Trends and future directions of artificial intelligence applications in Iranian livestock production systems

Abstract

Abstract In recent years, the global quest for livestock intensification driven by ever-increasing demands for animal food products raised concerns about animal welfare, environmental sustainability, and public health. Leveraging artificial intelligence (AI) technologies such as remote sensing, Internet of Things (IoT), computer vision, and data-driven modeling has become a hotspot in livestock farming that could facilitate animal monitoring, disease detection, feed optimization, and health management. This review includes an assessment of these topics and research done in Iran so far, proposing future steps for the deployment of AI-powered technologies in farm applications. The Iranian livestock sector already seeing benefits from AI advancements and information technologies, however, most studies focused on model development without applications or deployment for the industry. Significant work is needed to address the limitations and challenges namely lack of data, economic feasibility, ethical concerns, infrastructure issues, and regulatory frameworks. Furthermore, reported AI-based methods and approaches have some inconsistencies in Iran that hinder validation. Looking forward, AI could create a new era in the livestock sector of Iran that not only copes with upcoming challenges but also boosts the circular economy making this country a pioneer in the region. However, tackling some potential limitations accompanying AI application in the Iranian livestock sector warrants the multi-disciplinary collaboration of veterinarians, computer scientists, animal nutritionists, agri-engineers, and governmental organizations.