Accelerating IoT Development with ChatGPT E-Book

Jun Wen

• Herausgeber: Packt Publishing
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 419

Veröffentlichungsjahr: 2024

Beschreibung

Unlike other IoT books that focus on theory and generic applications, this guide takes a practical approach, empowering you to leverage ChatGPT to build your very first IoT prototype. With over 20 years of experience in wireless and IoT technologies and a background as an instructor, Jun Wen expertly guides you from project kick-off to a fully functional prototype.
The book emphasizes the transformative impact of ChatGPT for IoT, teaching you how to use ChatGPT to generate code for your applications, even with limited coding experience. You’ll be introduced to using PlatformIO IDE within Visual Studio Code and discover the cutting-edge RISC-V architecture, the ESP32 MCU, Arduino-compatible sensors, and integration methods for AWS and the ThingsBoard dashboard. Working through 10 different project examples, including flame detection, smoke detection, and air quality measurement, you’ll become proficient in the functions and specifications of each sensor and the use cases they solve.
By the end of this book, you’ll be ready to undertake IoT development projects, bridging the gap between your ideas and functional creations.

Leseprobe

Accelerating IoT Development with ChatGPT

A practical guide to building your first IoT project using AI-assisted coding and cloud integration

Jun Wen

Accelerating IoT Development with ChatGPT

Copyright © 2024 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

The author acknowledges the use of cutting-edge AI, such as ChatGPT, with the sole aim of enhancing the language and clarity within the book, thereby ensuring a smooth reading experience for readers. It’s important to note that the content itself has been crafted by the author and edited by a professional publishing team.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Preet Ahuja

Publishing Product Manager: Vidhi Vashisth

Book Project Manager: Ashwin Dinesh Kharwa

Senior Editor: Mudita S

Technical Editor: Arjun Varma

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First published: August 2024

Production reference: 1060824

Published by Packt Publishing Ltd.

Grosvenor House

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Birmingham

B3 1RB, UK.

ISBN 978-1-83546-162-4

www.packtpub.com

To my loving wife, Yajing Wu. Her steadfast support and constant encouragement have been my anchor during this challenging endeavor, serving as a beacon of light that guided me through the daunting times.

To my beloved children, Suixin Wen and Ryan Wen. Their presence in my life fuels my drive, and their boundless curiosity inspires me daily to strive to be the best role model I can be.

To my parents, Mrs. Linzhu Tan and Mr. Jiwu Wen, whose love and guidance have shaped me into the person I am today.

– Jun Wen

Contributors

About the author

Jun Wen, the founder of AI Discovery Academy, is a passionate evangelist for AI enlightenment education among school students. With more than twenty years of experience in technology development, Jun has specialized in a wide range of industrial domains, including 4G/LTE, 5G, Wi-Fi, BLE, LoRaWAN, IoT, robotics, and AI. He has previously held senior product management positions at Fortune 500 companies such as Amazon, Cisco, and Motorola. Jun holds a Master of Science degree from Brown University and is an AWS Certified Solutions Architect - Professional. His passion extends to creating IoT innovations, utilizing platforms including Arduino, Raspberry Pi, RISC-V, and the AWS cloud, and finding practical applications for AI.

I want to express heartfelt thanks to my beloved wife, Yajing Wu, and my children, Suixin Wen and Ryan Wen, for their support during the writing of this book. Gratitude also goes to my Brown University’s Master’s in Technology Leadership Program Cohort 6 friends and professors, whose enthusiasm and insights sparked my journey. Finally, I appreciate Ashwin Dinesh Kharwa, Mudita, and Vidhi Vashisth from the Packt team for their professional service.

About the reviewers

Bob Lo has been working in networking technologies for over 30 years, with 25 years of them spent developing networking software at Cisco Systems. He is highly experienced in network/protocols, L2/L3, switches, routers, ASIC design, network drivers, embedded devices, and more. In the last 10+ years at Cisco, he has led a big team across the globe developing and innovating the latest IoT technologies. He received his BS in computer science from the National University of Singapore and an MSc in computer science from North Dakota State University. He has also worked with researchers and professors from the University of Illinois, Urbana-Champaign, on cutting-edge network technologies.

Sebastián Viviani is an electronics “all-rounder.” His passion for technology started at the age of 6, when he got a kids’ book about lights and switches, followed by a Commodore 64 and writing his first programs in BASIC.

The learning journey has never stopped since. He graduated as an electronics engineer from U.T.N. (Argentina) and has worked for several industry leaders including Cisco, Renesas, Quectel, and AWS throughout a 25-year career in very diverse hardware and software roles. He has his own lab at home (including a 3D printer), which some university colleagues praised as “more complete and prepared than the ones we had when we studied.”

His other passions are his family, his dog, and playing and coaching underwater hockey.

It amazes me how much things have changed since I first connected a lightbulb, a switch, and a battery, or wrote “10 PRINT CHR$(147)”.

Coding on a computer was for “hackers” then; these days kids learn programming at primary school.

Making a 1-layer PCB required drawing skills and handling perchloric acid; today you can get a 4-layer design assembled and delivered to your door.

And learning? There are so many resources at “clicking” distance.

Love it, let’s do more!

