Chicken Behavior Analysis for Surveillance in Poultry Farms

Abstract

Poultry farming is an important industry that provides food for a growing population. However, the welfare of the birds is a major concern, as poor living conditions leads to abnormal behavior that affects the health and productivity of the flock. In order to monitor and improve the welfare of the birds, it is important to have a surveillance system in place that monitors the behavior of the chickens and alert farmers to potential issues. This paper reviews the current state of the art in behavior analysis for surveillance in poultry farms and discuss potential future directions for research in this area. This paper presents a computer-vision-based system that detects and monitors the behaviors of the chickens in poultry farms. The system classifies three behaviors which are eating, walking and sleeping. The system takes videos as input and then classifies the behavior of the chicken. The proposed system produces an accuracy of 94.7% using Light Gradient Boosting Machine on a collected data-set of chickens, and a 98.4% accuracy on a benchmarked Human Activity Recognition data-set.