Journal of Korean Society of Agricultural Engineers ISSN:1738-3692(Print) 2093-7709(Online) 한국농공학회논문집

Greenhouse gases such as carbon dioxide, ammonia, and methane emitted from the livestock sector accelerate global warming, leading to abnormal weather phenomena like heatwaves and typhoons, which cause significant damage. In line with the 2050 Carbon Neutrality policy, efforts are required in the livestock sector to manage carbon emissions effectively and minimize greenhouse gas production. Carbon emissions in pig farming facilities are influenced by external environmental factors, internal environmental factors, and manure characteristics. to estimate and predict carbon emissions accurately, the collection of big data on these influencing factors is essential. However, in real farms, it is challenging to measure the factors that affect carbon emissions, and there are significant difficulties in collecting big data. Furthermore, a thorough validation process is required for the practical application of the collected data. In this study, a small-scale smart pig farming engineering experimental and demonstration facility will be established to collect and monitor data on key influencing factors for carbon emissions, such as internal environmental factors and manure characteristics. Additionally, using various ICT devices, data on carbon emissions under specific conditions, such as feed intake control, feed type changes, ventilation, and temperature adjustments, can be collected. Therefore, it is expected that the design of a carbon emission prediction algorithm will be possible through the measurement and analysis of carbon emissions.