Table of Contents

Preface

Part 1: Understanding IoT Fundamentals

1

IoT Essentials, All You Should Know

The evolving definition of IoT

Deployed from fixed to mobility

Mobility from a local area to a wide area

Presence from city to barren fields

Throughput from Mb/s to Gb/s

Battery life from days to years

Networking from point-to-point and point-to-multipoint to mesh and star topologies

Intelligence at edge node

AI and ML

Addressable markets

Residential

Commercial and business

Neighborhood and campus

Cities

Rural areas

Industries

How IoT impacts us

Living comfort and safety improvement

Operational efficiency improvement

Environmental protection improvement

Industrial productivity improvement

Summary

Further reading

2

IoT Network, the Neural System of Things

IoT networks at home

Home Wi-Fi

BLE

Thread

IoT networks on campuses and in buildings

Enterprise Wi-Fi

Thread mesh

Private LoRaWAN network

No one-size-fits-all approach

IoT networks in cities

Cellular network

Public LoRaWAN network

IoT networks in rural areas

Private LoRaWAN network

LEO network

Summary

3

IoT End Devices, the Neuron Cells of an IoT System

Device types

Installing indoors versus outdoors

Powering via external supply versus batteries

Connected by wire versus wireless

The need for edge computing

Hardware architecture

MCUs

Roles

Key features

Critical components

Off-the-shelf MCU

DIY-friendly MCU

Peripherals and interfaces

GPIO

SPI

I2C

UART

USB

SDIO

ADCs

DACs

PWM outputs

JTAG

Timers

Real-time clock

Sensors and actuators

Sensors

Actuators

Common pins on sensors

Understanding sensor specifications

Summary

4

Wireless Connectivity, the Nervous Pathway to Delivering IoT Data

10 knowledge points about wireless data communication

OSI model

Signal processing

Electromagnetic waves

Frequency and wavelength

dB, dBm, and dBi

Signal strength and quality

Shannon’s Law and theoretical channel capacity

Modulation

Antenna technology

Propagation distance

BLE

History and current status

Bluetooth 1.0 to 3.0 – the age of Bluetooth Classic

Bluetooth 4.0 to 5.3 and beyond – the era of BLE

Wi-Fi

History and current status

Wi-Fi 6

Wi-Fi 6E

Wi-Fi 7

4G/LTE and 5G

History and current status

NB-IoT

LTE CAT-M

Standard organization

Ecosystem players

Summary

5

The Cloud, IoT’s “Superpower Brain”

Important tips

Why is the cloud essential for IoT?

The pain point of IoT before the cloud

The impact of the cloud

Integrating IoT with the cloud

Device management

Data ingestion

Communication protocols between IoT devices and the cloud

MQTT

LwM2M

CoAP

AWS for IoT

AWS IoT Core

AWS IoT Device Management

AWS IoT Device Defender

AWS IoT Analytics

AWS Lambda

AWS Kinesis

AWS DynamoDB

AWS QuickSight

Summary

Part 2: Utilizing AI in IoT Development

6

Applying ChatGPT in the IoT Innovation Journey

Important tips

Reshaping the future with AI

Utilizing ChatGPT in IoT development process

Interacting with ChatGPT properly

Best practices for beginner IoT projects

Prompt framework options

Best practice prompt examples

Generating code snippets on ESP32

Summary

7

Recommendations to Start Your First IoT Project

Technical requirements

Thinking big and starting small

Reaching out for the low-hanging fruits first

Summary

8

10 Beginner-Friendly IoT Projects with ChatGPT Prompts

Technical requirements

Project 1 – temperature and humidity measurement

Specifications

Applications

Prompt to ChatGPT

Code example

Project 2 – flame detection

Specifications

Analog output values

Applications

Prompt to ChatGPT

Code example

Project 3 – PIR motion detection

Specifications

Applications

Prompt to ChatGPT

Code example

Project 4 – gas detection

Specifications

Analog output values

Applications

Prompt to ChatGPT

Code example

Project 5 – distance measurement

Specifications

Applications

Prompt to ChatGPT

Code example

Project 6 – tilt detection

Specifications

Applications

Prompt to ChatGPT

Code example

Project 7 – vibration detection

Specifications

Applications

Prompt to ChatGPT

Code example

Project 8 – collision detection

Specifications

Applications

Prompt to ChatGPT

Code example

Project 9 – soil moisture detection

Specifications

Applications

Prompt to ChatGPT

Code example

Project 10 – magnetic change detection

Specifications

Applications

Prompt to ChatGPT

Code example

Summary

9

Using AI Tools to Draw Application Flow Diagrams

Using diagrams for a better application journey

Processing data locally

Establishing an internet connection

Sending sensor data to Cloud

Data processing on the cloud

Summary

Part 3: Practicing an End-to-End Project

10

Setting Up the Development Environment for Your First Project

Technical requirements

Installing Visual Studio Code (VS Code)

