@inproceedings{596ad7d5a96d40a3a731f6565eb50022,
title = "Antigen: Highway Abnormal Event Detection System Driven by Roadside Edge Computing",
abstract = "Nowadays, the volume of highway traffic data continues to grow rapidly. To achieve efficient and accurate detection of abnormal events on highways, it is essential to establish intelligent traffic monitoring systems. However, centralizing all computational tasks in a control center results in significant bandwidth consumption and operational costs. To address this challenge, we propose a highway abnormal event detection system based on roadside edge computing. By integrating the YOLO object detection algorithm with the DeepSORT multi-object tracking algorithm, the system automates the detection of abnormal events and offloads computational tasks to edge nodes located near surveillance cameras. We present the system architecture, core technologies, and application scenarios of Antigen.",
keywords = "Deep Learning, Edge Computing, Intelligent Transportation System, Vehicle Detection",
author = "Zhixin Qi and Jiaqiang Chen and Zemin Chao and Zejiao Dong and Hongzhi Wang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.; 9th Asia-Pacific Web and Web-Age Information Management Joint International Conference on Web and Big Data, APWeb-WAIM 2025 ; Conference date: 28-08-2025 Through 30-08-2025",
year = "2026",
doi = "10.1007/978-981-95-5722-6\_27",
language = "英语",
isbn = "9789819557219",
series = "Lecture Notes in Computer Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "280--283",
editor = "Jiajia Li and Richard Chbeir and Lei Li and Chuanyu Zong and Yanfeng Zhang and Mengxuan Zhang",
booktitle = "Web and Big Data - 9th International Joint Conference, APWeb-WAIM 2025, Proceedings",
address = "德国",
}