Software Sensors for the Monitoring of Bioprocesses

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F21%3A43921576" target="_blank" >RIV/60461373:22340/21:43921576 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-57802-2_20" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-57802-2_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-57802-2_20" target="_blank" >10.1007/978-3-030-57802-2_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Software Sensors for the Monitoring of Bioprocesses

Popis výsledku v původním jazyce

This paper presents various software based approaches suitable for the design of knowledge-based monitoring of biotechnological production processes. These processes require special treatment with respect to the complexity in biochemical reactions which make the design and construction of reasonably complex and practically usable mathematical models rather difficult. Additional complexity arises from the lack of industrially viable sensors for on-line measurement of key process variables. Software sensors which often use tools from the field of artificial intelligence represent one of the suitable approaches for the overcoming of the above mentioned limitations for its ability to utilize effectively both quantitative and qualitative knowledge about the monitored bioprocess. This approach is shown in practice using two different case studies of knowledge-based software sensors.

Název v anglickém jazyce

Software Sensors for the Monitoring of Bioprocesses

Popis výsledku anglicky

This paper presents various software based approaches suitable for the design of knowledge-based monitoring of biotechnological production processes. These processes require special treatment with respect to the complexity in biochemical reactions which make the design and construction of reasonably complex and practically usable mathematical models rather difficult. Additional complexity arises from the lack of industrially viable sensors for on-line measurement of key process variables. Software sensors which often use tools from the field of artificial intelligence represent one of the suitable approaches for the overcoming of the above mentioned limitations for its ability to utilize effectively both quantitative and qualitative knowledge about the monitored bioprocess. This approach is shown in practice using two different case studies of knowledge-based software sensors.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20902 - Bioprocessing technologies (industrial processes relying on biological agents to drive the process) biocatalysis, fermentation

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)

ISBN

978-3-030-57801-5

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

9

Strana od-do

207-215

Název nakladatele

Springer International Publishing Switzerland

Místo vydání

Cham

Místo konání akce

BURGOS

Datum konání akce

16. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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