A practical guide to the design, implementation, evaluation, and deployment of emerging technologies for intelligent Io T applications
With the rapid development in artificially intelligent and hybrid technologies, Io T, edge, fog-driven, and pervasive computing techniques are becoming important parts of our daily lives. This book focuses on recent advances, roles, and benefits of these technologies, describing the latest intelligent systems from a practical point of view. Fog, Edge, and Pervasive Computing in Intelligent Io T Driven Applications is also valuable for engineers and professionals trying to solve practical, economic, or technical problems. With a uniquely practical approach spanning multiple fields of interest, contributors cover theory, applications, and design methodologies for intelligent systems. These technologies are rapidly transforming engineering, industry, and agriculture by enabling real-time processing of data via computational, resource-oriented metaheuristics and machine learning algorithms. As edge/fog computing and associated technologies are implemented far and wide, we are now able to solve previously intractable problems. With chapters contributed by experts in the field, this book:
* Describes Machine Learning frameworks and algorithms for edge, fog, and pervasive computing
* Considers probabilistic storage systems and proven optimization techniques for intelligent Io T
* Covers 5G edge network slicing and virtual network systems that utilize new networking capacity
* Explores resource provisioning and bandwidth allocation for edge, fog, and pervasive mobile applications
* Presents emerging applications of intelligent Io T, including smart farming, factory automation, marketing automation, medical diagnosis, and more
Researchers, graduate students, and practitioners working in the intelligent systems domain will appreciate this book’s practical orientation and comprehensive coverage. Intelligent Io T is revolutionizing every industry and field today, and Fog, Edge, and Pervasive Computing in Intelligent Io T Driven Applications provides the background, orientation, and inspiration needed to begin.
Mục lục
About the Editors
List of contributors
Preface
Acknowledgment
Chapter 1 Fog, Edge and Pervasive computing in Intelligent Io T driven applications in Healthcare: Challenges, Limitations and Future Use
Chapter 2 Future opportunistic Fog/Edge Computational models and their Limitations
Chapter 3 Automating Elicitation Technique Selection using Machine Learning in Cloud Environment
Chapter 4 Machine Learning Frameworks and Algorithms for Fog and Edge Computing
Chapter 5 Integrated Cloud Based Library Management in Intelligent Io T driven applications
Chapter 6 A Systematic and Structured Review of Intelligent Systems for Diagnosis of Renal Cancer
Chapter 7 Location driven Edge assisted device and solutions for intelligent transportation
Chapter 8 Design and Simulation of MEMS for Automobile Condition Monitoring Using COMSOL Multiphysics Simulator
Chapter 9 Io T Driven Healthcare Monitoring System
Chapter 10 Fog Computing as Future Perspective in Vehicular Ad hoc Networks
Chapter 11 An overview to design an efficient and secure fog-assisted data collection method in Internet of Things
Chapter 12 Use of Fog Computing in Analytics of Internet of Things
Chapter 13 A Medical diagnosis of urethral stricture using Intuitionistic fuzzy sets
Chapter 14 Security Attacks in Internet of Things
Chapter 15 Fog Integrated Novel Architecture for Telehealth Services with Swift Medical Delivery
Chapter 16 Fruit Fly Optimization Algorithm for Intelligent Io T Applications
Chapter 17 Nature inspired driven multi-objective techniques for intelligent Io T Applications
Chapter 18 Optimization Techniques for Intelligent Io T Applications in Transport Processes
Chapter 19 Role of Intelligent IOT applications in Fog paradigm: Issues, Challenges and future opportunities
Chapter 20 Security and Privacy issues in Fog/Edge/Pervasive computing
Chapter 21 Fog and Edge driven Security & Privacy Issues in Io T Devices
Index
Giới thiệu về tác giả
Deepak Gupta, Ph D, is an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, Delhi, India. He has published 158 papers and 3 patents. He is associated with numerous professional bodies, including IEEE, ISTE, IAENG, and IACSIT. He is the convener and organizer of the ICICC, ICDAM Springer Conference Series.
Aditya Khamparia, Ph D, is Associate Professor of Computer Science at Lovely Professional University, Punjab, India. He has published more than 45 scientific research publications and is a member of CSI, IET, ISTE, IAENG, ACM and IACSIT.
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