Urban Wind Hazard Mapping for Low-Altitude Flight Paths
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to account for individual wind components in urban environments, particularly near obstacles like buildings, which can pose significant hazards to urban aviation operations.
Innovation Solution
A system that translates horizontal and vertical wind measurements into potential hazard metrics by segregating and combining 'Shake' (instantaneous turbulence) and 'Sharp' (wind gradients) data, visualizing these components as an overlay on a geographic area using a GUI, and generating navigation pathways for urban drones and air taxis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing meteorological data is used to derive wind hazards, then general weather threat assessment is provided, but individual wind components near obstacles such as buildings are not recognized
Solution Approach 1:
The patent segments the wind hazard assessment into two distinct components: 'Shake' representing instantaneous turbulence and 'Sharp' representing wind gradients near obstacles. This segmentation allows each component to be measured and analyzed separately with appropriate precision while managing overall system complexity through modular processing.
Solution Approach 2:
The patent applies local quality by differentiating between general meteorological wind hazards and localized wind components specifically near obstacles like buildings. The system measures and presents wind hazard information at different spatial scales, providing detailed local assessments where needed while maintaining broader context.
2Reliability
If detailed microscale wind hazard data is provided for urban aviation, then flight safety is improved, but data processing and visualization complexity increases
Solution Approach 1:
The patent divides complex wind hazard data into two manageable segments: Shake (turbulence) and Sharp (wind gradients). This segmentation simplifies data processing by handling each component separately with dedicated algorithms, while the results are integrated to provide comprehensive safety assessments for urban aviation operations.
Solution Approach 2:
The patent introduces an intermediary visualization layer that processes and presents complex wind hazard data in an accessible format. The system translates raw meteorological data into intuitive visual representations and hazard metrics that can be easily interpreted by aviation operators and regulators.
3Reliability
If real-time wind hazard assessment is implemented for urban aviation, then operational safety is enhanced, but computational resources and processing time are consumed
Solution Approach 1:
The patent segments the computational tasks into separate processing stages for Shake and Sharp components, allowing each to be handled with appropriate computational intensity. This segmentation enables real-time processing by dividing the workload into manageable, parallelizable operations that can execute efficiently with available computational resources.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for utilizing non-RAM memory to implement calculating a first wind metric over a geographic area, wherein the first wind metric reflects total wind velocity vector differences. The method further calculates a second wind metric over the geographic area, wherein the second wind metric reflects a horizontal wind gradient near obstacles. The method further generates a first data set of the first wind metric and a second data set of the second wind metric and combines the first data set and the second data set into a combined data set representing a combination of the first wind metric and the second wind metric. The combined data set represents wind hazards in an urban environment with buildings and is used to identify or generate low altitude flighted vehicle navigation paths for urban flighted vehicles, such as drones or air taxis.