ESP32-S3 Edge Impulse Gesture Kit
Build a Gesture Classifier with ESP32-S3 and Edge Impulse
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Train your own gesture classifier entirely in the cloud using Edge Impulse Studio, then deploy it to an ESP32-S3 that runs on-device inference. You'll capture real 3-axis accelerometer data from the MPU6050 IMU, label gestures like swipes, circles, or flicks, and train a neural network. Once deployed, the 0.96-inch OLED instantly shows the recognized gesture — no PC or internet needed. It's a complete edge AI pipeline from data collection to classification, ready for robotics control or wearable interfaces.
What You'll Build
A standalone gesture recognition system that reads your hand motion and displays the gesture name on the OLED screen. You'll create a labelled dataset in Edge Impulse, design a compact neural network that fits the ESP32-S3, and validate it against real-world movements. The final device can distinguish up to 5 custom gestures and forms the foundation for gesture-controlled drones, smart wearables, or interactive school projects.
What You'll Learn
- Collect and label accelerometer time-series data in Edge Impulse Studio
- Design a neural network classifier for 3-axis motion gestures
- Train, validate, and export the model to C++ for ESP32-S3 deployment
- Integrate the MPU6050 IMU with I2C and display real-time predictions on an OLED
Kit Contents
| Component | Quantity |
|---|---|
| ESP32-S3 Dev Board | 1 |
| MPU6050 IMU | 1 |
| 0.96in OLED | 1 |
| MicroUSB Cable | 1 |
| M-M Wires | 15 |
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 ideal for Indian students in CBSE Classes 11–12 exploring AI and IoT, B.Tech ECE/CSE students building mini projects for Smart India Hackathon, and ATL labs that need a structured introduction to Edge Impulse. It bridges the gap between cloud-based ML training and on-device inference on a real microcontroller, giving learners at IIT, NIT, VIT, and BITS campuses a hands-on edge AI credential.
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, trained on this exact kit. You can also message us on WhatsApp for real-time troubleshooting.
Do I need prior experience with Edge Impulse?
No prior experience is needed. The kit includes step-by-step guidance to create an Edge Impulse account, collect sensor data, design the model, and deploy it. The AI companion walks you through every screen.
Can I train more than 5 gestures?
Yes, the ESP32-S3 has enough memory to handle up to 10 gesture classes, depending on the complexity of the neural network. You can expand the project with additional training data and retrain right in the browser.
Is the kit compatible with a Mac or Windows PC?
Edge Impulse Studio runs in any modern browser, so the training workflow works on Windows, macOS, and Linux. Programming the ESP32-S3 uses Arduino IDE, which is also cross-platform.
Train a gesture classifier in Edge Impulse Studio and deploy to ESP32-S3 IMU — accelerometer-based gesture recognition.
What's in this kit
- ESP32-S3 Dev Board
- MPU6050 IMU
- 0.96in OLED
- MicroUSB Cable
- M-M Wires x15
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