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Research demonstrates improved biogas measurement accuracy in anaerobic digestion tests using an Arduino-based IoT device, suggesting better monitoring of methane production.
The manual manometric (MM) method is widely used in batch anaerobic digestion tests, such as the biochemical methane potential (BMP) and the specific methanogenic activity (SMA), but it can cause inaccuracies due to biogas loss during measurements. This study presents an IoT-based biogas pressure measurement device developed with an Arduino microcontroller to improve accuracy and reliability in batch tests. The device supports four reactors and was tested in 250 mL glass vessels with varying headspace (20 and 50%) and substrate/inoculum ratios (0.5 and 0.2). Two tests were performed: one with glucose (11 days) and another with food waste (60 days). A third 30 h test compared the IoT device to the MM method under identical conditions. All tests used inoculum from a septic tank. The results showed that the MM method underestimates biogas production, with an average biogas loss of 50.7 ± 12.9 mbar per measurement. These losses increased at higher reactor pressures. Implementing IoT-based monitoring in BMP or SMA testing improves measurement accuracy, enables early failure detection, and facilitates efficient data management. In addition, the IoT device allows real-time observation of early biogas production dynamics, including acidogenic and methanogenic activity, as well as the detection of potential methanogenesis inhibition.
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Pérez–Vidal et al. (2025) studied this question.
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