WiBot! In-vehicle behaviour and gesture recognition using wireless network edge

Muneeba Raja, Viviane Ghaderi, Stephan Sigg

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

22 Citations (Scopus)
253 Downloads (Pure)

Abstract

Recent advancements in vehicular technology have meant that integrated wireless devices such as Wi-Fi access points or bluetooth are deployed in vehicles at an increasingly dense scale. These vehicular network edge devices, while enabling in car wireless connectivity and infotainment services, can also be exploited as sensors to improve environmental and behavioural awareness that in turn can provide better and more personalised driver feedback and improve road safety. We present WiBot! a network-edge based behaviour recognition and gesture based personal assistant system for cars. WiBot leverages the vehicular network edge to detect distracted behaviour based on unusual head turns and arm movements during driving situations by monitoring radio frequency fluctuation patterns in real-time. Additionally, WiBot can recognise known gestures from natural arm movements while driving and use such gestures for passenger-car interaction. A key element of WiBot design is its impulsive windowing approach that allows start and end of gestures to be accurately identified in a continuous stream of data. We validate the system in a realistic driving environment by conducting a non-choreographed continuous recognition study with 40 participants at BMW Group Research, New Technologies and Innovation centre. By combining impulsive windowing with a unique selection of features from peaks and subcarrier analysis of RF CSI phase information, the system is able to achieve 94.5% accuracy for head-vs. arm movement separation. We can further confidently differentiate relevant gestures from random arm and head movements, head turns and idle movement with 90.5% accuracy.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 38th International Conference on Distributed Computing Systems, ICDCS 2018
PublisherIEEE
Pages376-387
Number of pages12
Volume2018-July
ISBN (Electronic)9781538668719
ISBN (Print)978-1-5386-6872-6
DOIs
Publication statusPublished - 19 Jul 2018
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Distributed Computing Systems - Vienna, Austria
Duration: 2 Jul 20185 Jul 2018
Conference number: 38

Publication series

NameInternational Conference on Distributed Computing Systems
ISSN (Electronic)2575-8411

Conference

ConferenceInternational Conference on Distributed Computing Systems
Abbreviated titleICDCS
Country/TerritoryAustria
CityVienna
Period02/07/201805/07/2018

Keywords

  • Behaviour recognition
  • Device free sensing
  • Distracted behaviour recognition
  • Emotion sensing
  • Machinelearning
  • Mood sensing
  • Pervasivecomputing
  • Ubiquitous learning
  • Wifisensors

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