Wi-Fi multi-floor indoor positioning considering architectural aspects and controlled computational complexity

作者：

Highlights：

• A novel method for the multi-floor indoor positioning problem is presented.

• Unsupervised clustering used to allow samples to group freely into the RSS space.

• Controlled computational complexity by using clusters with similar number of elements.

• High number of samples and floors provide high confidence level for the results.

摘要

•A novel method for the multi-floor indoor positioning problem is presented.•Unsupervised clustering used to allow samples to group freely into the RSS space.•Controlled computational complexity by using clusters with similar number of elements.•High number of samples and floors provide high confidence level for the results.

论文关键词：Indoor positioning,WiFi networks,Received signal strength,Fingerprint techniques,Clustering,Kohonen layer,K-medians,Backpropagation

论文评审过程：Available online 26 April 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.04.011