2024/04/03 更新

写真a

ウラノ ケンタ
浦野 健太
URANO Kenta
所属
大学院工学研究科 情報・通信工学専攻 情報通信 助教
大学院担当
大学院工学研究科
学部担当
工学部 電気電子情報工学科
職名
助教

学位 1

  1. 博士(工学) ( 2021年2月   名古屋大学 ) 

研究分野 2

  1. 情報通信 / ヒューマンインタフェース、インタラクション

  2. 情報通信 / 計算機システム  / サイバーフィジカルシステム

現在の研究課題とSDGs 3

  1. 生体信号の可視化

  2. BLE通信を利用した屋内位置推定

  3. 現実空間のスキャニングと経年変化監視

 

論文 36

  1. 配布型BLEタグを用いた屋内位置推定手法 査読有り

    浦野 健太

        2021年2月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:学位論文(博士)  

  2. An End-to-End BLE Indoor Localization Method Using LSTM 査読有り

    Urano Kenta, Hiroi Kei, Yonezawa Takuro, Kawaguchi Nobuo

    Journal of Information Processing   29 巻 ( 0 ) 頁: 58 - 69   2021年1月

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    担当区分:筆頭著者   記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:一般社団法人 情報処理学会  

    <p>This paper proposes an indoor localization method for Bluetooth Low Energy (BLE) devices using an end-to-end LSTM neural network. We focus on a large-scale indoor space where there is a tough environment for wireless indoor localization due to signal instability. Our proposed method adopts end-to-end localization, which means input is a time-series of signal strength and output is the estimated location at the latest time in the input. The neural network in our proposed method consists of fully-connected and LSTM layers. We use a custom-made loss function with 3 error components: MSE, the direction of travel, and the leap of the estimated location. Considering the difficulty of data collection in a short preparation term, the data generated by a simple signal simulation is used in the training phase, before training with a small amount of real data. As a result, the estimation accuracy achieves an average of 1.92m, using the data collected in GEXPO exhibition in Miraikan, Tokyo. This paper also evaluates the estimation accuracy assuming the troubles in a real operation.</p>

    DOI: 10.2197/ipsjjip.29.58

    Scopus

    CiNii Research

  3. ドキドキをセンシングして可視化するLEDライティングデバイス

    浦野 健太, 廣井 慧, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2020シンポジウム     頁: 1616 - 1622   2020年6月

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    担当区分:筆頭著者, 責任著者   記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  4. Human Mobility Prediction Challenge: Next Location Prediction using Spatiotemporal BERT

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

    HuMob 2023 - 1st ACM SIGSPATIAL International Workshop on the Human Mobility Prediction Challenge     頁: 1 - 6   2023年11月

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    出版者・発行元:HuMob 2023 - 1st ACM SIGSPATIAL International Workshop on the Human Mobility Prediction Challenge  

    Understanding, modeling, and predicting human mobility patterns in urban areas has become a crucial task from the perspectives of traffic modeling, disaster risk management, urban planning, and more. HuMob Challenge 2023 aims to predict future movement trajectories based on the past movement trajectories of 100,000 users[1]. Our team, "uclab2023", considered that model design significantly impacts training and prediction times in the task of human mobility trajectory prediction. To address this, we proposed a model based on BERT, commonly used in natural language processing, which allows parallel predictions, thus reducing both training and prediction times.In this challenge, Task 1 involves predicting the 15-day daily mobility trajectories of target users using the movement trajectories of 100,000 users. Task 2 focuses on predicting the 15-day emergency mobility trajectories of target users with data from 25,000 users. Our team achieved accuracy scores of GEOBLEU: 0.3440 and DTW: 29.9633 for Task 1 and GEOBLEU: 0.2239 and DTW: 44.7742 for Task 2[2][3].

    DOI: 10.1145/3615894.3628498

    Scopus

  5. 11th International Workshop on Human Activity Sensing Corpus and Applications (HASCA)

    Murao K., Enokibori Y., Gjoreski H., Lago P., Okita T., Siirtola P., Hiroi K., Scholl P.M., Ciliberto M., Urano K.

    UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing     頁: 773 - 776   2023年10月

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    出版者・発行元:UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing  

    The recognition of complex and subtle human behaviors from wearable sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g., dementia care). This will require a large-scale human activity corpus and much-improved methods to recognize activities and the context in which they occur. This workshop deals with the challenges of designing reproducible experimental setups, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world. We wish to reflect on future methods, such as lifelong learning approaches that allow open-ended activity recognition. This year HASCA will welcome papers from participants to the Fifth Sussex-Huawei Locomotion and Transportation Recognition Challenge in a special session.

