Publication

338 entries « ‹ 1 of 7 › »

2022

Journal Articles

佐々木航, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 西山勇毅, 大越匡, 中澤仁, 森将輝, 水鳥寿思, 塩田琴美, 永野智久, 東海林祐子, 加藤貴昭

SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム Journal Article

In: 情報処理学会論文誌デジタルプラクティス（TDP）, 3 (1), pp. 19–33, 2022, ISSN: 2435-6484.

Abstract | BibTeX | タグ: behavior change, COVID-19, healthcare, mHealth | Links:

@article{sasaki2021_sfcgob,

title = {SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム},

author = {佐々木航 and 柿野優衣 and 中縁嗣 and 野田悠加 and 羽柴彩月 and 山田佑亮 and 西山勇毅 and 大越匡 and 中澤仁 and 森将輝 and 水鳥寿思 and 塩田琴美 and 永野智久 and 東海林祐子 and 加藤貴昭},

url = {https://www.ipsj.or.jp/dp/contents/publication/49/S1301-index.html 

http://id.nii.ac.jp/1001/00215701/},

issn = {2435-6484},

year  = {2022},

date = {2022-01-15},

urldate = {2021-10-01},

journal = {情報処理学会論文誌デジタルプラクティス（TDP）},

volume = {3},

number = {1},

pages = {19--33},

abstract = {COVID-19感染拡大の影響を受け，慶應義塾大学では2020年春学期のすべての授業が，体育も含めてオンライン開催となった．特に大学新入生が全員履修する「体育1」は身体運動体験を通じたクラスメート同士のコミュニケーションの場であり，オンライン授業においてもその機会の損失を防ぐことが求められた．そこで我々は情報系教員・学生と体育教員の知見を融合させた，オンライン体育授業サポートシステム「SFC GO」を1ヶ月で構築し運用した．SFC GOではスマートフォン内蔵センサを用いた身体運動の記録や振り返りが可能であり，出題される課題に則した運動記録をタイムラインへ投稿できる．また，クラスメートの投稿を閲覧することや投稿へコメントすることなどのソーシャルネットワーク機能を有する．そして，バックグラウンドで定常的にセンサデータを収集することによって，家事や散歩などの授業時間以外の日常的な運動の記録や振り返りができる．体育1を履修した学生を対象に学生自身のスマートフォンに本アプリケーションをインストールし，2020年5月から7月のオンライン体育授業で使用した．本稿では，実施期間で収集された運動記録のデータ，テクニカルサポート対応事例やスマートフォンを活用した本実施の経験などから導かれる知見について考察を行う．},

keywords = {behavior change, COVID-19, healthcare, mHealth},

pubstate = {published},

tppubtype = {article}

}

Inproceedings

Zengyi Han, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki

Poster: Head Dynamics Enabled Riding Maneuver Prediction Inproceedings

In: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications, and Services, Association for Computing Machinery, Portland, Oregon, 2022.

Abstract | BibTeX | タグ: Activity Recognition, Mobile sensing, Wearable sensing | Links:

Liqiang Xu, Yuuki Nishiyama, Kaoru Sezaki

Enhancing Self-protection: What Influences Human’s Epidemic Prevention Behavior during the COVID-19 Pandemic Inproceedings

In: Distributed, Ambient and Pervasive Interactions, Springer International Publishing, Cham, 2022.

BibTeX | タグ: COVID-19, Infection prevention, Mobile sensing, Self-protection behavior, Self-Tracking | Links:

Yuki Komatsu, Kazuki Shimojo, Yuuki Nishiyama, Kaoru Sezaki

Toward Measuring Conversation Duration Using a Wristwatch-type Wearable Device Inproceedings

In: 2022 IEEE International Conference on Smart Computing (SMARTCOMP), IEEE Computer Society, Espoo, Finland, 2022.

BibTeX | タグ: Context-recognition, Conversation Events, Edge Processing, Sound Classification, Wearable Computing

下条和暉, 西山勇毅, 瀬崎薫

イアラブルデバイスを用いた街歩き時におけるユーザの道迷い状態の検知 Inproceedings

In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1 - 6, 2022.

Abstract | BibTeX | タグ: イアラブルデバイス, ナビゲーション, 行動認識 | Links:

Yuki Kasahara, Yuuki Nishiyama, Kaoru Sezaki

Detecting Childcare Activities Using an Off-the-shelf Smartwatch Inproceedings

In: 2022 IEEE International Conference on Smart Computing (SMARTCOMP), IEEE Computer Society, Espoo, Finland, 2022.

BibTeX | タグ: Activity Recognition, Childcare Activity, Wearable sensing

Xuefu Dong, Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki

DoubleCheck: Detecting Single-Hand Cycling with Inertial Measurement Unit of Smartphone Inproceedings

In: IEEE International Conference on Pervasive Computing and Communications (PerCom), IEEE, Pisa, Italy, 2022, ISBN: 978-1-6654-1648-1.

Abstract | BibTeX | タグ: | Links:

小野翔多, 西山勇毅, 瀬崎薫

ウェアラブルデバイスのマイクを用いたマスク装着状態の検知に向けて Inproceedings

In: 第102回MBL・第73回UBI合同研究発表会, online, 2022.

Abstract | BibTeX | タグ: スマートウォッチ, マスク装着情報, 感染症予防, 機械学習, 音声データ | Links:

牛島秀暢, 西山勇毅, 瀬崎薫

タクシー車両を用いたマイクロモビリティ再配置 Inproceedings Award

In: 情報処理学会第84回全国大会（愛媛大学）, 情報処理学会, 2022.

BibTeX | タグ: | Links:

10.

小松勇輝, 下条和暉, 西山勇毅, 瀬崎薫

腕時計型ウェアラブルデバイスを用いた会話時間計測手法の構築に向けて Inproceedings Award

In: 情報処理学会第84回全国大会（愛媛大学）, 情報処理学会, 2022.

BibTeX | タグ: | Links:

11.

小野翔多, 山崎託, 三好匠, 西山勇毅, 瀬崎薫

[奨励講演] 移動体通信併用型MANETにおける端末密度を用いた中継領域制御 Inproceedings

In: 電子情報通信学会情報通信マネジメント研究会（ICM）, online, 2022.

Abstract | BibTeX | タグ: MANET, モバイルネットワーク, 中継領域, 通信負荷 | Links:

12.

西山勇毅, 瀬崎薫

スマートフォンを用いたベビーカーのコンテキスト検知に向けた一検討 Inproceedings

In: 電子情報通信学会総合大会（オンライン）, 電子情報通信学会, 2022.

Abstract | BibTeX | タグ: Activity Recognition, context-awareness, Mobile sensing | Links:

13.

