1 Department of Computer Science, Faculty of Science, Aarhus University, Aarhus University2 Department of Computer Science, Science and Technology, Aarhus University3 Ludwig-Maximilian-University Munich4 Department of Computer Science, Science and Technology, Aarhus University
Detecting proximity and separation among mobile targets is a basic mechanism for many location-based services (LBSs) and requires continuous positioning and tracking. However, realizing both mechanisms for indoor usage is still a major challenge. Positioning methods like GPS cannot be applied there, and for distance calculations the particular building topology has to be taken into account. To address these challenges, this paper presents a novel approach for indoor proximity and separation detection, which uses location fingerprinting for indoor positioning of targets and walking distances for modeling the respective building topology. The approach applies efficient strategies to reduce the number of messages transmitted between the mobile targets and a central location server, thus saving the targets' battery power, bandwidth, and other resources. The strategies are evaluated in terms of efficiency and application-level accuracy based on numerous emulations on experimental data.
Proceedings of the First International Conference on Mobile Wireless Middleware, Operating Systems, and Applications (mobilware 2008): Acm International Conference Proceeding Series, Vol. 278, 2008, p. 1-8
Main Research Area:
International Conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications, 2008