Grant: Collaborative Research and Development Grants
Ryerson University
$98,333.00
A cloud based multimodal biometrics framework for road safety
EF 2018-19
Résumé
Alcohol-impaired driving caused 55% of fatal crashes among 16 to 25 years old in Canada in 2009, which is the leading cause of death in this age group. Therefore, ensuring that a driver is not impaired by alcohol is critical to improve road safety in Canada. Drowsy driving is another serious problem on Canada's roadways. Research by the Ontario Ministry of Transportation indicates that about 26% of all fatal and injury crashes are related to drowsiness while driving.* Collaborating with Alcohol Countermeasure Systems (ACS) Corp. , we will investigate a novel cloud-based multimodal biometrics framework to address the issues of continuous authentication and drowsiness detection, aiming to enhance road safety in Canada. Technically, we will apply computer vision, pattern recognition, and information theory to address the following research problems: 1) cloud based multimodal biometrics extraction: to extract the driver's multimodal biometrics of face, facial expression, eye movement, electrocardiogram (ECG) signal and Heart Rate Variability (HRV) signal at the cloud server; 2) continuous driver authentication: to continuously identify if the person driving the vehicle is the person who has started the engine based on face, facial expression, and ECG signal; 3) drowsiness detection: to accurately detect the drowsiness status based on eye movement, yawning and HRV signal, and alert the driver to prevent from crashes.* The research carried out in this project will result in the development of new road safety devices that will accurately and automatically authenticate the driver or alert a drowsy driver by incorporating multiple biometric traits. The outcome of the project will assist ACS in achieving further technical success and sales of interlock systems and drowsiness detection devices at home and abroad. Furthermore, the success of this project will promote Canada's R&D capability in multimedia and information technology internationally, and strengthen the competitiveness of Canada's products in the world market.*
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
486201-2015
Name nom
Guan, Ling
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2015
Award amount
98333
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2708
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Image processing
Research subject fr
Traitement des images
Partie
3
Nb partie
3
Application title
A cloud based multimodal biometrics framework for road safety
Keyword
NSERC
Application summary
Alcohol-impaired driving caused 55% of fatal crashes among 16 to 25 years old in Canada in 2009, which is the leading cause of death in this age group. Therefore, ensuring that a driver is not impaired by alcohol is critical to improve road safety in Canada. Drowsy driving is another serious problem on Canada's roadways. Research by the Ontario Ministry of Transportation indicates that about 26% of all fatal and injury crashes are related to drowsiness while driving.* Collaborating with Alcohol Countermeasure Systems (ACS) Corp. , we will investigate a novel cloud-based multimodal biometrics framework to address the issues of continuous authentication and drowsiness detection, aiming to enhance road safety in Canada. Technically, we will apply computer vision, pattern recognition, and information theory to address the following research problems: 1) cloud based multimodal biometrics extraction: to extract the driver's multimodal biometrics of face, facial expression, eye movement, electrocardiogram (ECG) signal and Heart Rate Variability (HRV) signal at the cloud server; 2) continuous driver authentication: to continuously identify if the person driving the vehicle is the person who has started the engine based on face, facial expression, and ECG signal; 3) drowsiness detection: to accurately detect the drowsiness status based on eye movement, yawning and HRV signal, and alert the driver to prevent from crashes.* The research carried out in this project will result in the development of new road safety devices that will accurately and automatically authenticate the driver or alert a drowsy driver by incorporating multiple biometric traits. The outcome of the project will assist ACS in achieving further technical success and sales of interlock systems and drowsiness detection devices at home and abroad. Furthermore, the success of this project will promote Canada's R&D capability in multimedia and information technology internationally, and strengthen the competitiveness of Canada's products in the world market.*
