Abstract
As a part of smart-buildings, indoor localisation systems – alternative to Global Positioning System localisation – bring constantly improving results. Several localisation methods works with a horizontal localisation error less than few meters. However, for small suburban houses, horizontal localisation is not as important as detection of the current floor, which in is still a challenge in multi-storey buildings. This paper compares several approaches that can be used in fingerprinting-based floor detection systems. The tests include the following fingerprints: pressure measures, Wi-Fi signals, and two generations of cellular networks signals. The tests have been done in the suburban 3-storey building with underdeveloped Wi-Fi and cellular infrastructure. Notwithstanding, the floor detection based on Received Signal Strength from both infrastructures reached from 98 to 100 %. Additionally, we showed that differences in the number of measures and differences in the number of received signals were not a major factor that influenced on accuracy.
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Acknowledgment
The research is supported by the National Centre for Research and Development, grant No. PBS2/B3/24/2014, application No. 208921.
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Luckner, M., Górak, R. (2016). Comparison of Floor Detection Approaches for Suburban Area. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_76
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