Indoor trajectory reconstruction using mobile devices

Risca Mukti Susanti; Kiki Maulana Adhinugraha; Sultan Alamri; Leonard Barolli; David Taniar

doi:10.1109/AINA.2018.00086

Indoor trajectory reconstruction using mobile devices

Risca Mukti Susanti, Kiki Maulana Adhinugraha, Sultan Alamri, Leonard Barolli, David Taniar

Department of Software Systems & Cybersecurity

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

6 Citations (Scopus)

Abstract

Trajectory is the path that is formed because of the moving object positioning history. Based on where it happened, trajectory can be formed in indoor or outdoor environment. While outdoor trajectory can be reconstructed by GPS technology, this technology is not sufficient to be used in indoor environment. However, there are some embedded sensors in mobile devices that can be utilized to track and reconstruct trajectory in indoor environment without utilizing GPS technology. In this paper, we propose the method to track and reconstruct trajectory for indoor environment using embedded mobiles sensors. Our experiment shows that these sensors are capable in tracking and reconstructing indoor trajectories without using any GPS technologies.

Original language	English
Title of host publication	Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018
Editors	Leonard Barolli, Makoto Takizawa, Tomoya Enokido, Marek R. Ogiela, Lidia Ogiela, Nadeem Javaid
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	550-555
Number of pages	6
ISBN (Electronic)	9781538621950, 9781538621943
ISBN (Print)	9781538621943, 9781538621967
DOIs	https://doi.org/10.1109/AINA.2018.00086
Publication status	Published - 2018
Event	International Conference on Advanced Information Networking and Applications 2018 - Krakow, Poland Duration: 16 May 2018 → 18 May 2018 Conference number: 32nd http://www.aina-conference.org/ https://ieeexplore.ieee.org/xpl/conhome/8424835/proceeding (Proceedings)

Conference

Conference	International Conference on Advanced Information Networking and Applications 2018
Abbreviated title	AINA 2018
Country/Territory	Poland
City	Krakow
Period	16/05/18 → 18/05/18
Internet address	http://www.aina-conference.org/ https://ieeexplore.ieee.org/xpl/conhome/8424835/proceeding (Proceedings)

Keywords

Accelerometer
Indoor space
Magnetometer
Mobile device
Reconstruction
Trajectory

Access to Document

10.1109/AINA.2018.00086

Cite this

Mukti Susanti, R., Maulana Adhinugraha, K., Alamri, S., Barolli, L., & Taniar, D. (2018). Indoor trajectory reconstruction using mobile devices. In L. Barolli, M. Takizawa, T. Enokido, M. R. Ogiela, L. Ogiela, & N. Javaid (Eds.), Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018 (pp. 550-555). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/AINA.2018.00086

Mukti Susanti, Risca ; Maulana Adhinugraha, Kiki ; Alamri, Sultan et al. / Indoor trajectory reconstruction using mobile devices. Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018. editor / Leonard Barolli ; Makoto Takizawa ; Tomoya Enokido ; Marek R. Ogiela ; Lidia Ogiela ; Nadeem Javaid. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. pp. 550-555

@inproceedings{0a47adbf427e4619bd0a59a065b84356,

title = "Indoor trajectory reconstruction using mobile devices",

abstract = "Trajectory is the path that is formed because of the moving object positioning history. Based on where it happened, trajectory can be formed in indoor or outdoor environment. While outdoor trajectory can be reconstructed by GPS technology, this technology is not sufficient to be used in indoor environment. However, there are some embedded sensors in mobile devices that can be utilized to track and reconstruct trajectory in indoor environment without utilizing GPS technology. In this paper, we propose the method to track and reconstruct trajectory for indoor environment using embedded mobiles sensors. Our experiment shows that these sensors are capable in tracking and reconstructing indoor trajectories without using any GPS technologies.",

keywords = "Accelerometer, Indoor space, Magnetometer, Mobile device, Reconstruction, Trajectory",

author = "{Mukti Susanti}, Risca and {Maulana Adhinugraha}, Kiki and Sultan Alamri and Leonard Barolli and David Taniar",

year = "2018",

doi = "10.1109/AINA.2018.00086",

language = "English",

isbn = "9781538621943",

pages = "550--555",

editor = "Leonard Barolli and Makoto Takizawa and Tomoya Enokido and Ogiela, {Marek R.} and Lidia Ogiela and Nadeem Javaid",

booktitle = "Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "International Conference on Advanced Information Networking and Applications 2018, AINA 2018 ; Conference date: 16-05-2018 Through 18-05-2018",

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}

Mukti Susanti, R, Maulana Adhinugraha, K, Alamri, S, Barolli, L & Taniar, D 2018, Indoor trajectory reconstruction using mobile devices. in L Barolli, M Takizawa, T Enokido, MR Ogiela, L Ogiela & N Javaid (eds), Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 550-555, International Conference on Advanced Information Networking and Applications 2018, Krakow, Poland, 16/05/18. https://doi.org/10.1109/AINA.2018.00086

Indoor trajectory reconstruction using mobile devices. / Mukti Susanti, Risca; Maulana Adhinugraha, Kiki; Alamri, Sultan et al.
Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018. ed. / Leonard Barolli; Makoto Takizawa; Tomoya Enokido; Marek R. Ogiela; Lidia Ogiela; Nadeem Javaid. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 550-555.

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

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T1 - Indoor trajectory reconstruction using mobile devices

AU - Mukti Susanti, Risca

AU - Maulana Adhinugraha, Kiki

AU - Alamri, Sultan

AU - Barolli, Leonard

AU - Taniar, David

N1 - Conference code: 32nd

PY - 2018

Y1 - 2018

N2 - Trajectory is the path that is formed because of the moving object positioning history. Based on where it happened, trajectory can be formed in indoor or outdoor environment. While outdoor trajectory can be reconstructed by GPS technology, this technology is not sufficient to be used in indoor environment. However, there are some embedded sensors in mobile devices that can be utilized to track and reconstruct trajectory in indoor environment without utilizing GPS technology. In this paper, we propose the method to track and reconstruct trajectory for indoor environment using embedded mobiles sensors. Our experiment shows that these sensors are capable in tracking and reconstructing indoor trajectories without using any GPS technologies.

AB - Trajectory is the path that is formed because of the moving object positioning history. Based on where it happened, trajectory can be formed in indoor or outdoor environment. While outdoor trajectory can be reconstructed by GPS technology, this technology is not sufficient to be used in indoor environment. However, there are some embedded sensors in mobile devices that can be utilized to track and reconstruct trajectory in indoor environment without utilizing GPS technology. In this paper, we propose the method to track and reconstruct trajectory for indoor environment using embedded mobiles sensors. Our experiment shows that these sensors are capable in tracking and reconstructing indoor trajectories without using any GPS technologies.

KW - Accelerometer

KW - Indoor space

KW - Magnetometer

KW - Mobile device

KW - Reconstruction

KW - Trajectory

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BT - Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018

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PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - International Conference on Advanced Information Networking and Applications 2018

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Mukti Susanti R, Maulana Adhinugraha K, Alamri S, Barolli L, Taniar D. Indoor trajectory reconstruction using mobile devices. In Barolli L, Takizawa M, Enokido T, Ogiela MR, Ogiela L, Javaid N, editors, Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2018. p. 550-555 doi: 10.1109/AINA.2018.00086

Indoor trajectory reconstruction using mobile devices

Abstract

Conference

Keywords

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