System Definition
Padi-P is a distributed, data-driven academic decision support system built on top of ETLab. It transforms raw academic data (attendance, results, timetables) into actionable insights, predictive analytics, and real-time student guidance.
System Architecture
The platform architecture focuses on a "Value Layer" which calculates attendance percentage, recovery estimation, and risk classification:
- Data Ingestion Layer: Periodic syncing of ETLab data through an attendance-service and automated background workers.
- Data Storage Layer: Converting temporary academic data into persistent intelligence-ready records within Supabase PostgreSQL.
- Core Brain: An intelligence and decision engine that evaluates future academic scenarios and suggests attendance-critical decisions.
- Worker Layer: The heartbeat of the system, running cron-based tasks to detect data changes, trigger analysis, and push notifications.
Core Modules
Attendance Management
Tracks subject-wise and daily attendance. It maintains historical logs and calculates "safe bunks" or recovery classes needed to reach specific academic targets.
Academic Resource System
A consolidated view of assignments (sourced from ETLab or student-shared) and module-based structured study notes for efficient examination preparation.
Outcome
Padi-P is built as a unified system with Expo, delivering a seamless experience across Android APK, Web, and PWA platforms. It continuously monitors and predicts academic behavior to provide real-time decision support, transforming raw logs into academic intelligence.