Kingsley Eghonghon Ukhurebor – författare

Digital Twins, Artificial Intelligence, and Internet of Things for a Sustainable Food Production in Agriculture: Transformative Technologies looks at how advanced technologies like digital twins, artificial intelligence (AI), and the Internet of Things (IoT) can be used in farming.

The book discusses how these innovations enhance resource efficiency, support sustainable food systems, and improve crop and livestock management. Focusing on both the theoretical and practical applications, it provides readers with current insight into sustainable agricultural practices. It also offers insights into how digital twins, AI, and IoT are integrated into agriculture for sustainable food production. The book will cover how digital copies of farms, smart computers, AI, IoT, and connected devices help farmers optimize food production. It draws its strength from a multidisciplinary approach with an emphasis on practical applications and future prospects in smart agriculture toward improved efficiency, sustainability, and profitability in food production.

This book is suitable for a broad academic audience, including undergraduate and graduate students, researchers, and professionals in fields such as agricultural science, environmental science, computer science, and engineering, as well as policymakers and government functionaries. It is meant to be used as a textbook or additional reading for courses on precision farming, smart agriculture, and sustainable food systems. The content is designed to be understandable to people who have just a cursory understanding of technology and agriculture, but it also provides in-depth analysis for practitioners and advanced students.

Digital Twins, Artificial Intelligence, and Internet of Things for a Sustainable Food Production in Agriculture: Transformative Technologies looks at how advanced technologies like digital twins, artificial intelligence (AI), and the Internet of Things (IoT) can be used in farming.

The book discusses how these innovations enhance resource efficiency, support sustainable food systems, and improve crop and livestock management. Focusing on both the theoretical and practical applications, it provides readers with current insight into sustainable agricultural practices. It also offers insights into how digital twins, AI, and IoT are integrated into agriculture for sustainable food production. The book will cover how digital copies of farms, smart computers, AI, IoT, and connected devices help farmers optimize food production. It draws its strength from a multidisciplinary approach with an emphasis on practical applications and future prospects in smart agriculture toward improved efficiency, sustainability, and profitability in food production.

This book is suitable for a broad academic audience, including undergraduate and graduate students, researchers, and professionals in fields such as agricultural science, environmental science, computer science, and engineering, as well as policymakers and government functionaries. It is meant to be used as a textbook or additional reading for courses on precision farming, smart agriculture, and sustainable food systems. The content is designed to be understandable to people who have just a cursory understanding of technology and agriculture, but it also provides in-depth analysis for practitioners and advanced students.

Harnessing Machine Learning for Environmental Restoration and Surveillance is an extensive and comprehensive book, showcasing the applications of machine learning and artificial intelligence in environmental monitoring of the quality of air, soil, and water; prediction of environmental risks; optimization and prediction of remediation processes; and enhancement of resource management.

The book offers readers an opportunity to understand how contemporary smart technology (machine learning and artificial intelligence) can be used to safeguard and improve our environment as well as to solve environmental problems and provide sustainable solutions. It offers insights and an opportunity to evaluate theoretical concepts and real-world case studies, thereby boosting innovation and collaboration. The authors give modest explanations of how artificial intelligence and machine learning can monitor pollution, forecast environmental hazards, and support the optimization process for the effective removal of environmental contaminants. Real-world examples where these advanced smart technology tools have been successfully utilized are also presented in this book.

The content and coverage of this academic text are ideal for undergraduate and postgraduate students, researchers, professionals in environmental science, data science, and engineering, as well as individuals interested in the environment and technology.

Harnessing Machine Learning for Environmental Restoration and Surveillance is an extensive and comprehensive book, showcasing the applications of machine learning and artificial intelligence in environmental monitoring of the quality of air, soil, and water; prediction of environmental risks; optimization and prediction of remediation processes; and enhancement of resource management.

The book offers readers an opportunity to understand how contemporary smart technology (machine learning and artificial intelligence) can be used to safeguard and improve our environment as well as to solve environmental problems and provide sustainable solutions. It offers insights and an opportunity to evaluate theoretical concepts and real-world case studies, thereby boosting innovation and collaboration. The authors give modest explanations of how artificial intelligence and machine learning can monitor pollution, forecast environmental hazards, and support the optimization process for the effective removal of environmental contaminants. Real-world examples where these advanced smart technology tools have been successfully utilized are also presented in this book.

The content and coverage of this academic text are ideal for undergraduate and postgraduate students, researchers, professionals in environmental science, data science, and engineering, as well as individuals interested in the environment and technology.

This book entails detailed information on the utilization of nanobiosensor as an effective technology for the effective detection, monitoring, and management of environmental contaminations to ensure its sustainability and humanity''s well-being. The higher level of anthropogenic action has been identified as a threat to humankind''s existence due to the higher level of xenobiotic and toxic substances that could interrupt the normal ecosystem. This has prompted numerous agencies both locally and internationally that could play a significant role in environmental pollution mitigation. The application of nanobiosensor has been identified as a sustainable technique that could be applied to ensure proper detection and identification of several environmental contaminants.  Nanomaterial’s possible applications created an innovative domain called nanomaterials based biosensors machinery as one of nanotechnology''s ultimate sub-divisions. The application of nanomaterials based biosensorsmachinery and their advancements could be applied globally to resolve numerous environmental sectors'' challenges to guarantee the environment''s quality and safety.

The book will be an excellent collection of reviews based on contemporary research and developments on nanomaterials utilization and applications in environmental monitoring along with their prospects. The book will attempt to give a comprehensive idea of nanomaterial concepts for nanobiosensors applications in an environmental context to help students, researchers, and professionals/practitioners recognize nanomaterials'' significance in the environmental domain. The book will also help understand and address the environmental sectors'' complications via nanomaterials'' utilization and applications. Hence, this book will serve as a textbook and will help students, professionals/practitioners, scientists, researchers, and academicians in various research domains.

This book explores some of the latest and recent advances in the synthesis, characterization and applications of magnetic nanomaterials. It starts with an overview of magnetic nanomaterials, followed by a list of their synthesis and characterization methods. The book shows the potential of magnetic materials in different applications, including theranostic nanomedicine, heavy metals detection, dyes sensing, solar cells, wastewater treatment,  decontamination of soil, and detection and monitoring of toxic gases. Moreover, it explores their use as drug and gene delivery agents, their biosafety and bioregulation facets, tissue engineering applications, and their potential for combating pathogens