Vijender Kumar Solanki – författare

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding.

Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc.

Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach uses an innovative approach to explore how the Internet of Things (IoT) and big data can improve approaches, create efficiencies and make discoveries. Rapid growth of the IoT has encouraged many companies in the manufacturing sector to make use of this technology to unlock its potential. Pharmaceutical manufacturing companies are no exception to this, as IoT has the potential to revolutionize aspects of the pharmaceutical manufacturing process, from drug discovery to manufacturing.

Using clear, concise language and real world case studies, this book discusses systems level from both a human-factors point-of-view and the perspective of networking, databases, privacy and anti-spoofing. The wide variety of topics presented offers readers multiple perspectives on a how to integrate the Internet of Things into pharmaceutical manufacturing.

This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it''s the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation.

Features

This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it''s the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation.

Features

Internet of Things (IoT) has become a valuable tool for connection and information exchange between devices. This book provides a brief introduction to this new field, focuses on wearable medical devices, and covers the basic concepts by providing the reader with enough information to solve various practical problems.

This book provides the latest applications, experiments, fundamentals concepts, and cutting-edge topics for the ehealth and wearable devices field. The book also offers topics related to Security in IoT and Wearable Devices, Wearable Devices and Internet of Medical Devices (IoMT), IoT for Medical Applications, and Tools and study cases.

The book brings new and valuable information to PhD researchers, students, professors, and professionals working in IoT and related fields.

Internet of Things (IoT) has become a valuable tool for connection and information exchange between devices. This book provides a brief introduction to this new field, focuses on wearable medical devices, and covers the basic concepts by providing the reader with enough information to solve various practical problems.

This book provides the latest applications, experiments, fundamentals concepts, and cutting-edge topics for the ehealth and wearable devices field. The book also offers topics related to Security in IoT and Wearable Devices, Wearable Devices and Internet of Medical Devices (IoMT), IoT for Medical Applications, and Tools and study cases.

The book brings new and valuable information to PhD researchers, students, professors, and professionals working in IoT and related fields.

Industrial Internet of Things: Technologies, Design, and Applications addresses the complete functional framework workflow in IoT technology. It explores basic and high-level concepts, thus serving as a manual for those in the industry while also helping beginners. The book incorporates the working methodology of Industrial IoT works, is based on the latest technologies, and will cover the major challenges, issues, and advances while exploring data-based intelligent and automated systems and their implications to the real world. The book discusses data acquisition, security, learning, intelligent data analysis, and case studies related to Industrial IoT-based applications.

Industrial Internet of Things: Technologies, Design, and Applications addresses the complete functional framework workflow in IoT technology. It explores basic and high-level concepts, thus serving as a manual for those in the industry while also helping beginners. The book incorporates the working methodology of Industrial IoT works, is based on the latest technologies, and will cover the major challenges, issues, and advances while exploring data-based intelligent and automated systems and their implications to the real world. The book discusses data acquisition, security, learning, intelligent data analysis, and case studies related to Industrial IoT-based applications.

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems.

Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions.

This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems.

Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions.

This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

Industry 4.0, marked by the integration of cyber-physical systems, automation, and smart manufacturing, has greatly enhanced the intricacy and interconnectedness of industrial operations. Industrial Internet of Things (IIoT) systems allow for smooth communication and collaboration among machines, devices, and sensors, enabling real-time monitoring, data collection, and decision-making. As a result, this increased connectivity leaves IIoT networks vulnerable to a wider array of cyber threats, underscoring the need for more advanced security protocols.

Cognitive Security for Industrial IoT AI-Driven Approaches to Industry 4.0 examines cognitive security principles for IIoT environments, emphasizing artificial intelligence (AI) and machine learning (ML) in security measures. This book provides practical case studies and real-world examples while addressing the unique security challenges inherent in Industry 4.0 technologies. Key focus areas include predictive maintenance, proactive threat mitigation, behavioral analytics, emerging trends, and best practices for implementing cognitive security in industrial environments.

This comprehensive resource explores cutting-edge trends and future prospects in IIoT security, including quantum-resilient technologies and decentralized security frameworks. Readers will find step-by-step guidelines and proven best practices for implementing cognitive security in industrial settings. This practical approach equips both practitioners and organizations to effectively combat evolving cyber threats, making it an invaluable resource for staying ahead in cybersecurity''s rapidly changing landscape.

Industry 4.0, marked by the integration of cyber-physical systems, automation, and smart manufacturing, has greatly enhanced the intricacy and interconnectedness of industrial operations. Industrial Internet of Things (IIoT) systems allow for smooth communication and collaboration among machines, devices, and sensors, enabling real-time monitoring, data collection, and decision-making. As a result, this increased connectivity leaves IIoT networks vulnerable to a wider array of cyber threats, underscoring the need for more advanced security protocols.

Cognitive Security for Industrial IoT AI-Driven Approaches to Industry 4.0 examines cognitive security principles for IIoT environments, emphasizing artificial intelligence (AI) and machine learning (ML) in security measures. This book provides practical case studies and real-world examples while addressing the unique security challenges inherent in Industry 4.0 technologies. Key focus areas include predictive maintenance, proactive threat mitigation, behavioral analytics, emerging trends, and best practices for implementing cognitive security in industrial environments.

This comprehensive resource explores cutting-edge trends and future prospects in IIoT security, including quantum-resilient technologies and decentralized security frameworks. Readers will find step-by-step guidelines and proven best practices for implementing cognitive security in industrial settings. This practical approach equips both practitioners and organizations to effectively combat evolving cyber threats, making it an invaluable resource for staying ahead in cybersecurity''s rapidly changing landscape.

Written by a team of leading experts, it is the only book focusing on the broad areas of both the Internet of things and big data. The thirteen chapters present real-time experimental methods and theoretical explanations, as well as the implementation of these technologies through various applications.