Publication

@inproceedings{sensys2020_selfguard,

title = {SelfGuard: Semi-Automated Activity Tracking for Enhancing Self-Protection against the COVID-19 Pandemic},

author = {Yuuki Nishiyama and Takuro Yonezawa and Kaoru Sezaki},

url = {https://youtu.be/KYmvCHl_U7g},

doi = {10.1145/3384419.3430592},

isbn = {978-1-4503-7590-0/20/11},

year  = {2020},

date = {2020-11-16},

booktitle = {the 18th ACM Conference on Embedded Networked Sensor Systems (SenSys '20), COVID-19 Pandemic Response, Virtual Event, Japan },

number = {2},

pages = {780–781},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

abstract = {Contagious diseases like COVID-19 spread periodically and threaten our lives. Self-protection, such as washing hands, wearing a mask, and staying home, are simple and practical solutions to safeguard against these diseases. Most governments and health departments recommend that people maintain self-protection. Although continuous self-protection effectively prevents the spread of infection, only the intent to self-protect is unsustainable in the long term. In this study, we design, develop, and deploy an application to track users' daily activities semi-automatically and enhance self-protection behavior using mobile sensing and gamified feedback techniques. Currently, more than 324 people have installed the app via AppStore, and 52 users have shared their activity data to our research group.},

keywords = {COVID-19, GPS, Mobile sensing, Self-Tracking},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{han2020_mobilehci,

title = {Context Aware Photo Protection for In-SituSharing},

author = {Zengyi Han},

year  = {2020},

date = {2020-10-05},

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

abstract = {People nowadays are getting used to using mobile phones for daily photography, and sharing these precious moments online or in-situ with their friends. However, there is a potential risk of privacy leakage during the in-situ photo-sharing process. To address this risk, we proposeOASIS, a cOntext Aware photoprotection for in-SItuSharing behavior: using the front camera to tell different viewers, OASIScustomize viewer’s photo gallery seamlessly between different viewers according to the context of the photo. In this way, we can provide viewers with a good sharing experience while protecting the privacy of the owner. The paper is presented at MobileHCI 2020 Doctoral Consortium.},

keywords = {Context-Aware, Face Recognition, In-situ Photo Sharing, smartphone},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ono_iccetw2020,

title = {An Information Sharing Method Using P2P and V2V Communications in VANET},

author = {Shota Ono and Fuga Kikuchi and Taku Yamazaki and Takumi Miyoshi and Kaoru Sezaki},

url = {https://edas.info/showManuscript.php?m=1570630496&ext=pdf&random=1117285026&type=stamped

http://www.icce-tw.org/index.html},

year  = {2020},

date = {2020-09-28},

booktitle = {IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW 2020)},

abstract = {For realizing information sharing among vehicles, various methods based on P2P (peer-to-peer) and V2V (vehicle-to-vehicle) communications have been proposed. However, in a case of using a P2P-based method, the network load of a source vehicle will increase due to the increase of receivers. On the other hand, in a case of using a V2V-based method, vehicles cannot communicate with each other if vehicles are far apart. In this paper, we propose an information sharing method among vehicles based on V2V and P2P communications.},

keywords = {P2P, V2V, VANET},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3410530.3414434,

title = {Towards Estimating UV Light Intensity Using GPS Signal Strength},

author = {Soichiro Higuma and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3410530.3414434

