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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.
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