In order to prevent road crashes caused by human error it is very much necessary to develop systems that monitor factors such as alcohol, sleepiness, distraction, stress, and fatigue including physical health conditions. All these factors contribute to human errors and can result in accidents on the road. The proposed project will provide tools for the development of safety systems including a basis to continuously monitor and predict driver’s mental and physical (health) situation and based on these, can carry out suitable counter measurements to prevent/reduce accidents. Due to the latest advances in car development, these solutions can be implemented in future cars. Also, people are more aware of their own safety than they were previously and such solutions will be welcomed gradually by more safety aware drivers.
|First Name||Last Name||Title|
|Mobyen Uddin||Ahmed||Postdoctoral research fellow|
Vision-Based Remote Heart Rate Variability Monitoring using Camera (Oct 2017) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum 4th EAI International Conference on IoT Technologies for HealthCare (HealthyIOT'17)
Deep Learning based Person Identification using Facial Images (Oct 2017) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum 4th EAI International Conference on IoT Technologies for HealthCare (HealthyIOT'17)
In-Vehicle Stress Monitoring Based on EEG Signal (Jul 2017) Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed International Journal of Engineering Research and Applications (IJERA)
Internet of Things Technologies for HealthCare (Jan 2017) Mobyen Uddin Ahmed, Shahina Begum, Wasim Raad The 3rd EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'16)
A Case-Based Classification for Drivers’ Alcohol Detection Using Physiological Signals (Oct 2016) Hamidur Rahman, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Bertil Hök The 3rd EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'16)