FloorLoc-SL: Floor Localization System with Fingerprint Self-Learning Mechanism

Abstract

Nowadays, a mobile phone plays an important role in daily life. There are many applications developed for mobile phones. Location service application is one kind of mobile application that serves location information. GPS receiver is embedded on a mobile phone for localization. However, GPS cannot provide localization service over indoor scenario efficiently. This is because obstacles and structures of building block GPS signal from the satellites. Many indoor localization systems have been proposed but most of them are developed over single-floor scenario only. The dimension of altitudes in localization results will be missed. In this paper, we propose floor localization system. The proposed system does not need any site survey and any support from back-end server. It has a self-learning algorithm for creating fingerprint in each floor. The self-learning algorithm utilizes sensors on the mobile phone for detecting trace of mobile phone user. This algorithm is low computation complexity, which can be operated on any mobile phones. Moreover, the mobile phone can exchange fingerprints with others via virtual ad hoc network instead of learning all floor fingerprints by themselves only. Our proposed floor localization system achieves 87% of accuracy.