Implementation of Facial Landmark Method on Smart BNWAS Integrated ESP32 VDR
DOI:
https://doi.org/10.55606/jtmei.v5i3.6404Keywords:
BNWAS, ESP3, Facial Landmark Detection, MediaPipe Face Mesh, VDRAbstract
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.
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Copyright (c) 2026 Insanul Arifin, Thomas Adi Sujatmiko, Muhammad Dhuhril Luddin Alfarizy, Muhammad Rizky Maulana, Muhammad Irfan, Muhammad Chasrun Hasani
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