As “smart” devices such as smart phone and smart TVs become widely distributed, various studies on location-based services have been conducted. Such location-based services are useless, however, unless the user’s location is known. A number of researchers have examined methods to trace and determine indoor locations for indoor location-based services. In particular, WALN has been examined in various studies because of its advantage to use a frequency band available without advanced settings. This study suggests a new indoor tracing method to reduce time delays upon location fingerprinting for point data collection, which is a disadvantage of the existing Kalman filtering algorithm and fingerprinting type location tracing algorithm. This study also compares its performance with that of existing methods based on the collected data. As a result of the experiment, the fast collection algorithm is presented as a solution to the problems of existing methods. It is proven that the fast collection algorithm presented in this study is applicable to a location tracing system in an actual environment.
목차
Abstract 1. Introduction 2. Algorithm of Fast Collection for Offline Step Data 3. Algorithm of Fast Collection for Real-time Step Data 4. Performance Analysis 4.1. Development of the RSSI Collection and Transfer Software 4.2. Measurement Setup 4.3. Experimental Methods 4.4. Experimental Results 5. Conclusion References
보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Software Engineering and Its Applications
간기
월간
pISSN
1738-9984
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.8 No.1