https://youtu.be/qsuyUv47M6E

https://github.com/sezakilab/M5Stack_UVLogger},

doi = {10.1145/3410530.3414434},

isbn = {9781450380768},

year  = {2020},

date = {2020-09-12},

booktitle = {Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers},

pages = {684–687},

publisher = {Association for Computing Machinery},

address = {Virtual Event, Mexico},

series = {UbiComp-ISWC '20},

abstract = {Due to recent urbanization and changing lifestyles, many people have been spending more time indoors. Hence, they tend to receive less direct sunlight than ever before. Although excessive/inadequate UV exposure can be harmful to human health leading to illnesses such as skin cancer, spots, or depression, moderate UV exposure is necessary for vitamin D production in the body. Therefore, estimating UV exposure with a commonly used device is useful for maintaining a healthy lifestyle from excessive/inadequate UV exposure in our daily life. In this study, we aim to estimate UV exposure, and to this end, we used the GPS signal strength (C/No) collected from an off-the-shelf smartphone for exploring the relationship between UV values and C/No. We conducted an experiment and measured UV values and C/No from 10 places in two different situations. From the results, we observed a significant correlation (R2 more than 0.87) between UV values and C/No when all the data were divided by the sun/shade condition. This result supports the fact that UV values potentially can be inferred from C/No to some degree if the sun/shade condition can be detected.},

keywords = {Estimation, GPS Signal Reception, Mobile sensing, UV},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3410530.3414369,

title = {Using IOS for Inconspicuous Data Collection: A Real-World Assessment},

author = {Yuuki Nishiyama and Denzil Ferreira and Wataru Sasaki and Tadashi Okoshi and Jin Nakazawa and Anind K Dey and Kaoru Sezaki},

url = {https://doi.org/10.1145/3410530.3414369

https://github.com/tetujin/AWAREFramework-iOS},

doi = {10.1145/3410530.3414369},

isbn = {9781450380768},

year  = {2020},

date = {2020-09-12},

booktitle = {Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers},

pages = {261–266},

publisher = {Association for Computing Machinery},

address = {Virtual Event, Mexico},

series = {UbiComp-ISWC '20},

abstract = {Mobile Crowd Sensing (MCS) is a method for collecting multiple sensor data from distributed mobile devices for understanding social and behavioral phenomena. The method requires collecting the sensor data 24/7, ideally inconspicuously to minimize bias. Although several MCS tools for collecting the sensor data from an off-the-shelf smartphone are proposed and evaluated under controlled conditions as a benchmark, the performance in a practical sensing study condition is scarce, especially on iOS. In this paper, we assess the data collection quality of AWARE iOS, installed on off-the-shelf iOS smartphones with 9 participants for a week. Our analysis shows that more than 97% of sensor data, provided by hardware sensors (i.e., accelerometer, location, and pedometer sensor), is successfully collected in real-world conditions, unless a user explicitly quits our data collection application.},

keywords = {Effective Data Collection, iOS, Mobile Crowd sensing, Mobile Sensing Toolkit, Real-world Assessment},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-030-50344-4_17,

title = {iOS Crowd-Sensing Won't Hurt a Bit!: AWARE Framework and Sustainable Study Guideline for iOS Platform},

author = {Yuuki Nishiyama and Denzil Ferreira and Yusaku Eigen and Wataru Sasaki and Tadashi Okoshi and Jin Nakazawa and Anind K Dey and Kaoru Sezaki},

editor = {Norbert Streitz and Shiníchi Konomi},

url = {https://www.yuukinishiyama.com/2020/07/25/hcii2020/

https://www.yuukinishiyama.com/wp-content/uploads/2020/07/AWARE-iOS_HCII2020_preprint.pdf

https://github.com/tetujin/aware-client-ios-v2

https://github.com/tetujin/AWAREFramework-iOS},

doi = {10.1007/978-3-030-50344-4_17},

isbn = {978-3-030-50344-4},

year  = {2020},

date = {2020-07-10},

booktitle = {Distributed, Ambient and Pervasive Interactions},

pages = {223--243},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The latest smartphones have advanced sensors that allow us to recognize human and environmental contexts. They operate primarily on Android and iOS, and can be used as sensing platforms for research in various fields owing to their ubiquity in society. Mobile sensing frameworks help to manage these sensors easily. However, Android and iOS are constructed following different policies, requiring developers and researchers to consider framework differences during research planning, application development, and data collection phases to ensure sustainable data collection. In particular, iOS imposes strict regulations on background data collection and application distribution. In this study, we design, implement, and evaluate a mobile sensing framework for iOS, namely AWARE-iOS, which is an iOS version of the AWARE Framework. Our performance evaluations and case studies measured over a duration of 288 h on four types of devices, show the risks of continuous data collection in the background and explore optimal practical sensor settings for improved data collection. Based on these results, we develop guidelines for sustainable data collection on iOS.},

