Embedded Machine Learning with Microcontrollers: Applications on STM32 Development Boards by Cem Ünsalan – A Hands-On Te

Introduction

Embedded systems are the invisible brains behind countless devices we use daily, from smart appliances to industrial controllers. Now, the fusion of embedded systems with machine learning is opening up exciting new possibilities—enabling intelligent decision-making right at the edge, without relying on cloud connectivity. Embedded Machine Learning with Microcontrollers: Applications on STM32 Development Boards by Cem Ünsalan is a comprehensive, hands-on textbook that introduces students and professionals to this transformative field. Published by Springer, this hardcover edition is an essential resource for Indian engineering students, hobbyists, and embedded systems enthusiasts who want to build practical, real-world machine learning applications on STM32 microcontrollers.

Book Overview

This book takes a unique, project-driven approach to teaching embedded machine learning. Rather than overwhelming readers with abstract theory, it focuses on implementing machine learning algorithms directly on STM32 development boards—popular, powerful microcontrollers widely used in Indian academic labs and industry. The author, a seasoned educator and researcher, guides readers through both traditional machine learning methods (like decision trees and k-nearest neighbors) and modern neural network-based techniques. Each chapter presents a complete application, from data collection and preprocessing to model training, deployment, and testing on the microcontroller. The text emphasizes the 'learning by doing' philosophy, ensuring that readers not only understand concepts but can immediately apply them to solve real engineering problems.

Key Highlights

• Practical, hands-on focus: Every concept is accompanied by a real-world example implemented on STM32 boards.
• Dual coverage: Covers both classical machine learning and neural network methods, giving readers a well-rounded foundation.
• Low-level control: Uses a programming environment that allows direct manipulation of microcontroller registers and peripherals, offering deeper insight into system behaviour.
• Complete learning package: Includes sample code, course slides, and step-by-step project instructions—ideal for self-study or classroom use.
• Industry relevance: Skills taught are directly applicable to the growing field of edge AI and IoT in India.

Inside the Book

The book is structured to build competence progressively. It begins with an introduction to embedded systems and STM32 architecture, then moves into data acquisition using sensors. Subsequent chapters delve into feature extraction, model training, and optimisation for resource-constrained microcontrollers. Readers will learn to implement classifiers, regression models, and small neural networks entirely on the STM32 platform. Each project includes detailed code walkthroughs, debugging tips, and performance analysis. The final chapters explore advanced topics like real-time inference and power-aware machine learning, preparing readers for professional challenges.

Key Topics

• STM32 microcontroller programming and peripheral interfacing
• Data collection from sensors (accelerometers, temperature, proximity)
• Traditional machine learning algorithms: decision trees, SVM, k-NN
• Neural network design and deployment on microcontrollers
• Model optimisation for memory and computation constraints
• Real-time inference and system integration
• Case studies: gesture recognition, anomaly detection, predictive maintenance

Reader Benefits

By studying this book, Indian readers will gain a competitive edge in the job market. They will be able to design intelligent embedded systems that operate independently, making decisions in milliseconds without internet connectivity. The hands-on projects build portfolio-worthy skills that are highly sought after by companies in automotive, consumer electronics, industrial automation, and healthcare sectors. Moreover, the book demystifies complex machine learning concepts, making them accessible to anyone with basic knowledge of C programming and microcontrollers.

Learning Outcomes

• Ability to set up an STM32 development environment and write efficient C code
• Understanding of how to collect and preprocess sensor data for machine learning
• Skill to implement and train multiple machine learning models on microcontrollers
• Competence in deploying neural networks on resource-constrained devices
• Knowledge to evaluate and optimise model performance in terms of speed, memory, and power
• Confidence to build complete edge AI applications from scratch

Who Should Read

This book is ideal for undergraduate and postgraduate students in electronics, electrical, computer science, and instrumentation engineering. It is also a valuable resource for embedded systems professionals, hobbyists, and researchers who wish to add machine learning to their skillset. Faculty members teaching courses on microcontrollers, embedded systems, or IoT will find it a perfect textbook for project-based learning. No prior machine learning experience is required—only a basic understanding of C programming and digital electronics.

About the Author

Cem Ünsalan is a professor with extensive experience in embedded systems and machine learning. He has authored multiple textbooks and research papers in the field, and his teaching methodology emphasises practical, application-oriented learning. His work bridges the gap between theoretical knowledge and real-world implementation, making him a trusted guide for students and professionals alike.

About the Publisher

Springer is a globally renowned academic publisher known for its high-quality scientific, technical, and medical books. With a legacy of excellence spanning decades, Springer ensures that every title meets rigorous editorial standards. This hardcover edition is printed on durable paper and bound to withstand frequent use in labs and classrooms across India.

Conclusion

Embedded Machine Learning with Microcontrollers: Applications on STM32 Development Boards is more than just a textbook—it is a practical toolkit for the next generation of Indian engineers. Whether you are a student aiming to ace your embedded systems course, a professional looking to upskill in edge AI, or a hobbyist eager to build smart devices, this book will empower you with the knowledge and confidence to innovate. Order your copy today from Bookshops.in and start building intelligent, autonomous systems that work right at the edge.