ELNAV Aware Mate - Aware Mate Fatigue and Distraction Detection System for Bridge Watchkeeping
Aware Mate is a technological advancement aimed at enhancing maritime safety by addressing the prevalent issue of seafarer fatigue and distraction during bridge watchkeeping. Utilizing video detection technology, Aware Mate monitors a watchkeeper’s levels of alertness through sophisticated infrared and intelligent algorithms that track iris movement, gaze fixation, and head positioning. This system ensures effective fatigue detection and distraction management both day and night. Engineered to prioritize user privacy, Aware Mate operates offline, eliminating the need for an internet or cloud connection. This ensures no personal data is recorded or shared, maintaining privacy with anonymized insights. Additionally, Aware Mate integrates seamlessly into existing Bridge Navigational Watch & Alarm System (BNWAS) setups. Its partnership with Axis Communications from Lund, Sweden, allows the use of hardware and software optimized for deep learning applications. Through such integrations, Aware Mate aims to significantly enhance navigational safety by reducing the risks of accidents caused by decreased attention and judgment among watchkeepers.
Problem
Insufficient fatigue monitoring in bridge watchkeeping poses a severe threat to maritime and inland waterways safety. Studies reveal alarming statistics, with 25% of marine casualties attributed to seafarers fatigue. IMO's research on seafarers fatigue revealed that one in four seafarers admitted to falling asleep while on watch.
BNWAS
The Bridge Navigational Watch & Alarm System (BNWAS), introduced two decades ago, falls short in addressing the complexities of modern watchkeeping. Dormant periods of 3 to 12 minutes and delegation of reset procedures exacerbate the issue.
Adapting to the Times
Sitting on the bridge during watchkeeping was once restricted. The shift to more sedentary watchkeeping practices with the advent of modern technology like ECDIS and flat-screen radar displays contribute to problem.
Aware Mate offers a solution by introducing fatigue and distraction detection cameras to bridge watchkeeping—leveraging modern technology and evolving practices to enable real-time monitoring that’s both feasible and effective.
How Aware Mate Works
These cameras track the watchkeeper’s irises and trigger alerts if their eyes close, head drops, or gaze fixes on distracting objects. Infrared and intelligent face and eye-tracking algorithms ensure accurate detection of fatigue and distraction, day or night.
Privacy and Security
Aware Mate does not require an internet or cloud connection, ensuring that no personal data is recorded, transmitted, or shared. All deep learning data is pre-trained to the device, providing a built-in solution.
Integration Capabilities
Aware Mate seamlessly integrates into existing Bridge Navigational Watch & Alarm System (BNWAS) setups. It's a versatile solution that enhances safety without disrupting daily bridge team duties.
Partnership with AXIS
For an Aware Mate technology demonstrator, Axis Communications AB from Lund, Sweden, is providing hardware and a sofware optimized for deep learning and intelligent facial analytics applications.
Enhanced Navigational Safety
Aware Mate directly contributes to maritime and inland waterways safety by using video detection technology to monitor signs of fatigue and distraction in bridge watchkeepers. This innovative approach helps prevent accidents caused by reduced alertness, significantly enhancing overall operational safety.
Fatigue & Distraction Monitoring
The system employs advanced video detection techniques—including infrared technology and intelligent algorithms—to accurately monitor fatigue and distraction levels among watchkeepers. This ensures effective detection day and night, providing a reliable solution to manage and mitigate human error risks.
Privacy & Data Security
Aware Mate prioritizes watchkeeper privacy by operating entirely offline. No personal data is recorded, transmitted, or shared. Fatigue and distraction are monitored locally, with only anonymized, aggregated insights used to track performance trends. This privacy-first approach ensures compliance while supporting safer navigation.