笠原有貴, 西山勇毅, 瀬崎薫

ウェアラブルデバイスを用いた子育てコンテキストの検知に向けて Inproceedings

In: 研究報告ヒューマンコンピュータインタラクション研究会（CHI）, 情報処理学会, 石垣島, 2022.

Abstract | BibTeX | タグ: モバイル・ウェアラブルセンシング, 子育てコンテキスト, 行動認識 | Links:

2021

Journal Articles

14.

西山勇毅, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 佐々木航, 大越匡, 中澤仁, 森将輝, 水鳥寿思, 塩田琴美, 永野智久, 東海林祐子, 加藤貴昭

感染症流行時におけるスマートフォンを用いた大学生の身体活動量分析 Journal Article

In: 情報処理学会論文誌 [特集：ユビキタスコンピューティングシステム（X）] , 62 (10), pp. 1630–1643, 2021.

Abstract | BibTeX | タグ: COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析 | Links:

@article{nishiyama2021_sfcgo_ipsj,

title = {感染症流行時におけるスマートフォンを用いた 大学生の身体活動量分析},

author = {西山勇毅 and 柿野優衣 and 中縁嗣 and 野田悠加 and 羽柴彩月 and 山田佑亮 and 佐々木航 and 大越匡 and 中澤仁 and 森将輝 and 水鳥寿思 and 塩田琴美 and 永野智久 and 東海林祐子 and 加藤貴昭},

url = {http://id.nii.ac.jp/1001/00213189/},

doi = {10.20729/00213189},

year  = {2021},

date = {2021-10-01},

journal = {情報処理学会論文誌 [特集：ユビキタスコンピューティングシステム（X）] },

volume = {62},

number = {10},

pages = {1630--1643},

abstract = {	新型コロナウイルス感染症（COVID-19）の世界的な感染拡大にともない，多くの大学ではキャンパス内での感染予防のために，キャンパスの封鎖とインターネット越しに授業を配信するオンライン授業が導入され，学生たちは自宅から授業に参加している．このような在宅中心の新しい生活様式は，感染予防効果が見込める一方で，運動不足による二次的な健康被害が懸念される．新しい生活様式における大学生の身体活動の実態，特に学生の属性や時間帯ごとの身体活動量とその内容を明らかにすることは，二次的な健康被害を予防するうえで必要不可欠である．そこで本研究では，日常生活中の身体活動データ（歩数と6種類の行動種別）を大学生が所有するスマートフォンを用いて自動収集し，大学生の身体活動量を明らかにする．身体活動データは，必修の体育授業を履修する大学1年生305名から10週間収集した．その結果，通学（7時から10時）や教室での授業，課外活動（11時から24時）の時間帯における歩数の減少と静止時間の長時間化が明らかになった．本結果は，新しい生活様式における大学生活が平日の身体活動量の低下を招く可能性を示唆する．

With the spreading of the new coronavirus infection (COVID-19) worldwide, several universities have closed their campuses to prevent the spread of infection. Consequently, university classes are being held over the Internet, and students attend these classes from their homes. While the COVID-19 pandemic is expected to be prolonged, the online-centric lifestyle has raised concerns about secondary health issues caused by reduced physical activity (PA). However, the actual status of PA among college students has not yet been examined in Japan. Hence, in this study, we collected daily PA data (including the data corresponding to the number of steps taken and the data associated with six types of activities) by employing off-the-shelf smartphones and thereby analyzing the PA changes of college students. The PA data were collected over a period of ten weeks from 305 first-year college students who were attending a mandatory class of physical education at the university. The obtained results indicate that the decrease in commuting time (7 AM to 10 AM), classroom time, and extracurricular activity time (11 AM to 12 AM) has led to a decrease in PA on weekdays owing to reduced unplanned exercise opportunities. The results suggest that college life in an online-centric lifestyle may lead to a decrease in PA on weekdays.},

keywords = {COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析},

pubstate = {published},

tppubtype = {article}

}

新型コロナウイルス感染症（COVID-19）の世界的な感染拡大にともない，多くの大学ではキャンパス内での感染予防のために，キャンパスの封鎖とインターネット越しに授業を配信するオンライン授業が導入され，学生たちは自宅から授業に参加している．このような在宅中心の新しい生活様式は，感染予防効果が見込める一方で，運動不足による二次的な健康被害が懸念される．新しい生活様式における大学生の身体活動の実態，特に学生の属性や時間帯ごとの身体活動量とその内容を明らかにすることは，二次的な健康被害を予防するうえで必要不可欠である．そこで本研究では，日常生活中の身体活動データ（歩数と6種類の行動種別）を大学生が所有するスマートフォンを用いて自動収集し，大学生の身体活動量を明らかにする．身体活動データは，必修の体育授業を履修する大学1年生305名から10週間収集した．その結果，通学（7時から10時）や教室での授業，課外活動（11時から24時）の時間帯における歩数の減少と静止時間の長時間化が明らかになった．本結果は，新しい生活様式における大学生活が平日の身体活動量の低下を招く可能性を示唆する．
With the spreading of the new coronavirus infection (COVID-19) worldwide, several universities have closed their campuses to prevent the spread of infection. Consequently, university classes are being held over the Internet, and students attend these classes from their homes. While the COVID-19 pandemic is expected to be prolonged, the online-centric lifestyle has raised concerns about secondary health issues caused by reduced physical activity (PA). However, the actual status of PA among college students has not yet been examined in Japan. Hence, in this study, we collected daily PA data (including the data corresponding to the number of steps taken and the data associated with six types of activities) by employing off-the-shelf smartphones and thereby analyzing the PA changes of college students. The PA data were collected over a period of ten weeks from 305 first-year college students who were attending a mandatory class of physical education at the university. The obtained results indicate that the decrease in commuting time (7 AM to 10 AM), classroom time, and extracurricular activity time (11 AM to 12 AM) has led to a decrease in PA on weekdays owing to reduced unplanned exercise opportunities. The results suggest that college life in an online-centric lifestyle may lead to a decrease in PA on weekdays.

15.

佐々木航, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 西山勇毅, 大越匡, 中澤仁, 森将輝, 水鳥寿思, 塩田琴美, 永野智久, 東海林祐子, 加藤貴昭

SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム Journal Article Open Access

In: 情報処理学会論文誌デジタルプラクティス（TDP）, 3 (1), pp. 19 - 33, 2021, ISSN: 2435-6484.

