Mobile Pothole Detection System for Automated Road Surface Monitoring
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Solution Overview
Problem
Current road maintenance systems are labor-intensive and costly, requiring significant resources and manpower to detect and analyze surface abnormalities, which strains budgets and limits their effectiveness due to shrinking infrastructure funds.
Innovation Solution
A surface imaging system equipped with a sensor and processing devices that acquire images, associate them with geo-coordinate data, identify surface abnormalities, and generate trend data on surface degradation over time, allowing for automated and efficient monitoring and maintenance planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated distress survey systems are implemented to assess pavement conditions, then measurement precision and productivity are improved, but device complexity and cost increase
Solution Approach 1:
The system segments the road surface analysis into distinct components: image acquisition by sensors, image processing to identify abnormalities, extraction of abnormality properties (crack density, rutting, roughness), and storage in a database. This segmentation allows each component to be optimized independently while maintaining overall system precision.
Solution Approach 2:
The patent introduces an intermediary processing system that bridges the gap between raw sensor data and meaningful pavement condition assessment. The processing device acts as a mediator that transforms complex sensor inputs into structured abnormality data with specific properties, reducing the complexity burden on both data collection and analysis stages.
2Measurement precision
If comprehensive surface analysis is performed to identify all types of pavement distress, then measurement precision is improved, but loss of time and productivity are worsened
Solution Approach 1:
The system performs preliminary actions by pre-defining multiple types of surface abnormalities (cracks, rutting, roughness) and their associated properties before actual surveying begins. The processing device is pre-configured with algorithms to detect and measure these specific abnormality types, allowing for rapid identification during the survey without requiring complex real-time analysis decisions.
Solution Approach 2:
The patent changes parameters by focusing measurements on specific abnormality properties (crack density, rutting depth, roughness metrics) rather than attempting comprehensive analysis of all surface characteristics. This parameter-specific approach maintains measurement precision for critical pavement conditions while reducing the overall time required for surveying.
3Measurement precision
If multiple sensors and processing devices are deployed to capture comprehensive surface data, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent implements universality by designing a multi-functional processing device that can handle multiple types of surface abnormalities (cracks, rutting, roughness) and extract various properties from the same set of sensor inputs. This single processing system performs what would otherwise require multiple specialized devices, reducing the quantity of components while maintaining comprehensive measurement precision.
4Productivity
If automated systems are used to reduce labor requirements, then productivity is improved, but device complexity and initial cost increase
Solution Approach 1:
The system implements self-service by enabling automated image processing and abnormality detection without requiring constant human intervention. The processing device autonomously identifies surface abnormalities, extracts their properties, and stores the data in the database, allowing the system to maintain and improve productivity while reducing the complexity of human-machine interaction.
Data Source
AI summary
An exemplary apparatus and associated method are disclosed for analyzing surface degradation. The apparatus can include a sensor configured to acquire images of a surface; and a processing device configured to correlate the acquired images to a geo-coordinate, to extract at least one property of a surface abnormality identified in at least one of the acquired images, and to generate trend data based on changes over time in the at least one property of the surface abnormality identified in the images, which are correlated to a common geo-coordinate.