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Enhancing Transportation Mode Detection using Multi-scale Sensor Fusion and Spatial-topological Attention

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Fang ZhaoAuthors Info & Claims

UbiComp/ISWC '23 Adjunct: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing

Pages 534 - 539

https://doi.org/10.1145/3594739.3610751

Published: 08 October 2023 Publication History

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Abstract

Mobile sensors have improved traffic prediction through transportation mode recognition. Researchers are interested in exploring mobile sensor-based recognition methods for transportation modes. The SHL Recognition Challenge is a prominent competition in this field. SHL Challenge 2023 introduced a diverse dataset with GNSS-based and motion sensor data for transportation mode recognition. Our team, "we-can-fly," presents a fine-grained method using a multi-scale fusion approach that incorporates motion sensor and GNSS information. With temporal and topological attention mechanisms, we capture scene characteristics and enhance contextual understanding for transportation mode recognition. On the validation set, our method achieves an impressive 72.39% accuracy and 71.25% F1 score, confirming the effectiveness of our multimodal fusion transportation mode recognition algorithm.

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Cited By

Wang LGjoreski HCiliberto MLago PMurao KOkita TRoggen D(2023)Summary of SHL Challenge 2023: Recognizing Locomotion and Transportation Mode from GPS and Motion SensorsAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610758(575-585)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1145/3594739.3610758

Index Terms

Enhancing Transportation Mode Detection using Multi-scale Sensor Fusion and Spatial-topological Attention

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Published In

cover image ACM Conferences

UbiComp/ISWC '23 Adjunct: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing

October 2023

822 pages

ISBN:9798400702006

DOI:10.1145/3594739

Editors:
Monica Tentori
(CICESE, Mexico)
,
Nadir Weibel
(UC San Diego, USA)
,
Kristof Van Laerhoven
(University of Siegen, Germany)
,
Zhongyi Zhou
(University of Tokyo, Japan)

Copyright © 2023 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

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Published: 08 October 2023

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Research-article
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Refereed limited

Funding Sources

National Key Research and Development Program
Strategic Priority Research Program of Chinese Academy of Sciences
Key Research and Development Project from Hebei Province
Fundamental Research Funds for the Central Universities
Key Research Projects of the Joint Research Fund for Beijing Natural Science Foundation and the Fengtai Rail Transit Frontier Research Joint Fund
Open Project of the Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences
Beijing Natural Science Foundation
National Natural Science Foundation of China

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UbiComp/ISWC '23

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UbiComp/ISWC '23: The 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing

October 8 - 12, 2023

Cancun, Quintana Roo, Mexico

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

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Cited By

Wang LGjoreski HCiliberto MLago PMurao KOkita TRoggen D(2023)Summary of SHL Challenge 2023: Recognizing Locomotion and Transportation Mode from GPS and Motion SensorsAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610758(575-585)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1145/3594739.3610758

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