A Novel Hybrid Model Based on Machine and Deep Learning Techniques for the Classification of Microalgae

Kaya, Volkan; Akgül, İsmail; Tanır, Özge Zencir

doi:10.32604/phyton.2023.029811

Phyton

2023

DOI: 10.32604/phyton.2023.029811

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A Novel Hybrid Model Based on Machine and Deep Learning Techniques for the Classification of Microalgae

Volkan Kaya¹,

İsmail Akgül²,

Özge Zencir Tanır³

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2024

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Software sensors in the monitoring of microalgae cultivations

Porras Reyes,

Havlik,

Beutel

2024

Rev Environ Sci Biotechnol

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Microalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the outstanding characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters, mostly concentrations of intracellular components, in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of Industry 4.0. In this review, a description of the microalgae components of interest as candidates for monitoring in a cultivation, an overview of software sensors, some of the available approaches and tools, and the current state-of-the-art of the design and use of software sensors in microalgae cultivation are presented. The latter is grouped on the basis of measurement methods used as software sensor inputs, employing either optical or non-optical techniques, or a combination of both. Some examples of software sensor design using simulated process data are also given, grouped according to their design, either as model-driven or data-driven estimators.

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Software sensors in the monitoring of microalgae cultivations

Porras Reyes,

Havlik,

Beutel

2024

Rev Environ Sci Biotechnol

View full text Add to dashboard Cite

show abstract

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A Novel Hybrid Model Based on Machine and Deep Learning Techniques for the Classification of Microalgae

Cited by 1 publication

References 0 publications

Software sensors in the monitoring of microalgae cultivations

Software sensors in the monitoring of microalgae cultivations

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