Rajesh Kumar Dhanaraj – författare

Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives�reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.

Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.

Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand

Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.- Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding- Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies- Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand

Blockchain-Based Systems for a Paradigm Shift in the Energy Grid explores the technologies and tools to utilize blockchain for energy grids and assists professionals and researchers to find alternative solutions for the future of the energy sector.

The focus of this globally edited book is on the application of blockchain technology and the balance between supply and demand for energy and where it is achievable. Looking at the integration of blockchain and how it will make the network resistant to any failure in sub-components, this book has very clearly explores the areas of energy sector that need in-depth study of Blockchain for expanding energy markets. Meeting the demands of energy by local trading, verifying use of green energy certificates and providing a greater understanding of smart energy grids and Blockchain use cases.

Exhaustively exploring the use of Blockchain for energy, this reference useful for all those in the energy industry looking to avoid disruption in the grid and sustain and control successful flow of electricity.

Methods and techniques of Blockchain-based trading and payments are included Provides process diagrams in techniques and balancing demand and supply Internet of Energy and its architecture for the future energy sector is explained

Blockchain-Based Systems for a Paradigm Shift in the Energy Grid explores the technologies and tools to utilize blockchain for energy grids and assists professionals and researchers to find alternative solutions for the future of the energy sector.The focus of this globally edited book is on the application of blockchain technology and the balance between supply and demand for energy and where it is achievable. Looking at the integration of blockchain and how it will make the network resistant to any failure in sub-components, this book has very clearly explores the areas of energy sector that need in-depth study of Blockchain for expanding energy markets. Meeting the demands of energy by local trading, verifying use of green energy certificates and providing a greater understanding of smart energy grids and Blockchain use cases.Exhaustively exploring the use of Blockchain for energy, this reference useful for all those in the energy industry looking to avoid disruption in the grid and sustain and control successful flow of electricity.- Methods and techniques of Blockchain-based trading and payments are included- Provides process diagrams in techniques and balancing demand and supply- Internet of Energy and its architecture for the future energy sector is explained

Digital Twin for Smart Manufacturing: Emerging Approaches and Applications provides detailed descriptions on how to integrate and optimize novel digital technologies for smart manufacturing. The book discusses digital twins, which combine the industrial internet of things, artificial intelligence, machine learning and software analytics with spatial network graphs to create living digital simulation models that update and change as their physical counterparts change. In addition, they provide an effective way to integrate technologies like cyber-physical systems into a smart manufacturing system, potentially optimizing the entire business process and operating procedure of the manufacturing firm.Drawing on the latest research, the book addresses the topics and technologies key to successful implementation of a smart manufacturing system, including augmented and virtual reality, big data and energy management. Broader subjects such as additive manufacturing and robotics are also covered in this context, covering every aspect of production.- Includes detailed case studies that show how digital twins have been successfully implemented- Shows how digital twins can be used to improve sustainability through superior energy usage management- Outlines potential future uses of the digital twin, thus pointing the way for future research directions

Digital Twin for Smart Manufacturing: Emerging Approaches and Applications provides detailed descriptions on how to integrate and optimize novel digital technologies for smart manufacturing. The book discusses digital twins, which combine the industrial internet of things, artificial intelligence, machine learning and software analytics with spatial network graphs to create living digital simulation models that update and change as their physical counterparts change. In addition, they provide an effective way to integrate technologies like cyber-physical systems into a smart manufacturing system, potentially optimizing the entire business process and operating procedure of the manufacturing firm.

Drawing on the latest research, the book addresses the topics and technologies key to successful implementation of a smart manufacturing system, including augmented and virtual reality, big data and energy management. Broader subjects such as additive manufacturing and robotics are also covered in this context, covering every aspect of production.

