Computer Vision Driven Precision Dairy Farming for Efficient Cattle Management

Abstract

Precision Dairy Farming (PDF)” or “The Per Animal Approach” can be enhanced through the implementation of three-dimensional computer vision, which offers improved cattle identification, disease monitoring, and growth assessment. The integration of 3D vision systems is particularly vital for advancing dairy farming practices in the next generation. These systems facilitate the automation of various animal husbandry tasks, including monitoring, herding, feeding, milking, and bedding of animals. The applications of 3D computer vision in PLF encompass diverse platforms, such as 3D camera installations for monitoring cow walking postures, and intelligent systems that interact safely with animals, capable of identifying dairy cattle and detecting health indicators like animal identification, recognition, body condition score, and lameness. To be effective, systems must be adaptable to unconstrained environments, varying herd characteristics, weather conditions, farmyard layouts, and animal-machine interaction scenarios. Considering these requirements, this paper proposes the application of emerging computer vision and artificial intelligence techniques in dairy farming. This review encourages future research in three-dimensional computer vision for cattle growth management and its potential extension to other livestock and wild animals