Book Image

Raspberry Pi Pico DIY Workshop

By : Sai Yamanoor, Srihari Yamanoor
Book Image

Raspberry Pi Pico DIY Workshop

By: Sai Yamanoor, Srihari Yamanoor

Overview of this book

The Raspberry Pi Pico is the latest addition to the Raspberry Pi family of products. Introduced by the Raspberry Pi Foundation, based on their RP2040 chip, it is a tiny, fast microcontroller that packs enough punch to power an extensive range of applications. Raspberry Pi Pico DIY Workshop will help you get started with your own Pico and leverage its features to develop innovative products. This book begins with an introduction to the Raspberry Pi Pico, giving you a thorough understanding of the RP2040's peripherals and different development boards for the Pico designed and manufactured by various organizations. You'll explore add-on hardware and programming language options available for the Pico. Next, you'll focus on practical skills, starting with a simple LED blinking project and building up to a giant seven-segment display, while working with application examples such as citizen science displays, digital health, and robots. You'll also work on exciting projects around gardening, building a weather station, tracking air quality, hacking your personal health, and building a robot, along with discovering tips and tricks to give you the confidence needed to make the best use of RP2040. By the end of this Raspberry Pi book, you'll have built a solid foundation in product development using the RP2040, acquired a skillset crucial for embedded device development, and have a robot that you built yourself.
Table of Contents (17 chapters)
1
Section 1: An Introduction to the Pico
6
Section 2: Learning by Making
10
Section 3: Advanced Topics

Developing edge devices

There are some factors to consider before you start developing a product that makes use of TinyML, as follows:

  • The datasets that are available for developing your product. The best place to start is by making use of existing datasets or making use of data from an existing application.
  • Product development cycles involving TinyML require a lot of trial and error to refine the parameters.
  • TinyML applications are suitable for tapping new revenue streams and improving productivity.
  • You also need to account for retraining your model from time to time to account for problems identified in the system.

Now that we have discussed some of the factors to consider before developing a product, let's summarize this chapter.