Setting up PlatformIO IDE

Installing other coding assistance extensions

Creating your first project under PlatformIO

Summary

11

Programming Your First Code on ESP32

Designing the application’s local logic

Creating a flow diagram with ChatGPT

Building a device hardware prototype

Instructing ChatGPT to generate C++ code

Code examples

Using PlatformIO to program code on the ESP32

Summary

12

Establishing Wi-Fi Connectivity

Designing Wi-Fi access logic

Creating the Wi-Fi access flow diagram

Instructing ChatGPT to generate code

Code examples

Validating internet access on ESP32

Summary

13

Connecting the ESP32 to AWS IoT Core

Technical requirements

Understanding the approach to connect the ESP32 to AWS IoT Core

Provisioning the ESP32 in AWS IoT Core

Creating an AWS credential header file on the ESP32

Instructing ChatGPT to produce TLS code on the ESP32

Code examples

Validating access status on the ESP32

Summary

14

Publishing Sensor Data to AWS IoT Core

Technical requirements

Sending sensor data through MQTT Publish

Constructing an MQTT Publish topic and payload in ESP32

Code examples

Validating the delivered sensor data

Summary

15

Processing, Storing, and Querying Sensor Data on AWS Cloud

Creating a customer-managed policy

Task 1 – abnormal event process

Configuration steps

Creating a message routing rule

Creating a Lambda function

Creating an SNS topic

Programming the Lambda function

Task 2 – data storage and querying

Creating IoT Analytics resources

Creating a second message routing rule

Running a data query

Summary

16

Creating a Data Visualization Dashboard on ThingsBoard

Technical requirements

Integrating the AWS cloud with ThingsBoard

Task 1 – Provisioning a ThingsBoard agent with AWS

Task 2 – Creating the data converter and integrating it with ThingsBoard

Task 3 – Producing a real-time dashboard with ThingsBoard

Summary

Index

Other Books You May Enjoy

Preface

Are you overflowing with innovative ideas, yet finding it difficult to navigate the intricacies of software coding? Utilize Artificial Intelligence (AI) to expedite your Internet of Things (IoT) development journey!

AI is a transformative force that is reshaping our lives, societies, and industries. This book guides beginners on how to use AI’s coding abilities to construct their first end-to-end IoT prototype. It covers everything from drawing an application flow diagram, crafting the hardware prototype, producing embedded C++ example code, establishing Wi-Fi connectivity, and accessing Amazon Web Services (AWS), to creating a real-time dashboard on ThingsBoard Cloud.

The book ensures a smooth learning curve, starting from the IoT fundamentals, architecture, key elements, recommendations, and best practice examples, to a thorough step-by-step hands-on project illustration. A distinguishing feature of this book is its exploration of recent AI advancements and their transformative impact on the IoT world. It emphasizes ChatGPT prompt skills specifically tailored for IoT projects and presents a detailed framework for crafting effective ChatGPT prompts. This empowers you to harness this powerful tool in your IoT endeavors, overcoming barriers related to inadequate software coding skills or experience.

You will be introduced to the PlatformIO IDE on Visual Studio Code, one of the most popular embedded software development environments. Additionally, you’ll learn about the cutting-edge RISC-V architecture MCU – ESP32, Arduino-compatible sensors, and integration methods for the AWS cloud and ThingsBoard dashboard.

As part of the learning approach, I provide the functional codes generated by ChatGPT and prompting instruction examples in the GitHub repo for this book.

By the end of this book, you will be equipped to build your first successful IoT prototype, effectively bridging the gap between your innovative ideas and functional creations.

Who this book is for

This book is designed for beginners who are eager to explore the world of IoT technology but face obstacles due to limited experience in embedded software coding, particularly in C++. The primary audience includes middle- to high-school and undergraduate students, hobbyists interested in smart home applications, hardware enthusiasts, DIY creators, startup entrepreneurs, educators, and professionals from non-technical backgrounds. Often, their innovative potential is hindered by the complexity of software coding. Fortunately, AI can serve as an intelligent assistant, offering example code to accelerate the development of IoT prototypes.

This book assumes that readers have a basic understanding of electronic physics, knowledge of internet and IP connectivity, a rudimentary grasp of software coding structure, and familiarity with basic cloud concepts.

What this book covers

Chapter 1, IoT Essentials, All You Should Know, offers an introduction to the core concepts and components that define IoT technologies.Chapter 2, IoT Network, the Neural System of Things, gives you a detailed look at the infrastructure and architecture of IoT systems.Chapter 3, IoT End Devices, the Neuron Cells of an IoT System, helps you understand the role and functionality of the devices at the edge of IoT networks.Chapter 4, Wireless Connectivity, the Nervous Pathway to Delivering IoT Data, explores the wireless technologies that convey data within IoT systems.Chapter 5, The Cloud, IoT’s “Superpower Brain”, discusses the capabilities and advantages of cloud computing in enhancing and scaling IoT applications.Chapter 6, Applying ChatGPT in the IoT Innovation Journey, explores how AI can assist in conceptualizing, planning, and executing IoT solutions, emphasizing the transformative impact of AI on the innovation process.Chapter 7, Recommendations to Start Your First IoT Project, provides you with practical advice on initiating your first IoT projects.Chapter 8, 10 Beginner-Friendly IoT Projects with ChatGPT Prompts, details 10 projects using ChatGPT to various extents, showcasing how AI can streamline the development process, from sensor integration to data handling.Chapter 9, Using AI Tools to Draw Application Flow Diagrams, teaches you about the use of AI-driven tools to create IoT application flow diagrams.Chapter 10, Setting Up the Development Environment for Your First Project, provides a detailed guide on how to establish a development environment using Visual Studio Code and the PlatformIO IDE.Chapter 11, Programming Your First Code on ESP32, walks through ChatGPT-assisted C++ programming on an ESP32 microcontroller to read sensor data locally.Chapter 12, Establishing Wi-Fi Connectivity, explains the steps to configure the ESP32 to connect to a Wi-Fi network.Chapter 13, Connecting the ESP32 to AWS IoT Core, illustrates the configuration of AWS IoT Core settings, certificate management, and how to establish a secure MQTT/TLS connection from the ESP32.Chapter 14, Publishing Sensor Data to AWS IoT Core, guides you through the process of setting up sensors, collecting data, and publishing it to the cloud.Chapter 15, Processing, Storing, and Querying Sensor Data on AWS Cloud, has you practicing tasks to process data via Python functions on AWS Lambda and store and query data using AWS IoT Analytics.Chapter 16, Creating a Data Visualization Dashboard on ThingsBoard, explains how to integrate the AWS cloud with ThingsBoard, set up real-time data feeds, and build your own dashboards.

To get the most out of this book

You will need to have an understanding of the basics of software development IDE tools, open source hardware, and the cloud.

