Developed an AI-powered attendance system using facial recognition for automated real-time user identification and attendance tracking. Built a scalable React Native application and FastAPI backend to manage attendance workflows and ML inference. Implemented cloud-based storage using AWS S3 and DynamoDB for secure management of facial data and attendance records.
An AI face-recognition attendance system: snap a class photo and attendance is marked automatically.
Architecture
- A Next.js API, a Python FastAPI face-recognition service and a React Native client with group recognition and offline mode.
- Storage split by workload: S3 for photos, DynamoDB for face encodings and PostgreSQL for attendance records.
- JWT-secured REST API.
Tech stack
React Native
FastAPI
OpenCVAWS S3AWS DynamoDB
Drizzle ORM
Next.js
TypeScriptAIFacial RecognitionML Inference