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 fingerprintingbased 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.
CITATION STYLE
Luckner, M., & Górak, R. (2016). Comparison of floor detection approaches for suburban area. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9622, pp. 782–791). Springer Verlag. https://doi.org/10.1007/978-3-662-49390-8_76
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