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Exploring the usefulness of bluetooth and wifi proximity for transportation mode recognition

Published: 09 September 2019 Publication History

Abstract

Understanding the mobility patterns of large groups of people is essential in transport planning. Today's assessments rely on questionnaires or self-reported data, which are cumbersome, expensive, and prone to errors. With recent developments in mobile and ubiquitous computing, it has become feasible to automate this process and classify transportation modes using data collected by users' smartphones. Previous work has mainly considered GPS and accelerometers; however, the achieved accuracies were often insufficient. We propose a novel method which also considers the proximity patterns of WiFi and Bluetooth (BT) devices in the environment, which are expected to be quite specific to the different transportation modes. In this poster, we present the promising results of a preliminary study in Zurich.

References

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Shih Hau Fang, Hao Hsiang Liao, Yu Xiang Fei, Kai Hsiang Chen, Jen Wei Huang, Yu Ding Lu, and Yu Tsao. 2016. Transportation Modes Classification Using Sensors on Smartphones. Sensors 16, 8 (Aug. 2016).
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Min Y. Mun, Deborah Estrin, Jeff Burke, and Mark H. Hansen. 2008. Parsimonious mobility classification using GSM and WiFi traces. In Proc. of the 5th Workshop on Embedded Networked Sensors (EmNets). 1--5.
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Meng-Chieh Yu, Tong Yu, Shao-Chen Wang, Chih-Jen Lin, and Edward Y. Chang. 2014. Big Data Small Footprint: The Design of a Low-power Classifier for Detecting Transportation Modes. Proc. VLDB Endow. 7, 13 (Aug. 2014), 1429--1440.
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Yu Zheng, Yukun Chen, Quannan Li, Xing Xie, and Wei-Ying Ma. 2010. Understanding transportation modes based on GPS data for web applications. ACM Transactions on the Web 4, 1 (2010), 1--36. arXiv:arXiv:1011.1669v3
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Cited By

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  • (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
  • (2023)Recognize Locomotion and Transportation Modes from Wi-Fi Traces via Lightweight Models2023 International Conference on Future Communications and Networks (FCN)10.1109/FCN60432.2023.10544151(1-6)Online publication date: 17-Dec-2023
  • (2023) Smartphone-Based CO 2 e Emission Estimation Using Transportation Mode Classification IEEE Access10.1109/ACCESS.2023.328130711(54782-54794)Online publication date: 2023
  • Show More Cited By

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Published In

cover image ACM Conferences
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
September 2019
1234 pages
ISBN:9781450368698
DOI:10.1145/3341162
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 September 2019

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Author Tags

  1. classification
  2. random forest
  3. transport planning
  4. transportation mode recognition

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UbiComp '19

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

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Cited By

View all
  • (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
  • (2023)Recognize Locomotion and Transportation Modes from Wi-Fi Traces via Lightweight Models2023 International Conference on Future Communications and Networks (FCN)10.1109/FCN60432.2023.10544151(1-6)Online publication date: 17-Dec-2023
  • (2023) Smartphone-Based CO 2 e Emission Estimation Using Transportation Mode Classification IEEE Access10.1109/ACCESS.2023.328130711(54782-54794)Online publication date: 2023
  • (2022)A Review of Wi-Fi-Based Traffic Detection Technology in the Field of Intelligent Transportation SystemsBuildings10.3390/buildings1204042812:4(428)Online publication date: 1-Apr-2022
  • (2022)Urban Transportation Mode Detection From Inertial and Barometric Data in Pedestrian MobilityIEEE Sensors Journal10.1109/JSEN.2021.306584822:6(4772-4780)Online publication date: 15-Mar-2022
  • (2021)Data Mining for Transportation Mode Recognition from Radio-dataAdjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479374(423-427)Online publication date: 21-Sep-2021
  • (2021)Locomotion and Transportation Mode Recognition from GPS and Radio Signals: Summary of SHL Challenge 2021Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479373(412-422)Online publication date: 21-Sep-2021
  • (2021)Kick-scooters detection in sensor-based transportation mode classification methodsIFAC-PapersOnLine10.1016/j.ifacol.2021.06.04354:2(81-86)Online publication date: 2021

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