Book Image

Developing IoT Projects with ESP32 - Second Edition

By : Vedat Ozan Oner
3 (2)
Book Image

Developing IoT Projects with ESP32 - Second Edition

3 (2)
By: Vedat Ozan Oner

Overview of this book

ESP32, a low-cost and energy-efficient system-on-a-chip microcontroller, has become the backbone of numerous WiFi devices, fueling IoT innovation. This book offers a holistic approach to building an IoT system from the ground up, ensuring secure data communication from sensors to cloud platforms, empowering you to create production-grade IoT solutions using the ESP32 SoC. Starting with IoT essentials supported by real-world use cases, this book takes you through the entire process of constructing an IoT device using ESP32. Each chapter introduces new dimensions to your IoT applications, covering sensor communication, the integration of prominent IoT libraries like LittleFS and LVGL, connectivity options via WiFi, security measures, cloud integration, and the visualization of real-time data using Grafana. Furthermore, a dedicated section explores AI/ML for embedded systems, guiding you through building and running ML applications with tinyML and ESP32-S3 to create state-of-the-art embedded products. This book adopts a hands-on approach, ensuring you can start building IoT solutions right from the beginning. Towards the end of the book, you'll tackle a full-scale Smart Home project, applying all the techniques you've learned in real-time. Embark on your journey to build secure, production-grade IoT systems with ESP32 today!
Table of Contents (15 chapters)
13
Other Books You May Enjoy
14
Index

Developing on Edge Impulse

As we talked about in the previous chapter, developing a TinyML application requires many steps, such as collecting requirements and data, pre-processing data, model development and optimization, deployment, performance tracking, and maintenance. In a traditional software project, we have DevOps to manage the software life cycle. When it comes to machine learning, we define Machine Learning Operations or MLOps. An MLOps platform provides us with the tools and resources to design, develop, and maintain our machine learning applications. What makes an MLOps platform different from a DevOps platform is that it also manages data and the resulting models in its versioning subsystem.

Edge Impulse is the leading MLOps platform for TinyML. It helps at every step of the ML application development process. Some important features of Edge Impulse are the following:

  • A web-based development environment, Edge Impulse Studio, to manage the entire ML life...