报告详情
  1. 活动首页
  2. 报告清单
  3. 报告详情
Machine Learning-Based Prediction and Classification of Bovine Diseases Using Physiological and Environmental Indicators
编号：120 访问权限：仅限参会人 更新：2025-12-23 13:12:26 浏览：104次 拓展类型2

报告开始：2025年12月30日 16:45（Asia/Amman）

报告时间：15min

所在会场：[S2] Track 2: IoT and applications [S2-2] Track 2: IoT and applications

视频 无权播放 演示文件

提示：该报告下的文件权限为仅限参会人，您尚未登录，暂时无法查看。

摘要
Animal health is integral to food security, rural livelihoods, and economic sustainability, particularly in developing nations like India where cattle form the backbone of the livestock sector. However, traditional methods of diagnosing bovine diseases are often time-consuming, resource-intensive, and inaccessible to small-scale farmers. This paper proposes a data-driven approach using machine learning (ML) models for the early prediction and classification of cattle diseases based on physiological and environmental indicators. A structured preprocessing pipeline was applied to a numerical dataset capturing features such as body temperature, heart rate, saliva pH, and more. Multiple classifiers including Linear Discriminant Analysis (LDA), Gaussian Naïve Bayes, Decision Trees, K-Nearest Neighbors (KNN), Linear SVM, and Logistic Regression were evaluated on accuracy, log-loss, and class-wise performance metrics. Results indicate that probabilistic models such as LDA and Gaussian Naïve Bayes outperform others, achieving high accuracy (>98%) and robust generalization across disease types. The study demonstrates the feasibility and effectiveness of intelligent disease prediction systems in livestock health monitoring and provides insights into the most reliable ML models for real-world deployment.
 
关键词
Cattle Disease Prediction, Machine Learning, Animal Health Monitoring, Gaussian Naïve Bayes, Physiological Indicators, Early Diagnosis Systems
报告人
Gurmeet Kaur
Assistant Professor Department of Computer Science & Engineering, University Institute of Engineering, Chandigarh University, Mohali-140413, Punjab, India

稿件作者
Gurmeet Kaur Department of Computer Science & Engineering, University Institute of Engineering, Chandigarh University, Mohali-140413, Punjab, India
Yogesh Kumar India； Gandhinagar；Department of CSE； School of Technology； Pandit Deendayal Energy University
Hani Hattar Zarqa University
Mohamed Hafez INTI-IU-University;Shinawatra University
Parvathaneni Naga Srinivasu India；Amrita School of Computing； Amrita Vishwa Vidyapeetham； Amaravati
Muhammad Umair Manzoor Australia；School of Engineering RMIT University； Melbourne
Muhammad Fazal Ijaz Australia；Torrens University
发表评论
验证码 看不清楚，更换一张
全部评论
重要日期

  • 会议日期

    12月29日

    2025

    至

    12月31日

    2025

  • 12月30日 2025

    报告提交截止日期

  • 02月10日 2026

    初稿截稿日期

  • 02月10日 2026

    注册截止日期

主办单位
国际科学联合会
承办单位
扎尔卡大学
联系方式
登录查看完整联系方式
历届会议
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询