keywords = {Data Collection Rate, Guideline, iOS, Mobile Sensing Framework, Sustainable Sensing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{kamimura2020_2020Soc,

title = {スマートフォンセンサを用いた気分情報を基にした都市空間評価手法に向けて},

author = {神村潤 and 西山勇毅 and 瀬崎薫},

url = {http://www.ieice-taikai.jp/2020society/jpn/},

year  = {2020},

date = {2020-03-17},

booktitle = {電子情報通信学会 電子情報通信学会総合大会},

address = {広島大学東広島キャンパス},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Chenwei2020_LOIS,

title = {Mobile Sensing of Pedestrian Mobility and its Assessment},

author = {Chenwei Song and Masaki Ito and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://www.ieice.org/ken/paper/20200312h1vo/eng/},

isbn = {0913-5685},

year  = {2020},

date = {2020-03-04},

booktitle = {IEICE Tech. Rep.},

volume = {119},

number = {477},

pages = {121--126},

publisher = {IEICE Technical Committee},

organization = {Life Intelligence and Office Information Systems (LOIS)},

abstract = {We propose a client-server system that provides crowd detection and mobility information. Our proposed system has the advantages of low cost and location flexibility without pre-deployed, as long as there is a sufficient number of users involved. We conducted several experiments in real environments to determine the feasibility, accuracy and applicable environment of the system. The result shows that the system can effectively capture the flow of people in the experimental area. In some cases, under the same environment, it can obtain almost the same mobility tracking information from fewer participating users than the GPS method.

},

keywords = {Bluetooth, Crowd detection, Human mobility},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{tadashi2019_ubi,

title = {人の限定合理性を超越した行動変容支援に向けた情報プラッ トフォームの設計},

author = {大越匡 and 西山勇毅 and 佐々木航 and 栄元優作 and 中澤仁},

url = {http://id.nii.ac.jp/1001/00200838/},

issn = {2188-8698},

year  = {2019},

date = {2019-12-03},

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 = {2019-UBI-64},

number = {8},

pages = {1--6},

publisher = { 情報処理学会},

series = {UBI64},

abstract = {ユビキタスコンピューティングシステムとして，例えば睡眠，食事，運動，学びといった人の多くの行動における行動変容を支援するための研究が数多くなされてきた一方，現状の取り組みは，人間が合理的であろうとするが種々の能力の限界によって限られた合理性しかもてない「限定合理性」(bounded rationality）を超えて人間を支援できていない．本研究では，この限定合理性を超越する情報技術の実現を目指し，その概念を整理し，解決手法における方針と情報アーキテクチャへの要件を明らかにする．},

keywords = {情報システム, 情報提示, 行動変容, 限定合理性},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{8885693,

title = {Channel Capacity Analysis of Diffusive DNA based Molecular Communication},

author = {Yao Sun and Masaki Ito and Kaoru Sezaki},

doi = {10.1109/WCNC.2019.8885693},

isbn = {978-1-5386-7646-2},

year  = {2019},

date = {2019-10-31},

booktitle = {2019 IEEE Wireless Communications and Networking Conference (WCNC)},

