RSSI Fingerprinting Based iPhone Indoor Localization System Without Apple API

Abstract

The flourish of mobile communications is driven by the increasing number of subscribers and rapid advance of electronic devices. This brings up many multimedia context-aware services, among which real time locating system (RTLS) has become necessary in many applications. To locate a mobile station (MS), RTLS could apply conventional fingerprinting algorithm using received signal strength indicator (RSSI), which allows a MS to collect RSSI data from beacons sent by access points (APs). However, this method does not work for iPhones because of the lack of open access to Apple application programming interface (API) to obtain RSSI values. This paper proposes an alternative approach, under which APs in the monitoring mode are used to collect RSSI values for semi-beacon packets sent from a MS. We implement the packet capture library, which enables us to obtain RSSI values of semi-beacon packets sent by an iPhone. With a region-based k-nearest neighbor (kNN) localization algorithm, we successfully locate an iPhone user in indoor environment. In addition, experimental results show that the proposed approach outperforms the conventional RSSI fingerprinting approach.