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| Content Provider | ACM Digital Library |
|---|---|
| Author | Langheinrich, Marc Niforatos, Evangelos Vourvopoulos, Athanasios |
| Abstract | Several mobile and social media weather apps support the incorporation of human input in increasing their coverage and accuracy of current weather conditions. This practice is also known as participatory sensing: the act of using sensors (i.e. smartphones) carried by volunteers to acquire highly localized measurements of physical phenomena. In order to assess the accuracy of such user contributed weather reports, we created an android app called Atmos that allows for the in situ collection of weather data in the form of descriptive manual input. Based on a yearlong study with Atmos deployed on the Google Play store, we investigate the ability of mobile users to both report current weather conditions accurately, and to predict future weather developments. We found that mobile users can be sufficiently accurate when reporting current conditions, though report accuracy was affected by hour of day. Users were also able to provide accurate short-term predictions, particularly for temperature and wind intensity. We also present results from an online survey that gathered data from 12 countries in order to understand the role weather plays in users' daily life, which helped us design Atmos. |
| Starting Page | 152 |
| Ending Page | 162 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781450336055 |
| DOI | 10.1145/2836041.2836056 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-11-30 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Crowdsourcing Experience sampling (esm) Mobile sensing Participatory sensing |
| Content Type | Text |
| Resource Type | Article |
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