pages = {1-6},

publisher = {IEEE},

address = {Marrakesh, Morocco, Morocco},

abstract = {In this paper, we present a diffusion-based molecular communication using DNA molecules as data packets. In particular, we design a scheme utilizing the two types of nucleobase pairs to represent binary bits so that a bit sequence can be encoded onto a single DNA molecule. Therefore, the DNA molecule can be used as a data packet. Because of the stochastic character of the diffusion process and the variation of DNA diffusion coefficient correlated to the size of the molecule, namely number of base pairs composing the DNA fragment, the uncertainty of arrival order is a crucial factor that influences the reliable transmission. By modeling the observation window and focus slot, we concentrate on the order of the arriving DNA sequences. Based on the probability of each state, we derive the channel capacity of the proposed diffusive DNA based molecular communication. We also testify the effect of some parameters on the channel capacity, including base pair number, communication distance, and time slot width. Furthermore, the analysis shows that due to the high-density information encoded onto the DNA molecule, the proposed diffusive DNA based molecular communication has a higher channel capacity than other diffusion-based molecular communication.},

keywords = {channel capacity analysis, diffusion-based channel, DNA-based information packet, Molecular Communication},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3338286.3340133b,

title = {Challenges of Parkinson's Disease: User Experiences with STOP},

author = {Elina Kuosmanen and Valerii Kan and Julio Vega and Aku Visuri and Yuuki Nishiyama and Anind K Dey and Simon Harper and Denzil Ferreira},

url = {https://doi.org/10.1145/3338286.3340133},

doi = {10.1145/3338286.3340133},

isbn = {9781450368254},

year  = {2019},

date = {2019-10-05},

booktitle = {Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services},

publisher = {Association for Computing Machinery},

address = {Taipei, Taiwan},

series = {MobileHCI '19},

abstract = {Parkinson's disease (PD) is the second most common neurodegenerative disorder, impacting an estimated seven to ten million people worldwide. Measuring the symptoms and progress of the disease, and medication effectiveness is currently performed using subjective measures and visual estimation. We developed and evaluated a mobile application, STOP for tracking hand's motor symptoms, and a medication journal for recording medication intake. We followed 13 PD patients from two countries for a 1-month long real-world deployment. We found that PD patients are willing to use digital tools, such as STOP, to track their medication intake and symptoms, and are also willing to share such data with their caregivers and medical personnel to improve their own care.},

keywords = {empirical evaluation, logging, Parkinson's disease, smartphone},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{,

title = {Relay Node Controlled Routing Based on Location Information for Mobile-Assisted Ad Hoc Networks},

author = {Shota ono and Taku Yamazaki and Takumi miyoshi},

year  = {2019},

date = {2019-03-21},

booktitle = {2019 IEICE General Conference English Session},

address = {waseda university},

abstract = {In a mobile ad hoc network (MANET), general ad hoc routing protocols cause the traffic load due to control messages in route discovery process. To alleviate this, location-based routing protocols reduce them in the route discovery process. However, they degrade the performance due to movement of nodes since it is difficult to track the locations by only exchanging messages locally. To address the above issue, assuming the applications of MANET in urban areas, this paper proposes a relay node controlled ad-hoc routing which reduces the control messages based on location information obtained from a server via mobile networks.},

keywords = {AODV, location information, MANET, mobile network},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{yao2019,

title = {Buffer Aided Receiver for Diffusive DNA Based Molecular Communication},

author = {Yao Sun and Masaki Ito and Kaoru Sezaki},

url = {https://www.ieice.org/cs/ns/jpn/es-awards.html},

year  = {2019},

date = {2019-03-20},

publisher = {IEICE General Conference 2019},

address = {Japan},

keywords = {Diffusive DNA, Molecular Communication},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{,

title = {端末の位置情報に基づいた中継端末限定形アドホックルーティング},

author = {小野翔多 and 山崎託 and 三好匠},

year  = {2019},

date = {2019-02-25},

booktitle = {電子情報通信学会 信学技報},

address = {沖縄コンベンションセンター},

abstract = {MANET（Mobile ad hoc network）では，電波干渉や端末の移動による動的なトポロジーの変化によってパケット到達率が低下する問題がある．

