| Summary: | 碩士 === 國立屏東科技大學 === 資訊管理系 === 94 === As rapid progress of ubiquitous computing, the location-based services for mobile applications are urgent required and popularly applied. However, it is difficult to achieve the high accuracy of identifying mobile user’s location due to the real interference of environmental factors, e.g., the unstable strength of radio signals and the obstacles. This thesis proposes the RSS-based (Received Signal Strength) Empirical Pattern Match (EPM) algorithm to improve the location identification accuracy of a mobile user. The proposed EPM algorithm considers the relationships between WLAN’s RSS, transmission distance, transmission direction, AP hardware stability and obstacles in a real building. Based on the iterative operations compared with the empirical location data, EPM algorithm improves the identification accuracy of traditional indoor location methods, which usually ignore the real interference factors and conducted their identification results upon a limited and open space, or a semi-closed/small area. The EPM algorithm achieves the location-aware service with high stability, error tolerance, highly accurate and efficient location identification under a high noise interference and multi-obstacle environment. Finally, the proposed EPM algorithm is implemented and operated in a real WLAN environment with high noise interference and multi-obstacle and is proved its accuracy and efficiency.
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