Vishnu Sharma – författare

The Internet of Things (IoT) and blockchain are two new technologies that combine elements in many ways. A system where the virtual and physical worlds interact is created by integrating pervasive computing, ubiquitous computing, communication technologies, sensing technologies, Internet Protocol, and embedded devices. A massive number of linked devices and vast amounts of data present new prospects for developing services that can directly benefit the economy, environment, society, and individual residents. Due to the size of IoT and insufficient data security, security breaches may have a huge impact and negative effects. IoT not only connects gadgets but also people and other entities, leaving every IoT component open to a wide variety of assaults. The implementation and application of IoT and blockchain technology in actual scientific, biomedical, and data applications are covered in this book. The book highlights important advancements in health science research and development by applying the distinctive capabilities inherent to distributed ledger systems. Each chapter describes the current uses of blockchain in real-world data collection, medicine development, device tracking, and more meaningful patient interaction. All of these are used to create opportunities for expanding health science research. This paradigm change is studied from the perspectives of pharmaceutical executives, biotechnology entrepreneurs, regulatory bodies, ethical review boards, and blockchain developers.

Key Features:

This book is primarily for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, and biomedical engineering.

The Internet of Things (IoT) and blockchain are two new technologies that combine elements in many ways. A system where the virtual and physical worlds interact is created by integrating pervasive computing, ubiquitous computing, communication technologies, sensing technologies, Internet Protocol, and embedded devices. A massive number of linked devices and vast amounts of data present new prospects for developing services that can directly benefit the economy, environment, society, and individual residents. Due to the size of IoT and insufficient data security, security breaches may have a huge impact and negative effects. IoT not only connects gadgets but also people and other entities, leaving every IoT component open to a wide variety of assaults. The implementation and application of IoT and blockchain technology in actual scientific, biomedical, and data applications are covered in this book. The book highlights important advancements in health science research and development by applying the distinctive capabilities inherent to distributed ledger systems. Each chapter describes the current uses of blockchain in real-world data collection, medicine development, device tracking, and more meaningful patient interaction. All of these are used to create opportunities for expanding health science research. This paradigm change is studied from the perspectives of pharmaceutical executives, biotechnology entrepreneurs, regulatory bodies, ethical review boards, and blockchain developers.

Key Features:

This book is primarily for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, and biomedical engineering.

This book provides a platform for presenting machine learning (ML)-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes ML techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.

Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses the Internet of Things (IoT) and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed at different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for Internet-based uses. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography and magnetic resonance imaging, which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks.

This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval and brain image segmentation.

This book provides a platform for presenting machine learning (ML)-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes ML techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.

Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses the Internet of Things (IoT) and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed at different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for Internet-based uses. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography and magnetic resonance imaging, which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks.

This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval and brain image segmentation.

The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality.

This book:

• Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources.

• Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy.

• Explains the role of emerging technology such as blockchain technology for transforming conventional business models.

• Highlights the importance of machine learning techniques in maintaining the privacy and security of data.

• Covers encryption and decryption techniques, their advantages and role in improving the privacy of data.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.

The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality.

This book:

• Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources.

• Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy.

• Explains the role of emerging technology such as blockchain technology for transforming conventional business models.

• Highlights the importance of machine learning techniques in maintaining the privacy and security of data.

• Covers encryption and decryption techniques, their advantages and role in improving the privacy of data.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.

The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making.

The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book.

Audience

Researchers and industry engineers in computer science, artificial intelligence, healthcare sector, IT professionals, network administrators, cybersecurity experts.

The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making.

The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book.

Audience

Researchers and industry engineers in computer science, artificial intelligence, healthcare sector, IT professionals, network administrators, cybersecurity experts.

Secure your understanding of vital security and forensic strategies by purchasing Securing the Digital Frontier: Threats and Advanced Techniques in Security and Forensics, a definitive guide that empowers you to protect sensitive information and tackle cyber threats with insights from leading experts and real-world case studies.

In the field of security and forensics, it’s crucial to implement strong security measures to protect sensitive data and effectively respond to cyber incidents. Digital forensics is vital for analyzing cyber threats, where experts use advanced techniques to scrutinize digital artifacts, system logs, and network traffic. This approach helps reconstruct incidents, pinpoint vulnerabilities, and support legal actions, ensuring the confidentiality, integrity, and availability of crucial data in our rapidly evolving digital world.

This book provides an in-depth look at security and forensics, pooling knowledge from top experts across various cybersecurity domains. It focuses on real-world applications and case studies, offering valuable insights for protecting information and responding to digital crimes. Designed for cybersecurity professionals, digital forensics investigators, legal teams, and academics, this comprehensive guide is a key resource for anyone looking to deepen their understanding of modern digital forensics and cybersecurity challenges.

Secure your understanding of vital security and forensic strategies by purchasing Securing the Digital Frontier: Threats and Advanced Techniques in Security and Forensics, a definitive guide that empowers you to protect sensitive information and tackle cyber threats with insights from leading experts and real-world case studies.

In the field of security and forensics, it’s crucial to implement strong security measures to protect sensitive data and effectively respond to cyber incidents. Digital forensics is vital for analyzing cyber threats, where experts use advanced techniques to scrutinize digital artifacts, system logs, and network traffic. This approach helps reconstruct incidents, pinpoint vulnerabilities, and support legal actions, ensuring the confidentiality, integrity, and availability of crucial data in our rapidly evolving digital world.

This book provides an in-depth look at security and forensics, pooling knowledge from top experts across various cybersecurity domains. It focuses on real-world applications and case studies, offering valuable insights for protecting information and responding to digital crimes. Designed for cybersecurity professionals, digital forensics investigators, legal teams, and academics, this comprehensive guide is a key resource for anyone looking to deepen their understanding of modern digital forensics and cybersecurity challenges.

Once there lived a learned brahman named Vishnu Sharma. Upon the king'' s request to make his sons ‘ masters of the art of practical life'' , he sought to enrich their minds through narrating animal fables. Thus Panchatantra— a collection of stories filled with incomparable beauty and wisdom— came to be. This is a book rife with entertaining stories laced with timeless teachings and moral values, stories that are read not only in their country of origin but far and wide in the world today.