Includes detailed case studies that show how digital twins have been successfully implemented Shows how digital twins can be used to improve sustainability through superior energy usage management Outlines potential future uses of the digital twin, thus pointing the way for future research directions

Agri 4.0 and the Future of Cyber-Physical Agricultural Systems is the first book to explore the potential use of technology in agriculture with a focus on technologies that enable the reader to better comprehend the full range of CPS opportunities. From planning to distribution, CPS technologies are available to impact agricultural output, delivery, and consumption. Specific sections explore ways to implement CPS effectively and appropriately and cover digitalization of agriculture, digital computers to assist the processes of agriculture with digitized data and allied technologies, including AI, Computer Vision, Big data, Block chain, and IoT. Other sections cover Agri 4.0 and how it can digitalize, estimate, plan, predict, and produce the optimum agricultural inputs and outputs required for commercial purposes. The global team of authors also presents important insights into promising areas of precision agriculture, autonomous systems, smart farming environment, smart production monitoring, pest detection and recovery, sustainable industrial practices, and government policies in Agri 4.0.

Addresses one of the most complex applications of CPSDescribes various technologies, covering CPS in agriculture from precision agriculture to smart supply chain managementFocuses on the digital framework, tools, and systems capable of supporting Agri 4.0

Agri 4.0 and the Future of Cyber-Physical Agricultural Systems is the first book to explore the potential use of technology in agriculture with the focus on the technologies, enabling the reader to better comprehend the full range of CPS opportunities. From planning to distribution, CPS technologies are available to impact agricultural output, delivery and consumption. The impact for food security may be significant and this book explores ways to implement CPS effectively and appropriately.Technology, especially computing technology, can play a significant in the field of agriculture by processing digitized data to solve the complex agronomic, agricultural demand and supply issues that impact the food supply chain, and ultimately food security. In Agri 4.0, the cyber physical system synchronously interacts with agricultural systems to control and execute the operation autonomously. Digitalization of agriculture integrates digital computers to assist the processes of agriculture with its digitized data and its allied technology including AI, Computer Vision, Big data, Block chain and IoT. Agri 4.0 digitalizes, estimate, plan, predict, and produce the optimum agricultural inputs and outputs for the required for commercial purposes. It can be used to get a fair, transparent and accountable process to serve the stakeholders. The convergence of IoT, ML, Big data and 5G networks have opened new possibilities to explore and exploit the cyber physical agricultural systems. The management and practices of smart multi-layer architecture and smart supply chain are one of the key application areas in Agri 4.0.The global team of authors also presents important insights into promising areas of precision agriculture, autonomous systems, smart farming environment, smart production monitoring, pest detection and recovery, sustainable industrial practices and government policies in Agri 4.0.- Addresses one of the most complex applications of CPS- Describes various technologies, covering CPS in agriculture from precision agriculture to smart supply chain management- Focuses on the digital framework, tools, and systems capable of supporting Agri 4.0

Metaverse Technologies in Healthcare focuses on data analysis, utilizing the possibilities of data to increase the effectiveness of healthcare organizations. As healthcare services aim to maintain the physical, mental, social and emotional well-being of human lives while the Metaverse is a blend of technological trends- Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality (VR), collectively, they can deliver treatments and medicines, lower costs, and substantially enhance patient outcomes. The book redefines the digital health experience and describes the advantages of the Metaverse-based NFT technology in the healthcare sector, facilitating NFT avatars to interact with targeted audiences, and more.

Shows the potential of digital experiences on the healthcare sectorFocuses on the leading channels fueling the digital health space, such as Telemedicine, Digital Twins, Block chain, Internet of Things, and Robotics, providing new directions in this sectorProvides guidance to healthcare companies on how to augment their Digital Roadmaps with personalized care

Metaverse Technologies in Healthcare focuses on data analysis, utilizing the possibilities of data to increase the effectiveness of healthcare organizations. As healthcare services aim to maintain the physical, mental, social and emotional well-being of human lives while the Metaverse is a blend of technological trends- Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality (VR), collectively, they can deliver treatments and medicines, lower costs, and substantially enhance patient outcomes. The book redefines the digital health experience and describes the advantages of the Metaverse-based NFT technology in the healthcare sector, facilitating NFT avatars to interact with targeted audiences, and more.- Shows the potential of digital experiences on the healthcare sector- Focuses on the leading channels fueling the digital health space, such as Telemedicine, Digital Twins, Block chain, Internet of Things, and Robotics, providing new directions in this sector- Provides guidance to healthcare companies on how to augment their Digital Roadmaps with personalized care

