Henken, R. (2014) Indoor-localization using a mobile phone. Master's Thesis / Essay, Artificial Intelligence.
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Abstract
In an era of mobile communication, the demand for indoor-localization is increasing. For instance, users could benefit from indoor-localization systems in complex indoor environments such as large shopping malls, museums, and location-based services (e.g. warn travelers to hurry to their gate). It is commonly known that GPS is unsuitable and inaccurate for these kinds of applications. Therefore, in this thesis the feasibility of indoor localization based on mobile phone motion and WiFi sensors is researched. Methods such as circular lateration, K-nearest neighbours, and extended Kalman filter simultaneous localization and mapping are assessed on their accuracy and applicability. The effects of building characteristics and mobile-phone features on the performance of these methods are discussed. Furthermore, it is shown that model-based methods such as K-nearest neighbours outperform memory-less methods like fingerprinting.
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Degree programme: | Artificial Intelligence |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:57 |
| Last Modified: | 15 Feb 2018 07:57 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/11711 |
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