| Project/Area Number |
18K13951
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 25010:Social systems engineering-related
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| Research Institution | Tohto University (2021)
Tokyo Denki University (2018-2020) |
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Principal Investigator |
DOINE Renon 東都大学, 幕張ヒューマンケア学部, 助教 (20784424)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 疲労 / 機械学習 / 視覚 / 視覚による疲労 / 重回帰分析 / エネルギー消費量 / 操船者 / 肉体的疲労 / スマートデバイス / IoT / AI |
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| Outline of Final Research Achievements |
Human errors account for 74% of marine accidents. Fatigue of ship operators is the primary reason of the accidents. The purpose of this study is to develop the remote alarm system of human physical fatigue for ship operators using artificial intelligence. The remote alarm system consists some smart watch, some smart phone and a network server. Physical fatigue was evaluated by the energy expenditure. We investigated the effective indicators for artificial intelligence that predict physical fatigue of ship operators. From this study, it was clarified that waist motion and the motion of center of gravity caused by visual information were the effective indicators.
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| Academic Significance and Societal Importance of the Research Achievements |
日本は海上貿易が盛んである一方，船舶事故の防止が課題となっている．操船者の腰部の動揺や重心動揺により，操船者の肉体的疲労度を早期に予測し，スマートデバイスへのアラーム発信が可能となれば，操船を妨げることなく，船舶事故を未然に防ぐことが可能となる．また本技術と，既に他の研究グループにおいて開発されているスマートデバイスを用いた精神的疲労の計測システムを組み合わせることで，教育機関における学生の疲労度やストレス状態のモニタリングなどへの応用が期待される．
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