Build the foundations
Wire circuits, read sensors, control outputs, and learn how to debug. Make the engineering notebook part of the daily routine.
Arduino · Electronics · C/C++THE CLASSROOM IS A WORKSHOP.
Small devices.
Big ideas.
Real engineering.
AI & Mechatronics connects code, circuits, and machine learning with things students can actually build.
THE AIM WORKBENCH2025–26
Sense → Think → Act → Refine01—03
A system diagram, not a wiring guide.
ARDUINORASPBERRY PIJETSON / JETBOTXIAO ESP32S3TINYMLPYTHON + C/C++
LEARN BY MAKING
More than a model.
A complete working system.
Students learn to connect an input to a decision and a physical response. Along the way, they solder, debug, collect data, train or deploy models, and explain the engineering choices behind a prototype.
AIM builds on the earlier Mechatronics Project Laboratory course, expanding the learning pathway into TinyML, embedded vision and audio, motion classification, and language models on edge devices.
THE LEARNING PATHWAY
From a blinking LED
to an idea of your own.
Connect hardware & software
Move into the Raspberry Pi desktop, terminal, and Python. Integrate displays, clocks, and environmental sensors.
Raspberry Pi · Python · FabricationGive the system intelligence
Collect images for JetBot, explore TinyML on small boards, and connect model predictions to a useful response.
Computer vision · Audio · Edge AIMake it your own
Propose, pitch, prototype, test, and present an independent capstone. Explain what changed and what still needs work.
Design · Teamwork · CommunicationFOUR WAYS TO MAKE AI TANGIBLE
What can your
device notice?
Explore the AI strands in the course. Select one to see how input becomes a response.
Illustrative learning pathways, not live model predictions. Edge language models run on more capable devices such as Raspberry Pi, not necessarily a microcontroller.
COMPUTER VISION
A camera becomes an input.
INPUTCamera image
PROCESSClassify a scene or gesture
RESPONSETrigger a controlled action
Students used a SenseCraft rock–paper–scissors model with the XIAO ESP32S3 Sense.
FROM THE STUDENT WORKBENCH
Different ideas.
Shared engineering habits.
Selected 2025–2026 projects, summarized anonymously from classroom accounts and final narratives.
VISION + PHYSICAL COMPUTING01
Rock, paper, scissors… and pie.
A camera and a SenseCraft gesture model recognize the player’s hand. Game logic connects the result to a servo-driven pie mechanism.
Engineering takeaway
Connecting a pretrained model to game logic and mechanical action.
SPEECH + PYTHON02
The Digital Converter
A Raspberry Pi device listens after a button press, transcribes speech, extracts a quantity and unit, and converts the result.
Engineering takeaway
Integrating models and code; refining the scope to fit the available time.
ELECTRONICS + GAME LOGIC03
Minesweeper leaves the screen
An electronic game combines an LED matrix, joystick, controls, and displays. The team replaced an ambitious mechanical design with an achievable electronic one.
Engineering takeaway
Managing complexity and making a design change. This is an electronics project, not an AI claim.
SENSORS + MECHANISMS04
A color-responsive gripper
Buttons position the arm while a color sensor and Arduino trigger a servo grip. The team moved on from an initial AI-drone concept; gripping reliability remained a limitation.
Engineering takeaway
Separating manual control, sensor logic, and mechanical reliability.
BUILT IN ONE CLASSROOM. SHARED WITH YOURS.
Start with one lesson.
Make it your own.
Browse editable handouts, teaching outlines, the syllabus, and the resources that helped shape AIM.