研究者詳細 - 河口　信夫

その他リンク： https://ieeexplore.ieee.org/document/11091313

SemantiPack: An Efficient Real-World Data Compressor Using Structural and Semantic Metadata 査読有り

Nagata, Y; Kohama, D; Watanabe, Y; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

IEEE ACCESS 13 巻頁： 114159 - 114178 2025年6月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE Access

The exponential growth of Real-World Data (RWD), primarily collected from IoT sensors and spanning domains such as mobility, environment, and energy consumption, presents critical challenges due to its scale, heterogeneity, and structural variability. Traditional compression methods often fail to adapt efficiently to these complexities, leading to sub-optimal storage and analysis performance. Additionally, while several metadata schemas exist to enhance the availability of RWD, smaller organizations often lack the resources to create and manage metadata effectively. This paper introduces RWD Profile, an automatically generatable metadata schema for RWD, and SemantiPack, which applies tailored compression to data fields in the individual RWD based on RWD Profile. RWD Profile has two kinds of metadata, Structural Profile and Semantic Profile. Structural Profile is generated through rule-based systems, while Semantic Profile is generated using large language models (LLMs) to capture semantic data properties. On the other hand, SemantiPack performs compression at the data field level in RWD using RWD Profile to achieve higher compression ratios. Experimental results demonstrate up to 23.2% improved compression rate for JSON and 19.3% for CSV compared to conventional methods while maintaining a faster or equivalent processing speed compared to conventional methods. Furthermore, SemantiPack supports lossy compression for applications prioritizing storage over precision. This research not only improves compression efficiency but also establishes a scalable solution for automated analysis and sustainable data utilization, paving the way for advancements in RWD management.

DOI： 10.1109/ACCESS.2025.3583829

Digitization Methods for a Logistics Warehouse Towards Digital Twin-Driven Optimization

Kawaguchi N., Asai Y., Kano K., Takaki K., Mori Y., Suzuki Y., Watanabe K., Gushi Y., Katayama S., Urano K., Yonezawa T., Hashiguchi S.

Proceedings 2025 IEEE International Conference on Smart Computing Smartcomp 2025 頁： 186 - 193 2025年6月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Proceedings 2025 IEEE International Conference on Smart Computing Smartcomp 2025

The rapid growth of e-commerce, rising consumer expectations, and labor shortages in Japan pose challenges for logistics warehouse optimization. While automation has advanced outbound operations, inbound processes remain inefficient. This study presents a comprehensive approach to digitizing and optimizing large-scale logistics warehouses, with a case study at TRUSCO NAKAYAMA Corp. in partnership with Nagoya University. Key technologies include a large-scale camera array, multi-camera object tracking, and smartphone-based task estimation. Our contributions include real-time tracking of personnel and packages, cooperative annotation for improved object recognition, and synthetic data augmentation. Additionally, truck berth analysis and indoor localization enhance operational efficiency. To optimize worker shifts and warehouse layout, we apply Factorization Machine Quantum Annealing (FMQA), achieving a 37.4% reduction in lead times and a 14.3% decrease in labor hours. A visualization tool enables warehouse operators to make data-driven decisions. This research demonstrates the potential of digital transformation in logistics and provides a scalable framework for broader industry adoption.

DOI： 10.1109/SMARTCOMP65954.2025.00035

Semi-Automated Framework for Digitalizing Multi-Product Warehouses with Large Scale Camera Arrays

その他リンク： https://db.uclab.jp/show/1538

Higashiura, K; Yokoyama, K; Asai, Y; Shimosato, H; Kano, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

2024 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS, PERCOM 頁： 98 - 105 2024年3月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：2024 IEEE International Conference on Pervasive Computing and Communications, PerCom 2024

As global demand for logistics continues to grow, optimizing the automation and efficiency of distribution warehouse operations is of paramount importance. Digitalizing warehouse environments, which refers to the process of sensing the physical space and extracting meaningful information from the obtained data, offers a promising solution to this challenge. However, converting raw warehouse data, such as video footage captured inside the warehouse, into actionable metadata (e.g., tracking the movement paths of workers and products or analyzing the usage patterns of different warehouse locations) often necessitates significant human intervention. The rise of machine learning further complicates this, as it requires the manual preparation of extensive training datasets. In this paper, we introduce a framework that semi-automates the digitalization process in complex warehouse settings. This framework employs dense optical flow and representation learning to autonomously segment warehouse objects and cluster similar objects, thereby substantially cutting down on annotation costs. To evaluate our approach, we constructed a large-scale data collection platform with over 60 fixed cameras in a real-world logistics warehouse, and the video data from this platform was then applied to our framework. Our evaluations indicate that our method markedly reduces both the time and resources required for warehouse digitalization using the captured video data.

DOI： 10.1109/PERCOM59722.2024.10494498

都市を対象とした大規模移動履歴に基づく疑似人流データ生成手法招待有り査読有り Open Access

田村直樹, 浦野健太, 青木俊介, 米澤拓郎, 河口信夫

情報処理学会論文誌 64 巻 ( 1 ) 頁： 123 - 133 2023年1月

ER-Chat: A Text-to-Text Open-Domain Dialogue Framework for Emotion Regulation 査読有り

Katayama Shin, Aoki Shunsuke, Yonezawa Takuro, Okoshi Tadashi, Nakazawa Jin, Kawaguchi Nobuo

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 13 巻 ( 4 ) 頁： 2229 - 2237 2022年10月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE Transactions on Affective Computing

Emotions are essential for constructing social relationships between humans and interactive systems. Although emotional and empathetic dialogue generation methods have been proposed for dialogue systems, appropriate dialogue involves not only mirroring emotions and always being empathetic but also complex factors such as context. This paper proposes Emotion Regulation Chat (ER-Chat) as an end-to-end dialogue framework for emotion regulation. Emotion regulation is concerned with actions to approach appropriate emotional states. Learning appropriate emotion and intent when responding on the basis of the context of the dialogue enables the generation of more human-like dialogue. We conducted automatic and human evaluations to demonstrate the superiority of ER-Chat over the baseline system. The results show that inclusion of emotion and intent prediction mechanisms enable generation of dialogues with greater fluency, diversity, emotion awareness, and emotion appropriateness, which are greatly preferred by humans.

