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2024–2025·Android · IA on-device · ML Kit · TensorFlow Lite · Visão Computacional

Maia · Facial Attendance Control

On-device facial biometrics at 10 FPS for corporate events

Context

Attendance control at corporate events historically suffers from queues, lost badges, smudged QR codes. Maia's pitch: replace all that with facial biometrics running directly on the staff's Android — no dependency on stable internet.

Architecture

  • Clean Architecture + MVVM with Hilt for DI — modular and testable code.
  • UI 100% Jetpack Compose with Material Design 3.
  • CameraX capture with frame processing, standardized 112×112px cropping and optimized multipart upload to the AWS backend.
  • AI pipeline using Google ML Kit + TensorFlow Lite, reaching 10 FPS with adaptive AOI validation.
  • Resilience via Sentry, smart retry logic and tracking IDs to guarantee data integrity on unstable networks.

Outcome

Solution in production, replacing legacy methods with sub-second latency and offline-first operation.