The third edition of Internet of Things builds on foundational concepts while incorporating the latest advancements in the field. It expands coverage on sensors, microcontrollers, and communication protocols, including IPv6. New topics such as digital twins, OpenVINO, and the integration of AI/ML in IoT systems are introduced. A dedicated chapter on emerging trends explores innovations like quantum computing, autonomous vehicles, and drones. The edition also enhances discussions on IoT applications, challenges, and machine learning models, making it a comprehensive and up-to-date resource for learners and professionals

Table of Contents
Cover
Title Page
Copyright
Dedication
Preface to the Third Edition
About the Authors
List of Video Content
Chapter 1 Introduction to Internet of Things (IoT)
Learning Objectives
1.1 Introduction and Definition of Internet of Things (IoT)
1.2 IoT Growth and Observations – A Statistical View
1.3 Application Areas of IoT
1.4 Characteristics of IoT
1.5 Things in IoT
1.6 IoT Stack
1.7 Enabling Technologies
1.7.1 Sensors
1.7.2 Cloud Computing
1.7.3 Big Data Analytics
1.7.4 Embedded Computing Boards
1.7.5 Communication Protocols
1.7.6 User Interfaces
1.8 IoT Challenges
1.9 IoT Levels
1.9.1 Level 1
1.9.2 Level 2
1.9.3 Level 3
1.9.4 Level 4
1.9.5 Level 5
Summary
Test Your Understanding
Review Question
Further Reading
Chapter 2 Introduction to Sensors, Microcontrollers and Their Interfacing
Learning Objectives
2.1 Introduction to Sensor Interfacing
2.2 Types of Sensors
2.2.1 MQ-02/05 – Gas Sensor Interfacing with NodeMCU/Arduino
2.2.2 Interfacing the Obstacle Sensor
2.2.3 Interfacing the Heartbeat Sensor
2.2.4 Interfacing the Ultrasonic Sound Sensor
2.2.5 Interfacing the Gyro Sensor
2.2.6 Interfacing the LDR Sensor
2.2.7 Interfacing the GPS
2.2.8 Interfacing the Color Sensor
2.2.9 Interfacing the pH Sensor
2.3 Controlling Sensors through Webpages
2.3.1 Controlling LED with a Webpage
2.4 Microcontrollers: A Quick Walkthrough
2.4.1 8051: An Architectural View
2.4.2 8051: Family Details
2.4.3 Registers in 8051 Microcontroller
2.4.4 Special Function Registers
2.5 Advanced RISC Machine
2.5.1 ARM7: A Quick Overview
2.5.2 ARM Evolution
2.5.3 Features of ARM
2.5.4 Basic ARM Architecture
2.5.5 ARM Organisation Core Data Flow Model
2.5.6 ARM Register Organisation
2.5.7 Current Program Status Register
2.5.8 ARM Family: A Comparison
Summary
Test Your Understanding
Review Questions
Further Reading
Chapter 3 Protocols for IoT
Learning Objectives
3.1 Introduction
3.2 Messaging Protocols
3.2.1 MQTT (Message Queuing Telemetry Transport)
3.2.2 CoAP (Constrained Application Protocol)
3.2.3 Layers of CoAP
3.3 Transport Protocols (Li-Fi, BLE)
3.3.1 Bluetooth Low Energy (BLE)
3.3.2 Li-Fi (Light Fidelity)
3.4 Internet Protocol – IPv6
3.4.1 IPv6 Protocol Format
Summary
Test Your Understanding
Review Questions
Further Reading
Chapter 4 Cloud for IoT – A Detailed Analysis and Understanding
Learning Objectives
4.1 Introduction
4.1.1 Private Cloud Deployment
4.1.2 Public Cloud Deployment
4.1.3 Hybrid Cloud Deployment
4.2 IoT with Cloud – Challenges
4.3 Selection of Cloud Service Provider for IoT Applications – An Overview
4.4 Introduction to Fog Computing
4.5 Cloud Computing – Security Aspects
4.6 A Case Study – How to Use ADAFRUIT Cloud?
4.6.1 Insights to Adafruit cloud
4.7 OpenVINO – The AI and IoT Convergence
4.7.1 Introduction to OpenVINO
4.7.2 Why OpenVINO?
