Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3267305.3267510acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
research-article

Study of LoRaWAN Technology for Activity Recognition

Published: 08 October 2018 Publication History

Abstract

In this paper, we explore LoRaWAN (Long Range Wide Area Network) sensor for human activity recognition. In this research, we want to explore relation between packet loss and activity recognition accuracy from LoRaWAN sensor data. We want to estimate the packet loss amount from realistic sensors. In LoRaWAN technology, the amount of sensor nodes connected with a single gateway have an impact on the performance of sensors ultimate data sending capability in terms of packet loss. By exploring a single gateway, we transfer the LoRaWAN sensor data to the cloud platform successfully. We evaluate LoRaWAN accelerometer sensors data for human activity recognition. We explore the Linear Discriminant Analysis (LDA), Random Forest (RnF) and K-Nearest Neighbor (KNN) for classification. We achieve recognition accuracy of 94.44% by LDA, 84.72% by RnF and 98.61% by KNN. Then we simulate the packet loss environment in our dataset to explore the relation between packet loss and accuracy. In real caregiving center, we did experiment with 42 LoRaWAN sensors node connectivity and data transfer ability to evaluate the packet received and packet loss performance with LoRaWAN sensors.

References

[1]
Md Atiqur Rahman Ahad, Motion History Images for Action Recognition and Understanding, ISBN: 978-1-4471-4730-5, Springer, 2012.
[2]
Md Atiqur Rahman Ahad, Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding, ISBN: 978-94-91216-20-6, available in Springer, 2011.
[3]
M. Centenaro, L. Vangelista, A. Zanella, and M. Zorzi, Long-range communications in unlicensed bands: The rising stars in the IoT and smart city scenarios, IEEE J. Wirel. Comm. Vol. 23, No. 5, pp. 60--67, 2016.
[4]
A.M. Baharudin and W. Yan, Long-range wireless sensor networks for geolocation tracking: Design and evaluation, Proc. of IES, pp. 76--80, 2016.
[5]
W. Guibene, J. Nowack, N. Chalikias, and M. Kelly, Evaluation of LPWAN technologies for smart cities: River monitoring use-case, Proc. of WCNCW, pp. 17--22, 2017.
[6]
O. Vondrous, Z. Kocur, T. Hegr, and O. Slavicek, Performance evaluation of IoT mesh networking technology in ISM frequency band, Proc. of ME, 2016.
[7]
Tahera Hossain, Hiroki Goto, Md Atiqur Rahman Ahad, and Sozo Inoue, Study of activity recognition having missing data, Joint 7th Int. Conf. on Informatics, Electronics & Vision; 2nd Int. Conf. on Imaging, Vision & Pattern Recognition, pp. 556--561, 2018.
[8]
SORACOM Air for LoRaWAN, (accessed on Jan. 2018) https://soracom.jp/services/air/lora/
[9]
A. Augustin, J. Yi, T. Clausen, and W. Townsley, A Study of LoRa: Long Range & Low Power Networks for the Internet of Things, Sensors, 2016.
[10]
P. Neumann, J. Montavond, and T. Noel, Indoor deployment of Low-Power Wide Area Networks (LPWAN): A LoRaWAN case study. IEEE 12th Int. Conf. on Wireless and Mobile Computing, Networking and Com., 2016.
[11]
J. Petajajarvi, K. Mikhaylov, A. Roivainen, T. Hanninen, and M. Pettissalo, On the coverage of LPWANs: Range evaluation and channel attenuation model for LoRa technology, 14th Int. Conf. on ITS Telecom., 2015.
[12]
D. Bankov, E. Khorov, and A. Lyakhov, On the limits of LoRaWAN channel access, Int. Conf. on Engineering and Telecom., 2016.
[13]
D. Bankov, E. Khorov, and A. Lyakhov, Mathematical model of LoRaWAN channel access. 18th Int. Symp. on A World of Wireless, Mobile and Multimedia Networks, 2017.

Cited By

View all
  • (2024)A Survey of LoRaWAN-Integrated Wearable Sensor Networks for Human Activity Recognition: Applications, Challenges and Possible SolutionsIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34840025(6713-6735)Online publication date: 2024
  • (2023)Gait Recognition Algorithm of Coal Mine Personnel Based on LoRaApplied Sciences10.3390/app1312728913:12(7289)Online publication date: 19-Jun-2023
  • (2023)AI-ERA: Artificial Intelligence-Empowered Resource Allocation for LoRa-Enabled IoT ApplicationsIEEE Transactions on Industrial Informatics10.1109/TII.2023.324807419:12(11640-11652)Online publication date: Dec-2023
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
UbiComp '18: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
October 2018
1881 pages
ISBN:9781450359665
DOI:10.1145/3267305
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 October 2018

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Activity Recognition
  2. Healthcare
  3. LPWA Technologies
  4. LoRaWAN Sensor

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

UbiComp '18
Sponsor:

Acceptance Rates

Overall Acceptance Rate 764 of 2,912 submissions, 26%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)16
  • Downloads (Last 6 weeks)2
Reflects downloads up to 27 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2024)A Survey of LoRaWAN-Integrated Wearable Sensor Networks for Human Activity Recognition: Applications, Challenges and Possible SolutionsIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34840025(6713-6735)Online publication date: 2024
  • (2023)Gait Recognition Algorithm of Coal Mine Personnel Based on LoRaApplied Sciences10.3390/app1312728913:12(7289)Online publication date: 19-Jun-2023
  • (2023)AI-ERA: Artificial Intelligence-Empowered Resource Allocation for LoRa-Enabled IoT ApplicationsIEEE Transactions on Industrial Informatics10.1109/TII.2023.324807419:12(11640-11652)Online publication date: Dec-2023
  • (2022)LoRa Networking Techniques for Large-scale and Long-term IoT: A Down-to-top SurveyACM Computing Surveys10.1145/349467355:3(1-36)Online publication date: 3-Feb-2022
  • (2021)Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and BeyondSustainability10.3390/su1308451113:8(4511)Online publication date: 19-Apr-2021
  • (2021)The Variegated Applications of Deep Learning Techniques in Human Activity RecognitionProceedings of the 2021 Thirteenth International Conference on Contemporary Computing10.1145/3474124.3474156(223-233)Online publication date: 5-Aug-2021
  • (2020)A Method for Sensor-Based Activity Recognition in Missing Data ScenarioSensors10.3390/s2014381120:14(3811)Online publication date: 8-Jul-2020
  • (2020)Exploring LoRa for Long-range Through-wall SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33973264:2(1-27)Online publication date: 15-Jun-2020
  • (2020)Combating interference for long range LoRa sensingProceedings of the 18th Conference on Embedded Networked Sensor Systems10.1145/3384419.3430731(69-81)Online publication date: 16-Nov-2020
  • (2020)Device free human gesture recognition using Wi-Fi CSIEngineering Applications of Artificial Intelligence10.1016/j.engappai.2019.10328187:COnline publication date: 1-Jan-2020
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media