Abstract | BibTeX | タグ: COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析 | Links:

@article{sasaki2021_sfcgo,

title = {SFC GO: 学生同士の繋がりを支援するオンライン体育授業サポートシステム},

author = {佐々木航 and 柿野優衣 and 中縁嗣 and 野田悠加 and 羽柴彩月 and 山田佑亮 and 西山勇毅 and 大越匡 and 中澤仁 and 森将輝 and 水鳥寿思 and 塩田琴美 and 永野智久 and 東海林祐子 and 加藤貴昭},

url = {http://id.nii.ac.jp/1001/00215701/

https://ipsj.ixsq.nii.ac.jp/ej/?action=repository_uri&item_id=215809&file_id=1&file_no=1},

issn = {2435-6484},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

journal = {情報処理学会論文誌デジタルプラクティス（TDP）},

volume = {3},

number = {1},

pages = {19 - 33},

abstract = {COVID-19感染拡大の影響を受け，慶應義塾大学では2020年春学期のすべての授業が，体育も含めてオンライン開催となった．特に大学新入生が全員履修する「体育1」は身体運動体験を通じたクラスメート同士のコミュニケーションの場であり，オンライン授業においてもその機会の損失を防ぐことが求められた．そこで我々は情報系教員・学生と体育教員の知見を融合させた，オンライン体育授業サポートシステム「SFC GO」を1ヶ月で構築し運用した．SFC GOではスマートフォン内蔵センサを用いた身体運動の記録や振り返りが可能であり，出題される課題に則した運動記録をタイムラインへ投稿できる．また，クラスメートの投稿を閲覧することや投稿へコメントすることなどのソーシャルネットワーク機能を有する．そして，バックグラウンドで定常的にセンサデータを収集することによって，家事や散歩などの授業時間以外の日常的な運動の記録や振り返りができる．体育1を履修した学生を対象に学生自身のスマートフォンに本アプリケーションをインストールし，2020年5月から7月のオンライン体育授業で使用した．本稿では，実施期間で収集された運動記録のデータ，テクニカルサポート対応事例やスマートフォンを活用した本実施の経験などから導かれる知見について考察を行う．

All classes including physical education were held online in the 2020 spring semester at Keio University due to the spread of the COVID-19 virus. In particular, “Physical Education 1” required for all first year university students, served as a place for communication between classmates. Therefore, it was crucial that such a place of communication was still available, even as an online course. Thus, we constructed the online physical education class support system “SFC GO”, which combines the knowledge of informatics teachers/students and physical education teachers. SFC GO can record and help the users reflect back on the physical exercises conducted using the sensors built in the smartphone, and it is possible to post the exercise record on the timeline according to the task. It also has social network functions such as viewing and commenting on posts made by classmates. By constantly collecting sensor data in the background, SFC GO can record and reflect back on daily exercises such as housework and walks. For students who took Physical Education 1, this system was installed on their own smartphones and was used in online physical education classes from May to July 2020. In this paper, we show the findings derived from the exercise record data collected, technical support cases, and the experience of this implementation using smartphones.},

keywords = {COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析},

pubstate = {published},

tppubtype = {article}

}

COVID-19感染拡大の影響を受け，慶應義塾大学では2020年春学期のすべての授業が，体育も含めてオンライン開催となった．特に大学新入生が全員履修する「体育1」は身体運動体験を通じたクラスメート同士のコミュニケーションの場であり，オンライン授業においてもその機会の損失を防ぐことが求められた．そこで我々は情報系教員・学生と体育教員の知見を融合させた，オンライン体育授業サポートシステム「SFC GO」を1ヶ月で構築し運用した．SFC GOではスマートフォン内蔵センサを用いた身体運動の記録や振り返りが可能であり，出題される課題に則した運動記録をタイムラインへ投稿できる．また，クラスメートの投稿を閲覧することや投稿へコメントすることなどのソーシャルネットワーク機能を有する．そして，バックグラウンドで定常的にセンサデータを収集することによって，家事や散歩などの授業時間以外の日常的な運動の記録や振り返りができる．体育1を履修した学生を対象に学生自身のスマートフォンに本アプリケーションをインストールし，2020年5月から7月のオンライン体育授業で使用した．本稿では，実施期間で収集された運動記録のデータ，テクニカルサポート対応事例やスマートフォンを活用した本実施の経験などから導かれる知見について考察を行う．
All classes including physical education were held online in the 2020 spring semester at Keio University due to the spread of the COVID-19 virus. In particular, “Physical Education 1” required for all first year university students, served as a place for communication between classmates. Therefore, it was crucial that such a place of communication was still available, even as an online course. Thus, we constructed the online physical education class support system “SFC GO”, which combines the knowledge of informatics teachers/students and physical education teachers. SFC GO can record and help the users reflect back on the physical exercises conducted using the sensors built in the smartphone, and it is possible to post the exercise record on the timeline according to the task. It also has social network functions such as viewing and commenting on posts made by classmates. By constantly collecting sensor data in the background, SFC GO can record and reflect back on daily exercises such as housework and walks. For students who took Physical Education 1, this system was installed on their own smartphones and was used in online physical education classes from May to July 2020. In this paper, we show the findings derived from the exercise record data collected, technical support cases, and the experience of this implementation using smartphones.

16.

西山勇毅, 川原圭博, 瀬崎薫

MOCHA: Bluetoothビーコンを用いた学内位置情報サービスの開発・運用 Journal Article Open Access

In: 画像電子学会誌, 50 (3), pp. 459-461, 2021, (ウィズコロナ・アフターコロナに向けた安心・安全・便利なキャンパスを目指して).

Abstract | BibTeX | タグ: Bluetoothビーコン, COVID-19, アフターコロナ, ウィズコロナ, 位置情報サービス, 学内システム, 開発・運用 | Links:

17.

Wataru Sasaki, Yuuki Nishiyama, Tadashi Okoshi, Jin Nakazawa

Investigating the occurrence of selfie-based emotional contagion over social network Journal Article Open Access

In: Social Network Analysis and Mining, 11 , pp. 8, 2021, ISSN: 1869-5450.

Abstract | BibTeX | タグ: Emotional contagion ·, Mobile sensing ·, Social content sharing, Social network · | Links:

18.

Sang Won Bae, Tammy Chung, Rahul Islam, Brian Suffoletto, Jiameng Du, Serim Jang, Yuuki Nishiyama, Raghu Mulukutla, Anind Dey

Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings Journal Article

In: Drug and Alcohol Dependence, pp. 108972, 2021, ISSN: 0376-8716.

