many sectors for reliable, cost-effective and rapid business transactions, this book is a welcomed addition on existing knowledge.

Financial services, retail, insurance, logistics, supply chain, public sectors and biomedical industries are now investing in Blockchain research and technologies for their business growth. Blockchain prevents double spending in financial transactions without the need of a trusted authority or central server. It is a decentralized ledger platform that facilitates verifiable transactions between parties in a secure and smart way.

Presents the evolution of blockchain, from fundamental theories, to present forms Explains the concepts of blockchain related to cloud/edge computing, smart healthcare, smart cities and Internet of Things (IoT) Provides complete coverage of the various tools, platforms and techniques used in blockchain Explores smart contract tools and consensus algorithms Covers a variety of applications with real world case studies in areas such as biomedical engineering, supply chain management, and tracking of goods and delivery

Focusing on different tools, platforms, and techniques, Blockchain and the Smart City: Infrastructure and Implementation uses case studies from around the world to examine blockchain deployment in diverse smart city applications. The book begins by examining the fundamental theories and concepts of blockchain. It looks at key smart cities' domains such as banking, insurance, healthcare, and supply chain management. It examines Using case studies for each domain, the book looks at payment mechanisms, fog/edge computing, green computing, and algorithms and consensus mechanisms for smart cities implementation. It looks at tools such as Hyperledger, Etherium, Corda, IBM Blockchain, Hydrachain, as well as policies and regulatory standards, applications, solutions, and methodologies. While exploring future blockchain ecosystems for smart and sustainable city life, the book concludes with the research challenges and opportunities academics, researchers, and companies in implementing blockchain applications. Independently organized chapters for greater readability, adaptability, and flexibility Examines numerous issues from multiple perspectives and academic and industry experts Explores both advances and challenges of cutting-edge technologies Coverage of security, trust, and privacy issues in smart cities

Green Blockchain Technology for Sustainable Smart Cities presents a detailed exploration of the adaptation and implementation of green blockchain technology for sustainable and eco-friendly smart city applications. This book covers all aspects of the topic and explores smart cities ecosystem applications of blockchain technology. Novel architectural and business blockchain use case solutions in smart city implementations are at the core of this book, which will be beneficial for all researchers, engineers, graduate students, smart city practitioners, and city administrators who are engaged in green blockchain and smart cities-related technologies. Covers a wide variety of topics Offers readers multiple perspectives from a variety of disciplines Written by an internationally diverse group of experts in their respective fields Includes a section on use cases as well as current challenges and future directions

Agriculture plays a vital role in a country’s growth. Modern-day technologies drive every domain toward smart systems. The use of traditional agricultural procedures to satisfy modern-day requirements is a challenging task. Cloud IoT Systems for Smart Agricultural Engineering provides substantial coverage of various challenges of the agriculture domain through modern technologies such as the Internet of Things (IoT), cloud computing, and many more.This book offers various state-of-the-art procedures to be deployed in a wide range of agricultural activities. The concepts are discussed with the necessary implementations and clear examples. Necessary illustrations are depicted in the chapters to ensure the effective delivery of the proposed concepts. It presents the rapid advancement of the technologies in the existing agricultural model by applying the cloud IoT techniques. A wide variety of novel architectural solutions are discussed in various chapters of this book.This book provides comprehensive coverage of the most essential topics, including: New approaches on urban and vertical farming Smart crop management for Indian farmers Smart livestock management Precision agriculture using geographical information systems Machine learning techniques combined with IoT for smart agriculture Effective use of drones in smart agricultureThis book provides solutions for the diverse domain of problems in agricultural engineering. It can be used at the basic and intermediary levels for agricultural science and engineering graduate students, researchers, and practitioners.

