Weather Drone Dispatch for Aircraft Flight Path Coverage Gaps
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Solution Overview
Problem
Current weather data collection systems, such as the Global Aircraft Meteorological Data Relay (AMDAR) program, have limitations in sourcing data from regions not covered by aircraft flights and are restricted to data from enrolled aircraft, resulting in incomplete and customizable weather data sets.
Innovation Solution
A computer-implemented method and system that analyzes flight path data to identify geographical regions not intercepted by aircraft, instructing weather drones to collect data in these areas, thereby supplementing existing weather data and enhancing weather prediction models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If weather data is collected only from aircraft participating in AMDAR programme, then data collection cost is reduced by using existing aircraft sensors, but weather data coverage is incomplete for regions not intercepted by aircraft flight paths
Solution Approach 1:
The patent combines existing AMDAR aircraft-based weather data collection with autonomous drone-based collection to create a hybrid system. The drone controller integrates flight path data from enrolled aircraft with autonomous drone deployment to fill coverage gaps, merging two different data sourcing approaches into a unified comprehensive weather monitoring system.
Solution Approach 2:
The autonomous drone acts as an intermediary between regions not covered by aircraft flight paths and weather data collection needs. The drone controller identifies coverage gaps and dispatches drones as intermediate data collection agents to reach geographical areas that primary aircraft-based systems cannot access.
2Device complexity
If existing aircraft on-board sensors are used for weather data collection, then system complexity is reduced, but geographical coverage is limited to regions where aircraft fly
Solution Approach 1:
The system dynamically adjusts weather data collection capabilities by deploying autonomous drones based on real-time analysis of aircraft flight path data. The drone controller continuously monitors flight path information and dynamically dispatches drones to cover identified gaps, making the overall system adaptable and dynamic rather than static and fixed.
Solution Approach 2:
The system performs preliminary analysis of aircraft flight path data to identify regions that will not be covered before deploying drones. The controller proactively determines coverage gaps and pre-positiones or dispatches drones to these identified regions in advance, ensuring comprehensive coverage before data collection needs arise.
3Ease of operation
If weather data collection is restricted to enrolled airline aircraft, then data sourcing is simplified, but data comprehensiveness is reduced
Solution Approach 1:
The autonomous drone system is self-managing, with the drone controller automatically analyzing flight path data, identifying coverage gaps, and dispatching drones without requiring manual intervention. The system serves itself by autonomously determining when and where additional weather data collection is needed and independently deploying resources to address those needs.
Data Source
AI summary
A computer implemented method and system of instructing one or more weather drones. The method includes analysing a first data set comprising flight path data indicative of the flight paths of one or more aircrafts over a predefined time period. The method includes identifying, based on said analysis, at least one geographical region which is not intercepted by or adjacent to, any of the flight paths of the one or more aircrafts. The method includes instructing one or more weather drones to fly to the at least one geographical region.