TY  - JOUR
TI  - Automatic Driver Drowsiness Detection Based on Visual Information and Artificial Intelligence
AU  - Yeshwanth Rao Bhandayker
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2019/06/30
PY  - 2019
DO  - https://doi.org/10.32628/CSEIT195369
UR  - https://ijsrcseit.com/CSEIT195369
VL  - 5
IS  - 3
SP  - 294	
EP  - 301
AB  - Drowsiness as well as Tiredness of motorists is amongst the considerable root causes of road crashes. Yearly, they raise the quantities of deaths as well as fatalities injuries globally. In this paper, a module for Advanced Motorist Aid System (ADAS) is presented to lower the number of crashes as a result of chauffeurs tiredness as well as therefore in-crease the transport safety; this system manages automatic chauffeur drowsiness detection based on aesthetic info and also Artificial Intelligence. We suggest a formula to find, track, and evaluate both the vehicle driver’s deal with and also eyes to determine PERCLOS, a scientifically supported measure of sleepiness related to slow-moving eye closure.