Agriculture plays a vital role in a country’s growth. Modern-day technologies drive every domain toward smart systems. The use of traditional agricultural procedures to satisfy modern-day requirements is a challenging task. Cloud IoT Systems for Smart Agricultural Engineering provides substantial coverage of various challenges of the agriculture domain through modern technologies such as the Internet of Things (IoT), cloud computing, and many more.This book offers various state-of-the-art procedures to be deployed in a wide range of agricultural activities. The concepts are discussed with the necessary implementations and clear examples. Necessary illustrations are depicted in the chapters to ensure the effective delivery of the proposed concepts. It presents the rapid advancement of the technologies in the existing agricultural model by applying the cloud IoT techniques. A wide variety of novel architectural solutions are discussed in various chapters of this book.This book provides comprehensive coverage of the most essential topics, including: New approaches on urban and vertical farming Smart crop management for Indian farmers Smart livestock management Precision agriculture using geographical information systems Machine learning techniques combined with IoT for smart agriculture Effective use of drones in smart agricultureThis book provides solutions for the diverse domain of problems in agricultural engineering. It can be used at the basic and intermediary levels for agricultural science and engineering graduate students, researchers, and practitioners.

This book covers different aspects of Internet of Drones (IoD) including fundamentals in drone design, deployment challenges, and development of applications. It starts with a detailed description of concepts and processes in designing an efficient system, and architecture. It details different applications of IoD and its implementations in smart cities, agriculture, health care, defense, security, logistics, GIS mapping, and so forth. Recent developments in IoD design, application of AI techniques, case studies, and future directions are covered.Features:Focuses on important perspectives of the Internet of Drones (IoD) Emphasizes drone deployment in smart cities, smart agriculture, smart health care, and 3D mappingCovers challenges in drone design for applications with security and privacy issuesReviews diversified drone applications with real-use cases from modern drone players ranging from start-up companies to big giants in the drone industryIncludes different aspects of drone design such as hardware and software architecture, potential applications, and opportunitiesThis book is aimed at researchers and professionals in computer sciences, electronics and communication engineering, and aeronautical engineering.

This book covers different aspects of Internet of Drones (IoD) including fundamentals in drone design, deployment challenges, and development of applications. It starts with a detailed description of concepts and processes in designing an efficient system, and architecture. It details different applications of IoD and its implementations in smart cities, agriculture, health care, defense, security, logistics, GIS mapping, and so forth. Recent developments in IoD design, application of AI techniques, case studies, and future directions are covered.Features:Focuses on important perspectives of the Internet of Drones (IoD) Emphasizes drone deployment in smart cities, smart agriculture, smart health care, and 3D mappingCovers challenges in drone design for applications with security and privacy issuesReviews diversified drone applications with real-use cases from modern drone players ranging from start-up companies to big giants in the drone industryIncludes different aspects of drone design such as hardware and software architecture, potential applications, and opportunitiesThis book is aimed at researchers and professionals in computer sciences, electronics and communication engineering, and aeronautical engineering.

Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.

Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.

Predictive Analysis in Smart Agricultureexplores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. The book also provides a case-oriented approach for IoT-based agricultural systems.This book deals with all aspects of smart agriculture with state-of-the-art predictive analysis in the complete 360-degree view spectrum. The book includes the concepts of urban and vertical farming using Agro IoT systems and renewable energy sources for modern agriculture trends. It discusses the real-world challenges, complexities in Agro IoT, and advantages of incorporating smart technology. It also presents the rapid advancement of the technologies in the existing Agri model by applying the various techniques. Novel architectural solutions in smart agricultural engineering are the core aspects of this book. Several predictive analysis tools and smart agriculture are also incorporated.This book can be used as a textbook for students in predictive analysis, agriculture engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in cloud computing, IoT, big data, machine learning, and deep learning working on smart agriculture applications.

