As global demands on the poultry production and welfare both intensify, the precision poultry farming technologies such as computer vision-based cybernetics and robotic system is becoming important in addressing the current issues related to animal welfare and production efficiencies. The integration of computer vision technology has become a catalyst for transformative change in precision farming, particularly concerning productivity and welfare. Precision farming is characterized by the precise management of food, water, and living conditions, and is particularly attentive to the health and well-being of the poultry. Animal welfare is a central component of this approach, acknowledging that healthier and less stressed animals yield greater productivity. Machine vision technologies are at the forefront of these innovations. They offer non-intrusive methods to monitor poultry, thereby supporting farm biosecurity and animal welfare. This technique, powered by advanced sensors and cameras, allows for subtle observations of poultry behavior and physiology, enhancing early detection capabilities while remaining non-invasive and maintaining biosecurity. The widespread implementation of computer vision for animal monitoring signifies a dramatic shift from conventional practices, utilizing a blend of learning algorithms to interpret behavior from visual data – a task that hinges on the precise extraction of features. Researchers at the University of Georgia summarized how cybernetics and robotics may aid the precision poultry management in the near future.
Fundamentals of Computer Vision in Poultry Management: Computer vision, rooted in interpreting visual data similarly to human vision, has seen a surge in applications, notably in animal farming. With the growing demand for poultry products due to a rising global population, the sector is pushed to maintain quality care for increasing numbers of animals. Traditional methods sometimes fail to detect early signs of abnormalities in animals, which may affect their health and productivity. To address this, computer vision technologies, particularly CNNs, provide objective and real-time monitoring tools. Emerging digital image acquisition technologies have enabled areas like digital image processing and image analysis, which play crucial roles in interpreting visual data. Modern sensors, such as infrared cameras and hyperspectral imaging tools, enable diverse applications in poultry farming, including behavior monitoring and body weight measurement. Cameras and sensors, the foundational components of computer vision, offer a holistic view of an environment when their data is fused. Red, green, and blue wavelengths (RGB) cameras, known for high-resolution images, capture the visual spectrum. Thermal infrared cameras provide insights into heat patterns, and depth sensors offer spatial information by combining with RGB data. However, challenges like the photogrammetric co-processing of thermal infrared and RGB images, make calibrated systems and advanced algorithms indispensable for accurate data interpretation. In poultry farming, obtaining clear visual data poses a challenge. Factors like dust, varying light conditions, and bird movement introduce noise and imperfections into raw images. Adaptive image noise removal tools, equipped with classification capabilities, ensure data remains free from visual degradation. Deep learning techniques further address challenges such as blur, shadows, and poor lighting. Therefore, specialized image processing techniques that cater to the unique challenges in poultry environments, like bird movement and dust, are essential for preparing data for further analysis. Figure 1 provides a succinct flowchart that illustrates the end-to-end integration of computer vision into poultry management, capturing each pivotal step from image acquisition to data-driven decision making.
Figure 1. The end-to-end process of computer vision-based cybernetics system in poultry management.
Integrating Robotics and Computer Vision: The integration of robotics and computer vision in poultry processing (Figure 2) reveals a landscape of innovative technologies aimed at enhancing efficiency and animal welfare. Existing poultry robots demonstrate the feasibility of using autonomous robots for tasks such as poultry health and welfare monitoring and warning or collection of dead chicken and floor eggs in commercial poultry houses, despite a need for further refinement in collection mechanisms and navigation systems. The advancements in evisceration are showcased by six degrees of freedom robot system, which used robotics and machine vision to achieve high accuracy in poultry incisions for evisceration.
Figure 2. Enhancing poultry sector security with computer vision-based robotics.
The convergence of robotics, computer vision, and ethology is not only enhancing production and efficiency but also contributing to better animal welfare and global health outcomes by enabling early detection of animal abnormal behaviors and removing unnormal birds in time, ensuring higher standards of food safety. As these technologies evolve, they hold the potential to address some of the most pressing challenges in the sector, including labor shortages, food safety, and disease surveillance. Figure 8 shows computer vision-based robotics and their roles of poultry sector.
Further reading: Yang, X., Bist, R.B., Paneru, B., Liu, T., Applegate, T., Ritz, C., Kim, W., Regmi, P. and Chai, L*., 2024. Computer Vision-Based cybernetics systems for promoting modern poultry Farming: A critical review. Computers and Electronics in Agriculture, 225, 109339. https://doi.org/10.1016/j.compag.2024.109339