Method of remote monitoring of biomethane production parameters
DOI:
https://doi.org/10.31548/Abstract
The relevance of the study is determined by the need to improve the reliability, stability and controllability of biomethane production from agricultural organic waste. A key problem in the automation of biomethane plants is the insufficient reliability and continuity of remote monitoring data, which limits predictive control, anomaly detection and the development of digital twins. The purpose of the study is to develop a theoretical and methodological approach to ensuring data reliability and continuity in remote monitoring systems based on an integrated sensor-edge-SCADA architecture. The study applies system analysis, structural modelling and an analytical review of modern IoT, SCADA, edge computing and digital twin approaches. A method is proposed that includes multiparametric data acquisition, edge-based validation, calculation of an integral data reliability index and transmission of validated data to SCADA or cloud analytics. The proposed approach forms a methodological basis for further experimental validation and implementation of predictive analytics in agricultural biomethane plants.
Recieved: 28.03.2026. Recieved: 21.05.2026. Accepted: 22.06.2026
References
1. Ukrainian Energy. (2025). Biomethane in Ukraine: Prospects, challenges and export breakthrough. Retrieved from https://ua-energy.org/en/posts/18-06-2025-c7cd66e3-bc00-4f59-92b0-703783bd6027
2. CEENERGYNEWS. (2025). Despite the energy crisis Ukraine’s domestic biomethane market remains largely untapped – Q&A with Anna Pastukh from UABIO. Retrieved from https://ceenergynews.com/interviews/ukraine-biomethane-anna-pastukh/
3. Batstone, D. J., Keller, J., Angelidaki, I., Kalyuzhnyi, S. V., Pavlostathis, S. G., Rozzi, A., Sanders, W. T. M., Siegrist, H., & Vavilin, V. A. (2002). Anaerobic Digestion Model No. 1 (ADM1). London: IWA Publishing.
4. Schroer, H. W., & Just, C. L. (2024). Feature engineering and supervised machine learning to forecast biogas production during municipal anaerobic co-digestion. ACS ES&T Engineering, 4(3), 660–672. https://doi.org/10.1021/acsestengg.3c00435
5. Negara, I. G. A., Anakottapary, D. S., Widiantara, I. B. G., Midiani, L. P. I., Nindhia, T. G. T., & Santhiarsa, I. G. N. N. (2024). Integrated microcontroller MQ sensors for monitoring biogas: Advancements in methane and hydrogen sulfide detection. Jurnal Teknosains, 13(2), 140–151.
6. Gong, R., Xu, L., Li, X., et al. (2023). IoT-based edge computing (IoTEC) for improved environmental monitoring in precision agriculture using LoRa-based wireless sensor networks. Sustainability, 15, 7491. https://doi.org/10.3390/su15097491
7. Akhtar, M. N., Shaikh, A. J., Khan, A., Awais, H., Bakar, E. A., & Othman, A. R. (2021). Smart sensing with edge computing in precision agriculture for soil assessment and heavy metal monitoring: A review. Agriculture, 11(6), 475. https://doi.org/10.3390/agriculture11060475
8. Moser, A., Appl, C., Pörtner, R., Baganz, F., & Hass, V. C. (2024). A new concept for the rapid development of digital twin core models for bioprocesses in various reactor designs. Fermentation, 10(9), 463. https://doi.org/10.3390/fermentation10090463
9. Amirkhanov, B., Kunelbayev, M., Sabina, I., Amirkhanova, G., Nurgazy, T., Zhumasheva, A., & Alipbeki, O. (2025). Enhancing sustainable biogas generation through a real-time digital twin of a modular bioreactor. Journal of Advanced Digital Systems. Retrieved from http://bright-journal.org/Journal/index.php/JADS/article/download/779/496
10. International Energy Agency. (2020). Outlook for biogas and biomethane: Prospects for organic growth. Paris: IEA. Retrieved from https://www.iea.org/reports/outlook-for-biogas-and-biomethane-prospects-for-organic-growth
11. Holm-Nielsen, J. B., Al Seadi, T., & Oleskowicz-Popiel, P. (2009). The future of anaerobic digestion and biogas utilization. Bioresource Technology, 100(22), 5478–5484. https://doi.org/10.1016/j.biortech.2008.12.046
12. Appels, L., Baeyens, J., Degrève, J., & Dewil, R. (2008). Principles and potential of the anaerobic digestion of waste-activated sludge. Progress in Energy and Combustion Science, 34(6), 755–781. https://doi.org/10.1016/j.pecs.2008.06.002
13. ISO/IEC. (2018). ISO/IEC 30141:2018 Internet of Things (IoT) — Reference Architecture. Geneva: International Organization for Standardization.
14. IEC. (2018). IEC 62443 Industrial communication networks — Network and system security. Geneva: International Electrotechnical Commission.
15. Law of Ukraine No. 4742-IX “On Academic Integrity”. (2025, December 18). Retrieved from https://zakon.rada.gov.ua/laws/show/4742-20
Published
Issue
Section
License
Copyright (c) 2026 Energy and Automation
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All materials are disseminated under the terms of the Creative Commons Attribution 4.0 International Public License, which permits others to distribute the manuscript with proper acknowledgement of the authorship and the original publication in this journal.
