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ThinkMind // ACCSE 2019, The Fourth International Conference on Advances in Computation, Communications and Services // View article accse_2019_1_10_90014


AirMap: A Reactive Map of Air Quality

Authors:
Dessislava Petrova-Antonova
Andrey Popradanov

Keywords: document database; time series data; spatial-temporal; data visualization; MERN stack

Abstract:
Today, air pollution is one of the biggest environment risks to health that continues to rise and affects both people’s quality of life and economies. It is identified as a global health priority by the World Health Organization, since it reflects to all parts of society around the world. A huge amount of air quality data is collected by different means, but it is not easily accessible for the citizens, who have a sensible role to mitigate the problem. In this paper, a visualization tool of multi-scaling, spatial-temporal air quality data, called AirMap, is proposed. An adaptive development method, based on modern MERN (MongoDB, Express, React, Node.js) application stack, is applied to integrate line charts with map-based localizations, trends and time views. The interactive visualization helps citizens to interpret air quality data that is published a long after health thresholds are reached in technical formats. The feasibility of AirMap is proved using a large multi-dimensional data set including measurement for 7 air pollutants and 4 weather parameters.

Pages: 1 to 7

Copyright: Copyright (c) IARIA, 2019

Publication date: July 28, 2019

Published in: conference

ISSN: 2519-8459

ISBN: ISBN: 978-1-61208-735-1

Location: Nice, France

Dates: from July 28, 2019 to August 2, 2019

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