Published August 3, 2023 | Version v1
Dataset Open

Data for "ChickenSense: A low-cost deep learning-based solution for real-time poultry feed intake monitoring using sound technology"

  • 1. University of Tennessee Knoxville
  • 1. University of Tennessee Knoxville

Description

The dataset includes two types of data: scale and audio. The scale data is recorded using a hanging scale and measures the feeders' weight with a 5 Hz frequency. The audio data contains 1824 hours of recorded audio using a piezo-electric sensor attached to a bucket feeder to capture vibrations as audio signals with a sampling rate of 48 kHz. Each .wav file contains 15 minutes of audio recording.
Along with the raw data, a part of the dataset containing 36 30-second audio recordings was sampled and labeled in four classes, including pecking, singing, anomaly, and silence, resulting in 3319 labeled events. 

Notes

This project is funded through AgResearch at the University of Tennessee and the United States Department of Agriculture AFRI Program (Award No. 2022-68014-36663).

Files

Dataset.zip

Files (68.9 GB)

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