<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>946</id>
    <completedYear>2020</completedYear>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>47</pageFirst>
    <pageLast>56</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>12</volume>
    <articleNumber/>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2020-12-30</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A framework for monitoring multiple databases in industries using OPC UA</title>
    <abstract language="eng">Database management and monitoring is an inseparable part of any industry. A uniform scheme of monitoring relational databases without explicit user access to database servers is not much explored outside the database environment. In this paper, we present an information distribution scheme related to databases using Open Platform Communication Unified Architecture (OPC UA) servers to clients when multiple databases are involved in a factory. The aim is for external, but relevant clients, to be able to monitor this information mesh independent of explicit access to user schemas. A methodology to dispense data from, as well as check changes in databases using SQL queries and events is outlined and implemented using OPC UA servers. The structure can be used as a remote viewing application for multiple databases in one address space of an OPC UA server.</abstract>
    <parentTitle language="eng">Journal of Ambient Intelligence and Humanized Computing</parentTitle>
    <identifier type="issn">1868-5145</identifier>
    <identifier type="urn">urn:nbn:de:bvb:573-9464</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1007/s12652-020-02850-x</enrichment>
    <enrichment key="THI_articleversion">published</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <licence>Creative Commons BY 4.0</licence>
    <author>
      <first_name>Selvine George</first_name>
      <last_name>Mathias</last_name>
    </author>
    <author>
      <first_name>Sebastian</first_name>
      <last_name>Schmied</last_name>
    </author>
    <author>
      <first_name>Daniel</first_name>
      <last_name>Großmann</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>OPC UA</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Relational databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Servers</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Clients</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aggregation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SQL</value>
    </subject>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="19310">Fakultät Wirtschaftsingenieurwesen</collection>
    <collection role="institutes" number="19379">AImotion Bavaria</collection>
    <collection role="persons" number="26836">Großmann, Daniel</collection>
    <thesisPublisher>Technische Hochschule Ingolstadt</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-haw/files/946/Mathias2021_AFrameworkForMonitoringMultipl-1.pdf</file>
  </doc>
</export-example>
