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Groundbreaking tools and models to reduce air pollution in urban areas

Descripción del proyecto

Una nueva herramienta de inteligencia artificial para abordar el creciente problema de la contaminación atmosférica urbana

La mayoría de la población urbana de Europa está expuesta a unos niveles de polutantes atmosféricos que exceden las nuevas directrices de la Organización Mundial de la Salud. La Agencia Europea de Medio Ambiente ha informado que las actividades antrópicas son las responsables principales de estos niveles perjudiciales. En este contexto, el proyecto MODELAIR, que cuenta con el apoyo de las Acciones Marie Skłodowska-Curie, ofrecerá formación especializada a diez estudiantes de doctorado para diseñar nuevas tecnologías disruptivas a fin de controlar la contaminación atmosférica y poner estas nuevas tecnologías al alcance de Ayuntamientos y sectores industriales relevantes. El equipo de MODELAIR desarrollará una herramienta de inteligencia artificial que permita tomar decisiones informadas y sensatas para el control de la contaminación atmosférica en zonas urbanas.

Objetivo

MODELAIR proposes a combination of theoretical, experimental, numerical, and data-driven science that will simulate, control and design new disruptive technologies for future sustainable cities and will provide specialized training to 10 doctoral candidates (DCs) to make these new technologies available to city Councils and relevant industrial sectors. MODELAIR contributes to EU Mission: Climate-neutral and smart cities, reducing gas emissions and offering cleaner air to citizens.
MODELAIR will develop an Artificial Intelligence (AI) - based tool to help make informed and sensible decisions to control air pollution in urban areas. For such aim, MODELAIR will develop novel analysis tools and new Reduced Order Models (ROMs) based on both non-intrusive sensing and innovative data sources. Assessed by the industry and city councils from Bristol, Brussels and Madrid, MODELAIR will improve the current state-of-the-art modeling capability, taking into account the influence that buildings, roadways and other structures have on the flow and dispersion of air pollution . The limits of applicability of the novel AI-based tool will be tested in three specific problems related to air pollution in urban areas by: (i) studying the influence of the urban topology on air pollution, (ii) characterizing the Ixelles District (Brussels-BE) to develop a real-time decision-making tool that will assess about the disposition and maintenance of the sensor network to provide a high-quality air pollution monitoring service, and (iii) investigating the influence of the pollutant emission source (strength and location) to optimize traffic routes to reduce air pollution. The final aim is to obtain transferable outputs using novel tools and methodology approaches (addressing three different challenges) to improve air quality dispersion models that will serve to city councils and industry to develop new regulations to control air pollution.

Coordinador

UNIVERSIDAD POLITECNICA DE MADRID
Aportación neta de la UEn
€ 503 942,40
Dirección
CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO
28040 Madrid
España

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Región
Comunidad de Madrid Comunidad de Madrid Madrid
Tipo de actividad
Higher or Secondary Education Establishments
Enlaces
Coste total
Sin datos

Participantes (5)

Socios (5)