Hybrid Educational Grading System Development

Замовник: AI | Опубліковано: 04.04.2026
Бюджет: 30 $

Project Overview: I am looking for a developer or team to build a dual-mode educational grading system. The system consists of: An iOS App: Capable of real-time scanning and grading of both standard OMR bubble sheets AND unique orientation-based cards (Plickers-style). A PHP Web Backend: A tool to generate customized PDF test sheets and student cards using Chromium (via Spatie/Browsershot). Privacy is paramount. All student scanning and grading must occur on-device to ensure data security. Module 1: The iOS App (Swift/SwiftUI) The app must feature a toggle or auto-detection to switch between two modes: Mode A: OMR Bubble Sheets: Detects standard multiple-choice grids. Real-time detection of "filled" vs. "empty" bubbles using local image thresholding. Mode B: Plickers-Style Cards: Detects unique geometric shapes (markers) assigned to each student. Grading is based on the orientation of the card (A, B, C, or D at the top). Must support scanning multiple cards in a single camera frame (e.g., scanning a whole classroom). Technical Requirements (iOS): Engine: Use Apple’s Vision Framework and Core Image for high-speed, real-time processing. Local Processing: No images should be sent to a server for grading. All logic must be local. Database: Use CoreData or SQLite with encryption to store student rosters and scores. Export: Generate CSV/Excel reports locally from the app. Module 2: PDF Generation Engine (PHP/Chromium) I need a system to generate the physical papers that the app will scan. Technology: PHP 8.x with Spatie/Browsershot (Headless Chromium). OMR Generator: Dynamically generate bubble sheets based on the number of questions (e.g., 10, 20, 50, 100 questions). Plickers Card Generator: Generate a unique set of cards (40–60 unique patterns) with student names printed on the back/corners. Layout: High-precision CSS layout to ensure that "anchor points" (the black squares in the corners) are perfectly placed for the iOS camera to find the grid. Output: High-quality, print-ready PDFs. Module 3: Privacy & Security Zero-Cloud Grading: The server only generates the PDFs. It should never see the students' filled-in answers. GDPR/FERPA Ready: The app must not include third-party trackers. Local Encryption: Student data stored on the iPhone must be protected via the iOS Secure Enclave/Keychain. Specific Deliverables: iOS Source Code: Fully documented Swift code. PHP Script/Backend: A web-based interface where I can input questions or student lists and download the generated PDFs. PDF Samples: Set of 5 sample OMR templates and 1 set of 40 unique Plickers cards. Hardware Calibration: The scanner must be optimized for different iPhone models (adjusting for focal length/distortions). Developer Requirements: Expertise in Computer Vision (Vision Framework, OpenCV, or AVFoundation). Strong PHP/Laravel skills with experience in Puppeteer/Chromium/Browsershot. Experience with Real-time Camera Overlays (drawing bounding boxes and scores over the live feed). Ability to demonstrate previous OMR or QR-related scanning projects. Application Instructions: Please start your proposal with the word "HYBRID". In your proposal, please answer: How will you ensure the OMR grid detection remains accurate if the teacher holds the phone at an angle? Have you used Browsershot/Chromium for high-precision print layouts before?