Self-powered Sensors: A Path to Wearable Electronics features recent developments in chemical, photonic, pharmaceutical, microbiological, biomimetic, and bio-inspired approaches for MEMS/NEMS and medicinal self-powered sensors. Unconventional nanomaterial sensors driven by self-sufficient energy are given a contemporary review, with a focus on the categorization of energy sources and comparisons of research involving self-powered solar, piezoresistive, triboelectric, and thermodynamic technologies. This book also focuses on the different techniques, materials, comparisons of fabrication of self-powered sensors as well as thermoelectric self-powered sensors and its implantable applications.Presents state-of-the-art technologies and advancements in the design and application of self-powered sensorsExamines the advantages and disadvantages of self-powered nanomaterial sensors in terms of energy collecting techniques and sensing applicationsReviews the incorporation of self-operating devices and novel uses for neuromorphic sensors

Self-powered Sensors: A Path to Wearable Electronics features recent developments in chemical, photonic, pharmaceutical, microbiological, biomimetic, and bio-inspired approaches for MEMS/NEMS and medicinal self-powered sensors. Unconventional nanomaterial sensors driven by self-sufficient energy are given a contemporary review, with a focus on the categorization of energy sources and comparisons of research involving self-powered solar, piezoresistive, triboelectric, and thermodynamic technologies. This book also focuses on the different techniques, materials, comparisons of fabrication of self-powered sensors as well as thermoelectric self-powered sensors and its implantable applications.- Presents state-of-the-art technologies and advancements in the design and application of self-powered sensors- Examines the advantages and disadvantages of self-powered nanomaterial sensors in terms of energy collecting techniques and sensing applications- Reviews the incorporation of self-operating devices and novel uses for neuromorphic sensors

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable.Presents computational, intelligence-based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial managementDevelops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resourcesIncludes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable.- Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management- Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources- Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Future of Transportation Logistics and Disaster Management with Drones: Opportunities and Challenges discusses the important aspects and recent technological advancements of future drones, the challenges faced in current practices, and their advanced applications. It will take readers through essential components of drone systems such as methodologies, modeling, design, statistics, implementation, and maintenance. It explains the use of real-life technologies such as smart devices, virtual systems, IoT-based technologies, AI-centric solutions, smart sensors, and telecom networks to train and evaluate simple-to-complex models for building drone systems. This edited book provides all the relevant concepts, theoretical frameworks, emerging technologies, analytics techniques, and the latest empirical research findings in smart cities, transportation logistics, disaster management, smart devices, smart solutions, and more. It describes the future intelligent and resilient transportation systems backed with the Internet of Vehicle Things, the problems faced by Big Data Analytics, and their optimization techniques for inhouse supply-chain management. It also establishes a framework for handover management in the Internet of Drone-based networks. It raises and addresses the concerns surrounding the role of 5G communication for handling communication in drones, its related security, and legal aspects. The perspective of all stakeholders is discussed using case studies of existing applications at the global level, including industrial use cases. This book is a valuable reference for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, at the level of global communication, economy, education, and organizations as actors in drone systems. By the end of this book, readers will have the ability to design an end-to-end solution for Transportation Logistics and Disaster Management with the aid of smart drones.

Flexible electronics, or flex circuits, involve the construction of electrical circuits using flexible plastic substrates, such as polyimide, PEEK, or transparent conductive polyester sheets. Flexible electronic assemblies are made using a variety of manufacturing techniques, including printing, laminating, and deposition, which enables the circuit board to bend or take on a desired shape. They allow the user to create extremely flexible, light-weight, and thin electronic components such as batteries, screens, and sensors. Green Flexible Electronics for Sustainable Healthcare discusses incorporating flexible and printed electronics in the field of sustainable healthcare. It details how to utilise natural materials in the design, fabrication and application of flexible electronic-based wearables and sensors. It also offers a detailed analysis of the effects and challenges of integrating flexible electronics within the healthcare ecosystem. Green Flexible Electronics for Sustainable Healthcare considers the implications of the advances in flexible electronics with regards data privacy, security and scalability.Explores the role of advanced technologies, such as nanomaterials and artificial intelligence, in the creation of flexible and printed electronicsAnalyses the design of flexible electronics-based wearables and sensors and their application for healthcareAddresses the issues of data privacy, security and scalability when utilising flexible electronics within healthcare ecosystems

