MOBIUS: Smart Mobility Tracking with Smartphone Sensors

Daniele Di Mitri; Khaleel Asyraaf Mat Sanusi; Kevin Trebing; Stefano Bromuri

doi:10.1007/978-3-030-76063-2_31

MOBIUS: Smart Mobility Tracking with Smartphone Sensors

Daniele Di Mitri^*, Khaleel Asyraaf Mat Sanusi, Kevin Trebing, Stefano Bromuri

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

Abstract

In this paper we introduce MOBIUS, a smartphone-based system for remote tracking of citizens’ movements. By collecting smartphone’s sensor data such as accelerometer and gyroscope, along with self-report data, the MOBIUS system allows to classify the users’ mode of transportation. With the MOBIUS app the users can also activate GPS tracking to visualise their journeys and travelling speed on a map. The MOBIUS app is an example of a tracing app which can provide more insights into how people move around in an urban area. In this paper, we introduce the motivation, the architectural design and development of the MOBIUS app. To further test its validity, we run a user study collecting data from multiple users. The collected data are used to train a deep convolutional neural network architecture which classifies the transportation modes using with a mean accuracy of 89%.

Original language	English
Title of host publication	Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings
Editors	Sara Paiva, Sérgio Ivan Lopes, Rafik Zitouni, Nishu Gupta, Sérgio F. Lopes, Takuro Yonezawa
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	462-475
Number of pages	14
ISBN (Print)	9783030760625
DOIs	https://doi.org/10.1007/978-3-030-76063-2_31
Publication status	Published - 2021
Event	6th EAI International Conference on Science and Technologies for Smart Cities, SmartCity 2020 - Virtual, Online Duration: 2 Dec 2020 → 4 Dec 2020 https://smartcity360.eai-conferences.org/2020/

Publication series

Series	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	372
ISSN	1867-8211

Conference

Conference	6th EAI International Conference on Science and Technologies for Smart Cities, SmartCity 2020
Period	2/12/20 → 4/12/20
Internet address	https://smartcity360.eai-conferences.org/2020/

Keywords

Human-activity recognition
Mobility tracking
Smart mobility
Smartphone data

Access to Document

10.1007/978-3-030-76063-2_31

Cite this

Di Mitri, D., Asyraaf Mat Sanusi, K., Trebing, K., & Bromuri, S. (2021). MOBIUS: Smart Mobility Tracking with Smartphone Sensors. In S. Paiva, S. I. Lopes, R. Zitouni, N. Gupta, S. F. Lopes, & T. Yonezawa (Eds.), Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings (pp. 462-475). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-76063-2_31

Di Mitri, Daniele ; Asyraaf Mat Sanusi, Khaleel ; Trebing, Kevin et al. / MOBIUS : Smart Mobility Tracking with Smartphone Sensors. Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings. editor / Sara Paiva ; Sérgio Ivan Lopes ; Rafik Zitouni ; Nishu Gupta ; Sérgio F. Lopes ; Takuro Yonezawa. Springer Science and Business Media Deutschland GmbH, 2021. pp. 462-475 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Vol. 372).

@inproceedings{fd57c31deec0433d8b1fad3d88de416f,

title = "MOBIUS: Smart Mobility Tracking with Smartphone Sensors",

abstract = "In this paper we introduce MOBIUS, a smartphone-based system for remote tracking of citizens{\textquoteright} movements. By collecting smartphone{\textquoteright}s sensor data such as accelerometer and gyroscope, along with self-report data, the MOBIUS system allows to classify the users{\textquoteright} mode of transportation. With the MOBIUS app the users can also activate GPS tracking to visualise their journeys and travelling speed on a map. The MOBIUS app is an example of a tracing app which can provide more insights into how people move around in an urban area. In this paper, we introduce the motivation, the architectural design and development of the MOBIUS app. To further test its validity, we run a user study collecting data from multiple users. The collected data are used to train a deep convolutional neural network architecture which classifies the transportation modes using with a mean accuracy of 89%.",

keywords = "Human-activity recognition, Mobility tracking, Smart mobility, Smartphone data",

author = "{Di Mitri}, Daniele and {Asyraaf Mat Sanusi}, Khaleel and Kevin Trebing and Stefano Bromuri",

note = "Funding Information: The authors gratefully acknowledge financial supports from the China 973 Research Program (2015CB251303 and 2015CB251301), the Key Technologies RandD Program of Jiangsu (BE2015199), and National Natural Science Foundation of China (21406231). Publisher Copyright: {\textcopyright} 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 6th EAI International Conference on Science and Technologies for Smart Cities, SmartCity 2020 ; Conference date: 02-12-2020 Through 04-12-2020",

