Atmos: a hybrid crowdsourcing approach to weather estimation

Niforatos, Evangelos; Vourvopoulos, Athanasios; Langheinrich, Marc; Campos, Pedro; Doria, Andre

http://hdl.handle.net/10400.13/4623

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Authors

Niforatos, Evangelos

Vourvopoulos, Athanasios

Langheinrich, Marc

Campos, Pedro

Doria, Andre

Abstract(s)

Motivated by the novel paradigm of participatory sensing in collecting in situ automated data and human input we introduce the Atmos platform. Atmos leverages a crowd-sourcing network of mobile devices for the collection of in situ weather related sensory data, provided by available on-board sensors, along with human input, to generate highly localized information about current and future weather conditions. In this paper, we share our first insights of an 8-month long deployment of Atmos mobile app on Google Play that gathered data from a total of 9 countries across 3 continents. Furthermore, we describe the underlying system infrastructure and showcase how a hybrid people-centric and environment-centric approach to weather estimation could benefit forecasting. Finally, we present our preliminary results originating from questionnaires inquiring into how people perceive the weather, how they use technology to know about the weather and how it affects their habits.

Keywords

Sensor networks Smart cities Crowd sensing Mobile sensing . Faculdade de Ciências Exatas e da Engenharia

URI

http://hdl.handle.net/10400.13/4623

Citation

Niforatos, E., Vourvopoulos, A., Langheinrich, M., Campos, P., & Doria, A. (2014, September). Atmos: a hybrid crowdsourcing approach to weather estimation. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication (pp. 135-138).