Topology-based indoor localization by means of WiFi fingerprinting with a computational intelligent classifier

This paper introduces a new system for people localization in indoor environments. It is mainly based on an intelligent classifier able to distinguish among a set of predefined and well identified topological locations. We adopt a WiFi signal strength fingerprint approach where most effort is done during the training phase, while online execution is fast and effective. Our proposal has been tested in a real environment with data collected in five different experimental sessions. Achieved results are encouraging since they overcome those ones provided by the well-known nearest neighbour fingerprint matching algorithm, that is usually considered as baseline for WiFi localization.