Objectives to Complete

Automated License Plate Capture System

Set up camera integration with parking spot sensors
Implement the YOLO model for license plate detection in images
Create an image preprocessing pipeline (brightness adjustment, noise reduction)
Test detection accuracy with different lighting conditions
Handle edge cases (dirty plates, obscured characters)

AI Data Processing & OCR

Train/fine-tune OCR model for license plate text extraction
Build an API endpoint to receive camera images and return plate text
Implement validation for extracted license plate formats
Set up error logging for failed detections
Create a fallback mechanism where AI confidence is low

Database Storage & Schema

Design a PostgreSQL database schema for parking sessions
Create tables for vehicles, spots, floors, and timestamps
Implement unique constraints to prevent duplicate spot assignments
Set up database indexing for fast license plate lookups
Write migration scripts for database setup

Objectives to Continue

Manual Check-in Feature

Complete the manual check-in UI form (license plate, floor, spot inputs)
Add input validation and error messages
Implement form submission to the backend API
Test with various input formats and edge cases

User Authentication setup

Set up basic user registration and login
Implement session management
Create user database tables
Add password hashing and security measures