Anti-Accident Mechanism to Detect Driver Drowsiness Integrated with Alerting Mechanism: An IoT-based Model-Reference-Cited by-同舟云学术

Anti-Accident Mechanism to Detect Driver Drowsiness Integrated with Alerting Mechanism: An IoT-based Model

Published:2023-01-23 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Computer Communication and Informatics (ICCCI)
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Author:

Katukam Srujan¹,Potluri Sai Vinay¹,Abburi Sunell Dutt¹,Cherukuri Rahul¹,Sreeka Parinishta C¹,Peddineni Mohith¹,Ram Kumar R. P.²,Polepaka Sanjeeva²

Affiliation:

1. Gokaraju Rangaraju Institute of Engineering and Technology,Department of AI & ML Engineering,Hyderabad,India

2. Gokaraju Rangaraju Institute of Engineering and Technology (GRIET),Department of Artificial Intelligence and Machine Learning Engineering,Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10128170/10128171/10128526.pdf?arnumber=10128526

Reference18 articles.

1. Real-Time System for Driver Fatigue Detection Based on a Recurrent Neuronal Network

2. Two Stream Deep Convolutional Neural Network for Eye State Recognition and Blink Detection

3. An FPGA-Based Real-Time Human Eye Pupil Detection System Using E2V Smart Camera

4. A real-time non-intrusive FPGA-based drowsiness detection system

5. A Novel Approach for Drowsy Driver Detection Using Eyes Recognition System Based on Wavelet Network

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