Trend Research of Maritime Autonomous Surface Ships (MASS) based on Shipboard Electronics: Focusing on Text Mining and Network Analysis

• DOI: 10.20944/preprints202404.0153.v1
• Publication Date: 2024-04-03T04:11:57Z
• Authors: Jinsick Kim; Sungwon Han; Hyeyoung Lee; Byeongsoo Koo; Moonju Nam; Kukjin Jang; Jooyeoun Lee; Myoungsug Chung
• Keywords: Network Analysis

The growing adoption of electric propulsion systems in Maritime Autonomous Surface Ships (MASS) necessitates advancements shipboard electronics for safe, efficient, and reliable operation. These are crucial tasks like real-time sensor data processing, control algorithms autonomous navigation, robust decision-making capabilities. This study investigates research trends MASS using bibliographic analysis to inform policy future directions this evolving field. We analyze 3,363 MASS-related articles from the Web Science database, employing co-occurrence word latent Dirichlet allocation (LDA) topic modeling. Findings reveal a rapidly field dominated by image recognition research. Keywords "datum," "image," "detection" suggest focus on collecting analyzing marine data, particularly with deep learning synthetic aperture radar imagery. LDA confirms this, "Image classification research" as leading topic. also identifies national organizational leaders However, Arctic routes lags behind other areas. work provides valuable insights policymakers researchers, promoting deeper understanding informing agendas integration maritime industry.