ML Feature Visualiser Kit with Arduino Mega - Radar Chart ADXL345
Arduino Mega ADXL345 Radar Chart Kit
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Ever wondered how raw sensor data gets transformed into the features that train a machine learning model? With this kit, you'll capture 3-axis acceleration from an ADXL345, compute statistical measures like mean and standard deviation, extract frequency-domain features via FFT bin magnitudes, and plot them all as a live radar chart on a TFT display. It's a hands-on bridge between sensor data and ML feature extraction.
What You'll Build
You'll assemble a self-contained instrument that reads accelerometer data, runs on-board DSP calculations on the Arduino Mega, and renders a 6-parameter radar chart (mean X/Y/Z, standard deviation, and dominant FFT bins) updated in real time. The timestamped data also logs to an SD card, creating a dataset you can export to Python or MATLAB for further ML training.
What You'll Learn
- Compute statistical features (mean, standard deviation) from streaming sensor data using fixed-point arithmetic on an 8-bit microcontroller.
- Implement Fast Fourier Transform (FFT) bin extraction to identify dominant vibration frequencies in the signal.
- Drive a 2.4-inch TFT ILI9341 display via SPI to draw dynamic radar chart geometries.
- Log timestamped feature vectors to a MicroSD card using SPI in a multi-device bus environment, managing CS lines and power constraints.
Kit Contents
| Component | Quantity |
|---|---|
| Arduino Mega 2560 | x1 |
| ADXL345 Accelerometer | x1 |
| 2.4in TFT ILI9341 | x1 |
| DS3231 RTC | x1 |
| MicroSD Module | x1 |
| 4.7k? Resistors | x5 |
| 100nF Capacitors | x5 |
| PCB Prototype Board | x2 |
| 9V Battery Snap | x1 |
| Soldering Iron | x1 |
| Solder Wire | x1 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
If you're a BTech ECE or EEE student exploring the intersection of IoT and machine learning, this kit gives you a tangible project to add to your portfolio. It's tailor-made for Smart India Hackathon teams tackling sensor analytics, for final-year projects at IIT, NIT, VIT, or BITS Pilani, and for tinkering labs like ATL that want to demonstrate the signal-processing pipeline behind edge ML.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project - accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
The AI companion, reachable through the QR code or WhatsApp, will guide you step-by-step through wiring, code upload, and debugging specific to this radar chart setup.
Do I need prior experience with FFTs or radar charts?
No. The companion explains the math intuitively and provides fully commented Arduino code that handles the FFT and display drawing, so you learn by building.
Can I export the logged data to train an actual ML model?
Yes. The MicroSD stores timestamped CSV files with all extracted features. You can import them into Python, MATLAB, or any ML framework to train classifiers on your own gesture or vibration patterns.
Is the Arduino IDE code included, and how is multi-SPI managed?
Absolutely. The companion delivers optimized code for the Mega, with separate SPI chip-select handling for the TFT, SD card, and RTC, plus a pre-tuned FFT library matched to the ADXL345 data rate.
ADXL345 features (mean, std, FFT bins) visualised as radar chart. Helps understand ML feature engineering.
What's in this kit
Choose your assembly option:
- Soldering Kit - 25W soldering iron, 60/40 solder wire, flux, and small perfboard for permanent assembly.
- Breadboard Combo - 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.
Other projects you can build
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items