Artificial Intelligence-Driven Decision Support System for Dairy Farm Operations: Findings from a Pilot Study

Abstract

This study is a preliminary exploration carried out within a Ph.D. Research project, focusing on creating an Intelligent Decision Support System (IDSS) to help improve the management of dairy farms in the Pune area. A survey was given to 50 dairy farmers to find out about their farming practices, how familiar they are with technology, the difficulties they face in running their farms, and how ready they are to use AI tools for making decisions. A reliability check using Cronbach's Alpha showed an overall score of 0.96, which means the results are very consistent internally. The Shapiro–Wilk test for normality showed that the data followed a normal distribution since the p-value was greater than 0.05. The pilot study showed that the research tool works well and is practical. It also showed that using Artificial Intelligence and Machine Learning methods like Random Forest, Decision Tree, Logistic Regression, and K-Means Clustering could be useful for improving dairy farms. The results show that the questionnaire works well for gathering data on a big scale and can help in creating an AI-based system to support decision-making in dairy farming, which can boost productivity, profits, and sustainability.