SASAKI Iori

写真a

Affiliation

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

Homepage URL

https://io-33kyanite.github.io/sasaki/

Mail Address

E-mail address

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Research Interests 【 display / non-display 】

  • Mobile Big Data

  • Cartography

  • Tourism Informatics

  • GPS Trajectory Mining

  • Location-Based Services

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Graduating School 【 display / non-display 】

  • 2016.04
    -
    2020.03

    Akita University   Faculty of Engineering and Science   Graduated

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Graduate School 【 display / non-display 】

  • 2022.04
    -
    2025.03

    Akita University  Graduate School, Division of Science and Engineering  Doctor's Degree Program  Completed

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Degree 【 display / non-display 】

  • Akita University -  Doctor (Engineering)

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Campus Career 【 display / non-display 】

  • 2025.04
    -
    Now

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

  • 2022.04
    -
    2025.03

    Akita University   Graduate School of Engineering Science   Department of Mathematical Science and Electrical-Electronic-Computer Engineering   Postdoctoral Fellowships of Japan Society for the Promotion of Science  

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Academic Society Affiliations 【 display / non-display 】

  • 2019.08
    -
    Now
     

    Japan

     

    Information Processing Society of Japan

  • 2021.10
    -
    Now
     

    Japan

     

    The Database Society of Japan

  • 2024.01
    -
    Now
     

    Japan

     

    Japan Cartographers Association

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Research Areas 【 display / non-display 】

  • Informatics / Intelligent informatics

  • Humanities & Social Sciences / Library and information science, humanistic and social informatics

  • Informatics / Web informatics and service informatics

  • Humanities & Social Sciences / Geography

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Thesis for a degree 【 display / non-display 】

  • Data-Driven Geofencing: Advancing Urban Tourist Exploration with Location Intelligence

    SASAKI Iori 

      2025.03

    Single author

    【和訳】データ駆動型ジオフェンシング：位置インテリジェンスによる都市観光行動の促進

    本論文は，プッシュ型位置情報サービスの中核をなす「ジオフェンシング」という技術について取り上げています。ジオフェンシングとは，あらかじめ設定した仮想エリアへの入退出を検知して，情報を自動的に送信するイベント処理の仕組みです。本論文の提案は，マップデータに基づいて経験や勘を頼りに設定するのではなく，ヒトの移動データを仮想エリアの最適化プロセスに組み込むことが必要であるということです。都市移動に際して必要な情報を適切なタイミングで届けられるような観光ガイドアプリケーションのデザインに寄与しました。

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Research Achievements 【 display / non-display 】

    ◆Original paper【 display / non-display 】

  • Hierarchical Geofencing for Location-Aware Generative Audio Tours

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

    Urban Informatics ( Springer Nature )  3 ( 33 )   2024.12  [Refereed]

    Research paper (journal)   Domestic Co-author

    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

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

        2024.09  [Refereed]

    Research paper (journal)   Domestic Co-author

    DOI

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

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

    ISPRS International Journal of Geo-Information ( ISPRS International Journal of Geo-Information )  13 ( 6 )   2024.06  [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

  • Mobile Collaborative Heatmapping to Infer Self-Guided Walking Tourists’ Preferences for Geomedia

    Iori Sasaki, Masatoshi Arikawa, Min Lu and Ryo Sato

    ISPRS International Journal of Geo-Information   12 ( 7 )   2023.07  [Refereed]

    Research paper (journal)   Domestic Co-author

    This paper proposes a model-less feedback system driven by tourist tracking data that are automatically collected through mobile applications to visualize the gap between geomedia recommendations and the actual routes selected by tourists. High-frequency GPS data essentially make it difficult to interpret the semantic importance of hot spots and the presence of street-level features on a density map. Our mobile collaborative framework reorganizes tourist trajectories. This processing comprises (1) extracting the location of the user-generated content (UGC) recording, (2) abstracting the locations where tourists stay, (3) discarding locations where users remain stationary, and (4) simplifying the remaining points of location. Then, our heatmapping system visualizes heatmaps for hot streets, UGC-oriented hot spots, and indoor-oriented hot spots. According to our experimental study, this method can generate a trajectory that is more adaptable for hot street visualization than the raw trajectory and a simplified trajectory according to its geometry. This paper extends our previous work at the 2022 IEEE International Conference on Big Data, providing deeper discussions on application for local tourism. The framework allows us to derive insights for the development of guide content from mobile sensor data.

