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政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 > Item 140.119/143299

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/143299

Title:	Applying Artificial Intelligence (AI) to improve fire response activities
Authors:	彭彥璁 Peng, Yan-Tsung Chang, Ray Hsienho;Choi, Seongchul;Cai, Changjie
Contributors:	資科系
Keywords:	Artificial Intelligence;Fire response activities;Firefighters;Fire apparatus;On-site Supervision;Deep learning
Date:	2022-07
Issue Date:	2023-02-06 14:30:27 (UTC+8)
Abstract:	This research discusses how to use a real-time Artificial Intelligence (AI) object detection model to improve on-site incident command and personal accountability in fire response. We utilized images of firegrounds obtained from an online resource and a local fire department to train the AI object detector, YOLOv4. Consequently, the real-time AI object detector can reach more than ninety percent accuracy when counting the number of fire trucks and firefighters on the ground utilizing images from local fire departments. Our initial results indicate AI provides an innovative method to maintain fireground personnel accountability at the scenes of fires. By connecting cameras to additional emergency management equipment (e.g., cameras in fire trucks and ambulances or drones), this research highlights how this technology can be broadly applied to various scenarios of disaster response, thus improving on-site incident fire command and enhancing personnel accountability on the fireground.
Relation:	Emergency Management Science and Technology, Vol.2, Article number: 7
Data Type:	article
DOI 連結:	https://doi.org/10.48130/EMST-2022-0007
DOI:	10.48130/EMST-2022-0007
Appears in Collections:	[資訊科學系] 期刊論文

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