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An AI-powered assessment system that leverages Gemini’s advanced vision and reasoning capabilities to automatically read, interpret, and grade student answer sheets with high accuracy.

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CheckMe

CheckMe: Grading System

An automated grading system that combines a Raspberry Pi hardware device with a cross-platform mobile app to digitize and accelerate the process of checking student answer sheets.


Overview

CheckMe eliminates manual paper checking by using a flatbed scanner, AI-powered OCR (Google Gemini), and a mobile app to automate the entire grading workflow — from scanning answer keys to scoring student sheets and storing results in the cloud.

Teachers interact with the hardware device on-site to scan and grade answer sheets. Results are instantly available in the mobile app for review, manual scoring of essay questions, and record keeping.


How It Works

Teacher creates assessment in mobile app
        ↓
Assessment UID is generated (e.g. QWER1234)
        ↓
Teacher writes UID on answer key paper
        ↓
Answer key is scanned on the Raspberry Pi device
        ↓
Gemini OCR extracts answers → saved to Firebase RTDB
        ↓
Student answer sheets are scanned one by one
        ↓
System scores each sheet automatically
        ↓
Results are saved to Firebase RTDB
        ↓
Teacher reviews results in the mobile app

System Design

Place your actual Raspberry Pi system product photo(s) here.

[ Insert system_design.png here ]

Circuit Diagram

Place your circuit diagram image here.

[ Insert circuit_diagram.png here ]

Mobile Interface

Place your mobile app UI screenshots here.

[ Insert mobile_interface.png here ]

Repository Structure

CheckMe/
├── app/
│   └── CheckMe/                        # React Native mobile app source
│
├── docs/
│   ├── app/
│   │   ├── cross-platform-setup/
│   │   │   ├── COMMON_TROUBLESHOOTING.md
│   │   │   └── DURING_DEVELOPMENT.md
│   │   └── troubleshooting/
│   │       └── WORKLETS_TROUBLESHOOTING.md
│   │
│   ├── firebase/
│   │   └── FIREBASE_STRUCTURE.md       # Firebase RTDB schema reference
│   │
│   ├── github/
│   │   ├── ssh/
│   │   │   ├── QUICK_SETUP.md
│   │   │   └── SSH_DETAILED_SETUP.md
│   │   └── work-in-progress/
│   │       ├── BRANCHING_GUIDE.md
│   │       └── WIP_GUIDE.md
│   │
│   └── raspi/
│       ├── AUTOSTART_CONVERTION.md     # Run CheckMe on boot (systemd)
│       ├── L3210_INITIAL_SETUP.md      # Epson L3210 scanner setup
│       ├── RASPI_SYSTEM_FLOW.md        # Full system flowchart
│       ├── SCAN_ANSWER_KEY_FLOW.md     # Answer key scanning flowchart
│       ├── SCAN_ANSWER_SHEET_FLOW.md   # Answer sheet checking flowchart
│       ├── SPEC.md                     # Hardware specs and pin config
│       └── SYSTEM_USER_MANUAL.md       # Teacher user guide
│
├── raspi_code/                         # Raspberry Pi Python source code
│
├── .gitignore
├── LICENSE
└── README.md

Components

Raspberry Pi Device

The physical grading machine. Runs Python on a Raspberry Pi 4B with an I2C LCD display, a 4x3 matrix keypad, and an Epson L3210 flatbed scanner.

See raspi_code/ and docs/raspi/ for setup and documentation.

Mobile App

Cross-platform mobile app (React Native) for teachers to create assessments, review graded results, and manually score essay questions.

See app/CheckMe/ and app/README.md for setup and documentation.


Tech Stack

Layer Technology
Hardware Raspberry Pi 4B, Epson L3210, I2C LCD, 4x3 Keypad
Raspi Software Python 3.12, Firebase Admin SDK, Gemini API, Cloudinary
Mobile App React Native (cross-platform)
OCR Google Gemini
Image Storage Cloudinary
Database Firebase Realtime Database
Authentication Firebase (temp code via mobile app)

License

This project is licensed under the MIT License.

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An AI-powered assessment system that leverages Gemini’s advanced vision and reasoning capabilities to automatically read, interpret, and grade student answer sheets with high accuracy.

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