Abstract | BibTeX | タグ: Acute intoxication, Cannabis smoking, Light gradient boosting machine model, Mobile phone sensors | Links:

@article{BAE2021108972,

title = {Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings},

author = {Sang Won Bae and Tammy Chung and Rahul Islam and Brian Suffoletto and Jiameng Du and Serim Jang and Yuuki Nishiyama and Raghu Mulukutla and Anind Dey},

url = {https://www.sciencedirect.com/science/article/pii/S0376871621004671

https://doi.org/10.1016/j.drugalcdep.2021.108972},

doi = {https://doi.org/10.1016/j.drugalcdep.2021.108972},

issn = {0376-8716},

year  = {2021},

date = {2021-01-01},

journal = {Drug and Alcohol Dependence},

pages = {108972},

abstract = {Background 

Given possible impairment in psychomotor functioning related to acute cannabis intoxication, we explored whether smartphone-based sensors (e.g., accelerometer) can detect self-reported episodes of acute cannabis intoxication (subjective “high” state) in the natural environment. 

Methods Young adults (ages 18–25) in Pittsburgh, PA, who reported cannabis use at least twice per week, completed up to 30 days of daily data collection: phone surveys (3 times/day), self-initiated reports of cannabis use (start/stop time, subjective cannabis intoxication rating: 0–10, 10 = very high), and continuous phone sensor data. We tested multiple models with Light Gradient Boosting Machine (LGBM) in distinguishing “not intoxicated” (rating = 0) vs subjective cannabis “low-intoxication” (rating = 1–3) vs “moderate-intensive intoxication” (rating = 4–10). We tested the importance of time features (i.e., day of the week, time of day) relative to smartphone sensor data only on model performance, since time features alone might predict “routines” in cannabis intoxication. 

Results Young adults (N = 57; 58 % female) reported 451 cannabis use episodes, mean subjective intoxication rating = 3.77 (SD = 2.64). LGBM, the best performing classifier, had 60 % accuracy using time features to detect subjective “high” (Area Under the Curve [AUC] = 0.82). Combining smartphone sensor data with time features improved model performance: 90 % accuracy (AUC = 0.98). Important smartphone features to detect subjective cannabis intoxication included travel (GPS) and movement (accelerometer). 

Conclusions 

This proof-of-concept study indicates the feasibility of using phone sensors to detect subjective cannabis intoxication in the natural environment, with potential implications for triggering just-in-time interventions.},

keywords = {Acute intoxication, Cannabis smoking, Light gradient boosting machine model, Mobile phone sensors},

pubstate = {published},

tppubtype = {article}

}

Inproceedings

19.

西山勇毅, 瀬崎薫

イヤラブルデバイスを用いた身体感覚記録・利活用システムの構築に向けて Inproceedings Award

In: 第72回情報処理学会ユビキタスコンピューティングシステム（UBI）研究発表会, pp. 1–8, 情報処理学会, 淡路島, 2021, ISSN: 2188-8698.

Abstract | BibTeX | タグ: アスリート, ウェアラブルデバイス, 言語化支援, 身体感覚, 音声認識 | Links:

20.

Helinyi Peng, Yuuki Nishiyama, Kaoru Sezaki

Estimation of Greenhouse Gas Emission Reduction from Shared Micromobility System Inproceedings

In: 2021 IEEE Green Energy and Smart Systems Conference (IGESSC), pp. 1-6, IEEE, Long Beach, CA, USA, 2021, ISSN: 2640-0138.

Abstract | BibTeX | タグ: environmental impacts, greenhouse gas emission, Machine learning, shared micromobility | Links:

@inproceedings{igessc2021_peng,

title = {Estimation of Greenhouse Gas Emission Reduction from Shared Micromobility System},

author = {Helinyi Peng and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://ieeexplore.ieee.org/document/9618701

https://www.youtube.com/watch?v=vbt622kXNuU},

doi = {10.1109/IGESSC53124.2021.9618701},

issn = {2640-0138},

year  = {2021},

date = {2021-11-01},

urldate = {2021-11-01},

booktitle = {2021 IEEE Green Energy and Smart Systems Conference (IGESSC)},

pages = {1-6},

publisher = {IEEE},

address = {Long Beach, CA, USA},

abstract = {Shared micromobility is widely recognized as an environmentally friendly travel mode and a critical component of transportation decarbonization. However, quantitatively assessing its environmental impact using real-world trip data is an unresolved and challenging subject. In this research, we proposed a system combining machine learning algorithms and the Monte Carlo simulation to address this issue. First, several machine learning algorithms (Random Forest, XGBoost, and LightGBM) were utilized to identify citizens’ travel mode choice preferences and then estimate the substituted travel mode of each micromobility trip. Second, to ensure the reliability of the final environmental impact assessment, the Monte Carlo simulations were used to simulate the substituted mode of each trip. Then the environmental impacts were calculated based on the life cycle greenhouse gas emissions. Instead of estimating a specific number, we obtained a probabilistic outcome for environmental impacts by using the Monte Carlo simulation, which considers the uncertainty. According to the studies, the shared bike service and the shared e-scooter service have positive environmental impacts. However, these effects are limited compared to the transportation sector’s total emissions. The most compelling reason is that shared micromobility comprises a minuscule part of total urban travel.},

keywords = {environmental impacts, greenhouse gas emission, Machine learning, shared micromobility},

pubstate = {published},

tppubtype = {inproceedings}

}

21.

Hong Duc Nguyen, Shunsuke Aoki, Yuuki Nishiyama, Kaoru Sezaki

A Run-time Dynamic Computation Offloading Strategy in Vehicular Edge Computing Inproceedings

In: 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall), IEEE, Online, 2021.

Abstract | BibTeX | タグ: Connected vehicles, Edge computing, Off-loading, Vehicular networks | Links:

22.

Zengyi Han, Hong Duc Nguyen, Shunsuke Aoki, Yuuki Nishiyama, Kaoru Sezaki

MiMoSense: An Open Crowdsensing Platform for Micro-Mobility Inproceedings

In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 1-6, IEEE, 2021.

Abstract | BibTeX | タグ: e-scooter, Micro-Mobility, Mobile Sensing Toolkit | Links:

23.

Hidenaga Ushijima, Shunsuke Aoki, Peng Helinyi, Yuuki Nishiyama, Kaoru Sezaki

An Unsupervised Learning-based Approach for User Mobility Analysis of E-Scooter Sharing Systems Inproceedings

In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), IEEE, 2021.

BibTeX | タグ: data analysis, e-scooter | Links:

24.

Hong Duc Nguyen, Shunsuke Aoki, Yuuki Nishiyama, Kaoru Sezaki

An Online Task Offloading Strategy in Vehicular Edge Computing Inproceedings Award

In: IEICE Society Conference 2021 , IEICE, 2021.

BibTeX | タグ: Connected vehicles, Edge computing, Off-loading, Vehicular networks | Links:

25.

小野翔多, 山崎託, 三好匠, 西山勇毅, 瀬崎薫

移動体通信併用形MANETにおける経路要求送信回数に基づく経路構築手法 Inproceedings

In: 2021 電子情報通信学会ソサイエティ大会, オンライン, 2021.

