Retail Footfall Camera Kit - Edge AI People Counter on Raspberry Pi 5
Retail Footfall Camera Kit - Build an Edge AI People Counter by Training Your Own Classifier
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Transform a Raspberry Pi 5 into a real-time retail footfall counter, trained entirely on your own laptop using transfer learning. You'll extract a dataset, fine-tune a classifier in TensorFlow, quantize to INT8 TFLite, and deploy directly to the Pi for on-device inference - a complete MLOps cycle, not a plug-and-play demo. This is how smart stores in India track customer density without sending video to the cloud.
What You'll Build
A stand-alone camera unit that monitors a store entrance, classifies each person crossing the threshold, and logs timestamps onto the NVMe SSD. The Pi Camera Module 3 captures a stream, your TFLite model runs at the edge with zero network latency, and the system keeps a privacy-respecting headcount ready for peak-hour analysis or shopper conversion metrics.
What You'll Learn
- Curate and label your own custom footfall dataset from captured images
- Apply transfer learning with a pre-trained MobileNet backbone on a laptop
- Quantize the resulting model to INT8 TFLite for Raspberry Pi 5 acceleration
- Deploy the on-device inference engine and log structured analytics to NVMe
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
Designed for B.Tech ECE, EEE, and CSE students tackling final-year projects or Smart India Hackathon retail challenges. IIT, NIT, VIT, and BITS teams working on edge analytics will find the exact MLOps workflow used in industry. This is also a direct fit for CBSE Class 12 advanced computing projects and ATL Tinkering Lab mentors who want to show a production-grade people counter, not a toy.
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 inside the box to access your AI companion that walks through each step of the MLOps pipeline. You can also reach our support team on WhatsApp any working day.
Does my laptop need a dedicated GPU for transfer learning?
A modern quad-core laptop with 8GB RAM works fine for the image classifier training using CPU-based transfer learning. A GPU will speed things up, but the guide covers both paths.
Can I repurpose the classifier to count vehicles or products instead of people?
Absolutely. The pipeline is generic; you simply swap the dataset and labels. The LCD formatting and logging logic on the Pi remain reusable with minimal changes.
Will the Pi 5 handle 24/7 inference without overheating?
With the included USB-C PSU and the Pi 5's improved thermal management, the footfall counter stays stable under continuous load. For enclosed spaces, a small heatsink (not included) can add extra headroom, but for typical indoor use it's fine out of the box.
Retail 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