Driver Monitoring System

Driver monitoring systems (DMS) aim to enhance road safety by automatically assessing driver alertness and behavior, using various sensor modalities (e.g., cameras, infrared sensors) to detect drowsiness, distraction, and improper seatbelt use. Current research emphasizes developing robust and efficient algorithms, including convolutional neural networks (CNNs), spiking neural networks (SNNs), and federated learning approaches, often incorporating multi-view and multimodal data fusion techniques like masked multi-head self-attention. These advancements are crucial for improving the accuracy and real-time performance of DMS in autonomous and semi-autonomous vehicles, contributing to safer driving environments and potentially reducing accident rates.