What is it about?
The driver drowsiness detection system aims to reduce risks during long drives using technologies like EEG, thermal imaging, eye tracking, and AI-based facial expression recognition. It includes direct monitoring, which tracks signals like eye movement and EEG, offering higher accuracy and convenience than indirect methods. Warning systems, such as sound alerts and vibrating seats, notify drivers of drowsiness. Advanced technologies like automatic control and assisted driving help prevent accidents. The future focuses on deep learning, cloud computing, wearable devices, and human-computer interaction (HCI) interfaces to improve safety in both vehicles and aviation. Lightweight wearable devices and intelligent HCI interfaces are recommended to enhance driver safety.
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Why is it important?
The paper contributed a lot in promoting the development and application of driver drowsiness detection systems. At the same time, it also provides potential challenges for future research, providing impetus for further innovation and improvement of driver drowsiness detection systems.
Perspectives
Writing this article was a great pleasure as it involved co-authors with whom I have had long-standing collaborations. This article also led to human-computer interaction groups contacting me and ultimately to a greater involvement in human-computer interaction research.
Yunshang Wang
Read the Original
This page is a summary of: The driver drowsiness detection system based on human-computer interaction, January 2024, American Institute of Physics,
DOI: 10.1063/5.0222836.
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