# IoT-Assisted Automatic Driver Drowsiness Detection through Facial Movement Analysis Using Deep Learning and a U-Net-Based Architecture

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/iot-assisted-automatic-driver-drowsiness-detection-through-facial-movement/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Shiplu Das,Sanjoy Pratihar,Buddhadeb Pradhan,Rutvij H. Jhaveri,Francesco Benedetto |
| Citations | 37 |
| DOI | 10.3390/info15010030 |
| Fields | Computer Science,Neuroscience,Psychology |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2078-2489/15/1/30/pdf?version=1704196786 |
| OpenAlex ID | https://openalex.org/W4390511035 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Shiplu Das](https://scholariq.org/researchers/shiplu-das/)

## Paper primary topic

- [Sleep and Work-Related Fatigue](https://scholariq.org/topics/sleep-and-work-related-fatigue/)

## Paper topics

- [Sleep and Work-Related Fatigue](https://scholariq.org/topics/sleep-and-work-related-fatigue/)
- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Gaze Tracking and Assistive Technology](https://scholariq.org/topics/gaze-tracking-and-assistive-technology/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.