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A Smartphone-Based Driver Safety Monitoring System Using Data Fusion
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 applicati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571852/ https://www.ncbi.nlm.nih.gov/pubmed/23247416 http://dx.doi.org/10.3390/s121217536 |
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author | Lee, Boon-Giin Chung, Wan-Young |
author_facet | Lee, Boon-Giin Chung, Wan-Young |
author_sort | Lee, Boon-Giin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3571852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-35718522013-02-19 A Smartphone-Based Driver Safety Monitoring System Using Data Fusion Lee, Boon-Giin Chung, Wan-Young Sensors (Basel) Article 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. Molecular Diversity Preservation International (MDPI) 2012-12-17 /pmc/articles/PMC3571852/ /pubmed/23247416 http://dx.doi.org/10.3390/s121217536 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Lee, Boon-Giin Chung, Wan-Young A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title | A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title_full | A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title_fullStr | A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title_full_unstemmed | A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title_short | A Smartphone-Based Driver Safety Monitoring System Using Data Fusion |
title_sort | smartphone-based driver safety monitoring system using data fusion |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571852/ https://www.ncbi.nlm.nih.gov/pubmed/23247416 http://dx.doi.org/10.3390/s121217536 |
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