An IoT Edge Self-Adaptable Vehicle Slowdown Earliest Warning System Using R-CNN Based Traffic Prediction Model-Reference-Cited by-同舟云学术

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An IoT Edge Self-Adaptable Vehicle Slowdown Earliest Warning System Using R-CNN Based Traffic Prediction Model

Published:2024-04-04 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
language:
Short-container-title:

Author:

N Murali¹,David D. Beulah²

Affiliation:

1. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University,Department of Computer Science and Engineering,Chennai,Tamilnadu,India

2. Institute of Information Technology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University,Department of Quantum Intelligence,Chennai,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568759.pdf?arnumber=10568759

Reference21 articles.

1. Roadside Unit Allocation for Fog-based Information Sharing in Vehicular Networks

2. A Machine Learning Edged Self-Adaptable Vehicle Slowdown Earliest Warning Information System Using IOT Based Traffic Prediction Model

3. Dedicated Short-Range Communications (DSRC) Standards in the United States

4. SafeSmart: A VANET System for Faster Responses and Increased Safety in Time-Critical Scenarios

5. Advanced VANET Technology for Emergency Vehicle Safety in Time-Critical Scenario

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