2014 · 25 citations · 6 references
ComputingAutonomous SystemsMeteorologyMobile ComputingMobile SystemsWeather ForecastingContext-aware ComputingMobile Human-computer InteractionMobile SensingMobile Sensor IntegrationSensor NetworksAmbient SensingContext AwarenessCrowdsensingDeploymentHuman SensingMobile CrowdsensingOn-board SensingSensing
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.
6
Prashanth Mohan, Venkata N. Padmanabhan, Ramachandran Ramjee · 2008 · 1.3K citations · Full text
Sensing meets mobile social networks
Emiliano Miluzzo, Nicholas D. Lane, Kristóf Fodor et al. · 2008 · 1K citations
Prabal Dutta, Paul M. Aoki, Neil Kumar et al. · 2009 · 382 citations
Public Health, Environmental Sciences, Environmental Social Science +17
Image browsing, processing, and clustering for participatory sensing
Sasank Reddy, Andrew Parker, Josh Hyman et al. · 2007 · 248 citations