A probabilistic convex hull query tool

Uncertain data is inherently important in a lot of real-world applications, such as environmental surveillance and mobile tracking. Probabilistic convex hull is very useful for discovering the territory of imprecise data in such applications with a high confidence. In order to deal with this, we propose and study probabilistic convex hull queries based on the possible world semantics, which are able to retrieve the objects whose probability of being on the convex hull is at least α. The demonstration is based on animal tracking whose GPS coordinate is no longer considered to be precise due to device limitation or privacy issues. We demonstrate two interesting results from studying the migration habit of one specific species and the correlation between species through probabilistic convex hull queries.