Utility Infrastructure Mapping via Image Processing
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Solution Overview
Problem
Utility companies face challenges in accurately identifying and mapping utility structures such as poles and line corridors due to disjointed information from different utility companies and incomplete databases, which hinders easement and placement rights determination.
Innovation Solution
A method involving image processing techniques, including edge detection and feature extraction, to identify utility structures from images, providing location information and associating them with geographical pathways, using neural networks for object detection and GIS tools for spatial analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional database methods are used to store utility structure information, then data storage is simple, but the information is incomplete and inaccurate
Solution Approach 1:
The patent introduces image data as an intermediary between the utility structures and the database. Images captured by vehicles serve as a visual record that complements and verifies the structured data in the database, providing both complete information coverage and accurate verification of utility structure locations and characteristics
Solution Approach 2:
The patent replaces traditional manual surveying and data collection methods with automated image capture and processing systems. Vehicles equipped with cameras automatically capture images of utility structures along their routes, eliminating the need for manual field surveys and reducing human error in data collection
2Productivity
If manual surveying methods are used to identify utility structures, then data collection is straightforward, but the process is time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service mapping where vehicles automatically capture images and the system automatically processes these images to identify and map utility structures. This eliminates the need for dedicated surveying teams to manually locate and record each utility structure, allowing the infrastructure itself to generate its own mapping data through normal vehicle traffic
Solution Approach 2:
The patent transforms discrete, periodic surveying operations into continuous data collection. As vehicles continuously travel along roads throughout the day and year, they continuously capture images of utility structures, creating an ongoing process of data collection and updates rather than periodic manual surveys
3Measurement precision
If comprehensive image processing is performed to accurately identify utility structures, then mapping accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct stages: initial image capture, pre-processing to enhance relevant features, utility structure detection using trained models, and final mapping integration. This segmentation allows each stage to be optimized independently and processed efficiently, reducing overall computational complexity while maintaining high accuracy
Solution Approach 2:
The system performs preliminary training of image processing models using labeled utility structure images before deployment. This preliminary action creates pre-trained models that can quickly and accurately identify utility structures in new images without requiring complex real-time processing, shifting computational complexity from operation time to preparation time
Data Source
AI summary
A method for identifying utility structures is described. The method includes identifying a geographical area for locating the utility structures, receiving images of the geographical area that was identified, performing image processing on the images that were received, identifying the utility structures based on the image processing, and providing location information associated with the utility structures that were identified. Related devices and computer program products are also described.