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Автор: search.filters.author.Kuanyshbek IgibayevТема: search.filters.subject.biogas quality

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    Development of an IoT System for Monitoring the Operation of a Biogas Plant
    (2025-07-04)
    Omirlan Auelbekov
    ;
    Айнур Козбакова
    ;
    Kuanyshbek Igibayev
    ;
    Kairat Yessentayev
    It is well known that the quality of biogas directly affects its energy value and efficiency of use in power plants, as well as determines the profitability of production. However, it can be difficult to identify deviations in the quality of biogas at early stages, especially in industrial conditions, as this requires in-depth knowledge of the physico-chemical characteristics of the gas. As part of this project, an intelligent biogas quality management system was developed using Internet of Things technologies designed to monitor key parameters such as temperature, methane levels and gas humidity. The ESP32 microcontroller, programmed in C, was used as the control module, which collected data from sensors and transferred them to cloud storage. A web application has also been created that provides the user with the ability to remotely monitor and control the system in real time from any device connected to the Internet. Notifications and alarms could be transmitted via WhatsApp messenger. The system has demonstrated high efficiency in increasing the stability and productivity of biogas production.
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    Тип записи:Публикация,
    An Internet of Things-Based Multisensor Platform for Biogas Monitoring and Experimental Data Analysis
    (Multidisciplinary Digital Publishing Institute, 2026-09-03)
    Omirlan Auelbekov
    ;
    Айнур Козбакова
    ;
    Kairat Yessentayev
    ;
    Kuanyshbek Igibayev
    This article discusses the intelligent analysis of multisensory biogas data obtained from an experimental dataset generated by a Lab-on-Chip platform. The relevance of this work stems from the need for real-time monitoring of biogas quality and biomass condition under anaerobic digestion conditions, where changes in the concentrations of methane, carbon dioxide, hydrogen sulfide, oxygen, and temperature directly affect the stability of the technological process and the energy efficiency of the plant. This study utilizes a multisensor Lab-on-Chip/biosensor platform designed for rapid analysis of small samples of biogas, biomass, and biomix. The platform integrates gas, liquid, and optical sensor channels, as well as a module for transmitting data to the cloud. The experimental data obtained are processed using intelligent data analysis methods, including statistical analysis, correlation analysis, anomaly detection, and assessment of the relationships between monitored parameters. The scientific significance of this work lies in the application of an integrated approach to the analysis of multichannel experimental data obtained from the ESP32 microcontroller, which enables a more accurate and timely assessment of the state of the biogas process. The practical significance lies in the ability to use the proposed approach for remote monitoring, early detection of anomalies, and improving the efficiency of biogas plant management.