SimuNex - AI-Powered IoT Simulation Platform

Overview

SimuNex is an AI-driven IoT simulation platform that helps users identify components, receive project suggestions, and test hardware simulations in real-time. The platform integrates YOLOv8 for component detection, Llama3-70B for AI assistance, and HardCode, a LeetCode-like system for coding and validating IoT projects.

Features

• IoT Component Identification: Uses YOLOv8 to detect and recognize IoT components with 85% accuracy.
• AI-Driven Assistance: Implements Llama3-70B to provide real-time guidance for IoT simulations.
• HardCode - IoT Coding Platform: Allows users to simulate hardware connections, write code, and test solutions.

Tech Stack

• Frontend: HTML, CSS, JavaScript.
• Backend: Flask
• Machine Learning: YOLOv8, Llama3-70B
• Database: SQLite3

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• Flask
• OpenCV
• PyTorch (for YOLOv8)
• Llama3-70B Model (API or local deployment)

Steps

1. Clone the repository:

   git clone https://github.com/Harinee2501/SimuNex.git
   cd SimuNex
   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   python app.py

4. Open the browser and visit:

   http://localhost:5000

Usage

• Upload an image of an IoT component for identification.
• Get AI-generated suggestions for IoT projects.
• Use HardCode to simulate and validate circuit connections.