arXiv Open Access 2024

Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms

Mónica Mora Lucile Riaboff Ingrid David Juan Pablo Sánchez Miriam Piles

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Abstrak

This study explores how wearable accelerometers, small devices that measure acceleration, can help monitor the activity of growing rabbits. We equipped 16 rabbits with these devices and filmed them for two weeks. By watching the videos and using a special software we figure out what the rabbits were doing -- things like lying down, eating, moving around, and more. These activitties were grouped into two states: active or inactive. Then, this information along acceleration data was used to teach a computer program to recognize when the rabbits were active or not. This technology offers a reliable way to understand rabbit behavior, which could lead to better management practices in animal production.

Topik & Kata Kunci

eess.SP

Penulis (5)

Mónica Mora

Lucile Riaboff

Ingrid David

Juan Pablo Sánchez

Miriam Piles

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APA MLA BibTeX

Mora, M., Riaboff, L., David, I., Sánchez, J.P., Piles, M. (2024). Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms. https://arxiv.org/abs/2407.04729

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