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Towards Improved Air Quality Monitoring Using Publicly Available Sky Images

Eleftherios Spyromitros-Xioufis; Anastasia Moumtzidou; Symeon Papadopoulos; Stefanos Vrochidis; Yiannis Kompatsiaris; Aristeidis K. Georgoulias; Georgia Alexandri; Konstantinos Kourtidis

Air pollution causes nearly half a million premature deaths each year in Europe. Despite air quality directives that demand compliance with air pollution value limits, many urban populations continue being exposed to air pollution levels that exceed by far the guidelines. Unfortunately, official air quality sensors are sparse, limiting the accuracy of the provided air quality information. In this chapter, we explore the possibility of extending the number of air quality measurements that are fed into existing air quality monitoring systems by exploiting techniques that estimate air quality based on sky-depicting images. We first describe a comprehensive data collection mechanism and the results of an empirical study on the availability of sky images in social image sharing platforms and on webcam sites. In addition, we present a methodology for automatically detecting and extracting the sky part of the images leveraging deep learning models for concept detection and localization. Finally, we present an air quality estimation model that operates on statistics computed from the pixel color values of the detected sky regions.

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