Low-power listen based driver drowsiness detection system using smartwatch

  • Shiyuan Zhang
  • , Hui He
  • , Zhi Wang
  • , Mingze Gao
  • , Jinsong Mao

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

6 Scopus citations

Abstract

Drowsy driving is a major cause of car accidents, because drivers are unable to swiftly perceive, process, and respond to the varying road conditions. Existing detecting solutions includes checking eye-blink, monitoring heartbeat with EEG or ECG device support, and analyzing the way the driver steers the steering wheel. Though effective, these solutions require extra hardware which causes distraction and inconvenience to the driver. We design and implement an unobtrusive and energy-efficient driver drowsiness detection system using only a commercial smartwatch through monitoring the steering behavior and heart rate of the driver. The system comprises two major modules, a hand state monitor and a drowsiness detector. The system is built by following insights. First, when the hand wearing smartwatch is off the steering wheel, no validate steering data will be captured. Thus it’s necessary to detect whether the hand is on the steering wheel to ensure the validity of the steering motion data. Second, heart rate features can reflect the alert level of the driver, and it can work no matter whether the hand is on the steering wheel. Consequently, we adopt the heart rate sensor of the smartwatch as a supplementary indicator of driver’s drowsiness level. Meanwhile, power consumption is considered given the limited smartwatch battery power. We evaluate our drowsiness detection system using a driving simulator, and it achieves an accuracy of 94.39%.

Original languageEnglish
Title of host publicationCloud Computing and Security - 4th International Conference, ICCCS 2018, Revised Selected Papers
EditorsXingming Sun, Zhaoqing Pan, Elisa Bertino
PublisherSpringer Verlag
Pages453-464
Number of pages12
ISBN (Print)9783030000172
DOIs
StatePublished - 2018
Event4th International Conference on Cloud Computing and Security, ICCCS 2018 - Haikou, China
Duration: 8 Jun 201810 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11067 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Cloud Computing and Security, ICCCS 2018
Country/TerritoryChina
CityHaikou
Period8/06/1810/06/18

Keywords

  • Drowsiness detection
  • Hand on/off steering wheel detection
  • Smartwatch built-in sensors
  • SVM

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