Master Edge AI Compression: Raspberry Pi 5 Pruning & Quantisation Research 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.

You’re ready to push MobileNet to its limits. This research kit puts a Raspberry Pi 5 with high-speed NVMe storage at your disposal to prune, quantise, and benchmark a computer vision model on real edge hardware — measuring exactly what you lose in accuracy for every byte of compression you gain. No cloud GPUs needed; all experiments run locally on the Pi.

What You'll Build

A fully instrumented edge AI testbed that runs MobileNetV2 inference faster and leaner than the standard model. You’ll generate pruned and quantised variants, log accuracy metrics, and produce a research-grade comparison of compression vs. accuracy — all running locally on the Pi 5 with NVMe-accelerated model loading.

What You'll Learn

• Apply magnitude-based weight pruning to a convolutional neural network and retrain the remaining weights to recover accuracy
• Implement post-training quantisation using PyTorch or TensorFlow Lite to reduce model size and inference latency
• Benchmark inference speed, memory footprint, and Top-1 accuracy on the Raspberry Pi 5 NVMe-accelerated system
• Analyse the saturation point where aggressive compression severely degrades model performance

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

This kit is for final-year B.Tech ECE/EEE students and research interns who need a reproducible edge AI optimization setup for their capstone project or SIH submission. Faculty guiding Smart India Hackathon teams will value the ready-to-use NVMe storage stack, while ATL lab coordinators can deploy it as a demo rig for advanced computer vision workshops at IIT, NIT, or VIT campuses.

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.