Real-time adaptive data filtering with multiple sensors for indoor monitoring

Kuon Akiyama; Ryoichi Shinkuma; Jun Shiomi

doi:10.1109/NOMS54207.2022.9789786

Real-time adaptive data filtering with multiple sensors for indoor monitoring

Kuon Akiyama, Ryoichi Shinkuma, Jun Shiomi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

This demonstration proposes a scheme that suppresses the data size of a 3D-image sensing network by adaptively filtering low-importance points, such as the points of floors and ceilings when the task is to track pedestrians. The adaptive filter can be dynamically changed to further reduce the amount of data if it is difficult for packets to reach the edge computer. We evaluate the proposed scheme through experiments and demonstrate that it performs better than benchmark schemes in terms of prompt arrival of the data.

Original language	English
Title of host publication	Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022
Subtitle of host publication	Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022
Editors	Pal Varga, Lisandro Zambenedetti Granville, Alex Galis, Istvan Godor, Noura Limam, Prosper Chemouil, Jerome Francois, Marc-Oliver Pahl
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665406017
DOIs	https://doi.org/10.1109/NOMS54207.2022.9789786
Publication status	Published - 2022
Event	2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022 - Budapest, Hungary Duration: 2022 Apr 25 → 2022 Apr 29

Publication series

Name	Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022

Conference

Conference	2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022
Country/Territory	Hungary
City	Budapest
Period	22/4/25 → 22/4/29

Keywords

3D image sensing
LIDAR
adaptive filtering
sensor network
smart monitoring

ASJC Scopus subject areas

Management of Technology and Innovation
Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Software
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/NOMS54207.2022.9789786

Cite this

Akiyama, K., Shinkuma, R., & Shiomi, J. (2022). Real-time adaptive data filtering with multiple sensors for indoor monitoring. In P. Varga, L. Z. Granville, A. Galis, I. Godor, N. Limam, P. Chemouil, J. Francois, & M-O. Pahl (Eds.), Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022 (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NOMS54207.2022.9789786

Real-time adaptive data filtering with multiple sensors for indoor monitoring. / Akiyama, Kuon; Shinkuma, Ryoichi; Shiomi, Jun.
Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. ed. / Pal Varga; Lisandro Zambenedetti Granville; Alex Galis; Istvan Godor; Noura Limam; Prosper Chemouil; Jerome Francois; Marc-Oliver Pahl. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Akiyama, K, Shinkuma, R & Shiomi, J 2022, Real-time adaptive data filtering with multiple sensors for indoor monitoring. in P Varga, LZ Granville, A Galis, I Godor, N Limam, P Chemouil, J Francois & M-O Pahl (eds), Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022, Budapest, Hungary, 22/4/25. https://doi.org/10.1109/NOMS54207.2022.9789786

Akiyama K, Shinkuma R, Shiomi J. Real-time adaptive data filtering with multiple sensors for indoor monitoring. In Varga P, Granville LZ, Galis A, Godor I, Limam N, Chemouil P, Francois J, Pahl M-O, editors, Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022). doi: 10.1109/NOMS54207.2022.9789786

Akiyama, Kuon ; Shinkuma, Ryoichi ; Shiomi, Jun. / Real-time adaptive data filtering with multiple sensors for indoor monitoring. Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. editor / Pal Varga ; Lisandro Zambenedetti Granville ; Alex Galis ; Istvan Godor ; Noura Limam ; Prosper Chemouil ; Jerome Francois ; Marc-Oliver Pahl. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022).

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abstract = "This demonstration proposes a scheme that suppresses the data size of a 3D-image sensing network by adaptively filtering low-importance points, such as the points of floors and ceilings when the task is to track pedestrians. The adaptive filter can be dynamically changed to further reduce the amount of data if it is difficult for packets to reach the edge computer. We evaluate the proposed scheme through experiments and demonstrate that it performs better than benchmark schemes in terms of prompt arrival of the data.",

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note = "Funding Information: V. ACKNOWLEDGEMENT This work was supported in part by JST PRESTO no. JPMJPR1854, JST SBIR-1 no. JPMJST2151, and JSPS KAK-ENHI no. 21H03427, Japan. The evaluation results were partly obtained from research commissioned by NICT, Japan. Funding Information: This work was supported in part by JST PRESTO no. JPMJPR1854, JST SBIR-1 no. JPMJST2151, and JSPS KAKENHI no. 21H03427, Japan. The evaluation results were partly obtained from research commissioned by NICT, Japan. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022 ; Conference date: 25-04-2022 Through 29-04-2022",

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doi = "10.1109/NOMS54207.2022.9789786",

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Real-time adaptive data filtering with multiple sensors for indoor monitoring

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Keywords

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