Kiki Ahmad Baihaqi, Ahmad Fauzi, Jamaludin Indra

SOSIALISASI PENGGUNAAN DETEKSI KENDARAAN BERMOTOR DENGAN COMPUTER VISION

Introduction

Sosialisasi penggunaan deteksi kendaraan bermotor dengan computer vision. Pelajari sosialisasi dan implementasi teknologi computer vision untuk deteksi kendaraan bermotor. Sistem ini memantau lalu lintas real-time, mengenali jenis, menghitung kendaraan, dan mengurangi kemacetan secara efektif.

Abstract

erkembangan teknologi pengolahan cita digital berkembang pesat dari waktu kewaktu, merambah semua sendi-sendi dan bidang kehidupan. Pada Pengabdian masyarakat ini bertujuan untuk mengimplementasikan teknologi computer vision dalam deteksi kendaraan bermotor sebagai solusi untuk memantau dan mengontrol lalu lintas secara efisien. Dengan memanfaatkan metode deteksi objek yang canggih, penelitian ini akan mengembangkan sistem yang mampu mengenali jenis-jenis kendaraan, menghitung jumlah kendaraan yang melintas, serta memonitor kondisi lalu lintas secara real-time. Implementasi teknologi ini diharapkan dapat meningkatkan pengaturan lalu lintas yang lebih efektif dan mengurangi potensi kemacetan di area yang diuji coba. Hasilnya berupa pengetahuan yang diberikan ke peserta dan menunjukan hasil penelitian berupa prototype.

Review

The article, "SOSIALISASI PENGGUNAAN DETEKSI KENDARAAN BERMOTOR DENGAN COMPUTER VISION," presents a highly relevant and timely topic concerning the application of advanced technology for societal benefit. The abstract clearly outlines a community service initiative focused on leveraging the rapid advancements in digital image processing, specifically computer vision, to address critical urban challenges like traffic management. The integration of "socialization" in the title with the abstract's mention of delivering knowledge to participants underscores a valuable dual objective: both technological implementation and knowledge transfer, aiming to empower communities with practical solutions for efficient traffic monitoring and control. The proposed approach to implement computer vision for motor vehicle detection is sound, aiming to develop a system capable of real-time vehicle recognition, counting, and overall traffic condition monitoring. The abstract highlights the use of "canggih" (advanced) object detection methods, which is crucial for building a robust and effective system. The practical objectives of enhancing traffic regulation and mitigating congestion in pilot areas are compelling. The stated outcome of a prototype, coupled with the educational component for participants, suggests a well-rounded project that bridges research and direct community impact. While the abstract provides a strong overview, a full paper would benefit significantly from more specific details regarding the technical implementation and evaluation. For instance, elaborating on the particular "advanced object detection methods" employed (e.g., specific deep learning architectures or algorithms) would strengthen the methodological contribution. Further, details on the scope of the "area yang diuji coba" (tested area), including its characteristics and how performance metrics (e.g., accuracy, processing speed, robustness to varying conditions) were measured for the prototype, would be essential. Finally, a clear description of the "socialization" process and how the "pengetahuan yang diberikan ke peserta" (knowledge given to participants) was assessed would further solidify the community service aspect of this valuable initiative.

Full Text

Comments

You need to be logged in to post a comment.