Artificial Intelligence in Meat Processing: A Comprehensive Review of Data-Driven Applications and Future Directions

Abstract

Traditional meat processing technologies and methods are predominantly manual and labor intensive, but they can be significantly optimized through automation and advanced data-driven systems. Artificial intelligence (AI) and internet of things technologies enable noninvasive, automated, and real-time solutions that enhance efficiency, safety, and consistency, while also reducing labor demands. These capabilities mark an inflection point in meat processing, with AI-driven solutions spanning every stage of the livestock sector, from meat production to quality assessment and market analysis. This review comprehensively explores existing research throughout the meat processing cycle, with a specific focus on data-driven AI applications that perform classification, regression, and image analysis tasks. The analysis emphasizes the types of data collected, the preprocessing strategies employed, and the AI models adopted. It also identifies key challenges, emerging trends, and potential pathways for future development, specifically highlighting opportunities to improve efficiency, safety, and sustainability. The insights presented herein offer valuable guidance for researchers and industry professionals seeking to advance meat processing technologies through AI-driven innovation.