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.

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

Inhalt
Concentration Level of Learner Using Facial Expressions On E-Learning Platform Using IoT-Based Pycharm Device.- IoT-based Machine learning system for Nutritional Ingredient Analyzer for Food.- A Secured Manhole Management System Using IoT and Machine Learning.