Software/hardware covered in the book

Operating system requirements

PlatformIO IDE extension on VS Code

macOS and Windows

ESP32 MCU

Arduino-compatible sensors

AWS services

MacOS, Windows, Linux(Any)

ThingsBoard Cloud

MacOS, Windows, Linux(Any)

Download the example code files

You can download the example codes and ChatGPT prompting files for this book from GitHub at https://github.com/PacktPublishing/Accelerating-IoT-Development-with-ChatGPT. If there’s an update to the code, it will be updated in the GitHub repository.

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “Utilizing build_flags in this context offers several benefits.”

A block of code is set as follows:

 1. [env:esp32-c3-devkitc-02]  2. platform = espressif32  3. board = esp32-c3-devkitc-02  4. framework = arduino  5. monitor_filters = esp32_exception_decoder, colorize  6. monitor_speed = 115200  7. build_src_filter = +<../../src/>  +<./>  8. board_build.flash_mode = dio  9. build_flags =  10.     -DARDUINO_USB_MODE=1 11.     -DARDUINO_USB_CDC_ON_BOOT=1 12.     -w 13. lib_deps =  14.     adafruit/DHT sensor library@^1.4.6 15.     adafruit/Adafruit Unified Sensor@^1.1.14

Any command-line input or output is written as follows:

pio platform install espressif32

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “The ESP32 will reboot and you can locate the Serial Monitor button.”

Tips or important notes

Appear like this.

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Part 1: Understanding IoT Fundamentals

In this section, you will explore in depth the fundamental components of IoT systems, using an enlightening analogy with the human neural system to illustrate the functions and interconnected nature of these technologies. You will gain a solid understanding of the essential concepts that underpin the IoT ecosystem, learning about the critical roles of IoT networks and end devices, and the various options for wireless connectivity that act like the nerves in a body, delivering data seamlessly across distances. Moreover, you will study how the cloud functions as the brain of IoT systems, providing substantial computing power and vast storage capabilities to process and manage data efficiently. This section sets the stage for a deeper appreciation of how IoT operates within and interacts with various applications.

This part contains the following chapters:

Chapter 1, IoT Essentials, All You Should KnowChapter 2, IoT Network, the Neural System of ThingsChapter 3, IoT End Devices, the Neuron Cells of an IoT SystemChapter 4, Wireless Connectivity, the Nervous Pathway to Delivering IoT DataChapter 5, The Cloud, IoT’s “Superpower Brain”

1

IoT Essentials, All You Should Know

In this chapter, you will go through the concepts and definitions of the Internet of Things (IoT) as defined by the industry, as well as its remarkable evolution milestones since its inception. By understanding the historical context and outlook of IoT, you will gain valuable insights into its significance and potential applications in the market.

Furthermore, you will zoom into the wide-ranging market that IoT addresses and various industries and sectors where its impact is most prominent. From healthcare to transportation, from smart homes to industrial automation, IoT has revolutionized the way we live, work, and interact with our environment. You will explore these real-world applications and the transformative power of IoT in shaping our society.

By the end of this chapter, you will have acquired a solid foundation and a well-rounded understanding of essential concepts and knowledge required to embark on your journey into the intricate world of IoT. You will be fully prepared to explore the details and intricacies of IoT as we dive deeper into the subject matter in subsequent chapters of this book.

In the engineering projects in Chapter 11, with the assistance of ChatGPT, you will learn to program C++ code on an ESP32 microcontroller unit (MCU), send diverse sensors’ data through your home Wi-Wi network, and store, analyze, and visualize live and dynamic sensor data on the Amazon Web Services (AWS) cloud. In this chapter, we will acquaint ourselves with these terms so as to build the right foundation.

This chapter covers the following topics:

The evolving definition of IoTAddressable marketsHow IoT impacts us

The evolving definition of IoT

IoT has never stopped evolving its definition since its debut in the 1990s.

According to Gartner (https://www.gartner.com/en/information-technology/glossary/internet-of-things), the concept of IoT is defined as follows:

“The Internet of Things (IoT) is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.”

However, as of today, this definition may seem a little cliché and out of date. Initially, the notion of IoT was specifically designed to support traditional machine-to-machine (M2M) communication within manufacturing plants, where it was constrained by wired copper twists, Ethernet cables, and power supply cords. It was typically deployed in a fixed scenario with no mobility, scalability, elasticity, power consumption, and cost efficiency.

Since 1999, when IoT was officially named by Kevin Ashton, MIT’s Executive Director of Auto-ID Labs, it has been making significant strides in various areas. This is thanks to breakthroughs in industrial innovations such as silicon chipsets, wireless technologies, and cloud services. IoT no longer operates solely on a local network but goes beyond massive geographical areas on a vast scale. IoT is now expanding its reach beyond homes, residential and commercial areas, campuses, and cities, and is even reaching deserts, barren zones, oceans, and aerospace.

Looking back, the evolution of IoT has experienced several remarkable leaps since its inception. These leaps include improvements in deployment coverage, power consumption, cost structure, and architecture, as described next.

Deployed from fixed to mobility

The year 2000 was a pivotal moment for the IoT explosion. It marked a significant milestone in the advancement of IoT applications. This was made possible by the industrial innovation of low-cost 802.11 Wi-Fi networks, which were rapidly and widely adopted in both homes and enterprises. The introduction of the 802.11 Wi-Fi network brought about a revolution for IoT devices. They were no longer solely reliant on cables (although a power cable might still be necessary), but could now benefit from the convenience of mobility. This groundbreaking development enabled IoT devices to be seamlessly connected through wireless connectivity in residential, commercial, and business spots, whether they were stationary or on the move. This was a monumental shift in the IoT landscape, paving the way for even greater possibilities and innovations in the future.

