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Bluetooth-Tracing RSSI Sampling Method as Basic Technology of Indoor Localization for Smart Homes

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  • 발행기관
    보안공학연구지원센터(IJSH) 바로가기
  • 간행물
    International Journal of Smart Home 바로가기
  • 통권
    Vol.10 No.10 (2016.10)바로가기
  • 페이지
    pp.9-22
  • 저자
    Jun-Ho Huh, Yohan Bu, Kyungryong Seo
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A288555

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원문정보

초록

영어
In recent years, smart homes have become the center of interest for IT companies and construction companies and various types of smart homes have been made currently available on the market. Yet, these equipment are costly and it is not easy to convert existing equipment for smart home application as they may require additional resources which could also inflict much costs. The extra costs involving the remodeling of existing housing structure and installment of new equipments can be avoided by using advanced wireless technologies. As an example, this paper proposes an indoor localization system that adopts Bluetooth technology and uses RSSI values for localization. Researchers have configured a system where the central control device will recognize all other devices or equipments in the system, communicate with each other, and respond to the commands or the information provided. However, despite the efforts of many researchers, existing RSSI-based indoor localization systems do not show a satisfactory level of accuracy such that we have devised a system that traces the trend in the RSSI samples. The RSSI sampling algorithm uses Delta values obtained from the Delta sampling process to improve system accuracy and to lower the costs. The analysis results led us to believe that our algorithm has a reduced localization error rate by 12%-point compared to the algorithm that used raw sampling method.

목차

Abstract
 1. Introduction
 2. Related Research
  2.1 iBeacon
  2.2 Estimote
  2.3 Market Situation
  2.4 Comparison with Other Studies
 3. Delta Trace Sampling for RSSI-Based Distance Estimation for Smart Homes
  3.1 RSSI
  3.2 Decibel
  3.3 dBM
  3.4 RSSI Model
  3.5 RSSI-based Distance Estimation
  3.6. RSSI Sampling
 4. Delta Trace Sampling for RSSI-Based Distance Estimation for Smart Homes
 5. Performance Evaluation
  5.1 Experiments
  5.2 Analysis
 6. Conclusion
 References

키워드

Bluetooth RSSI Smart Home RSSI-based indoor localization system Python

저자

  • Jun-Ho Huh [ Senior Research Engineer of SUNCOM Co. / Dept. of Computer Engineering, Pukyong National University at Daeyeon ]
  • Yohan Bu [ Developer & Manager, Gameberry Inc. / Dept. of Computer Engineering, Pukyong National University at Daeyeon ]
  • Kyungryong Seo [ Dept. of Computer Engineering, Pukyong National University at Daeyeon ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSH) [Science & Engineering Research Support Center, Republic of Korea(IJSH)]
  • 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 Smart Home
  • 간기
    격월간
  • pISSN
    1975-4094
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

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