Gopal Chaudhary - Böcker

Most of the business sectors consider the Digital Twin concept as the next big thing in the industry. A current state analysis of their digital counterparts helps in the prediction of the future of physical assets. Organizations obtain better insights on their product performance through the implementation of Digital Twins, and the applications of the technology are frequently in sectors such as manufacturing, automobile, retail, health care, smart cities, industrial IoT, etc. This book explores the latest developments and covers the significant challenges, issues, and advances in Digital Twin Technology. It will be an essential resource for anybody involved in related industries, as well as anybody interested in learning more about this nascent technology.This book includes:The future, present, and past of Digital Twin Technology. Digital twin technologies across the Internet of Drones, which developed various perceptive and autonomous capabilities, towards different control strategies such as object detection, navigation, security, collision avoidance, and backup. These approaches help to deal with the expansive growth of big data solutions. The recent digital twin concept in agriculture, which offers the vertical framing by IoT installation development to enhance the problematic food supply situation. It also allows for significant energy savings practices. It is highly required to overcome those challenges in developing advanced imaging methods of disease detection & prediction to achieve more accuracy in large land areas of crops.The welfare of upcoming archetypes such as digitalization in forensic analysis. The ideas of digital twin have arisen to style the corporeal entity and associated facts reachable software and customers over digital platforms.Wind catchers as earth building: Digital Twins vs. green sustainable architecture.

Most of the business sectors consider the Digital Twin concept as the next big thing in the industry. A current state analysis of their digital counterparts helps in the prediction of the future of physical assets. Organizations obtain better insights on their product performance through the implementation of Digital Twins, and the applications of the technology are frequently in sectors such as manufacturing, automobile, retail, health care, smart cities, industrial IoT, etc. This book explores the latest developments and covers the significant challenges, issues, and advances in Digital Twin Technology. It will be an essential resource for anybody involved in related industries, as well as anybody interested in learning more about this nascent technology.This book includes:The future, present, and past of Digital Twin Technology. Digital twin technologies across the Internet of Drones, which developed various perceptive and autonomous capabilities, towards different control strategies such as object detection, navigation, security, collision avoidance, and backup. These approaches help to deal with the expansive growth of big data solutions. The recent digital twin concept in agriculture, which offers the vertical framing by IoT installation development to enhance the problematic food supply situation. It also allows for significant energy savings practices. It is highly required to overcome those challenges in developing advanced imaging methods of disease detection & prediction to achieve more accuracy in large land areas of crops.The welfare of upcoming archetypes such as digitalization in forensic analysis. The ideas of digital twin have arisen to style the corporeal entity and associated facts reachable software and customers over digital platforms.Wind catchers as earth building: Digital Twins vs. green sustainable architecture.

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human–computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies.Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human–computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies.Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

Focusing on the challenges, directions, and future predictions with the role of 5G in smart healthcare monitoring, this book offers the fundamental concepts and analyses on the methods to apply Internet of Things (IoT) in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their patients' healthcare experience.Smart Healthcare Monitoring Using IoT with 5G: Challenges, Directions, and Future Predictions illustrates user-focused wearable devices such as Fitbit health monitors and smartwatches by which consumers can self-manage and self-monitor their own health. The book covers new points of security and privacy concerns, with the expectation of IoT devices gaining more popularity within the next ten years. Case studies depicting applications and best practices as well as future predictions of smart healthcare monitoring by way of a 5G network are also included.Interested readers of this book include anyone working or involved in research in the field of smart healthcare, such as healthcare specialists, computer science engineers, electronics engineers, and pharmaceutical practitioners.

Focusing on the challenges, directions, and future predictions with the role of 5G in smart healthcare monitoring, this book offers the fundamental concepts and analyses on the methods to apply Internet of Things (IoT) in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their patients' healthcare experience.Smart Healthcare Monitoring Using IoT with 5G: Challenges, Directions, and Future Predictions illustrates user-focused wearable devices such as Fitbit health monitors and smartwatches by which consumers can self-manage and self-monitor their own health. The book covers new points of security and privacy concerns, with the expectation of IoT devices gaining more popularity within the next ten years. Case studies depicting applications and best practices as well as future predictions of smart healthcare monitoring by way of a 5G network are also included.Interested readers of this book include anyone working or involved in research in the field of smart healthcare, such as healthcare specialists, computer science engineers, electronics engineers, and pharmaceutical practitioners.

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more.  The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields.Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures;Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more.  The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields.Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures;Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

This book gathers the best papers presented at the International Conference on Data Sciences, Security and Applications (ICDSSA 2019), organized by Bharati Vidyapeeth’s College of Engineering, New Delhi, India, on 7–8 March 2019.