IoT Face Attendance System

I’m building an Internet of Things solution that centres on a face-recognition system whose sole purpose is attendance tracking. The idea is simple: a camera (or a small edge device such as a Raspberry Pi) recognises registered faces in real time, time-stamps the event, and stores the record so I can pull daily, weekly, or monthly attendance reports without manual intervention.

Here’s what I expect as the finished product:
• Fully-coded face detection and recognition pipeline (Python/OpenCV, TensorFlow, or a comparable framework).
• A lightweight local or cloud database that logs each recognised face with a time and date stamp.
• A minimal web or mobile dashboard—or a clear REST API—that lets me review, export, or integrate the attendance data.
• Step-by-step setup instructions so I can replicate the system on additional devices if needed.
• A short demo (recorded video or live walk-through) proving the system detects faces accurately and marks attendance correctly.

Accuracy, low latency, and clean, well-commented code are the key acceptance criteria. I’ll release payment once I have tested the build and confirmed it meets the points above.