LU MIN

写真a

Affiliation

Faculty of Informatics and Data Science  Department of Informatics and Data Science 

Date of Birth

1986
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Research Interests 【 display / non-display 】

  • ラーニングアナリティクス

  • 位置情報サービス

  • 利用者インタフェース

  • 地図

  • 地図学

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Graduating School 【 display / non-display 】

  • 2004.09
    -
    2008.07

    Peking University   School of Space and Earth Sciences   Geographic Information System   Graduated

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Graduate School 【 display / non-display 】

  • 2011.10
    -
    2014.09

    The University of Tokyo  Graduate School of Frontier Sciences  Socio-Cultural Environmental Studies  Doctor's Course  Completed

  • 2008.09
    -
    2011.07

    Peking University  School of Space and Earth Sciences  Cartology and Geographyic Information System  Master's Course  Completed

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Campus Career 【 display / non-display 】

  • 2025.10
    -
    Now

    Akita University   Faculty of Informatics and Data Science   Department of Informatics and Data Science   Lecturer  

  • 2025.04
    -
    2025.09

    Akita University   Faculty of Informatics and Data Science   Department of Informatics and Data Science   Assistant Professor  

  • 2022.09
    -
    2025.03

    Akita University   Graduate School of Engineering Science   Department of Mathematical Science and Electrical-Electronic-Computer Engineering   Human-Centered Computing Course   Assistant Professor  

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Academic Society Affiliations 【 display / non-display 】

  • 2022.11
    -
    Now
     

    Japan

     

    IEEE

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Research Areas 【 display / non-display 】

  • Natural Science / Human geosciences

  • Humanities & Social Sciences / Geography

  • Informatics / Learning support system

  • Informatics / Human interface and interaction

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Thesis for a degree 【 display / non-display 】

  • Human-Centered Mapping in Mobile Environments

    Min Lu 

      2014.09  [Refereed]

    Single author

    DOI

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Research Achievements 【 display / non-display 】

    ◆Original paper【 display / non-display 】

  • Development and Application of a Dynamic Local Georeferencing Web Platform for Promoting Historical Map Literacy

    Min LU, Quang Sang TRAN, Iroi SASAKI, Koki TAMURA, Masatoshi ARIKAWA

    Map, Journal of the Japan Cartographers Association ( Japan Cartographers Association )  63 ( 2 ) 37 - 52   2025.06  [Refereed]  [Invited]

    Research paper (journal)   Domestic Co-author

    DOI CiNii Research J-GLOBAL

  • Hierarchical geofencing for location-aware generative audio tours

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    Urban Informatics ( Springer Science and Business Media LLC )  3 ( 1 )   2024.12  [Refereed]

    Research paper (journal)   Domestic Co-author

    Abstract

    This study aims to restructure a location-aware audio guide mobile application designed for urban walking tours. Traditional points of interest-based geofencing, which triggers automatic guide delivery as users approach specific locations, struggle to provide continuous and consistent storytelling in areas with limited notable spots, thereby diminishing tourist experiences. To address this challenge, we propose a hierarchical geofencing framework that forms the basis for seamless audio guide experiences through scale-based feature switching and the definition of story serialization rules. In addition, this study proposes geofence-to-conversation techniques utilizing text-to-speech engines and large language models to dynamically adapt guide document resources to dynamic tourists’ movements. A demonstration conducted in a historic urban park area highlighted that the guide generation time in both English and Japanese guide modes is significantly shorter than playback duration, confirming technical feasibility for seamless regional storytelling. Furthermore, we define metrics such as starting time errors, ending time errors, undelivered time to evaluate the real-time performance of location-aware audio guide applications. The experimental results demonstrate effective strategies for geofence configuration and operations, enhancing user experiences in our generative audio tours. This intelligent guide approach, designed for complex urban environments, is expected to enrich tourism and foster regional learning.

    DOI

  • Verification of Sensor Data-Driven Lifecycle for Improvement of Location-Based Services in Walking Tourism

    SASAKI Iori, ARIKAWA Masatoshi, Min LU, UTSUMI Tomihiro, SATO Ryo

    Map, Journal of the Japan Cartographers Association ( Japan Cartographers Association )  62 ( 3 ) 1 - 12   2024.09  [Refereed]

    Research paper (journal)   Domestic Co-author

    DOI CiNii Research

  • Data-Driven Geofencing Design for Point-Of-Interest Notifiers Utilizing Genetic Algorithm

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    ISPRS International Journal of Geo-Information ( MDPI AG )  13 ( 6 ) 174 - 174   2024.05  [Refereed]

    Research paper (journal)   Domestic Co-author

    This study proposes a method for generating geofences driven by GPS trajectory data to realize scalable point-of-interest (POI) notifiers, encouraging walking tourists to discover new local spots. The case study revealed that manual geofence settings degrade the location relevance and user coverage—key objectives of POI notifiers—and hinder the scalability and reliability of services. The formalization presented computationally equips geofence designers with practical solutions through two implementations based on prior GPS trajectory logs: (1) a multiobjective genetic algorithm that suggests cost-effective geofences by providing trade-off visualizations and (2) a user coverage-penalized genetic algorithm that determines an optimal geofence based on the designers’ expectations. The feasibility and stability of the proposed implementations were tested in areas with varying tourist flow patterns. A comparative survey among manual settings, settings incorporating a reliability simulation, and data-driven settings demonstrates significant performance improvements for geofence services.

    DOI

  • Indoor AR Navigation Framework Based on Geofencing and Image-Tracking with Accumulated Error Correction

    Min Lu, Masatoshi Arikawa, Kohei Oba, Keiichi Ishikawa, Yuhan Jin, Tomihiro Utsumi, Ryo Sato

    Applied Sciences ( Applied Sciences (Switzerland) )  14 ( 10 ) 4262   2024.05  [Refereed]

    Research paper (journal)   Domestic Co-author

    DOI

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    ◆International conference proceedings【 display / non-display 】

  • Activating Location-Based Storytelling in a City: Geofence Identification from Crowdsourced Mobile Sensing

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ( Copernicus GmbH )  XLVIII-4/W16-2025   99 - 104   2025.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    Abstract. Location-based storytelling is a key strategy in smart tourism, enabling immersive engagement through narrative content triggered by user movement. This study proposes a data-driven framework for designing enclosure- and viewpoint-geofences that align with storytelling modes, leveraging GPS horizontal-accuracy clustering and motion-sensor noise filtering to detect meaningful spatial engagement zones. We introduce a lightweight decision-tree classifier using cluster duration and motion variability features to distinguish valid indoor stays from transient or noise-induced clusters. In a field experiment with 12 participants in Akita City, our method achieved 94 percent classification accuracy and a 0.96 F1-score under leave-one-out cross-validation. Furthermore, our qualitative comparisons imply the geofence identifications can outperform baseline techniques such as HDBSCAN and stay point detection. The results demonstrate the practical potential of the proposed approach for context-sensitive geofencing in urban tourism. This framework advances autonomous, adaptive geofencing for enriched tourist experiences.

    DOI

  • Generative AI-Based Application for Producing Tourism Video Blogs with Proximity and Direction to Points of Interest

    Hayate Eguchi, Iori Sasaki, Min Lu, Tomihiro Utsumi, Ryo Sato, Masatoshi Arikawa

    The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ( Copernicus GmbH )  XLVIII-4/W16-2025   33 - 38   2025.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    Abstract. Taking and sharing videos of tourist attractions has become a common activity among tourists. When accompanied by captions and audio, these videos serve as an effective way of conveying impressions and information about the places visited through social media. Such content not only enriches the post-travel experience of individuals but also contributes to promoting local tourism and stimulating inbound demand. However, producing highly informative video content poses challenges in that it requires editing skills and reliability of information. This study establishes a method for automatically overlaying captions onto videos by (1) estimating appropriate time periods during which points of interest (POIs) are captured within the camera’s field of view, and (2) generating explanatory comments with a suitable word count for the corresponding durations. This method was implemented in the author’s video blog application to enable users to easily share the appeal of a region. In a field experiment simulating tourist movement and POI filming within a predefined guide area, the average error between the time a POI appeared in the video and the calculated caption display duration was approximately 1.8 seconds, with a maximum error of 4.0 seconds. This level of accuracy is considered sufficient for viewers to associate each caption with the corresponding POI as it appears in the video. Furthermore, the text length of the generated captions was also reasonable for the display duration, and their content was confirmed to be factually accurate through qualitative evaluation. Future improvements should incorporate the users’ personal experiences into the caption generation.

    DOI

  • Connect E-Book Content and Structure to Student Jump-Back Behavior

    Boxuan Ma, Min Lu, Li Chen, Masanori Yamada

    2025 IEEE International Conference on Advanced Learning Technologies (ICALT) ( IEEE )    114 - 116   2025.07  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Exploring the Role of Metacognition in Enhancing Learning Outcomes through Learning Analytics Dashboard

    Masanori Yamada, Xuewang Geng, Min Lu, Yuta Taniguchi

    Proceedings of eLearn 2024     2024.10  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

  • Directional Progress Indicator for Visualizing Off-Screen Point-of-Interest in Handheld Augmented Reality

    Ren Kurosaki, Masatoshi Arikawa, Ryoo Fujiwara, Iori Sasaki, Min Lu, Tomihiro Utsumi, Ryo Sato

    Proceedings of the 2024 8th International Conference on Big Data and Internet of Things ( ACM )    114 - 119   2024.09  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI CiNii Research

