First name: 
Please select your type of occupation: 
How are you performing research on Citizen Science, taking part in Citizen Science activities and/or supporting Citizen Science?: 
I believe Crowdsourcing, and from a broader perspective, Participatory Sensing holds a significant potential in turning everyone into a Citizen Scientist. As part of a research project, I have designed and developed an Android app called Atmos, that apart from automatic sensor input aggregation, also collects human observations about current and future weather conditions at a given place. Atmos then analyses those inputs and produces highly localised weather forecasts available to everyone through the app or the web. I strongly believe Atmos showcases an ideal example of how technology can enable citizens, who simply based on direct observation and prior experience, can be turned into amateur meteorologists for solving the complex task of local weather estimation. Currently, I have received a GEOSS EU grant for developing the iOS counterpart app of Atmos which I will present in the 1st ECSA Conference in Berlin.
Name of Citizen Science Project: 
Atmos: a hybrid crowdsourcing approach to weather estimation
Project URL:
Organization running the project: 
Brief description of project: 
Atmos ecosystem will offer a particular advantage for weather forecasting in places with microclimates, where current weather models prove insufficient. Currently, we are employing machine-learning algorithms for efficiently combining both human input and sensor data and generating our own hybrid weather models. Our approach utilizes the power of crowds, individually (mobile devices) and collectively (public displays), combining both explicit (human input) and implicit (automated sensor readings) sampling to significantly improve the accuracy of weather forecasting in areas with challenging climatic conditions.