Conference Paper

Towards Air Quality Estimation Using Collected Multimodal Environmental Data

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Abstract

This paper presents an open platform, which collects multimodal environmental data related to air quality from several sources including official open sources, social media and citizens. Collecting and fusing different sources of air quality data into a unified air quality indicator is a highly challenging problem, leveraging recent advances in image analysis, open hardware, machine learning and data fusion. The collection of data from multiple sources aims at having complementary information, which is expected to result in increased geographical coverage and temporal granularity of air quality data. This diversity of sources constitutes also the main novelty of the platform presented compared with the existing applications.

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... Low-cost and relatively good result correlations with reference air pollution stations (Karagulian et al., 2019) allows users to set up citizen science initiatives and involve local communities into global problem solving. The most relevant of these projects are listed in Table 1, which is an extension of the review carried out by Moumtzidou et al. (2016). The relatively simple design of citizen science sensors makes them suitable for do-it-yourself (DiY) workshops. ...
Preprint
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