AcousticsLab
AcousticsLab is a cross-platform framework for sound and vibration analysis, with advanced algorithms for anomaly detection and audio classification integrated and optimized, we deliver a simple, universal, and robust acoustics analysis toolkit for MCUs and SBCs.
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AcousticsLab

AcousticsLab is a cross-platform framework for sound and vibration analysis, with advanced algorithms for anomaly detection and audio classification integrated and optimized, we deliver a simple, universal, and robust acoustics analysis toolkit for MCUs and SBCs.

Getting Started

Please follow the instructions in ESP-IDF - Get Started to setup the build toolchain first. Currently we're using the latest version v5.4.1.

  1. Clone and setup the repository.

    git clone https://github.com/Seeed-Studio/AcousticsLab.git --depth=1
    cd AcousticsLab
    git submodule update --init

  2. Build and run examples (replace DEMO with the example you want to run).

    cd examples/${DEMO}
    idf.py set-target esp32s3
    idf.py build
    idf.py flash monitor

Web Console

AcousticsLab implements a user-friendly web interface to visualize audio/vibration data, control the device, and view results in real-time.

Console Preview

  1. Install the required python dependencies.

    pip3 install -r requirements.txt

  2. Launch console with the device connected to your computer via USB cable.

    python3 scripts/console.py --help # see available options
    python3 scripts/console.py # launch console with default options
  3. Open the console in your web browser at http://localhost:7860.

Algorithms

AcousticsLab aims to provide a comprehensive set of SOTA algorithms for sound and vibration analysis. The current implementation includes:

  • Gyroscope Euclidean Distance Anomaly Detection (GEDAD): A lightweight algorithm for detecting anomalies in gyroscope and 3-axis accelerometer data.
  • Speech Commands: An algorithm for recognizing keywords and simple audio events, compatible with models trained using tools like Google's Teachable Machine.

Architecture Overview

This diagram shows a modular embedded AI architecture. It features a layered design with a Hardware Abstraction Layer (HAL), a Core Library (with DSP/ML), an API, and an Application layer. The architecture is designed to simplify development and integrate easily with platforms like Arduino and MicroPython.

Architecture Overview

The high-level architecture consists of 2 main components:

  • Acoustics: features the core functionality for sound and vibration analysis, including algorithms for anomaly detection and audio classification.
  • Acoustics-Porting: provides the hardware abstraction layer (HAL) for the Acoustics component, allowing it to run on different hardware platforms.

License

This software is licensed under the GPLv3 license, see [LICENSE](LICENSE) for more information.