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Self-diagnosis Algorithm for Water Quality Sensors Based on Water Quality Monitoring Data

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2023, 9(1), pp.41-47
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : November 12, 2022
  • Accepted : December 29, 2022
  • Published : February 28, 2023

HongJoong, Kim 1 Kim Jong Min 2 강태형 3 Ryu Gab Sang 2

1지아이랩
2동신대학교
3조인트리

Accredited

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.

Citation status

* References for papers published after 2022 are currently being built.