    DOI: 10.1145/3594739.3605106

    Scopus

  6. Co-ordinated autonomous networks for remote synchronized video services with the autonomous mobility robots - prelude implementation 査読有り

    Hideki Yamamoto, Masato Iwashita, Norio Kondo, Leon Wong, Yusaku Kaneta, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

    International Conference on Artificial Inteligence in Incformation and Communication     2023年2月

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    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)  

    DOI: https://doi.org/10.1109/ICAIIC57133.2023.10067079

  7. 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

    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     2023年1月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)  

  8. Understanding Regional Characteristics Through EC Data Analysis

    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

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    The COVID-19 pandemic, which began in 2020, has changed people’s lives, and people are shopping more online. While the analysis of online shopping is becoming increasingly important, regional differences in consumption trends exist. This study proposes a data-driven regional modeling method based on EC purchase data to examine the regional characteristics of online shopping purchase trends. Using the proposed method, we quantified and visualized the degree of similarity of consumption trends among regions and the degree of dispersion of consumption trends within regions using approximately 300,000 lines of online shopping history for 3 years in Japan. As a result, we found that there was some disruption in the early stages of e-commerce for food products by region, while there was little difference in consumption trends among regions for daily necessities. In addition, for consumer durables and clothing, regional differences in consumption trends were confirmed in terms of the number of cars owned per capita, urbanization status, and other regional characteristics.

    DOI: 10.1007/978-3-031-34668-2_26

    Scopus

  9. Digitization and Analysis Framework for Warehouse Truck Berth

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

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

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  10. Mobility Link XR: Interspace Interaction System in Electric Wheelchair

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

    Communications in Computer and Information Science   1833 CCIS 巻   頁: 314 - 320   2023年

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    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

    Scopus

  11. Open-Domain Dialogue Management Framework Across Multiple Device for Long-Term Interaction

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

    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

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    This study explores the feasibility of dialogue systems with individuality capable of providing continuous and lasting assistance via a multiple device dialogue system. A framework has been devised to manage dialogue history, allowing for the use of a singular identity across various interfaces, including chatbots and virtual avatars. This framework can summarize and save the dialogue history, which can be utilized to generate responses. The impact of dialogue history sharing on users’ interactions with a particular character across various devices was assessed for naturalness, continuity, and reliability. The results indicate that dialogue history sharing can foster more natural and continuous conversations, thereby enhancing the potential for long-term support. This research advances the proposition that a digital agent endowed with a consistent identity across multiple devices can provide personalized and sustained support to users.

    DOI: 10.1007/978-3-031-35602-5_25

    Scopus

  12. CrowdFlowTransformer: Capturing Spatio-Temporal Dependence for Forecasting Human Mobility

    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

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    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

    Scopus

  13. XR Communication System for Remote Control Wheelchairs 査読有り

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

    ACM International Conference Proceeding Series     頁: 219 - 223   2022年11月

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    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:ACM International Conference Proceeding Series  

    With the introduction of the IoT, communication is becoming more diverse. While IoT is becoming more and more widespread, there are some forms of human communication are being lost. The development of self-propelled robots has progressed, and electric and automated wheelchairs are also being utilized. A caregiver was originally required to operate a wheelchair. However, with the advent of IoT wheelchairs, wheelchairs can be operated by wheelchair users only, increasing convenience. On the other hand, wheelchairs have been used as a kind of communication between caregivers and wheelchair users, and the development of IoT wheelchairs has reduced the opportunities for communication between caregivers and wheelchair users. In this paper, we propose a method to reproduce communication scenarios in the following two scenarios using an IoT wheelchair and present the design and implementation of the prototype created.

    DOI: 10.1145/3567445.3571111

    Scopus

  14. 10th International Workshop on Human Activity Sensing Corpus and Applications (HASCA)

    Murao K., Enokibori Y., Gjoreski H., Lago P., Okita T., Siirtola P., Hiroi K., Scholl P.M., Ciliberto M., Urano K.

    UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers     頁: 321 - 323   2022年9月

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    出版者・発行元:UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers  

    The recognition of complex and subtle human behaviors from wearable sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g., dementia care). This will require large-scale human activity corpus and much improved methods to recognize activities and the context in which they occur. This workshop deals with the challenges of designing reproducible experimental setups, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world. We wish to reflect on future methods, such as lifelong learning approaches that allow open-ended activity recognition.

