{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:17:34Z","timestamp":1792790254539,"version":"4.5.0"},"reference-count":42,"publisher":"Korean Society of Animal Science and Technology","issue":"5","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"funder":[{"name":"Ministry of Agriculture, Food and Rural\n                                Affairs","award":["319093-04"],"award-info":[{"award-number":["319093-04"]}]},{"name":"Seoul National University of Science and\n                                Technology"}],"content-domain":{"domain":["www.ejast.org"],"crossmark-restriction":true},"short-container-title":["J Anim Sci Technol"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:p>Broilers are bred at a higher density than large livestock, and their relatively\n                    small size makes monitoring challenging, requiring a reliable, cost-effective\n                    automatic monitoring system for precision farming. Particularly in the case of\n                    managing large-scale broiler breeding systems, such as multi-tier broiler\n                    houses, it is important to reduce investment in computing facilities and to\n                    improve productivity through automatic monitoring technology. However, financial\n                    ability of farmers to equip and manage the high-specification computing\n                    equipment required by these technologies is limited, necessitating development\n                    of affordable monitoring systems. We there propose a lightweight\n                    broiler-detection model that augments YOLOv5 with two efficiency modules:\n                    Bi-directional Feature Pyramid Network (BiFPN), which fuses multi-scale features\n                    with learnable weights to sharpen small-object and GhostNet, which replaces many\n                    convolutions with inexpensive \u201cghost\u201d operations to cut\n                    parameters. Performance was benchmarked against the original YOLOv5 on a\n                    high-spec local GPU machine and CPU based cloud platform. The proposed model\n                    attained 90.5% mAP@0.5, marginally below the baseline\u2019s 92.8%, yet\n                    inference time dropped by 30% on CPU (50.9 ms) and 50% on GPU (1.8 ms). By\n                    implementing lightweight models, farmers can utilize monitoring systems from\n                    anywhere via mobile devices, leveraging cloud-based technology. This eliminates\n                    the necessity for expensive hardware, offering an affordable and practical\n                    solution for improving farming management.<\/jats:p>","DOI":"10.5187\/jast.2400235","type":"journal-article","created":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T02:20:32Z","timestamp":1755656432000},"page":"1631-1644","update-policy":"https:\/\/doi.org\/10.5187\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Broiler detection system for multi-tier broiler house using a cloud\n                    platform"],"prefix":"10.5187","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1435-9207","authenticated-orcid":false,"given":"Jung-sang","family":"Yoo","sequence":"first","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8459-7814","authenticated-orcid":false,"given":"Chang-hyup","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3017-5146","authenticated-orcid":false,"given":"Jung-Sun Gloria","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2395-4387","authenticated-orcid":false,"given":"JoonYong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2177-0031","authenticated-orcid":false,"given":"Ghiseok","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"},{"name":"Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9608-4362","authenticated-orcid":false,"given":"Taehyeong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"},{"name":"Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6351-4055","authenticated-orcid":false,"given":"Joong Yong","family":"Rhee","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Seoul National University, Seoul, Korea"},{"name":"Convergence Major in Global Smart Farm, Seoul National University, Seoul, Korea"},{"name":"Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3132","published-online":{"date-parts":[[2026,9,30]]},"reference":[{"key":"key2.0261013094154e+13_B1","doi-asserted-by":"crossref","first-page":"107347","DOI":"10.1016\/j.compag.2022.107347","article-title":"Y-BGD: broiler counting based on multi-object\n                        tracking","volume":"202","author":"Li","year":"2022","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B2","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.1017\/S175173112000110X","article-title":"Early intensification of backyard poultry systems in the tropics:\n                        a case study","volume":"14","author":"Chaiban","year":"2020","journal-title":"Animal"},{"key":"key2.0261013094154e+13_B3","doi-asserted-by":"crossref","first-page":"E108","DOI":"10.1016\/S1473-3099(16)00153-5","article-title":"Global epidemiology of avian influenza A H5N1 virus infection in\n                        humans, 1997\u20132015: a systematic review of individual case\n                        data","volume":"16","author":"Lai","year":"2016","journal-title":"Lancet Infect Dis."},{"key":"key2.0261013094154e+13_B4","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1007\/s10640-020-00484-3","article-title":"Infectious diseases and meat production","volume":"76","author":"Espinosa","year":"2020","journal-title":"Environ Resour Econ."