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

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Implementation and Performance Evaluation of Pavilion Management Service including Availability Prediction based on SVM Model

SVM 모델 기반 가용성 예측 기능을 가진 야외마루 관리 서비스 구현 및 성능 평가

  • Rijayanti, Rita (Department of Information & Communication Engineering, Changwon National University) ;
  • Hwang, Mintae (Department of Information & Communication Engineering, Changwon National University)
  • Received : 2021.03.18
  • Accepted : 2021.04.18
  • Published : 2021.06.30
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Abstract

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

본 논문은 숲속 야외 마루의 실시간 이용 현황을 제공할 뿐만 아니라 기계학습을 통한 예측 서비스를 제공하는 야외 마루 관리 서비스의 구현 및 성능 평가 결과를 담고있다. 개발한 하드웨어 프로토타입은 모션 감지 센서를 이용해 야외 마루의 점유 여부를 감지한 후 위치 정보, 날짜 및 시간, 온도 및 습도 데이터와 함께 클라우드 기반 데이터베이스로 전달한다. 수집된 야외 마루의 실시간 이용 현황은 이용자들에게 모바일 애플리케이션을 통해 제공된다. 성능 평가 결과 하드웨어 모듈에서부터 모바일 애플리케이션까지 평균 1.9초의 응답 시간을 보여주었으며, 정확도는 99%를 보여주고 있음을 확인하였다. 아울러 수집 데이터에다 기계학습 기반의 SVM(Support Vector Model) 모델을 적용한 야외 마루의 가용성 예측 서비스를 구현하고서 이를 모바일 및 웹 애플리케이션을 통해 제공할 수 있도록 하였다.

Keywords

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