UAV Route Visibility Detection for Faded Mountain Trail Markings
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Solution Overview
Problem
Existing trail markings using scattered colcothar for mountain climbing routes are difficult to visually recognize due to blurring or disappearance caused by snow, rainfall, or depressions, making it challenging to identify the route accurately.
Innovation Solution
An information processing device and method utilizing an unmanned aerial vehicle (UAV) to acquire sensing information, identify the state of scattered colcothar, and determine locations with poor visibility by detecting blurring or disappearance, with additional capabilities to detect depressions and suggest detours.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If scattered colcothar is used as trail marking material, then installation cost is reduced, but visibility of the trail marking deteriorates due to blurring or disappearance
Solution Approach 1:
The system performs preliminary identification of locations where trail markings are likely to blur or disappear using AI processing of aerial images. This allows proactive detection of visibility problems before they completely compromise the trail marking, enabling timely re-application of colcothar at critical locations.
Solution Approach 2:
The patent replaces manual visual inspection and physical trail marking maintenance with an automated system using UAVs, AI image processing, and automated analysis. This substitution enables continuous monitoring and identification of visibility issues without requiring constant human presence in the field.
2Reliability
If additional colcothar is scattered on places with poor visibility, then trail marking visibility is improved, but it becomes difficult to identify which specific places need additional marking
Solution Approach 1:
The system replaces manual field inspection with automated UAV-based aerial imaging and AI processing. The AI algorithm automatically analyzes images to identify locations where colcothar has blurred or disappeared, providing precise coordinates and visibility assessments without requiring human inspectors to physically traverse and examine each section of the trail.
Solution Approach 2:
The patent introduces an intermediary AI processing system that acts as a mediator between the physical trail markings and the decision-making process for maintenance. The AI analyzes the state of scattered materials, determines visibility quality, and identifies specific locations requiring re-application, translating physical conditions into actionable information.
3Reliability
If manual inspection of trail markings is performed, then visibility issues can be detected, but time and labor resources are consumed
Solution Approach 1:
The system replaces manual ground-based inspection with automated UAV aerial surveys combined with AI image processing. Multiple images can be captured and analyzed simultaneously, covering large trail sections quickly. The AI processing occurs automatically, identifying visibility issues and generating location data without human intervention, dramatically reducing the time required compared to manual inspection methods.
Solution Approach 2:
The patent transitions from ground-level inspection to aerial perspective using UAVs. This dimensional change allows for broader coverage and more comprehensive viewing of trail markings, enabling detection of visibility issues across difficult-to-access areas that would be time-consuming to inspect from ground level.
Data Source
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Figure 3
AI summary
The management server 2 acquires sensing information obtained by the UAV 1 sensing, from the sky, scatter area where a colcothar is scattered on a mountain climbing route, identifies a state of the colcothar on the basis of the sensing information, and identifies, on the basis of the state of the colcothar, at least one location for notification as a place that is difficult to visually recognize as the mountain climbing route.