Artificial Intelligence Evaluation of Environmental Enrichment for Stress Reduction in Goats

Abstract

Introduction: Animal stress management is essential for improving goat welfare, health, and productivity in modern livestock farming. Environmental enrichment practices provide opportunities to improve natural behaviours, reduce stress responses, and enhance overall animal well-being. However, conventional assessment methods mainly depend on manual observation, which is
time-consuming and difficult for continuous monitoring. This study developed an artificial intelligence-based framework to evaluate the impact of environmental enrichment on stress reduction in goats. The proposed approach analysed behavioural indicators, activity patterns, feeding behaviour, and social interactions under different enrichment conditions. The collected behavioural data were processed and evaluated using artificial intelligence techniques to identify stress-related patterns and assess welfare changes. The results demonstrated that AI-based analysis effectively recognized behavioural variations and supported accurate evaluation of enrichment effects on stress reduction. The framework enabled continuous monitoring of goat responses and provided valuable insights for improving welfare management practices. The study concluded that artificial intelligence can serve as an effective tool for automated animal welfare assessment by supporting evidence-based enrichment strategies, reducing stress levels, and promoting sustainable goat farming systems.