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

Industrial data analytics

We have seen the usage of data analytics in the past two sections and how it can be beneficial for our workloads. Now, let’s look at how it can benefit industry cases and how we can accordingly evaluate our deployments based on the best practices that are set out for us.

Evaluating performance

Use services such as CloudWatch metrics to monitor the performance of the IoT Analytics pipeline, such as the number of messages processed, the time it takes to process each message, and the number of errors that are encountered. This will be critical for use in further analysis and eventual optimization. The following are factors to consider in evaluating performance:

  • Analyze your data: We can use IoT Analytics SQL or other data analytics tools to identify any patterns or issues that we may need to address if they affect system performance.
  • Optimize your pipeline: From the analysis of the data, we can optimize the pipeline by adding data normalization...