Review: The application and challenges of advanced detection technologies in poultry farming
Weiqin Fan, Hui Peng, Diqi Yang
Abstract
With the rapid advancement of artificial intelligence, the Internet of Things (IoT), and big data, poultry breeding management is undergoing a critical transition from traditional manual practices to intelligent and automated systems. Intelligent detection technologies have appeared as a key driver for enhancing breeding efficiency and sustainability. This review focuses on the application of computer vision (CV), infrared thermography (IRT), radio frequency identification (RFID), and sound analysis technology (SAT) within modern poultry farming systems. Multi-technology integration proves considerable potential in key areas such as monitoring poultry behavior, detecting early-stage diseases, assessing semen quality, evaluating egg quality, and regulating rearing environments. However, challenges such as environmental interference, limited algorithm generalizability, lack of data standardization, and high equipment costs persist in practical applications. Future advancements need multimodal data integration, lightweight model development, standardized ecosystem construction, and ethical considerations for animal welfare. Continuous innovation in intelligent sensing technologies will drive the advancement of precision-based and efficiency-oriented poultry breeding systems, significantly improving production efficiency while reducing operational costs, thereby offering substantial promise for bolstering global food security and sustainable livestock production.