Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things
eBook - ePub

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things

  1. 290 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things

About this book

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.

The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency.

A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

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Yes, you can access Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things by Pankaj Bhambri,Sita Rani,Valentina E. Balas,Ahmed A. Elngar in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Civil Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half Title page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. About the Editors
  8. Contributors
  9. Preface
  10. 1 Challenges, Opportunities, and the Future of Industrial Engineering with IoT and AI
  11. 2 Evolution and the Future of Industrial Engineering with the IoT and AI
  12. 3 Applications of Artificial Intelligence and Internet of Things IoT in Marketing
  13. 4 An Introduction to Multi-Objective Decision Programming with Fuzzy Parameters
  14. 5 Data Analytics
  15. 6 Recent Advances on Deep Learning Based Thermal Infrared Object Tracking in Videos: A Survey
  16. 7 Heuristics to Secure IoT-based Edge Driven UAV
  17. 8 Phased.js: Automated Software Deployment and Resource Provisioning and Management for AI
  18. 9 Robust Image Enhancement Technique to Automatically Enrich the Visibility of Satellite Captured Snaps
  19. 10 Implementation of FIR Filter and the Creation of Custom IP Blocks
  20. 11 Use Cases of Blockchain in Post-Covid Healthcare
  21. 12 A Prediction of Telecom Customer Churn Analysis Using the I-GBDT Algorithm
  22. 13 Deployment of Machine Learning and Deep Learning Algorithms in Industrial Engineering
  23. 14 Simulation Analysis of AODV and DSDV Routing Protocols for Secure and Reliable Service in Mobile Adhoc Networks (MANETs)
  24. 15 Landmine Detection and Classification Based on Machine Learning Algorithms
  25. 16 Application of Queuing Technique in an Educational Institute Canteen: A Case Study
  26. 17 IoT-Based Driver Drowsiness Detection and Alerting System Using Haar Cascade and Eye Aspect Ratio Algorithms
  27. 18 Force/Position Control of Constrained Reconfigurable Manipulators Using Hybrid Backstepping Neural Networks Based Control Approach
  28. Index