    DOI: 10.1145/3544793.3560377

    Scopus

  15. 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

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    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: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

    Scopus

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

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

    Distributed, Ambient and Pervasive Interactions. Smart Environments, Ecosystems, and Cities     2022年6月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)  

    DOI: https://doi.org/10.1007/978-3-031-05463-1_21

  17. 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

    人工知能学会「社会における AI」研究会 第43回研究会     2022年3月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  18. 深層学習を用いたIMU付きペンによる手書き文字認識

    挺屋 友幹, 永田 吉輝, 東浦 圭亮, 下里 浩昇, 山口 公平, 村井 大地, 深谷 暢也, 坂倉 波輝, 戸出 悠太, 浦野 健太, 米澤 拓郎, 河口 信夫

    人工知能学会研究会資料 知識ベースシステム研究会   125 巻 ( 0 ) 頁: 3   2022年3月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)   出版者・発行元:一般社団法人 人工知能学会  

    DOI: 10.11517/jsaikbs.125.0_03

    CiNii Research

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

    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1月

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    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: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

    Scopus

  20. Smartphone Localization with Solar-Powered BLE Beacons in Warehouse

    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, PT I   13325 巻   頁: 291 - 310   2022年

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    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

    Web of Science

    Scopus

  21. 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   101 巻 ( 34 ) 頁: 1 - 6   2021年12月

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  22. RGNet: Robust Gravity Estimation Neural Network for IMU-based Localization Using Smartphone 査読有り 国際誌

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

    13th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2021     頁: 1 - 8   2021年11月

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    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:13th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2021  

    With the rapid development of Micro Electro-Mechanical Systems (MEMS) technologies, indoor navigation and localization with Inertial Measurement Unit (IMU) has been increasingly feasible. IMU-based indoor localization is a low-cost, energy-efficient, and infrastructure-free approach. There are various methods for it, and most of them require gravity estimation (e.g. the projection of angular velocity, the extraction of horizontal acceleration). In particular, when you use a smartphone, it changes the orientation of its IMU frequently, therefore the gravity estimation needs to be more robust to sensor orientation and its noise. In this paper, we propose a gravity estimation method based on deep learning called RGNet (Robust Gravity Estimation Neural Network) that is robust to sensor orientation and noise. We train an LSTM (Long short-term memory)-based neural network that estimates gravity from acceleration and angular velocity. Furthermore, for the problem that it is difficult to prepare the ground truth of gravity directly, we propose a method to train the gravity estimation neural network indirectly using the heading, taking advantage of the fact that the heading can be estimated from the gravity and angular velocity. The evaluation results show that the accuracy of the proposed method outperformed the baseline gravity estimation method (Android API, Low-pass filter, and Extended Kalman filter). We also confirmed that the accuracy of IMU-based localization is affected by the difference in gravity estimation methods.

    DOI: 10.23919/ICMU50196.2021.9638853

    Scopus

  23. Estimating and Leveraging Latent Social Demand Based on IoT sensors: An Empirical Study in a Large Public Park 査読有り 国際誌

    Nagata Y., Murai D., Katayama S., Urano K., Aoki S., Yonezawa T., Kawaguchi N.

    13th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2021     頁: 1 - 8   2021年11月

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    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:13th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2021  

    The continuously changing conditions of cities are now technically understandable in the information space through real-world sensing methods and analytical methods such as big data analysis and machine learning. On the other hand, it is currently difficult to estimate and present what the people in the city need (latent demand). This paper aims to solve latent demand by developing Latent Demand Resolver (LD-Resolver), the new latent demand estimation and exchanging system. LD-Resolver has two components, Latent Demand Extractor (LD-Extractor) and Latent Demand Exchanger (LD-Exchanger). LD-Extractor extracts a latent demand from various social conditions using IoT sensors, Web, and SNS. LD-Exchanger has a new structure to exchange a latent demand with an appropriate service supply. Finally, we developed the LD-Resolver and conducted a demonstration experiment at the Higashiyama Zoo and Botanical Garden to verify the method. As a result of the two-week experiment, the proposed method can be effectively used in actual facility operations.