802.11 Wi-Fi is not the only option dominating the home and enterprise spaces; there are other new players that provide local mobility as well, including the 802.15.1 family of Bluetooth and Bluetooth Low Energy (BLE) and the 802.15.4 family comprising ZigBee, Thread, and Matter, and Sub-GHz Z-Wave.

Mobility from a local area to a wide area

The year 2005 was a significant catalyst for boosting IoT with the introduction of service provider’s (SP) 3G cellular networks, including Code-Division MultipleAccess (CDMA) and the Universal Mobile Telecommunications System (UMTS). These networks offered faster and wider area mobility connectivity, enabling a greater variety of devices to connect to the internet at will. This breakthrough has opened up numerous opportunities for IoT applications in various areas, including beyond residential and campus, spanning cities and rural areas. Some examples of these applications include fleet management, smart agriculture, and asset tracking.

Heading into the year 2010, the introduction of 4G/Long-Term Evolution (LTE) technology accelerated the growth of IoT by providing higher data rates. In 2020, the era of 5G brought even more rapid progress. As a result, IoT has penetrated almost every population corner of the world, transforming the way we live and work.

Presence from city to barren fields

The wide area expansion of the IoT footprint is not solely tied to the coverage of traditional 4G/LTE and 5G cellular networks provided by SPs. In less populated areas such as barren fields, forests, mountains, offshore, and even oceans, where SPs are hesitant to offer coverage due to unwise investment, industries are adopting new wireless technologies to provide IoT coverage. Examples of such technologies include low-power wide area networks (LPWANs), such as Long-Term Evolution Category M (LTE-M), Narrow Band Internet of Things (NB-IOT), long-range wide-area network from LoRa Alliance (LoRaWAN), Sigfox, and Low Earth Orbit (LEO) networks, such as SpaceX Starlink and Amazon Kuiper, which do not rely ontraditional SPs.

LTE-M and NB-IoT are both derived from SPs’ cellular networks. Unlike traditional 4G/LTE and 5G technologies, which strive to provide high data rates to mobile phones, LTE-M and NB-IoT prioritize wider coverage and superior lower power consumption for battery-powered IoT devices with reduced receiving sensitivity, bandwidth, and data rates, which are distinct from conventional 4G/LTE and 5G networks.

LoRaWAN is an industrial standard supported by the LoRa Alliance. It is designed to provide long-range coverage and low power consumption for various IoT applications. By operating on unlicensed spectrum (such as the band allocated for Industrial, Scientific, and Medical (ISM)), LoRaWAN offers accessibility to a wide range of users who are interested in utilizing it for their IoT projects. This standard ensures that devices can communicate over long distances while consuming minimal power, making it an ideal choice for many IoT scenarios.

SpaceX Starlink and Amazon Kuiper LEO satellite constellations will be instrumental in facilitating the deployment of IoT applications in those areas. With their extensive coverage and high-speed connectivity, these satellite networks will empower various IoT devices and enable seamless data transmission, enhancing communication and connectivity for users in remote and underserved regions. Furthermore, the integration of SpaceX Starlink and Amazon Kuiper LEO with IoT technologies will unlock new possibilities for industries such as agriculture, transportation, and environmental monitoring, revolutionizing the way we collect, analyze, and utilize data for improved decision-making and efficiency.

Throughput from Mb/s to Gb/s

When IoT was initially designed for M2M communication in manufacturing plants, it was commonly accomplished using RS232 or RS485 wire interfaces. The twisted wire limited the data rate from a few hundred kilobits per second up to 10 Mb/s. However, with the emergence of advanced technologies such as Wi-Fi 5, Wi-Fi 6, 4G/LTE, and 5G, the maximum data rate has significantly increased to a range of over 100 Mb/s to 1 Gb/s. This tremendous enhancement in data transfer capabilities has opened up a multitude of new possibilities for IoT applications.

One of the major benefits of these advancements is the ability to support high-definition video surveillance. With the increased data rate, IoT devices can now transmit high-quality video feeds, allowing for better monitoring and security. This is particularly useful in areas such as public spaces, where surveillance is crucial for ensuring safety.

Another exciting possibility enabled by these advancements is the immersive experiences they can provide. With the higher data rate, IoT devices can now support technologies such as augmented reality (AR) and virtual reality (VR). This means that users can have more interactive and engaging experiences, whether it’s through AR apps that overlay digital information onto the real world or VR simulations that transport them to virtual environments.

Battery life from days to years

Chasing a high data rate for IoT applications is not always necessary. While some IoT applications do require high data rates, it is important to consider that there are also many instances where external power input is not available. In these cases, the IoT applications must be powered by batteries that need to last for several years. As a trade-off, these applications can accept very low data rates ranging from a few bytes per second to a few hundred kilobits per second, and have higher latency of up to a few seconds.

Recognizing this need, in addition to continue exploring high data rate technology, industries also shifted their focus toward developing technologies offering low data rates and low power consumption. This has led to the emergence of various wireless technologies that cater to these requirements. LoRaWAN, which was mentioned earlier, is one such example. Other notable technologies include NB-IOT and LTE-M, which are offered by SPs through their cellular networks. Additionally, there is Bluetooth Low Energy Long Range (BLE-LR), and 802.11 ah Wi-Fi Halow.

Networking from point-to-point and point-to-multipoint to mesh and star topologies

Traditional M2M communication, such as RS232 (point-to-point) and RS485 (point-to-multipoint) has limitations when it comes to the scale of nodes and communication distance. In order to overcome these limitations and expand IoT connectivity beyond manufacturing plants to residential, community, city, and rural areas, industries have developed mesh topologies. These mesh topologies connect IoT devices as child nodes and bridge to each other to deliver data to parent nodes, enabling a wider coverage area. Examples of mesh topologies include BLE and ZigBee meshes for smart homes and Wi-SUN meshes for utility smart metering.

