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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
LiDAR¿ë ¿§Áö ÄÄÇ»ÆÃÀ» È°¿ëÇÑ Áß¿ä½Ã¼³ °æ°è ½Ã½ºÅÛ |
¿µ¹®Á¦¸ñ(English Title) |
Important Facility Guard System Using Edge Computing for LiDAR |
ÀúÀÚ(Author) |
°ÁöÈÆ
Jihun Kang
Á¶Àº°æ
ÀÌÀº¼®
½Åº´¼®
Eun-Kyung Jo
Eun-Seok Lee
Byeong-Seok Shin
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¿ø¹®¼ö·Ïó(Citation) |
VOL 11 NO. 10 PP. 0345 ~ 0352 (2022. 10) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±ÙÀÇ LiDAR(Light Detection And Ranging) ¼¾¼´Â ½Ç½Ã°£À¸·Î ÁÖº¯¿¡ ÀÖ´Â ¹°Ã¼¸¦ ½ºÄµÇÏ´Â µ¥ »ç¿ëµÈ´Ù. LiDAR ¼¾¼¸¦ ÀÌ¿ëÇÏ¿© ÁÖº¯ ȯ°æÀ» ½ºÄµÇÒ °æ¿ì °¨ÁöµÇ¾ú´ø »ç¹°µé¿¡ ´ëÇÑ º¯È¸¦ °¨ÁöÇÏ°í ½Ç½Ã°£À¸·Î ¿òÁ÷ÀÌ´Â ¹°Ã¼¸¦ ÀνÄÇÒ ¼ö ÀÖ´Ù. ¼¾¼µéÀÇ Á¦ÀÛ ºñ¿ëÀÌ ³·¾ÆÁö¸é¼ LiDAR´Â Áß¿ä½Ã¼³ÀÇ °æ°è, ½º¸¶Æ®½ÃƼ, ÀÚÀ²ÁÖÇàÂ÷ µî ´Ù¾çÇÑ »ê¾÷ ºÐ¾ß¿¡¼ ´Ù¾çÇÏ°Ô È°¿ëµÇ°í ÀÖ´Ù. ÀÌ·¯ÇÑ LiDAR µ¥ÀÌÅÍ´Â ½Ç½Ã°£¿¡ »ç¹°À» ½ºÄµÇÏ´Â ¸¸Å ÀÔ·Â µ¥ÀÌÅÍÀÇ Å©±â°¡ Å©´Ù. µû¶ó¼ ÀÌ·¯ÇÑ LiDAR¸¦ È°¿ëÇÏ´Â ½Ã½ºÅÛ¿¡¼´Â ÀÌ·¯ÇÑ ´ë¿ë·® µ¥ÀÌÅÍÀÇ ½Ç½Ã°£ 󸮰¡ º´¸ñÀÌ µÉ ¼ö ÀÖ¾î¼ ÀÌ·¯ÇÑ ´ë¿ë·® 󸮿¡ ´ëÇÑ ´ë¾ÈÀÌ ÇÊ¿äÇÏ´Ù. º» ³í¹®¿¡¼´Â ¿§Áö ÄÄÇ»Æà ¼¹ö¸¦ ÀÌ¿ëÇÏ¿© ¹æ´ëÇÑ Æ÷ÀÎÆ® Ŭ¶ó¿ìµå¸¦ ¾ÐÃàÇÏ¿© ºü¸£°Ô ó¸®ÇÏ´Â ¿§Áö ÄÄÇ»Æà ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. LiDAR ¼¾¼ÀÇ ·¹ÀÌÀúÀÇ ¹Ý»ç ¹üÀ§°¡ Á¦ÇѵǾî ÀÖÀ¸¹Ç·Î ½Ç½Ã°£À¸·Î ³ÐÀº ¿µ¿ªÀ» ½ºÄµÇϱâ À§Çؼ´Â ¿©·¯ ´ëÀÇ ¶óÀÌ´Ù¸¦ »ç¿ëÇØ¾ß ÇÑ´Ù. µû¶ó¼ ½Ç½Ã°£À¸·Î ¹°Ã¼¸¦ °¨ÁöÇϰųª ÀνÄÇϱâ À§Çؼ´Â ¿©·¯ °³ÀÇ LiDAR ¼¾¼¿¡ ´ëÇÑ µ¥ÀÌÅ͸¦ ÇÑ ¹ø¿¡ ó¸®ÇØ¾ß ÇÑ´Ù. ¿¡Áö ÄÄÇ»ÅÍ´Â µ¥ÀÌÅÍ °¡¼ÓÀ» ¼öÇàÇϱâ À§ÇØ Æ÷ÀÎÆ® Ŭ¶ó¿ìµå¸¦ È¿À²ÀûÀ¸·Î ¾ÐÃàÇÏ°í ¸ðµç µ¥ÀÌÅ͸¦ ¸ÞÀΠŬ¶ó¿ìµå¿¡¼ ½Ç½Ã°£¿¡ ¾ÐÃàÇØÁ¦ÇÏ¿© »ç¿ëÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÇ¾ú´Ù. À̸¦ ÅëÇØ »ç¿ëÀÚ´Â ½Ã½ºÅÛÀ» Áß¾Ó¿¡¼ º´¸ñ ¾øÀÌ ½Ç½Ã°£¿¡ LiDAR ¼¾¼µéÀ» Á¦¾îÇÒ ¼ö ÀÖ´Ù. ½ÇÇè¿¡ »ç¿ëµÈ ½Ã½ºÅÛÀº ÀÌ·¯ÇÑ ¿§Áö ÄÄÇ»Æà ¼ºñ½º¸¦ Àû¿ëÇÔÀ¸·Î½á ±âÁ¸ Ŭ¶ó¿ìµå ±â¹Ý ¹æ½Ä¿¡¼ ¹®Á¦¿´´ø µ¥ÀÌÅÍ º´¸ñ Çö»óÀ» È¿°úÀûÀ¸·Î ÇØ°áÇÏ¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser¡¯s reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor¡¯s data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service. |
Å°¿öµå(Keyword) |
°í¼º´É Ŭ¶ó¿ìµå
ÄÁÅ×À̳Ê
GPU ÄÄÇ»ÆÃ
GPU °øÀ¯
ÀÚ¿ø °æÀï
HPC Cloud
Container
GPU Computing
GPU Sharing
Resource Race
¿§Áö ÄÄÇ»ÆÃ
LiDAR
°æ°è ½Ã½ºÅÛ
Æ÷ÀÎÆ® Ŭ¶ó¿ìµå
µ¥ÀÌÅÍ º¯È¯
Edge Computing
LiDAR
Guard System
Point Cloud
Data Transformation
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