On Localization Using Location Fingerprints and Energy Efficient Operation of WLANs in Indoor Areas
This study focuses on the power efficient localization by fingerprinted KNN algorithm in the indoor wireless local area network (WLAN) environment. To the best of our knowledge, although the fingerprint algorithm has been utilized to supply some special location based service (LBS) with high precision and accuracy, these associated location systems have resulted in significant energy consumption. Therefore, serious attention should be paid on the energy consumption because of the hundreds to thousands of access points (APs) with high-density deployed in our university campuses and corporate offices. In response to this compelling problem, we discuss the relationship between energy costs and radio map-based location performance for the Gaussian radio signal strength (RSS) distribution with different neighboring points in KNN. Furthermore, using our results, the guidelines on the power efficient fingerprint location algorithm is also provided.