https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Khaddaj_et_al_2020aKhaddaj et al 2020a - Revision history2026-04-25T21:42:26ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Khaddaj_et_al_2020a&diff=212722&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 105860426 to Khaddaj et al 2020a2021-02-12T13:54:26Z<p>Scipediacontent moved page <a href="/public/Draft_Content_105860426" class="mw-redirect" title="Draft Content 105860426">Draft Content 105860426</a> to <a href="/public/Khaddaj_et_al_2020a" title="Khaddaj et al 2020a">Khaddaj et al 2020a</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Khaddaj_et_al_2020a&diff=212721&oldid=prevScipediacontent: Created page with " == Abstract == Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heter..."2021-02-12T13:54:22Z<p>Created page with " == Abstract == Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heter..."</p>
<p><b>New page</b></p><div><br />
== Abstract ==<br />
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Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heterogeneous data, in order to perform smart analytics of urban networks in real time. However, dynamic response that relies on intelligent demand-side transport management is particularly challenging due to the increasing flow of transmitted sensor data. In this work, a novel smart service-driven, adaptable middleware architecture is proposed to acquire, store, manipulate, and integrate information from heterogeneous data sources in order to deliver smart analytics aimed at supporting strategic decision-making. The architecture offers adaptive and scalable data integration services for acquiring and processing dynamic data, delivering fast response time, and offering data mining and machine learning models for real-time prediction, combined with advanced visualisation techniques. The proposed solution has been implemented and validated, demonstrating its ability to provide real-time performance on the existing, operational, and large-scale bus network of a European capital city.<br />
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Document type: Article<br />
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== Full document ==<br />
<pdf>Media:Draft_Content_105860426-beopen436-8715-document.pdf</pdf><br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [http://dx.doi.org/10.1155/2020/8894705 http://dx.doi.org/10.1155/2020/8894705] under the license http://creativecommons.org/licenses/by/4.0/<br />
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* [https://doi.org/10.1155/2020/8894705 https://doi.org/10.1155/2020/8894705]<br />
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* [http://downloads.hindawi.com/journals/jat/2020/8894705.pdf http://downloads.hindawi.com/journals/jat/2020/8894705.pdf],<br />
: [http://downloads.hindawi.com/journals/jat/2020/8894705.xml http://downloads.hindawi.com/journals/jat/2020/8894705.xml],<br />
: [http://dx.doi.org/10.1155/2020/8894705 http://dx.doi.org/10.1155/2020/8894705] under the license cc-by<br />
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* [http://downloads.hindawi.com/journals/jat/2020/8894705.pdf http://downloads.hindawi.com/journals/jat/2020/8894705.pdf],<br />
: [https://www.hindawi.com/journals/jat/2020/8894705 https://www.hindawi.com/journals/jat/2020/8894705],<br />
: [https://academic.microsoft.com/#/detail/3087166688 https://academic.microsoft.com/#/detail/3087166688] under the license http://creativecommons.org/licenses/by/4.0/<br />
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* [http://dx.doi.org/10.1155/2020/8894705 http://dx.doi.org/10.1155/2020/8894705],<br />
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],<br />
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195]</div>Scipediacontent