Airport Apron Object Detection Using LIDAR-Triggered Image Segmentation
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Solution Overview
Problem
The apron area of an airport poses a risk of unnoticed objects being sucked into aircraft engines or collided with, due to the inability of existing systems to effectively detect small obstacles from a distance.
Innovation Solution
A system utilizing a camera sensor and LIDAR sensor, combined with a computing device, divides apron area images into irregular slices and employs machine learning models to detect obstacles, ensuring accurate detection of small objects before and during aircraft docking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire image is processed to detect small objects, then detection coverage is improved, but processing time increases
Solution Approach 1:
The image processing system divides the apron area image into multiple regions of interest based on aircraft position and movement direction. By segmenting the image into relevant and irrelevant areas, the system processes only necessary portions, maintaining detection coverage for small objects while reducing overall processing time and computational load.
2Measurement precision
If image processing is performed at full resolution, then detection accuracy is improved, but computational load increases
Solution Approach 1:
The system applies different processing qualities to different regions of the image. High-resolution processing is applied only to regions of interest where small objects may be present, while other areas receive lower-resolution processing or are skipped entirely. This maintains detection accuracy in critical areas while reducing overall computational load and power consumption.
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 enables rapid and precise detection of small obstacles from long distances, preventing collisions and engine suction, thereby ensuring safe aircraft operations.
Implementation Method 1
a light detection and ranging (LIDAR) sensor device configured to detect an aircraft entering the apron area of the airport
Data Source
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AI summary
Devices, methods, and systems for detecting objects in an apron area of an airport are described herein. One system includes a camera sensor device configured to capture images of an airport apron area, a LIDAR sensor device configured to detect an aircraft entering the apron, and a computing device configured to, prior to the aircraft entering the apron, divide a portion of an image of the apron captured by the camera sensor device into a number of sub-portions that are irregular slices of the image and detect whether an object is present in each respective sub-portion. The computing device can, upon the LIDAR sensor device detecting the aircraft entering the apron, determine whether to divide a portion of an image of the apron captured by the camera sensor device into a number of sub-portions or consider the entire image to detect whether an object is present in the image.