BibTeX | タグ: MANET, モバイルネットワーク, 位置情情報, 負荷分散

26.

笠原有貴, 西山勇毅, 瀬崎薫

スマートウォッチを用いた子育て行動の推定に向けた一検討 Inproceedings

In: 計測自動制御学会計測部門スマートセンシングシステム部会, 計測自動制御学会, 2021.

BibTeX | タグ: childcare, Context-Aware, sensing, Wearable | Links:

27.

下条和暉, ⻄山勇毅, 瀬崎薫

常時装着型イアラブルデバイスにおける割り込み可能タイミングの検討 Inproceedings

In: CSIS DAYS 2021, pp. xx–xx, 東京大学空間情報科学研究センター, 2021.

BibTeX | タグ: UX, イヤラブル, タイミング, 割り込み

28.

小池優太郎, 西山勇毅, 瀬崎薫

集約型都市におけるライドシェアサービス導入効果のシミュレーション Inproceedings

In: CSIS DAYS 2021, pp. xx–xx, 東京大学空間情報科学研究センター, 2021.

BibTeX | タグ: MaaS, コンパクトシティー, シュミレーション, ライドシェア

29.

鈴木凌斗, 村上弘晃, 西山勇毅, 川原圭博, 瀬崎薫

部屋毎の滞在時間特性を考慮した頑健な滞在場所推定手法 Inproceedings

In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1–7, 情報処理学会, 2021.

Abstract | BibTeX | タグ: Bluetoothビーコン, COVID-19, ワイブル分布, 滞在場所推定 | Links:

30.

陳美怡, 幡井皓介, 西山勇毅, 瀬崎薫

感染症予防行動を促進させるインセンティブモデルに関する一検討 Inproceedings

In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1–7, 情報処理学会, 2021, ISSN: 2188-8698.

Abstract | BibTeX | タグ: COVID-19, ゲーミフィケーション, モバイル・ウェアラブルセンシング, 感染症予防, 行動変容促進 | Links:

31.

陳美怡, 幡井皓介, 西山勇毅, 瀬崎薫

感染症予防行動を促進させるインセンティブモデルの構築に向けて Inproceedings

In: 第20回情報科学技術フォーラム（FIT2021）, 情報処理学会, オンライン, 2021.

Abstract | BibTeX | タグ: COVID-19, セルフトラッキング, 位置情報, 感染症予防, 行動変容促進 | Links:

@inproceedings{fit2021_selfguard,

title = {感染症予防行動を促進させるインセンティブモデルの構築に向けて},

author = {陳美怡 and 幡井皓介 and 西山勇毅 and 瀬崎薫},

url = {https://www.ipsj.or.jp/event/fit/fit2021/},

year  = {2021},

date = {2021-08-25},

booktitle = {第20回情報科学技術フォーラム（FIT2021）},

publisher = {情報処理学会},

address = {オンライン},

abstract = {現在、新型コロナウイルス感染症（COVID-19）の感染が拡大しており，人々の生命と健康を大きく脅かしている．2021年4月18日時点で，COVID-19による全世界の累計死亡者数が300万人を超えたことが報告された[1]．市や政府は，感染症の感染拡大を防ぐために，自己隔離，ロックダウン，行動制限などの対策を実施している．また政府や保健機関は，人々が手洗い・マスクの着用・行動記録・外出自粛などの感染症予防策を積極的に取り続けることを推奨している．西山らの研究では，行動記録アプリ（SelfGuard）を開発し，半自動的にユーザの滞在情報・行動履歴を記録することで，感染症予防行動の促進を実現している[2]．本研究では，ユーザの感染症予防行動の促進を目標として，既存アプリ（SelfGuard）を拡張し，感染症予防行動に対する最適なインセンティブモデルの導入を検討する．具体的には，スマートフォンとウェアラブルデバイスに搭載されたセンサを利用してユーザの感染症予防行動を認識し，行動に応じてインセンティブとして換金可能なポイントを付与する．定額・加算・減算モデルという三種類のインセンティブモデルにおいて人の行動に与える影響の違いを評価する},

keywords = {COVID-19, セルフトラッキング, 位置情報, 感染症予防, 行動変容促進},

pubstate = {published},

tppubtype = {inproceedings}

}

32.

Soichiro Higuma, Kosuke Hatai, Yuuki Nishiyama, Kaoru Sezaki

Towards Estimating UV Exposure Using GPS Signal Strength from a Carrying Smartphone Inproceedings

In: 2021 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 299-304, IEEE, Irvine, CA, USA, 2021, ISBN: 2693-8340.

Abstract | BibTeX | タグ: Estimation, GPS, Mobile sensing, UV | Links:

33.

Hidenaga Ushijima, Shota Ono, Yuuki Nishiyama, Kaoru Sezaki

Towards Infectious Disease Risk Assessment in Taxis using Environmental Sensors Inproceedings

In: Streitz, Norbert; Konomi, Shin'ichi (Ed.): Distributed, Ambient and Pervasive Interactions, pp. 178–188, Springer International Publishing, Cham, 2021, ISBN: 978-3-030-77015-0.

Abstract | BibTeX | タグ: CO2, COVID-19, Mobile sensing, Public Transportation | Links:

34.

木口裕太, 杉山健, 小野翔多, 山崎託, 三好匠, シルバーストントーマス

位置情報に基づく歩車間危険通知システムにおける負荷削減手法 Inproceedings

In: 第26回電子情報通信学会東京支部学生会研究発表会, オンライン, 2021.

BibTeX | タグ:

35.

立岡俊, 山本嶺, 山崎託, 三好匠, 片田寛志, 小野翔多, 田中良明

車両の移動特性に基づくセルラ通信併用形V2V情報共有手法 Inproceedings

In: 第26回電子情報通信学会東京支部学生会研究発表会, オンライン, 2021.

BibTeX | タグ:

36.

Xuefu Dong, Zengyi Han, Yuuki Nishiyama, Kaoru Sezaki

Detecting Single-Hand Riding with Integrated Accelerometer and Gyroscope of Smartphone Inproceedings

In: 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, pp. 19–20, Association for Computing Machinery, Virtual, USA, 2021, ISBN: 9781450384612.

Abstract | BibTeX | タグ: Accelerometer, Gyroscope, Human Activity recognition | Links:

37.

Yuuki Nishiyama, Kaoru Sezaki

Experience Sampling Tool for Repetitive Skills Training in Sports Using Voice User Interface Inproceedings

In: 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, pp. 54–55, Association for Computing Machinery, Virtual, USA, 2021, ISBN: 9781450384612.

