Journal of Internet of Things and Convergence (사물인터넷융복합논문지)

The Korea Internet of Things Society (한국사물인터넷학회)
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Self-diagnosis Algorithm for Water Quality Sensors Based on Water Quality Monitoring Data

수질 모니터링 데이터 기반의 수질센서 자가진단 알고리즘

  • Received : 2022.11.12
  • Accepted : 2022.12.29
  • Published : 2023.02.28
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Abstract

Today, due to the increase in global population growth, the international community is discussing solving the food problem. The aquaculture industry is emerging as an alternative to solving the food problem. For the innovative growth of the aquaculture industry, smart fish farms that combine the fourth industrial technology are recently being distributed, and full-cycle digitalization is being promoted. Water quality sensors, which are important in the aquaculture industry, are electrochemical portable sensors that check water quality individually and intermittently, making it impossible to analyze and manage water quality in real time. Recently, optically-based monitoring sensors have been developed and applied, but the reliability of monitoring data cannot be guaranteed because the state information of the water quality sensor is unknown. Therefore, this paper proposes an algorithm representing self-diagnosis status such as Failure, Out of Specification, Maintenance Required, and Check Function based on monitoring data collected by water quality sensors to ensure data reliability.

오늘날, 세계 인구성장률의 증가로 국제사회는 심각하게 식량문제 해결을 논의하고 있다. 식량문제 해결을 위한 대안으로는 양식산업이 대두되고 있다. 최근 양식산업의 혁신성장을 위해 4차 산업기술을 융합한 스마트 양식장이 보급되고 있으며, 전주기적 디지털화가 추진되고 있다. 양식산업에서 중요한 수질센서는 전기화학방식의 휴대용 센서를 사용하고 있으며, 이를 이용하여 개별적, 간헐적으로 수질을 체크하고 있어서 양식장 수질을 실시간 분석하고 관리하기가 불가능하다. 최근 광학 기반의 모니터링이 가능한 수질센서들이 개발되어 현장에 적용되고 있다. 그러나 수질센서의 상태정보를 알 수 없기 때문에 모니터링 데이터의 신뢰성을 보장할 수 없는 상황이다. 따라서, 본 논문에서는 데이터의 신뢰성을 확보할 수 있도록, 수질센서가 수집하는 모니터링 데이터를 기반으로 고장, 기준일탈, 유지보수, 점검 등의 수질센서 자가진단 상태를 파악할 수 있는 알고리즘을 제안한다.

Keywords

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