IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. - Provides state-of-art methods and current trends in data analytics for the healthcare industry - Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques - Discusses several potential AI techniques developed using IoT for the healthcare industry - Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages

In the post-COVID-19 healthcare landscape, the demand for smart healthcare solutions and precision medicine systems has grown significantly. To address these challenges, the book AI and IoT-Based Technologies for Precision Medicine provides a comprehensive resource for doctors, researchers, engineers, and students. By leveraging AI and IoT technologies, the book equips healthcare professionals with advanced tools and methodologies for predictive disease analysis, informed decision-making, and other aspects of precision medicine. This resource bridges the gap between theory and practice, exploring concepts like machine learning, deep learning, computer vision, AI-integrated applications, IoT-based technologies, healthcare data analytics, and biotechnology applications. Through this, the book empowers healthcare practitioners to pioneer innovative solutions that enhance efficiency, accuracy, and security in medical practices. AI and IoT-Based Technologies for Precision Medicine not only offer insights into the potential of AI-powered applications and IoT-equipped techniques in smart healthcare but also foster collaboration among healthcare scholars and professionals. This authoritative guide encourages knowledge sharing and collaboration to harness the transformative potential of AI and IoT, leading to revolutionary advancements in medical practices and healthcare services. With this book as a guide, readers can navigate the evolving landscape of high-tech medicine, taking confident steps toward a cutting-edge and precise medical ecosystem.

The book, Transformation in Healthcare with Emerging Technologies, presents healthcare industrial revolution based on service aggregation and virtualisation that can transform the healthcare sector with the aid of technologies such as Artificial Intelligence (AI), Internet of Things (IoT), Bigdata and Blockchain. These technologies offer fast communication between doctors and patients, protected transactions, safe data storage and analysis, immutable data records, transparent data flow service, transaction validation process, and secure data exchanges between organizations. Features: • Discusses the Integration of AI, IoT, big data and blockchain in healthcare industry • Highlights the security and privacy aspect of AI, IoT, big data and blockchain in healthcare industry • Talks about challenges and issues of AI, IoT, big data and blockchain in healthcare industry • Includes several case studies It is primarily aimed at graduates and researchers in computer science and IT who are doing collaborative research with the medical industry. Industry professionals will also find it useful.

This book provides insights into IoT, its applications, and various implementation techniques. The authors first discuss the IoT design methodology to define the domain model. They then cover various connection methodologies used in IoT such as Ethernet, Wi-Fi, low powered wide area network (LPWAN), Bluetooth, RFID, cellular, and satellite, and more, along with their challenges. An example is made on the designing process using Arduino, which offers smart, connected, and secure elements; they also illustrate the integration of IoT with Blockchain, cloud, machine learning, big data, embedded software, sensors, etc. The book going on to cover the future of IoT in various sectors and how IoT will continue to be game-changing technology.

While ultra-high field strength diagnosis technologies and artificial intelligence have propelled medicine imaging towards microstructure analysis and precise medicine, persistent challenges remain. These range from long scanning times to motion sensitivity and issues with imaging quality for certain types of tissue. Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry summarizes emerging techniques, outlines clinical applications, and confronts the challenges head-on, proposing avenues for further research. It explores emerging techniques such as human-like robotics, medical Internet of Things (IoT), low-cost CT scanners, portable MRI devices, and breakthroughs in diagnosis technologies like zero echo time (ZTM) and compressed sensing volume interpolation breath-holding test sequences (CS-VIBE). This book provides an overview of the current state of medical imaging and clinical diagnosis applications, then expands into a roadmap for the future, envisioning the seamless integration of medical robotics and AI-assisted applications in the high-tech healthcare industry. As the influence of artificial intelligence continues to grow, the book serves as a clarion call for collaborative efforts, increased research, and unified strategies to navigate the challenges and harness the opportunities presented by the high-tech medical industry. This book is ideal for medical analysts, healthcare scientists, biotechnology analysts, scholars, researchers, academics, professionals, engineers, and students worldwide.

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: Covers a variety of deep learning architectures useful for computer vision tasks Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem Addresses the different issues and further research opportunities in computer vision and soft computing Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain Considers recent real word problems and the prospective solutions to these problems This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.

Tremendous growth in healthcare treatment techniques and methods has led to the emergence of numerous storage and communication problems and need for security among vendors and patients. This book brings together latest applications and state-of-the-art developments in healthcare sector using Blockchain technology. It explains how blockchain can enhance security, privacy, interoperability, and data accessibility including AI with blockchains, blockchains for medical imaging to supply chain management, and centralized management/clearing houses alongside DLT. Features: Includes theoretical concepts, empirical studies and detailed overview of various aspects related to development of healthcare applications from a reliable, trusted, and secure data transmission perspective. Provide insights on business applications of Blockchain, particularly in the healthcare sector. Explores how Blockchain can solve the transparency issues in the clinical research. Discusses AI with Blockchains, ranging from medical imaging to supply chain management. Reviews benchmark testing of AI with Blockchains and its impacts upon medical uses. This book aims at researchers and graduate students in healthcare information systems, computer and electrical engineering.

Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks.

The Industrial Internet of Things (IIoT) has become an effective tool with significant implications for industrialisation and Market Research (MR), especially in the field of green production. Green IIoT (GRIIoT) can be used to implement Green Production (GP) goals for the environment. The purpose of this study is to examine the drivers behind the adoption of GIIoT, MR, and industrialization decision-making, as well as the effects these drivers have on industrialization performance (IP). A structured questionnaire was used to gather information in order to evaluate the suggested study paradigm. The results indicate that institutional isomorphism influences the acceptance of GRIIoT in a favorable way. Furthermore, Green innovation (GI) activities that result in IP are favorably correlated with GIIoT. The potential effects of the various institutional isomorphisms discussed in this study can aid organizations in better understanding the responsibilities to protect and satisfying stakeholders, particularly as the adopt GIIoT to handle production problems and possible accordance pressures in the process.