year = "2021",

doi = "10.1007/978-3-030-76063-2_31",

language = "English",

isbn = "9783030760625",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "462--475",

editor = "Sara Paiva and Lopes, {S{\'e}rgio Ivan} and Rafik Zitouni and Nishu Gupta and Lopes, {S{\'e}rgio F.} and Takuro Yonezawa",

booktitle = "Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings",

address = "Germany",

url = "https://smartcity360.eai-conferences.org/2020/",

}

Di Mitri, D, Asyraaf Mat Sanusi, K, Trebing, K & Bromuri, S 2021, MOBIUS: Smart Mobility Tracking with Smartphone Sensors. in S Paiva, SI Lopes, R Zitouni, N Gupta, SF Lopes & T Yonezawa (eds), Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings. Springer Science and Business Media Deutschland GmbH, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 372, pp. 462-475, 6th EAI International Conference on Science and Technologies for Smart Cities, SmartCity 2020, 2/12/20. https://doi.org/10.1007/978-3-030-76063-2_31

MOBIUS: Smart Mobility Tracking with Smartphone Sensors. / Di Mitri, Daniele; Asyraaf Mat Sanusi, Khaleel; Trebing, Kevin et al.
Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings. ed. / Sara Paiva; Sérgio Ivan Lopes; Rafik Zitouni; Nishu Gupta; Sérgio F. Lopes; Takuro Yonezawa. Springer Science and Business Media Deutschland GmbH, 2021. p. 462-475 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Vol. 372).

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

TY - GEN

T1 - MOBIUS

T2 - 6th EAI International Conference on Science and Technologies for Smart Cities, SmartCity 2020

AU - Di Mitri, Daniele

AU - Asyraaf Mat Sanusi, Khaleel

AU - Trebing, Kevin

AU - Bromuri, Stefano

N1 - Funding Information: The authors gratefully acknowledge financial supports from the China 973 Research Program (2015CB251303 and 2015CB251301), the Key Technologies RandD Program of Jiangsu (BE2015199), and National Natural Science Foundation of China (21406231). Publisher Copyright: © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

PY - 2021

Y1 - 2021

N2 - In this paper we introduce MOBIUS, a smartphone-based system for remote tracking of citizens’ movements. By collecting smartphone’s sensor data such as accelerometer and gyroscope, along with self-report data, the MOBIUS system allows to classify the users’ mode of transportation. With the MOBIUS app the users can also activate GPS tracking to visualise their journeys and travelling speed on a map. The MOBIUS app is an example of a tracing app which can provide more insights into how people move around in an urban area. In this paper, we introduce the motivation, the architectural design and development of the MOBIUS app. To further test its validity, we run a user study collecting data from multiple users. The collected data are used to train a deep convolutional neural network architecture which classifies the transportation modes using with a mean accuracy of 89%.

AB - In this paper we introduce MOBIUS, a smartphone-based system for remote tracking of citizens’ movements. By collecting smartphone’s sensor data such as accelerometer and gyroscope, along with self-report data, the MOBIUS system allows to classify the users’ mode of transportation. With the MOBIUS app the users can also activate GPS tracking to visualise their journeys and travelling speed on a map. The MOBIUS app is an example of a tracing app which can provide more insights into how people move around in an urban area. In this paper, we introduce the motivation, the architectural design and development of the MOBIUS app. To further test its validity, we run a user study collecting data from multiple users. The collected data are used to train a deep convolutional neural network architecture which classifies the transportation modes using with a mean accuracy of 89%.

KW - Human-activity recognition

KW - Mobility tracking

KW - Smart mobility

KW - Smartphone data

U2 - 10.1007/978-3-030-76063-2_31

DO - 10.1007/978-3-030-76063-2_31

M3 - Conference Article in proceeding

AN - SCOPUS:85111166524

SN - 9783030760625

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 462

EP - 475

BT - Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings

A2 - Paiva, Sara

A2 - Lopes, Sérgio Ivan

A2 - Zitouni, Rafik

A2 - Gupta, Nishu

A2 - Lopes, Sérgio F.

A2 - Yonezawa, Takuro

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 2 December 2020 through 4 December 2020

ER -

Di Mitri D, Asyraaf Mat Sanusi K, Trebing K, Bromuri S. MOBIUS: Smart Mobility Tracking with Smartphone Sensors. In Paiva S, Lopes SI, Zitouni R, Gupta N, Lopes SF, Yonezawa T, editors, Science and Technologies for Smart Cities - 6th EAI International Conference, SmartCity360°, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 462-475. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Vol. 372). doi: 10.1007/978-3-030-76063-2_31

MOBIUS: Smart Mobility Tracking with Smartphone Sensors

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