Flexible electronics, or flex circuits, involve the construction of electrical circuits using flexible plastic substrates, such as polyimide, PEEK, or transparent conductive polyester sheets. Flexible electronic assemblies are made using a variety of manufacturing techniques, including printing, laminating, and deposition, which enables the circuit board to bend or take on a desired shape. They allow the user to create extremely flexible, light-weight, and thin electronic components such as batteries, screens, and sensors. Green Flexible Electronics for Sustainable Healthcare discusses incorporating flexible and printed electronics in the field of sustainable healthcare. It details how to utilise natural materials in the design, fabrication and application of flexible electronic-based wearables and sensors. It also offers a detailed analysis of the effects and challenges of integrating flexible electronics within the healthcare ecosystem. Green Flexible Electronics for Sustainable Healthcare considers the implications of the advances in flexible electronics with regards data privacy, security and scalability. - Explores the role of advanced technologies, such as nanomaterials and artificial intelligence, in the creation of flexible and printed electronics- Analyses the design of flexible electronics-based wearables and sensors and their application for healthcare- Addresses the issues of data privacy, security and scalability when utilising flexible electronics within healthcare ecosystems

Future of Internet of Bio-nano Things in Personalized Healthcare: Applications and Challenges explores the core principles of nanomaterials and the sensing paradigms essential for medical devices based on nano-sensors technology, examining the latest theoretical and practical developments in Internet of Bio-nano Things (IoBNT) for health applications. This book explores how IoBNT facilitates the detection and treatment of diseases within the human body through communication between an in-body network of nanodevices and an external control unit. Readers will discover the transformative benefits of IoBNT, which integrates information and communication technologies with medical and nano-bio sensor devices to enhance patient care. The book highlights advances in telemedicine, including highly functional electronic medical devices like implantable and wearable devices engineered through nanotechnology. It details real-time case studies on smart drug delivery, edge computing, and personalized healthcare applications to provide valuable insights into optimizing network performance and utilization in personalized healthcare. The comprehensive exploration of machine learning algorithms and communication protocols further equips readers with the knowledge to design and implement end-to-end IoBNT solutions.Presents models based on edge computing, communication protocols, machine learning, smart drug delivery, disease detection mechanism, and bio-nano sensor-based applications, among othersIncludes wearable sensors, nano sensors and IoT applications that are enabling Internet of Bio-Nano Things system initiatives worldwideElaborates the different bio-computing techniques of intelligent systems from a practical point of view: solving common life problems

Future of Internet of Bio-nano Things in Personalized Healthcare: Applications and Challenges explores the core principles of nanomaterials and the sensing paradigms essential for medical devices based on nano-sensors technology, examining the latest theoretical and practical developments in Internet of Bio-nano Things (IoBNT) for health applications. This book explores how IoBNT facilitates the detection and treatment of diseases within the human body through communication between an in-body network of nanodevices and an external control unit. Readers will discover the transformative benefits of IoBNT, which integrates information and communication technologies with medical and nano-bio sensor devices to enhance patient care. The book highlights advances in telemedicine, including highly functional electronic medical devices like implantable and wearable devices engineered through nanotechnology. It details real-time case studies on smart drug delivery, edge computing, and personalized healthcare applications to provide valuable insights into optimizing network performance and utilization in personalized healthcare. The comprehensive exploration of machine learning algorithms and communication protocols further equips readers with the knowledge to design and implement end-to-end IoBNT solutions. - Presents models based on edge computing, communication protocols, machine learning, smart drug delivery, disease detection mechanism, and bio-nano sensor-based applications, among others- Includes wearable sensors, nano sensors and IoT applications that are enabling Internet of Bio-Nano Things system initiatives worldwide- Elaborates the different bio-computing techniques of intelligent systems from a practical point of view: solving common life problems

The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches. Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable. Case studies and other practical discussions exemplify these methods’ promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide.

