Design of a Traffic Counting System With Object Detection Using Rtsp Camera With Yolo Algorithm And Rest API Architecture

The design of an effective traffic counting system is crucial for improving traffic management in urban environments. This study aims to develop a traffic counting system that utilizes object detection through Internet of Things (IoT)-based cameras. The system employs the You Only Look Once (YOLO) algorithm for real-time vehicle detection, enabling high accuracy in vehicle identification and counting. In this design, a REST API architecture is implemented to ensure efficient data communication between the detection and storage modules, allowing for flexible and scalable data retrieval and analysis. Test results show that this system can provide quick and accurate information regarding traffic flow under various conditions. Thus, this research makes a significant contribution to the development of smart city technology and provides a useful tool for traffic analysis and decision-making.

Authors

Institutions

Publication Details

Journal
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT)
Published
2024-11-29
DOI
https://doi.org/10.52005/ijeat.v7i2.114
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design of a Traffic Counting System With Object Detection Using Rtsp Camera With Yolo Algorithm And Rest API Architecture

H Andy Achmad, Seliwati
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT)
Vehicle License Plate Recognition
article

Design of a Traffic Counting System With Object Detection Using Rtsp Camera With Yolo Algorithm And Rest API Architecture

H Andy Achmad, Seliwati
article en

Abstract

The design of an effective traffic counting system is crucial for improving traffic management in urban environments. This study aims to develop a traffic counting system that utilizes object detection through Internet of Things (IoT)-based cameras. The system employs the You Only Look Once (YOLO) algorithm for real-time vehicle detection, enabling high accuracy in vehicle identification and counting. In this design, a REST API architecture is implemented to ensure efficient data communication between the detection and storage modules, allowing for flexible and scalable data retrieval and analysis. Test results show that this system can provide quick and accurate information regarding traffic flow under various conditions. Thus, this research makes a significant contribution to the development of smart city technology and provides a useful tool for traffic analysis and decision-making.

INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT)Vol. 7(2)
Institute of Engineering Science (RU)
Openalex Percentile: Top 66%
Vehicle License Plate Recognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Design of a Traffic Counting System With Object Detection Using Rtsp Camera With Yolo Algorithm And Rest API Architecture — H Andy Achmad, Seliwati · INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) (2024) | TGRS Research Map | TGRS