A semantic-based indexing for indoor moving objects

Abstract

The increasing availability of indoor positioning, driven by techniques like RFID, Bluetooth, and smart phones, enables a variety of indoor location-based services (LBSs). Efficient queries based on semantic-constraint in indoor spaces play an important role in supporting and boosting LBSs. However, the existing indoor index techniques cannot support these semantic constraints-based queries. To solve this problem, this paper addresses the challenge of indexing moving objects in indoor spaces, in which both the moving objects and the indoor environments include semantic meanings. We present an indoor semantic-based model, which gives the formal description of semantics of indoor cells and moving objects. Then, a new semantic-based index is proposed for indoor environment, which can support queries under semantic constraint. In addition, we develop efficient algorithms for two new queries, which are the nearest neighbor query based on semantic constraints for static indoor cells and moving objects, respectively. The conducted experiment demonstrates that the proposed index structure is effective, robust, and efficient. © 2014 Tingting Ben et al.