A digital library for water main break identification and visualization
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This paper describes a prototype of a digital library for water main break identification and visualization. Many utilities rely on an emergency call to detect water main breaks, because breaks are difficult to predict. Collecting the information by call requires time consuming human efforts. Furthermore, it is not archived and not shared with others. Collecting and archiving the information by tweets, news, and web resources helps users to identify relevant water main breaks efficiently. In developing this prototype, we extracted location information from text instead of using GPS data. We also describe the importance of tweet visualization by location, and how we visualize tweets on a map.
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