SOFTWARE AND HARDWARE OF THE SUBSYSTEM FOR MEASURING TECHNOLOGICAL PARAMETERS OF THE BIOGAS PRODUCTION PROCESS USING THE INTERNET OF THINGS

Authors

  • Lendiel Taras National University of Life and Environmental Sciences of Ukraine image/svg+xml
  • Yevtushenko Maksym National University of Life and Environmental Sciences of Ukraine image/svg+xml
  • Safina Olga Kyiv Professional College of Urban Economy , Taurida National V.I. Vernadsky University image/svg+xml

DOI:

https://doi.org/10.31548/itees.2026.01.054

Keywords:

Biogas, Anaerobic Digestion, Measurement Subsystem, Bioreactor, Internet of Things

Abstract

The article considers the issue of building a model of a subsystem for measuring technological parameters of the biogas production process. The specified measurement subsystem will collect data on the fermentation process of biomaterials (organic raw materials) for an intelligent control system for the technological process of biogas production. In this case, the type of organic raw materials used will be indicated in the data collection process. This is necessary for forming a control action in the algorithm of the functioning of the automated biogas production control system. The features of anaerobic biomass fermentation are analyzed and the main technological parameters are indicated from the analysis of literary sources. This affects the efficiency of the biogas production process. A model of the measurement subsystem is proposed, which is considered as a technical tool for measuring parameters of the fermentation process of organic raw materials, while the specified approach is implemented using Internet of Things technologies. The structure of the hardware of the measurement subsystem is developed and calculations of measurement errors of the information and measurement channel are given. The implementation of the Internet of Things technology is presented on the basis of the created web server, which operates on the principle of a client-server system using HTTP requests. The developed model of the subsystem for measuring technological parameters provides for measurements in the real-time system, and all measurement data will be stored in a separate file to non-volatile memory, namely to a micro-SD memory card. The measured data file will be stored in CSV format, which will allow data to be processed via cloud services or the Microsoft Office Excel application package. The specified approach will also allow data systematization and the possibility of prompt adjustment, if necessary, of the technological process. The functionality of the proposed model of the subsystem for measuring technological parameters can be increased by improving software and hardware.

Received 2026-03-17

Accepted 2026-04-14

References

1. Holub, H. A. (Ed.), Kukharets, S. M., Marus, O. A., Pavlenko, M. Yu., Sera, K. M., & Chuba, V. V. (2017). Bioenergy systems in agricultural production: A textbook [Bioenerhetychni systemy v ahrarnomu vyrobnytstvi: Navchalnyi posibnyk]. NUBiP Ukrainy.

2. Skliar, O. H., Skliar, R. V., Boltianskyi, B. V., Syrotiuk, S. V., Korobka, S. V., & Stukalets, I. H. (2024). Analysis of methods of improving the process of processing organic animal waste in methane tanks [Analiz metodiv udoskonalennia protsesu pererobky orhanichnykh vidkhodiv tvarynnytstva u metantenkakh]. Scientific Bulletin of Tavria State Agrotechnological University, 14(1). https://doi.org/10.32782/2220-8674-2024-24-1-6.

3. Skliar, O.H., Skliar, R.V., & Akulov, V.D. (2024). Ways to increase the energy efficiency of a biogas installation [Shliakhy pidvyshchennia enerhetychnoi efektyvnosti biohazovoi ustanovky]. Proceedings of the Tavria State agrotechnological university, 24(2), 27–36. https://doi.org/10.32782/2078-0877-2024-24-2-3.

4. Abdurrahman, A. H., Kirom, M. R., & Suhendi, A. (2020). Biogas production volume measurement and Internet of Things based monitoring system. In 2020 IEEE International Conference on Communication, Networks and Satellite (Comnetsat) (pp. 213-217). IEEE. https://doi.org/10.1109/Comnetsat50391.2020.9328948.

5. Lysenko, V., Lendiel, T., Bolbot, I., & Pavlov, S. (2023). Mobile system for monitoring plant environment parameters for biogas production. Machinery & Energetics, 14(4), 111–120. https://doi.org/10.31548/machinery/4.2023.111.

6. Motornyi, A., & Kabachii, V. (2025). Automation of Household Waste Processing Enterprises: World Experience and Prospects for Ukraine [Avtomatyzatsiia pidpryiemstv pererobky pobutovykh vidkhodiv: Svitovyi dosvid ta perspektyvy dlia Ukrainy]. Visnyk of Vinnytsia Politechnical Institute, (4), 8–16. https://doi.org/10.31649/1997-9266-2025-181-4-8-16.

7. Zhou, M., & Zou, Z. (2018). Design of an intelligent control system for rural biogas engineering. In 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 1636-1639). IEEE. https://doi.org/10.1109/IMCEC.2018.8469547.

8. Onu, P., Mbohwa, C., & Pradhan, A. (2023). Artificial intelligence-based IoT-enabled biogas production. In 2023 International Conference on Control, Automation and Diagnosis (ICCAD) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCAD57653.2023.10152349.

9. Tohoiev, O. R., Puzyrov, S. V., Havrylko, S. M., & Zhulanov, M. O. (2025). Software and hardware complex for organizing voice communication in decentralized mesh networks [Prohramno-aparatnyi kompleks dlia orhanizatsii holosovoho zviazku v detsentralizovanykh mesh-merezhakh]. Methods and Devices of Quality Control, (2)(55), 121–129. https://doi.org/10.31471/1993-9981-2025-2(55)-121-129.

10. Vozár, M., & Ludas, N. (2025). Application of Arduino microcomputer. In 15th International Scientific Conference on Distance Learning in Applied Informatics: DiVAI 2024 (p. 271). Springer Nature.

11. Rani, D., Kaur, A., Mittal, R., Kaur, A., & Garg, N. (2025). Exploring Arduino board applications in embedded systems: The role of AI, cloud computing, and edge computing. In 2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI) (pp. 1730–1734). IEEE. https://doi.org/10.1109/ICCSAI64074.2025.11063918.

12. Raju, S. S., Wu, S., & Wang, N. (2025). Design and implementation of a multi-protocol converter supporting SPI, I2C, and UART interfaces. In 2025 8th International Conference on Information Communication and Signal Processing (ICICSP) (pp. 677–681). IEEE. https://doi.org/10.1109/ICICSP66564.2025.11338395.

13. Tsiutsiura, V. D., & Tsiutsiura, S. V. (2003). Metrology and fundamentals of measurements: A textbook [Metrolohiia ta osnovy vymiriuvan: Navchalnyi posibnyk]. Znannia-Pres.

14. Lysenko, V. P., Bolbot, I. M., Lendiel, T. I., & Chernov, I. I. (2014). Prohramno-aparatne zabezpechennia systemy fitomonitorynhu v teplytsi [Hardware and software support of the phytomonitoring system in a greenhouse]. Bulletin of the Petro Vasylenko Kharkiv National Technical University of Agriculture, (154), 42–45.

15. Palamar, M. I., Strembitskyi, M. O., & Palamar, A. M. (2019). Design of computerized measurement systems and complexes: A textbook [Proektuvannia kompiuteryzovanykh vymiriuvalnykh system i kompleksiv: Navchalnyi posibnyk]. TNTU.

Published

2026-04-22

Issue

Section

Automation, computer-integrated technologies and robotics