Business Intelligence for Enterprise Internet of Things

ISBN-13: 9783030444099 / Angielski / Miękka / 2021 / 289 str.

Anandakumar Haldorai; Arulmurugan Ramu; Syed Abdul Rehman Khan

Spis treści

Preface

1) Internet of Things (IoTs) Evolutionary Computation, Enterprise Modeling and Simulation

2) Organization Internet of Things (IoTs): Supervised, Unsupervised and Reinforcement Learning

3) Enterprise IoT Modeling: Supervised, Unsupervised and Reinforcement Learning

4) An Overall Perspective on Establishing End-To-End Security In Enterprise-IOT (E-IOT)

5) Advanced Machine learning for Enterprise IoT modelling

6) Enterprise Architecture for IoT: Challenges and Business Trends

7) Semi Supervised Machine Learning Algorithm for Predicting Diabetes using Big Data Analytics

8) On-The-Go Network Establishment of IoT Devices To Meet The Need of Processing Big Data Using Machine Learning Algorithms

9) Analysis of Virtual Machine Placement and Optimization Using Swarm Intelligence Algorithms

10) Performance Evaluation of Different Neural Network Classifiers for Sanskrit Character Recognition

11) GA With Repeated Crossover for Rectifying Optimization Problems

12) An Algorithmic Approach to System Identification In the Delta Domain Using FADFPA Algorithm

13) An IoT Based Controller Realization for PV System Monitoring and Control

14) Development of An Efficient, Cheap and Flexible IoT Based Wind Turbine Emulator

15) An Application of IoT to Develop Concept of Smart Remote Monitoring System

16) Heat-Maps for Human Group Activity in Academic Blocks

17) Emphasizing on Space Complexity in Social Networks for the Investigation of Link Prediction Using Hybrid Approach

18) Overview on Deep Neural Networks: Architecture, Application and Rising Analysis Trends

O autorze

Dr. Anandakumar Haldorai, Professor (Associate) and Research Head in Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India. He has received his Master’s in Software Engineering from PSG College of Technology, Coimbatore and PhD in Information and Communication Engineering from PSG College of Technology under, Anna University, Chennai. His research areas include Big Data, Cognitive Radio Networks, Mobile Communications and Networking Protocols. He has authored more than 82 research papers in reputed International Journals and IEEE conferences. He has authored 7 books and many book chapters with reputed publishers such as Springer and IGI. He is editor of Inderscience IJISC and served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Elsevier, Springer, Inderscience, etc. He has been the General Chair, Session Chair, and Panelist in several conferences. He is senior member of IEEE, IET, ACM and Fellow member of EAI research group.

Dr. Arulmurugan Ramu is a Professor, Presidency University, Bangalore, India. His research focuses on the automatic interpretation of images and related problems in machine learning and optimization. His main research interest is in vision, particularly high-level visual recognition. He has authored more than 35 papers in major computer vision and machine learning conferences and journals. He is the recipient of Ph.D. degrees in Information and Communication Engineering from the Anna University at Chennai, M.Tech in Information Technology Anna University of Technology and B.Tech degree in Information Technology. He is guided many Ph.D. research scholar under the area of Image Processing using Machine Learning. He is an Associate Editor of Inderscience IJISC journal. He is awarded as Best Young Faculty Award 2018 and nominated for Best Young Researcher Award (Male) by International Academic and Research Excellence Awards (IARE-2019).

Dr. Syed Abdul Rehman Khan is a Professor of Supply Chain and Logistics Management. Dr. Khan achieved his CSCP—Certified Supply Chain Professional certificate from the U.S.A. and successfully completed his Ph.D. in China. Since 2018, Dr. Khan has been affiliated with Tsinghua University as a postdoctoral researcher. He has more than nine years’ core experience of supply chain and logistics at industry and academic levels. He has attended several international conferences and also has been invited as keynote speaker in different countries. He has published more than 55 scientific research papers in different well-renowned international journals and conferences. He is a regular contributor to conferences and workshops around the world. In addition, Dr. Khan has achieved scientific innovation awards two times consecutively by the Education Department of Shaanxi Provincial Government, China. Also, Dr. Khan holds memberships in the following well-renowned institutions and supply chain bodies/associations: APCIS-U.S.; Production and Operation Management Society, India; Council of Supply Chain Management of Professionals U.S.; Supply Chain Association of Pakistan; and Global Supply Chain Council China.

Blurb

This book discusses Internet of Things (IoT) as it relates to enterprise applications, systems, and infrastructures. The authors discuss IoT and how it’s disrupting industries such as enterprise manufacturing, enterprise transportation, enterprise smart market, enterprise utilities, and enterprise healthcare. They cover how IoT in the enterprise will have a major impact on the lives of consumers and professionals around the world and how it will change the way we think about professional and consumer networks. The book's topics include IoT enterprise system architecture, IoT enabling enterprise technologies, and IoT enterprise services and applications. Examples include enterprise on demand, market impacts, and implications on smart technologies, big data enterprise management, and future enterprise Internet design for various IoT use cases, such as share markets, healthcare, smart cities, smart environments, smart communications and smart homes.

• Illustrates how enterprise network infrastructure teams contribute to IoT strategies at their organizations;
• Presents the most recent challenges and developments in business management in Internet of Things systems;
• Includes planning and engineering challenges and describes the methodology and implementation of a powerful tool for enterprise management.