},{"key":"key2.0261013094154e+13_B5","doi-asserted-by":"crossref","first-page":"793","DOI":"10.3389\/fgene.2020.00793","article-title":"Large-scale phenotyping of livestock welfare in commercial\n                        production systems: a new frontier in animal breeding","volume":"11","author":"Brito","year":"2020","journal-title":"Front Genet."},{"key":"key2.0261013094154e+13_B6","first-page":"31","article-title":"Effects of stocking density on immune function and oxidative\n                        stress level of Peking ducks reared on plastic wire-floor","volume":"37","author":"LuShuang","year":"2015","journal-title":"China Poult."},{"key":"key2.0261013094154e+13_B7","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1079\/WPS20020037","article-title":"Some alternative litter materials used for growing broilers and\n                        turkeys","volume":"58","author":"Grimes","year":"2002","journal-title":"World\u2019s Poult Sci J."},{"key":"key2.0261013094154e+13_B8","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.3390\/ijerph16193521","article-title":"How safe is chicken litter for land application as an organic\n                        fertilizer?: a review","volume":"16","author":"Kyakuwaire","year":"2019","journal-title":"Int J Environ Res Public Health"},{"key":"key2.0261013094154e+13_B9","doi-asserted-by":"crossref","first-page":"763","DOI":"10.3382\/japr.2014-01000","article-title":"Effect of ventilation on distributions, concentrations, and\n                        emissions of air pollutants in a manure-belt layer house","volume":"23","author":"Wang","year":"2014","journal-title":"J Appl Poult Res."},{"key":"key2.0261013094154e+13_B10","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1017\/S1751731115000713","article-title":"Welfare of organic laying hens kept at different indoor stocking\n                        densities in a multi-tier aviary system. I: Egg laying, and use of veranda\n                        and outdoor area","volume":"9","author":"Steenfeldt","year":"2015","journal-title":"Animal"},{"key":"key2.0261013094154e+13_B11","doi-asserted-by":"crossref","unstructured":"Fabian-Wheeler\n                            E\n                        \n                    \n                    Unintended impacts on animal welfare and environment of combined farm\n                        animal housing with manure storage\n                    In\n                    10th International Livestock Environment Symposium (ILES\n                        X)\n                    2018 Sep 25-27\n                    Omaha, NE\n                    10.13031\/iles.18-137","DOI":"10.13031\/iles.18-137"},{"key":"key2.0261013094154e+13_B12","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.3390\/agriculture12081176","article-title":"A dead broiler inspection system for large-scale breeding farms\n                        based on deep learning","volume":"12","author":"Hao","year":"2022","journal-title":"Agriculture"},{"key":"key2.0261013094154e+13_B13","doi-asserted-by":"crossref","first-page":"6","DOI":"10.2527\/af.2017.0102","article-title":"General introduction to precision livestock\n                        farming","volume":"7","author":"Berckmans","year":"2017","journal-title":"Anim Front"},{"key":"key2.0261013094154e+13_B14","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.compag.2008.05.005","article-title":"Is precision livestock farming an engineer\u2019s daydream or\n                        nightmare, an animal\u2019s friend or foe, and a farmer\u2019s panacea\n                        or pitfall?","volume":"64","author":"Wathes","year":"2008","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B15","doi-asserted-by":"crossref","first-page":"105291","DOI":"10.1016\/j.compag.2020.105291","article-title":"Smart poultry management: smart sensors, big data, and the\n                        Internet of things","volume":"170","author":"Astill","year":"2020","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B16","doi-asserted-by":"crossref","first-page":"3055","DOI":"10.3390\/ani12213055","article-title":"An advanced chicken face detection network based on GAN and\n                        MAE","volume":"12","author":"Ma","year":"2022","journal-title":"Animals"},{"key":"key2.0261013094154e+13_B17","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.biosystemseng.2023.06.006","article-title":"Domain adapted broiler density map estimation using\n                        negative-patch data augmentation","volume":"231","author":"Kim","year":"2023","journal-title":"Biosyst Eng."},{"key":"key2.0261013094154e+13_B18","doi-asserted-by":"crossref","first-page":"3179","DOI":"10.3390\/s20113179","article-title":"A machine vision-based method for monitoring broiler chicken\n                        floor distribution","volume":"20","author":"Guo","year":"2020","journal-title":"Sensors"},{"key":"key2.0261013094154e+13_B19","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.biosystemseng.2019.01.003","article-title":"Detection of sick broilers by digital image processing and deep\n                        learning","volume":"179","author":"Zhuang","year":"2019","journal-title":"Biosyst Eng."