Malathy Sathyamoorthy – författare

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

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

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

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

The book explores the critical challenge of securing sensitive medical data in the face of rising cyber threats. It examines how artificial intelligence can be leveraged to detect and mitigate cyber threats in healthcare environments. It integrates advanced technologies such as AI security applications, blockchain techniques, cryptanalysis, and 5G security to strengthen the protection of healthcare systems. By offering insights into the latest vulnerability assessment technologies and effective protection strategies, this book serves as an essential resource for professionals and researchers dedicated to enhancing cyber security in the healthcare industry.

The book explores the critical challenge of securing sensitive medical data in the face of rising cyber threats. It examines how artificial intelligence can be leveraged to detect and mitigate cyber threats in healthcare environments. It integrates advanced technologies such as AI security applications, blockchain techniques, cryptanalysis, and 5G security to strengthen the protection of healthcare systems. By offering insights into the latest vulnerability assessment technologies and effective protection strategies, this book serves as an essential resource for professionals and researchers dedicated to enhancing cyber security in the healthcare industry.

SMART GRIDS AND INTERNET OF THINGS Smart grids and the Internet of Things (IoT) are rapidly changing and complicated subjects that are constantly changing and developing. This new volume addresses the current state-of-the-art concepts and technologies associated with the technologies and covers new ideas and emerging novel technologies and processes. Internet of Things (IoT) is a self-organized network that consists of sensors, software, and devices. The data is exchanged among them with the help of the internet. Smart Grids (SG) is a collection of devices deployed in larger areas to perform continuous monitoring and analysis in that region. It is responsible for balancing the flow of energy between the servers and consumers. SG also takes care of the transmission and distribution power to the components involved. The tracking of the devices present in SG is achieved by the IoT framework. Thus, assimilating IoT and SG will lead to developing solutions for many real-time problems. This exciting new volume covers all of these technologies, including the basic concepts and the problems and solutions involved with the practical applications in the real world. Whether for the veteran engineer or scientist, the student, or a manager or other technician working in the field, this volume is a must-have for any library. Smart Grids and Internet of Things: Presents Internet of Things (IoT) and smart grid (SG)-integrated frameworks along with their components and technologiesCovers the challenges in energy harvesting and sustainable solutions for IoTSGs and their solutions for practical applicationsDescribes and demystifies the privacy and security issues while processing data in IoTSGIncludes case studies relating to IoTSG with cloud and fog computing machine learning and blockchain

This book is essential for anyone interested in understanding how smart agriculture, utilizing information and technology such as computer vision and deep learning, can revolutionize agriculture productivity, resolve ongoing concerns, and enhance economic and general effectiveness in farming. The need for a reliable food supply has driven the development of smart agriculture, which leverages technology to assist farmers, especially in remote areas. A key component is computer vision (CV) technology, which, combined with deep learning, can manage agricultural productivity and enhance automation systems for improved efficiency and cost-effectiveness. Automation in agriculture ensures benefits like reduced costs, high performance, and accuracy. Aerial imaging and high-throughput research enable effective crop monitoring and management. Computer vision and AI models aid in detecting plant health, impurities, and pests, supporting sustainable farming. This book explores using CV and AI to develop smart agriculture through deep learning, data mining, and intelligent applications.

Position yourself at the forefront of the transportation revolution with this guide to mastering computational intelligence that serves as the essential linchpin for the safe, sustainable, and hyper-connected Internet of Vehicular Things. The rapid adoption of the Internet of Things has transformed the way we interact with our environment, ushering in an era of unprecedented connectivity and data sharing. One of the most dynamic and influential manifestations of this technological revolution is the Internet of Vehicular Things, a paradigm that connects the digital and physical worlds through the integration of intelligent vehicles, smart infrastructure, and advanced communication networks. In this fast-evolving landscape, computational intelligence emerges as the linchpin that enables IoVT to realize its full potential. This book addresses the fascinating intersection of vehicle technology and computational intelligence. It explores the transformative power of algorithms, machine learning, artificial intelligence, and data analytics shaping the future of transportation. As vehicles become smarter, safer, and more efficient, the opportunities for innovation and optimization are limitless. The IoVT ecosystem encompasses a wide range of applications, from autonomous vehicles and traffic management systems to driver assistance technologies and predictive maintenance. By harnessing the collective intelligence of vehicles and infrastructures, IoVT promises to revolutionize not only our daily commute, but the broader transportation landscape, paving the way for sustainable, efficient, and safe mobility solutions. This book is a comprehensive guide for researchers, engineers, practitioners, and policymakers looking to navigate the complex terrain of IoVT using computational intelligence. It provides a multidisciplinary perspective and draws on recent advances in computer science, data science, electrical engineering, and transportation science to facilitate a deep understanding of the key concepts, challenges, and opportunities associated with IoVT and computational intelligence.

Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications gives invaluable insights into the ethical complexities of artificial intelligence, empowering the navigation of critical decisions that shape our future in an era where AI’s influence on society is rapidly expanding. The significant impact of artificial intelligence on society cannot be overstated in a time of lightning-fast technical development and growing integration of AI into our daily lives. A new frontier of human potential has emerged with the development and application of AI technologies, pushing the limits of what is possible in the areas of innovation and efficiency. AI systems are increasingly trusted with complicated decisions that affect our security, well-being, and the fundamental foundation of our societies as they develop in intelligence and autonomy. These choices have substantial repercussions for both individuals and communities in a wide range of fields, including healthcare, finance, criminal justice, and transportation. The necessity for moral direction and deliberate decision-making procedures is critical as AI systems develop and become more independent. Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications examines the complex relationship between artificial intelligence and the moral principles that guide its application. This book addresses fundamental concerns surrounding AI ethics, namely what moral standards ought to direct the creation and use of AI systems. In order to promote responsible AI development that is consistent with human values and goals, this book’s goal is to equip readers with the knowledge and skills they need to traverse the ethical landscape of AI decision-making.

Bridge the critical gap between AI transparency and security with this essential guide to the systematic defense frameworks and ethical strategies needed to protect explainable AI (XAI) systems from sophisticated adversarial attacks.In the artificial intelligence era, explainable AI (XAI) is an essential breakthrough that plays a vital role in unfolding complex AI model decisions and predictions. However, adversarial attacks can break XAI systems and create dangerous cyber threats. This book is a fundamental guide to the systematic framework and solutions surrounding XAI and its vulnerabilities. It presents strategies for detecting adversarial attacks and focuses on various attack scenarios and defense mechanisms essential in stimulating AI systems. The book will provide a systematic and detailed exploration of the complexity of adversarial attacks on XAI systems and propose theoretical concepts, methodological solutions, and essential tools for protecting the XAI systems against adversarial attacks. Thus, the presented book will provide insights for researchers, academicians, governments, industries, and stakeholders to fill the gap in understating the XAI theory and its real-time applications with possible solutions. It will also provide insights into the ethical considerations concerning XAI in inviting users to study and deliver moral behaviours. Lastly, it will represent the broader perspectives on XAI with its growth, applications, vulnerabilities, defence mechanisms, and ethical considerations. Moreover, the case studies are on real-life applications such as healthcare, environmental studies, finance sectors, legal systems, cybersecurity, educational studies, crewless vehicles, and industrial processes.

Networked Sensing Systems is essential for anyone seeking innovative and sustainable solutions across diverse sectors. It explores the integration of cutting-edge IoT technologies and digital transformation aimed at enhancing resource efficiency and addressing climate change challenges. With today’s advancements in wireless and mobile connectivity, Internet of Things (IoT) sensor technologies, and digital innovation, sustainability principles are increasingly reinforcing one another. To transition to more resource-efficient solutions, use resources responsibly, and streamline operations, businesses must embrace digital transformation. Potential application areas include energy management, air pollution monitoring, fleet management, water management, and agriculture. Simultaneously, the expansion of IoT deployments and their integration into the contexts of 5G and emerging 6G mobile networking necessitate that the solutions themselves be green and sustainable. This includes incorporating energy- and environmentally-conscious technical solutions for communications. By offering previously unattainable solutions, networked sensing can contribute to a more sustainable society by enabling the collection of data from heterogeneous sources in unique and novel ways. Additionally, the networking-based solutions themselves must be sustainable and environmentally friendly. For example, optimizing network architecture and relocating network equipment to strategic locations can significantly reduce energy waste. These goals drive the search for improved sensing technologies, emphasizing energy-efficient mobile sensing devices. The goal of Networked Sensing Systems is to present and highlight the latest developments in sustainable networked sensing systems across a variety of contexts, all united by the aim of enhancing human well-being and combating climate change. Regardless of the area of expertise, this work seeks to offer practical solutions to the major challenges of building a sustainable smart society 5.0. This book serves as a platform to discuss networked sensing systems for a sustainable society, focusing on systems and applications based on mobile computing and wireless networks, while adopting multidisciplinary approaches that emphasize the human element in addressing these challenges.

This book also covers key technologies and techniques such as AI, ML, and IoT in the development of smart agriculture and provides information on various types of smart farming technology, platforms, and machine learning algorithms with case studies based on real-time problems.