Introduction to Internet of things in management science and operations research : implemented studies
著者
書誌事項
Introduction to Internet of things in management science and operations research : implemented studies
（International series in operations research & management science, v. 311）
Springer, c2021
- : hardback
大学図書館所蔵 全3件
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book aims to provide relevant theoretical frameworks and the latest empirical research findings in Internet of Things (IoT) in Management Science and Operations Research. It starts with basic concept and present cases, applications, theory, and potential future. The contributed chapters to the book cover wide array of topics as space permits. Examples are from smart industry; city; transportation; home and smart devices. They present future applications, trends, and potential future of this new discipline. Specifically, this book provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning capabilities of managing IoT.
This book deals with the implementation of latest IoT research findings in practice at the global economy level, at networks and organizations, at teams and work groups and, finally, IoT at the level of players in the networked environments.
This book is intended for professionals in the field of engineering, information science, mathematics, economics, and researchers who wish to develop new skills in IoT, or who employ the IoT discipline as part of their work. It will improve their understanding of the strategic role of IoT at various levels of the information and knowledge organization. The book is complemented by a second volume of the same editors with practical cases.
目次
Chapter 1. Prescriptive Analytics in Internet of Things With Concentration on Deep Learning.- Chapter 2. Internet of Things: Technologies & Applications.- Chapter 3. Internet of Things Cybersecurity .- Blockchain as First Securitisation Layer of an IOT Network.- Chapter 4. Using Other Multi-Attribute Decision Making Techniques to Measure Efficiency When Data Envelopment Analysis Fails.- Chapter 5. A Data-Driven Traffic Responsive Signal Control for a Smart City Road Network Under Uncertainty.- Chapter 6. A Hybrid Model of Learning Methodology Analyzed Through the Use of Machine Learning Techniques.- Chapter 7. IOT Security and New Trends of Solutions.- Chapter 8. Application of Internet of Things (Iot) to Demand-Side Management in Smart Grids.- Chapter 9. Development Path, Experience and Implications of the Internet of Things Industry in Wuxi, Jiangsu Province, China.- Chapter 10. Understanding the Factors Influencing Consumers' Behaviour Towards Autonomous Vehicles Adoption.- Chapter 11. Utilization of Consumer Appliances in Smart Grid Services for Coordination With Renewable Energy Sources.- Chapter 12. Use of Convolutional Neural Networks for Quality Control in Automotive Industry.
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