Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Navigator Lookout Activity Classification Using Wearable Accelerometers

  • Youn, Ik-Hyun (Department of Computer Science, College of IS&T, University of Nebraska at Omaha) ;
  • Youn, Jong-Hoon (Department of Computer Science, College of IS&T, University of Nebraska at Omaha)
  • Received : 2017.08.30
  • Accepted : 2017.09.13
  • Published : 2017.09.30
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Abstract

Maintaining a proper lookout activity routine is integral to preventing ship collision accidents caused by human errors. Various subjective measures such as interviewing, self-report diaries, and questionnaires have been widely used to monitor the lookout activity patterns of navigators. An objective measurement of a lookout activity pattern classification system is required to improve lookout performance evaluation in a real navigation setting. The purpose of this study was to develop an objective navigator lookout activity classification system using wearable accelerometers. In the training session, 90.4% accuracy was achieved in classifying five fundamental lookout activities. The developed model was then applied to predict real-lookout activity in the second session during an actual ship voyage. 86.9% agreement was attained between the directly observed activity and predicted activity. Based on these promising results, the proposed unobstructed wearable system is expected to objectively evaluate navigator lookout patterns to provide a better understanding of lookout performance.

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