Abstract
The Wi-Fi fingerprinting (WF) technique normally suffers from the Received Signal Strength (RSS) variance problem caused by environmental changes that are inherent in both the training and localization phases. Several calibration algorithms have been proposed but they only focus on the hardware variance problem. Moreover, smartphones were not evaluated and these are now widely used in WF systems. In this paper, we analyzed various aspects of the RSS variance problem when using smartphones for WF: device type, device placement, user direction, and environmental changes over time. To overcome the RSS variance problem, we also propose a smartphone-based, indoor pedestrian-tracking system. The scheme uses the location where the maximum RSS is observed, which is preserved even though RSS varies significantly. We experimentally validate that the proposed system is tolerant to the RSS variance problem.
| Original language | English |
|---|---|
| Pages (from-to) | 406-420 |
| Number of pages | 15 |
| Journal | Pervasive and Mobile Computing |
| Volume | 9 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2013 Jun |
Bibliographical note
Funding Information:This work was supported by a National Research Foundation of Korea grant funded by the Korean government, Ministry of Education, Science and Technology (No. 2012-0005522 ).
All Science Journal Classification (ASJC) codes
- Software
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications