Leveraging YOLO for Real-Time Video Analysis of Animal Welfare in Pig Slaughtering Processes

Artificial intelligence has empowered digitization into a new era of intelligent systems. Machine learning solutions are being tailored to various application scenarios, leading to automated functionalities along complex real world processes. In this paper, we investigate the domain of animal welfare and present our latest findings in relation to the detection of animal welfare violations. To this end, we introduce four different situations of increased animal welfare risk occurring in a slaughtering process and elucidate different deep learning approaches to detect these situations based on video data. Though the reported results are considered to be preliminary, our solution already detects most of the situations of increased animal welfare risk with high accuracy.