EnTrans : Leveraging Kinetic Energy Harvesting Signal for Transportation Mode Detection

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

6 Scopus Citations
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Author(s)

  • Guohao Lan
  • Dong Ma
  • Sara Khalifa
  • Mahbub Hassan
  • Wen Hu

Detail(s)

Original languageEnglish
Article number8730510
Pages (from-to)2816-2827
Number of pages12
Journal / PublicationIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number7
Online published4 Jun 2019
Publication statusPublished - Jul 2020
Externally publishedYes

Abstract

Monitoring the daily transportation modes of an individual provides useful information in many application domains, such as urban design, real-time journey recommendation, and providing location-based services. In existing systems, accelerometer and GPS are the dominantly used signal sources for transportation context monitoring which drain out the limited battery life of the wearable devices very quickly. To resolve the high energy consumption issue, in this paper, we present EnTrans, which enables transportation mode detection by using only the kinetic energy harvester as an energy-efficient signal source. The proposed idea is based on the intuition that the vibrations experienced by the passenger during traveling with different transportation modes are distinctive. Thus, voltage signal generated by the energy harvesting devices should contain sufficient features to distinguish different transportation modes. We evaluate our system using over 28 h of data, which is collected by eight individuals using a practical energy harvesting prototype. The evaluation results demonstrate that EnTrans is able to achieve an overall accuracy over 92% in classifying five different modes while saving more than 34% of the system power compared to conventional accelerometer-based approaches.

Research Area(s)

  • energy harvesting, sparse representation, Transportation mode detection, wearable devices

Citation Format(s)

EnTrans : Leveraging Kinetic Energy Harvesting Signal for Transportation Mode Detection. / Lan, Guohao; Xu, Weitao; Ma, Dong; Khalifa, Sara; Hassan, Mahbub; Hu, Wen.

In: IEEE Transactions on Intelligent Transportation Systems, Vol. 21, No. 7, 8730510, 07.2020, p. 2816-2827.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review