UNIST announced that a joint research paper, authored by Professor Sungil Kim and his Ph.D. student, YongKyung Oh in the Department of Industrial Engineering was highly commended for excellence at the 2021 Institute of Industrial and Systems Engineers (IISE) Annual Conference, the single most prestigious conference in the field of industrial engineering.
Their work, entitled “Logistics Anomaly Detection with Maritime Big Data: A Bootstrap Approach,” has been selected as the 2021 IISE Logistics and Supply Chain (LSC) Division Best Paper. Took place virtually from May 21 to 24, this annual conference featured over 800 sessions, including 75 paper presentations in the LSC division.
The research team has developed a real-time anomaly detection model for vessel abnormalities, using real-time tracking data on vessels, and thus demonstrated a technique to quantify the uncertainty of anomaly detection based on bootstrap techniques.
Meanwhile, their work has recently been selected as the 2021 Basic Science Research Project, supported through the National Research Foundation of Korea (NRF). They plan on conducting related research for the next three years under the theme of “Development of AI-based Prediction Method for Vessel Arrival Time, Intended for Smart Ports.”
