National Honam Biological Resources Center, Docking Seomnuriho with Public Data

Development of Predictive Models Utilizing Big Data

The National Honam Biodiversity Institute (hereinafter referred to as the Institute), under the Ministry of Environment, announced on the 6th that it has developed a safe docking location prediction analysis model using big data and is actively utilizing it for the operation of the Seomnurimho research vessel.

The Institute is a specialized organization researching island and coastal biological resources, and has been conducting research by operating the Seomnurimho research vessel, which was built last year, across 21 island areas to date.

The Seomnurimho, operated by the National Honam Biological Resources Center, is using data to analyze docking locations and dock safely. Provided by the National Honam Biological Resources Center

For the safe operation of the research vessel, the selection of docking and mooring points is particularly important, as navigators must predict docking locations by comprehensively considering various maritime environmental factors such as weather conditions and routes, and there is a possibility of errors in such human predictions.

Accordingly, in collaboration with the Ministry of the Interior and Safety’s Integrated Data Analysis Center, a data-driven scientific approach was taken to enhance safe navigation by developing a docking prediction model using public data such as tide observation data, exposed rock information, and marine weather buoys.

This model visualizes the risk level of the target docking area to predict possible docking locations. Since its application starting with Chuja Island in August, it has been used in actual operations at Gageodo, Heuksando, Geomundo, and other locations, enabling quick and safe docking without accidents.

An official from the Institute stated, “We will continue to do our best to enhance policy utilization through data-driven administration using public data so that researchers can work in a safe research environment,” adding, “We plan to further strengthen data-driven administrative capabilities by sharing data analysis cases with related organizations performing similar tasks.”