Retail Footfall Camera Kit v31 — an intermediate-level kit for teens.

Retail Footfall Camera Kit — Raspberry Pi 5 Pan-Tilt Vision Tracking for Store Analytics

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 1-5 days.

Turn a Raspberry Pi 5 into a smart retail camera that mimics the pan‑tilt footfall counters used in malls and stores. As a person moves through the frame, the Pi Camera Module 3 swivels on two servos to keep them dead centre, while an OpenCV‑based tracker logs their path. It’s a hands‑on way to understand how real‑world retail analytics systems measure customer flow and dwell time.

What You'll Build

A live video pipeline where the camera physically moves to follow a person. The Pi Camera 3 is mounted on an adjustable pan‑tilt servo bracket, and your Python script uses OpenCV’s built‑in object detection to find a person in each frame. You’ll calculate the offset from centre, map it to pan and tilt angles, and drive two SG90 servos via PWM. The result is a responsive tracking system that can be extended to log entry counts, trigger snapshots when a customer pauses, or feed data to a dashboard.

What You'll Learn

• Capture high‑resolution video with Pi Camera Module 3 and process frames in real time on Raspberry Pi 5
• Apply OpenCV’s pre‑trained deep learning models for person detection and centroid tracking
• Generate PWM signals to control two SG90 servos for smooth pan and tilt motion
• Convert pixel coordinates to servo angles, closing the loop between vision and mechanical movement

Kit Contents