sudo apt-get update
sudo apt-get install python3-pyaudio portaudio19-dev ffmpeg

Sound Monitor - Noise Pollution Documentation Tool

I hate loud cars so I made an application LOG WHEN THEY ARE TOO LOUD.

Professional Statatment:

An app for monitoring, recording, and documenting noise pollution to present evidence to city councils or other authorities.

GUI

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Features

Audio Recording & Storage

• Continuous Recording: Records audio continuously from your selected microphone

Sound Detection & Logging

• Real-time Decibel Monitoring: Tracks sound levels continuously
• Low-Frequency Detection: Specifically identifies low-frequency noise like car rumble (20-200 Hz)

Install

Ubuntu/Debian:

sudo apt-get update
sudo apt-get install python3-pyaudio portaudio19-dev ffmpeg

macOS:

brew install portaudio ffmpeg

Windows:

• Download and install FFmpeg
• PyAudio wheels available via pip

Python Dependencies

pip install -r requirements.txt

Usage

Starting the Application

python run.py

File Organization

The application creates the following structure at runtime:

sound-monitor/
├── sound_monitor.py          # Main application (1030+ lines, handles GUI, audio processing, database)
├── run.py                    # Launcher script with dependency checks
├── requirements.txt          # Python dependencies
├── setup.py                  # Installation script
├── test_sound_monitor.py     # Test suite
├── example_demo.py           # Demo with sample data
│
├── recordings/               # Audio recordings directory (created at runtime)
│   ├── YYYYMMDD_HHMMSS.mp3         # Regular 1-minute audio segments
│   ├── event_YYYYMMDD_HHMMSS_ffffff.mp3   # Detected loud events with pre/post buffers
│   └── temp_*.wav            # Temporary WAV files (cleaned up after MP3 conversion)
│
├── videos/                   # Video recordings directory (created at runtime, optional)
│   ├── event_YYYYMMDD_HHMMSS_ffffff.mp4   # Video recordings of loud events (if enabled)
│   └── ...
│
└── sound_events.db           # SQLite database with event logs
└── events table:
- id (PRIMARY KEY)
- timestamp (event time)
- duration (event length in seconds)
- peak_db (highest dB level)
- avg_db (average dB level)
- filename (audio file path)
- video_filename (optional video file path)
- low_frequency (boolean, car rumble detection)

Technical Details

• Sample Rate: 44.1 kHz
• Format: 16-bit PCM (recording), MP3 64kbps (storage)
• Channels: Mono
• Chunk Size: 1024 samples
• Segment Duration: 60 seconds
• dB Calculation: RMS-based, referenced to max int16 value, calibrated to ~94 dB SPL
• Low-Frequency Detection: FFT-based, 20-200 Hz range, >40% energy threshold

Support

For issues, questions, or suggestions, please open an issue on GitHub.