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Recent Advances in Internet of Things and Machine Learning

Real-World Applications

  • Book
  • © 2022

Overview

Editors:
  1. Valentina E. Balas

    1. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

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  2. Vijender Kumar Solanki

    1. Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, India

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  3. Raghvendra Kumar

    1. Department of Computer Science Engineering, GIET University, Gunupur, India

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  • Presents Recent Advances in Internet of Things and Machine Learning
  • Includes a variety of real world applications useful for Industry in IoT with Machine Learning approaches
  • Provides Machine Learning models, technologies, and solutions

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 215)

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Table of contents (25 chapters)

  1. Front Matter

    Pages i-xxiv
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  2. Internet of Things

    1. Front Matter

      Pages 1-1
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    2. Concentration Level of Learner Using Facial Expressions on e-Learning Platform Using IoT-Based Pycharm Device

      • Karlapudi Rahul Sai, Bhumireddy Sohith Reddy, S. Vijaya Kumar
      Pages 3-8

    3. IoT-Based Machine Learning System for Nutritional Ingredient Analyzer for Food

      • A. Thilagavathy, Tadavarthi Rishi, Veeram Deepak Reddy, Sudesh Nimmagadda
      Pages 9-18

    4. A Secured Manhole Management System Using IoT and Machine Learning

      • R. Santhana Krishnan, A. Sangeetha, D. Abitha Kumari, N. Nandhini, G. Karpagarajesh, K. Lakshmi Narayanan et al.
      Pages 19-30

    5. Internet of Things Based Smart Accident Recognition and Rescue System Using Deep Forests ML Algorithm

      • K. Lakshmi Narayanan, Y. Harold Robinson, Rajkumar Krishnan, C. Ramasamy Sankar Ram, R. Santhana Krishnan, R. Niranjana et al.
      Pages 31-41

    6. Revolutionizing the Industrial Internet of Things Using Blockchain: An Unified Approach

      • A. K. M. Bahalul Haque, Bharat Bhushan, Md.Rifat Hasan, Md.Oahiduzzaman Mondol Zihad
      Pages 43-66

    7. Attacks and Countermeasures in IoT Based Smart Healthcare Applications

      • A. K. M. Bahalul Haque, Bharat Bhushan, Afra Nawar, Khalid Raihan Talha, Sadia Jeesan Ayesha
      Pages 67-90

  3. Machine Learning

    1. Front Matter

      Pages 91-91
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    2. Online Product Review Monitoring System Using Machine Learning

      • J. Madhumathi, R. Aishwarya, V. Vedha Pavithra, Sandra Johnson
      Pages 93-101

    3. Deep Learning Analysis for COVID 19 Using Neural Network Algorithms

      • V. Vijaya Baskar, V. G. Sivakumar, S. P. Vimal, M. Vadivel
      Pages 103-110

    4. A Machine Learning Approach to Design and Develop a BEACON Device for Women’s Safety

      • S. Srinivasan, P. Muthu Kannan, R. Kumar
      Pages 111-115

    5. Tea Plant Leaf Disease Identification Using Hybrid Filter and Support Vector Machine Classifier Technique

      • S. Prabu, B. R. Tapas Bapu, S. Sridhar, V. Nagaraju
      Pages 117-128

    6. Machine Learning Based Efficient and Secured Car Parking System

      • R. Santhana Krishnan, K. Lakshmi Narayanan, S. T. Bharathi, N. Deepa, S. Mathumitha Murali, M. Ashok Kumar et al.
      Pages 129-145

    7. Machine Learning Approaches for Smart City Applications: Emergence, Challenges and Opportunities

      • Sonam Mehta, Bharat Bhushan, Raghvendra Kumar
      Pages 147-163

    8. Machine Learning and Deep Learning Models for Privacy Management and Data Analysis in Smart Cites

      • Trisha Bhowmik, Abhishek Bhadwaj, Avinash Kumar, Bharat Bhushan
      Pages 165-188

  4. Applications

    1. Front Matter

      Pages 189-189
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    2. FPGA Based Implementation of Brent Kung Parallel Prefix Adder

      • K. Gunasekaran, D. Muthukumaran, K. Umapathy, S. A. Yuvaraj
      Pages 191-198

    3. Vehicle Entry Management System Using Image Processing

      • R. Vallikannu, Krishna kanth, L. SaiPavan Kumar, Monisha, Karthik
      Pages 199-210

    4. A Non-negative Matrix Factorization for IVUS Image Classification Using Various Kernels of SVM

      • S. P. Vimal, M. Vadivel, V. Vijaya Baskar, V. G. Sivakumar
      Pages 211-215
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Keywords

About this book

This book covers a domain that is significantly impacted by the growth of soft computing. Internet of Things (IoT)-related applications are gaining much attention with more and more devices which are getting connected, and they become the potential components of some smart applications. Thus, a global enthusiasm has sparked over various domains such as health, agriculture, energy, security, and retail. So, in this book, the main objective is to capture this multifaceted nature of IoT and machine learning in one single place. According to the contribution of each chapter, the book also provides a future direction for IoT and machine learning research. The objectives of this book are to identify different issues, suggest feasible solutions to those identified issues, and enable researchers and practitioners from both academia and industry to interact with each other regarding emerging technologies related to IoT and machine learning. In this book, we look for novel chapters that recommend new methodologies, recent advancement, system architectures, and other solutions to prevail over the limitations of IoT and machine learning.



Editors and Affiliations

  • Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  • Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, India

    Vijender Kumar Solanki

  • Department of Computer Science Engineering, GIET University, Gunupur, India

    Raghvendra Kumar

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