• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• The Journal of Korean Association of Computer Education
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• v.15 no.6
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• pp.75-82
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• 2012

The sensor registry system has been proposed to interpret and process semantics of sensor data independently of heterogeneous sensor networks. However, the existing sensor registry system provides the static processing method. In other words, the existing system reduces the overall performance because it executes unnecessary operations and does not consider data scope to be used. To resolve the problem of the existing sensor registry system, this paper proposes a performance enhancement model based on sensor metadata reusability and scoping. The proposed model in this paper provides a function that can decide a proper scope of sensor metadata from the sensor registry system. The proposed model improves the overall performance by providing reusability of sensor metadata. This paper also shows the advantages of the proposed model through the comparative performance evaluation.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.195-198
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• 2012

이 논문에서는 센서 레지스트리 시스템의 성능 개선을 위한 실험 평가를 기술한다. 센서 레지스트리 시스템(Sensor Registry System, SRS)은 이기종 센서 네트워크 환경에서 다양한 유형의 센서 정보(Sensor Information)를 의미 처리하기 위해 제안되었다. 기존 연구에서는 반복적인 SRS와 모바일 기기 간 통신이 전체적인 성능을 저하시키는 문제점을 지닌다. 이러한 문제점을 해결하기 위해서 데이터 범위 및 센서 메타데이터의 재사용을 고려한 모델(IM-1, IM-2, IM-3)을 제안한다. 기존 모델과 달리 메타데이터의 재사용을 한 결과가 더 좋은 성능을 보인다. 이 연구의 결과는 SRS를 이용하는 사용자에게 좀 더 빠른 서비스를 제공할 수 있는 장점을 지닌다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1235-1238
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• 2015

센서 레지스트리 시스템(Sensor Registry System, CRS)은 이기종 센서 네트워크 환경에서 센서 데이터의 일관성 있는 의미 해석을 위하여 센서 메타데이터를 등록하고 관리하는 시스템이다. 최근 사물인터넷(Internet of Things, IoT) 패러다임이 대두됨에 따라 센서 네트워크의 개념 및 이용 목적 등이 변화되고 있으며, SRS 역시 이를 반영하여 센서와 연관된 데이터 모델의 개선 및 확장이 요구된다. 따라서 이 논문은 IoT 환경에서 기존 SRS를 개선하기 위하여 Semantic Sensor Network Ontology(SSNO) 기반의 SRS 데이터 모델을 제안한다. 이를 위하여 IoT 환경에서 SRS의 목적 및 요구사항을 분석하고 SSNO의 개념들 중 필요 요소와 불필요 요소를 반영하여 제안 모델을 설계한다. 또한 생성된 SRS 데이터 모델을 이용하여 관계형 데이터베이스로 구축하고 SRS를 웹 어플리케이션으로 구현한다. 제안하는 SRS 데이터 모델은 기존 모델들에 비해 SSNO 온톨로지를 가장 적합하게 표현하므로 풍부한 의미 처리가 가능하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.12-14
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• 2021

A sensor registry system (SRS) provides semantic metadata about a sensor based on location information of a mobile device in order to solve a problem of interoperability between a sensor and a device. However, if the GPS of the mobile device is incorrectly received, the SRS receives incorrect sensor information and has a problem in that it cannot connect with the sensor. This paper proposes a dual collaboration strategy based on geographical embedding and LSTM-based path prediction to improve the probability of successful requests between mobile devices and sensors to address this problem and evaluate with the Monte Carlo approach. Through experiments, it was shown that the proposed method can compensate for location abnormalities and is an effective multicasting mechanism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.7-14
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• 2022

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.