DOI： 10.1109/TAFFC.2022.3191973

Deep Learning for Ballroom Dance Recognition: A Temporal and Trajectory-Aware Classification Model With Three-Dimensional Pose Estimation and Wearable Sensing 査読有り

Matsuyama Hitoshi, Aoki Shunsuke, Yonezawa Takuro, Hiroi Kei, Kaji Katsuhiko, Kawaguchi Nobuo

IEEE SENSORS JOURNAL 21 巻 ( 22 ) 頁： 25437 - 25448 2021年11月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE Sensors Journal

Dance performance recognition methods have been investigated and shown various applications such as picture-pose evaluation and synchronizing foot timing and direction. However, detailed analysis and feedback are still missing. To provide them, understanding the performance by component level is necessary. Specifically, we formulate it as a dance-figure classification problem using three-dimensional body joints and wearable sensors. Our model is based on long short-term memory (LSTM) and includes the temporal and trajectory-wise structure that uses the trajectory information in a timestep and the temporal masking module. As a result, we achieved 93% accuracy with our proposed method, which is highly overwhelming the baseline result (84.7%) and very close to the accuracy of the experienced dancers (93.6%). We have made the dataset of ballroom dance performance dataset open to researchers to develop the activity recognition field further.

DOI： 10.1109/JSEN.2021.3098744

大規模ユーザの滞在情報に基づくエリアの特徴付けとCOVID-19による影響分析査読有り Open Access

庄子和之, 青木俊介, 米澤拓郎, 河口信夫

情報処理学会論文誌 62 巻頁： 1644 - 1657 2021年10月

Real-time Activity-Aware Video Streaming While Preserving Privacy 査読有り

Ubicomp Companion 2025 Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing 頁： 236 - 240 2025年12月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Ubicomp Companion 2025 Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing

We present ActStream, a remote communication system that selectively shares the user and objects relevant to their current activities. By combining vision-language models and real-time segmentation, ActStream detects and highlights only activity-relevant elements, enhancing awareness while preserving privacy. The system identifies key objects through user focus or interaction, synthesizes them with the user's image, and streams the result to a remote partner. ActStream aims to provide useful context without exposing unnecessary information, highlighting the potential of selective sharing in privacy-sensitive remote collaboration.

DOI： 10.1145/3714394.3754399

Smartphone-Based Activity Recognition in a Logistics Warehouse Using Self-supervised Representation Learning 査読有り

Ubicomp Companion 2025 Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing 頁： 1067 - 1073 2025年12月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Ubicomp Companion 2025 Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing

To address labor shortages in logistics, digital twins that digitize physical environments are gaining attention, as they enable visualization and simulation-based optimization of warehouse operations. However, digitizing worker activities is particularly challenging due to operational burden and difficulty in adapting to diverse tasks. In response to this issue, we propose a deep learning-based framework for automatic warehouse task recognition using smartphone inertial sensors (accelerometer and gyroscope). Our model combines a CNN pretrained on unlabeled data using SimCLR, a self-supervised representation learning method, to improve generalization, and a Transformer encoder to capture task-level context. We collected data in a logistics warehouse and conducted cross-validation using 6 hours of annotated data from 10 individuals. As a result, the proposed method achieved a weighted F1 score of 0.89, improving by 7 points over the model without pretraining.

DOI： 10.1145/3714394.3756198

Multi-City Next Location Prediction through Mobility-Derived Multi-Pattern Transfer Learning 査読有り

Terashima H., Tamura N., Shoji K., Urano K., Yonezawa T., Kawaguchi N.

33rd ACM Sigspatial International Conference on Advances in Geographic Information Systems ACM Sigspatial 2025 頁： 1218 - 1221 2025年11月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：33rd ACM Sigspatial International Conference on Advances in Geographic Information Systems ACM Sigspatial 2025

In this study, we propose MoDeMIT (Mobility-Derived Multi-Insight Transfer), a human mobility prediction method that transfers various patterns shared across cities, extracted from mobility histories. Existing studies on human mobility prediction have primarily focused on learning the mobility patterns of users in the target city, without considering applications in cities with limited data. Moreover, relying solely on mobility patterns poses inherent limitations on prediction accuracy. The proposed MoDeMIT addresses these issues by defining and transferring multiple patterns shared across cities, such as lifestyle patterns and large-scale mobility patterns derived from mobility histories, as well as mobility patterns. This approach enables improvements in prediction accuracy compared to existing methods. We validate the effectiveness of MoDeMIT using real-world human mobility datasets. Furthermore, in the HuMob Challenge 2025 (GISCUP), MoDeMIT achieved a GEOBLEU score of [Average: 0.1632, CityA: 0.1504, CityB: 0.1471, CityC: 0.1801, CityD: 0.1753] and ranked within the top five teams.

DOI： 10.1145/3748636.3771311

Soccer Player Tracking Using Multiple Features for ID Switch Correction in Fixed-View Videos 査読有り

8TH INTERNATIONAL ACM WORKSHOP ON MULTIMEDIA CONTENT ANALYSIS IN SPORTS, MMSPORTS 2025 頁： 189 - 195 2025年10月

CorVS: Person Identification via Video Trajectory-Sensor Correspondence in a Real-World Warehouse 査読有り Open Access

Kano K., Mori Y., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

Proceedings of the 15th International Conference on Indoor Positioning and Indoor Navigation Ipin 2025 2025年9月

Design and Deployment of a Private 5G Testbed Integrated with a Nationwide Academic Backbone 査読有り

Sasayama K., Nakao A., Takezawa H., Kawaguchi N., Maruyama M., Kondo T., Shimoji H., Urushidani S., Kurimoto T.

2025 IEEE Conference on Standards for Communications and Networking Cscn 2025 2025年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2025 IEEE Conference on Standards for Communications and Networking Cscn 2025

This paper presents a nationwide academic testbed that integrates private 5G mobile networks, known as "local 5G"in Japan, with SINET6, the country's ultra-high-speed and low-latency academic backbone network. Unlike public 5G networks, local 5G systems offer advanced features such as flexible uplink/downlink resource allocation and independent deployment of core and radio access functions. We developed a novel architecture in which both the 5G core and RAN are integrated into a compact, portable system connected to SINET via campus LANs. Deployed across multiple universities in Japan, this testbed enables high-performance mobile data communication tailored for academic research. We report on its design, implementation, performance evaluations, and a range of practical use case demonstrations conducted by participating institutions.

