Retail Footfall Camera Kit v20
Retail Footfall Camera Kit – Count Shoppers in Real-Time with YOLOv8 Nano 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.
Transform a Raspberry Pi 5 into a live retail footfall counter that uses YOLOv8 Nano to detect and annotate people in a video stream. With an NVMe SSD for high-speed storage and a Pi Camera Module 3, you’ll achieve 30fps inference and display results in real time on an HDMI monitor. Ideal for students building a mini-project on edge AI or an engineer prototyping a customer analytics system.
What You'll Build
You’ll build a self-contained computer vision unit that recognizes people in a camera feed, draws bounding boxes and labels them, and streams the annotated video to a connected screen. The system runs entirely on the Raspberry Pi 5, processing frames directly from the Pi Camera Module 3 and storing model data on the high-speed NVMe SSD.
What You'll Learn
- Deploying YOLOv8 Nano on Raspberry Pi 5 for edge inference
- Optimizing a video pipeline with NVMe storage to hit 30fps
- Configuring the Pi Camera Module 3 for low-latency capture
- Writing Python scripts to overlay bounding boxes and display live analytics
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 4GB | 1 |
| Pi Camera Module 3 | 1 |
| NVMe SSD 128GB | 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
This kit suits B.Tech ECE or CSE students exploring edge AI for mini-projects, participants of Smart India Hackathon building retail analytics solutions, and ATL tinkering lab instructors demonstrating real-time object detection. If you’re an engineering student at IIT, NIT, VIT, or BITS preparing a final-year demo, you’ll find the build time and complexity right for a 4–5 hour practical assignment.
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 to start the AI companion that walks you through every step; you can also send us a WhatsApp message for quick human help.
Can I count specific types of objects or only people?
The base project detects people using YOLOv8 Nano, but you can retrain the model on your own dataset to count vehicles, products, or any other object.
Does the kit include a monitor or display?
No, you’ll connect the Raspberry Pi 5 to any standard HDMI monitor or TV to view the live annotated feed.
Is the NVMe SSD pre-loaded with the operating system?
No, you will flash the OS and load the model yourself using the AI companion’s step-by-step guide; the SSD provides high-speed storage for the model and optional video recording.
Retail Analytics — YOLOv8 Nano detects objects in real time on Raspberry Pi 5 — 30fps on NVMe, USB camera, live annotated display.
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