Ahmed J Obaid – författare

Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science.

Features

• Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place

• Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0

• Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security

• Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0

This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.

Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science.

Features

• Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place

• Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0

• Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security

• Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0

This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.

The Next Generation Innovation in IoT and Cloud Computing with Applications is a thought-provoking edited book that explores the cutting-edge advancements and transformative potential of the Internet of Things (IoT) and cloud computing. This comprehensive volume brings together leading experts and researchers to delve into the latest developments, emerging trends, and practical applications that define the next era of technological innovation.

Readers will gain valuable insights into how IoT and cloud computing synergize to create a dynamic ecosystem, fostering unprecedented connectivity and efficiency across various industries. The book covers a wide spectrum of topics, including state-of-the-art technologies, security and privacy considerations, and real-world applications in fields such as healthcare, smart cities, agriculture, and more.

With a focus on the future landscape of technology, this edited collection serves as a pivotal resource for academics, professionals, and enthusiasts eager to stay at the forefront of the rapidly evolving IoT and cloud computing domains. By offering a blend of theoretical perspectives and hands-on experiences, The Next Generation Innovation in IoT and Cloud Computing with Applications serves as a guide to the forefront of technological progress, providing a roadmap for the exciting possibilities that lie ahead in this era of connectivity and digital transformation.

The Next Generation Innovation in IoT and Cloud Computing with Applications is a thought-provoking edited book that explores the cutting-edge advancements and transformative potential of the Internet of Things (IoT) and cloud computing. This comprehensive volume brings together leading experts and researchers to delve into the latest developments, emerging trends, and practical applications that define the next era of technological innovation.

Readers will gain valuable insights into how IoT and cloud computing synergize to create a dynamic ecosystem, fostering unprecedented connectivity and efficiency across various industries. The book covers a wide spectrum of topics, including state-of-the-art technologies, security and privacy considerations, and real-world applications in fields such as healthcare, smart cities, agriculture, and more.

With a focus on the future landscape of technology, this edited collection serves as a pivotal resource for academics, professionals, and enthusiasts eager to stay at the forefront of the rapidly evolving IoT and cloud computing domains. By offering a blend of theoretical perspectives and hands-on experiences, The Next Generation Innovation in IoT and Cloud Computing with Applications serves as a guide to the forefront of technological progress, providing a roadmap for the exciting possibilities that lie ahead in this era of connectivity and digital transformation.

This book covers a wide range of topics such as mathematical modeling, computational methods, simulation techniques in engineering, and their applications in environmental sciences. It begins with an introduction to the fundamental concepts and principles of mathematical modeling with subsequent sections delving into various simulation techniques, including numerical methods, statistical modeling, and bio-mathematical modeling. It also explores the application of these techniques in addressing complex environmental problems.

Features:

This book is aimed at researchers and graduate students in computer engineering, applied mathematics, and applied ecology.

This book covers a wide range of topics such as mathematical modeling, computational methods, simulation techniques in engineering, and their applications in environmental sciences. It begins with an introduction to the fundamental concepts and principles of mathematical modeling with subsequent sections delving into various simulation techniques, including numerical methods, statistical modeling, and bio-mathematical modeling. It also explores the application of these techniques in addressing complex environmental problems.

Features:

This book is aimed at researchers and graduate students in computer engineering, applied mathematics, and applied ecology.

The main goal of the book is to explore the idea behind data modeling in smart agriculture using information and communication technologies and tools to make agricultural practices more functional, fruitful and profitable.

The research in the book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers’ choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models were utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies.

Farm management information systems (FMIS) have constantly advanced in complexity as they have incorporated new technology, the most recent of which is the internet. However, few FMIS have fully tapped into the internet’s possibilities, and the newly developing idea of precision agriculture receives little or no support in the FMIS that are now being sold. FMIS for precision agriculture must meet a few more criteria beyond those of regular FMIS, which increases the technological complexity of these systems’ deployment in a number of ways. In order to construct an FMIS that meet these extra needs, the authors here evaluated various cutting-edge web-based methods. The goal was to determine the requirements that precision agriculture placed on FMIS.

The main goal of the book is to explore the idea behind data modeling in smart agriculture using information and communication technologies and tools to make agricultural practices more functional, fruitful and profitable.

The research in the book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers’ choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models were utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies.

Farm management information systems (FMIS) have constantly advanced in complexity as they have incorporated new technology, the most recent of which is the internet. However, few FMIS have fully tapped into the internet’s possibilities, and the newly developing idea of precision agriculture receives little or no support in the FMIS that are now being sold. FMIS for precision agriculture must meet a few more criteria beyond those of regular FMIS, which increases the technological complexity of these systems’ deployment in a number of ways. In order to construct an FMIS that meet these extra needs, the authors here evaluated various cutting-edge web-based methods. The goal was to determine the requirements that precision agriculture placed on FMIS.

This book presents the latest cutting edge research, theoretical methods, and novel applications in the field of computational intelligence and computational biological approaches that are aiming to combat COVID-19. The book gives the technological key drivers behind using AI to find drugs that target the virus, shedding light on the structure of COVID-19, detecting the outbreak and spread of new diseases, spotting signs of a COVID-19 infection in medical images, monitoring how the virus and lockdown is affecting mental health, and forecasting how COVID-19  cases and deaths will spread across cities and why. Further, the book helps readers understand computational intelligence techniques combating COVID-19 in a simple and systematic way.