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Design and Implementation of a Deep Learning-Based Safety Helmet Compliance Detection System Using the Faster R-CNN Method Palman; Sandy Azizi; Muhammad Ilhamdi Rusydi; Rahmadi Kurnia
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 6 No. 1 (2026): May 2026
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v6i1.218

Abstract

Workplace accidents remain one of the major issues in industrial environments and are often caused by low compliance with the use of Personal Protective Equipment (PPE), particularly safety helmets. Manual supervision of PPE usage tends to be inefficient and prone to human error. This study aims to develop an intelligent computer-vision-based system capable of automatically and real-time monitoring helmet compliance. The proposed system employs the Faster Region-Convolutional Neural Network (Faster R-CNN) algorithm to detect and classify workers who are wearing and not wearing helmets. The dataset was obtained from CCTV video recordings in industrial areas, which were converted into image frames for training and testing processes. The experimental results show that the system achieved an accuracy of 90% for helmet-wearing workers and 87% for non-helmet-wearing workers during daytime conditions, and 97% and 91% respectively at night. With an average computation time of 0.1 seconds per frame, the system is capable of real-time detection at up to 10 frames per second. These results indicate that the Faster R-CNN method is effective in detecting PPE compliance and has the potential to be implemented as an automated safety-support system in industrial environments.
Co-Authors . Darwison Adam Jordan Agung W. Setiawan Agung Wibowo Ardiyanta Surbakti Agung Wibowo Ardiyanta Surbakti Andi Pawawoi Andre Paskah Gultom Andrivo Rusydi Andrivo Rusydi Anton Hidayat Ariadi Hazmi Arrya Anandika Asrul Azani Mahmood Aulia Novira Aulia Rahman Aulia Rahman Avelia Fairuz Faadhilah Azmi, Luxfy Roya Budi Agung Santoso Budi Sunaryo Chatarina Umbul Wahyuni Daelita Berliana H. Devianda Ananta Sandri Dhiny Yurichy Putri Dhiny Yurichy Putri Eka Fitrianto Elmiyasna Kimin Febdian Rusydi Feskaharny Alamsjah Hafidzah Putri Rahmadani Haznam Putra Hermawan Nugroho Hermawan Nugroho Ikhwan Arief Indra Laksmana Jack Febrian Rusdi Joseph Muguro Joseph Muguro Khairunnisa Lizzikrillah Kojiro Matsushita Laksono, Heru Dibyo M. Farhan Minarni Minarni Minoru Sasaki Minoru Sasaki Minoru Sasaki Muhammad Dani Anwar Muhammad Fikri muhammad fikri Muhammad Fikri Muhammad Hadi Sucipto Muhammad Imran Hamid Muhammad Ismail Opera Muhammad Khalish Muhammad Naufalun Nabil Muhammad Syaiful Amri bin Suhaimi Muhammad Syaiful Amri bin Suhaimi Mumuh Muharram Mutia Firza Nadia Alfitri Nurul Azizah Dhuha Oluwarotimi Williams Samuel Oluwarotimi Williams Samuel Palman Pepi Putri Utami Pepi Putri Utami Pepi Putri Utami Pratama Halim Pratama Halim Prima Fithri Pringgo Widyo Laksono Rahdian Hadi Farhan Rahmad Novan Nurhadi Rahmadi Kurnia Ramadhani, Salisa 'Asyarina Ridho Tullah Syahputra Rifda Suriani Riko Chandra Riko Nofendra Riko Nofendra Rio Nakajima Rizka Hadelina Robbi Noberlam Dasyura Roza Susanti Roza Susanti Sandy Azizi Sunaryo, Budi Sunaryo, Budi Syafii . Syafril Daus Syamsul Huda Syarkawi Syamsuddin Takaaki Iida Takayuki Nakagome Taufiqurrahman Vinoza Shalsabila Waweru Njeri Waweru Njeri Yoan Winata Yoan Winata Zaini Zaini Zaini, Zaini Zen Resti Maulana