2019 Fiscal Year Final Research Report
Information presentation for congestion avoidance based on real-time data
Project/Area Number |
17K00438
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Web informatics, Service informatics
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Research Institution | Kyoto University |
Principal Investigator |
Kasahara Hidekazu 京都大学, 学術情報メディアセンター, 特定講師 (00784191)
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Project Period (FY) |
2017-04-01 – 2020-03-31
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Keywords | 観光情報学 / 機械学習 / 逸脱行動検知 / 異常検知 / GPS移動軌跡 |
Outline of Final Research Achievements |
In this study, I focused on the overtourism problem, which has become a major problem in the world, and worked to resolve it using information technology. Tourist behavior is a behavior which changes dynamically according to the real time situation of sightseeing spots, mostly following the travel plan set based on the static information of tourist spots obtained beforehand. I aimed to change the behavior of tourists by appropriate presentation of information, and to improve the satisfaction of both tourists and local residents by reducing congestion. Specifically, I constructed a tourist behavior model based on real-time information and developed a method to detect deviant behavior without inputting destination beforehand. And, the design of the regional sightseeing information base was also carried out, and I discussed in the region and research community.
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Free Research Field |
観光情報学
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Academic Significance and Societal Importance of the Research Achievements |
不動産価格の高騰などを通じて地域コミュニティを壊しかねないオーバーツーリズムの弊害を抑えるため,人の行動を予測し,変容を促すことで集中を緩和する技術の社会的意義は大きく,観光以外の分野への応用も期待できる.学術的にも,リアルタイム情報を元に,目的地が分からなくても迷子を含めた逸脱を検知できる技術には新規性がある.
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