A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit <a rel="external noopener" href="https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200810">the original URL</a>. The file type is <code>application/pdf</code>.
<i title="IOS Press">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/g4albir3gzbibgdotf5bxnbkxu" style="color: black;">Frontiers in Artificial Intelligence and Applications</a>
Recently, more and more attention has been paid to ship intelligence. However, in the sensor data acquisition network represented by the integrated ship bridge system, sensor data is collected and transmitted point to point, and the data coupling is strong, which is not conducive to the hierarchical utilization of data. To provide more effective data communication methods and flexible support to applications, intelligent integrated platform is needed by modern ship. Prototype design and<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3233/faia200810">doi:10.3233/faia200810</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n2wd6jgkwjczldqbjlcqcrj3gq">fatcat:n2wd6jgkwjczldqbjlcqcrj3gq</a> </span>
more »... of a ship intelligent platform is proposed, and the key technologies of the platform is discussed. The overall architecture of the platform is described. A hybrid network architecture with fieldbus, real-time ethernet and ethernet information network is introduced. And data storage architecture using NoSQL and hadoop distributed file system is described. The system can meet the real-time performance requirement of the control and information communication. An energy efficiency application based on the designed platform is developed, machine learning based method is employed to predict the heavy oil fuel consumption for ship navigation.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715153822/https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200810" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/94/7294ef1dc1b34a30369e5d53954ac0c5127a3f96.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3233/faia200810"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>