Abstract | BibTeX | タグ: context-awareness, Experience Sampling, Voice User Interface, Wearable Devices | Links:

38.

Zengyi Han, Xuefu Dong, Yuuki Nishiyama, Kaoru Sezaki

HeadSense: A Head Movement Detecting System for Micro-Mobility Riders Inproceedings

In: 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, pp. 26–27, Association for Computing Machinery, Virtual, USA, 2021, ISBN: 9781450384612.

Abstract | BibTeX | タグ: Head Movement Detection, Human Activity recognition, Wearable | Links:

Masters Theses

39.

牛島秀暢

マイクロモビリティの移動パターン分類と再配置スケジューリング Masters Thesis

東京大学大学院新領域創成科学研究科社会文化環境学専攻, 2021.

BibTeX | タグ: Micromobility, タクシー, 再配置スケジューリング, 移動パターン分析

40.

陳美怡

感染症予防行動を促進させるインセンティブモデルの構築 Masters Thesis

東京大学大学院新領域創成科学研究科社会文化環境学専攻, 2021.

BibTeX | タグ: COVID-19, ゲーミフィケーション, モバイル・ウェアラブルセンシング, 行動変容促進

41.

Nguyen Hong Duc

Online Task Offloading Strategy in Vehicular Edge Computing Masters Thesis

Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo, 2021.

BibTeX | タグ: Connected vehicles, Edge computing, Off-loading, Vehicular networks

Miscellaneous

42.

西山勇毅, 柿野優衣, 中縁嗣, 野田悠加, 羽柴彩月, 山田佑亮, 佐々木航, 大越匡, 中澤仁, 森将輝, 水鳥寿思, 塩田琴美, 永野智久, 東海林祐子, 加藤貴昭

感染症流行時におけるスマートフォンを用いた大学生の身体活動量分析 Miscellaneous Open AccessSelf Archive

2021.

Abstract | BibTeX | タグ: COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析 | Links:

@misc{nishiyama2021_sfcgo,

title = {感染症流行時におけるスマートフォンを用いた 大学生の身体活動量分析},

author = {西山勇毅 and 柿野優衣 and 中縁嗣 and 野田悠加 and 羽柴彩月 and 山田佑亮 and 佐々木航 and 大越匡 and 中澤仁 and 森将輝 and 

水鳥寿思 and 塩田琴美 and 永野智久 and 東海林祐子 and 加藤貴昭},

url = {https://arxiv.org/abs/2103.06515},

year  = {2021},

date = {2021-03-01},

abstract = {新型コロナウイルス感染症（COVID-19）の世界的な感染拡大に伴い，多くの大学ではキャンパス内での感染予防のために，キャンパスの封鎖とインターネット越しに授業を配信するオンライン授業が導入され，学生達は自宅から授業に参加している．オンライン中心の新しい生活様式は，感染リスクを低減できる一方で，運動不足による二次的な健康被害を引き起こす可能性が危惧されている．学生の健康状態の把握は大学にとって重要であるが，新しい生活様式における大学生の身体活動量の実態は明らかになっていない．そこで本研究では，日常生活中の身体活動データ（歩数と 6 種類の行動種別）を大学生が所有するスマートフォンを用いて自動収集し，大学生の身体活動量の変化を明らかにする．身体活動データは，大学の必修授業（体育）を履修する大学 1 年生 305 名から 10 週間収集した．その結果，COVID-19 流行下での平均歩数（3522.5 歩）は流行前の平均歩数（6474.87 歩）より 45.6%低下し，特に平日の歩数は COVID19 流行前と比べる 51.9%低下していることが明らかになった．また時刻別では，通学・授業中の時間帯において歩数の低下と静止時間の増加が見られ，通学や教室移動に伴う日常生活中の無意識の運動機会の減少が，平日の身体活動量の低下を招いている可能性が示唆された．},

keywords = {COVID-19, モバイルセンシング, 歩数, 行動認識, 身体活動量分析},

pubstate = {published},

tppubtype = {misc}

}

2020

Journal Articles

43.

Elina Kuosmanen, Florian Wolling, Julio Vega, Valerii Kan, Yuuki Nishiyama, Simon Harper, Kristof Van Laerhoven, Simo Hosio, Denzil Ferreira

Smartphone-Based Monitoring of Parkinson Disease: Quasi-Experimental Study to Quantify Hand Tremor Severity and Medication Effectiveness Journal Article Open Access

In: JMIR Mhealth Uhealth, 8 (11), pp. e21543, 2020, ISSN: 2291-5222.

Abstract | BibTeX | タグ: hand tremor, mobile health, Parkinson disease, smartphone | Links:

@article{info:doi/10.2196/21543,

title = {Smartphone-Based Monitoring of Parkinson Disease: Quasi-Experimental Study to Quantify Hand Tremor Severity and Medication Effectiveness},

author = {Elina Kuosmanen and Florian Wolling and Julio Vega and Valerii Kan and Yuuki Nishiyama and Simon Harper and Kristof Van Laerhoven and Simo Hosio and Denzil Ferreira},

url = {http://www.ncbi.nlm.nih.gov/pubmed/33242017},

doi = {10.2196/21543},

issn = {2291-5222},

year  = {2020},

date = {2020-11-26},

journal = {JMIR Mhealth Uhealth},

volume = {8},

number = {11},

pages = {e21543},

abstract = {Background: Hand tremor typically has a negative impact on a person's ability to complete many common daily activities. Previous research has investigated how to quantify hand tremor with smartphones and wearable sensors, mainly under controlled data collection conditions. Solutions for daily real-life settings remain largely underexplored. Objective: Our objective was to monitor and assess hand tremor severity in patients with Parkinson disease (PD), and to better understand the effects of PD medications in a naturalistic environment. Methods: Using the Welch method, we generated periodograms of accelerometer data and computed signal features to compare patients with varying degrees of PD symptoms. Results: We introduced and empirically evaluated the tremor intensity parameter (TIP), an accelerometer-based metric to quantify hand tremor severity in PD using smartphones. There was a statistically significant correlation between the TIP and self-assessed Unified Parkinson Disease Rating Scale (UPDRS) II tremor scores (Kendall rank correlation test: z=30.521, P<.001, $tau$=0.5367379; n=11). An analysis of the ``before'' and ``after'' medication intake conditions identified a significant difference in accelerometer signal characteristics among participants with different levels of rigidity and bradykinesia (Wilcoxon rank sum test, P<.05). Conclusions: Our work demonstrates the potential use of smartphone inertial sensors as a systematic symptom severity assessment mechanism to monitor PD symptoms and to assess medication effectiveness remotely. Our smartphone-based monitoring app may also be relevant for other conditions where hand tremor is a prevalent symptom.},

keywords = {hand tremor, mobile health, Parkinson disease, smartphone},

pubstate = {published},

tppubtype = {article}

}

44.

