Pi 5 Contrastive Learning IoT Kit – Self-Supervised Pretraining on Sensor Data

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 equips you to run SimCLR self-supervised pretraining directly on a Raspberry Pi 5, turning raw, unlabelled sensor streams into a robust feature extractor. Then, with just a handful of labelled examples, fine-tune for a targeted IoT classification task and consistently outperform a fully supervised model trained on the same tiny dataset.

What You'll Build

You'll configure a high-speed NVMe-backed Pi 5 to train a SimCLR model on unlabelled sensor data – perhaps from accelerometers, temperature sensors, or camera feeds – learning powerful representations. Then you'll demonstrate that few-shot fine-tuning on as few as 5–10 labelled samples yields higher accuracy than training from scratch on the full labeled set. The result is a research-grade pipeline ready for Smart India Hackathon submissions, B.Tech final-year projects, or publication prototypes.

What You'll Learn

• Setting up Raspberry Pi 5 with M.2 NVMe SSD for deep learning workloads
• Implementing contrastive learning (SimCLR) from scratch using PyTorch on edge hardware
• Preprocessing and augmenting unlabelled sensor data for self-supervised training
• Few-shot fine-tuning strategies and benchmarking against supervised baselines

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

Designed for B.Tech ECE/EEE students tackling final-year projects at IITs, NITs, VIT, BITS Pilani, or any research-focused engineering college. Perfect for Smart India Hackathon participants building AI/ML prototypes on resource-constrained hardware. Also suited for early-stage researchers publishing on edge AI, few-shot learning, and self-supervised methods.

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.