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Artificial intelligence in ISES Measureserver for Remote Experiment Control

The result's identifiers

  • Result code in 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>

  • Alternative codes found

    RIV/70883521:28140/14:43872136

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Artificial intelligence in ISES Measureserver for Remote Experiment Control

  • Original language description

    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

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Nostradamus 2014: prediction, modeling and analysis of complex systems

  • ISBN

    978-3-319-07400-9

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    411-421

  • Publisher name

    Springer

  • Place of publication

    London

  • Event location

    Ostrava

  • Event date

    Jun 23, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article