DOI： 10.1109/CSCN67557.2025.11230704

Mitigating Latency Effects in VR180 Teleoperation via Virtual Robotic Arm Overlay 査読有り

Tsutsui S., Watanabe K., Usami R., Gushi Y., Watanabe Y., Shimura K., Hayashida N., Jimenez F., Urano K., Yonezawa T., Kawaguchi N.

15th International Conference on Mobile Computing and Ubiquitous Networking Icmu 2025 2025年9月

MetaUniTour: Enhancing Engagement and Intercultural Understanding through A Metaverse Tourism Platform 査読有り

Matsumoto K., Watanabe Y., Shimura K., Hayashida N., Katayama S., Urano K., Kawaguchi N., Aoki S., Leleito E., Yonezawa T.

Proceedings 2025 International Conference on Metaverse Computing Networking and Applications Metacom 2025 頁： 125 - 130 2025年8月

Discovering Emerging Urban Hotspots Using Satellite Imagery and Human Mobility Data 査読有り

Tillayeva N., Terashima H., Tamura N., Shoji K., Hossain T., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

Distributed, Ambient and Pervasive Interactions: 13th International Conference, DAPI 2025, Held as Part of the 27th HCI International Conference, HCII 2025 15803 LNCS 巻頁： 110 - 120 2025年6月

Clustering-Based Multitask Classification for Predictive Consumer Behavior Modeling 査読有り国際共著

2025年4月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2025 International Conference on Activity and Behavior Computing Abc 2025

Understanding customers and segmenting in an appropriate way play a vital role in business operations and effective marketing strategies. It helps target specific customer groups for increased engagement and profit. However, traditional approaches often struggle to predict future purchase patterns, especially when user data is sparse and fragmented across multiple sources. This research proposes a novel clustering-based multitask classification method to address these limitations. We integrated the Recency, Frequency Monetary (RFM) model to cluster customers based on their purchase patterns from various purchase categories (tickets, merchandise, fan club membership) to create a more comprehensive understanding of loyalty for a professional basketball team in Japan. The proposed model predicts a customer’s segment across all purchase categories, implying the potential relationships between each category. Initial results demonstrate that the model effectively analyzes purchase behaviors, offering actionable insights to enhance marketing strategies.

DOI： 10.1109/ABC64332.2025.11118620

Additive Compositionality in Urban Area Embeddings Based on Human Mobility Patterns

Efficient Edge AI based Annotation and Detection Framework for Logistics Warehouses 査読有り

Yuki Mori, Yusuke Asai, Keisuke Higashiura, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

IEEE Consumer Communications & Networking Conference 2025 2025年1月

Tamura N., Terashima H., Shoji K., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024 頁： 577 - 580 2024年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024

Understanding the characteristics of various urban areas is crucial for applications such as urban planning, tourism policies, market analysis, and infection control. Techniques for embedding areas as vectors in a latent space based on human mobility patterns are actively researched. Many of these area embedding methods define areas as points, grids, or polygons on a geospatial plane and then embed them. However, existing methods do not allow for mutual transformation between these forms and sizes after the initial embedding. Additionally, if the characteristics of an area change due to events such as the opening of new buildings, re-embedding is necessary. Meanwhile, the Word2Vec technique, a representative word embedding method, has a property called additive compositionality. This property allows for the arithmetic operation of word meanings through the arithmetic operations of word embeddings. In this paper, we propose a method to apply this property to existing area embedding techniques, leveraging it for practical tasks such as area shape transformation and searching for areas with trends change.

DOI： 10.1145/3678717.3691279

Unveiling Human Attributes through Life Pattern Clustering using GPS Data Only

Shoji K., Terashima H., Tamura N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024 頁： 621 - 624 2024年10月

Clustering people by their life patterns is valuable in government and business fields. Existing studies often rely on semantic data such as Point of Interest or stay purpose. However, they have the problem that obtaining large datasets is difficult due to the need for annotation work. Some studies try to use only location data. However, they do not reveal the semantics of the area where visitors stay because they only label visited areas by significance according to duration and frequency of stay. In this paper, we propose a framework, LPSeL, for clustering people’s Life Patterns at a Semantic Level using only raw GPS location data. LPSeL is based on the idea that analyzing human mobility first requires understanding urban space. Therefore, it begins with area modeling, which models areas in a city based on people’s activities. Then, treating human mobility as a sequence of area representations makes it possible to model individuals by semantic-level characteristics of their life patterns. We showed that LPSeL is capable of estimating people’s attributes from their life patterns using a real-world dataset consisting of GPS data collected from tens of thousands of smartphone users.

DOI： 10.1145/3678717.3691309

Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs 査読有り

Terashima H., Takagi S., Tamura N., Shoji K., Hossain T., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

32nd ACM SIGSPATIAL International Workshop on the Human Mobility Prediction Challenge, HuMob-Challenge 2024 頁： 5 - 9 2024年10月

自律移動ロボットを用いた人流計測のための探索経路生成招待有り査読有り Open Access

下里浩昇, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

情報処理学会論文誌 65 巻頁： 1511 - 1522 2024年10月

倉庫内業務の量子アニーリングによる最適化とシミュレーションによる評価

瀧上昂希，福島悠人，浅井悠佑，片山晋，浦野健太，米澤拓郎，河口信夫

第81回UBI研究会 2024年2月

スマートフォン・全方位カメラを用いた作業効率化のための半自動天伏図作成システム Open Access

小濱大輝, 永田吉輝, 安武和成, 酒見和幸, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

空気調和・衛生工学会大会　学術講演論文集 2024.10 巻 ( 0 ) 頁： 485 - 488 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：公益社団法人空気調和・衛生工学会

建物の改修工事の際，現状の図面が必要となる．10年以上運用された建物では，図面がなかったり，あったとしても過去の改修を反映していなかったりする．天井設備が記載された天伏図の修正のために現地調査がよく行われる．しかし，天井設備の位置や種類を正確に確認するのは手間が掛かる．本研究では，天伏図作成の作業効率を高めるために，スマートフォン・全方位カメラで撮影した動画から，既存建物の天伏図を少ない作業時間で半自動的に作成するシステムを提案する．

DOI： 10.18948/shasetaikai.2024.10.0_485

Open Access

Area Modeling using Stay Information for Large-Scale Users and Analysis for Influence of COVID-19.