Information and communication technology and the Internet of Things play key roles in smart city projects. It is challenging to handle the large amount of data generated by the different processes related to land use, the environment, the social and economic milieu, energy consumption, and transportation. This book emphasizes that green computing-based infrastructure initiatives benefit not only the environment but the enterprise as well.Green Computing for Sustainable Smart Cities: A Data Analytics Applications Perspective covers the need for smart green computing from various engineering disciplines and offers diversified applications for such computing with cases studies. The book highlights the sustainable development of smart cities using recent technology and emphasizes advances and cutting-edge techniques throughout. Focused on the different tools, platforms, and techniques associated with smart green computing, this book presents multiple perspectives from academia, industry, and research fields.The primary audience for this book includes academics, researchers, graduate students, smart city industry practitioners, and city administrators who are engaged in smart cities and related technology.

Information and communication technology and the Internet of Things play key roles in smart city projects. It is challenging to handle the large amount of data generated by the different processes related to land use, the environment, the social and economic milieu, energy consumption, and transportation. This book emphasizes that green computing-based infrastructure initiatives benefit not only the environment but the enterprise as well.Green Computing for Sustainable Smart Cities: A Data Analytics Applications Perspective covers the need for smart green computing from various engineering disciplines and offers diversified applications for such computing with cases studies. The book highlights the sustainable development of smart cities using recent technology and emphasizes advances and cutting-edge techniques throughout. Focused on the different tools, platforms, and techniques associated with smart green computing, this book presents multiple perspectives from academia, industry, and research fields.The primary audience for this book includes academics, researchers, graduate students, smart city industry practitioners, and city administrators who are engaged in smart cities and related technology.

Predictive Analysis in Smart Agricultureexplores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. The book also provides a case-oriented approach for IoT-based agricultural systems.This book deals with all aspects of smart agriculture with state-of-the-art predictive analysis in the complete 360-degree view spectrum. The book includes the concepts of urban and vertical farming using Agro IoT systems and renewable energy sources for modern agriculture trends. It discusses the real-world challenges, complexities in Agro IoT, and advantages of incorporating smart technology. It also presents the rapid advancement of the technologies in the existing Agri model by applying the various techniques. Novel architectural solutions in smart agricultural engineering are the core aspects of this book. Several predictive analysis tools and smart agriculture are also incorporated.This book can be used as a textbook for students in predictive analysis, agriculture engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in cloud computing, IoT, big data, machine learning, and deep learning working on smart agriculture applications.

Sustainable Development Goals (SDGs) are goals set by the United Nations to address the global challenges and foster sustainable development and harmony. To effectively achieve these goals, leveraging advanced technologies and engineering techniques is paramount. This edited volume explores the pivotal role of technology and engineering in advancing the SDGs across various sectors such as green energy, water management, healthcare, agriculture, and smart manufacturing. From innovative solutions in clean energy production to precision agriculture and smart cities, technological advancements offer scalable and efficient approaches to tackle complex sustainability issues.

A digital twin represents the indistinguishable digital counterpart of the physical object to simulate, monitor and test with real time synchronization. This book presents the framework and important key aspects of digital twins, including various technologies with coverage of the digital twins in various industry and business applications. It provides a background of modeling and simulation, computer sensor technology and other areas required creating the next wave of digital twins.Features:Presents exclusive material on industrial and business applications of digital twinsIncludes diversified digital twin applications with use casesFocuses on tools and methods for digital twins, platforms, application domains and industriesEmphasizes advances and cutting-edge technologies throughoutReviews artificial intelligence (AI), fog/edge computing, industrial automation, blockchains and the Internet of Things (IoT)This book is aimed at researchers and graduate students in cloud computing, simulation, the IoT and computer engineering.

Sustainable Development Goals or SDGs refer to the UN stipulated road-map for development in 17 defined areas, by 2030. It was built on the previously established Millennium Development Goals (MDG). This first volume (SDG-1) deals with eradicating poverty with the help of modern ICT technologies needed to end poverty and create a better society. This much needed book, which is the first of its type to offer a specific focus on the relationship between technology and the SDG-1 goal, will be valuable for all working in the subject of global sustainable development. Global organisations and representatives of governments targeting no poverty share knowledge on these ICT practices to eradicate poverty in all means.

