📡 RF Audio Monitor – Real-Time Radio Mic Fault Detection

🏆 Best Overall Project – Hackathon 2025

RF Audio Monitor is a real-time monitoring dashboard that uses machine learning to detect microphone issues like popping caused by loose or snapped radio mic cables — helping event technicians catch faults before they ruin a performance.

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🚀 What It Does

• 🎧 Detects subtle mic faults (e.g. popping, snaps) in live audio streams.
• 📊 Visualizes device activity and audio status in a clean React dashboard.
• ⚠️ Sends real-time alerts when a fault is detected using WebSockets.

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🧠 How It Works

• Frontend: Built with React + Tailwind CSS for responsive, real-time UI.
• Backend: Python (Flask + PyAudio) streams and analyzes live audio from multiple devices.
• Machine Learning: A Random Forest model trained on audio features like:
  • Spectral Flatness
  • RMS Energy
  • Zero Crossing Rate
  • Spectral Centroid
• Multithreading: Handles multiple devices in parallel using Python threads.
• Real-Time Alerts: WebSocket-based live warning system for fast feedback.

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⚙️ Tech Stack

• 🧩 Frontend: React, Tailwind CSS
• 🧠 Backend: Python, Flask, PyAudio, WebSockets
• 📊 ML: Librosa, scikit-learn (Random Forest Classifier)
• 🚀 Workflow: Agile methodology in a 24-hour hackathon sprint using version control

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👥 Team

Built by Sumbhav, Finn and Alyson at Hackathon 2025

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📥 Clone & Run

1. Clone the repository:

   bash

   git clone https://github.com/HAGerox/rf-audio-monitor.git cd rf-audio-monitor

Frontend Setup:

Navigate to the frontend/ directory.

Run npm install to install the required dependencies.

bash cd frontend npm install

Backend Setup:

Navigate to the backend/ directory.

Install the Python dependencies from requirements.txt.

bash cd backend pip install -r requirements.txt Run the Application:

Start the frontend:

bash

npm run dev

In a new terminal, run the backend:

python server.py
python main_backend.py