    DOI: 10.23919/ICMU50196.2021.9638789

    Scopus

  24. A data-driven approach for online pre-impact fall detection with wearable devices 査読有り

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

    The 3rd International Conference on Activity and Behavior Computing     2021年10月

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    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)  

  25. 9th International Workshop on Human Activity Sensing Corpus and Applications (HASCA) 査読有り 国際共著 国際誌

    Murao Kazuya, Enokibori Yu, Gjoreski Hristijan, Lago Paula, Okita Tsuyoshi, Siirtola Pekka, Hiroi Kei, Scholl Philipp M., Ciliberto Mathias, Urano Kenta

    UBICOMP/ISWC '21 ADJUNCT: PROCEEDINGS OF THE 2021 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2021 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS     頁: 281 - 284   2021年9月

     詳細を見る

    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/ISWC 2021 - Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers  

    The recognition of complex and subtle human behaviors from wearable sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g., dementia care). This will require large-scale human activity corpus and much improved methods to recognize activities and the context in which they occur. This workshop deals with the challenges of designing reproducible experimental setups, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world. We wish to reflect on future methods, such as lifelong learning approaches that allow open-ended activity recognition. This year HASCA will welcome papers from participants to the Fourth Sussex-Huawei Locomotion and Transportation Recognition Challenge and the Third Nursing Activity Recognition Challenge in special sessions.

    DOI: 10.1145/3460418.3479266

    Web of Science

    Scopus

  26. 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

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    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  27. 大規模公園環境におけるWiFiパケットセンサデータの利活用に関する分析と課題

    村井 大地, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  28. 自律移動ロボットのセンサ機器を用いた人流推定手法の提案

    下里 浩昇, 片山 晋, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  29. 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

    田村 直樹, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  30. 加速度の時空間情報を考慮した進行方向推定手法の検討

    吉田 拓人, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  31. Transformerモデルを用いた人流の時系列予測

    挺屋 友幹, 片山 晋, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  32. 赤外線グリッドセンサを用いた深層学習での人の位置推定手法の検討

    戸出 悠太, 片山 晋, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  33. 時空間ルーティングを用いた複数自律移動ロボットの協調走行

    福島 悠人, 浅井 悠佑, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  34. IoTに基づく潜在的社会需要の推定と柔軟なサービス需給交換基盤

    永田 吉輝, 村井 大地, 片山 晋, 浦野 健太, 青木 俊介, 米澤 拓郎, 河口 信夫

    マルチメディア、分散、協調とモバイル DICOMO2021シンポジウム     2021年7月

     詳細を見る

    記述言語:日本語   掲載種別:研究論文(研究会,シンポジウム資料等)  

  35. Off-line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences from IPIN 2020 Competition 査読有り 国際共著 国際誌

    Potorti F., Torres-Sospedra J., Quezada-Gaibor D., Jimenez A.R., Seco F., Perez-Navarro A., Ortiz M., Zhu N., Renaudin V., Ichikari R., Shimomura R., Ohta N., Nagae S., Kurata T., Wei D., Wei D., Wei D., Wei D., Ji X., Zhang W., Kram S., Stahlke M., Mutschler C., Crivello A., Barsocchi P., Girolami M., Palumbo F., Chen R., Wu Y., Li W., Yu Y., Xu S., Huang L., Liu T., Kuang J., Niu X., Yoshida T., Nagata Y., Fukushima Y., Fukatani N., Hayashida N., Asai Y., Urano K., Ge W., Lee N.T., Fang S.H., Jie Y.C., Young S.R., Chien Y.R., Yua C.C., Ma C., Wub B., Zhangc W., Wang Y., Fan Y., Poslad S., Selviah D.R., Wangd W., Yuan H., Yonamoto Y., Yamaguchi M., Kaichi T., Zhou B., Liue X., Gu Z., Yang C., Wu Z., Xie D., Huang C., Zheng L., Peng A., Jin G., Wangh Q., Luo H., Xiong H., Bao L., Zhangi P., Zhao F., Yuj C.A., Hung C.H., Antsfeld L., Chidlovskii B., Jiang H., Xia M., Yan D., Li Y., Dong Y., Silva I., Pendao C., Meneses F., Nicolau M.J., Costa A., Moreira A., De Cock C., Plets D., Opiela M., Dzama J., Zhang L., Li H., Chen B.

    IEEE Sensors Journal   22 巻 ( 6 ) 頁: 5011 - 5054   2021年5月

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    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  

    Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1m for the Smartphone Track and 0.5m for the Footmounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.