更に，一般的なオンデマンド形の経路制御では，通信要求発生時に宛先端末との経路を構築することから，宛先端末探索のための経路要求をネットワーク全体にフラッディングする必要があり，通信資源を過剰に消費する問題がある．

この問題に対し，端末の位置情報に基づき冗長な経路要求の転送を抑制する手法が提案されている．

しかし，従来手法では，各端末が，MANET内での通信を通じて位置情報を事前に共有する必要があるため，適切な位置情報の共有が困難である問題や位置情報を共有するために通信資源を消費する問題がある．

そこで，本稿では，移動体通信を通じて各端末の位置情報の共有や管理を行い，得られた位置情報に基づき中継端末を制限する経路制御手法を提案する．

また，シミュレーションにより，既存の経路制御手法と提案手法の比較を行い有効性を評価する． },

keywords = {AODV, MANET, モバイルネットワーク, 位置情報},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{7561f51ea85a49728fc32d70873932fe,

title = {Location-based Flooding Area Restriction for Mobile-assisted Ad Hoc Networks},

author = {Shota Ono and Taku Yamazaki and Takumi Miyoshi and Kaoru Sezaki},

doi = {10.23919/APNOMS.2019.8892856},

year  = {2019},

date = {2019-01-01},

booktitle = {2019 20th Asia-Pacific Network Operations and Management Symposium},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

series = {2019 20th Asia-Pacific Network Operations and Management Symposium: Management in a Cyber-Physical World, APNOMS 2019},

abstract = {In mobile ad hoc networks, radio interference and mobility of nodes may degrade the packet arrival rate due to the dynamic topological change. Then, traditional reactive routing protocols may cause huge network resource consumption due to the route request flooding for discovering the destination. To solve the above issue, flooding area restriction methods can reduce the unnecessary control messages to narrow the flooding area based on the location information. However, each node must share location information before sending route requests via control messages. Besides, it is also difficult to share the correct location information of nodes due to the mobility of nodes. This paper proposes a flooding area restriction method to reduce the unnecessary control messages to determine the flooding area by sharing the location information via a mobile network. In addition, computer simulations reveal the effectiveness of the proposed method in comparison with a traditional routing protocol.},

note = {20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 ; Conference date: 18-09-2019 Through 20-09-2019},

keywords = {Mobile ad hoc networks, Receivers, Relays, Routing protocols, Servers, Topology},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3356995.3364541,

title = {Using Mobile Sensing Technology for Capturing People Mobility Information},

author = {Chenwei Song and Masaki Ito and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3356995.3364541},

doi = {10.1145/3356995.3364541},

isbn = {9781450369640},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility},

pages = {33–40},

publisher = {Association for Computing Machinery},

address = {Chicago, IL, USA},

series = {PredictGIS’19},

keywords = {Bluetooth, Crowd detection, Human mobility},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3307334.3328719,

title = {Capturing Subjective Time as Context and It’s Applications (Poster)},

author = {Takuro Yonezawa and Yuuki Nishiyama and Kei Hiroi and Nobuo Kawaguchi},

url = {https://doi.org/10.1145/3307334.3328719},

doi = {10.1145/3307334.3328719},

isbn = {9781450366618},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services},

pages = {647–648},

publisher = {Association for Computing Machinery},

address = {Seoul, Republic of Korea},

series = {MobiSys ’19},

abstract = {We propose an integrated framework for sensing, recognizing and utilizing of subjective time as context. Various studies on experimental psychology have showed several factors which affects subjective time. Those factors should be partially captured by ubiquitous sensors such as smartphones and wearable devices, therefore, we tackle to create common and individual model for subjective time based on the sensor data. We report our first prototype implementation for the framework based on AWARE framework with adding experience sampling method for subjective time recognition. In addition, we discuss potential applications which leveraging advantages of subjective time as context.},

keywords = {context-awareness, experience sampling method, subjective time},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3301293.3309553,

