Book Image

Internet of Things from Scratch

By : Renaldi Gondosubroto
Book Image

Internet of Things from Scratch

By: Renaldi Gondosubroto

Overview of this book

Develop the skills essential for building Internet of Things solutions with this indispensable guide. In an era where industries heavily rely on IoT, this book will quickly familiarize you with its foundations, widespread use, implementation guided by best practices, and the crucial technologies that allow it to work effectively. Starting with the use of IoT in real-life scenarios, this book offers comprehensive insights into basic IoT hardware, protocols, and technologies. You’ll then learn about architecting and implementing solutions such as wireless sensor networks, cloud computing with AWS, and crucial security considerations. You’ll understand how these systems are operated and monitored over time and work with simple to complex, industry-grade systems, adhering to best practices. In later chapters, you’ll be apprised of future IoT trends and strategies to manage the risks and opportunities that come with them. You’ll also get to grips with a diverse set of tools, including hardware such as ESP32 and Raspberry Pi, and software such as Mosquitto and ChatGPT for generative AI capabilities. By the end of this IoT book, you’ll be able to independently build and design complex, industry-standard solutions fully aligned with best practices.
Table of Contents (22 chapters)
1
Part 1: Getting Started with the Internet of Things
6
Part 2: Developing and Optimizing IoT Systems for Smart Environments
11
Part 3: Operating, Maintaining, and Securing IoT Networks
16
Part 4: Delving into Complex Systems and the Future of IoT

Creating Applications on the Edge

Edge computing is a nascent technology that facilitates the processing of data near or at its point of generation, rather than in a central hub such as the cloud. This will break down a centralized computing problem and instead create a decentralized, distributed way of processing data, allowing for real-time decision-making, faster response times, and a reduction in data transmission costs. This enables you to cut costs associated with traditional investments required for centralized data processing, such as setting up a data center or cloud infrastructure. Instead, you can utilize the same devices used to collect the data to perform a portion or all of the required processing work.

Often, this is a solution that many turn to when they start looking at bigger, more complex workloads. In many cases, challenges such as processing multiple streams of data that may involve hundreds or thousands of streams at the same time in a centralized system may...