This book discusses the concepts and processes of different livestock systems with the integration of smart technologies. The application of these technologies embedded in livestock systems will enrich the quality of mass production to satisfy the needs of the modern world.Smart Technologies for Sustainable Livestock Systems presents the framework and important key aspects of livestock systems. The authors first address eco-friendly livestock techniques and approaches by discussing the effective management of manure and greenhouse gas emissions that result from large-scale livestock operations. They also explore concepts such as livestock supply chain management using blockchain and livestock health monitoring through AI. Technologies such as smart sensors, mobile technology, wireless sensors, cloud computing, Internet of Things, fog/edge computing, automation, robotics and drones are discussed throughout the book. Throughout the book, and through real-world case studies, various sustainability issues that are paramount for ensuring the long-term viability of livestock production systems and achieving global food security and environmental sustainability goals are explored.The book is intended for engineers, computer scientists, and agricultural analysts working to improve the sustainability of livestock, through smart technologies, such as AI, the Internet of Things, and smart sensors.

Sustainable Development Goals (SDGs) give the UN a road-map for development, with Agenda 2030 as the target. It was built on the previously established Millennium Development Goals (MDGs). This book examines the supporting technologies needed to achieve SDG 2: reducing hunger and creating a better society. This much-needed book, the first of its type to offer a specific focus on the relationship between technology and SDG 2, will be valuable for academics working in the subject of global sustainable development. This book will also be useful for international organisations and representatives, who will be able to share knowledge on technological views to minimise hunger rates.

Sustainable Development Goals (SDGs) give the UN a road-map for development with Agenda 2030 as target. It was built on the previously established Millennium Development Goals (MDG). This book examines the supporting technologies needed to achieve the SDG 3 to ensure healthy lives and promote well-being for all at all ages. This much-needed book, which is the first of its type to offer a specific focus on the relationship between technology and the SDG 3, will be valuable for academicians working in the subject of global sustainable development. International organisations and representatives of national governments will be able to share knowledge on technological views to improve to health and wellbeing’s of human in all means.

This edited volume, Smart Technologies for Sustainable Development Goals: Quality Education, explores the transformative role of emerging technologies in advancing SDG 4—Quality Education. Through diverse chapters on AI, XR, gamification, adaptive learning, blockchain, and inclusive pedagogy, the book offers practical insights and research-based strategies for enhancing teaching, learning, and institutional excellence. It serves as a vital resource for educators, policymakers, and researchers striving to build resilient, equitable, and future-ready education systems.

Explores the role of emerging technologies in advancing SDG 5 – Gender Equality, a key pillar of the UN Agenda 2030. The book examines how artificial intelligence, big data, IoT, blockchain, and other smart technologies can bridge gender gaps and empower women across various sectors. Highlighting the role of technology to promote gender equality, this book will serve as a valuable resource for academics, policymakers, researchers, and international organizations working toward inclusive and equitable development. National governments, NGOs, and industry leaders will gain insights into technological innovations that can accelerate progress toward achieving SDG 5 and fostering a more gender-equitable future.

This volume explores the transformative potential of emerging technologies in achieving SDG 6 – Clean Water and Sanitation, a foundational goal of the UN Agenda 2030. This volume investigates how smart technologies— including artificial intelligence, the Internet of Things, big data analytics, blockchain, and remote sensing—are reshaping water resource management, sanitation systems, and wastewater treatment across diverse geographies. As one of the first comprehensive works to address the synergy between technological innovation and sustainable water solutions, this book is an essential resource for academics, researchers, engineers, and policy professionals. It offers practical insights for national and local governments, NGOs, and industry leaders aiming to implement inclusive, efficient, and climate-resilient water and sanitation infrastructure. By bridging global gaps in access to clean water, this work supports the collective mission toward universal health, environmental sustainability, and human dignity.Key Features:Focuses on SDG 6 and Smart TechnologiesExplains Multidisciplinary and Global PerspectivesReviews Case Studies and Real-World ApplicationsDiscusses Policy and Implementation GuidanceBridges Academia and PracticeSupports UN 2030 Agenda and Climate Resilience

