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- W2526538213 abstract "Many emerging problems increasingly rely on integrating complex heterogeneous sensor streams, ranging from photos, texts, environmental data streams and other participating human sensors. The diversity of data types from disparate sensors poses a major challenge in data aggregation and assimilation. EventShop was originally designed for situation recognition using diverse data sources. We propose and develop new interpolation and prediction models on top of EventShop, allowing for effective ingesting and combining appropriate data streams to improve data quality and predict specific situations. We also incorporate data from participatory sensing into the system. The synergy of data gives powerful insight into better understanding of evolving situations, in which participatory sensing is integrated with the surrounding environment. Furthermore, the enhanced system is used for two real-world problems: asthma risk management and smart city." @default.
- W2526538213 created "2016-10-07" @default.
- W2526538213 creator A5032682918 @default.
- W2526538213 date "2016-10-01" @default.
- W2526538213 modified "2023-09-26" @default.
- W2526538213 title "Geospatial Multimedia Data for Situation Recognition" @default.
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- W2526538213 doi "https://doi.org/10.1145/2964284.2971472" @default.
- W2526538213 hasPublicationYear "2016" @default.
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