Datasets:
metadata
license: mit
tags:
- wifi
- localization
pretty_name: wifine
size_categories:
- 100K<n<1M
WiFine
Paper: Finer-level Sequential WiFi-based Indoor Localization
GitHub: https://github.com/IS2AI/WiFine
Description: A finer-level sequential dataset of WiFi received signal strengths (RSS). The dataset contains 290 trajectories collected across 3 floors of C4 building of Nazarbayev University. The RSS values with corresponding position coordinates (x,y,z) are recorded around every 5 seconds.
#Buildings | #Floors | #Wireless access points (WAP) | Area (m2) |
---|---|---|---|
1 | 3 | 436 | 9,564 |
Sets | #Trajectories | #Reference points (RP) | #Samples | Total length (m) | Total duration (s) |
---|---|---|---|---|---|
Train | 120 | 18,975 | 18,975 | ≈31,814 | 112,321 |
Validation | 85 | 3,034 | 3,034 | ≈4,789 | 17,280 |
Test | 85 | 3,781 | 3,781 | ≈6,162 | 22,116 |
Total | 290 | 25,790 | 25,790 | ≈42,765 | 151,717 |
Citation:
@inproceedings{khassanov2021finer,
title={Finer-level Sequential WiFi-based Indoor Localization},
author={Khassanov, Yerbolat and Nurpeiissov, Mukhamet and Sarkytbayev, Azamat and Kuzdeuov, Askat and Varol, Huseyin Atakan},
booktitle={2021 IEEE/SICE International Symposium on System Integration (SII)},
pages={163--169},
year={2021},
organization={IEEE}
}