Man Overboard Detection Using NIR-LIDAR and Thermal Imaging
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Solution Overview
Problem
Current man overboard detection systems on cruise ships are ineffective in accurately and quickly identifying true incidents due to high false alarm rates and inability to detect small objects, such as children, with existing sensors, which poses a significant risk as crew has limited time to respond effectively.
Innovation Solution
A Man Overboard surveillance and detection system utilizing Near-Infrared Light Detection and Ranging Lasers (NIR-LIDAR) and Long-Wave Infrared thermal imaging cameras, providing continuous 360-degree coverage with self-learning software to reduce false alarms and accurately detect objects as small as 10 square inches, integrated with GPS and audible/visual alarms for rapid response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing sensors are used to detect objects overboard, then the system can detect objects, but the measurement precision is insufficient to accurately detect small objects such as children
Solution Approach 1:
The system segments the detection task into multiple specialized sensors: NIR-LIDAR for precise ranging and object detection, thermal cameras for temperature-based identification, and visible light cameras for visual confirmation. Each sensor type targets specific characteristics of falling objects, enabling accurate detection of small objects while reducing false alarms through multi-parameter verification
Solution Approach 2:
The patent implements a multi-functional detection system where a single integrated platform performs multiple detection functions using different sensor modalities. The system can detect objects in various lighting conditions (day/night), identify objects by size, temperature, and visual characteristics, and distinguish between true MOB events and false alarm sources such as birds or debris
2Measurement precision
If the detection system increases sensitivity to detect small objects, then detection accuracy improves, but the false alarm rate increases
Solution Approach 1:
The system incorporates feedback loops where detection data from multiple sensors is continuously cross-validated. When an object is detected, the system immediately queries thermal camera data and visible light camera data to verify the object's characteristics. This feedback mechanism allows the system to maintain high sensitivity for small object detection while filtering out false alarms by requiring consistent signals across multiple sensor types
Solution Approach 2:
The patent introduces an intelligent processing unit that acts as an intermediary between the sensors and the alarm system. This unit analyzes data from all sensors, applies algorithms to distinguish true MOB events from false alarm sources, and only triggers alarms when confidence thresholds are met. The intermediary processing layer enables high detection sensitivity while maintaining low false alarm rates through sophisticated pattern recognition
3Speed
If the system uses traditional detection methods, then the device complexity is low, but the response time is insufficient for effective rescue
Solution Approach 1:
The system performs preliminary actions by continuously monitoring the area around the ship with multiple sensors before any MOB event occurs. The NIR-LIDAR, thermal cameras, and visible light cameras are constantly scanning and ready to detect objects immediately upon departure from the ship. This continuous preliminary monitoring enables instantaneous detection and response, reducing response time despite the increased system complexity
Solution Approach 2:
The patent replaces traditional mechanical detection methods with advanced optical and electronic sensing systems. Instead of relying on human visual inspection or simple mechanical sensors, the system uses NIR-LIDAR for precise distance measurement, thermal imaging for temperature-based object identification, and computer vision algorithms for real-time image analysis. This substitution enables faster, more accurate detection but increases device complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and classifies objects in any light condition, reducing false alarms through self-learning analytics and providing immediate alerts to bridge officers, ensuring timely and accurate response to man overboard situations.
Implementation Method 1
The ship is further equipped with mounted detection equipment that scans the exterior of the ship with Near-Infrared Light Detection and Ranging Lasers (NIR-LIDAR)
Implementation Method 2
The present invention uses camera detection of an electromagnetic radiation in the spectrum of 8-15 μm, commonly referred to as the long wave IR (LWIR) portion of the spectrum
Data Source
AI summary
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.