Tammy Chung, Sang Won Bae, Eun-Young Mun, Brian Suffoletto, Yuuki Nishiyama, Serim Jang, Anind K Dey

Mobile Assessment of Acute Effects of Marijuana on Cognitive Functioning in Young Adults: Observational Study Journal Article Open Access

In: JMIR Mhealth Uhealth, 8 (3), pp. e16240, 2020, ISSN: 2291-5222.

Abstract | BibTeX | タグ: cannabis, cell phone, cognition, marijuana, memory, short-term | Links:

@article{info:doi/10.2196/16240,

title = {Mobile Assessment of Acute Effects of Marijuana on Cognitive Functioning in Young Adults: Observational Study},

author = {Tammy Chung and Sang Won Bae and Eun-Young Mun and Brian Suffoletto and Yuuki Nishiyama and Serim Jang and Anind K Dey},

url = {http://www.ncbi.nlm.nih.gov/pubmed/32154789},

doi = {10.2196/16240},

issn = {2291-5222},

year  = {2020},

date = {2020-03-10},

journal = {JMIR Mhealth Uhealth},

volume = {8},

number = {3},

pages = {e16240},

abstract = {Background: Mobile assessment of the effects of acute marijuana on cognitive functioning in the natural environment would provide an ecologically valid measure of the impacts of marijuana use on daily functioning. Objective: This study aimed to examine the association of reported acute subjective marijuana high (rated 0-10) with performance on 3 mobile cognitive tasks measuring visuospatial working memory (Flowers task), attentional bias to marijuana-related cues (marijuana Stroop), and information processing and psychomotor speed (digit symbol substitution task [DSST]). The effect of distraction as a moderator of the association between the rating of subjective marijuana high and task performance (ie, reaction time and number of correct responses) was explored. Methods: Young adults (aged 18-25 years; 37/60, 62% female) who reported marijuana use at least twice per week were recruited through advertisements and a participant registry in Pittsburgh, Pennsylvania. Phone surveys and mobile cognitive tasks were delivered 3 times per day and were self-initiated when starting marijuana use. Completion of phone surveys triggered the delivery of cognitive tasks. Participants completed up to 30 days of daily data collection. Multilevel models examined associations between ratings of subjective marijuana high (rated 0-10) and performance on each cognitive task (reaction time and number of correct responses) and tested the number of distractions (rated 0-4) during the mobile task session as a moderator of the association between ratings of subjective marijuana high and task performance. Results: Participants provided 2703 data points, representing 451 reports (451/2703, 16.7%) of marijuana use. Consistent with slight impairing effects of acute marijuana use, an increase in the average rating of subjective marijuana high was associated with slower average reaction time on all 3 tasks---Flowers (B=2.29; SE 0.86; P=.008), marijuana Stroop (B=2.74; SE 1.09; P=.01), and DSST (B=3.08; SE 1.41; P=.03)---and with fewer correct responses for Flowers (B=−0.03; SE 0.01; P=.01) and DSST (B=−0.18; SE 0.07; P=.01), but not marijuana Stroop (P=.45). Results for distraction as a moderator were statistically significant only for certain cognitive tasks and outcomes. Specifically, as hypothesized, a person's average number of reported distractions moderated the association of the average rating of subjective marijuana high (over and above a session's rating) with the reaction time for marijuana Stroop (B=−52.93; SE 19.38; P=.006) and DSST (B=−109.72; SE 42.50; P=.01) and the number of correct responses for marijuana Stroop (B=−0.22; SE 0.10; P=.02) and DSST (B=4.62; SE 1.81; P=.01). Conclusions: Young adults' performance on mobile cognitive tasks in the natural environment was associated with ratings of acute subjective marijuana high, consistent with slight decreases in cognitive functioning. Monitoring cognitive functioning in real time in the natural environment holds promise for providing immediate feedback to guide personal decision making.},

keywords = {cannabis, cell phone, cognition, marijuana, memory, short-term},

pubstate = {published},

tppubtype = {article}

}

Background: Mobile assessment of the effects of acute marijuana on cognitive functioning in the natural environment would provide an ecologically valid measure of the impacts of marijuana use on daily functioning. Objective: This study aimed to examine the association of reported acute subjective marijuana high (rated 0-10) with performance on 3 mobile cognitive tasks measuring visuospatial working memory (Flowers task), attentional bias to marijuana-related cues (marijuana Stroop), and information processing and psychomotor speed (digit symbol substitution task [DSST]). The effect of distraction as a moderator of the association between the rating of subjective marijuana high and task performance (ie, reaction time and number of correct responses) was explored. Methods: Young adults (aged 18-25 years; 37/60, 62% female) who reported marijuana use at least twice per week were recruited through advertisements and a participant registry in Pittsburgh, Pennsylvania. Phone surveys and mobile cognitive tasks were delivered 3 times per day and were self-initiated when starting marijuana use. Completion of phone surveys triggered the delivery of cognitive tasks. Participants completed up to 30 days of daily data collection. Multilevel models examined associations between ratings of subjective marijuana high (rated 0-10) and performance on each cognitive task (reaction time and number of correct responses) and tested the number of distractions (rated 0-4) during the mobile task session as a moderator of the association between ratings of subjective marijuana high and task performance. Results: Participants provided 2703 data points, representing 451 reports (451/2703, 16.7%) of marijuana use. Consistent with slight impairing effects of acute marijuana use, an increase in the average rating of subjective marijuana high was associated with slower average reaction time on all 3 tasks---Flowers (B=2.29; SE 0.86; P=.008), marijuana Stroop (B=2.74; SE 1.09; P=.01), and DSST (B=3.08; SE 1.41; P=.03)---and with fewer correct responses for Flowers (B=−0.03; SE 0.01; P=.01) and DSST (B=−0.18; SE 0.07; P=.01), but not marijuana Stroop (P=.45). Results for distraction as a moderator were statistically significant only for certain cognitive tasks and outcomes. Specifically, as hypothesized, a person's average number of reported distractions moderated the association of the average rating of subjective marijuana high (over and above a session's rating) with the reaction time for marijuana Stroop (B=−52.93; SE 19.38; P=.006) and DSST (B=−109.72; SE 42.50; P=.01) and the number of correct responses for marijuana Stroop (B=−0.22; SE 0.10; P=.02) and DSST (B=4.62; SE 1.81; P=.01). Conclusions: Young adults' performance on mobile cognitive tasks in the natural environment was associated with ratings of acute subjective marijuana high, consistent with slight decreases in cognitive functioning. Monitoring cognitive functioning in real time in the natural environment holds promise for providing immediate feedback to guide personal decision making.

