Computer Vision in Chicken Monitoring System Using Machine Learning: A General Review

¹ Doctoral Program of Information System, School of Postgraduate Studies, Diponegoro University, Semarang, 50275, Central Java, Indonesia
² Dept. of Animal Science, Faculty of Animal Science, Universitas Sebelas Maret, 57126, Central Java, Indonesia

^* Corresponding author: ekosupriyanto@students.undip.ac.id

Abstract

The chicken monitoring in closed cages is vital in welfare assessment and management of health factors. Computer vision can be relied upon for real-time automation of chicken health monitoring systems due to its non-invasive and invasive properties and its capacity to present a wide variety of information due to the development of information technologies. This article thoroughly overviews computer vision technology for poultry industry research. We recommend searching with the keywords 'computer vision' and 'chicken' or ‘broiler’ or 'health monitoring' or 'machine learning', or 'deep learning' were published between 2013 and early 2023 with open access provided by Diponegoro University only. All of the chosen articles were manually examined and categorized according to their applicability to computer vision in a poultry farm. This article summarizes the most recent developments in chicken health monitoring techniques utilizing computer vision systems, i.e., machine learning-based and deep learning-based systems. Prior to the successful implementation of this technology in the poultry industry, this article concludes by emphasizing the future work and significant challenges that must be addressed by researchers in the field of chicken health monitoring to guarantee the quality of this technology.