AmbiLoc — A year-long dataset for ambient indoor localization
Ambient indoor localization is a research field that studies indoor localization systems based on ambient signals of opportunity, such as those from broadcasting TV and FM radio stations or GSM networks. By using already existing high-power transmitters, such systems provide very wide coverage (in contrast to current short-range solutions). However, the need for specialized receivers and laborious data collection complicate further research in this area, despite the promising initial results.
AmbiLoc solves this problem by providing a ready-made dataset of ambient radio fingerprints. The dataset has been systematically collected in multiple testbeds, including large-scale and multi-floor buildings, over the course of one year. Using AmbiLoc, any researcher can quickly experiment with ambient indoor localization, create, evaluate and compare novel localization methods.
Dataset
AmbiLoc is a collection of ambient radio fingerprints (RSS and more), collected in multiple predefined locations across several testbeds. All the locations were systematically sampled in a time-lapse manner: 2-second long samples for each radio type, at each location, approximately twice a month, during one year.
| Testbed | Dimensions | Floors | Test points | Duration | Sessions |
| Offices |
100×50 m |
1, 0, -2 |
33+36+16 |
12 months |
23 |
| Campus |
80×80 m |
1, 0 |
13+13 |
12 months |
20 |
| Apartment |
14×7 m |
3 |
37 |
3 months |
6 |
For more technical details, please refer to documentation.
Publications
The following list includes publications based on and related to AmbiLoc.
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Andrei Popleteev. Please Stand By: TV-based Indoor Localization. Proceedings of the IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC-2017), Montreal, Canada, October 2017. (pdf)
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Andrei Popleteev. AmbiLoc: A year-long dataset of FM, TV and GSM fingerprints for ambient indoor localization. Proceedings of the 8th International Conference on Indoor Positioning and Indoor Navigation (IPIN-2017), Sapporo, Japan, September 2017. (pdf)
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Andrei Popleteev. Indoor localization using ambient FM radio RSS fingerprinting: A 9-month study. Proceedings of the 17th IEEE International Conference on Computer and Information Technology (CIT-2017), Helsinki, Finland, August 2017. (pdf, link)
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Andrei Popleteev. Indoor positioning using ambient radio signals: Data acquisition platform for a long-term study. Proceedings of the IEEE 13th Workshop on Positioning, Navigation and Communications (WPNC-2016), Bremen, Germany, October 2016. (pdf)
AmbiLoc
