Design and development of an Artificial Intelligence-based decision support system for predicting air quality and determining the health risks of particulate matter

Air pollution and atmospheric particles are major public health issues. The health impact of these particles is well-established, but uncertainties remain regarding the role of their physicochemical characteristics. In this context, the IARISQ project aims to study, design, and develop a decision support system based on Artificial Intelligence (AI) to predict air quality, with a focus on two complementary aspects: (1) evaluating the population's exposure to air pollution in the daily monitoring of air quality, and (2) assessing the health risks posed by atmospheric particles, taking into account their complex physicochemical characteristics. One of the project's main innovations lies in its holistic approach to atmospheric particles by considering their physicochemical properties. By assessing the health risks associated with these particles and monitoring the population's daily exposure to pollution, the project will provide a relevant decision support tool. It will address a significant gap by exploring alternative methodologies for evaluating the health impacts of particles. Furthermore, by supplementing information related to air quality and its health effects through AI, the project will facilitate the integration of environmental health considerations into both individual and collective decision-making. Thus, the project offers significant added value to the understanding and management of public health issues related to air pollution.