By implementing mesh topologies, the scale and coverage of IoT networks have been significantly extended. However, this expansion also brings forth new challenges, such as increased networking complexity, less efficient usage of radio resources, and higher device power consumption. Despite these challenges, the benefits of mesh topologies in terms of connectivity and coverage make them a viable solution for some specific use cases, as mentioned previously.

To address these challenges and meet the growing demands of industries, various networking approaches have been explored. One widely used option is the star topology, which offers networking simplicity, such as LoRaWAN, NB-IOT, LTE-M, and LEO satellite networks.

In a star topology, the IoT device can easily connect to an access device with just one radio hop. This access device can take the form of a LoRaWAN gateway, the base station (that is, eNodeB ) in a cellular network, or even a LEO satellite. This type of networking is known for its Plug and Play (PnP) functionality, making it easy to set up and use. Furthermore, it allows IoT devices to conserve power by entering deep sleep mode when they are not actively executing tasks, thereby reducing overall power consumption compared to a mesh topology where every device needs to be always on to bridge the network.

Intelligence at edge node

In the era of M2M communication, IoT devices, known as slave nodes, collect and transmit untapped protocol data to their upstream nodes, such as the RS232 or RS485 master node. The main function of these IoT devices is to forward raw data without locally possessing intelligence. However, industries have recognized the benefits of developing local computing capabilities for IoT devices. This includes using containers on top of the device OS, Google TensorFlow, and AWS IoT Greengrass.

Edge intelligence provides significant advantages to IoT by processing untapped data locally using predefined algorithms instead of sending all raw data upstream indiscriminately. This approach leads to savings in backhaul bandwidth consumption, reduced application decision latency, and offloading work from the cloud.

While the benefits of edge intelligence are significant, it is important to note that it may not be suitable for every IoT application. This is due to increased requirements for IoT device hardware design, such as the need for a powerful processor, larger memory, and high-power consumption.

AI and ML

The evolution of intelligence does not stop at IoT devices alone. Industries are continuously pushing artificial intelligence (AI) and machine learning (ML) capabilities into the IoT cloud. By leveraging AI and ML algorithms, cloud platforms such as AWS and Microsoft Azure empower businesses to analyze and make sense of vast amounts of IoT data. These platforms provide advanced tools and services that enable organizations to develop intelligent applications, automate processes, and make data-driven decisions.

One key advantage of integrating AI and ML into the cloud is the scalability and flexibility it offers. With the ability to scale resources on demand, businesses can easily handle the increasing volume, velocity, and variety of IoT data. This ensures that organizations can process and analyze data in real time, enabling them to respond quickly to changing conditions and make informed decisions.

Furthermore, AI and ML algorithms can uncover patterns, trends, and correlations in IoT data that might otherwise go unnoticed. This allows businesses to gain valuable insights into customer behavior, operational efficiency, and predictive maintenance, among other things. By leveraging these insights, organizations can optimize processes, improve customer experiences, and drive innovation.

In addition to processing and analyzing IoT data, cloud platforms also provide the infrastructure and tools needed to train and deploy AI models. This enables businesses to build intelligent applications that can learn and adapt over time, improving their performance and accuracy. With services such as Amazon SageMaker and Azure Machine Learning (AML), organizations can easily develop, train, and deploy AI models without the need for extensive computational resources or expertise.

Moreover, cloud-powered AI and ML bring the benefits of accessibility and affordability. By leveraging the cloud, businesses of all sizes can access cutting-edge AI and ML capabilities without the need for significant upfront investments in infrastructure or specialized talent. This democratization of AI allows organizations to level the playing field and compete in an increasingly data-driven world.

With its exponential growth and rapid expansion from its initial purpose, IoT has ambitiously embraced and integrated various innovative technologies within a relatively short span of time. Its primary objective is to cater to an extensive market, extending beyond just homes and campuses to industries, cities, and even rural areas. By doing so, IoT seeks to revolutionize and transform the way we live, work, and interact with technology on a global scale, which proactively extending its addressable markets from residential, neighborhood, campus, city and rural areas. Let’s learn more about it next.

Addressable markets

When exploring the IoT addressable market, there are several approaches available to make segmentation possible, such as differentiating from technology specifications, application designs, business models, or applicable verticals. However, this chapter will focus on an easy-to-understand market segmentation approach based on the application’s premises. This approach can be especially beneficial for beginners to precisely identify their target market for innovation. By understanding where applications are being deployed, beginners can gain valuable insights into the specific needs and challenges of various locations.

Residential

A smart home is a convenient and accessible environment for beginners to practice their first IoT innovations. It provides a low-hanging fruit scenario for newbie developers to experiment with their innovation.

One major advantage of a smart home is its easy access to existing home Wi-Fi networks, eliminating the need for additional network infrastructure. Additionally, the power supply is not a concern as IoT devices can be powered by DC power from wall sockets. Even for IoT devices that require batteries, replacing them is effortless when needed.

There are already several major vendors that offer a central hub solution for hosting smart home applications, including Google Home, Amazon Alexa, and Apple HomeKit. Beginners can follow these vendors’ specifications to ensure compatibility and seamless integration of their IoT innovations into mobile applications and cloud platforms. This is particularly important for the recent smart home interworking protocols of If This Then That (IFTTT) and Matter.

