Coffee machine stages

Task: Sensor Fusion Classification

License: BSD 3-Clause Clear

Dataset Screenshot

Description

This dataset has been collected by Edge Impulse team to demonstrate how to perform Sensor Fusion Classification leveraging Neural Networks Embeddings.

Sensor fusion refers to the process of combining data from different types of sensors to give more information to the neural network. To extract meaningful information from this data, you can use the same DSP block, multiples DSP blocks, or use neural networks embeddings.

You can have a look at this tutorial for more information to see how to use this dataset.

This dataset combines audio data and accelerometer data.

Recommended Impulse

• Feature extraction: Audio Embeddings (Spectrogram + Convolution Neural Network Embeddings) + Spectral Analysis (accelerometer)

• Learning block: Classification using a fully-connected network

Dataset Details

• Total Data Items: 36

• Labeling Method: single label

• Train/Test Split: 91.67% / 8.33%

	Training Set	Testing Set
Total Data Items	33	3
Labels	extract, grind, idle, pump

Usage

• Clone the public project

  To clone and use this project, visit the Edge Impulse Studio link, click on the Clone button on the top-right corner and follow the cloning instructions.

• Download

  • Direct link

  • HuggingFace - Soon

  • Kaggle - Soon

• Import this dataset to your Edge Impulse project

  This project uses the Edge Impulse Exporter Format (info.labels). See this documentation page for more info.

  Edge Impulse also supports different data sample formats and dataset annotation formats that you can import into your project to build your edge AI models:

  • Studio uploader

  • CLI uploader

  • CSV Wizard

  • Python SDK

  • Ingestion API

  • Import from S3 buckets

  • Upload portals

Citation

If you use this dataset in your research paper, please cite it using the following BibTeX:

@misc{edgeimpulse_dataset_497832,
    title = {Sensor Fusion Classification - Coffee machine stages},
    author = {Edge Impulse},
    year = {2024},
    url = {https://studio.edgeimpulse.com/public/497832/latest},
    note = {Apache 2.0}
}