Azidine Guezzaz – författare

The Internet of Things (IoT) involves physical devices, cars, household appliances, and any other physical appliance equipped with sensors, software, and network connections to gather and communicate data. Nowadays, this technology is embedded in everything from simple smart devices, to wearable equipment, to complex industrial machinery and transportation infrastructures. On the other hand, IoT equipment has been designed without considering security issues. Consequently, there are many challenges in terms of protection against IoT threats, which can lead to distressing situations. In fact, unlike other technological solutions, there are few standards and guidelines governing the protection of IoT technology. Moreover, few users are aware of the risks associated with IoT systems.

Hence, Blockchain and Machine Learning for IoT Security discusses various recent techniques and solutions related to IoT deployment, especially security and privacy. This book addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer by considering how both the architecture and underlying technologies are employed. As acknowledged experts in the field, the authors provide remediation solutions for impaired security, as well as mitigation methods, and offer both prevention and improvement suggestions.

Key Features:

This book is designed to provide all the necessary knowledge for young researchers, academics, and industry professionals who want to understand the advantages of artificial intelligence technology, machine learning, data analysis methodology, and Blockchain for securing IoT technologies.

The Internet of Things (IoT) involves physical devices, cars, household appliances, and any other physical appliance equipped with sensors, software, and network connections to gather and communicate data. Nowadays, this technology is embedded in everything from simple smart devices, to wearable equipment, to complex industrial machinery and transportation infrastructures. On the other hand, IoT equipment has been designed without considering security issues. Consequently, there are many challenges in terms of protection against IoT threats, which can lead to distressing situations. In fact, unlike other technological solutions, there are few standards and guidelines governing the protection of IoT technology. Moreover, few users are aware of the risks associated with IoT systems.

Hence, Blockchain and Machine Learning for IoT Security discusses various recent techniques and solutions related to IoT deployment, especially security and privacy. This book addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer by considering how both the architecture and underlying technologies are employed. As acknowledged experts in the field, the authors provide remediation solutions for impaired security, as well as mitigation methods, and offer both prevention and improvement suggestions.

Key Features:

This book is designed to provide all the necessary knowledge for young researchers, academics, and industry professionals who want to understand the advantages of artificial intelligence technology, machine learning, data analysis methodology, and Blockchain for securing IoT technologies.

Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system.

This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues.

This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students

Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system.

This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues.

This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students

This book introduces a variety of the latest researches that are related to smart devices, machine learning algorithms, and the Internet of things that are applied for a sustainable environment. These recent technologies cover all fields including agriculture, transportation, smart grid, smart building, and others. In addition, IoT has provided an innovative vision that is completely alternative to the conventional methodologies: the new approach comes in the form of a single-component system that can be connected to the network and can incorporate smart policies. As a consequence, the covered subjects encompass smart system design and control, networking and machine learning, environmental monitoring and surveillance, smart meters, authentication and authorization, ensuring private data security, software solutions, and systems, among others.

This book covers subjects that are related to the Internet of Things and smart used tools and methods for fighting environmental problems. Therefore, it discusses recent ideas that are not covered by other competitor books. This book is different because it can be a reference for researchers, professionals, and students in both smart thinking and environmental domains.

Nowadays, the efficient sustainable systems are becoming more and more important for sustainable life either in urban and in rural environments. Despite the advances in technologies, it is always important to consider the environment where we live.

Hence, the present book presents some recent and fresh works that deal with environmental problems including water quality, wastewater management, air pollution monitoring, renewable energy solutions, food security solutions, and so on. Besides, the book investigates different applications of Artificial Intelligence for previous environmental issues. This book is targeting junior researchers, graduate and graduate students, environmental specialists, and all people who want to learn more about recent advancement in environmental solutions.