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March 14, 2026ACS Omega0 citationsOpen Access

Low-Cost IoT-Based Computational System for Real-Time Biogas Monitoring in UASB Reactors Using NDIR Sensors and ESP32

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FNFlávio César Brito NunesInstituto Federal de Educação, Ciência e Tecnologia do CearáPAPrecival Victor Andrade AlvesInstituto Federal de Educação, Ciência e Tecnologia do CearáAGAllan Bruno Dantas GonçalvesUniversidade Federal do Cariri

Key Points

  • This research aims to develop a low-cost IoT system for monitoring biogas production in UASB reactors.
  • Developed an IoT system integrating NDIR and temperature sensors
  • Conducted deployment in a bench-scale UASB reactor
  • Monitored CH4 and flow rates over 30 days, measuring stability and latency
  • Achieved average latency of approximately 1.77 seconds
  • Recorded flow rates of 42.84–76.16 NL·d–1 and CH4 levels of 53.31–88.0%
  • Demonstrated low sensor drift and temporal agreement with measurements and estimates

Abstract

UASB reactors are widely employed in wastewater treatment due to their operational simplicity and the potential for energy recovery from biogas, although continuous, low-cost monitoring of CH4 and flow rate remains challenging. This work presents the development and validation of an IoT system for remote, real-time monitoring, integrating NDIR sensors for CH4/CO2, a temperature sensor, a pressure sensor, a thermal mass flow meter, and an ESP32 platform with web/mobile interfaces. Deployment was carried out in a bench-scale UASB reactor treating an industrial slaughterhouse effluent. Over 30 days of continuous operation, stable data transmission was recorded with an average latency of ∼1.77 s; measurements covered 42.84–76.16 NL·d–1 (flow) and 53.31–88.0% (CH4), with temperature within a narrow mesophilic range (22.25–27.80 °C) and near-zero sensor drift. Estimates based on removed chemical oxygen demand (COD), normalized to STP, yielded 45.18–74.72 NL·d–1 (flow). Temporal agreement with the measured series was observed (MAE = 6.58 NL·d–1 and 4.69 percentage points; MAPE = 9.88% and 6.69% for flow and composition, respectively). This modular, fault-tolerant architecture demonstrates feasibility for supporting operational control and assessing the methane energy potential in decentralized applications.

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Cite This Study

Nunes et al. (2026) studied this question.

synapsesocial.com/papers/69b4b9eb18185d8a398022c6https://doi.org/10.1021/acsomega.5c12291
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