Application of Computer-Based Techniques for Monitoring Animal Health, Behavior and Welfare: A Review

Abstract

This review explores the application of computer-based technologies for monitoring animal health, behavior, and welfare, focusing on innovative methods and their impact on modern animal management. Computerized monitoring systems, including sensors, wearables, and artificial intelligence, provide continuous, real-time data that enhances the accuracy and efficiency of tracking animal welfare indicators such as stress, disease, and environmental comfort. Advances in machine learning, IoT, and blockchain have further expanded capabilities, enabling predictive insights and ensuring data security and transparency. These technologies support early disease detection, facilitate better decision-making, and reduce human labor, addressing both productivity and welfare standards. However, challenges remain, such as high costs, ethical considerations, and potential stress from monitoring devices. Despite these limitations, emerging trends toward non-invasive and animal-friendly tools highlight a promising future for humane monitoring practices. This review concludes by discussing the broad implications for improved welfare and productivity in various settings and recommends continued innovation to overcome challenges and enhance technology adoption in animal welfare management.