Intelligent monitoring and control of alcoholic fermentation: advances in sensors, IoT and artificial intelligence
DOI:
https://doi.org/10.37636/recit.v9n4e508Keywords:
Biosensors, Internet of Things (IOT), Bioprocesses, Predictive analytics, Machine learning, BiomassAbstract
Alcoholic fermentation is a widely used bioprocess in the food and biotechnology industries, the monitoring of which depends on the precise measurement of critical variables such as ethanol, glucose, CO₂, pH, and biomass. This review analyzes research published between 2021 and 2026 on electronic sensors, IoT technologies, and artificial intelligence applied to the monitoring, estimation, prediction, and control of fermentation processes. The review was complemented by a bibliometric analysis of 69 documents retrieved from Scopus, published between 1984 and 2026. The analysis was performed using software such as Bibliometrix, VOSviewer, and Scimago Graphica. Electrochemical sensors, biomimetic systems, optical and physical sensors, as well as intelligent platforms for real-time control and predictive analysis, were evaluated. The reviewed research points toward automated systems that facilitate process monitoring and adjustment. Electrochemical sensors stand out for their sensitivity and ability to measure multiple parameters simultaneously. Electronic noses and tongues perform indirect analysis supported by machine learning, and still yield good results. Spectroscopy and other non-invasive systems add the ability to monitor several variables simultaneously without intervening in the process. However, challenges related to calibration, operational stability, costs, and industrial validation persist. Overall, the integration of smart sensors, IoT, and artificial intelligence is a key trend for the modernization and automation of fermentation control.
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This is a review article, which the reviewed research points towards automated systems that make it easier to monitor and adjust the process.
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