Rutvij H. Jhaveri – författare

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

Volume 1 of Computational Approaches in Bioengineering—Computational Approaches in Biotechnology and Bioinformatics—explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores recent developments and applications in bioinformatics, biomechanics, artificial intelligence (AI), signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in disease diagnosis and treatment, the book will help readers understand how these technologies are being applied across the areas of biomedical engineering, bioinformatics, and healthcare. The chapters also include case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms. The contributors are all leading experts across multiple disciplines and provide chapters that truly represent a complete view of these state-of-the-art technologies.FEATURESCovers a wide range of subjects from biomedical engineering like wearable devices, biomaterials, synthetic biology, phytochemical extraction, and prostheticsExplores AI, machine learning, big data analysis, and algorithms in biomedical engineering and bioinformatics in an easily understandable formatIncludes case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithmsDiscusses genetic diagnosis, classification, and risk prediction in cancer using next-generation sequencing in oncologyThis book is ideally designed for biomedical professionals, biomedical engineers, healthcare professionals, data engineers, clinicians, physicians, medical students, hospital directors, clinical researchers, and others who work in the field of artificial intelligence, bioinformatics, and computational biology.

Volume 1 of Computational Approaches in Bioengineering—Computational Approaches in Biotechnology and Bioinformatics—explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores recent developments and applications in bioinformatics, biomechanics, artificial intelligence (AI), signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in disease diagnosis and treatment, the book will help readers understand how these technologies are being applied across the areas of biomedical engineering, bioinformatics, and healthcare. The chapters also include case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms. The contributors are all leading experts across multiple disciplines and provide chapters that truly represent a complete view of these state-of-the-art technologies.FEATURESCovers a wide range of subjects from biomedical engineering like wearable devices, biomaterials, synthetic biology, phytochemical extraction, and prostheticsExplores AI, machine learning, big data analysis, and algorithms in biomedical engineering and bioinformatics in an easily understandable formatIncludes case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithmsDiscusses genetic diagnosis, classification, and risk prediction in cancer using next-generation sequencing in oncologyThis book is ideally designed for biomedical professionals, biomedical engineers, healthcare professionals, data engineers, clinicians, physicians, medical students, hospital directors, clinical researchers, and others who work in the field of artificial intelligence, bioinformatics, and computational biology.

Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The book’s two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include:HPC use cases, application programming interfaces (APIs), and applicationsParallelization techniquesHPC for machine learningImplementation of parallel computing with AI in big data analyticsHPC with AI in healthcare systemsAI in industrial automationCoverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book’s discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI.

Computational Approaches in Bioengineering, Volume 2—Computational Approaches in Biomaterials and Biomedical Engineering Applications is a comprehensive and up-to-date resource that provides a broad overview of the use of computational methods in the fields of biomaterials and biomedical engineering. Written by a team of experts in the field of biomaterials and biomedical engineering, it provides a wealth of information on the use of computational methods in these fields. Furthermore, it explores emerging trends and discusses future directions and associated limitations in the field. Through thorough exploration and explanation, it showcases the latest research and advancements, offering valuable insights into how computational methods are utilized to design and optimize biomaterials, simulate biological processes, and develop innovative medical devices.FEATURESProvides practical guidance and real-world examples to help readers apply computational approaches effectively in their workExplores the diverse computational approaches employed in biomaterials and biomedical engineering applications, offering a comprehensive view of the fieldIntroduces emerging topics and cutting-edge techniques, keeping wide range of readers at the forefront of advancements in computational bioengineeringDiscusses the integration of computational methods in biomaterials and biomedical engineering, fostering a deeper understanding of their synergistic potentialProvides a valuable resource for researchers, practitioners, and students alike, serving as a comprehensive guide to computational approaches in biomaterials and biomedical engineering applicationsThe book is well-organized and easy to read. The chapters are written in a clear and concise style, and they provide a comprehensive overview of the topics covered. The book is also well-illustrated with figures and tables that help to explain the concepts discussed in the text. With its comprehensive coverage, practical examples, and expert insights, this book serves as a valuable resource for researchers, students, and professionals in the fields of biomaterials and biomedical engineering.

Computational Approaches in Bioengineering, Volume 2—Computational Approaches in Biomaterials and Biomedical Engineering Applications is a comprehensive and up-to-date resource that provides a broad overview of the use of computational methods in the fields of biomaterials and biomedical engineering. Written by a team of experts in the field of biomaterials and biomedical engineering, it provides a wealth of information on the use of computational methods in these fields. Furthermore, it explores emerging trends and discusses future directions and associated limitations in the field. Through thorough exploration and explanation, it showcases the latest research and advancements, offering valuable insights into how computational methods are utilized to design and optimize biomaterials, simulate biological processes, and develop innovative medical devices.FEATURESProvides practical guidance and real-world examples to help readers apply computational approaches effectively in their workExplores the diverse computational approaches employed in biomaterials and biomedical engineering applications, offering a comprehensive view of the fieldIntroduces emerging topics and cutting-edge techniques, keeping wide range of readers at the forefront of advancements in computational bioengineeringDiscusses the integration of computational methods in biomaterials and biomedical engineering, fostering a deeper understanding of their synergistic potentialProvides a valuable resource for researchers, practitioners, and students alike, serving as a comprehensive guide to computational approaches in biomaterials and biomedical engineering applicationsThe book is well-organized and easy to read. The chapters are written in a clear and concise style, and they provide a comprehensive overview of the topics covered. The book is also well-illustrated with figures and tables that help to explain the concepts discussed in the text. With its comprehensive coverage, practical examples, and expert insights, this book serves as a valuable resource for researchers, students, and professionals in the fields of biomaterials and biomedical engineering.

Computational Approaches in Biomedical Engineering is a two-volume set that explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores the recent developments and applications in bioinformatics, biomechanics, AI, signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms.This book is divided into two volumes, Volume 1: Computational Approaches in Biotechnology and Bioinformatics; Volume 2: Computational Approaches in Biomaterials and Biomedical Engineering Applications. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in the decision for disease diagnosis and treatment, this set will help readers get an insight into understanding how these technologies are being applied across areas of biomedical engineering, bioinformatics, and healthcare. The chapters also include case studies on the role of medical robots in surgery, and the determination of protein structure using genetic algorithms. The contributors are all leading experts across multiple disciplines and provide chapters that truly represent a complete view of these state-of-the-art technologies.This set is ideally designed for biomedical professionals, biomedical engineers, healthcare professionals, data engineers, clinicians, physicians, medical students, hospital directors, clinical researchers, and those who work in the fields of artificial intelligence, bioinformatics, and computational biology.

Predictive Methods in Next-Generation Computing is essential for anyone looking to understand how next-generation computing technologies are driving predictive models to create smarter, safer, and more sustainable solutions across diverse fields. Computing technologies are significantly evolving in all sectors, aiming to provide an automated, energy-efficient solution for various real-world problems with an advanced predictive model. This book explores computing technologies in various domains and provides novel strategies and designs for a smart, secure, and sustained environment for the future. Predictive Methods in Next-Generation Computing provides a realistic overview of various computer technologies that have made drastic advances in the field of smart applications, resulting in smart agriculture, healthcare, traffic management, and sustainability. The book comprehensively covers predictive models using artificial intelligence, machine learning, and Internet of Things and considers these applications for various smart applications to create a safe, smart environment for everyone. The chapters include real-world case studies, giving readers a glimpse into the benefits of integrating technology into predictive analytics to make the practice more automated, energy-efficient, safe, and profitable.