Advancing Traffic Safety through Innovative AI Techniques

Optimizing CNN Architectures for Driver Drowsiness Detection via Genetic Algorithms

8 mins
What is it about?



The research focuses on a pressing issue: driver drowsiness, which significantly contributes to traffic accidents. Highlighting the severity, statistics suggest many accidents occur annually due to driver fatigue, which not only endangers lives but also imposes substantial economic burdens. To tackle this, the study introduces an innovative approach utilizing Convolutional Neural Networks (CNNs) optimized through genetic algorithms, aiming to enhance the detection accuracy of driver drowsiness.