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TinyML Cookbook

You're reading from   TinyML Cookbook Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801814973
Length 344 pages
Edition 1st Edition
Tools
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Author (1):
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Gian Marco Iodice Gian Marco Iodice
Author Profile Icon Gian Marco Iodice
Gian Marco Iodice
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Toc

Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Getting Started with TinyML 2. Chapter 2: Prototyping with Microcontrollers FREE CHAPTER 3. Chapter 3: Building a Weather Station with TensorFlow Lite for Microcontrollers 4. Chapter 4: Voice Controlling LEDs with Edge Impulse 5. Chapter 5: Indoor Scene Classification with TensorFlow Lite for Microcontrollers and the Arduino Nano 6. Chapter 6: Building a Gesture-Based Interface for YouTube Playback 7. Chapter 7: Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS 8. Chapter 8: Toward the Next TinyML Generation with microNPU 9. Other Books You May Enjoy

Acquiring accelerometer data

The accelerometer is one of the most common sensors that's incorporated into the IMU.

In this recipe, we will develop an application to read the accelerometer measurements from the MPU-6050 IMU with a frequency of 50 Hz. The measurements will then be transmitted over the serial so that they can be acquired with the Edge Impulse data forwarder tool in the following recipe.

The following Arduino sketch contains the code that's referred to in this recipe

  • 02_i2c_imu_read_acc.ino0:

https://github.com/PacktPublishing/TinyML-Cookbook/blob/main/Chapter06/ArduinoSketches/02_i2c_imu_read_acc.ino.

Getting ready

The accelerometer is a sensor that measures accelerations on one, two, or three spatial axes, denoted as X, Y, and Z.

In this and the following recipes, we will use the three-axis accelerometer that's integrated into the MPU-6050 IMU to measure the accelerations of three orthogonal directions.

However, how...

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