Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Improved Sensor Filtering Method for Sensor Registry System

센서 레지스트리 시스템을 위한 개선된 센서 필터링 기법

  • Chen, Haotian (Department of Software Convergence Engineering, Kunsan National University) ;
  • Jung, Hyunjun (Department of Software Convergence Engineering, Kunsan National University) ;
  • Lee, Sukhoon (Department of Software Convergence Engineering, Kunsan National University) ;
  • On, Byung-Won (Department of Software Convergence Engineering, Kunsan National University) ;
  • Jeong, Dongwon (Department of Software Convergence Engineering, Kunsan National University)
  • Received : 2021.11.18
  • Accepted : 2021.11.30
  • Published : 2022.01.31
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Abstract

Sensor Registry System (SRS) has been devised for maintaining semantic interoperability of data on heterogeneous sensor networks. SRS measures the connectability of the mobile device to ambient sensors based on positions and only provides metadata of sensors that may be successfully connected. The step of identifying the ambient sensors which can be successfully connected is called sensor filtering. Improving the performance of sensor filtering is one of the core issues of SRS research. In reality, GPS sometimes shows the wrong position and thus leads to failed sensor filtering. Therefore, this paper proposes a new sensor filtering strategy using geographical embedding and neural network-based path prediction. This paper also evaluates the service provision rate with the Monte Carlo approach. The empirical study shows that the proposed method can compensate for position abnormalities and is an effective model for sensor filtering in SRS.

센서 레지스트리 시스템(Sensor Registry System, SRS)은 이기종 센서 네트워크에서 의미적 상호운용성 유지를 위해 개발되었다. SRS는 위치 정보를 기반으로 주변 센서와 모바일 기기와의 연결 여부를 확인하며, 연결이 되었을 때 센서의 메타데이터를 제공한다. 성공적으로 연결되는 주위의 센서를 식별하는 과정을 센서 필터링이라고 정의한다. 이러한 센서 필터링의 성능 개선이 SRS 연구의 핵심 주제 중 하나이다. 실제 상황에서, GPS에서 제공된 잘못된 위치 정보로 인해 센서 필터링이 실패하는 경우가 발생한다. 따라서 이 논문에서는 지리적 임베딩과 뉴럴 네트워크 기반 경로 예측을 이용한 새로운 센서 필터링 방법을 제안하고 몬테카를로 접근방법을 통해 서비스 제공률을 평가한다. 실증 연구에서, 제안 방법이 위치 정보 이상 문제를 개선하고 SRS 센서 필터링에 효과적인 모델임을 보였다.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF); grant funded by the Korean government (MSIP) (No. 2019R1I1A3A01060826).

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