},{"key":"key2.0261013094154e+13_B20","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.compag.2018.11.022","article-title":"Behavior-induced health condition monitoring of caged chickens\n                        using binocular vision","volume":"156","author":"Xiao","year":"2019","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B21","doi-asserted-by":"crossref","first-page":"105596","DOI":"10.1016\/j.compag.2020.105596","article-title":"Analysis of feeding and drinking behaviors of group-reared\n                        broilers via image processing","volume":"175","author":"Li","year":"2020","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B22","doi-asserted-by":"crossref","first-page":"2628","DOI":"10.1017\/S1751731120001676","article-title":"A machine vision system to detect and count laying hens in\n                        battery cages","volume":"14","author":"Geffen","year":"2020","journal-title":"Animal"},{"key":"key2.0261013094154e+13_B23","doi-asserted-by":"crossref","first-page":"3823515","DOI":"10.1155\/2019\/3823515","article-title":"Recognition and classification of broiler droppings based on deep\n                        convolutional neural network","volume":"2019","author":"Wang","year":"2019","journal-title":"J Sens."},{"key":"key2.0261013094154e+13_B24","first-page":"2553","article-title":"Deep neural networks for object detection","volume":"26","author":"Szegedy","year":"2013","journal-title":"Adv Neural Inf Process Syst."},{"key":"key2.0261013094154e+13_B25","doi-asserted-by":"crossref","first-page":"104700","DOI":"10.1016\/j.livsci.2021.104700","article-title":"A review of deep learning algorithms for computer vision systems\n                        in livestock","volume":"253","author":"Oliveira","year":"2021","journal-title":"Livest Sci."},{"key":"key2.0261013094154e+13_B26","doi-asserted-by":"crossref","unstructured":"Lee\n                            J\n                        \n                        \n                            Wang\n                            J\n                        \n                        \n                            Crandall\n                            D\n                        \n                        \n                            \u0160abanovi\u0107\n                            S\n                        \n                        \n                            Fox\n                            G\n                        \n                    \n                    Real-time, cloud-based object detection for unmanned aerial\n                        vehicles\n                    In\n                    2017 First IEEE International Conference on Robotic Computing\n                        (IRC)\n                    2017\n                    10.1109\/IRC.2017.77","DOI":"10.1109\/IRC.2017.77"},{"key":"key2.0261013094154e+13_B27","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.compag.2017.06.008","article-title":"Architecting an IoT-enabled platform for precision agriculture\n                        and ecological monitoring: a case study","volume":"140","author":"Popovi\u0107","year":"2017","journal-title":"Comput Electron Agric."},{"key":"key2.0261013094154e+13_B28","doi-asserted-by":"crossref","first-page":"37050","DOI":"10.1109\/ACCESS.2019.2903720","article-title":"Internet of things monitoring system of modern eco-agriculture\n                        based on cloud computing","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"key2.0261013094154e+13_B29","doi-asserted-by":"crossref","first-page":"8929","DOI":"10.1007\/s10586-018-2022-5","article-title":"Agricultural product monitoring system supported by cloud\n                        computing","volume":"22","author":"Jinbo","year":"2019","journal-title":"Clust Comput."},{"key":"key2.0261013094154e+13_B30","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1109\/TCC.2017.2672554","article-title":"Multimedia processing pricing strategy in GPU-accelerated cloud\n                        computing","volume":"8","author":"Li","year":"2017","journal-title":"IEEE Trans Cloud Comput."},{"key":"key2.0261013094154e+13_B31","doi-asserted-by":"crossref","unstructured":"Han\n                            K\n                        \n                        \n                            Wang\n                            Y\n                        \n                        \n                            Tian\n                            Q\n                        \n                        \n                            Guo\n                            J\n                        \n                        \n                            Xu\n                            C\n                        \n                        \n                            Xu\n                            C\n                        \n                    \n                    Ghostnet: more features from cheap operations\n                    In\n                    2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition\n                        (CVPR)\n                    2020\n                    10.1109\/CVPR42600.2020.00165\n                    30334799","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"key2.0261013094154e+13_B32","doi-asserted-by":"crossref","unstructured":"Tan\n                            M\n                        \n                        \n                            Pang\n                            R\n                        \n                        \n                            Le\n                            QV\n                        \n                    \n                    EfficientDet: scalable and efficient object recognition\n                    In\n                    2020 IEEE\/CVF Conference on Computer Vision and Pattern\n                        Recognition\n                    2020\n                    10.1109\/CVPR42600.2020.01079","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"key2.0261013094154e+13_B33","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/LCA.2018.2839189","article-title":"The architectural implications of cloud\n                        microservices","volume":"17","author":"Gan","year":"2018","journal-title":"IEEE Comput Arch Lett."