AIを用いた建物の損傷度判定モデルと車載カメラの動画による被災率の評価

DOI Web Site 参考文献5件
  • 大笹 航汰
    室蘭工業大学大学院工学研究科環境創生工学系専攻
  • 加藤 圭祐
    室蘭工業大学大学院工学研究科環境創生工学系専攻
  • 高瀬 裕也
    室蘭工業大学大学院工学研究科もの創造系領域
  • 中嶋 唯貴
    北海道大学大学院工学研究院

書誌事項

タイトル別名
  • BUILDING DAMAGE ASSESSMENT MODEL USING AI AND DAMAGE RATE EVALUATION BY VIDEO FROM VEHICLE MOUNTED CAMERA

抄録

<p>In Japan, large earthquakes often occur. For rehabilitation efforts, a damage assessment of buildings is important. Currently, the damage assessment is done by investigators; however, it takes a lot of time. In this study, the authors tried to propose the assessment using AI and IoT for more effective and faster assessment. First, the deep learning model was constructed using the images of damaged buildings from previous earthquakes. Next, the accuracy of the model was verified using the video shot in Futaba, Fukushima. As a result, the large and small scale damage could be reasonably estimated.</p>

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