Classroom Engagement Camera Kit v36
Classroom Engagement Camera Kit v36 – Build an Edge AI MLOps Pipeline on Raspberry Pi 5
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Turn a laptop-trained image classifier into a real-time classroom engagement monitor. This kit walks you through every step of the MLOps pipeline: collect data, train a custom model with transfer learning, quantize it to TensorFlow Lite INT8, and deploy it on a Raspberry Pi 5 with an NVMe SSD for fast inference. Perfect for B.Tech final-year projects, Smart India Hackathon challenges, or building a portfolio piece that mirrors industry practices.
What You'll Build
A complete edge AI camera that captures images via Pi Camera Module 3, runs a quantized classifier on the Pi 5, and logs engagement predictions to the NVMe SSD. You’ll own the full workflow—from dataset preparation and model training on your laptop to on-device inference—mimicking a production MLOps cycle.
What You'll Learn
- Train a custom image classifier using transfer learning (TensorFlow/Keras) on a standard laptop
- Quantize a floating-point model to TFLite INT8 for efficient edge deployment
- Set up Raspberry Pi 5 with an M.2 HAT+ and NVMe SSD for high-speed storage and model access
- Profile and optimize an edge computer vision pipeline for real-world classroom analytics
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 8GB | 1 |
| Pi Camera Module 3 | 1 |
| NVMe SSD 256GB | 1 |
| Pi 5 M.2 HAT+ | 1 |
| USB-C PSU | 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
B.Tech ECE/EEE students working on final-year AI or embedded systems projects, teams preparing for Smart India Hackathon 2025, and makers from IITs, NITs, VIT, or BITS Pilani who want to go beyond simulation and deploy a real MLOps pipeline. If you are comfortable with Python basics and want to carve a niche in edge AI, this kit gives you a production-grade reference architecture.
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?
Open the AI companion from the QR code, describe your issue, and receive step-specific help. For more complex snags, we offer direct WhatsApp support from our Bengaluru team.
Do I need a GPU or cloud account to train the classifier?
No. The transfer learning workflow is designed for a standard laptop CPU. You will train entirely offline, then quantize the model before deployment.
Can I swap in my own dataset instead of the sample classroom images?
Absolutely. The companion guide walks you through structuring any image dataset and retraining the classifier — it's the same pipeline you'll use for hackathons.
How do I access the engagement metrics after deployment?
The kit includes sample code to log predictions with timestamps to a CSV file on the NVMe SSD. From there, you can feed data into any analytics dashboard or even stream it over Wi-Fi.
Education Analytics — Train a custom image classifier on a laptop using Transfer Learning, quantise to TFLite INT8 and deploy to Pi 5 — full MLOps pipeline.
What's in this kit
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