Drowsiness: modeling, prediction, and early detection systems: A statistical digital signal processing approach

By Pouyan Ebrahimbabaie

Drowsiness is a major cause of accidents in many areas of human activity, and transportation is probably the single most important source of drowsiness-related accidents. For example, one-third (1/3) of fatal accidents on highways in France are reported due to the driver falling asleep at the wheel. The large number of such driving accidents is due to the combined sheer number of road vehicles and the fact that, until recently, car manufacturers and safety authorities have taken no drastic, effective actions to prevent these accidents (even though they are generally preventable).In 2019, the European Union (EU) Parliament adopted rules requiring life-saving technologies in means. Starting in May 2022, all road vehicles sold in the EU will need to be Fitted with safety systems, including for drowsiness monitoring and intelligent speed assistance. Despite the importance of drowsiness, one can find only very few books about drowsiness. To date, the present reference is the only book that teaches different methods to design and evaluate early drowsiness detection systems. The applications of the methods presented in this book, which are based on statistical digital signal processing, are not limited to drowsiness. I strongly believe that an interested person who knows about probability theory could use these methods to design early warning systems for other applications. This book is the result of my six years of research on drowsiness.

• Format: Paperback
• Language: English
• ISBN: B08ZB91F1G
• ISBN13: 9798724207416
• Release Date: March 2021
• Publisher: Independently Published
• Length: 212 Pages
• Weight: 1.30 lbs.
• Dimensions: 0.6" x 8.0" x 10.0"