🧠 LabMind

From performing experiments to understanding them.

LabMind is an AI-powered smart laboratory platform designed to help students learn, simulate, troubleshoot, practice viva, and document laboratory experiments through a single intelligent environment.

It combines a deterministic experiment simulation engine with Generative AI, computer vision, adaptive viva, automated reporting, analytics, and a 3D digital twin of laboratory hardware.

🚀 Why LabMind?

Traditional laboratory learning is often fragmented:

Perform Experiment → Unexpected Output → Manual Troubleshooting → Ask for Help → Prepare Viva → Write Report

LabMind connects this entire workflow into one platform.

LabMind helps students:

🔬 Perform interactive laboratory experiments
🤖 Ask an AI tutor questions about experiments
🛠️ Diagnose circuit and experiment failures
👁️ Analyze circuit images using computer vision
🎤 Practice adaptive AI-generated viva questions
📄 Generate structured laboratory reports
📊 Track experiment and learning analytics
🧩 Explore experiments through an interactive 3D digital twin

✨ Core Features

🔬 Interactive Experiment Simulation

LabMind currently supports digital electronics experiments including:

Logic Gates
Half Adder
Full Adder
4:1 Multiplexer

The deterministic simulation engine calculates expected and observed outputs while allowing students to interact with circuit inputs and faults.

🛠️ AI-Powered Troubleshooter

The troubleshooting system combines deterministic circuit state with AI-assisted reasoning.

Context used by the diagnostic layer

Experiment
     +
Expected Output
     +
Observed Output
     +
Injected Fault
     +
Current Experiment State
     ↓
Context-Aware Diagnosis
     ↓
Likely Cause + Explanation + Guidance

Instead of simply saying "Wrong Output", LabMind helps explain why the output is wrong and what the student should investigate.

🤖 AI Tutor

The AI Tutor provides experiment-specific assistance instead of only generic answers.

Students can ask questions about:

Circuit operation
Truth tables
Experiment concepts
Troubleshooting
Viva preparation
Laboratory procedures

👁️ Vision Inspector

Students can provide circuit images for AI-assisted visual inspection.

The system is designed to help identify potential:

Wiring problems
Incorrect connections
Component placement issues
Circuit inconsistencies

🎤 Adaptive AI Viva

LabMind converts laboratory experiments into interactive viva sessions.

The system can generate experiment-related questions and adapt the questioning flow based on the student's responses.

📄 Lab Report Generator

After completing an experiment, LabMind can generate a structured laboratory report containing relevant experiment information and results.

This keeps documentation connected to the experiment workflow instead of treating the report as a completely separate task.

🧩 Virtual Smart Lab & Digital Twin

The Virtual Smart Lab is one of LabMind's major differentiators.

Instead of displaying only a conventional circuit diagram, LabMind provides an interactive 3D representation of laboratory hardware.

3D hardware pipeline

Blender
   ↓
GLB / 3D Assets
   ↓
Three.js + React Three Fiber
   ↓
Interactive WebGL Digital Twin

The current digital twin includes:

DIP IC packages
Breadboard
Interactive switches
LEDs
Resistors
Jumper wires
Power rails

Blender-generated IC assets

DIP14_7486
DIP14_7408
DIP14_7432
DIP14_7400
DIP14_7402
DIP14_7404
DIP16_74153

A representative 24-column × 10-row breadboard asset is also integrated into the Smart Lab.

The Blender assets are representative educational digital-twin models and are not claimed to be exact manufacturer replicas.

⏱️ 4D Experiment Timeline

LabMind records experiment state transitions and allows students to:

Capture experiment states
Replay previous states
Pause and resume the timeline
Scrub through state changes
Compare input and output states

This creates a lightweight 4D view of the experiment's evolution over time.

📊 Dashboard & Analytics

The platform provides a centralized dashboard for:

Experiment activity
Diagnostic activity
Viva sessions
Lab reports
Learning statistics

Persistent student data can be stored using Supabase.

🏗️ System Architecture

                         ┌──────────────────────┐
                         │       Student        │
                         └──────────┬───────────┘
                                    │
                                    ▼
                         ┌──────────────────────┐
                         │    LabMind Web App   │
                         └──────────┬───────────┘
                                    │
            ┌───────────────────────┼───────────────────────┐
            │                       │                       │
            ▼                       ▼                       ▼
 ┌──────────────────┐    ┌──────────────────┐    ┌──────────────────┐
 │ Experiment Engine│    │ AI Intelligence  │    │ 3D Digital Twin  │
 │                  │    │                  │    │                  │
 │ Circuit Logic    │    │ Gemini AI        │    │ Blender Assets   │
 │ Truth Tables     │    │ Troubleshooter   │    │ Three.js / WebGL │
 │ Fault Injection  │    │ Vision           │    │ React Three Fiber│
 └────────┬─────────┘    │ Viva             │    └────────┬─────────┘
          │              │ Reports          │             │
          │              └────────┬─────────┘             │
          │                       │                       │
          └───────────────────────┼───────────────────────┘
                                  │
                                  ▼
                         ┌──────────────────────┐
                         │       Supabase       │
                         │ Persistence & Data   │
                         └──────────────────────┘
                                  │
                                  ▼
                         ┌──────────────────────┐
                         │ Future Cyber-Physical│
                         │ Integration          │
                         │ ESP32 / Sensors /    │
                         │ Real Lab Equipment   │
                         └──────────────────────┘

🗄️ Entity-Relationship Diagram

The following is a conceptual application-level ER diagram showing how students, experiments, experiment sessions, diagnostics, viva sessions, and laboratory reports relate to one another.

