Man overboard detection system

Abstract

The present invention surveils a ship and automatically detects movement around a ship such as, for example, a man overboard condition. Detection is achieved using a continually scanning set of lasers that cooperate with long-wave infrared thermal imaging cameras that are used to classify the movement. If a MOB event is determined, an alarm is then initiated on the bridge of the ship.

Description

BACKGROUND[0001]Cruise ships for tourism and vacation have become increasingly popular over the last two decades. In 2014, the cruise industry estimated that 22.1 million passengers traveled by cruise ship globally—a four percent increase over 2013's previous high of 21.3 million. Coupled with an annual occupancy percentage again exceeding 100 percent, this passenger growth shows sustained consumer interest in cruising and an industry where demand continues to outstrip supply. Cruise lines released an additional 15 full service cruise ships in 2014, but they also enhanced demand by establishing and increasing their presence in international ports-of-call.[0002]The vast number of these passengers enjoy a fun filled, vacation without incident. For a very small fraction of these passengers, however, the experience ends in tragedy. It is estimated that over two hundred incidents of “man overboard” has occurred since the year 2000, where a passenger jumps, falls, or by other nefarious me...

AI Technical Summary

Benefits of technology

The present invention is a software system that uses a graphical interface to display sensors and alarms on a ship. It allows the bridge officer to interact with the alarms and mark them as either positive or negative. This helps the system learn and refine its detection over time, reducing the likelihood of false alarms. The system also has a backup storage system that ensures live video and events are always recorded and retained in case of failure, ensuring uptime and compliance.

Problems solved by technology

For a very small fraction of these passengers, however, the experience ends in tragedy.

Most ships are equipped with rescue equipment, and some ships are also equipped with man overboard (“MOB) detection equipment, but most systems are either ineffective or incapable of quickly and accurately determining a true MOB occurrence from the numerous false alarms that occur.

Until now solving the person overboard problem had not yielded satisfactory solutions, in part because the sensors required to detect an event that occurred over a span of 180 degrees in close proximity to the sensor head and thereafter accompanied by the means to capture the event itself were unavailable.

A significant reason why a satisfactory solution has not been found is that the detection of a relatively small object (e.g., size of a baby) falling from a ship, relative to a sensing and detection mechanism, has a very high angular rate of change.

The prior art has attempted to solve this problem with mixed results.

It has been found that using NIR cameras do not have the requisite accuracy to consistently detect images the size of babies or small children, and so it is not an optimal solution to the problem.

However, if a passenger removes the RFID tag, or the reader fails to detect the tag, the system is inoperative.

Thus, this is also not an optimal solution.

This approach has been proven to have create numerous false alarms and has been rejected by the industry.

Visible light cameras do not provide visual in the evening hours due to the lack of visible light, thus not providing visual confirmation of a man overboard event.

The prior art systems all lack a comprehensive, robust solution for surveillance, detection, and tracking of a MOB occurrence in daylight or evening, that can also apply computer analytics (learning) of the ships environment and structure to progressively improve detection.

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