Floor determination for positioning in multi-story building

WiFi access points (APs) are nowadays ubiquitous in multi-level buildings to provide uninterrupted network access to mobile users. WiFi signals are the widely recognized option to provide feasible indoor positioning system (IPS). However majority of IP research concentrates on 2D positioning compared to vertical or floor level determination. To date the most reliable floor determination techniques based on WiFi signals use fingerprinting approaches. However, fingerprint (FP) method is computationally extensive due to its large database size. This paper proposed a new computationally efficient floor determination system based on reduced database. The performance of proposed algorithm is tested using real-world measurement and is compared against other few available floor determination algorithms. The experiment shows that the proposed method outperforms other floor positioning methods by utilizing only 14% of original FP database size.