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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) ºñÄÜÀ» È°¿ëÇÏ¿© ½Ç³»À§Ä¡ ã´Â »çÀü ÄÆ-¿ÀÇÁ ¹æ½Ä
¿µ¹®Á¦¸ñ(English Title) A Preliminary Cut-off Indoor Positioning Scheme Using Beacons
ÀúÀÚ(Author) ±èµ¿ÁØ   ¹Úº´°ü   ¼ÕÁÖ¿µ   Dongjun Kim   Byoungkwan Park   Jooyoung Son  
¿ø¹®¼ö·Ïó(Citation) VOL 23 NO. 02 PP. 0110 ~ 0115 (2017. 02)
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(Korean Abstract)
½Ç³»À§Ä¡¸¦ ã´Â ¹æ¹ýÀ¸·Î °¢ ºñÄÜÀ¸·ÎºÎÅÍ ¼ö½ÅµÈ ¿©·¯ ½ÅÈ£µéÀÇ ÃÖ´ë°ªÀÇ »ó´ëÀûÀÎ ¼øÀ§¿¡ µû¶ó ºñ±³´ë»ó ºñÄÜ°ú ÂüÁ¶À§Ä¡¸¦ µ¿½Ã¿¡ ÀÏÂ÷ÀûÀ¸·Î ¼Ô¾Æ³½ ÈÄ »ì¾Æ³²Àº ºñÄÜ°ú ÂüÁ¶À§Ä¡ ¸¸À¸·Î ±âÁ¸ÀÇ ÇΰÅÇÁ¸°Æ® ¹æ½ÄÀ» Àû¿ëÇÏ´Â Cut-off ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. ÀÌ ¹æ½ÄÀº µÎ ´Ü°è·Î ÀÌ·ç¾îÁ® ÀÖ´Ù. ¿ÀÇÁ¶óÀδܰ迡¼­´Â ºñÄÜÀ» ½Ç³» ¿©·¯ ÂüÁ¶À§Ä¡¿¡ ¼³Ä¡ÇÏ°í ±×·ÎºÎÅÍ ¹ß»ýµÇ´Â ½ÅÈ£¼¼±â¿Í UUID¸¦ ¹Ì¸® ÆľÇÇÏ¿© ÇΰÅÇÁ¸°Æ® Áöµµ¸¦ ¸¸µç´Ù. ¿Â¶óÀÎ ´Ü°è¿¡¼­´Â ¿ì¼± »ç¿ëÀÚÀÇ À̵¿ÀåÄ¡¿¡¼­ ¼ö½ÅµÈ ºñÄܵéÀÇ ½ÅÈ£¼¼±â µ¥ÀÌÅÍ¿¡ ÀÇ°ÅÇÏ¿© ¾Õ¼­ ¸¸µç Áöµµ¸¦ ÁÙÀδÙ. ÁÙ¾îµç Áöµµ¸¦ È°¿ëÇÏ¿© °¡Àå À¯·ÂÇÑ K°³ÀÇ ÂüÁ¶À§Ä¡¸¦ ÆľÇÇÏ°í ±× À§Ä¡¸¦ ÀÌ¿ëÇÏ¿© »ç¿ëÀÚÀÇ À§Ä¡¸¦ ÃßÁ¤ÇÑ´Ù. ƯÀÌÇÑ Á¡Àº, ÇΰÅÇÁ¸°Æ® Áöµµ¿¡ ±â·ÏÇϰųª À§Ä¡¸¦ ÃßÁ¤ÇÏ´Â °úÁ¤¿¡¼­ °í·ÁµÇ´Â »çÇ×Àº °¢ ºñÄÜÀ¸·ÎºÎÅÍ ¼ö½ÅµÈ ½ÅÈ£µéÀÇ ÃÖ´ë°ªµéÀÇ »ó´ëÀûÀÎ ¼øÀ§¶ó´Â Á¡ÀÌ´Ù. ¼ö½Ã·Î º¯È­ÇÏ´Â ½ÅÈ£¼¼±â ÀÚüÀÇ ºÒ¾ÈÁ¤¼ºÀ» ÃÖ¼ÒÈ­ÇÏ´Â È¿°ú¸¦ ³»±â ¶§¹®¿¡ ÃßÁ¤À§Ä¡ÀÇ Á¤È®¼ºÀÌ ±âÁ¸ ¹æ½Ä°ú Â÷º°È­ µÇ¾ú´Ù.
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(English Abstract)
We propose a new indoor positioning algorithm named Cut-off algorithm. This algorithm cuts off candidates of beacons and reference points in advance, before looking for K neighbor reference points which are guessed to be closest to the user¡¯s actual location. The algorithm consists of two phases: off-line phase, and on-line phase. In the off-line phase, RSSI and UUID data from beacons are gathered at reference points placed in the indoor environment, and construct a fingerprint map of the data. In the on-line phase, the map is reduced to a smaller one according to the RSSI data of beacons received from the user¡¯s device. The nearest K reference points are selected using the reduced map, which are used for estimating user¡¯s location. In both phases, relative ranks of the peak signals received from each beacon are used, which smoothen the fluctuations of the signals. The algorithm is shown to be more efficient in terms of accuracy and estimating time.
Å°¿öµå(Keyword) ½Ç³»À§Ä¡ ã±â   ÇΰÅÇÁ¸°Æ® Áöµµ   ºñÄÜ   ÂüÁ¶À§Ä¡   ÄÆ-¿ÀÇÁ   K-Nearest-Neighbor   indoor positioning   fingerprint   beacon   reference point   cut-off   K-Nearest-Neighbor  
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