[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127254-en":3,"doc-seo-127254-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127254,2336475104362,"Eden","https://ap-avatar.wpscdn.com/avatar/22000c4c46a41b752dd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786595829695023868",8,"Research & Report","Role of Machine Learning in Livestock Health Monitoring System - A Systematic Literature Review","Machine learning enhances livestock health monitoring by enabling real-time insights into animal behavior, wellbeing, and disease risk. A systematic review consolidates research on IoT devices for cattle health monitoring, emphasizing device characteristics, wearable technologies, sensor types, and machine learning algorithms. Studies published between 2018 and 2023 are examined and synthesized. Results indicate that pressure and pulse-rate sensors are among the most commonly used for capturing abnormal health status. The review also maps algorithm categories and welfare-focused measures.","Role of Machine Learning in Livestock Health Monitoring System: A Systematic Literature Review  \nMuhammad Mohsin Raza1, Rabia Tehseen1,2, Uzma Omer3,2, Muhammad Qasim1, Usman Aamer1, Ramsha Saeed1, Muhammad Farrukh Khan4  \n1 Department of Computer Science, University of Central Punjab, Lahore, Pakistan 2Department of Computer Science, University of Management & Technology, Lahore, Pakistan  \n3Department of Computer Science, University of Education, Lahore, Pakistan  \n4 Department of Computing, NASTP Institute of Information Technology, Lahore, Pakistan *Correspondence: [rabia.tehseen@ucp.edu.pk](rabia.tehseen@ucp.edu.pk)  \nCitation | Raza. M. M, Tehseen. R, Omer. U, Qasim. M, Aamer. U, Saeed. R, Khan. M. F,“Role of Machine Learning in Livestock Health Monitoring System: A Systematic Literature Review”, IJIST, Vol. 07 Issue. 02 pp 986-1005, May 2025  \nReceived| May 03, 2025 Revised| May 26, 2025 Accepted| May 27, 2025 Published| May 28, 2025.   \nMachine Learning (ML) can significantly enhance livestock management in various  \nways by providing real-time insights into animal health, behavior, and well-being.  \nLivestock production, monitoring, and management can be revolutionized by using ML techniques. This study presents a comprehensive review of the literature regarding IoT devices used for monitoring cattle health, key characteristics of these devices, wearable technology used, sensors, and ML algorithms. In order to complete the review, a thorough examination and synthesis of the research articles published in reputable research venues between 2018 and 2023 are conducted. The findings revealed that pressure and pulse-rate sensors are the most often utilized types for recording the health status of animals experiencing health issues.  \nKeywords: Machine Learning, IoT, Livestock Health System, Precision Livestock, Livestock Monitoring, Animal Welfare, Precision Farming, Livestock diseases  \nIntroduction:  \nMachine learning is a technique of Artificial Intelligence (AI) that involves training algorithms on huge datasets so that outcomes may be predicted or actions may be taken actions without being explicitly programmed. In healthcare, ML has the potential to revolutionize how we diagnose, treat, and prevent diseases [1] . While ML holds immense potential in healthcare, there are several challenges and considerations that need to be addressed for its effective and responsible application data quality, data availability, city, ethical, and bias considerations. Livestock plays a crucial role in global agriculture, providing a significant source of protein and other essential nutrients for human consumption. They support the economy by producing a range of goods and creating jobs in the agriculture industry. Notwithstanding, the livestock sector encounters obstacles concerning sustainability, animal welfare, and ecological consequences, prompting continuous deliberations and endeavors to enhance methodologies inside the sector [2]. Only about 11% of the world’s landarea is suitable for the production of foods that can be directly consumed by humans. About 75% of energy intake is consumed by ruminants and 30% from non-ruminants is from waste materials that cannot be consumed directly by the human population. With world food production already inadequately able to provide balanced diets for people of the world, it is important that we continue to utilize livestock [2] . Taking care of the health of livestock is essential for both the animals' well-being and the livestock industry's production, as they may encounter a variety of health issues. Mastitis, foot and mouth disease (FMD), reproductive problems, bovine, lameness, and avian are considered the top dairy cattle diseases [3] .  \nAddressing these health constraints requires a combination of preventative measures, veterinary care, and good management practices to ensure the overall well-being of livestock. Regular monitoring, early detection of health issues, and prompt interven","cbCairhCkZhpxL7D","https://ap.wps.com/l/cbCairhCkZhpxL7D","pdf",595535,1,20,"English","en",105,"# Introduction\n# Related Work\n# Research Methodology\n## Research Questions and Objectives\n## Search Scheme and Shortlisting Criteria\n## Review Procedure\n# Results and Analysis","[{\"question\":\"What is the main purpose of this systematic literature review?\",\"answer\":\"It provides a state-of-the-art review of smart technologies that support dairy animal health. It also categorizes machine learning algorithms reported or discussed in recent research and highlights measures linked to animal welfare.\"},{\"question\":\"Which IoT sensors are most frequently used for tracking livestock health status?\",\"answer\":\"Pressure and pulse-rate sensors are reported as the most often used sensor types for recording health status when animals experience issues.\"},{\"question\":\"How does combining IoT and machine learning help with livestock disease management?\",\"answer\":\"IoT enables real-time monitoring and data analytics, while machine learning supports prediction and continuous improvement as new data become available. Together they support early detection, timely interventions, and reduced disease spread.\"}]","Role of Machine Learning in Livestock Health Monitoring System - A Systematic Literature Review | PDF",1785937773,50,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"role-of-machine-learning-in-livestock-health-monitoring-system-a-systematic-literature-review","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/role-of-machine-learning-in-livestock-health-monitoring-system-a-systematic-literature-review/127254/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-22","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main purpose of this systematic literature review?","Question",{"text":76,"@type":77},"It provides a state-of-the-art review of smart technologies that support dairy animal health. It also categorizes machine learning algorithms reported or discussed in recent research and highlights measures linked to animal welfare.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which IoT sensors are most frequently used for tracking livestock health status?",{"text":81,"@type":77},"Pressure and pulse-rate sensors are reported as the most often used sensor types for recording health status when animals experience issues.",{"name":83,"@type":74,"acceptedAnswer":84},"How does combining IoT and machine learning help with livestock disease management?",{"text":85,"@type":77},"IoT enables real-time monitoring and data analytics, while machine learning supports prediction and continuous improvement as new data become available. 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