TinyML Foundations and Applications on Arduino Microcontrollers with MATLAB

1. Auflage 2026
ISBN: 978-1-041-32945-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 300 Seiten, Format (B × H): 174 mm x 246 mm

This book is a comprehensive guide to TinyML, focusing on its foundations and practical applications using Arduino microcontrollers and MATLAB. It will empower readers with the knowledge and skills to implement machine learning models on resource-constrained devices, bridging the gap between cutting-edge technology and real-world applications. With an emphasis on innovation, efficiency, and accessibility, the book provides a roadmap for leveraging TinyML to solve complex problems in areas such as IoT, robotics, and embedded systems.

The content is structured to offer a seamless learning experience, starting with the fundamentals of TinyML and progressing to advanced techniques for deploying models on Arduino microcontrollers. Readers will explore topics such as data preprocessing, feature extraction, and model optimization, all within the MATLAB environment. Practical examples and hands-on projects are included to demonstrate key concepts, from building predictive models to implementing real-time applications. Each chapter is designed to provide actionable insights, ensuring readers can apply their knowledge to diverse scenarios.

With its accessible language and practical focus, this book is a valuable tool for professionals and educators in IoT, automation, and smart systems, offering a dependable guide for learning or teaching TinyML concepts.

Zielgruppe

Postgraduate, Professional Training, and Undergraduate Advanced

Autoren/Hrsg.

Bai, Ying

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

1. Introduction
2. Learning and Decision Making Process
3. Introduction to Arduino Nano 33 BLE Sense MCU Board
4. Introduction to Arduino Nano 33 IoT MCU Board
5. Introduction to Machine Learning and Tiny Machine Learning

6. Introduction to Regressions and Classifications
7. Introduction to MATLAB Deep Learning Tools
8. Using TinyML to Classify Letters and Shapes with Arduino Microcontrollers
9. Using TinyML to Detect and Identify Images with Arduino Microcontrollers
10. Using TinyML to Detect and Identify Audio Signals with Arduino MCU
11. Build TinyML Applications with Unsupervised Learning Models
12. Build TinyML Applications with Adaptive Neuro Fuzzy Inference System

Über Autor(innen)

Dr. Ying Bai is a Professor in the Department of Computer Science and Engineering at Johnson C. Smith University located at Charlotte, North Carolina. His special interests include: Artificial intelligence, soft-computing, database programming, fuzzy logic controls, automatic and robots controls, as well as robots calibrations. His industry experience includes positions as software and senior software engineers at companies such as Motorola MMS, Schlumberger ATE Technology, Immix TeleCom, and Lam Research. Since 2003, Dr. Bai has published 22 books with publishers such as Prentice Hall, CRC Press LLC, Springer, Cambridge University Press and Wiley IEEE Press. He also published about 80 academic research papers in IEEE Trans. journals and international conferences. Most books are about AI foundations and applications with MATLAB, micro-controller controls and programming, fuzzy logic implementations, classical and modern controls, cross-language interface programming, database programming and applications.