AI-based traffic counting: A Case Study in Vietnam

被引：0

作者：

Nhu Phuc Nguyen ^{[1
]}

Hoang Minh Nguyen ^{[1
]}

Hoang-Loc La ^{[1
]}

Truong Thi Tran Thi ^{[2
]}

Ngoc Hieu Duong ^{[1
]}

Thanh Sach Le ^{[1
]}

Duy Lai Nguyen Le ^{[1
]}

Nam Thoai ^{[1
]}

机构：

[1] Ho Chi Minh City Univ Technol HCMUT, Ho Chi Minh City, Vietnam

[2] Hoa Sen Univ, Ho Chi Minh City, Vietnam

来源：

2022 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND ANALYTICS (ACOMPA) | 2022年

关键词：

deep learning; traffic counting; intelligent transportation; system; CCTV; SYSTEM;

D O I：

10.1109/ACOMPA57018.2022.00012

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Ho Chi Minh City, particularly Vietnamese cities in general, is so busy and crowded since tremendous numbers of motorbikes move on roads. Ho Chi Minh City leaders have encountered several challenges in fully understanding and effectively dealing with problems of urban traffic for the past few decades. Software-based solutions are proper and dramatically necessary, currently. This paper presents the deployment of an AI-based application at the Ho Chi Minh City Department of Transportation. The paper mainly concentrates on traffic counting problems during the outbreak of the Covid-19 pandemic from June 2021. The performance of the AI-based application was compared with medical declaration data and achieved an accuracy of 93.80%.

引用

页码：34 / 39

页数：6

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