This SpringerBrief presents the fundamentals of driver drowsiness
detection systems, provides examples of existing products, and offers
guides for practitioners interested in developing their own solutions to
the problem. Driver drowsiness causes approximately 7% of all road
accidents and up to 18% of fatal collisions. Proactive systems that are
capable of preventing the loss of lives combine techniques, methods, and
algorithms from many fields of engineering and computer science such as
sensor design, image processing, computer vision, mobile application
development, and machine learning which is covered in this brief. The
major concepts addressed in this brief are: the need for such systems,
the different methods by which drowsiness can be detected (and the
associated terminology), existing commercial solutions, selected
algorithms and research directions, and a collection of examples and
case studies. These topics equip the reader to understand this critical
field and its applications. Detection Systems and Solutions: Driver
Drowsiness is an invaluable resource for researchers and professionals
working in intelligent vehicle systems and technologies. Advanced-level
students studying computer science and electrical engineering will also
find the content helpful.