Jurnal Teknik Mesin, Industri, Elektro dan Informatika
Vol. 5 No. 3 (2026): Jurnal Teknik Mesin, Industri, Elektro dan Informatika

Implementation of Facial Landmark Method on Smart BNWAS Integrated ESP32 VDR

Insanul Arifin (Universitas Muhammadiyah Malang)
Thomas Adi Sujatmiko (Universitas Muhammadiyah Malang)
Muhammad Dhuhril Luddin Alfarizy (Universitas Muhammadiyah Malang)
Muhammad Rizky Maulana (Universitas Muhammadiyah Malang)
Muhammad Irfan (Universitas Muhammadiyah Malang)
Muhammad Chasrun Hasani (Universitas Muhammadiyah Malang)



Article Info

Publish Date
02 Aug 2026

Abstract

Fatigue among bridge watchkeepers is a major contributor to maritime accidents caused by human error, particularly on non-conventional vessels that lack active safety systems and voyage data recording devices. Conventional Bridge Navigational Watch Alarm Systems (BNWAS) remain passive and rely on manual interaction, limiting their effectiveness in detecting actual operator drowsiness. Furthermore, the high implementation cost of standard Voyage Data Recorders (VDR) restricts their adoption on smaller vessels. This study proposes a Smart BNWAS integrated with an ESP32-based VDR subsystem to provide active fatigue monitoring and structured voyage data recording at a lower cost. An experimental approach with a prototyping development model was employed, including system design, implementation, integration, and performance evaluation under controlled laboratory conditions. Operator alertness was monitored using MediaPipe Face Mesh through Eye Aspect Ratio (EAR) and Mouth Aspect Ratio (MAR) analysis executed on a Raspberry Pi 5, which also functioned as a web server for real-time monitoring. System performance was evaluated through alarm response testing, fatigue detection experiments, web dashboard functionality assessment, and VDR data logging verification. Experimental results demonstrated a 100% detection success rate across ten predefined laboratory test scenarios and successful recording of timestamp, positioning, and orientation data in CSV format. The proposed Smart BNWAS-VDR system provides a low-cost maritime safety platform with fatigue detection, adaptive data logging, real-time web-based monitoring, and remote system management capabilities for non-conventional vessel applications.

Copyrights © 2026






Journal Info

Abbrev

jtmei

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Description

JTMEI merupakan jurnal ilmiah berkala dengan ciri khas/identitas bidang Teknik (Mekanik, Elektrikal, Industri, Informatika, Sipil dan Sains). Tema makalah ini difokuskan pada aplikasi industri baru, kelautan dan pengembangan energi hijau yang ...