Indoor Framework

Abstract

The tracking of spatial objects in indoor location-based services is becoming increasingly important for many applications. However, much research has focused only on querying and indexing in indoor spaces without considering the indoor variations. Therefore, this paper presents an indoor framework which includes data structures of indoor environments comprised of various building features and multiple floors. Moreover, the indoor framework includes indoor navigation and routing for both directed and undirected indoor environments, indoor density which takes into account the room capacity, and movement trajectories in single and multi-floor structures. Using synthetic data, the authors conducted extensive experiments to evaluate the proposed framework. The results show that this indoor framework can be implemented efficiently and effectively.