Jamal Mabrouki – 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

The growth of the Internet of Things (IoT) technology has indeed led to an increase in cybersecurity issues. While the Internet of Things enhances accessibility, integrity, availability, scalability, confidentiality, and interoperability among devices, it also faces vulnerabilities due to its diverse attack sources and lack of standardization in security protocols. This makes Internet of Things systems particularly susceptible to cyberattacks. It is essential to ensure proper security measures are in place to protect Internet of Things devices and networks, given their critical role in modern communications and the evolving threat landscape. Always remember to verify important security information from trusted sources.

Recent Advances in Internet of Things Security discusses the critical importance of robust security frameworks to protect Internet of Things ecosystems against various cyber threats. It highlights the security risks associated with Internet of Things devices and applications and presents a variety of potential solutions. It is essential to remain aware of these challenges to effectively safeguard Internet of Things systems. This book delves into the complexities of IoT security, exploring a range of vulnerabilities across different layers of the IoT architecture.

The book provides a comprehensive overview of Internet of Things security, emphasizing the significance of securing Internet of Things products and applications. It serves as a foundational resource for young researchers, academics, and industry professionals keen on advanced security solutions within the Internet of Things landscape, reflecting the current state of research and ongoing challenges in this field.

The growth of the Internet of Things (IoT) technology has indeed led to an increase in cybersecurity issues. While the Internet of Things enhances accessibility, integrity, availability, scalability, confidentiality, and interoperability among devices, it also faces vulnerabilities due to its diverse attack sources and lack of standardization in security protocols. This makes Internet of Things systems particularly susceptible to cyberattacks. It is essential to ensure proper security measures are in place to protect Internet of Things devices and networks, given their critical role in modern communications and the evolving threat landscape. Always remember to verify important security information from trusted sources.

Recent Advances in Internet of Things Security discusses the critical importance of robust security frameworks to protect Internet of Things ecosystems against various cyber threats. It highlights the security risks associated with Internet of Things devices and applications and presents a variety of potential solutions. It is essential to remain aware of these challenges to effectively safeguard Internet of Things systems. This book delves into the complexities of IoT security, exploring a range of vulnerabilities across different layers of the IoT architecture.

The book provides a comprehensive overview of Internet of Things security, emphasizing the significance of securing Internet of Things products and applications. It serves as a foundational resource for young researchers, academics, and industry professionals keen on advanced security solutions within the Internet of Things landscape, reflecting the current state of research and ongoing challenges in this field.

Smart agriculture is an approach to maintaining nature without compromising the basic needs of future generations while at the same time improving the efficiency of farming. The main achievements of smart agriculture in terms of sustainable agriculture are crop rotation, controlling nutrient deficiencies in crops, pest and disease control, recycling, and water harvesting, leading to a safer environment overall. Living organisms depend on the nature of biodiversity and are exposed to pollution due to waste emissions, use of fertilizers and pesticides, degraded dead plants, and so on. The emission of greenhouse gases affects plants, animals, humans, and the environment; hence, this necessitates a better environment for living organisms.

The purpose of this book is to provide a comprehensive overview of the latest advancements, challenges, and potential applications of artificial intelligence (AI) technology and the Internet of Things (IoT) in the future of intelligent agriculture. The book is primarily focused on equipping younger researchers, graduates, and professionals in the industry with the necessary knowledge to understand the advantages of AI technology, machine learning, and data analytics methods in improving current agricultural practices.

Key features include the following:

Smart agriculture is an approach to maintaining nature without compromising the basic needs of future generations while at the same time improving the efficiency of farming. The main achievements of smart agriculture in terms of sustainable agriculture are crop rotation, controlling nutrient deficiencies in crops, pest and disease control, recycling, and water harvesting, leading to a safer environment overall. Living organisms depend on the nature of biodiversity and are exposed to pollution due to waste emissions, use of fertilizers and pesticides, degraded dead plants, and so on. The emission of greenhouse gases affects plants, animals, humans, and the environment; hence, this necessitates a better environment for living organisms.

The purpose of this book is to provide a comprehensive overview of the latest advancements, challenges, and potential applications of artificial intelligence (AI) technology and the Internet of Things (IoT) in the future of intelligent agriculture. The book is primarily focused on equipping younger researchers, graduates, and professionals in the industry with the necessary knowledge to understand the advantages of AI technology, machine learning, and data analytics methods in improving current agricultural practices.

Key features include the following:

An intelligent electrical network (smart grid—SG) includes heterogeneous and distributed electricity production, transmission, distribution and consumption components. It is the next generation of electricity network able to manage electricity demand (consumption/production/distribution) in a sustainable, reliable and economical way taking into account the penetration of renewable energies (solar, wind, etc.). Therefore, a (SG) smart grid also includes an intelligent layer that analyzes the data provided by consumers as well as that collected from the production side in order to optimize consumption and production according to weather conditions, the profile and habits of the consumer. In addition, this system can improve the use of green energy through renewable energy penetration and demand response.

Environmental risks put one in six people at risk, as well as our complex ecosystems. Today, IoT sites can monitor the environment and assess risks. Clean technologies can help detect toxic substances, chemical spills, hazardous pollutants, and other issues, enabling both governments and industries to clean or protect the air, land, water, and other environments, and how IoT can support these processes. IoT-enabled environmental intelligence is the constant measurement and collection of our physical environment, through sensors and smart devices. Integrated sensors in irrigation facilities, water supply systems, pipelines, cisterns, weather stations, ocean, and industrial facilities—anywhere on the globe—can record temperature, relative humidity, water content, leaks, and any other physical parameters.