    DOI

  • Articulated Trajectory Mapping for Reviewing Walking Tours

    Iori Sasaki, Masatoshi Arikawa and Akinori Takahashi

    ISPRS International Journal of Geo-Information ( ISPRS International Journal of Geo-Information )  9 ( 10 )   2020.10  [Refereed]

    Research paper (journal)   Domestic Co-author

    This paper addresses how to enrich a map-based representation for reviewing walking tours with the features of trajectory mapping and tracing animation. Generally, a trajectory generated by raw GPS data can often be difficult to browse through on a map. To resolve this issue, we first illustrated tangled trajectory lines, inaccurate indoor positioning, and unstable trajectory lines as problems encountered when mapping raw trajectory data. Then, we proposed a new framework that focuses on GPS horizontal accuracy to locate indoor location points and find stopping points on an accelerometer. We also applied a conventional line simplification algorithm to make the trajectory cleaner and then integrated the extracted points with the clean trajectory line. Furthermore, our experiments with some actual logs of walking tours demonstrated that articulated trajectory mapping, which comprises simplification and characterization methods, sufficiently reliable and effective for better reviewing experiences. The paper contributes to the research on cleaning up map-based displays and tracing animations of raw trajectory GPS data by using not only location data but also sensor data that smartphones can collect.

    DOI

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    ◆International conference proceedings【 display / non-display 】

  • 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 and Ryo Sato

    BDIOT ‘24: Proceedings of the 2024 8th International Conference on Big Data and Internet of Things ( ACM International Conference Proceeding Series )    114 - 119   2024.12  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Generative Live Commentaries Interacting with Geospatial Context for Promoting Local Festivals

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

    BDIOT ‘24: Proceedings of the 2024 8th International Conference on Big Data and Internet of Things ( ACM International Conference Proceeding Series )    125 - 131   2024.12  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Adaptable Data-Driven Geofences for Notifying Points of Interest Using Tourists’ GPS Trajectories

    Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato and Tomihiro Utsum

    LocalRec'23: Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising ( Association for Computing Machinery )    37 - 43   2023.11  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

  • Thematic Geo-Density Heatmapping for Walking Tourism Analytics using Semi-Ready GPS Trajectories

    Iori Sasaki, Masatoshi Arikawa, Min Lu and Ryo Sato

    2022 IEEE International Conference on Big Data (Big Data)     4944 - 4951   2023.01  [Refereed]

    Research paper (international conference proceedings)   Single author

    DOI

  • Adaptive Visualization of Tourists’ Preferred Spots and Streets Using Trajectory Articulation

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

    Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility, HANIMOB 2022 ( Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility, HANIMOB 2022 )    27 - 32   2022.11  [Refereed]

    Research paper (international conference proceedings)   Domestic Co-author

    DOI

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    ◆Other【 display / non-display 】

  • Report on participation in the 31st International Cartographic Conference and 19th International Cartographic Association General Meeting (Cape Town, South Africa)

    ITO Kaori, WAKABAYASHI Yoshiki, MORITA Takashi, YANO Keiji, SASAKI Iori, YOSHIDA Momoko, KAWAI Takuya, ISHIKAWA Hajime

    Map, Journal of the Japan Cartographers Association ( Japan Cartographers Association )  61 ( 4 ) 1 - 16   2023.12

    Meeting report etc.   Domestic Co-author

    DOI CiNii Research

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

  • Grant-in-Aid for JSPS Fellows

    Project Year： 2022.04  -  2025.03  Investigator(s): SASAKI Iori

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Presentations 【 display / non-display 】

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

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

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

  • Geofence-to-Conversation: Hierarchical Geofencing for Augmenting City Walks with Large Language Models

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

    International Conference on Mobile Human-Computer Interaction  2024.09  -  2024.10 

    デモセッション

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

    Iori Sasaki, Masatoshi Arikawa, Min Lu and Ryo Sato

    31st International Cartographic Conference (ICC2023)  2023.08  -  2023.08 

    An abstract was published in Abstracts of the ICA.

  • Concept Design of Generative Location-Based Audio Tours

    Iori Sasaki, Masatoshi Arikawa, Tomokazu Tamura and Min Lu

    Workshop of the Commission on Ubiquitous Mapping and Commission on Maps and the Internet organized as part of 31st International Cartographic Conference  (Online)  2023.08  -  2023.08 

  • Semantic GPS Trajectory Representation via Articulation Processings

    Iori Sasaki, Masatoshi Arikawa, Ryo Sato and Akinori Takahashi

    Workshop of the Commission on Maps and the Internet and Commission on Ubiquitous Mapping organized as part of 30th International Cartographic Conference  2021.12  -  2021.12 

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Media Report 【 display / non-display 】

  • 23面

  • 17面

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