Modeling Climate Change Impacts on Cattle Behavior Using Generative Artificial Intelligence: A Pathway to Adaptive Livestock Management

Amid the increasing challenges of climate change, including rising temperatures, extreme weather events, and erratic precipitation, it is imperative to devise adaptive strategies for livestock exposed to these environmental shifts. This study delves into the innovative use of generative artificial intelligence (genAI) to predict the effects of future climatic scenarios on cattle behavior using wearable sensor data. The pronounced impact of climate-induced heat stress on cattle significantly affects their behavior, health, welfare, and key factors such as performance and reproduction, ultimately influencing the quality and quantity of livestock products. Unlike conventional machine learning models, genAI's distinctive capability to generate synthetic data for anticipated environmental conditions offers insights into cattle behavior under extreme future climates. Our study begins with a comprehensive review of existing research on the impact of climate change on cattle behavior and the use of wearable sensor data, particularly accelerometer data, to predict cattle behavior. We then explore recent weather projections to set the context for our predictive modeling. Building on previous work utilizing genAI for synthetic sensor data generation, we introduce a two-stage approach for modeling the effects of climate change on cattle behavior. First, we create varied climatic scenarios and generate synthetic accelerometer data using genAI. Subsequently, utilizing the synthesized sensor data, we employ an appropriate AI model to predict cattle behavior under forecasted future environmental conditions. This innovative methodology underscores the potential of genAI in advancing predictive livestock management and climate adaptation strategies. By enabling farmers to proactively adapt to and mitigate the effects of climate change, our research represents a significant step forward in agricultural systems engineering.