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    ◆Research society, Symposium materials, etc.【 display / non-display 】

  • Integrating Art and Functionality: A Study of Yoshida Hatsusaburo's Panoramic Transit Maps

    Hsiang-Yun Wu, Min Lu, Shigeo Takahashi, Masatoshi Arikawa

    4th Schematic Mapping Workshop     2025.04  [Refereed]  [Invited]

    Research paper (research society, symposium materials, etc.)   International Co-author

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    ◆Other【 display / non-display 】

  • Proposal and Implementation of a Web Mapping Tool for Interpreting Positional Inconsistencies and Representational Differences in Historic Maps

    TRAN Quang Sang, LU Min, 佐々木一織, NUR Shafiza Binti Mohd Afandi, 有川正俊

    日本地図学会定期大会発表論文・資料集   2025   2025.08

    Summary of the papers read (national conference and other science council)   Domestic Co-author

    J-GLOBAL

  • Enhancing E-Book Learning Dashboards with GPT-Assisted Page Grouping and Adaptive Navigation Link Visualization

    Min Lu, Boxuan Ma, Xuewang Geng, Masatoshi Yamada

    The 15th International Learning Analytics and Knowledge Conference (LAK 2025)     2025.03  [Refereed]

    Summary of the papers read (international conference)   Domestic Co-author

  • Educational Potential of Map Storytelling Creation using Data Objects-Driven Mobile Mapping Toolkit – KoPpoMai

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato

    Abstracts of the ICA ( Copernicus GmbH )  6   1 - 2   2023.08  [Refereed]

    Summary of the papers read (international conference)   Domestic Co-author

    DOI

  • Learning Analytics Dashboard Supporting Metacognition

    Li Chen, Min Lu, Yoshiko Goda, Atsushi Shimada, Masanori Yamada

    Balancing the Tension between Digital Technologies and Learning Sciences ( Springer International Publishing )    129 - 149   2021.02  [Refereed]

    Domestic Co-author

    DOI

  • Visualizing Studying Activities for a Learning Dashboard Supporting Meta-cognition for Students

    Min Lu, Li Chen, Yoshiko Goda, Atsushi Shimada, Masanori Yamada

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) )  12203 LNCS   569 - 580   2020.07  [Invited]

    Domestic Co-author

    DOI

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Books 【 display / non-display 】

  • Ubiquitous Mapping: Perspectives from Japan - Chapter 2: Ubiquitous Digital Storytelling with Local and Dynamic Georeferencing of Analog Maps

    Masatoshi Arikawa, Min Lu

    Springer Singapore  2022.07 ISBN: 978-981-19-1535-2

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Grant-in-Aid for Scientific Research 【 display / non-display 】

  • Grant-in-Aid for Scientific Research(C)

    Project Year： 2023.04  -  2027.03 

  • Grant-in-Aid for Scientific Research(A)

    Project Year： 2022.04  -  2026.03 

  • Grant-in-Aid for Challenging Research (Pioneering)/(Exploratory)

    Project Year： 2021.07  -  2025.03 

  • Grant-in-Aid for Early-Career Scientists

    Project Year： 2020.04  -  2023.03 

  • Fund for the Promotion of Joint International Research

    Project Year： 2019.10  -  2023.03 

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Presentations 【 display / non-display 】

  • Exploring Corresponding Geographic Features across Historical Maps via Dynamic Local Georeferencing

    Quang Sang Tran, Min Lu, Iori Sasaki, Masatoshi Arikawa

    PNC 2025 Annual Conference and Joint Meetings  2025.09  -  2025.09 

  • A Data-Driven Ecosystem for AI-Enhanced Cultural Narratives with Tourist and Citizen Participations

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Tomihiro Utsumi, Ryo Sato

    PNC 2025 Annual Conference and Joint Meetings  2025.09  -  2025.09 

  • Bridging Traditional and Digital Cartography: Techniques in Dynamic Local Georeferencing

    Quang Sang Tran, Min Lu, Iori Sasaki, Masatoshi Arikawa

    The First Asian Cartographic Conference (AsiaCarto 2024)  2024.12  -  2024.12 

  • Dynamic Local Georeferencing for Investigating Common and Different Objects among Distorted Maps

    チャン クアン サン, Lu Min, 佐々木 一織, 田村 公季, 有川 正俊

    2024年度電気関係学会東北支部連合大会  2024.08  -  2024.08 

  • Functions of Orienting Users to Right Position for Viewing Photos in AR Spaces

    藤原稜大, 黒崎 蓮, 有川正俊, Lu Min, 佐藤 諒, 佐々木一織, 内海富博

    2023年度 電気関係学会 東北支部連合大会  2023.09  -  2023.09 

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