Development of an Internet of Things–based real-time greenhouse gas and weather monitoring system for precision dairy farming

The environmental footprint of dairy production is one of the most pressing challenges faced by the industry globally. Our study aimed to develop and validate a cost-effective sensing solution for real-time monitoring of dairy farms' GHG emissions and microclimatic conditions. Each of the integrated sensing nodes was equipped with carbon dioxide (CO₂), methane (CH₄), and ammonia (NH₃) gas sensors, along with an all-in-one weather sensor. Sensing nodes were validated against gold-standard measurements using open-circuit respiration chambers with individual cows under controlled conditions. The CH₄ emissions (133.0 ± 22.5 ppm, mean ± SD) showed an overall correlation (r = 0.46) with the gold-standard respiration chamber (166.0 ± 32.8 ppm) across all 3 d. However, the correlation changed over time, with a strong correlation on d 1 (r = 0.62), a moderate correlation on d 2 (r = 0.35), and a weak correlation on d 3 (r = 0.11). In contrast, sensor node quantified CO₂ emissions (905 ± 779 ppm) showed a weaker correlation (r = 0.019, 2,461 ± 346 ppm), indicating the need for further improvements to the sensing node. A wireless network of calibrated sensing nodes was deployed in 3 different locations within a dairy farm: dry cow pen (DCP), feed bunk (FB), and freestall beds (FSB) at a research dairy farm. The CH₄ emissions were greater in the DCP (12.5 ± 6.65 ppm) compared with FB (2.80 ± 0.61 ppm) and FSB (2.34 ± 0.62 ppm). The CO₂ emissions at the FB were greater (1,498 ± 1,020 ppm) compared with the DCP (534 ± 222 ppm) and FSB (724 ± 517 ppm). The NH₃ emissions were highest in the FSB (4.24 ± 0.91 ppm) compared with DCP (2.93 ± 1.35 ppm) and FB (1.10 ± 0.44 ppm). The differences in GHG emissions across the different areas of the dairy farm may be influenced by ambient temperature, humidity, housing conditions, and manure management practices. Our sensing nodes may provide a low-cost, scalable sensing network that can offer a practical solution for continuous GHG monitoring.