Systematically covers knowledge graphs for automated driving processesIncludes real-life case studies, facilitating an understanding of current challengesAnalyzes the impact of various technological aspects related to automation across a range of transport modes, networks, and infrastructures

The global race to develop and deploy automated vehicles is still hindered by significant challenges, with the related complexities requiring multidisciplinary research approaches. Knowledge Graph-Based Methods for Automated Driving offers sought-after, specialized know-how for a wide range of readers both in academia and industry on the use of graphs as knowledge representation techniques which, compared to other relational models, provide a number of advantages for data-driven applications like automated driving tasks. The machine learning pipeline presented in this volume incorporates a variety of auxiliary information, including logic rules, ontology-informed workflows, simulation outcomes, differential equations, and human input, with the resulting operational framework being more reliable, secure, efficient as well as sustainable. Case studies and other practical discussions exemplify these methods'' promising and exciting prospects for the maturation of scalable solutions with potential to transform transport and logistics worldwide.- Systematically covers knowledge graphs for automated driving processes- Includes real-life case studies, facilitating an understanding of current challenges- Analyzes the impact of various technological aspects related to automation across a range of transport modes, networks, and infrastructures

Neuromorphic Computing for Brain Computer Interfaces: Enhanced Synergies in Mind and Machine examines practical situations where interpretability is crucial, going beyond theoretical considerations and providing case studies and examples to illustrate how Brain Computer Interfaces could be implemented in the real world. The book encompasses novel concepts, cutting-edge research, frameworks, and tools that facilitate comprehension of neuromorphic computing models. It is an ideal, comprehensive reference for professionals, researchers, and students who want to grasp the fundamental concepts and most recent developments in brain-computer interfaces (BCIs) and neuromorphic computing.Provides an in-depth study of the principles, technology, and applications that drive neuromorphic computing and brain-computer interfacesOffers an interdisciplinary approach that includes cognitive science, neuroscience, artificial intelligence, and biomedical engineeringPresents actionable insights and methodologies that can be applied to real-world challenges by presenting practical implementations and case studies

Emotional Artificial Intelligence: Practical Challenges and Applications explores the intersection of artificial intelligence and human emotions, challenging the myth that AI will replace humans. Instead, it emphasizes how emotional AI can enhance collaboration, improving efficiency across fields like healthcare, transportation, and space exploration. The book explores foundational theories such as Goleman’s emotional model and Ekman’s emotion theory, discussing methodologies for understanding human emotions through natural language processing and the ethical implications of AI in decision-making. It showcases real-world applications, from virtual nurses to emotion-aware driving systems, illustrating how these technologies can improve daily interactions and outcomes.This essential resource equips researchers, practitioners, and policymakers with practical insights for integrating emotional AI into diverse domains. By addressing the complexities of human emotion recognition and ethical frameworks, it provides a forward-looking perspective on enhancing collaboration between humans and AI, ultimately driving improved productivity and efficiency.Provides a thorough examination of emotional AI, integrating foundational theories and methodologies to help readers understand human emotions in the context of artificial intelligenceShowcases practical applications of emotional AI across various fields, including healthcare and transportation, demonstrating how these technologies improve daily interactions and outcomesAddresses the ethical implications of deploying emotional AIOffers a forward-looking perspective on emerging trends, equipping readers with insights to navigate the evolving landscape of human-centered artificial intelligence

Emotional Artificial Intelligence: Practical Challenges and Applications explores the intersection of artificial intelligence and human emotions, challenging the myth that AI will replace humans. Instead, it emphasizes how emotional AI can enhance collaboration, improving efficiency across fields like healthcare, transportation, and space exploration. The book explores foundational theories such as Goleman's emotional model and Ekman's emotion theory, discussing methodologies for understanding human emotions through natural language processing and the ethical implications of AI in decision-making. It showcases real-world applications, from virtual nurses to emotion-aware driving systems, illustrating how these technologies can improve daily interactions and outcomes.This essential resource equips researchers, practitioners, and policymakers with practical insights for integrating emotional AI into diverse domains. By addressing the complexities of human emotion recognition and ethical frameworks, it provides a forward-looking perspective on enhancing collaboration between humans and AI, ultimately driving improved productivity and efficiency. - Provides a thorough examination of emotional AI, integrating foundational theories and methodologies to help readers understand human emotions in the context of artificial intelligence- Showcases practical applications of emotional AI across various fields, including healthcare and transportation, demonstrating how these technologies improve daily interactions and outcomes- Addresses the ethical implications of deploying emotional AI- Offers a forward-looking perspective on emerging trends, equipping readers with insights to navigate the evolving landscape of human-centered artificial intelligence

