A study on the analysis method of passenger flow in airport using laser sensor
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, S.-H. | - |
dc.contributor.author | Lee, H.-T. | - |
dc.contributor.author | Phan, N.-Q. | - |
dc.contributor.author | Gim, G.-Y. | - |
dc.date.available | 2019-03-13T01:51:59Z | - |
dc.date.created | 2018-09-12 | - |
dc.date.issued | 2018-03 | - |
dc.identifier.issn | 2005-4297 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/31896 | - |
dc.description.abstract | There are wide and recent research efforts to extract location information of people in certain spaces, with new services using this information in real space being launched in the market. In particular, there are emerging services and solutions that measure movement flow of people in airports, public facilities, commercial facilities, factories, warehouses, and other locations to mitigate congestion or enhance security and safety in these spaces. Methods of measuring the movement flow of people include camera image analysis, Wi-Fi, beacon, and RFID, but these methods are inconvenient as the tracking targets must carry a certain medium (smartphone, RFID tag, etc.), while camera images infringe upon personal privacy, posing many problems for commercialization of these movement flow technologies. In order to solve this problem, the current study applies a movement flow measurement technology using laser sensors, applying it to a Korean airport to verify its feasibility through an experiment. The researchers propose a method to improve customer service by analyzing the passenger movement flow, congestion levels, and wait time at the airport using the acquired data. © 2018 SERSC Australia. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Science and Engineering Research Support Society | - |
dc.relation.isPartOf | International Journal of Control and Automation | - |
dc.title | A study on the analysis method of passenger flow in airport using laser sensor | - |
dc.type | Article | - |
dc.identifier.doi | 10.14257/ijca.2018.11.5.12 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | International Journal of Control and Automation, v.11, no.5, pp.129 - 142 | - |
dc.description.journalClass | 1 | - |
dc.identifier.scopusid | 2-s2.0-85047986909 | - |
dc.citation.endPage | 142 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 129 | - |
dc.citation.title | International Journal of Control and Automation | - |
dc.citation.volume | 11 | - |
dc.contributor.affiliatedAuthor | Gim, G.-Y. | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordAuthor | Big Data | - |
dc.subject.keywordAuthor | Congestion | - |
dc.subject.keywordAuthor | Flow tracking analysis | - |
dc.subject.keywordAuthor | Laser sensor | - |
dc.subject.keywordAuthor | Visualization | - |
dc.description.journalRegisteredClass | scopus | - |
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