Location Analytics as a Service: Providing Insights for Heterogeneous Spatiotemporal Data

The increasing availability of positioning data from mobile devices facilitates new opportunities for location analytics systems, which provide insights into the movement behavior of targets across various localities. Similar to web analytics systems, positioning data can be utilized to count, for example, returning visitors in venues, calculate visit frequencies for certain time intervals, or to identify typical movement paths for different groups of visitors inside and outside buildings. However, a major challenge for location analytics is still to deal with the heterogeneity of data from various positioning systems. In this paper we present a platform that enables location analytics as a service and copes with the heterogeneous spatiotemporal data of diverse accuracy, frequency, and coverage. Furthermore, it allows to query large positioning datasets according to various data dimensions and metrics. In an additional four-month field trial the applicability of our approach was reviewed using the example of WLAN positioning data from an office environment.