Kazuyuki Shoji, Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

arxiv.org/abs/2401.10648v1 abs/2401.10648 巻 2024年

Towards a Real-Time and Energy-Efficient Edge AI Camera Architecture in Mega Warehouse Environment

Asai Y., Mori Y., Higashiura K., Yokoyama K., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

Proceedings - 2024 IEEE 3rd Real-Time and Intelligent Edge Computing Workshop, RAGE 2024 頁： 12 - 17 2024年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Proceedings - 2024 IEEE 3rd Real-Time and Intelligent Edge Computing Workshop, RAGE 2024

In response to the exponential growth of e-commerce, our paper addresses the transformation of warehouse operations towards mega warehouses, necessitating advanced digitalization. We focus on the integration and optimization of edge AI technologies to enhance operational efficiency, accuracy, and timeliness in logistic warehouses. We propose a novel edge AI architecture tailored to the processes of warehouse operations ensuring that digitalization aligns with operational workflows. Utilizing a real-world warehouse equipped with over 60 cameras as a testbed, we demonstrate the practical application and benefits of edge computing in logistics. Our experiments have shown significant potential improvements in energy efficiency and timeliness, crucial metrics for the successful integration of edge AI technologies in warehouses.

DOI： 10.1109/RAGE62451.2024.00010

Poster: Sustainable Data Management Flow for Spatio-Temporal Datasets

Nagata, Y; Kohama, D; Watanabe, Y; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 頁： 688 - 689 2024年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：MOBISYS 2024 - Proceedings of the 2024 22nd Annual International Conference on Mobile Systems, Applications and Services

Spatio-temporal data is utilized in various fields, but its scale is continuously growing, leading to significant labor and costs in storage and processing. Therefore, the value that can be derived from spatio-temporal data is diluted due to management costs. We propose a new data management flow using various metadata and common programs for spatio-temporal data utilization. Traditionally, various spatio-temporal data processing have been implemented and processed according to each spatio-temporal data. We defined spatio-temporal data structure metadata and performed data processing based on metadata using a common data processing program. Furthermore, we automated the generation of data structure metadata by combining our data skeleton recognition method and generative AI model. Using this flow, we expect to improve the sustainability of utilizing spatio-temporal data.

DOI： 10.1145/3643832.3661423

Demo: Assisting System for Creating Ceiling Plan Using a Video from a Smatrphone

Kohama, D; Nagata, Y; Yasutake, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 頁： 620 - 621 2024年

We present an assisting system for creating a ceiling plan. Conventional methods of creating a ceiling plan are time-consuming and high-cost. Our system requires only two inputs from a user and outputs the panoramic ceiling image that shows the whole ceiling surface. The system detects the ceiling fixtures and depicts them seamlessly for a reliable resulting image. We confirmed the possibility of assisting in creating a ceiling plan with our system through the experiment.

DOI： 10.1145/3643832.3661847

Balancing Excitement and Environmental Conservation in Information Dissemination for Safari Game Drives

Shimura, K; Katayama, S; Urano, K; Leleito, E; Yonezawa, T; Kawaguchi, N

DISTRIBUTED, AMBIENT AND PERVASIVE INTERACTIONS, PT I, DAPI 2024 14718 巻頁： 311 - 323 2024年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In the context of Kenyan Safari Game Drives, which traditionally rely on visual scouting and intermittent communication, challenges arise regarding the effectiveness of animal detection and environmental conservation. Consequently, animals experience stress, and tourists encounter difficulties in observation due to obstruction by other visitors. Addressing these challenges involves maintaining animal welfare while enhancing tourist satisfaction. To revitalize post-pandemic tourism and enrich safari experiences, this study proposes a wildlife spotting and sharing system. The proposed method integrates wildlife detection and sharing technologies guided by three core principles: preserving encounter serendipity, regulating information access, and promoting environmental conservation. The system architecture incorporates sensors, GPS, and tablet terminals to facilitate real-time data collection, animal identification, and information dissemination. This approach aims to foster an engaging, efficient, and environmentally conscious wildlife spotting and sharing experience, potentially establishing a model for sustainable wildlife tourism in comparable wildlife-rich regions.

DOI： 10.1007/978-3-031-59988-0_19

Enhancing Group Telepresence Interaction through Seamless Inverse Panorama Projection on Spherical Display

Hayashida, N; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 286 - 289 2024年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：UbiComp Companion 2024 - Companion of the 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing

In recent years, advancements in telepresence technology have made remote communication and collaboration easier. MetaPo is a system that uses spherical displays to seamlessly integrate physical and digital interactions. However, conventional inverse panorama techniques face challenges such as image seams, coverage issues, and overlapping displays. To address these challenges, this study proposes an inverse panorama technique based on coordinate transformation, enhancing visual continuity and user experience. Additionally, evaluation methods necessary to demonstrate the effectiveness of the proposed method in improving the quality of remote communication have been devised. This research provides a novel solution to challenges in spherical display technology and paves the way for more immersive telepresence experiences.

DOI： 10.1145/3675094.3678369

Demonstration:Remote 3D Scanning with VR and Robotic Arm

Usami, R; Watanabe, K; Gushi, Y; Tsutsui, S; Watanabe, Y; Kano, K; Aikawa, Y; Shimura, K; Hayashida, N; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 201 - 204 2024年

Although VR headsets have gained widespread acceptance, their potential for real-world actuation remains underexplored. We propose a system that allows to work in VR space using a robotic arm and VR headset, focusing on 3D scanning as the task. The robotic arm is equipped with an RGB-D camera to achieve remote 3D scanning. This system enables immersive remote work and enhances the link between real space and VR space by reproducing the real objects into the VR space.

DOI： 10.1145/3675094.3677548

Composite Image Generation Using Labeled Segments for Pattern-Rich Dataset without Unannotated Target Open Access

Kano, K; Mori, Y; Higashiura, K; Hossain, T; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 507 - 512 2024年

Although object detection technology using cameras offers potential for various applications, it incurs dataset creation costs to train new models where general-purpose models are ineffective, such as in industrial settings. We have previously developed a semi-automated annotation framework that employs optical flow and representation learning techniques to reduce human effort significantly. However, it was likely to cause unintended annotation omissions and mistakes compared to manual annotation. In this study, we propose a composite image generation approach to create omission-free and pattern-rich datasets. The proposed method synthesizes natural-looking images without unannotated targets by placing labeled foreground segments at their original positions on targetless background frames collected with the same fixed-point cameras. Evaluation with video footage in a logistics warehouse confirmed that improved dataset reliability led to higher model performance.

DOI： 10.1145/3675094.3678447

Open Access

OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city Analysis of Area Usage Patterns.

