CGSIL: Collaborative Geo-clustering Search-Based Indoor Localization
Many works have been proposed to use Wi-Fi signals to locate the position of the mobile devices. However, most of these approaches require a costly training step to build a Wi-Fi's map for each location. ISIL has been proposed as the first Wi-Fi-based technique that is training-free, in which the localization can be done instantly at any location without the need of training. However, due to its simplicity, ISIL does not provide adequate accuracy. In this paper, we proposed CGSIL, another training-free localization that is two times more accurate than ISIL by utilizing collaborative filtering and geographic clustering on the location information.