Anti-Sleep Alarm with Vehicle Speed Reducer and Accident Alarm + Location Detector
Abstract
References
Singh, S., Papanikolopoulos, N.P. Monitoring Driver Fatigue Using Facial Analysis Techniques. IEEE Transactions on Intelligent Transportation Systems. 1999, 1(2), 122– 131p.
Ji, Q., Yang, X. Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance. Real-Time Imaging. 2002, 8(5), 357–377p.
Bergasa, L.M. et al. Real-Time System for Monitoring Driver Vigilance. IEEE Transactions on Intelligent Transportation Systems. 2006, 7(1), 63–77p.
Abulkhair, M., Naji, A. Intelligent Accident Detection and Alert System Using GSM and GPS Technologies. International Journal of Engineering Research and Applications. 2013, 3(4), 123–129p.
Sharma, A., Kumar, R. Vehicle Accident Detection and Reporting System Using GSM and GPS. International Journal of Computer Applications. 2015, 112(9), 15–19p.
D’Orazio, T., Leo, M. A Review of Vision-Based Driver Monitoring Systems. Journal of Real-Time Image Processing. 2010, 5(2), 89–104p.
Mohan, D., Tsimhoni, O. Driver Behavior and Fatigue Analysis in Intelligent Transportation Systems. Transportation Research Part F. 2009, 12(5), 456–468p.
Arduino. Arduino Uno Technical Specifications. Arduino Official Documentation. 2018.
Lee, J.D., Young, K.L. Driver Distraction and Fatigue in Intelligent Vehicles. Human Factors Journal. 2008, 50(3), 391–404p.
World Health Organization. Global Status Report on Road Safety. WHO Press. 2018.
Refbacks
- There are currently no refbacks.