Smart Edge-Based Driver Drowsiness Detection in Mobile Crowdsourcing-Reference-Cited by-同舟云学术

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Smart Edge-Based Driver Drowsiness Detection in Mobile Crowdsourcing

Published:2023 Issue: Volume:11 Page:21863-21872
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lamaazi Hanane¹^ORCID,Alqassab Aisha²,Fadul Ruba Ali²^ORCID,Mizouni Rabeb¹^ORCID

Affiliation:

1. EECS Department, Center for Cyber-Physical Systems, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

2. Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10056954.pdf?arnumber=10056954

Reference30 articles.

1. Real-Time Drowsiness Detection Algorithm for Driver State Monitoring Systems

2. Smart-3DM: Data-driven decision making using smart edge computing in hetero-crowdsensing environment

4. Real-Time Driver Drowsiness Detection for Embedded System Using Model Compression of Deep Neural Networks

5. Smart Edge-based Fake News Detection using Pre-trained BERT Model

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematic survey on artificial intelligence based mobile crowd sensing and sourcing solutions: Applications and security challenges;Ad Hoc Networks;2024-11

2. IoT-based Car Driver Assistance System using Computer Vision and Machine Learning;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

3. Survey Paper on the Driver Drowsiness Detection using IoT;International Journal of Advanced Research in Science, Communication and Technology;2024-03-05

4. MIDGNWD : Design of an efficient multimodal iterative deep graph network wearable interface for detecting drowsy drivers;Journal of Statistics and Management Systems;2024

5. Systematic Survey on Ai-Based Mobile Crowd Sensing/Sourcing Solutions: Applications and Securitychallenges;2024

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