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert’s knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert’s knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

The COVID-19 epidemic has helped to expand the function of the Internet of Medical Things in healthcare at an exponential rate. This book offers a comprehensive exploration of IoMT in the post-COVID-19 era, providing an overview of modern technologies used for the improvement of healthcare, such as IoT, artificial intelligence, robotics, big data, and wearable devices used in healthcare applications, with a focus on the detection and treatment of COVID-19 and related viruses. The volume presents the principles, state-of-the-art developments, architecture, real-world applications, actual case studies, results of IoMT experiments and sensor-based systems, and more. The chapters look at various aspects of artificial intelligence in IoMT-based telemedicine, health monitoring, early COVID detection, automatic intravenous fluids feeds, chest x-ray images, data collection for decision-making, security of health information, and more. This volume provides an understanding of the real applications, development of healthcare systems, architectural frameworks, and modern design elements of healthcare systems.

Large language models (LLMs) represent a profound breakthrough in artificial intelligence. More than just statistical tools, these vast neural networks undergo an intensive training process that unlocks unexpected, emergent abilities. Models like ChatGPT are now demonstrating a surprising grasp of reasoning, semantics, and real-world concepts, leading many researchers to ask: are we witnessing the first sparks of Artificial General Intelligence (AGI)?These models are doing more than just revolutionizing natural language processing; they are forcing us to reconsider the boundaries of machine intelligence. While their applications in chatbots, complex problem-solving, and content creation are already reshaping our digital world, their deeper implications point toward an entirely new era of AI.To understand these emergent capabilities and confront the AGI question, a deep dive into the core technology is essential. This co-authored book provides that crucial foundation. The authors explore the significance and capabilities of LLMs, alongside the immense ethical, social, and security challenges that arise as these models grow more powerful.For anyone seeking a comprehensive guide to navigate this new territory, The Power of Large Language Models and AI in the Digital Age: Technologies, applications, security and ethics is a valuable resource. It is essential reading for data scientists, researchers from academia and industry, lecturers, and advanced students in AI, computer science, and data science who will shape the future of intelligent systems.

This book stands out in the field due to its interdisciplinary approach, integrating cutting-edge computational methods with environmental sciences to offer practical solutions for sustainable development. One of the most important worldwide issues of our day is climate change, which calls for creative, data-driven, and scalable solutions. A thorough examination of how computational intelligence (CI) methods can be applied to different facets of climate change, from assessing its effects to developing mitigation and adaptation plans, can be found in the book. The chapters explain how these tools can be harnessed to tackle the complexities of climate change. The book contextualizes climate change as a data-rich problem, highlighting the challenges posed by its vast, heterogeneous, and dynamic datasets. The book also discusses about climate data analytics, which discusses the role of CI in managing and analyzing large-scale climate data collected from satellites, weather stations, and IoT devices. This book presents techniques for preprocessing, cleaning, and normalizing climate data to enhance its usability. This book details the use of computational intelligence for creating accurate climate models. This book explores techniques for predicting long-term trends, such as global warming and sea level rise, and short-term events like hurricanes and heatwaves. Case studies demonstrate how machine learning algorithms, such as random forests and support vector machines, have been used to refine predictive models. It presents vulnerability analysis frameworks that use CI to assess the susceptibility of regions, ecosystems, and communities to climate risks. The book discusses real-world applications, such as identifying drought-prone areas using neural networks or assessing flood risks using fuzzy logic systems. The book delves into the integration of CI with emerging technologies such as blockchain, quantum computing, and the Internet of Things (IoT) for more robust climate solutions.