A. Prasanth – författare

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.

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT.Key FeaturesExploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applicationsAddresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applicationsDescribes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problemsExplores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systemsFocuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systemsThis book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT.Key FeaturesExploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applicationsAddresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applicationsDescribes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problemsExplores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systemsFocuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systemsThis book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare presents an overview of the innovative concepts, technologies, and various biomedical applications of the Internet of Medical Things (IoMT).Features:• Provides insights into smart contracts, healthcare monitoring equipment, and the next generation of Internet of Things sensors to improve adherence to chronic disease management programs and patient health.• Discusses the IoMT for personalized healthcare, security, and privacy issues of the IoMT in the healthcare sector.• Elaborates on the opportunities and challenges of blockchain technology in the healthcare system.• Focuses on the convergence of the IoMT and blockchain for emerging personalized healthcare systems.• Presents techniques and methods to secure IoMT devices to protect them from cyberattacks.This book is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, biomedical engineering, and electrical engineering.

Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare presents an overview of the innovative concepts, technologies, and various biomedical applications of the Internet of Medical Things (IoMT).Features:• Provides insights into smart contracts, healthcare monitoring equipment, and the next generation of Internet of Things sensors to improve adherence to chronic disease management programs and patient health.• Discusses the IoMT for personalized healthcare, security, and privacy issues of the IoMT in the healthcare sector.• Elaborates on the opportunities and challenges of blockchain technology in the healthcare system.• Focuses on the convergence of the IoMT and blockchain for emerging personalized healthcare systems.• Presents techniques and methods to secure IoMT devices to protect them from cyberattacks.This book is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, biomedical engineering, and electrical engineering.

This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.

This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments. The book particularly:Focuses on the federated learning–based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applicationsDescribes the different optimization techniques of federated learning systems from a practical point of viewHighlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/ 6G communication, and computing standardsProvides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twinsOffers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issuesIt covers fundamental concepts, practical implementations, and trends, to serve as a reference resource for professionals and researchers in the field.

Transform the future of sustainable farming with this guide to mastering deep reinforcement learning architectures and algorithms that turn complex environmental data into precise, high-yield decisions for climate-smart agriculture. It conveys the importance of deep reinforcement learning and its technological advancements across climate-smart agriculture applications, addresses challenges related to privacy, security, and scalability of climatic and agricultural data, and explains reinforcement learning from AI and optimal control perspectives. The book explores advanced solutions such as meta learning, hierarchical learning, multi-agent learning, and imitation learning, emphasizing modern frameworks, algorithms, tools, and decision-making systems that support farmers through intelligent, data-driven applications. A machine learning method called reinforcement learning trains computers to make decisions that produce optimal outcomes by learning through trial and error. Applicable across robotics, autonomous vehicles, healthcare, finance, and agriculture, reinforcement learning plays a critical role in modern intelligent systems. This book provides a detailed analysis of climate-smart agriculture, examining farmers’ challenges, current technology-enabled systems, and deep reinforcement learning frameworks, algorithms, and architectures. It also addresses data privacy, security, and scalability issues in applications such as yield prediction, crop management, disease prediction, soil health monitoring, precision agriculture, and environmental monitoring.

Explore the future of logistics and disaster management with this essential guide to the design, applications, and challenges of integrating advanced drone technology into intelligent transportation systems. Drones are quickly becoming an essential technology for navigating inaccessible areas, especially during emergency situations. However, the implementation of these drones requires strict standards, policies, and procedures. Currently, drones are being used in several industrial and service sectors, extending the possibilities of handling transportation and logistics. The future of transportation is based on unmanned vehicles, and it is important to identify their challenges and futuristic applications. Drones for Transportation Logistics and Disaster Management introduces the essential aspects of the technological advancement of drones, the challenges faced in current practices, and their advanced applications. The book describes future intelligent and resilient transportation systems backed by the Internet of Vehicle Things, the problems of big data analytics, and optimization techniques for in-house supply-chain management. Using a global multi-sector perspective, this volume will comprehensively cover essential components of drone systems, including their modeling, design, and maintenance, making it an essential guide for anyone looking to the future of disaster management.