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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) µ¿¿µ»ó ºÐ¼®À» ÅëÇÑ ½Ç½Ã°£ Æ÷Àå ¼Õ»ó ŽÁö ¹× ¾Ë¸² ¼­ºñ½º
¿µ¹®Á¦¸ñ(English Title) Real-Time Pavement Damage Detection Based on Video Analysis and Notification Service
ÀúÀÚ(Author) ¹ÚÁÖ¿µ   ÀÌÈñ¼ø   °­°æÅ   ±èº´È¸   Juyoung Park   Heuisoon Lee   Kyungtae Kang   Byung-Hoe Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 24 NO. 02 PP. 0059 ~ 0066 (2018. 02)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â ÁÖÇà Áß °¡¼Óµµ ¼¾¼­¿Í Ä«¸Þ¶ó·ÎºÎÅÍ µ¥ÀÌÅ͸¦ ½Ç½Ã°£À¸·Î ¼öÁý, ºÐ¼®ÇÏ¿© ÀÚµ¿À¸·Î µµ·Î Æ÷ÀåÀÇ ´Ù¾çÇÑ ¼Õ»óÀ» ŽÁöÇÏ´Â ½Ã½ºÅÛÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ½Ã½ºÅÛÀº µµ·ÎÀÇ Æ÷Àå ¼Õ»óÀ» ŽÁöÇÏ´Â Áï½Ã ÇØ´ç À̹ÌÁö¿Í °¡¼Óµµ ½ÅÈ£, GPSÁÂÇ¥¸¦ µµ·Î°ü¸®ÀÚ¿¡°Ô Àü¼ÛÇϸç À̸¦ ¼­¹ö¿¡µµ Àü¼ÛÇÏ¿© µ¥ÀÌÅͺ£À̽º¿¡ ÀÌ·ÂÈ­ÇÑ´Ù. À̸¦ ÅëÇØ, µµ·Î Æ÷Àå ¼Õ»ó ŽÁö ½Ã½ºÅÛÀº µµ·Î°ü¸®ÀÚ·Î ÇÏ¿©±Ý 1) ½Å¼Ó, Á¤È®, Æí¸®ÇÏ°Ô µµ·ÎÀÇ »óŸ¦ °ü¸®ÇÒ ¼ö ÀÖ°Ô Çϸç, 2) ´Ù¾çÇÑ Á¾·ùÀÇ µµ·Î Æ÷Àå ¼Õ»óÀ» Á¶±â¿¡ ¹ß°ßÇÏ¿© °ü¸®ÇÒ ¼ö ÀÖµµ·Ï Çϸç, 3) µµ·ÎÀÇ Æ÷Àå ¼Õ»óÀ» ÃßÀû °ü¸®ÇÒ ¼ö ÀÖµµ·Ï ÇÑ´Ù. °á°úÀûÀ¸·Î, Á¦¾ÈÇÏ´Â ½Ã½ºÅÛÀº 10¹øÀÇ °í¼Óµµ·Î ÁÖÇà ½ÇÁõ Æò°¡¿¡¼­ Æò±Õ 100 km/h·Î ÁÖÇà Áß 74%ÀÇ ¹Î°¨µµ¿Í 84%ÀÇ Á¤¹Ðµµ·Î µµ·Î Æ÷ÀåÀÇ ¼Õ»óÀ» ŽÁöÇÏ¿© ±× À¯È¿¼ºÀÌ ÀÔÁõµÇ¾ú´Ù.
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(English Abstract)
In this paper, we propose a system to detect various damage automatically inflicted on road pavement by collecting and analyzing data from acceleration and camera sensors in real time. The proposed system sends the collected images, acceleration signals, and GPS coordinates to the road manager and the database in the remote server, shortly after detecting the damage to the road pavement. Our study makes three key contributions. The proposed system 1) enables road managers to maintain road conditions quickly, accurately, and conveniently; 2) allows road mangers to take care of various kinds of damage to the road pavement at the initial stage; and finally 3) even makes it possible to track the damage, which suggests that the integration of a high-level decision support function becomes affordable. We tested the sensitivity and precision of the proposed system against real-time data obtained from the vehicles driving on the highway at an average speed of 100 km/h. With ten iterations, the proposed system achieved an average sensitivity of 74% and an average precision of 84% in road pavement damage detection, which is comparable with the best competing schemes.
Å°¿öµå(Keyword) µµ·Î Æ÷Àå ¼Õ»ó ŽÁö   µ¿¿µ»ó ºÐ¼®   ¿µ»ó󸮠  ¾Ë¸² ¼­ºñ½º   ½Ç½Ã°£ µµ·Î Æ÷Àå »óÅ °ü¸®   road pavement damage detection   video analysis   image processing   notification service   real-time pavement management  
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