Valentina Emilia Balas

Sheng-Lung Peng

M. Niranjanamurthy

E. Naresh

S. R. Jayasimha

This book presents the emerging technologies of Industry 4.0. It describes the growing trend towards automation and data exchange in the manufacturing industry, with a focus on the internet of things (IoT), the industrial internet of things (IIoT), cyberphysical systems (CPS), smart factories, cloud computing, cognitive computing, and artificial intelligence.

Concepts and Applications

Advances in Industry 4.0

Aynur Unal

Kukatlapalli Pradeep Kumar

Vinay Jha Pillai

Hari Murthy

DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Data Engineering and Data Science

T. Ananth Kumar

T. S. Arun Samuel

R. Dinesh Jackson Samuel

This reference text discusses various security techniques and challenges for cloud data protection from both software and hardware aspects. The text provides readers with an overview of cloud computing, beginning with historical perspectives on mainframe computers and early networking protocols, moving to current issues such as security of hardware and networks, performance, evolving IoT areas, edge computing, etc. It also deals with threat detection and incident response in cloud security. It covers important topics including operational security agitations in cloud computing, cyber artificial intelligence (AI) platform for cloud security, and security concerns of virtualization in cloud computing. The book will serve as a useful resource for graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology.

A Holistic Approach

Privacy and Security Challenges in Cloud Computing

Shibin David

R. S. Anand

V. Jeyakrishnan

The scope of Security Issues, Privacy Concerns in Industry 4.0 Applications is to envision the need for security in Industry 4.0 applications and the research opportunities for the future. This book discusses the security issues in the Industry 4.0 applications for research development. It will also enable the reader to develop solutions for the security threats and attacks that prevail in the industry. The chapters will be framed on par with advancements in the industry in the area of Industry 4.0 with its applications in additive manufacturing, cloud computing, IoT (Internet of Things), and many others. This book helps a researcher and an industrial specialist to reflect on the latest trend and the need for technological change in Industry 4.0. Smart water management using IoT, cloud security issues with network forensics, regional language recognition for industry 4.0, IoT based health care management system, artificial intelligence for fake profile detection, and packet drop detection in agriculture-based IoT are covered in this outstanding new volume. Leading innovations such as smart drone for railway track cleaning, everyday life-supporting blockchain and big data, effective prediction using machine learning, classification of the dog breed based on CNN, load balancing using the SPE approach and cyber culture impact on media consumers are also addressed. Whether a reference for the veteran engineer or an introduction to the technologies covered in the book for the student, this is a must-have for any library.

Security Issues and Privacy Concerns in Industry 4.0 Applications

M. Niranjanamurthy

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