[{"command":"settings","settings":{"pluralDelimiter":"\u0003","suppressDeprecationErrors":true,"user":{"uid":0,"permissionsHash":"d9587e6f410d2e7f476e3da6cb10a457c78ab82347f962bf83d9020620f901dd"}},"merge":true},{"command":"add_css","data":[{"rel":"stylesheet","media":"all","href":"\/modules\/contrib\/addtocal\/addtocal.css?t2408i"},{"rel":"stylesheet","media":"all","href":"\/themes\/custom\/cest2025\/css\/components\/node.css?t2408i"}]},{"command":"add_js","selector":"body","data":[{"src":"\/core\/assets\/vendor\/jquery\/jquery.min.js?v=3.7.1"},{"src":"\/core\/assets\/vendor\/once\/once.min.js?v=1.0.1"},{"src":"\/core\/misc\/drupalSettingsLoader.js?v=10.5.1"},{"src":"\/core\/misc\/drupal.js?v=10.5.1"},{"src":"\/core\/misc\/drupal.init.js?v=10.5.1"},{"src":"\/modules\/contrib\/addtocal\/addtocal.js?v=10.5.1"},{"src":"\/modules\/contrib\/addtocal\/addtocal-download.js?v=10.5.1"}]},{"command":"openDialog","selector":"#drupal-modal","settings":null,"data":"\n\u003Carticle class=\u0022node node--type-presentation node--promoted node--view-mode-modal\u0022\u003E\n      \u003Cdiv\u003ESession 26 - Environmental data analysis and modelling\u003C\/div\u003E\n  \n      \u003Cb\u003E\u003Cspan\u003EA Spatial Platform for Predicting Health Impacts of Air Pollution\u003C\/span\u003E\n\u003C\/b\u003E\n  \n      \u003Cdiv\u003E\u003Cb\u003ECEST ID: cest2025_00317\u003C\/b\u003E\u003C\/div\u003E\n  \n        \u003Cdiv class=\u0022mb-3\u0022\u003E\n      \u003Cb\u003ERoom Aegle A | Fri 5 Sep 2025 | 16:35 - 16:45 pm\u003C\/b\u003E\n    \u003C\/div\u003E\n  \n          \n    \n  \n      \u003Cdiv class=\u0022mt-10\u0022\u003E\n            \u003Cdiv class=\u0022clearfix text-formatted field field--name-presentation-body field--type-text-long field--label-hidden field__item\u0022\u003EAir pollution is a critical global health concern, contributing to millions of premature deaths each year. Although significant progress has been made in air quality monitoring, there remains a gap in predictive tools that effectively link pollution exposure to health outcomes. To bridge this gap, we developed ODESSA, an AI-powered WebGIS platform designed to forecast hospital admissions attributable to air pollution.\nODESSA integrates diverse data sources, including air quality measurements, satellite imagery, meteorological variables, demographic information, and health records, to generate spatially explicit risk assessments. These insights aim to support proactive public health planning and response. Our approach employs advanced machine learning techniques, to uncover patterns and correlations between air pollution and hospitalizations. These models are trained on historical datasets to capture both short-term pollution spikes and long-term exposure effects.\nPreliminary results from pilot studies conducted in Lisbon, Portugal, demonstrate promising predictive accuracy, offering a valuable tool for healthcare systems to anticipate and manage patient surges. An interactive WebGIS interface is currently under development to enable policymakers, urban planners, and health authorities to visualize high-risk areas, evaluate intervention strategies, and optimize the allocation of healthcare resources.\nThis work aligns with the Sustainability and AI track by showcasing how artificial intelligence can enhance environmental health management. By combining AI and spatial analysis, ODESSA offers real-time decision support, contributing to smarter urban planning and more resilient, sustainable cities. Furthermore, its participatory and data-driven design fosters community engagement and informed decision-making.\nAcknowledgements\nThe authors would like to acknowledge the support of CESAM (UIDP\/50017\/2020 + UIDB\/50017\/2020 + LA\/P\/0094\/2020) and C2TN (UIDB\/04349\/2020). Special thanks to FCT\/MCTES for the research contract awarded to Helder Relvas (10.54499\/2021.00185.CEECIND\/CP1659\/CT0026) and ODESSA - https:\/\/doi.org\/10.54499\/2024.07293.IACDC.  \n\u003C\/div\u003E\n      \u003C\/div\u003E\n  \n  \u003Cdiv class=\u0022mt-5 mb-5\u0022\u003E\n          \u003Cspan\u003E\n          \u003Cb\u003EPresenter:\u003C\/b\u003E\n                      \u003Cp\u003E\n            Dr Helder Relvas\n            \u003C\/p\u003E\n                  \u003C\/span\u003E\n      \u003C\/div\u003E\n\n  \u003Cdiv class=\u0022mb-5\u0022\u003E\n          \u003Cdiv class=\u0022field__label\u0022\u003E\n        Authors\n      \u003C\/div\u003E\n              \u003Cp\u003E\n          Helder Relvas\n        \u003C\/p\u003E\n              \u003Cp\u003E\n          Vania Martins\n        \u003C\/p\u003E\n              \u003Cp\u003E\n          Diogo Lopes\n        \u003C\/p\u003E\n              \u003Cp\u003E\n          Pedro Cirne\n        \u003C\/p\u003E\n              \u003Cp\u003E\n          Ana Isabel  Miranda\n        \u003C\/p\u003E\n            \u003C\/div\u003E\n\n\u003C\/article\u003E\n","dialogOptions":{"width":"700","position":{"my":"right top","at":"right top"},"closeOnEscape":true,"dialogClass":"presentation-dialog","modal":true,"title":"","classes":{"ui-dialog":"presentation-dialog"}}}]