Self-Learning AI in Healthcare: Agentic Systems for Smarter Medicine covers the transformative potential of advanced artificial intelligence within modern medicine. The book addresses the critical need for self-learning and agentic AI systems that autonomously adapt, refine decision-making, and navigate complex clinical environments with minimal intervention. Chapters provide foundational insights into the rise of self-learning AI and neural networks tailored for adaptive medical systems. Subsequent chapters delve into unsupervised, semi-supervised, and reinforcement learning for autonomous healthcare decision-making, alongside decentralized edge AI approaches. Specialized sections cover personalized medicine, hospital workflow optimization, remote patient monitoring, early disease detection, federated learning for privacy preservation, and more.Further, this book explores AI applications in drug discovery, mental health support, radiology, digital twins, and medical robotics, culminating with an examination of future challenges, ethics, and regulatory frameworks shaping self-learning AI’s trajectory in healthcare. It is tailored to serve a diverse yet specialized audience spanning academic, professional, and research sectors. Healthcare IT professionals and clinical informatics specialists will gain practical guidance for implementing adaptive AI solutions within complex healthcare environments. AI researchers and data scientists focused on developing self-learning models will find cutting-edge methodologies and case studies that advance medical applications.Enhances understanding of autonomous AI systems for improved diagnostic accuracy and personalized treatment optimization in healthcareProvides practical insights into integrating adaptive AI for streamlined hospital workflows and real-time patient monitoringAddresses ethical, regulatory, and privacy challenges critical to deploying AI in sensitive medical environmentsOffers interdisciplinary perspectives that benefit students, researchers, and healthcare professionals seeking advanced AI applicationsExplores cutting-edge AI techniques for accelerating drug discovery, rehabilitation, and autonomous medical robotics

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks.

Features:

Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven research

The targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks.

Features:

Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven research

The targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.

The book IoT and Big Data Analytics (IoT-BDA) for Smart Cities – A Global Perspective, emphasizes the challenges, architectural models, and intelligent frameworks with smart decisionmaking systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications. The text is a coordinated amalgamation of research contributions and industrial applications in the field of smart cities.

Features:

Provides the necessity of convergence of Big Data Analytics and IoT techniques in smart city application Challenges and Roles of IoT and Big Data in Smart City applications Provides Big Data-IoT intelligent smart systems in a global perspective Provides a predictive framework that can handle the traffic on abnormal days, such as weekends and festival holidays Gives various solutions and ideas for smart traffic development in smart cities Gives a brief idea of the available algorithms/techniques of Big Data and IoT and guides in developing a solution for smart city applications

This book is primarily aimed at IT professionals. Undergraduates, graduates, and researchers in the area of computer science and information technology will also find this book useful.

The book IoT and Big Data Analytics (IoT-BDA) for Smart Cities – A Global Perspective, emphasizes the challenges, architectural models, and intelligent frameworks with smart decisionmaking systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications. The text is a coordinated amalgamation of research contributions and industrial applications in the field of smart cities.

Features:

Provides the necessity of convergence of Big Data Analytics and IoT techniques in smart city application Challenges and Roles of IoT and Big Data in Smart City applications Provides Big Data-IoT intelligent smart systems in a global perspective Provides a predictive framework that can handle the traffic on abnormal days, such as weekends and festival holidays Gives various solutions and ideas for smart traffic development in smart cities Gives a brief idea of the available algorithms/techniques of Big Data and IoT and guides in developing a solution for smart city applications

This book is primarily aimed at IT professionals. Undergraduates, graduates, and researchers in the area of computer science and information technology will also find this book useful.