ESP32-S3 Tinygrad NN Engine Kit with ESP32 + MPU6050
ESP32-S3 Tinygrad NN Engine Kit: On-Device Training in 60 Seconds
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
This kit transforms an ESP32-S3 into a miniature neural network engine. Using Tinygrad’s custom matrix multiplication routines running directly in SRAM, you’ll train a small classifier on live MPU6050 accelerometer and gyroscope data in under a minute. It’s edge AI that learns on the spot—ideal for gesture recognition, anomaly detection, or wearable motion analysis.
What You'll Build
You’ll wire up a compact sensor node with temperature, humidity, motion, and real-time clock logging. The OLED displays training loss as the network converges on motion patterns, and the microSD stores trained model weights for later deployment. Everything fits inside a portable ABS enclosure, ready for field testing.
What You'll Learn
- Implement custom matrix multiplication on ESP32-S3 SRAM to maximize Tinygrad throughput
- Preprocess MPU6050 6-axis sensor data into training tensors using sliding windows
- Execute backpropagation and weight updates entirely on a microcontroller without external compute
- Integrate DHT22, OLED, and RTC into a complete data logging and visualization pipeline
Kit Contents
| Component | Quantity |
|---|---|
| ESP32-S3 Dev Board | 1 |
| MPU6050 | 1 |
| DHT22 | 1 |
| 0.96in OLED | 1 |
| DS3231 RTC | 1 |
| MicroSD Module | 1 |
| 4.7kΩ Resistors | 5 |
| 100nF Caps | 5 |
| PCB Prototype Board | 2 |
| ABS Enclosure Box | 1 |
| Micro USB Cable | 1 |
| Soldering Iron | 1 |
| Solder Wire | 1 |
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
This kit is built for advanced makers, B.Tech ECE/EEE students, and Smart India Hackathon teams who need a fully integrated edge AI prototype without months of sourcing and debugging. It’s equally valuable for IIT/NIT/VIT/BITS researchers validating TinyML algorithms on real hardware, and for professionals prototyping on-device learning for wearable or IoT products.
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?
Scan the QR code on the box to launch the AI build companion. It offers wiring diagrams, live debugging steps, and code walkthroughs. If you need a human, message us on WhatsApp for direct assistance.
Do I need prior experience with Tinygrad or neural networks?
Familiarity with C/C++ and basic linear algebra is recommended. The AI companion explains key concepts, but prior experience with Arduino or ESP-IDF will help you move faster.
Can I swap sensors or train for a different task?
Yes, the code is modular. Replace the MPU6050 with other I2C sensors, and the Tinygrad model adapts to input dimensions. The AI companion can guide you in modifying data preprocessing.
How do I deploy the trained model after building?
Trained weights are saved to microSD as binary files. You can freeze the model and use it for inference only on the same ESP32-S3, or port the model to a smaller chip using the exported header files.
ESP32-S3 runs custom matrix multiplication in SRAM. Trains a small NN on sensor data in under 60 seconds.
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.
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