°ÇÃ൵½Ã°ø°£¿¬±¸¼Ò

Architecture & Urban Research Institute

pdf¿ø¹®º¸±â ¿¡·¯ ÇØ°á¹æ¹ý ¹Ù·Î°¡±â



¹®ÇåȨ > ¿¬±¸³í¹® > »ó¼¼

[¿ø¹®º¸±â½Ã ¼ÒºñµÇ´Â Æ÷ÀÎÆ® : 100 Æ÷ÀÎÆ®] ¹Ì¸®º¸±â Àοë

´ëÇÑ°ÇÃàÇÐȸ|ARCHITECTURAL RESEARCH(³í¹®Áý) 2018³â 12¿ù

³í¹®¸í Crowdsourced Urban Sensing: Urban Travel Behavior Using Mobile Based Sensing
ÀúÀÚ¸í ½Åµ¿À±(Dongyoun Shin)
¹ßÇà»ç ARCHITECTURAL INSTITUTE OF KOREA(´ëÇÑ°ÇÃàÇÐȸ)
¼ö·Ï»çÇ× ARCHITECTURAL RESEARCH(´ëÇÑ°ÇÃàÇÐȸ ³í¹®Áý), Vol.20 No.4 (2018-12)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(109) ÃÑÆäÀÌÁö(12)
ISSN 12296163
ÁÖÁ¦ºÐ·ù µµ½Ã
ÁÖÁ¦¾î ; Crowdsourcing ; Urban Sensing ; Urban Big Data ; Mobile Sensing ; Travel Behavior
¿ä¾à2 In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.
¼ÒÀåó ´ëÇÑ°ÇÃàÇÐȸ
¾ð¾î ¿µ¾î
DOI https://doi.org/10.5659/AIKAR.2018.20.4.109