A Deep Learning-Based Integrated Smart Dairy Farming System for Cattle Health Monitoring and Milk Quality Analysis

DOI

10.2991/978-94-6239-791-0_15How to use a DOI?

Keywords

Smart dairy farming; cattle health monitoring; Deep learning; EfficientNetV2; Random Forest classifier; precision livestock farming

Abstract

The modern dairy farming is shifting more towards intelligent and data-driven systems to improve productivity, animal welfare, and milk quality measurement. Nevertheless, conventional methods of monitoring are also based on manual observation leading to the late diagnosis of the disease and the lack of a consistent quality assessment. This research paper presents a proposed smart dairy farming system that integrates the deep learning and machine learning algorithms to create a real-time cattle health monitoring and milk quality predictive tool. Evaluation of various supervised learning models was done using a structured dataset comprising of physicochemical and sensory attributes. The highest precision, recall and F1-score was obtained with the Random Forest classifier with the highest accuracy of 95, compared to the K-Nearest Neighbors, Naive Bayes and Support Vector Machine classifiers. To detect cattle diseases, the EfficientNetV2 deep learning architecture was used in order to classify diseases like Lumpy Skin Disease, Bovine infections and Foot-and-Mouth Disease based on images. The model performed better as it was able to extract features efficiently and generalize features effectively. The proposed system combines the multi-domain data and offers a scalable, automated and reliable solution to the modern day management and decision support of a dairy farm.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Pratik Shingade
AU  - Adhik Sarak
AU  - Abhishek Walkoli
AU  - Lucky Ragde
AU  - Roshani Raut
AU  - Radha Deoghare
PY  - 2026
DA  - 2026/10/09
TI  - A Deep Learning-Based Integrated Smart Dairy Farming System for Cattle Health Monitoring and Milk Quality Analysis
BT  - Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
PB  - Atlantis Press
SP  - 176
EP  - 187
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-791-0_15
DO  - 10.2991/978-94-6239-791-0_15
ID  - Shingade2026
ER  -