A Dynamic Fuzzy Temporal Clustering for Imprecise Location Streams

摘要

The clustering has provided data analysis in many contexts of Computer Science. It is widely applied in Ambient Intelligence and Ubiquitous Computing for information processing, with geolocation data prominently. In this paper, we introduce a dynamic fuzzy temporal clustering algorithm (DFTC) to detect stays of users in urban environments based on locations from imprecise sensors. Our approach includes fuzzy evaluation of temporal and probabilistic data providing analysis in real time. As results, we have developed a mobile application which integrates the DFTC and detects satisfactorily user stays related to urban commerces from a real environment.