},{"key":"key2.0261013094154e+13_B34","author":"Bochkovskiy","year":"2020","journal-title":"Yolov4: Optimal speed and accuracy of object detection\n                        [Preprint]"},{"key":"key2.0261013094154e+13_B35","doi-asserted-by":"crossref","unstructured":"Wang\n                            CY\n                        \n                        \n                            Liao\n                            HYM\n                        \n                        \n                            Wu\n                            YH\n                        \n                        \n                            Chen\n                            PY\n                        \n                        \n                            Hsieh\n                            JW\n                        \n                        \n                            Yeh\n                            IH\n                        \n                    \n                    CSPNet: a new backbone that can enhance learning capability of\n                        CNN\n                    In\n                    2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition\n                        Workshops (CVPRW)\n                    2020\n                    10.1109\/CVPRW50498.2020.00203","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"key2.0261013094154e+13_B36","doi-asserted-by":"crossref","unstructured":"Wang\n                            K\n                        \n                        \n                            Liew\n                            JH\n                        \n                        \n                            Zou\n                            Y\n                        \n                        \n                            Zhou\n                            D\n                        \n                        \n                            Feng\n                            J\n                        \n                    \n                    Panet: few-shot image semantic segmentation with prototype\n                        alignment\n                    In\n                    2019 IEEE\/CVF International Conference on Computer Vision\n                        (ICCV)\n                    2019\n                    10.1109\/ICCV.2019.00929","DOI":"10.1109\/ICCV.2019.00929"},{"key":"key2.0261013094154e+13_B37","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1007\/s11263-022-01575-y","article-title":"GhostNets on heterogeneous devices via cheap\n                        operations","volume":"130","author":"Han","year":"2022","journal-title":"Int J Comput Vis."},{"key":"key2.0261013094154e+13_B38","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.5187\/jast.2021.e127","article-title":"A deep learning-based approach for feeding behavior recognition\n                        of weanling pigs","volume":"63","author":"Kim","year":"2021","journal-title":"J Anim Sci Technol."},{"key":"key2.0261013094154e+13_B39","doi-asserted-by":"crossref","first-page":"519","DOI":"10.5187\/jast.2022.e87","article-title":"Automatic identification and analysis of multi-object cattle\n                        rumination based on computer vision","volume":"65","author":"Wang","year":"2023","journal-title":"J Anim Sci Technol."},{"key":"key2.0261013094154e+13_B40","doi-asserted-by":"crossref","first-page":"846","DOI":"10.5187\/jast.2023.e76","article-title":"A study of duck detection using deep neural network based on\n                        RetinaNet model in smart farming","volume":"66","author":"Lee","year":"2024","journal-title":"J Anim Sci Technol."},{"key":"key2.0261013094154e+13_B41","doi-asserted-by":"crossref","first-page":"103514","DOI":"10.1016\/j.dsp.2022.103514","article-title":"A survey of modern deep learning based object detection\n                        models","volume":"126","author":"Zaidi","year":"2022","journal-title":"Digit Signal Process"},{"key":"key2.0261013094154e+13_B42","doi-asserted-by":"crossref","first-page":"548","DOI":"10.3390\/info13110548","article-title":"Object detection based on YOLOv5 and GhostNet for orchard\n                        pests","volume":"13","author":"Zhang","year":"2022","journal-title":"Information"}],"container-title":["Journal of Animal Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.ejast.org\/download\/download_pdf?doi=10.5187\/jast.2400235","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/www.ejast.org\/download\/download_pdf?doi=10.5187\/jast.2400235","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T07:44:30Z","timestamp":1791877470000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.ejast.org\/archive\/view_article?doi=10.5187\/jast.2400235"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":42,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,9,30]]},"published-print":{"date-parts":[[2026,9]]}},"alternative-id":["10.5187\/jast.2400235"],"URL":"https:\/\/doi.org\/10.5187\/jast.2400235","relation":{},"ISSN":["2672-0191","2055-0391"],"issn-type":[{"value":"2672-0191","type":"print"},{"value":"2055-0391","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"2024-07-11","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-14","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}