CIMLoc: A crowdsourcing indoor digital map construction system for localization

Abstract

Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, we propose CIMLoc - a crowdsourcing indoor map construction system for localization. The system is evaluated with real-world trajectories collected from different mobile devices. We quantify the construction errors by computing the localization errors achieved with the constructed map and the real map. Experimental results reveal that CIMLoc is able to construct accurate maps that significantly improve localization results. We believe that CIMLoc provides an effective solution to the indoor localization problems where the indoor maps are unavailable.