I2UTS: An IoT based Intelligent Urban Traffic System

被引:3
作者
Achari, Vejey Pradeep Suresh [1 ]
Khanam, Zeba [2 ]
Singh, Amit Kumar [2 ]
Jindal, Anish [2 ]
Prakash, Alok [3 ]
Kumar, Neeraj [1 ]
机构
[1] Thapar Inst Engn & Technol Deemed Univ, Dept Comp Sci Engn, Patiala, Punjab, India
[2] Univ Essex, Sch Comp Sci & Elect Engn, Colchester, Essex, England
[3] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
来源
2021 IEEE 22ND INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE SWITCHING AND ROUTING (IEEE HPSR) | 2021年
关键词
Vehicle Detection; Deep Neural Network; Traffic Control; Edge Computing;
D O I
10.1109/HPSR52026.2021.9481822
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Growing population and migration to cities have given birth to multiple urban issues. Traffic congestion is one of the most prominent ones with severe side effects like fuel wastage, loss of lives, and slow productivity. The traditional traffic control system deploys programming logic control (PLC) which uses round-robin scheduling algorithm. However, few recent works have proposed IoT-based framework which requires the deployment of a series of sensors. In this paper, we propose an IoT-based framework that uses the existing network of CCTV cameras at the junction. An edge device is used to estimate the traffic density and detect emergency vehicles using YOLO v3 -Efficient Net. These two parameters are used as an input to a novel traffic control algorithm. The performance of the proposed framework has been evaluated by analyzing its properties using the UA-DETRAC dataset. The proposed framework achieves 68.10% vehicle detection accuracy.
引用
收藏
页数:6
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