Naoki Tamura, Kazuyuki Shoji, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

CoRR abs/2407.19872 巻 2024年

深層学習PDRとBLEビーコンを用いたハイブリッド測位

加納一馬，東浦圭亮，瀧上昂希，山口公平，永田吉輝，片山晋，浦野健太，米澤拓郎，河口信夫

HCGシンポジウム 2023 2023年12月

Digitization and Analysis Framework for Warehouse Truck Berth 査読有り

Yokoyama, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

2023 FOURTEENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK, ICMU 2023年12月

Panoramic Ceiling Image Synthesis Method Prioritizing Fixture Outlines using an Omnidirectional Camera 査読有り

Kohama D., Nagata Y., Yasutake K., Urano K., Katayama S., Yonezawa T., Kawaguchi N.

2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023 2023年12月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023

The manual creation of a ceiling plan consumes many human resources to confirm the current state of existing buildings for the renovation. Especially the positions and the types of existing fixtures are important. In this paper, we propose a synthesis method for a panoramic ceiling image using a video shot by an omnidirectional camera. We utilize a Visual SLAM method to map the positions of omnidirectional video frames including the ceiling. We prioritize the clear depiction of fixture outlines for easier identification of the types of ceiling fixtures. To draw clear fixture outlines in the resulting image, each fixture is referred from the single video frame that captures it most clearly. In the experiment, we collected an omnidirectional video in the indoor area of approximately 273 square meters with multiple rooms. We evaluated the synthesized image for positional accuracy of the ceiling fixtures, and our proposed method demonstrated higher accuracy compared to the baseline.

DOI： 10.23919/ICMU58504.2023.10412256

Digitization and Analysis Framework for Warehouse Truck Berth

Yokoyama K., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023 2023年12月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：2023 14th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2023

In distribution warehouses, various forms of data transformation are underway, such as the conversion of data related to receiving and inventory management. Distribution warehouses have designated areas known as truck berths, where trucks are parked for loading/unloading. While data collection is expected to enhance work efficiency at these truck berths, there is no data regarding the status of work in progress in the unloading space, and no system is in place to analyze the work. Consequently, it is unclear which tasks are problematic and how to enhance efficiency. To address this issue, this paper proposes a framework for analyzing the loading/unloading situation at truck berths with the objective of enhancing berth utilization efficiency and work efficiency. Specifically, we employed a fixed camera for object detection through instance segmentation. This approach enables us to understand the situation of trucks, unloading spaces, and workers. The training data were annotated using a large amount of real-world data, allowing for the measurement and analysis of the efficiency of loading/unloading operations. By calculating the amount of cargo based on the floor space, we assessed the efficiency of unloading operations per truck. Through the analysis of both efficient and inefficient operations, insights for enhancing work efficiency were provided.

DOI： 10.23919/ICMU58504.2023.10412228

360 Robot Hand Interaction for Group Telepresence with MetaPo

Human Mobility Prediction Challenge: Next Location Prediction using Spatiotemporal BERT 招待有り査読有り

Haru Terashima, Naoki Tamura, Kazuyuki Shoji, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

ACM SIGSPATIAL 2023 Workshop HuMob 2023 2023年11月

Watanabe Y., Hayashida N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series 頁： 183 - 185 2023年11月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：ACM International Conference Proceeding Series

In this demonstration paper, we present the RHS360, a 360-degree robotic hand system designed to facilitate communication across spatial domains. The RHS360 is capable of providing continuous alignment between the user's position in the cyber space and the robotic hand's position. Furthermore, it allows users in the cyber space to reposition the robotic hand to accommodate their movements within the space. Our system not only enables communication, including gestures, through the use of the robotic hand but also provides essential social cues that are crucial in effective communication.

DOI： 10.1145/3627050.3630730

Wildlife Spotting and Sharing System for Kenyan Safari Game Drives

Shimura K., Katayama S., Urano K., Leleito E., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series 頁： 150 - 153 2023年11月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：ACM International Conference Proceeding Series

Traditional wildlife spotting on Kenyan Safari Game Drives, rooted in visual scouting and sporadic communication, encounters challenges in animal detection efficiency and environmental preservation. In light of rejuvenating post-pandemic tourism and enhancing safari experiences, this study proposes a wildlife spotting and sharing system. The methodology melds wildlife detection and sharing technologies, anchored by three core principles: preserving chance of encounters, regulating information accessibility, and endorsing environmental conservation. The system architecture employs sensors, GPS, and tablet terminals for real-Time data acquisition, animal identification, and information propagation. This approach aims to nurture an engaging, efficient, and eco-conscious wildlife spotting and sharing experience, potentially setting a benchmark for sustainable wildlife tourism in similar wildlife-rich regions.

DOI： 10.1145/3627050.3630727

360 Robot Hand System for Omni-directional Interaction by Multiple Users

Watanabe Y., Hayashida N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series 頁： 295 - 299 2023年11月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：ACM International Conference Proceeding Series

The rise of diverse digital environments like digital twins and the metaverse emphasizes the importance of telepresence methods for linking users across different spaces. These methods aim to boost communication and services between these spaces. This paper introduces RHS360, a 360-degree robot hand system designed for inter-spatial communication. RHS360 ensures the robot hand aligns precisely with the user in cyberspace, adjusting based on the user's movements in the virtual realm. This enables the robot hand not only to aid communication and gestures but also to convey crucial social cues, enhancing the overall communication experience. Additionally, a user survey was conducted, revealing that observing the robot hand's movements significantly improved understanding their partner's thoughts and fostered a greater sense of intimacy. These findings suggest that the proposed method enhances communication between different spaces.

DOI： 10.1145/3627050.3631573

Mobility Link XR: Interspace Interaction System in Electric Wheelchair

Gait-Robust Heading Estimation Using Horizontal Acceleration for Smartphone-based PDR 査読有り

Kazuma Kano, Takuto Yoshida, Shin Katayama, Kenta Urano, Takuro Yonezawa, and Nobuo Kawaguchi

Proceedings of the Work-in-Progress Papers at the 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN-WiP 2023) 2023年9月

天伏図作成補助システムにおける全方位カメラを用いた天井設備の多視点画像抽出手法

小濱大輝, 永田吉輝, 安武和成, 浦野健太, 片山晋, 米澤拓郎, 河口信夫

2023年(第41回)電気設備学会全国大会 2023年8月

駅ホームの人流センサおよび改札通過情報による電車乗降情報の分析

浦野健太，米澤拓郎，河口信夫

第51回可視化情報シンポジウム 2023年8月

LiDARの視野を考慮した能動的な人流計測手法の検討

下里浩昇，片山晋，浦野健太，米澤拓郎，河口信夫

第51回可視化情報シンポジウム 2023年8月

Hayashida N., Shimosato H., Urano K., Yonezawa T., Kawaguchi N.

