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Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
| Publication date | 5/01/2023 |
|---|---|
| Host publication | 2022 32nd International Telecommunication Networks and Applications Conference (ITNAC) |
| Publisher | IEEE |
| Pages | 280-286 |
| Number of pages | 7 |
| ISBN (electronic) | 9781665471039 |
| ISBN (print) | 9781665471046 |
| <mark>Original language</mark> | English |
| Event | 32nd International Telecommunication Networks and Applications Conference - Wellingotn, New Zealand Duration: 30/11/2022 → 2/12/2022 |
| Conference | 32nd International Telecommunication Networks and Applications Conference |
|---|---|
| Country/Territory | New Zealand |
| City | Wellingotn |
| Period | 30/11/22 → 2/12/22 |
| Conference | 32nd International Telecommunication Networks and Applications Conference |
|---|---|
| Country/Territory | New Zealand |
| City | Wellingotn |
| Period | 30/11/22 → 2/12/22 |
Wi-Fi fingerprinting techniques are commonly used in Indoor Positioning Systems (IPS) as Wi-Fi signal is available in most indoor settings. In such systems, the position is estimated based on a matching algorithm between the enquiry points and the recorded fingerprint data. In this paper, our objective is to investigate and provide quantitative insight into the performance of various Nearest Neighbour (NN) algorithms. The NN algorithms such as KNN are also often employed in IPS. We extensively study the performance of several NN algorithms on a publicly available dataset, UJIIndoorLoc. Furthermore, we propose an improved version of the Weighted KNN algorithm. The proposed model outperforms the existing works on the UJIIndoorLoc dataset and achieves better results for the success rate and the mean positioning error.