The system is designed to detect persons going overboard from passenger ships and cruise ships.
It is being developed in response to a challenge of the Innovate UK (Intelligent Data Insights Innovation Contest of the InnovateUK, File Reference Number 230028), set in conjunction with Carnival Corporation & PLC, the world's largest cruise company, with almost 100 cruise vessels operating across 10 different brands, including P&O and Cunard in the UK. On any single day there are in excess of 270,000 people at sea with Carnival.
The method of detection our company came up with, does not require the passengers to wear a device to trigger an alarm. The challenge is to achieve high rates of detection of a human falling overboard, while keeping the false alarms limited to no more than one, daily.
The International Signal Flag for a Man Overboard event
The unique offering of this project, consists in the development of a data fusion middleware that builds on an innovative set of image recognition and motion detection algorithms, aimed at lowering false alarms and achieving accurate detection of real (human-shaped) targets.
The system will operate with very good performance at a wide range of sea condition which affect the movement of the ship. Feature reduction algorithms are guaranteed to discriminate actual events even in the most crowded scenes (when people gather in one of the ship’s observation decks). The sensors’ location and coverage is such that all areas around the ship and to an extent (typically 5m) from the ship’s hull are covered.
It is very important to mention that the system is not based on a single-factor authentication method, i.e. the process does not rely on one method to identify a user. Instead the system relies on Image Classification, Trajectory and Thermal Footprint analysis.
Following the alarm, the safety responsible will use a control station to review the footage of the event from the available sensors.