Communications in Computer and Information Science 1833 CCIS 巻頁： 314 - 320 2023年7月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Communications in Computer and Information Science

This research proposes a communication system called Mobility Link XR that connects physical space and cyberspace with mobility. Mobility Link XR is a system that enables remote users to view panoramic video from a 360-degree camera attached to a mobility vehicle in different space by wearing a VR device, and mobility users to view the remote user as an avatar by wearing an MR device. In this way, sharing space in three dimensions using XR enables a higher level of human communication. In this paper, we apply Mobility Link XR to an electric wheelchair and design two types of scenarios: an assistance mode that reproduces the positional relationship of communication in a conventional wheelchair, and a passenger mode that reproduces the positional relationship inside a vehicle, which is said to be a suitable distance for conversation. We also evaluated the reproducibility of communication in the wheelchair and the effectiveness of communication using the avatar. The results showed that the reproducibility of voice and emotion was highly evaluated and that the side-by-side positional relationship enabled higher quality communication as the avatar was more easily seen and felt present.

DOI： 10.1007/978-3-031-35992-7_43

Understanding Regional Characteristics Through EC Data Analysis 査読有り

Yamaguchi K., Shoji K., Tamura N., Sakakura N., Matsukura Y., Hiranaga Y., Shimomura K., Urano K., Yonezawa T., Kawaguchi N.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14036 LNCS 巻頁： 390 - 404 2023年7月

Open-Domain Dialogue Management Framework Across Multiple Device for Long-Term Interaction 査読有り

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14013 LNCS 巻頁： 354 - 365 2023年7月

点群データと基盤地図情報を用いた屋外自律移動ロボット向け地図の生成手法査読有り Open Access

相川雄也, 浦野健太, 片山晋, 米澤拓郎, 河口信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム 2023年7月

インスタンスセグメンテーションを用いたトラックバース状況の分析査読有り Open Access

横山皓大, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム 2023年7月

全方位カメラによる設備外形を考慮した天井パノラマ画像合成手法査読有り Open Access

小濱大輝, 永田吉輝, 安武和成, 浦野健太, 片山晋, 米澤拓郎, 河口信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム 2023年7月

天井設置型の複数マイクと話者の位置情報を用いた発話方向推定手法査読有り Open Access

市川直人, 戸出悠太 , 片山晋, 浦野健太, 米澤拓郎, 河口信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム 2023年7月

複数ユーザによる全方位インタラクションを可能にする360ロボットハンドシステム査読有り Open Access

渡辺圭貴，林田望海，片山晋，浦野健太，米澤拓郎，河口信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム 2023年7月

通過情報を活用した移動経路分析・応用手法の評価と応用

永田吉輝, 浦野健太, 米澤拓郎, 河口信夫

第78回UBI研究会 2023年5月

滞在ビッグデータに基づくエリア分散表現の加法構成性の分析と活用

田村直樹, 浦野健太, 米澤拓郎, 河口信夫

第107回MBL研究会 2023年5月

移動ビッグデータを用いた公共空間の価値評価手法

坂倉波輝, 米澤拓郎, 田村直樹, 永田吉輝, 庄子和之, 山口公平, 浦野健太, 河口信夫

第107回MBL研究会 2023年5月

IRIS: Interpretable Rubric-Informed Segmentation for Action Quality Assessment Open Access

Matsuyama H., Kawaguchi N., Lim B.Y.

International Conference on Intelligent User Interfaces, Proceedings IUI 頁： 368 - 378 2023年3月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：International Conference on Intelligent User Interfaces, Proceedings IUI

AI-driven Action Quality Assessment (AQA) of sports videos can mimic Olympic judges to help score performances as a second opinion or for training. However, these AI methods are uninterpretable and do not justify their scores, which is important for algorithmic accountability. Indeed, to account for their decisions, instead of scoring subjectively, sports judges use a consistent set of criteria - rubric - on multiple actions in each performance sequence. Therefore, we propose IRIS to perform Interpretable Rubric-Informed Segmentation on action sequences for AQA. We investigated IRIS for scoring videos of figure skating performance. IRIS predicts (1) action segments, (2) technical element score differences of each segment relative to base scores, (3) multiple program component scores, and (4) the summed final score. In a modeling study, we found that IRIS performs better than non-interpretable, state-of-the-art models. In a formative user study, practicing figure skaters agreed with the rubric-informed explanations, found them useful, and trusted AI judgments more. This work highlights the importance of using judgment rubrics to account for AI decisions.

DOI： 10.1145/3581641.3584048

CrowdFlowTransformer: Capturing Spatio-Temporal Dependence for Forecasting Human Mobility 査読有り

Choya T., Tamura N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023 頁： 496 - 501 2023年3月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023

Crowd flow forecasting is expected to have a wide range of applications such as human resource allocation, guidance design, marketing, disaster mitigation and congestion prediction for avoiding epidemic such as COVID-19. Crowd flow forecasting is challenging because it requires considering both the task of capturing the temporal dependency of data and capturing the spatial dependence. To address these challenges, in this paper, we propose a mechanism for referencing time-series features that are important for forecasting and incorporating graph convolution into Transformer, and we introduce CrowdFlowTransformer(CF-Transformer), a deep learning model based on Google's Transformer framework captures the Spatio-temporal dependency of time series. CF-Transformer captures the time series dependency by extracting important local time series from the past time series, inputting them to the decoder of Transformer, and encoding critical features into the model's input. We adapted CF-Transformer to a real-world crowd flow dataset. We evaluated it by comparing its forecasting accuracy with conventional models, and the results demonstrate that our model outperforms the conventional models.