title = {Mobility Control of Mobile Sensing for Time-Varying Parameter},

author = {Yuichi Nakamura and Masaki Ito and Kaoru Sezaki},

url = {https://doi.org/10.1145/3301293.3309553},

doi = {10.1145/3301293.3309553},

isbn = {9781450362733},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications},

pages = {159},

publisher = {Association for Computing Machinery},

address = {Santa Cruz, CA, USA},

series = {HotMobile ’19},

keywords = {active sensing, kriging, Mobile sensing, sensor networks},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3338286.3340133,

title = {Challenges of Parkinson’s Disease: User Experiences with STOP},

author = {Elina Kuosmanen and Valerii Kan and Julio Vega and Aku Visuri and Yuuki Nishiyama and Anind K Dey and Simon Harper and Denzil Ferreira},

url = {https://doi.org/10.1145/3338286.3340133},

doi = {10.1145/3338286.3340133},

isbn = {9781450368254},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services},

publisher = {Association for Computing Machinery},

address = {Taipei, Taiwan},

series = {MobileHCI ’19},

abstract = {Parkinson's disease (PD) is the second most common neurodegenerative disorder, impacting an estimated seven to ten million people worldwide. Measuring the symptoms and progress of the disease, and medication effectiveness is currently performed using subjective measures and visual estimation. We developed and evaluated a mobile application, STOP for tracking hand's motor symptoms, and a medication journal for recording medication intake. We followed 13 PD patients from two countries for a 1-month long real-world deployment. We found that PD patients are willing to use digital tools, such as STOP, to track their medication intake and symptoms, and are also willing to share such data with their caregivers and medical personnel to improve their own care.},

keywords = {empirical evaluation, logging, Parkinson’s disease, smartphone},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Song2019-kl,

title = {Crowd Information System Utilizing Smartphone Bluetooth},

author = {Chenwei Song and Masaki Ito and Kaoru Sezaki},

year  = {2019},

date = {2019-01-01},

journal = {IEICE Conferences Archives},

publisher = {The Institute of Electronics, Information and Communication  Engineers},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{kitazato2018study,

title = {A Study of the Detection of Pedestrian Flow Using Bluetooth Low Energy},

author = {Tomoya Kitazato and Masaki Ito and Kaoru Sezaki},

doi = {10.1109/PERCOMW.2018.8480336},

year  = {2018},

date = {2018-10-08},

booktitle = {2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)},

pages = {716--721},

publisher = {IEEE},

address = {Athens, Greece},

organization = {IEEE},

abstract = {Analysis of human mobility data provide us many important insights. For example, a detailed analysis of human mobility in urban space can provide important insights into gathering events. This insight is useful when addressing urban planning and public safety issues, and serves as a powerful tool for solving traffic congestion, early detection of social unrest, and so on. The analysis of human mobility in an indoor space such as in a museum exhibition, can assist us in anticipating the behavior of visitors; and in the early recognition of potential problems, such as the buildup of foot traffic at specific points. However, there is no universally accepted method for easily sensing human mobility. To address this problem, we developed a novel method to detect pedestrian flow using Bluetooth Low Energy (BLE). Our approach is based on the assumption that a BLE beacon is always affixed to the pedestrian. Thus, the individual's velocity can be readily determined by analyzing the Received Signal Strength Indicator (RSSI) of their BLE beacon. Apart from velocity, the direction of the pedestrian can also be determined by detecting their BLE beacon with multiple sensors. In this investigation, we evaluated the proposed method using both experimental real-world data and simulations. Participants with BLE beacons walked straight in a hall while the RSSI of their beacons was monitored from a moving sensor. This information was used to estimate the velocities of the beacons. We also simulated the RSSIs of the beacons and estimated their velocities under various conditions. Our results indicate that the proposed method can precisely detect the velocities of pedestrians.},

keywords = {Bluetooth, Directive antennas, Global Positioning System, Laser radar, Proposals, sensors, Wireless fidelity},

pubstate = {published},

tppubtype = {inproceedings}

}