IoT and Machine Learning for Smart Applications - Selvi, G. Vennira; Kumar, T. Ganesh; Prasad, M.;(ed.) - Prospero Internet Bookshop
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IoT and Machine Learning for Smart Applications

 
Edition number: 1
Publisher: Chapman and Hall
Date of Publication:
 
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GBP 130.00
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Short description:

This book provides an illustration of the various methods and structures that are utilized in machine learning to make use of data that is generated by IoT devices. Numerous industries utilize machine learning, specifically Machine learning-as-a-Service (MLaaS) to realize IoT to its full potential. 

Long description:

This book provides an illustration of the various methods and structures that are utilized in machine learning to make use of data that is generated by IoT devices. Numerous industries utilize machine learning, specifically machine learning- as- aservice (MLaaS), to realize IoT to its full potential. On the application of machine learning to smart IoT applications, it becomes easier to observe, methodically analyze, and process a large amount of data to be used in various fields.


Features:



  • Explains the current methods and algorithms used in machine learning and IoT knowledge discovery for smart applications


  • Covers machine- learning approaches that address the difficulties posed by IoT- generated data for smart applications



  • Describes how various methods are used to extract higher- level information from IoT- generated data



  • Presents the latest technologies and research findings on IoT for smart applications



  • Focuses on how machine learning algorithms are used in various real- world smart applications and engineering problems


It is a ready reference for researchers and practitioners in the field of information technology who are interested in the IoT and Machine Learning fields.

Table of Contents:

1. Recent Advances in Machine Learning Strategies and its Applications 2. Understanding the Concept of IoT 3. Unlocking the Power of IoT: An In-Depth Exploration 4. Machine Learning in Internet of Things 5. Role of Machine Learning in Real Life Environment 6. Efficient Blockchain Based Edge Computing System Using Transfer Learning Model 7. Introducing a Compact and High-Speed Machine Learning Accelerator for IoT enabled health monitoring systems 8. Realization of smart city based on IoT and AI 9. Sentiment Analysis of airline tweets using Machine Learning Algorithms and Regular Expression 10. Smart Workspace Automation: Harnessing IoT and AI for Sustainable Urban Development and Improved Quality of Life 11. Application of Digital Image Watermarking in the Internet of Things and Machine Learning