HAPS Exchange Timing Using Weather and Flight Route Prediction
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Solution Overview
Problem
Existing High Altitude Platform Stations (HAPS) require frequent maintenance, such as propeller replacement, which is challenging due to weather conditions and wind variations, necessitating optimal timing for exchange to minimize disruptions.
Innovation Solution
A data processing apparatus determines the optimal date and time for exchanging HAPS by analyzing meteorological data, flight vehicle status, and topographical data using machine learning models to predict stable weather conditions and efficient flight routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If HAPS exchange is performed frequently to maintain service continuity, then service reliability is improved, but operational complexity and weather-related risks increase
Solution Approach 1:
The system performs preliminary actions by predicting weather conditions and flight routes in advance before the HAPS exchange. The determination unit predicts meteorological phenomena and flight paths for multiple candidate dates, allowing operators to select optimal exchange timing that avoids adverse weather while maintaining service continuity.
Solution Approach 2:
The system provides beforehand cushioning by preparing multiple candidate exchange dates with predicted weather conditions and flight routes. This allows the system to cushion against adverse weather conditions by having pre-evaluated alternative dates ready, reducing weather-related risks without increasing operational complexity during the actual exchange.
2Adaptability or versatility
If HAPS exchange is performed during unstable weather conditions, then operational flexibility is improved, but flight safety and maintenance quality deteriorate
Solution Approach 1:
The system performs preliminary weather predictions and flight route assessments for multiple candidate dates before making the exchange decision. This allows operational flexibility to be maintained by evaluating various conditions in advance, while flight safety is ensured by selecting dates with favorable predicted weather conditions.
Solution Approach 2:
The system uses feedback from weather predictions and flight route assessments to determine the optimal exchange timing. The determination unit receives predicted meteorological phenomena and flight path information, then selects the candidate date with the most favorable conditions, balancing operational flexibility with flight safety.
3Measurement precision
If machine learning models are used to predict weather conditions and flight routes, then prediction accuracy is improved, but computational requirements and system complexity increase
Solution Approach 1:
The system introduces a determination unit as an intermediary that coordinates between multiple machine learning models (meteorological phenomenon prediction model and flight route prediction model). This intermediary integrates predictions from different models and synthesizes them into a comprehensive exchange timing recommendation, managing system complexity while maintaining high prediction accuracy.
Solution Approach 2:
The determination unit serves multiple functions: it predicts meteorological phenomena, predicts flight routes, evaluates candidate dates, and determines optimal exchange timing. By making this single component multi-functional, the system achieves high prediction accuracy through integrated modeling while avoiding the need for separate complex systems for each function.
Data Source
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AI summary
Provided is a data processing apparatus comprising: a data acquisition unit which acquires determination data used for determining a date and time of exchanging, wherein the determination data includes meteorological data between a flight area of a serving flight vehicle which forms a wireless communication area by radiating a beam to a ground to provide a wireless communication service for a user terminal within the wireless communication area and a takeoff area in which a to-be exchanged flight vehicle which is to replace the serving flight vehicle takes off; a data storage unit which stores the determination data acquired by the data acquisition unit; a proposed schedule acquisition unit which acquires a proposed schedule for exchanging between the serving flight vehicle and the to-be exchanged flight vehicle; a determination unit which determines a date and time of exchanging out of the proposed schedule for exchanging based on the determination data stored in the data storage unit; and a data output unit which outputs output data based on the date and time of exchanging determined by the determination unit.