45.

Shota Ono, Taku Yamazaki, Takumi Miyoshi, Kaoru Sezaki

Mobile-assisted ad hoc networking architecture based on location information Journal Article Open Access

In: IEICE Communications Express, 9 (3), pp. 94-99, 2020.

Abstract | BibTeX | タグ: Ad hoc network, device-to-device communication, location information, mobile network, relay range | Links:

Inproceedings

46.

山下陸, 西山勇毅, 小松寛弥, 川原圭博

BLEビーコンを用いた屋内位置推定システムの設計と実装 Inproceedings

In: 研究報告ユビキタスコンピューティングシステム（UBI）, pp. 1–7, 情報処理学会, 2020, ISBN: 2188-8698.

Abstract | BibTeX | タグ: COVID-19, 屋内位置情報, 接触検知 | Links:

@inproceedings{weko_208650_1,

title = {BLEビーコンを用いた屋内位置推定システムの設計と実装},

author = {山下陸 and 西山勇毅 and 小松寛弥 and 川原圭博},

url = {http://id.nii.ac.jp/1001/00208548/

https://mocha.t.u-tokyo.ac.jp/},

isbn = {2188-8698},

year  = {2020},

date = {2020-12-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2020-UBI-68},

number = {8},

pages = {1--7},

publisher = {情報処理学会},

abstract = {現在，我々は大学キャンパスでの COVID-19 感染対策，そして，ポストコロナ時代における望ましい位置情報インフラの構築を目指している．ユーザーのプライバシーに配慮し，講義で活用する教室や図書館等の 181 のスペースに 200 の Bluetooth ビーコンを設置した．ビーコンが発する ID をスマートフォンで検知し，ユーザの部屋への入退室を判定する．ユーザの位置情報はサーバーサイドに集約された後，ユーザの同意に基づいたルールで，ニーズに応じた位置情報の開示が可能になっている．設置したビーコンをもとにキャンパス内で位置情報の取得予備実験を行ったところ，室内を隔てる壁の材質によっては電波の減衰率が大きく異なることや，大学の施設管理データベースの登録情報が実態を反映していないことなどが明るみになった．本稿では，MOCHA と名付けた本システムの設計と実装，システムアーキテクチャや利用規約を制定する際のポイントについて共有する．



We are currently working to build the desirable location infrastructure on university campus to combat COVID-19 and also in the post-corona era. In consideration of the user privacy, we have installed 200 Bluetooth beacons in 181 spaces, including the libraries and the classrooms used for the lectures. The IDs emitted by the beacons are detected by a smartphone to determine the user's entering and exiting the room. After the user's location information is collected on the server side, rules based on the user's consent enable the location information to be disclosed according to their needs. A preliminary experiment of the location information acquisition in the campus using the beacons revealed that the attenuation rate of radio waves differs greatly depending on the material of the wall, and the information registered in the facility management database of the university does not reflect the reality. In this paper, we share the design and implementation of our system, named MOCHA, and the key points for establishing the system architecture and terms of use.},

keywords = {COVID-19, 屋内位置情報, 接触検知},

pubstate = {published},

tppubtype = {inproceedings}

}

現在，我々は大学キャンパスでの COVID-19 感染対策，そして，ポストコロナ時代における望ましい位置情報インフラの構築を目指している．ユーザーのプライバシーに配慮し，講義で活用する教室や図書館等の 181 のスペースに 200 の Bluetooth ビーコンを設置した．ビーコンが発する ID をスマートフォンで検知し，ユーザの部屋への入退室を判定する．ユーザの位置情報はサーバーサイドに集約された後，ユーザの同意に基づいたルールで，ニーズに応じた位置情報の開示が可能になっている．設置したビーコンをもとにキャンパス内で位置情報の取得予備実験を行ったところ，室内を隔てる壁の材質によっては電波の減衰率が大きく異なることや，大学の施設管理データベースの登録情報が実態を反映していないことなどが明るみになった．本稿では，MOCHA と名付けた本システムの設計と実装，システムアーキテクチャや利用規約を制定する際のポイントについて共有する．

We are currently working to build the desirable location infrastructure on university campus to combat COVID-19 and also in the post-corona era. In consideration of the user privacy, we have installed 200 Bluetooth beacons in 181 spaces, including the libraries and the classrooms used for the lectures. The IDs emitted by the beacons are detected by a smartphone to determine the user's entering and exiting the room. After the user's location information is collected on the server side, rules based on the user's consent enable the location information to be disclosed according to their needs. A preliminary experiment of the location information acquisition in the campus using the beacons revealed that the attenuation rate of radio waves differs greatly depending on the material of the wall, and the information registered in the facility management database of the university does not reflect the reality. In this paper, we share the design and implementation of our system, named MOCHA, and the key points for establishing the system architecture and terms of use.

47.

日隈壮一郎, 西山勇毅, 瀬崎薫

スマートフォンのGPS信号受信強度を用いた紫外線量推定手法に関する研究 Inproceedings

In: CSIS DAYS 2020, Center for Spatial Information Science, The University of Tokyo, オンライン, 2020.

BibTeX | タグ: GPS信号受信状態, モバイルセンシング, 紫外線量推定 | Links:

48.

牛島秀暢, 西山勇毅, 小野翔多, 瀬崎薫

環境センサを用いたタクシー車室内における感染症リスク評価に関する一検討 Inproceedings Award

In: 研究報告高度交通システムとスマートコミュニティ（ITS）, pp. 1–6, 情報処理学会, 2020, ISSN: 2188-8965.

Abstract | BibTeX | タグ: 二酸化炭素, 感染症対策, 車内環境センシング | Links:

49.

Yuuki Nishiyama, Takuro Yonezawa, Kaoru Sezaki

SelfGuard: Semi-Automated Activity Tracking for Enhancing Self-Protection against the COVID-19 Pandemic Inproceedings

In: the 18th ACM Conference on Embedded Networked Sensor Systems (SenSys '20), COVID-19 Pandemic Response, Virtual Event, Japan , pp. 780–781, Association for Computing Machinery, New York, NY, USA, 2020, ISBN: 978-1-4503-7590-0/20/11.

Abstract | BibTeX | タグ: COVID-19, GPS, Mobile sensing, Self-Tracking | Links:

50.

Zengyi Han

Context Aware Photo Protection for In-SituSharing Inproceedings

In: MobileHCI '20: Proceedings of the 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services (Doctoral Consortium), Virtual Event, Germany, 2020.

Abstract | BibTeX | タグ: Context-Aware, Face Recognition, In-situ Photo Sharing, smartphone

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