DOI： 10.1109/PerComWorkshops56833.2023.10150301

Coordinated autonomous networks for remote synchronized video services with the autonomous mobility robots - prelude implementation 査読有り

異種空間間のコミュニケーションを実現するロボット型メタポータルMetaPoにおけるロボットハンド・インタラクション Open Access

渡辺圭貴, 林田望海, 浦野健太, 米澤拓郎, 河口信夫

インタラクション2023 2023年3月

自律ネットワークにつながる自律移動ロボットを用いる映像サービス実現に向けた初期プロトタイプの開発

髙橋美乃里, 山本秀樹, 岩下将人, 金田悠作, Leon Wong, 浦野健太, 米澤拓郎, 河口信夫

電子情報通信学会　総合大会 2023年3月

Yamamoto, HH; Iwashita, M; Kondo, N; Wong, L; Kaneta, Y; Urano, K; Yonezawa, T; Kawaguchi, N

2023 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION, ICAIIC 頁： 598 - 601 2023年2月

A Survey of Ground Truth Measurement Systems for Indoor Positioning 査読有り

Yoshida T., Kaji K., Ogiso S., Ichikari R., Uchiyama H., Kurata T., Kawaguchi N.

Journal of Information Processing 31 巻 ( 0 ) 頁： 15 - 20 2023年1月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Journal of Information Processing

Various types of indoor positioning methods have been proposed. Accordingly, various ground-truth measurement methods have also been used. The selection of the ground-truth measurement method is crucial when appropriately evaluating the indoor positioning methods. In recent years, data-driven methods have been actively proposed, making the ground-truth measurement even more critical. Most existing survey papers only focus on classifying indoor positioning methods and datasets for evaluation. Our survey paper investigates the methods to measure the ground truth. First, we list the primary examples of ground truth measurement systems and summarize their characteristics, such as the scale, accuracy, and frequency when collecting ground truth. Then, we classify them into the following five categories: OMC, ToF/MFPS, SLAM, Manual, and Others. Their advantages and disadvantages are also discussed based on four indices: accuracy, coverage, device cost, and labor cost. Finally, we discuss the appropriate way to select the ground-truth measurement system for quantitative evaluation. Our survey will be the guideline for selecting an appropriate ground-truth measurement system for indoor positioning and indoor navigation.

DOI： 10.2197/ipsjjip.31.15

XR Communication System for Remote Control Wheelchairs 査読有り

Hironori Shimosato, Nozomi Hayashida, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

IoT '22: Proceedings of the 12th International Conference on the Internet of Things 頁： 219 - 223 2022年11月

テキスト対話システムにおける感情制御を伴う応答生成手法

片山晋, 米澤拓郎, 河口信夫

知能と情報 34 巻 ( 3 ) 頁： 568 - 578 2022年8月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：日本知能情報ファジィ学会

感情を扱う対話システムはユーザの満足度向上や肯定的なインタラクション増加の効果が認められており，人間に寄り添うデジタルパートナーとしての役割が期待されている．対話システムがユーザの感情を認識し，対話システム自身の感情を表現するためには，対話の文脈から適切な感情を選択する感情制御が不可欠である．本研究では，応答時の適切な感情を推定する感情制御を伴うテキスト応答生成フレームワークを提案する．提案手法はユーザの発話テキストにおける意味的文脈と感情的文脈を考慮することで応答時の適切な感情を推定し，感情表現を含んだ応答テキストをニューラルネットワークを用いて生成する．実験では，対話生成の品質に対する評価指標を用いた自動評価と，クラウドソーシングサイトを用いて集めた100人の被験者による人手評価を行い，提案手法の有効性を示した．

DOI： 10.3156/jsoft.34.3_568

法令間の関係を利用したモビリティ関連法令検索に関する一考察

駒水孝裕, 外山勝彦, 河口信夫, 佐野智也

人工知能学会第二種研究会資料 2022 巻 ( SWO-057 ) 頁： 04 2022年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：一般社団法人人工知能学会

本稿では，法令間の関係を用いた法令検索について述べる．特に，モビリティに関連する法令を対象として，その検索方法および検索結果を示す．法令データのオープンデータ化は徐々に進みつつある．これまでに，法令オープンデータのハブとなる法令の Linked Open Data (LOD) としてのデータ化をはじめに，種々の法令文書，国会での会議録や議案に関するデータのオープン化が進められてきた．一方で，その応用については十分に研究されていない．本稿では，モビリティを題材に，関連する法令を検索する方法について示す．具体的には，法令に関する LOD から法令間の関係を抽出し，グラフにおける検索技術であるPersonalized PageRank を用いて，関連法令を検索する．この検索を通して，現状の法令オープンデータの限界を明らかにするとともに，今後の展開について議論する．

DOI： 10.11517/jsaisigtwo.2022.swo-057_04

MetaPo: A Robotic Meta Portal for Interspace Communication 査読有り

Yonezawa T., Hayashida N., Przybilla J., Kyono Y., Urano K., Kawaguchi N.

Proceedings - SIGGRAPH 2022 Posters 2022年7月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Proceedings - SIGGRAPH 2022 Posters

We introduce MetaPo, a mobile robot with spheric display, 360° media I/O and robotic hands for creating a unified model of interspace communication. MetaPo works as a portal between pairs of physical-physical, cyber-cyber and cyber-physical spaces to provide 1) panoramic communication for multiple remote users, and 2) immersive interspace migration with mobility functionality. The paper overviews our concept and first prototype of MetaPo with its hardware and software implementation.

DOI： 10.1145/3532719.3543255

Smartphone Localization with Solar-Powered BLE Beacons in Warehouse 査読有り

Kano Kazuma, Yoshida Takuto, Hayashida Nozomi, Asai Yusuke, Matsuyama Hitoshi, Katayama Shin, Urano Kenta, Yonezawa Takuro, Kawaguchi Nobuo

DISTRIBUTED, AMBIENT AND PERVASIVE INTERACTIONS, SMART ENVIRONMENTS, ECOSYSTEMS, AND CITIES 13325 巻頁： 291 - 310 2022年6月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Workloads in logistics warehouses have been increasing to meet growing demand, and a labor shortage has become a problem. Utilizing information of laborer locations leads to an increase in productivity. We propose an integrated positioning method using solar-powered Bluetooth Low Energy (BLE) beacons. They are easy to install and maintenance-free since they can work without power sources. However, their advertisement interval depends on illuminance and is unstable. Moreover, there are many obstructions in warehouses, such as shelves and products, which cause signal attenuation, interference, and packet losses. We apply particle filters, map matching, and speed prediction with a neural network model to improve robustness and accuracy. We installed 94 beacons in a logistics warehouse. We evaluated the accuracy and found that our method is more accurate than a baseline method.

