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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ¸ñ°ÉÀÌÇü ¼¾¼­¸¦ ÀÌ¿ëÇÑ ¸Ó½Å·¯´× ±â¹Ý °¡Ãà»óÅ ¸ð´ÏÅ͸µ
¿µ¹®Á¦¸ñ(English Title) Health Monitoring of Livestock using Neck Sensor based on Machine Learning
ÀúÀÚ(Author) ÀÌ¿õ¼·   ¹Ú¼º¹Î   ¹ÝÅ¿ø   ±è¼ºÈ¯   ·ùÁ¾¿­   ¼º±æ¿µ   Woongsup Lee   Seongmin Park   Tae-Won Ban   Seong Hwan Kim   Jongyeol Ryu   Kil-Young Sung  
¿ø¹®¼ö·Ïó(Citation) VOL 22 NO. 11 PP. 1421 ~ 1427 (2018. 11)
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(Korean Abstract)
»ç¹° ÀÎÅÍ³Ý ±â¼úÀÇ ±Þ¼ÓÇÑ ¹ßÀüÀ¸·Î ´Ù¾çÇÑ Á¾·ùÀÇ ½º¸¶Æ® ¼¾¼­µéÀÌ °³¹ß º¸±ÞµÇ°í ÀÖ´Ù. ÀÌ·¯ÇÑ ½º¸¶Æ® ¼¾¼­µéÀº ÁÖ·Î °ü¸®ÀÚÀÇ °æÇè¿¡ ÀÇÇؼ­ °ü¸®µÇ´ø Ãà»ê¾÷¿¡µµ ÃÖ±Ù Àû¿ëµÇ¾î °¡Ãà °³Ã¼¿¡ ¿þ¾î·¯ºí ¼¾¼­¸¦ ´Þ°Å³ª »ç¹°ÀÎÅÍ³Ý ¼¾¼­¸¦ °®Ãá ½º¸¶Æ®ÆÊ »ç¿ëÀ» ÅëÇؼ­ °¡Ãà°ü¸®ÀÇ È¿À²¼ºÀ» Çâ»ó½ÃÅ°°í ÀÖ´Ù. º» ³í¹®¿¡¼­´Â ¸ñ°ÉÀÌÇü ½º¸¶Æ® ¼¾¼­¸¦ ÀÌ¿ëÇÏ¿© Á¥¼ÒÀÇ Ã¼¿Â°ú ¿îµ¿·®À» ÃøÁ¤ÇÏ°í À̸¦ ±â¹ÝÀ¸·Î °³Ã¼ÀÇ »óŸ¦ ÆľÇÇÏ´Â ¹æ¾ÈÀ» °³¹ßÇÏ¿´´Ù. ƯÈ÷ Á¥¼Ò °ü¸®¿¡¼­ Á¦ÀÏ Áß¿äÇÑ ¿ä¼ÒÀÎ Á¥¼ÒÀÇ ¹ßÁ¤¿©ºÎ¸¦ ÆľÇÇÏ´Â ¹æ¾ÈÀ» ´Ù¾çÇÑ ¸Ó½Å·¯´× ¹æ¹ýÀ» ÀÌ¿ëÇÏ¿© ºÐ¼®ÇÏ¿´°í À̸¦ ÅëÇؼ­ ³ôÀº Á¤È®µµ·Î ¹ßÁ¤¿©ºÎ¸¦ ¿¹ÃøÇÒ ¼ö ÀÖÀ½À» º¸¿´´Ù. Á¦¾ÈÇÑ ¹æ¾ÈÀÇ »ç¿ëÀ» ÅëÇؼ­ Á¥¼ÒÀÇ ¹ßÁ¤¿©ºÎ¸¦ ºü¸£°Ô È®ÀÎÇÏ°í À̸¦ ÅëÇؼ­ Á¥¼Ò °ü¸®ÀÇ È¿À²¼ºÀ» Çâ»ó½Ãų ¼ö ÀÖ´Ù.
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(English Abstract)
Due to the rapid development of Internet-of-Things technology, different types of smart sensors are now devised and deployed widely. These smart sensors are now used in animal husbandry which was traditionally managed by the experience of farmers, such that wearable sensors for livestock, and the smart farm which is equipped with multiple sensors are utilized to increase the efficiency of livestock management. Herein, we consider a scheme in which the body temperature and the level of activity are measured by smart sensor which is attached to the neck of dairy cattle and the health condition is monitored based on collected data. Especially, we find that the estrous of dairy cattle which is one of most important metric in milk production, can be predicted with high precision using various machine learning techniques. By utilizing the proposed prediction scheme, estrous of cattle can be detected immediately and this can improve the efficiency of cattle management.
Å°¿öµå(Keyword) Á¥¼Ò   Çコ ¸ð´ÏÅ͸µ   ±â°èÇнÀ   ¿þ¾î·¯ºí ¼¾¼­   Dairy cattle   Health monitoring   Machine learning   Wearable sensor  
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