Artificial Intelligence in Smart Dairy Farming: A Review of Cattle Breed Recognition, Milk Production Prediction, and Voice-Based Assistance

Author

Ketan Ajay Bhoye, Shlok Kishor Kadam, Ankesh Kishor Sondkar, Dr. Kajol Chaudhari

Abstract

Artificial intelligence (AI) is being investigated in dairy farming for image-based animal analysis, milk-production forecasting, and access to agricultural information. These tasks use different data and methods: cattle recognition commonly uses computer vision and deep learning, milk-yield prediction uses historical records and machine-learning models, and conversational assistants use information retrieval and natural-language processing. This review examines representative research in these areas and considers multilingual speech technologies as a potential interface for farmers who prefer speaking rather than typing. Published studies show promising applications, but reported results depend on datasets, evaluation conditions, and the task being measured. The review identifies challenges involving dataset diversity, record quality, evidence-grounded answers, regional-language speech recognition, and real-world validation. Based on these findings, it discusses the proposed CowCare AI concept, which brings breed recognition, milk-production prediction, and a dairy question-answering assistant together in one farmer-oriented application. The paper presents an initial targeted review rather than an exhaustive systematic review; its conclusions should therefore be interpreted as a synthesis of selected literature.

Keywords

Artificial intelligence, smart dairy farming, cattle breed recognition, milk production prediction, machine learning, retrieval-augmented generation, multilingual voice assistant, precision agriculture.

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References

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