{"id":16159,"date":"2025-09-01T10:39:16","date_gmt":"2025-09-01T10:39:16","guid":{"rendered":"https:\/\/www.itaca.upv.es\/ictvscc\/new-traffic-alert-system-based-on-artificial-intelligence-to-anticipate-high-pollution-episodes-in-valencia\/"},"modified":"2025-09-01T10:39:16","modified_gmt":"2025-09-01T10:39:16","slug":"new-traffic-alert-system-based-on-artificial-intelligence-to-anticipate-high-pollution-episodes-in-valencia","status":"publish","type":"post","link":"https:\/\/www.itaca.upv.es\/ictvscc\/new-traffic-alert-system-based-on-artificial-intelligence-to-anticipate-high-pollution-episodes-in-valencia\/","title":{"rendered":"New traffic alert system based on artificial intelligence to anticipate high pollution episodes in Valencia"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">A team from the <a href=\"https:\/\/www.itaca.upv.es\/\" target=\"_blank\" rel=\"noreferrer noopener\">Institute of Information and Communication Technologies (ITACA) at the Polytechnic University of Valencia <\/a>(UPV) and the Institute of Corpuscular Physics (IFIC), a joint centre of the Spanish National Research Council (CSIC) and the University of Valencia (UV), <strong>has developed an innovative urban traffic prediction and early warning system based on deep learning techniques.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The new method, which enables the anticipation of hig<strong>h-pollution episodes and thus facilitates the adoption of preventive measures, <\/strong>\u201cis ready to be exported and help improve air quality in urban environments around the world,\u201d the researchers emphasize.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this project, the team from the ITACA institute and IFIC started from the premise that<strong> reducing transport emissions not only helps mitigate climate change but also directly improves air quality in cities<\/strong>. In Valencia, for example, traffic represents around 60% of total greenhouse gas (GHG) emissions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To address this situation, the researchers applied a system in this city that predicts, 30 minutes in advance, whether a street segment will experience heavy traffic, thus facilitating preventive measures to reduce pollution and protect public health.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cUrban traffic is an important source of harmful air pollutants. We must not forget that air pollution is the leading environmental cause of premature deaths,\u201d <strong>says Edgar Lorenzo-S\u00e1ez, researcher at the ITACA Institute and one of the study\u2019s authors. <\/strong>Poor air quality has also been linked to diseases such as asthma, lung cancer, and cardiovascular problems, \u201cresponsible for around 300,000 premature deaths per year in the European Union,\u201d he adds.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A precise, reliable, and scalable system<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The system developed by the UPV and IFIC team h<strong>as been trained on data from 1,472 traffic sensors distributed across the city of Valencia, complemented by meteorological variables<\/strong> (wind, rain, atmospheric pressure, etc.). The new method classifies each road segment into three alert levels and, thanks to Long Short-Term Memory (LSTM) neural networks, achieves high real-time accuracy, even during rush hour.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The model has also demonstrated that traffic data can serve as a reliable indicator of NOx (nitrogen oxides) levels, one of the most harmful pollutants to health. This is particularly useful in areas without a dense network of air quality sensors. This capability could strengthen the effectiveness of Low Emission Zones (LEZs), with more localized measures tailored to each street&#8217;s actual risk, avoiding generalized restrictions with greater social impact.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cOur <strong>system is right 90% of the time when traffic is smooth and 70% when predicting heavy traffic episodes<\/strong>. This opens the door to quicker decisions that prevent exceeding legal pollution limits in sensitive areas,\u201d adds Edgar Lorenzo-S\u00e1ez.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For his part, <strong>Javier Urchuegu\u00eda, also an ITACA researcher, highlights: \u201cWe have found a direct correlation between traffic flows and recorded NOx levels<\/strong>, which allows us to generate alerts even without a complete air quality sensor network. This is a key finding for many European cities with limited resources.\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Likewise,<strong> Ver\u00f3nica Sanz<\/strong>, professor at the UV, IFIC researcher, and coauthor of the study, explains that the system\u2019s intelligence has been developed using AI models capable of learning how the city \u201cbreathes\u201d and anticipating changes in traffic and pollution. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cThe models have been designed to be robust and adaptable to different scenarios, opening the door to their application in many other cities,\u201d she notes. <strong>\u201cArtificial intelligence can be a great ally to help cities breathe better<\/strong>. This system, developed in Valencia, is ready to be exported and help improve air quality in urban environments around the world,\u201d she stresses.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>A step toward more sustainable and resilient cities<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This work represents significant progress in data-driven urban management by integrating artificial intelligence to address complex environmental challenges. According to its authors, the system could become an essential tool for designing more dynamic, effective, and socially acceptable interventions, particularly aimed at protecting vulnerable groups such as schoolchildren, the elderly, and patients with respiratory diseases.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Future development lines include creating a digital twin of the city of Valencia to simulate measures before real implementation and incorporating additional Internet of Things (IoT) sensors to improve the direct prediction of pollutants.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The study was published in the scientific journal <em>Neural Computing and Applications<\/em> and supported by institutions such as the Generalitat Valenciana and the Ministry of Science and Innovation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Reference: Miguel G. Folgado, Ver\u00f3nica Sanz, Johannes Hirn, Edgar Lorenzo-S\u00e1ez, Javier Urchuegu\u00eda. <em>Methodology development for high-resolution monitoring of emissions in urban road traffic systems, Atmospheric.<\/em> Neural Computing and Applications. <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s00521-025-11316-0?utm_source=chatgpt.com\">https:\/\/link.springer.com\/article\/10.1007\/s00521-025-11316-0<\/a><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n&nbsp;\n<br><br>\n<hr>\n\n\n\n<p class=\"wp-block-paragraph\"><em><sub><code>Noticia elaborada por ITACA FORWARD, financiada por Ivace+i Innovaci\u00f3n y la Uni\u00f3n Europea a trav\u00e9s del Programa Fondo Europeo de Desarrollo Regional (FEDER) Comunitat Valenciana 2021-2027 (Referencia del proyecto: INNVA2\/2025\/17)<\/code><\/sub><\/em><\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-style-plain is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><\/p>\n<\/blockquote>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.itaca.upv.es\/wp-content\/uploads\/2025\/11\/Logo-FEDER-2025-ES-1024x66.png\" alt=\"\" class=\"wp-image-15814\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>The alert system developed by ITACA-UPV and CSIC provides 30 minutes\u2019 notice if a street segment is expected to experience heavy traffic.<\/p>\n","protected":false},"author":0,"featured_media":16160,"comment_status":"","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[58],"tags":[],"class_list":["post-16159","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-ictvscc"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - 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