The following is a list of the top 10 popular smart home applications:

Indoor temperature and humidity monitoringSmoke/flame detectorsSecurity camerasSmart lighting/bulbsSmart thermostatsSmart locksSmart doorbellsSmart wall power socketSmart garage door openerSmart trash bin

Without a doubt, the primary focus for IoT deployment is at home due to its significant market scale and easy go-to-market (GTM) approach. In comparison, IoT applications designed for commercial and business markets present higher requirements for product quality, management, reliability, and security, along with the potential for higher profit margins.

Security concerns pertaining to the use of IoT applications within the home environment primarily revolve around potential breaches of privacy. These concerns arise from the fact that these IoT devices, which are increasingly becoming pervasive in our daily lives, are often connected to the internet and, therefore, carry the inherent risk of sensitive personal information being exposed to unauthorized individuals or entities.

Commercial and business

IoT applications in commercial and business locations can be easily extended from smart home applications. For instance, a smoke detector can be used in both homes and business buildings. However, accessing enterprise Wi-Fi networks poses challenges due to the security mechanisms implemented for enterprise-grade access. While accessing a home Wi-Fi network requires simply using the Wi-Fi service set identifier (SSID) and password, accessing an enterprise Wi-Fi network requires support for Wi-Fi Protected Access 2 (WPA2), 802.1X Extensible Authentication Protocol (EAP), and Remote Authentication Dial-In User Service (RADIUS) authentication.

When it comes to installing and managing IoT devices within a business location, there are two usual challenges. Firstly, finding an external power supply above the floor is not always easy. You cannot simply lay power cords inside the building as you please. Secondly, if you are deploying hundreds of devices, you will need to create a management solution to effectively monitor and manage them.

The following is a list of the top 10 popular IoT applications within commercial and business locations:

Indoor temperature and humidity monitoringSmoke/flame detectorsSecurity camerasSmart lighting/bulbsSmart Heating, Ventilation, and Air Conditioning (HVAC) managementSmart parkingAsset tracking and inventory managementWater leakage detectionBuilding intrusion detectionOccupancy detection

The IoT applications designed for commercial and business markets mainly focus on indoor deployment, while at its adjacent segment, penetrating the community and campus market has to overcome challenges from the deployment of IoT applications in open spaces, the outdoor case, which raises the bar to the product’s robustness and reliability.

Securing IoT applications in commercial and business environments involves regular device updates, strong authentication, secure boot processes, and hardware security modules (HSMs) to protect devices. Network security is enhanced through encryption, network segmentation, firewalls, and intrusion detection systems (IDSs). Data security measures include encrypting data at rest and in transit, strict access controls, and data minimization. Cloud security involves secure APIs, compliance with regulations, and regular security audits. Physical security measures include access control and tamper detection.

Neighborhood and campus

Most IoT applications in neighborhood and campus settings are primarily focused on outdoor use cases. The process of building IoT applications in neighborhood and campus environments poses greater challenges compared to commercial and business premises. These challenges include the need for outdoor ruggedized design, reliable wireless connectivity, and power supply availability.

When IoT devices come to outdoor hardware designs, they adhere to the Ingress Protection standard (IP grade). This standard ensures that the hardware is capable of withstanding various environmental factors and conditions, such as dust, water, and extreme temperatures. By following the IP grade, manufacturers can ensure that their outdoor hardware is durable, reliable, and suitable for outdoor deployments. Whether it is for smart city infrastructure, rural area applications, or neighborhood and campus settings, outdoor hardware needs to be designed with the utmost consideration for protection and resilience. The details will be explained in the Device types section of Chapter 3. Wireless connectivity in the neighborhood and campus poses a challenge. Ideally, a public 802.11 Wi-Fi network should be able to meet the requirements. However, IoT devices must support WPA2, 802.1X EAP, and RADIUS authentication, as with the security access mechanism used in enterprise networks. In case a public 802.11 Wi-Fi network is not available, alternative networks should be explored.

One option is to access the 4G/LTE or 5G network provided by local SPs. To do this, your IoT device module needs to have a compatible cellular module. You will also need to purchase a SIM card and data plan from the SPs. Another option is to access the LoRaWAN network hosted by local public LoRaWAN operators. The worst-case scenario is that you build your own private LoRaWAN network, although this option can be complex and costly.

Another major challenge in neighborhood and campus settings is the availability of an external power supply for IoT devices. It can be difficult to find an accessible power source or to lay down power cables to the installation location. To address this issue, it is recommended to design IoT devices with low power consumption, incorporating solar panels or rechargeable batteries.

The following is a list of the top 10 popular IoT applications within neighborhood and campus locations:

Smart pathway lightingSmoke/flame detectorsSecurity camerasSmart parkingSmart water irrigationSmart health careAsset/pet trackingSmart waste managementWireless emergency buttonFacility security

The neighborhood and campus markets need to support IoT applications either by fixed installations or local mobility within a limited area. In most cases, enterprise Wi-Fi and private LoRaWAN networks are the preferred cost-effective options. 4G/LTE and 5G can also be considered, but cost is always the top concern. For the city market, in addition to cost, wide area mobility, seamless coverage, and business scalability also matter.

In terms of security considerations, neighborhood and campus spaces are significantly more vulnerable to potential attacks. This increased vulnerability is due to the openness of these spaces, which allows users to bring their own IoT devices. For example, a user might bring a device such as a pet tracking tag. These devices, while useful and convenient, can inadvertently introduce security risks into the network, thereby increasing the potential for unauthorized access and attacks. Therefore, it’s crucial to have robust security measures in place to mitigate these risks and protect the network.

Cities

When IoT applications are deployed in cities, they can be seen as an expanded version of community and campus environments, but on a larger scale and with more challenges. The main challenges are ensuring wide area mobility, seamless coverage, and business scalability. To address these challenges, one option is to utilize a 4G/LTE or 5G network provided by local SPs or access the public LoRaWAN network from local LoRaWAN operators.

