Angol
A project-driven guide to designing, training, and deploying artificial intelligence directly on embedded hardware, showing how to build intelligent, autonomous systems under real-world constraints.
If you already know your way around a microcontroller and want to add embedded AI to it—or you work in ML and you''re ready to get your hands on real hardware—this book is for you. It covers the full embedded AI stack, from circuit design and custom PCB fabrication through sensor fusion and signal processing to on-device inference.
You''ll learn how to wire the sensor, condition the signal, fuse IMU data using complementary filters, Madgwick, Mahony, and Kalman filters, deploy decision trees that run inside the sensor itself, and figure out why your tensor arena is the wrong size. Along the way, you''ll tackle exploratory data analysis, model quantization, and the debugging realities that documentation never mentions—like what to do when the firmware uploader is fragile and your breadboard connections are dodgy.
Working on Arduino (UNO R3 and R4, Nano 33 BLE Sense, Nicla Vision, Nicla Voice), Raspberry Pi Pico 2, and ST evaluation boards, you''ll build 25 complete projects, including:
