My colleague Andrea Tapia and her team at PennState University have developed an interesting iPhone application designed to support humanitarian response. This application is part of their EMERSE project: Enhanced Messaging for the Emergency Response Sector. The other components of EMERSE include a Twitter crawler, automatic classification and machine learning.
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The iPhone application developed by PennState is designed to help humanitarian professionals collect information during a crisis. “In case of no service or Internet access, the application rolls over to local storage until access is available. However, the GPS still works via satellite and is able to geo-locate data being recorded.” The Twitter crawler component captures tweets referring to specific keywords “within a seven-day period as well as tweets that have been posted by specific users. Each API call returns at most 1000 tweets and auxiliary metadata […].” The machine translation component uses Google Language API.