Federated Learning for Drowsiness Detection in Connected Vehicles

arXiv:2405.03311v1 Announce Type: cross
Abstract: Ensuring driver readiness poses challenges, yet driver monitoring systems can assist in determining the driver's state. By observing visual cues, such systems recognize various behaviors and associate them with specific conditions. For instance, yawning or eye blinking can indicate driver drowsiness. Consequently, an abundance of distributed data is generated for driver monitoring. Employing machine learning techniques, such as driver drowsiness detection, presents a potential solution. However, transmitting the data to a central machine for model …

abstract arxiv challenges cs.cv cs.lg data detection distributed distributed data driver federated learning instance monitoring state systems them type vehicles visual visual cues