Building Blind-Spot Imaging Requests for Disaster Damage Assessment
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Solution Overview
Problem
Existing methods for ascertaining damage status during disasters are limited by the inability to image blind spots of tall buildings, leading to incomplete assessment of building damage using bird's-eye view images from fixed cameras.
Innovation Solution
An information processing apparatus and method that extracts building images from bird's-eye view images, identifies unimaged buildings using trained models or similarity calculations, and requests nearby terminals to capture images of these blind spots, integrating the images into a comprehensive damage assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a bird's-eye view image is captured by a fixed camera on a tall building, then a detailed damage status of buildings in the imaging range can be ascertained, but buildings in blind spots cannot be captured
Solution Approach 1:
The system segments the assessment task into two parts: (1) automated analysis of bird's-eye view images for buildings within imaging range, and (2) targeted collection of ground-level images for buildings in blind spots. This segmentation allows the system to optimize each part separately, using automated image processing where possible and human mobile terminals only where necessary, thereby improving overall assessment completeness while maintaining efficiency.
Solution Approach 2:
The system introduces an intermediary mechanism (mobile terminals with imaging functions) that bridges the gap between the fixed camera's limited coverage and the need for complete building assessment. The mobile terminals act as mobile intermediaries that can capture images of buildings in blind spots and transmit them to the server, thereby eliminating information loss without requiring changes to the fixed camera system.
2Area of stationary object
If an aircraft or drone is used to capture images, then a wide area can be covered, but the distance to buildings is long making detailed damage status difficult to ascertain
Solution Approach 1:
The system segments the imaging task by aerial vehicles into two categories: (1) wide-area survey for identifying potential damage zones, and (2) targeted detailed assessment of specific buildings. By separating these functions, the system can use aerial vehicles effectively for broad coverage while relying on ground-level mobile terminals for detailed building assessment, thus avoiding the limitation of long-distance imaging.
3Loss of information
If manual image collection by personnel is used, then complete building coverage can be achieved, but time consumption increases
Solution Approach 1:
The system performs preliminary automated analysis of bird's-eye view images to identify which buildings require detailed ground-level imaging. By pre-processing the aerial images and using image recognition algorithms to detect potential damage or blind spots, the system can generate a targeted list of buildings that need further assessment, thereby reducing the time personnel need to spend on image collection compared to manual survey of all buildings.
Solution Approach 2:
The system implements a feedback mechanism where the results from automated bird's-eye view analysis inform the subsequent ground-level image collection process. The server analyzes aerial images, identifies buildings in blind spots or with suspected damage, and automatically generates requests for mobile terminals to capture images of those specific buildings. This feedback loop ensures that manual image collection is focused only where necessary, minimizing time loss while achieving complete coverage.
Data Source
AI summary
A processor included in the information processing apparatus executes an acquisition process of acquiring a bird's-eye view image captured by a fixed camera, an extraction process of individually extracting an image that is estimated to be a building from the bird's-eye view image, a specifying process of specifying an unimaged building that is not captured in the bird's-eye view image among buildings included in map information in which the buildings and their addresses are associated with each other based on the basis of the extracted image, and an imaging request process of transmitting, among a plurality of terminals having an imaging function and a function of transmitting position information, request information for requesting imaging of the unimaged building to a terminal that is determined as being present in the vicinity of the unimaged building on the basis of the position information.