    DOI: 10.1109/JSEN.2021.3083149

    Scopus

  36. 社交ダンスの動作特性を考慮した マルチモーダルセンサによるダンスフィガー認識 査読有り

    松山 仁, 浦野 健太,廣井 慧, 梶 克彦, 米澤 拓郎, 河口 信夫

    情報処理学会論文誌   61 巻 ( 10 ) 頁: 1591 - 1604   2020年10月

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    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 情報処理学会  

    本研究では社交ダンスを対象とし,加速度・角速度,視覚のマルチモーダルセンサを用いたダンスフィガー分類手法を提案する.社交ダンスにおける基本技術であるフィガーは,その種類の多さや複雑さゆえ初心者や中級者にとって練習が困難である.フィガーの自動認識によりユーザは自身の踊りの客観的な把握が可能となるため,ダンスフィガーの学習支援が可能となると考えられる.一方で,社交ダンスは2人1組で多彩な動きを行うため,既存の行動認識手法をそのまま適用することは難しい.本稿では,社交ダンスの動作特性を考慮し,フィガーの複雑さや遮蔽などの課題を解決したダンスフィガー認識手法を実現した.本研究では一般的な行動認識手法をベースライン手法として実装したうえで,社交ダンスの姿勢や動作特性を考慮した特徴量を設計・利用した手法を提案・実現し,両者の評価を行った.結果,提案手法の認識精度はF値0.97となり,ベースライン手法を全体で0.06上回った.特にフィガー別の分類精度では,最大で0.6の精度向上を達成した.さらに提案手法が遮蔽物に対しても頑健さを有することを示した.

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講演・口頭発表等 2

  1. データサステナビリティのための実世界データ醸造基盤 招待有り

    浦野健太

    ICTイノベーションセミナー2022  2023年2月13日  総務省東海総合通信局

     詳細を見る

    開催年月日: 2023年2月

    記述言語:日本語   会議種別:公開講演,セミナー,チュートリアル,講習,講義等  

    開催地:ナゴヤイノベーターズガレージ  

  2. WiFiパケットセンサを用いた東山動植物園での人流分析・サービス提供と東山線への拡大

    浦野健太

    計測自動制御学会・スマートセンシングシステム部会  2022年9月10日  計測自動制御学会

     詳細を見る

    開催年月日: 2022年9月

    記述言語:日本語   会議種別:口頭発表(一般)  

    開催地:豊橋技術科学大学  

その他研究活動 1

  1. 丸太運搬作業の完全自動化に向けた荷役作業自動化技術の開発と自律走行技術の高度化

    2022年6月
    -
    現在

 

担当経験のある科目 (本学) 8

  1. 電気電子情報工学実験第2

    2023

  2. 電気電子情報工学実験第1

    2023

  3. 離散数学及び演習

    2022

  4. 電気電子情報工学実験第2

    2022

  5. 電気電子情報工学実験第1

    2022

  6. 離散数学及び演習

    2021

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    計算機科学の基礎数学として,離散数学の基礎概念・基礎知識を学び,演習を通じて身につけることを目的とする.

    集合論,整数論,代数系の基礎的な定義を理解し,種々の問題を解くことができる.

  7. 電気電子情報工学実験第1

    2021

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    電気電子情報工学に関する以下のテーマについて実験・レポートの作成を行う。
    実験を通して、線形回路論、電気回路論、電子回路工学、情報理論、電気磁気学、ディジタル回路に関する確かな知識を獲得するとともに、計画力、応用力、チームワーク能力が養成されることを目的とする。

    C3B8 ディジタル信号処理
    学生は、取り組んだテーマについて理解し、説明ができる。

  8. 電気電子情報工学実験第2

    2021

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    電気電子情報工学に関する以下のテーマのうち1つについて、実験の計画案、実行、検討、結果の報告発表を行う。それぞれの自主性・独創性を期待する。
    実験を通して、課題探求と問題解決の過程を体験し、そのテーマに関する確かな知識を獲得するとともに、計画力、応用力、チームワーク能力が養成されることを目的とする。

    学生は、取り組んだテーマについて理解し、説明ができる。
    EH15 「実社会データセンシング・分析・可視化」

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社会貢献活動 1

  1. 現実空間とVR空間をつなぐ新しい扉、ロボット型メタポータル「MetaPo」

    役割:出演, パネリスト

    名古屋市(事務局)経済局イノベーション推進部次世代産業振興課  Hatch Technology Fes.2022  2022年11月 - 2023年11月

メディア報道 1

  1. 本格派 ミニチュア信長像 新聞・雑誌

    中日新聞  中日新聞  13面  2023年11月

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    執筆者:本人以外 

学術貢献活動 1

  1. 電気・電子・情報関係学会東海支部連合大会

    役割:パネル司会・セッションチェア等

    電気・電子・情報関係学会東海支部  2022年8月

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    種別:学会・研究会等