Monitoreo y control inteligente de la fermentación alcohólica: avances en sensores, IoT e inteligencia artificial

Nahomi Rubí Llontop-Ayasta; Elthon Steven  Boñon Rocha; Ulises Benjamín Narro-Altamirano; Víctor Javier Vásquez-Villalobos

doi:10.37636/recit.v9n4e508

Autores/as

Nahomi Rubí Llontop-Ayasta Escuela de Ingeniería Agroindustrial, Universidad Nacional de Trujillo. Av. Juan Pablo II S/N, C.P. 13011. Ciudad Universitaria, Trujillo, Perú. https://orcid.org/0000-0002-9452-0343

Conflictos de interés

No expresa conflicto de intereses
Elthon Steven Boñon-Rocha Escuela de Ingeniería Agroindustrial, Universidad Nacional de Trujillo. Av. Juan Pablo II S/N, C.P. 13011. Ciudad Universitaria, Trujillo, Perú. https://orcid.org/0000-0003-4510-9731

Conflictos de interés

No expresa conflicto de intereses
Ulises Benjamín Narro-Altamirano Laboratorio de Biotecnología y Agropecuaria con Tecnología (BIOAGROTEC), Universidad Nacional de Trujillo. Av. Juan Pablo II S/N, Ciudad Universitaria, Trujillo, Perú. C.P. 13011. Urb. San Andrés, Trujillo, Perú https://orcid.org/0000-0002-8992-6154

Conflictos de interés

No expresa conflicto de intereses
Víctor Javier Vásquez-Villalobos Laboratorio de Biotecnología y Agropecuaria con Tecnología (BIOAGROTEC), Universidad Nacional de Trujillo. Av. Juan Pablo II S/N, Ciudad Universitaria, Trujillo, Perú. C.P. 13011. Urb. San Andrés, Trujillo, Perú. https://orcid.org/0000-0002-9625-8385

Conflictos de interés

No expresa conflicto de intereses

DOI:

https://doi.org/10.37636/recit.v9n4e508

Palabras clave:

Biosensores, Internet de las cosas (IoT), Bioprocesos, Análisis predictivo, Aprendizaje automático, Biomasa

Resumen

La fermentación alcohólica es un bioproceso ampliamente utilizado en la industria alimentaria y biotecnológica, cuyo seguimiento depende de la medición precisa de variables críticas como etanol, glucosa, CO₂, pH y biomasa. Esta revisión analiza investigaciones publicadas entre 2021 y 2026 sobre sensores electrónicos, tecnologías IoT e inteligencia artificial aplicadas al monitoreo, estimación, predicción y control de procesos fermentativos. La revisión se complementó con un análisis bibliométrico de 69 documentos recuperados de Scopus, publicados entre 1984 y 2026. El análisis se realizó con programas como Bibliometrix, VOSviewer y Scimago Graphica. Se evaluaron sensores electroquímicos, sistemas biomiméticos, sensores ópticos y físicos, además de plataformas inteligentes para el control en tiempo real y análisis predictivo. Las investigaciones revisadas apuntan hacia sistemas automatizados que facilitan la supervisión y el ajuste del proceso. Los sensores electroquímicos destacan por su sensibilidad y por medir varios parámetros a la vez. Las narices y lenguas electrónicas hacen un análisis indirecto apoyado en aprendizaje automático, y aun así dan buenos resultados. La espectroscopía y otros sistemas no invasivos suman la posibilidad de seguir varias variables al mismo tiempo sin intervenir en el proceso. No obstante, persisten desafíos relacionados a la calibración, estabilidad operativa, costos y validación industrial. En conjunto, la integración de sensores inteligentes, IoT e inteligencia artificial constituye una tendencia esencial para la modernización y automatización del control fermentativo.

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