Template-Type: ReDIF-Article 1.0
Author-Name:Muhammad  Mohsin  Raza, Rabia  Tehseen1,  Uzma  Omer,  Muhammad  Qasim,  Usman Aamer, Ramsha Saeed,Muhammad Farrukh Khan
Author-Email:rabia.tehseen@ucp.edu.pk
Author-Workplace-Name:Department of Computer Science, University of Central Punjab, Lahore, Pakistan, Department  of  Computer  Science,  University  of  Management  &  Technology,  Lahore, Pakistan, Department of Computer Science, University of Education, Lahore, Pakistan, Department of Computing, NASTP Institute of Information Technology, Lahore, Pakistan
Title:Role of Machine Learning in Livestock Health Monitoring System: A Systematic Literature Review
Abstract:Machine  Learning  (ML)  can  significantly  enhance  livestock  management  in  various ways  by  providing  real-time  insights  into  animal  health,  behavior,  and  well-being. Livestock 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. 
Keywords:Machine Learning, IoT, Livestock Health System, Precision Livestock, Livestock Monitoring, Animal Welfare, Precision Farming, Livestock diseases
Journal:International Journal of Innovations in Science and Technology
Pages:986-1005
Volume:7
Issue:2
Year:2025
Month:May
File-URL:https://journal.50sea.com/index.php/IJIST/article/view/1403/1917
File-Format: Application/pdf
File-URL:https://journal.50sea.com/index.php/IJIST/article/view/1403
File-Format: text/html
Handle: RePEc:abq:IJIST:v:7:y:2025:i:2:p:986-1005