DOI： 10.1007/978-3-031-05463-1_21

Time-Sensitive Cooperative Perception for Real-Time Data Sharing over Vehicular Communications: Overview, Challenges, and Future Directions 招待有り査読有り国際共著

Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi, Peter Steenkiste, Ragunathan Raj Rajkumar

IEEE Internet of Things Magazine 2022年6月

大規模屋外施設におけるWi-Fiパケットセンサへの影響と利活用の検証査読有り Open Access

村井大地, 浦野健太, 望月祐洋, 米澤拓郎, 西田純二, 河口信夫

情報処理学会デジタルプラクティス 3 巻 ( 2 ) 頁： 12 - 21 2022年4月

機械学習による慣性センサを用いた転倒動作検知に関する研究

東浦圭亮，吉田拓人，加納一馬，瀧上昂希，山口公平，浦野健太，青木俊介，米澤拓郎，河口信夫

社会システムと情報技術研究ウィーク (WSSIT2022) 2022年3月

RobotNEST: Toward a Viable Testbed for IoT-Enabled Environments and Connected and Autonomous Robots 査読有り

Aoki Shunsuke, Yonezawa Takuro, Kawaguchi Nobuo

IEEE SENSORS LETTERS 6 巻 ( 2 ) 2022年1月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE Sensors Letters

Autonomous mobile robots (AMRs), including delivery robots, security robots, and automated wheelchairs, are very promising for improving the quality of life, safety, mobility, and productivity. To deploy such sensor-rich AMRs in real-world society, we have to resolve not only technical challenges but also ethical and societal issues. In addition, since multiple companies are developing different types of AMRs individually, we have to design and develop practical platform to enable safe cooperation and collaboration before using them in the society. Hence, in this letter, we present a viable Nagoya Experimental Site and Testbed named <italic>RobotNEST</italic> developed at Nagoya City, Japan, where we leverage vehicular communications and edge/cloud computing technologies to develop cooperative mobile robots. RobotNEST provides real-world AMRs, experimental fields, learning kits, and infrastructural sensors and communications, including 5G private networks. We also introduce multiple developed applications at RobotNEST that enable safe cooperation for autonomous robots. Finally, we discuss the scalability and limitations of the testbed and conclude with future research directions.

DOI： 10.1109/LSENS.2021.3139624

Synthetic People Flow: Privacy-Preserving Mobility Modeling from Large-Scale Location Data in Urban Areas 査読有り

Tamura N., Urano K., Aoki S., Yonezawa T., Kawaguchi N.

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST 419 LNICST 巻頁： 553 - 567 2022年

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Recently, there has been an increasing demand for traffic simulation and congestion prediction for urban planning, especially for infection simulation due to the Covid-19 epidemic. On the other hand, the widespread use of wearable devices has made it possible to collect a large amount of user location history with high accuracy, and it is expected that this data will be used for simulation. However, it is difficult to collect location histories for the entire population of a city, and detailed data that can reproduce trajectories is expensive. In addition, such personal location histories contain private information such as addresses and workplaces, which restricts the use of raw data. This paper proposes Agent2Vec, a mobility modeling model based on unsupervised learning. Using this method, we generate synthetic human flow data without personal information.

DOI： 10.1007/978-3-030-94822-1_36

A Data-Driven Approach for Online Pre-impact Fall Detection with Wearable Devices 査読有り

Yoshida Takuto, Kano Kazuma, Higashiura Keisuke, Yamaguchi Kohei, Takigami Koki, Urano Kenta, Aoki Shunsuke, Yonezawa Takuro, Kawaguchi Nobuo

SENSOR- AND VIDEO-BASED ACTIVITY AND BEHAVIOR COMPUTING, ABC 2021 291 巻頁： 133 - 147 2022年

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Smart Innovation, Systems and Technologies

The implementation of wearable airbags to prevent fall injuries depends on accurate pre-impact fall detection and a clear distinction between activities of daily living (ADL) and them. We propose a novel pre-impact fall detection algorithm that is robust against ambiguous falling activities. We present a data-driven approach to estimate the fall risk from acceleration and angular velocity features and use thresholding techniques to robustly detect a fall before impact. In the experiment, we collect simulated fall data from subjects wearing an inertial sensor on their waist. As a result, we succeeded in significantly improving the accuracy of fall detection from 50.00 to 96.88%, the recall from 18.75 to 93.75%, and the specificity 81.25 to 100.00% over the baseline method.

DOI： 10.1007/978-981-19-0361-8_8

How to monitor multiple autonomous vehicles remotely with few observers: An active management method

大規模移動履歴に基づく滞在推定結果を用いた公園の滞在特徴の分類手法 Open Access

河口信夫

情報処理学会第104回MBL研究会 2022-MBL-104 巻頁： 1 - 6 2022年

物流倉庫における人・配送ロボット協調のためのセンサ統合システム Open Access

河口信夫

情報処理学会研究報告 (MBL) 2022-MBL-104 巻頁： 1 - 8 2022年

3次元LiDARを搭載した自律走行ロボットを用いたWi-Fi電波強度および通信速度測定システム

盛下泰暉, 浅井悠佑, 浦野健太, 米澤拓郎, 河口信夫

情報処理学会研究報告 2021-MBL-101 巻 ( 34 ) 頁： 1 - 6 2021年12月

スマートメータを利用した行動認識のための電気使用量クラスタリングに関する検討

深谷暢也，浦野健太，青木俊介, 米澤拓郎, 河口信夫

令和3年度電気・電子・情報関係学会東海支部連合 2021年9月

Ding M., Takeuchi E., Ishiguro Y., Ninomiya Y., Kawaguchi N., Takeda K.

IEEE Intelligent Vehicles Symposium, Proceedings 2021-July 巻頁： 1168 - 1173 2021年7月

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE Intelligent Vehicles Symposium, Proceedings

In this research, we proposed an active management method to tele-monitor and tele-operate more autonomous vehicles (AVs) with few observers by adjusting the movement of the AVs actively. A management system is created to get the status from the AVs and separate the monitoring requirement to the observers optimally. When the requirements might be intensive, the management system can also adjust the movements of the AVs actively to distribute the monitoring time, which can make the observers monitor more vehicles. We implement and verify the management system in an autonomous driving simulator - CARLA for the limited number of AVs and observers. Based on the data acquired from the driving simulator, we also create a numerical simulator and tested our method with the pairs of a large number of AVs and observers. The result of both simulators shows that our method can reduce the utilization degree of observers and make them monitor more AVs.

DOI： 10.1109/IV48863.2021.9575997