AMB_2024v14n5

2 Current Applications of Machine Learning in Prec	43
2.1 Animal health monitoring	43
2.2 Milk production optimization	43
2.3 Reproduction and fertility management	43
2.4 Environmental monitoring and management	43
3 Data Sources for Machine Learning in Dairy Farmi	44
3.1 Sensor technology and IoT devices	44
3.2 Genomic data and animal genetics	44
3.3 Behavioral and environmental data	44
4 Machine Learning Models and Techniques Used	45
4.1 Supervised learning in dairy farming	45
4.2 Unsupervised learning techniques	45
4.3 Deep learning approaches	46
5 Challenges and Limitations in Applying Machine L	46
5.1 Data quality and availability	46
5.2 Integration with traditional farming practices	47
5.3 Ethical and privacy concerns	47
6 Case Study: Predictive Health Monitoring in a La	47
6.1 Farm overview and setup	47
6.2 Use of machine learning for disease prediction	47
7 Future Prospects of Machine Learning in Precisio	48
7.1 Advancements in ml algorithms and their potent	48
7.2 Integration of ML with robotics and automated	48
7.3 Role of cloud computing and big data analytics	48
7.4 Policy and regulatory support for ml adoption	48
8 Concluding Remarks	48

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