4.7.3 Installing and Setting Up OpenVINO
4.7.4 Prerequisites
4.7.5 Installation Steps on Windows
4.7.6 Installing OpenVINO on Ubuntu
4.7.7 Converting Models to OpenVINO IR Format
4.7.8 Why Convert to OpenVINO IR?
4.7.9 The Conversion Workflow
4.7.10 Step-by-Step Guide to Model Conversion
4.7.11 Using OpenVINO Functions
4.7.12 Benefits of Using OpenVINO IR
4.7.13 Understanding the OpenVINO IR Structure
Summary
Test Your Understanding
Review Questions
Further Reading
Chapter 5 Data Analytics – Visualising the Power of Data from IoT
Learning Objectives
5.1 Introduction
5.2 Data Analysis
5.2.1 Types of IOT Data
5.3 Artificial Intelligence Models
5.3.1 Machine Learning
5.3.2 Deep Learning
5.4 Types of Artificial Intelligence Models
5.4.1 Classification
5.4.2 Regression
5.4.3 Clustering
5.5 Model Building Process
5.5.1 Training the Model
5.5.2 Testing the Model
5.5.3 Validation of the Model
5.6 Modelling Algorithms
5.6.1 Decision Tree
5.6.2 Linear Regression
5.6.3 Logistic Regression
5.6.4 k-Means
5.6.5 Convolutional Neural Networks
5.6.6 Long Short-Term Memory
5.7 Model Performance
5.7.1 Confusion Matrix
5.7.2 R2 Score
5.8 Big Data Platform
5.9 Big Data Pipeline
5.9.1 Kafka
5.9.2 Flink
5.9.3 Data Lake
5.10 Tools and Techniques for Analysing IoT Data
5.10.1 Stream Analysis: Off-Trend Alert
5.10.2 Anomaly Detection
5.10.3 Predictive Maintenance
5.10.4 Digital Twin Analysis
5.10.5 Platforms for IoT Data Analysis
5.11 Integration of AI/ML for Decision Making
5.12 Real Life Projects
5.12.1 Internet of Trains – By Siemens
5.12.2 Machine Condition Monitoring Library – By National Instruments in LabVIEW
5.13 Recommendation in IoT Gadgets
Summary
Test Your Understanding
Review Questions
Further Reading
Chapter 6 Emerging Trends in IoT
Learning Objectives
6.1 Introduction
6.2 Quantum Computing and IoT
6.2.1 Making and Reading Qubits
6.3 Potential Impact of Quantum Computing on IoT
6.3.1 Quantum Key Distribution
6.4 Integration of IoT in Autonomous Vehicles and Drones
Summary
Test Your Understanding
Review Questions
Further Reading
Chapter 7 Applications Building with IoT
Learning Objectives
7.1 Introduction
7.2 Smart Perishable Tracking with IoT and Sensors
7.3 Smart Healthcare – Elderly Fall Detection with IoT and Sensors
7.3.1 Design
7.4 Smart Lavatory Maintenance – Inflight Innovation with IoT
7.4.1 Lavatory Monitoring – How Is It Done Now?
7.5 Smart Water Metering Solutions
7.5.1 Manual Method
7.5.2 Electronic Sensor Monitoring (Nodal Network Method)
7.6 Smart Warehouse Monitoring – Let the Drone Fly for You
7.6.1 Working
7.7 Smart Retail – Possibilities in Retail Sector
7.7.1 Feedback – A Key Tool for Enhancing Customer Relationship
7.8 Smart Driver Assistance Systems – Driver Drowsy Detection – System Detect Highway Hypnosis in Drivers with IoT
7.8.1 Problem Statement
7.8.2 Detecting the Stillness in the Driver
7.8.3 Working of the System
7.9 Collision Impact Measurement – System to Measure the Impact of an Accident with IoT
7.9.1 Problem Statement
7.9.2 How Is It Built?
7.9.3 Architecture of the System
Summary
Test Your Understanding
Review Questions
Further Reading
Annexure A1 Getting Familiarised with Arduino IDE
Annexure A2 Getting Familiarised with Raspberry Pi
Annexure B Analysis and Study of IoT Security: Case Study Examples
Annexure C Sensors and Applications – A Quick Summary
Annexure D Interview Questions and Answers Authors : Shriram K Vasudevan, RMD Sundaram, Abhishek S Nagarajan