Mobiceil

Abstract

Location awareness of people inside commercial establishments can help with occupancy-based dynamic energy management and indoor navigation. In this paper, we propose MobiCeil, a novel phone-based indoor localization technique. The proposed technique is offline, automated, and uses image captured from phone's camera to identify the unique ceiling structure of any particular location in the office building. The proposed method is based on these assumptions: (a) in office, employees tend to keep their phones lying on the table, and (b) the layout of ceiling landmarks in a portion of the ceiling structure (as captured by the phone's camera on the table) is unique. We validated these assumptions by checking the phone placement of 47 employees randomly at their cubicle or meeting room, and collecting ceiling layout data from 18 meeting rooms and 6 cubicles in an IT office building. To evaluate the performance of MobiCeil, we collected images of the ceiling as seen by the phone (front and back) camera in three different rotations of the phone placed on the table, to capture a total of 960 ceiling images. Our approach achieved an accuracy of 88.2% for identifying locations, with a low computation time of 2.8s per image.