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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Modified Random Forest Algorithm for Wi–Fi Indoor Localization System
verfasst von : Rafał Górak, Marcin Luckner
Erschienen in: Computational Collective Intelligence
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Abstract
The paper presents a modification of Random Forest approach to the indoor localization problem. The localization solution is based on RSS (Received Signal Strength) from multiple sources of Wi–Fi signal. We analyze two localization models. The first one is built using a straightforward application of a random forest method. The second model is a combination of localization models built for each Access Point from the building’s network using similar technique (Random Forests) as for the first model. The modification proposed in the second model gives us a substantial accuracy improvement when compared to the first model. We test also the solution against a network malfunction when some Access Points are turned off as the malfunction immunity is another important feature of the presented localization solution.