Human-Centered Design of Cattle Behavior Monitoring System for Grazing in Abandoned Farmland

Abstract

The livestock industry faces a shortage of workers due to aging populations and falling numbers of young farmers. Researchers have collected and analyzed big data, and attempted to use it to improve livestock farming practices and reduce labor costs. We developed a cattle behavior monitoring system, PETER, using edge-AI and low-power wide-area (LPWA) technologies. PETER enables us to detect behaviors of grazing cattle (e.g., foraging, ruminating, walking, resting). Conversely, in the development of conventional livestock breeding support systems, user requirements are defined in a top-down manner. Few R&D projects feature user-centered design (UCD) or consider interactions between actors (e.g., farmers, livestock, technologies). This study aimed to apply UCD to the raising of grazing livestock, and to develop a prototype system offering farmers more precise and less labor-intensive livestock management.Our study started with fieldwork at a small grazing farm in Japan, located on abandoned farmland about 700 km from Tokyo. Two Japanese Black breeding cows are being raised and managed by a farmer and the farm owner. The farmer is employed part-time. The owner lives in Tokyo, is a veterinarian, and decides how to manage the cows. The information used by the owner to make decisions, such as nutritional deficiencies, or signs of disease or estrus, is provided only by the farmer. We investigated how remotely located veterinarians or owners could notice abnormalities in cattle and decide how to treat them, without waiting to consult the local farmer. Our UCD comprised three rounds: sketches; mock-ups; and finally functional prototypes to test and validate our ideas and hypotheses on users. We developed a web-based app as a functional user-interface prototype of PETER, showing the cows’ behavior history, the farm calendar, and the estimated amount of pasture grass. This information alone is insufficient for the farmer’s or owner’s understanding and decision-making. Therefore, the app can notify the chat communication service originally used by the farmer and owner whenever PETER detects possibly abnormal behavior in cattle, such as a reduced daily foraging or ruminating or walking duration, or an increase in resting duration. This is to attract their attention whenever PETER detects something unusual about the cattle. The farmer can then provide supplementary practical information on the spot, and the remote owner can make decisions and give instructions on the spot. During the four-week user test with the functional prototype, 10 notifications were made to the chat service, eight of which were supplemented with further information, such as farmers sending photos, and six of which confirmed the owner’s instructions and advice to the farmer. Some of the responses were confirmed, such as the owner calling a local veterinarian when a cow had diarrhea.This study shows that when the cattle behavior monitoring system detects any unusual information in pasture-raised livestock, it notifies the communication tool used by the owners, enabling them to take action before the matter becomes serious, even if they are remotely located. This study also indicates that the UCD approach is effective in the raising of pasture livestock.

Keywords: User-centered design, smart farm, cattle monitoring system

DOI: 10.54941/ahfe1001650