Jurnal Teknologi Elekterika
Vol. 21 No. 2 (2024)

Usage of Safety Helmet Warning System Using Deep Learning Method

Ambarwati, Nur Masyita Ayu (Unknown)
Aryani, Dharma (Unknown)
Asriyadi, Asriyadi (Unknown)



Article Info

Publish Date
15 Nov 2024

Abstract

K3 Helmet Usage Warning System Using Deep Method Learning Algorithm YOLOv8 is a technological innovation that combines the advanced object detection method YOLOv8 (You Only Look Once version 8) with the needs of safety in the work environment, especially the use of K3 (Occupational Health and Safety) helmets. This research aims to improve compliance with the use of K3 helmets through an automation approach using Deep Learning technology.The YOLOv8 algorithm is used to detect whether individuals in the work area are wearing K3 helmets or not. The detection results will be processed by the system to provide automatic warnings if individuals do not wearing an OHS helmet according to safety regulations. The use of Deep Learning technology in this method enables fast and accurate detection, contributing to increased awareness and compliance with workplace safety policies.With proper implementation, the system is expected to help create a safer work environment and improve the safety of workers, making the workplace more compliant with established OHS standards.

Copyrights © 2024






Journal Info

Abbrev

JTE

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Description

Jurnal Teknologi Elekterika: Jurnal penelitian PNUP sebagai wadah komunikasi ilmiah antar akademisi, peneliti dan praktisi dalam menyebarluaskan hasil penelitian bidang rumpun elektro dan informatika yaitu teknik listrik, energi, elektronika, kontrol, telekomunikasi, komputer dan jaringan, dan ...