A Smartphone-based Driver Safety Monitoring System using Data Fusion

Boon Giin Lee, Wan Young Chung

Research output: Journal PublicationArticlepeer-review

95 Citations (Scopus)

Abstract

This paper proposes a method for monitoring driver safety levels using a data fusion approach based on several discrete data types: eye features, bio-signal variation, in-vehicle temperature, and vehicle speed. The driver safety monitoring system was developed in practice in the form of an application for an Android-based smartphone device, where measuring safety-related data requires no extra monetary expenditure or equipment. Moreover, the system provides high resolution and flexibility. The safety monitoring process involves the fusion of attributes gathered from different sensors, including video, electrocardiography, photoplethysmography, temperature, and a three-axis accelerometer, that are assigned as input variables to an inference analysis framework. A Fuzzy Bayesian framework is designed to indicate the driver's capability level and is updated continuously in real-time. The sensory data are transmitted via Bluetooth communication to the smartphone device. A fake incoming call warning service alerts the driver if his or her safety level is suspiciously compromised. Realistic testing of the system demonstrates the practical benefits of multiple features and their fusion in providing a more authentic and effective driver safety monitoring.

Original languageEnglish
Pages (from-to)17536-17552
Number of pages17
JournalSensors
Volume12
Issue number12
DOIs
Publication statusPublished - Dec 2012
Externally publishedYes

Keywords

  • Android-based smartphone
  • Bio-signal variation
  • Bluetooth
  • Driver safety
  • Electrocardiography
  • Eye features
  • Fuzzy Bayesian
  • Photoplethysmography
  • Temperature sensor
  • Three-axis accelerometer

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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