Satellite Imagery for Waterproof Paint State Detection
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Solution Overview
Problem
Current methods for determining the applied state of waterproof paint on buildings are inefficient, requiring on-site visits and failing to address heat absorption issues, especially with green urethane paint, which affects cooling efficiency and rooftop aesthetics.
Innovation Solution
A method and apparatus using satellite imagery and convolutional neural networks (CNN) to detect rooftop areas and calculate a state index based on color consistency and variation, allowing for remote assessment of waterproof paint application states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-site visits are used to determine waterproof paint application state, then measurement precision is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The patent uses satellite imagery as a copy or representation of the actual rooftop surface, allowing remote analysis of waterproof paint application state without physical inspection. The satellite images capture visual information that can be analyzed to determine paint condition, eliminating the need for on-site visits while maintaining detection capability
Solution Approach 2:
The patent replaces manual on-site inspection (mechanical/human system) with automated image processing and analysis systems. The mechanical process of physically visiting and inspecting rooftops is substituted with automated algorithms that analyze satellite imagery to assess waterproof paint application state
2Reliability
If green urethane waterproof paint is used, then waterproofing effectiveness is improved, but temperature inside building increases due to high heat absorption rate
Solution Approach 1:
The patent monitors and analyzes the color of waterproof paint on rooftops using satellite imagery. By detecting color changes and variations, the system can identify paint degradation, peeling, or improper application that may lead to waterproofing failures. The color analysis helps assess both the aesthetic appearance and functional integrity of the waterproof coating
Solution Approach 2:
The patent establishes a feedback mechanism where satellite imagery is continuously or periodically captured and analyzed to monitor the condition of waterproof paint. This feedback loop allows building managers to detect deterioration early, assess the effectiveness of applied paint, and make informed decisions about maintenance and reapplication timing based on actual condition rather than fixed schedules
3Reliability
If comprehensive building inspection is conducted, then reliability of building management is improved, but device complexity and cost increase
Solution Approach 1:
The patent utilizes satellite imagery technology that serves multiple functions: it can monitor waterproof paint application state, assess building location and context, track changes over time, and provide data for multiple buildings simultaneously. This multi-functional approach eliminates the need for specialized inspection equipment for each building, reducing overall system complexity while maintaining comprehensive monitoring capability
Data Source
AI summary
A waterproof paint state determining method of a building using a satellite imagery according to an exemplary embodiment of the present disclosure includes receiving search information including information about a location in which a waterproof paint application state of a rooftop of a building is to be measured from a user; searching a search satellite imagery which is at least one satellite imagery corresponding to the search information from a satellite imagery DB including a plurality of satellite imagery data; detecting a rooftop area which is a waterproof paint application area of at least one building corresponding to the search information from the search satellite imagery, using a convolutional neural network (CNN) technique; and calculating a state index which is an index indicating a waterproof paint application state of at least one building, based on reference color information and color information of the rooftop area.