{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T05:29:01Z","timestamp":1773984541301,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT\/MCTES through national funds","award":["UIDB\/50008\/2020-UIDP\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020-UIDP\/50008\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Animal monitoring is a task traditionally performed by pastoralists, as a way of ensuring the safety and well-being of animals; a tremendously arduous and lonely task, it requires long walks and extended periods of contact with the animals. The Internet of Things and the possibility of applying sensors to different kinds of devices, in particular the use of wearable sensors, has proven not only to be less invasive to the animals, but also to have a low cost and to be quite efficient. The present work analyses the most impactful monitored features in the behavior learning process and their learning results. It especially addresses the impact of a gyroscope, which heavily influences the cost of the collar. Based on the chosen set of sensors, a learning model is subsequently established, and the learning outcomes are analyzed. Finally, the animal behavior prediction capability of the learning model (which was based on the sensed data of adult animals) is additionally subjected and evaluated in a scenario featuring younger animals. Results suggest that not only is it possible to accurately classify these behaviors (with a balanced accuracy around 91%), but that removing the gyroscope can be advantageous. Results additionally show a positive contribution of the thermometer in behavior identification but evidences the need for further confirmation in future work, considering different seasons of different years and scenarios including more diverse animals\u2019 behavior.<\/jats:p>","DOI":"10.3390\/ani13010120","type":"journal-article","created":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T02:52:21Z","timestamp":1672282341000},"page":"120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["On the Development of a Wearable Animal Monitor"],"prefix":"10.3390","volume":"13","author":[{"given":"Lu\u00eds","family":"Fonseca","sequence":"first","affiliation":[{"name":"Departamento de Eletr\u00f3nica Telecomunica\u00e7\u00f5es e Inform\u00e1tica and Instituto de Telecomunica\u00e7\u00f5es, Universidade de Aveiro, 3830-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7484-1027","authenticated-orcid":false,"given":"Daniel","family":"Corujo","sequence":"additional","affiliation":[{"name":"Departamento de Eletr\u00f3nica Telecomunica\u00e7\u00f5es e Inform\u00e1tica and Instituto de Telecomunica\u00e7\u00f5es, Universidade de Aveiro, 3830-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0864-0809","authenticated-orcid":false,"given":"William","family":"Xavier","sequence":"additional","affiliation":[{"name":"iFarmTec\u2014Intelligent Farm Technologies, 3830-527 Gafanha da Encarna\u00e7\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7696-4231","authenticated-orcid":false,"given":"Pedro","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Escola Superior de Tecnologia e Gest\u00e3o de \u00c1gueda and Instituto de Telecomunica\u00e7\u00f5es, Universidade de Aveiro, 3830-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100429","DOI":"10.1016\/j.animal.2021.100429","article-title":"Review: Precision Livestock Farming Technologies in Pasture-Based Livestock Systems","volume":"16","author":"Aquilani","year":"2022","journal-title":"Animal"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"106610","DOI":"10.1016\/j.compag.2021.106610","article-title":"Predicting Livestock Behaviour Using Accelerometers: A Systematic Review of Processing Techniques for Ruminant Behaviour Prediction from Raw Accelerometer Data","volume":"192","author":"Riaboff","year":"2022","journal-title":"Comput. 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