Prasanth Aruchamy – författare

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

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.

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.

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.

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.

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.