JICCE (한국정보통신학회)
Current Result Document :
| 한글제목(Korean Title) |
Navigator Lookout Activity Classification Using Wearable Accelerometers |
| 영문제목(English Title) |
Navigator Lookout Activity Classification Using Wearable Accelerometers |
| 저자(Author) |
Ik-Hyun Youn
Jong-Hoon Youn
|
| 원문수록처(Citation) |
VOL 15 NO. 03 PP. 0182 ~ 0186 (2017. 09) |
한글내용
(Korean Abstract) |
|
영문내용
(English 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.
|
| 키워드(Keyword) |
Lookout activity classification
Machine learning
Maritime information
Wearable sensor
|
| 파일첨부 |
PDF 다운로드
|
