{"id":3472,"date":"2022-01-01T00:00:00","date_gmt":"2022-01-01T00:00:00","guid":{"rendered":"https:\/\/isdefeinnova.es\/proyectos\/cl-vcon-clustering-connected-vehicles\/"},"modified":"2026-02-13T13:20:50","modified_gmt":"2026-02-13T13:20:50","slug":"cl-vcon-clustering-connected-vehicles","status":"publish","type":"proyectos","link":"https:\/\/isdefeinnova.es\/en\/projects\/cl-vcon-clustering-connected-vehicles\/","title":{"rendered":"CL-VCON &#8211; Clustering Connected Vehicles"},"content":{"rendered":"\n<p><em>Winner of the 2021 Isdefe&#8217;s IDEAS challenge (7th edition)<\/em><\/p>\n\n<p><strong>Internal R&amp;D project<\/strong><\/p>\n\n<p>Isdefe&#8217;s internal R&amp;D project <em><strong>Clustering of Connected Vehicles<\/strong><\/em> (CL-VCON) aims to obtain useful information about a fleet of vehicles by applying clustering techniques (unsupervised machine learning algorithms).<\/p>\n\n<p>Data from the vehicles are collected by means of sensors installed in the vehicles. The information from the sensors is stored for further analysis using clustering algorithms. <\/p>\n\n<p>The project will result in vehicle information related to the following concepts:<\/p>\n\n<ul class=\"wp-block-list\">\n<li>Detect anomalous or defective vehicles<\/li>\n\n\n\n<li>Anticipate breakdowns by benchmarking vehicles with similar behaviour.<\/li>\n\n\n\n<li>Detect vehicle misuse and driving deficiencies.<\/li>\n\n\n\n<li>Environmental recommendations for driving (consumption, gas emissions).<\/li>\n\n\n\n<li>Graphical display of connected vehicles according to their similarities.<\/li>\n<\/ul>\n\n<p>The advantage of applying such algorithms is that less time is needed to collect data from the vehicles and it is not necessary to have a vehicle maintenance history in order to achieve useful results for predictive vehicle maintenance.<\/p>\n\n<p>The project is being developed in the UME with a fleet of 25 Renault K-430 vehicles. The contract is currently being awarded to the company that will carry out the instrumentation of the vehicles. <\/p>\n\n<p>In this project, data is downloaded from the vehicles manually, but everything will be prepared to allow for unattended wireless downloading of data at a later stage.<\/p>\n\n<p>It is intended that this project will be the basis for further development of AI-based projects in the EMU. Once the vehicles have been sensorised, this data can be used for further predictive analysis. <\/p>\n\n<p>In addition to the initial proposal, some further technological innovations will be incorporated into the project:<\/p>\n\n<ul class=\"wp-block-list\">\n<li>Unsupervised anomaly detection algorithms.<\/li>\n\n\n\n<li>Joint use of Excel (Visual basic) and Python.<\/li>\n\n\n\n<li>Generation of synthetic data for the development of AI models, in the event that we do not have sufficient data for a given environment.<\/li>\n<\/ul>\n\n<p>The project is being developed by a team coordinated by Gonzalo Santamaria Freire and Javier Castrillo Mazagatos of Isdefe&#8217;s Defence and Security Technologies Division.<\/p>\n\n<p>For further information, please contact innovacion@isdefe.es<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Winner of the 2021 Isdefe&#8217;s IDEAS challenge (7th edition) Internal R&amp;D project Isdefe&#8217;s internal R&amp;D project Clustering of Connected Vehicles (CL-VCON) aims to obtain useful information about a fleet of vehicles by applying clustering techniques (unsupervised machine learning algorithms). Data from the vehicles are collected by means of sensors installed in the vehicles. The information [&hellip;]<\/p>\n","protected":false},"featured_media":3473,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"sector-proyecto":[96],"tipo-de-proyecto":[101],"class_list":["post-3472","proyectos","type-proyectos","status-publish","has-post-thumbnail","hentry","sector-proyecto-defense-and-security","tipo-de-proyecto-internal-rd-project"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>CL-VCON - Clustering Connected Vehicles - Isdefe Innova<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/isdefeinnova.es\/en\/projects\/cl-vcon-clustering-connected-vehicles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"CL-VCON - Clustering Connected Vehicles - Isdefe Innova\" \/>\n<meta property=\"og:description\" content=\"Winner of the 2021 Isdefe&#8217;s IDEAS challenge (7th edition) Internal R&amp;D project Isdefe&#8217;s internal R&amp;D project Clustering of Connected Vehicles (CL-VCON) aims to obtain useful information about a fleet of vehicles by applying clustering techniques (unsupervised machine learning algorithms). 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