{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T14:32:37Z","timestamp":1780410757872,"version":"3.54.1"},"reference-count":128,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T00:00:00Z","timestamp":1711584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2021R1I1A3049475"],"award-info":[{"award-number":["NRF-2021R1I1A3049475"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The increasing popularity of pigs has prompted farmers to increase pig production to meet the growing demand. However, while the number of pigs is increasing, that of farm workers has been declining, making it challenging to perform various farm tasks, the most important among them being managing the pigs\u2019 health and welfare. This study proposes a pattern mining-based pig behavior analysis system to provide visualized information and behavioral patterns, assisting farmers in effectively monitoring and assessing pigs\u2019 health and welfare. The system consists of four modules: (1) data acquisition module for collecting pigs video; (2) detection and tracking module for localizing and uniquely identifying pigs, using tracking information to crop pig images; (3) pig behavior recognition module for recognizing pig behaviors from sequences of cropped images; and (4) pig behavior analysis module for providing visualized information and behavioral patterns to effectively help farmers understand and manage pigs. In the second module, we utilize ByteTrack, which comprises YOLOx as the detector and the BYTE algorithm as the tracker, while MnasNet and LSTM serve as appearance features and temporal information extractors in the third module. The experimental results show that the system achieved a multi-object tracking accuracy of 0.971 for tracking and an F1 score of 0.931 for behavior recognition, while also highlighting the effectiveness of visualization and pattern mining in helping farmers comprehend and manage pigs\u2019 health and welfare.<\/jats:p>","DOI":"10.3390\/s24072185","type":"journal-article","created":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T12:22:46Z","timestamp":1711628566000},"page":"2185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Pattern Mining-Based Pig Behavior Analysis for Health and Welfare Monitoring"],"prefix":"10.3390","volume":"24","author":[{"given":"Hassan Seif","family":"Mluba","sequence":"first","affiliation":[{"name":"Department of Computer and Information Science, Korea University, Sejong City 30019, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6165-3297","authenticated-orcid":false,"given":"Othmane","family":"Atif","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Korea University, Sejong City 30019, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2077-4850","authenticated-orcid":false,"given":"Jonguk","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Convergence Software, Sejong Campus, Korea University, Sejong City 30019, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daihee","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Computer Convergence Software, Sejong Campus, Korea University, Sejong City 30019, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongwha","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Computer Convergence Software, Sejong Campus, Korea University, Sejong City 30019, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/s40781-015-0057-1","article-title":"Characteristics of pork belly consumption in South Korea and their health implication","volume":"57","author":"Choe","year":"2015","journal-title":"J. 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