Vehicle tracking and license plate recognition (LPR) over video surveillance cameras are essential intelligent traffic monitoring systems. Due to the enormous amount of data collected each day, it would be difficult to track vehicles by license plate in a real-world traffic setting. Large volumes of data processing, real-time request responses, and emergency scenario response may not be possible using conventional approaches. By combining license plate recognition with the docker container-based structure of the Apache Kafka node ecosystem, the suggested solution takes a novel approach to vehicle tracking. The primary components of our suggested framework for reading license plates are the identification of license plates and text data queries. License plate localization is performed with You Only Look Once version 3 (YOLOv3) and character recognition with Optical Character Recognition (OCR). The detected vehicle images with license plate results are published on related topics with Apache Kafka. Apache Kafka is a publish-subscribe (producers-consumers) messaging system and one of the most popular architectures used for streaming data. For each license plate search, a topic will be created in the framework where producers publish and consumers receive data. Thus, the workload of the operators will be reduced and they will be able to pay attention to more important events in traffic.
Docker Container-Based Framework of Apache Kafka Node Ecosystem: Vehicle Tracking System by License Plate Recognition on Surveillance Camera Feeds
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 22 , 2 ; 290-297
01.08.2024
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Intelligent transportation system , Apache Kafka , Publish-subscribe messaging system , Vehicle tracking , License plate recognition , Docker , Distributed systems , Optical character recognition Automotive Engineering , Civil Engineering , Electrical Engineering , Engineering , User Interfaces and Human Computer Interaction , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics
Springer Verlag | 2024
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