{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T22:40:39Z","timestamp":1765233639275,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Science and Technology of Anhui Province","award":["2023n06020051","202103b06020013","202104a06020022","2022lhpysfjd023","2022cxcyjs010"],"award-info":[{"award-number":["2023n06020051","202103b06020013","202104a06020022","2022lhpysfjd023","2022cxcyjs010"]}]},{"name":"Anhui Province Department of Education","award":["2023n06020051","202103b06020013","202104a06020022","2022lhpysfjd023","2022cxcyjs010"],"award-info":[{"award-number":["2023n06020051","202103b06020013","202104a06020022","2022lhpysfjd023","2022cxcyjs010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The existing algorithms for identifying and tracking pigs in barns generally have a large number of parameters, relatively complex networks and a high demand for computational resources, which are not suitable for deployment in embedded-edge nodes on farms. A lightweight multi-objective identification and tracking algorithm based on improved YOLOv5s and DeepSort was developed for group-housed pigs in this study. The identification algorithm was optimized by: (i) using a dilated convolution in the YOLOv5s backbone network to reduce the number of model parameters and computational power requirements; (ii) adding a coordinate attention mechanism to improve the model precision; and (iii) pruning the BN layers to reduce the computational requirements. The optimized identification model was combined with DeepSort to form the final Tracking by Detecting algorithm and ported to a Jetson AGX Xavier edge computing node. The algorithm reduced the model size by 65.3% compared to the original YOLOv5s. The algorithm achieved a recognition precision of 96.6%; a tracking time of 46 ms; and a tracking frame rate of 21.7 FPS, and the precision of the tracking statistics was greater than 90%. The model size and performance met the requirements for stable real-time operation in embedded-edge computing nodes for monitoring group-housed pigs.<\/jats:p>","DOI":"10.3390\/s23218952","type":"journal-article","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T10:59:54Z","timestamp":1699009194000},"page":"8952","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Research on the Recognition and Tracking of Group-Housed Pigs\u2019 Posture Based on Edge Computing"],"prefix":"10.3390","volume":"23","author":[{"given":"Wenwen","family":"Zha","sequence":"first","affiliation":[{"name":"School of Information and Computer, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Hualong","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China"}]},{"given":"Guodong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information and Computer, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Liping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Economy and Information, Anhui Academy of Agricultural Sciences, Hefei 230031, China"}]},{"given":"Weihao","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Information and Computer, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Lichuan","family":"Gu","sequence":"additional","affiliation":[{"name":"School of Information and Computer, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Jun","family":"Jiao","sequence":"additional","affiliation":[{"name":"School of Information and Computer, Anhui Agricultural University, Hefei 230036, China"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.compag.2017.11.022","article-title":"Multi-level automation of farm management information systems","volume":"142","author":"Paraforos","year":"2017","journal-title":"Comput. 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