Road Camera Abnormality Detection Using Adjacent Traffic Conditions
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Solution Overview
Problem
Existing traffic monitoring systems struggle to accurately detect abnormalities in camera images due to external factors, leading to unnecessary maintenance alerts and inefficiencies.
Innovation Solution
A monitoring apparatus and method that incorporates traffic information, statistical information, and road information from adjacent points to differentiate between camera malfunctions and external factors affecting image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traffic monitoring systems use camera images to monitor traffic conditions, then traffic monitoring capability is improved, but accuracy in detecting camera abnormalities deteriorates due to external factors affecting image quality
Solution Approach 1:
The system segments the detection task into multiple components: traffic condition detection from camera images, road condition detection from separate road surface images, and abnormality detection by comparing both datasets. This segmentation allows the system to distinguish between camera abnormalities and external road conditions independently.
Solution Approach 2:
The system introduces road condition information as an intermediary factor to mediate between camera image quality and traffic monitoring accuracy. By comparing camera-derived traffic information with road condition data, the system can determine whether image abnormalities are caused by camera failures or external road factors.
2Area of stationary object
If cameras are installed in various places for comprehensive traffic monitoring, then monitoring coverage is improved, but maintenance complexity increases due to difficulty in abnormality detection
Solution Approach 1:
The system enables self-diagnosis by automatically detecting camera abnormalities through comparison of traffic information with road condition information. This self-service capability reduces manual inspection requirements and simplifies maintenance operations across the distributed camera network.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring traffic conditions and road states, comparing them to identify camera abnormalities. This feedback loop provides automatic diagnostic information that simplifies maintenance decision-making for distributed camera systems.
3Speed
If camera images are analyzed to detect traffic conditions, then real-time monitoring is improved, but false alarms increase due to external factors like road construction or accidents
Solution Approach 1:
The system dynamically adjusts abnormality detection by incorporating real-time road condition information into the comparison process. This dynamic approach allows the system to adapt to changing road conditions such as construction or accidents, reducing false alarms while maintaining real-time monitoring responsiveness.
Data Source
AI summary
A monitoring apparatus (10) includes: a camera image acquisition unit (11) that acquires a camera image of a road captured at a first point from a camera disposed at the first point; a traffic information acquisition unit (12) that acquires traffic information indicating a traffic condition of the road at the first point by analyzing the camera image; a road information acquisition unit (13) that acquires road information indicating a traffic-limiting situation at a second point leading to the first point; and an abnormality detection unit (14) that detects an abnormality in the camera image based on the traffic information, statistical information of the traffic information, and the road information.