Xingmeng Wang

Chongqing University of Science and Technology

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About

Xingmeng Wang is a researcher at the forefront of precision livestock farming, specializing in the application of advanced computer vision and deep learning techniques to animal health and welfare monitoring. Wang’s work is distinguished by a focus on developing autonomous, non-invasive systems for detecting and analyzing animal behavior and physiological states. A key contribution is the development of an autonomous inspection robot for detecting dead laying hens in caged layer houses, a practical innovation with 19 citations that addresses a critical need in poultry management. Wang also leads pioneering work in thermal infrared imaging, as demonstrated by the creation of the TIRPigEar dataset. This research explores how the stable physiological structure and rich vascular network of pig ears can be leveraged for health monitoring, showing that thermal patterns can reveal important temperature variations, even if not a direct proxy for core body temperature. By combining robotics with thermal and visible-light deep learning models, Wang is building the foundational tools for more humane, efficient, and data-driven animal agriculture.