Artificial intelligence in ISES Measureserver for Remote Experiment Control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093205" target="_blank" >RIV/61989100:27240/14:86093205 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28140/14:43872136

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Artificial intelligence in ISES Measureserver for Remote Experiment Control

Popis výsledku v původním jazyce

The paper deals with the area of Internet School Experimental System (ISES) remote experiments in general and its core module called ISES Measu- reserver(R). In particular ISES Measureserver(R) is, in fact, a finite state machine, serving for the measured data accumulation, processing and providing commu- nication in the server-client system. Recently, we replenished ISES Measure- server(R) by a new functionality, namely diagnostics of the connected to the RE physical hardware, using the artificial intelligence solutions. In the introduction, the state of the art of ISES remote experiments is de- scribed. In the next chapter a consideration for the applying of proper artificial intelligence method to improve the Measureserver(R) reliability is made. Wefo- cused on the cognitive Fault Diagnosis System (FDS) intended for distributed sensor networks. FDS makes advantage of spatial and temporal relationship among sensors connected to RE physical hardware to give the information for reduct

Název v anglickém jazyce

Artificial intelligence in ISES Measureserver for Remote Experiment Control

Popis výsledku anglicky

The paper deals with the area of Internet School Experimental System (ISES) remote experiments in general and its core module called ISES Measu- reserver(R). In particular ISES Measureserver(R) is, in fact, a finite state machine, serving for the measured data accumulation, processing and providing commu- nication in the server-client system. Recently, we replenished ISES Measure- server(R) by a new functionality, namely diagnostics of the connected to the RE physical hardware, using the artificial intelligence solutions. In the introduction, the state of the art of ISES remote experiments is de- scribed. In the next chapter a consideration for the applying of proper artificial intelligence method to improve the Measureserver(R) reliability is made. Wefo- cused on the cognitive Fault Diagnosis System (FDS) intended for distributed sensor networks. FDS makes advantage of spatial and temporal relationship among sensors connected to RE physical hardware to give the information for reduct

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Nostradamus 2014: prediction, modeling and analysis of complex systems

ISBN

978-3-319-07400-9

ISSN

2194-5357

e-ISSN

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Počet stran výsledku

10

Strana od-do

411-421

Název nakladatele

Springer

Místo vydání

London

Místo konání akce

Ostrava

Datum konání akce

23. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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