erDiagram

    STUDENTS ||--o{ EXPERIMENT_SESSIONS : performs
    EXPERIMENTS ||--o{ EXPERIMENT_SESSIONS : contains

    STUDENTS ||--o{ DIAGNOSTIC_SESSIONS : has
    STUDENTS ||--o{ VIVA_SESSIONS : attempts
    STUDENTS ||--o{ LAB_REPORTS : creates

    EXPERIMENT_SESSIONS ||--o{ DIAGNOSTIC_SESSIONS : generates
    EXPERIMENT_SESSIONS ||--o{ VIVA_SESSIONS : supports
    EXPERIMENT_SESSIONS ||--o{ LAB_REPORTS : produces

    STUDENTS {
        UUID id PK
        string name
        string email
    }

    EXPERIMENTS {
        UUID id PK
        string name
        string slug
    }

    EXPERIMENT_SESSIONS {
        UUID id PK
        UUID student_id FK
        UUID experiment_id FK
    }

    DIAGNOSTIC_SESSIONS {
        UUID id PK
        UUID student_id FK
        UUID experiment_session_id FK
    }

    VIVA_SESSIONS {
        UUID id PK
        UUID student_id FK
        UUID experiment_session_id FK
    }

    LAB_REPORTS {
        UUID id PK
        UUID student_id FK
        UUID experiment_session_id FK
    }

Note: This diagram represents the application's logical relationships. It is intended as a high-level architecture diagram rather than a claim that every listed field exactly matches the current physical Supabase schema.

🧠 Key Innovation

Context-Aware Laboratory Troubleshooting

Many educational AI systems can explain a concept.

LabMind goes further by combining:

Current Experiment
        +
Circuit State
        +
Expected Result
        +
Observed Result
        +
Fault Condition
        +
Student Context
        ↓
Context-Aware AI Assistance
        ↓
Likely Cause + Explanation + Guidance

Core principle

The simulator establishes what happened. AI helps explain why it happened.

This separation keeps the experiment's core logic deterministic while using AI where natural-language reasoning and guidance are valuable.

🌐 Technology Stack

Frontend

Next.js
React
TypeScript
Tailwind CSS

AI

Google Gemini
AI-assisted troubleshooting
Vision analysis
Adaptive viva generation
AI tutoring

Simulation

TypeScript-based circuit simulation
Truth-table generation
Fault injection
Expected/observed output comparison

3D / Digital Twin

Blender
Three.js
React Three Fiber
Drei
GLB assets

Backend / Persistence

Supabase
PostgreSQL

Development

Git
GitHub
Blender 5.2.2 LTS

📁 Project Structure

LabMind/
│
├── public/
│   └── assets/
│       └── hardware/
│           ├── Breadboard_24x10.glb
│           └── ic/
│               ├── DIP14_7486.glb
│               ├── DIP14_7408.glb
│               ├── DIP14_7432.glb
│               ├── DIP14_7400.glb
│               ├── DIP14_7402.glb
│               ├── DIP14_7404.glb
│               └── DIP16_74153.glb
│
├── src/
│   ├── app/
│   ├── components/
│   ├── context/
│   ├── data/
│   ├── lib/
│   └── types/
│
├── package.json
├── package-lock.json
├── next.config.ts
├── tsconfig.json
└── README.md

⚙️ Local Setup

1. Clone the repository

git clone <YOUR_GITHUB_REPOSITORY_URL>
cd LabMind

2. Install dependencies

npm install

3. Configure environment variables

Create:

.env.local

Add your own credentials:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
GEMINI_API_KEY=your_gemini_api_key

Never commit .env.local or API keys to GitHub.

4. Start the development server

npm run dev

Open:

http://localhost:3000

🧪 Supported Experiments

Experiment	Simulation	3D Smart Lab
Logic Gates	✅	✅
Half Adder	✅	✅
Full Adder	✅	✅
4:1 Multiplexer	✅	✅

🔮 Future Roadmap

LabMind is designed as a software-first platform with a path toward a cyber-physical laboratory.

Near-Term

More digital electronics experiments
More physical component assets
Improved diagnostic reasoning
Expanded analytics
Additional laboratory subjects

Cyber-Physical Integration

ESP32
   ↓
Sensors
   ↓
Real Laboratory Equipment
   ↓
LabMind Data Layer
   ↓
AI Analysis
   ↓
Digital Twin

Potential future applications include:

Real-time equipment monitoring
Sensor-based experiment validation
Automatic fault detection
Physical-to-digital synchronization
Instructor dashboards
Remote laboratory experimentation

🎯 Hackathon Vision

LabMind aims to transform laboratory education from a passive "perform and submit" workflow into an intelligent learning loop.

Perform
   ↓
Observe
   ↓
Understand
   ↓
Diagnose
   ↓
Learn
   ↓
Practice
   ↓
Improve

🏆 Project Highlights

🤖 AI-assisted laboratory troubleshooting
🔬 Deterministic experiment simulation
🧩 Interactive 3D digital twin
🎨 Blender → GLB → WebGL hardware pipeline
🎤 Adaptive AI viva
👁️ Computer vision inspection
📄 Automated laboratory reporting
📊 Student analytics
🔌 Future-ready cyber-physical architecture

📌 Project Status

Prototype / Hackathon Ready

The current platform is a functional software prototype demonstrating the complete digital laboratory workflow and a WebGL-based hardware digital twin.

🔐 Security Note

API credentials are intentionally kept outside the repository.

Use environment variables through .env.local for:

Gemini API configuration
Supabase configuration

Never commit secret keys, tokens, passwords, or private credentials.

📜 License

This project currently does not include a separate open-source license.