The following is a list of the top 10 popular IoT applications within cities:

Smart street lightingNoise detectionSecurity camerasSmart parkingSmart water irrigationConnected carAsset/pet trackingSmart waste managementAir quality monitoringFacility security

The city market is the most complex and challenging segment, especially due to its geographic space. The rural market is also a challenging one, as it often lacks cellular network coverage despite having IoT applications deployed over large areas.

Security considerations for IoT deployment in cities are also a multifaceted challenge. As cities become increasingly interconnected and reliant on IoT technologies for their functioning, the importance of ensuring the security of these systems escalates significantly. Foremost among security concerns is the complexity arising from the sheer number of interconnected devices. Cities deploying IoT technologies may be dealing with millions of devices, each representing a potential point of vulnerability. These devices, ranging from traffic sensors to smart meters, all need to be secured to prevent malicious actors from exploiting them, which is a daunting task due to their sheer number and diversity. Data security is another major concern. The vast amount of data generated by IoT devices needs to be securely transmitted, stored, and processed. This data often includes sensitive personal information, making its security a key priority. Any breach in data security could have severe implications, ranging from privacy violations to significant operational disruptions.

Rural areas

IoT applications deployed in rural areas are most relevant to agriculture, the natural environment, and wildlife tourism. In most cases, there is a lack of cellular network coverage. The options include accessing the public LoRaWAN network from local LoRaWAN operators, building your own private LoRaWAN network, or accessing LEO satellite networks. However, both hardware costs (CapEx) and data plans (OpEx) are always a concern.

The following is a list of the top 10 popular IoT applications within cities:

Soil moisture monitoringWildfire detectionAir quality monitoringRiver water pollution monitoringFlood monitoringLandslide alertingAnimal trackingFleet managementSecurity camerasFacility security

The rural area market is witnessing the flourishing of IoT applications related to agriculture production, environment protection, and natural disaster-proofing. However, wireless connectivity remains a top concern that needs to be addressed. As with the industrial market, there are numerous options available for resolving this issue.

Security considerations for rural areas are often less complex than those for cities. The primary reason behind this is that rural areas are likely to have fewer types of IoT applications. For example, in a city, IoT technology might be used for everything from traffic management systems to smart home applications and environmental monitoring. In contrast, in a rural setting, the applications might be more limited, perhaps focusing mainly on agriculture or weather monitoring. This limited scope can result in fewer security concerns, simply because there are fewer potential points of vulnerability. However, it’s still crucial to have robust security measures in place, regardless of the complexity or scope of the IoT deployment.

Industries

IoT is also an indispensable component of Industry 4.0. It empowers a multitude of industrial processes such as smart manufacturing, predictive maintenance, and supply-chain optimization (SCO). Through the collection and analysis of real-time data, IoT enhances automation, improves energy management, ensures quality control, and enables customized production.

However, the integration of IoT in industrial environments is not without challenges. These include ensuring robust security measures to protect against cyberattacks, achieving interoperability among a diverse range of devices, managing vast volumes of data, and scaling systems efficiently. Balancing the costs of implementation, addressing privacy concerns, obtaining the necessary technical expertise, and maintaining reliability in demanding industrial environments are also significant hurdles to overcome.

Despite these challenges, overcoming them is of paramount importance for industries to fully leverage the potential of IoT. The increased efficiency, innovation, and competitiveness that IoT offers can revolutionize industrial processes and significantly enhance productivity and profitability.

In the industrial market, IoT applications are often unique, leading to a wide variety of wireless connectivity options across different verticals. Depending on the specific needs and requirements of the industry, various wireless connectivity options can be utilized. These may include Wi-Fi 6, 6E, and 7, private 4G/LTE such as Citizens Broadband Radio Service (CBRS), 5G Ultra-Reliable Low Latency Communications (URLLC), WiSUN mesh, ISA100, and WirelessHART for more specialized applications.

The following is a list of the top 10 popular IoT applications within industries:

Smart meteringSupervisory Control and Data Acquisition (SCADA)Automotive mobile roboticsSecurity camerasPipeline leakage monitoringPreventive maintenanceFleet managementAsset trackingHazardous location (Hazloc) monitoringFacility security and people safety

The industrial IoT (IIOT) market is unique compared to other IoT markets because each vertical, such as utilities, mining, oil and gas, manufacturing, and transportation, has its own specific requirements. This requires special expertise from IoT application developers in these industries. This situation raises the bar for market penetration.

We are seeing the widespread use of IoT applications in many markets, such as homes, cities, and industries. This expansion is not only changing our immediate surroundings but also influencing various aspects of our lives. In the next section, we will discuss the real effects of this technological revolution. We will look at how IoT is changing convenience and efficiency in our homes, promoting sustainable and smart solutions in our cities, and transforming processes and safety measures in industries. Each of these areas shows the diverse impact of IoT, highlighting its significant role in the era of digital transformation.

How IoT impacts us

Following the stride of IoT expanding into new spaces, it consistently impacts us from every corner, every dimension, and every time. Some of them you are just aware of, with tangible benefits that catch your attention remarkably; some of them you are ignoring because they have already been part of your daily life for many years.

In summary, there are four key improvements that have been brought about by the expansion of IoT into various spaces. These improvements have had a significant impact on our lives, making them more comfortable, safe, efficient, and environmentally friendly.

Living comfort and safety improvement

In our daily lives, IoT has brought about numerous benefits, greatly enhancing our comfort and safety within various areas of our living spaces.

Personal care

Personal care