Drone Buoy Dynamic Placement for Storm Forecasting
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Solution Overview
Problem
Current stationary ocean buoys are arbitrarily arranged relative to hurricane paths, leading to inadequate data collection in regions predictive of storm intensity, limiting early and accurate forecasts of rapid intensification.
Innovation Solution
A method and system utilizing drone buoys that determine optimal placement locations based on data received from initial positions, employing algorithms like Levenberg-Marquardt least squares, Nelder-Mean simplex, and Holland parametric tropical cyclone models to calculate buoy placement scores and adjust positions for enhanced data relevancy and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stationary buoys are placed at fixed geographical lattice points, then deployment is simple and cost-effective, but data collection coverage is inadequate for predicting storm intensity
Solution Approach 1:
The patent transforms stationary buoys into mobile drone buoys that can dynamically reposition themselves based on storm location and predicted intensity regions. The buoy system includes propulsion mechanisms and control systems that enable movement to optimal data collection locations, converting a static measurement network into a dynamic one that adapts to storm conditions.
Solution Approach 2:
The system uses real-time data from buoys and storm monitoring to calculate predicted storm intensity regions, then feeds this information back to determine optimal buoy placement locations. This closed-loop feedback system continuously adjusts buoy positions to maximize data relevancy for intensity prediction, resolving the contradiction between measurement precision and system complexity.
2Loss of information
If buoys are positioned arbitrarily relative to hurricane paths, then deployment is straightforward, but data collection in predictive regions is insufficient
Solution Approach 1:
The system performs preliminary calculations to predict storm intensity regions before the storm reaches buoy locations. By advance computing which regions will be most predictive of intensity and pre-positioning buoys in those areas, the system ensures complete data collection without requiring complex real-time repositioning during the storm event.
Solution Approach 2:
The buoy system includes onboard computing capabilities that enable individual buoys to autonomously determine their optimal positions based on storm data and prediction algorithms. This self-service positioning reduces the need for external control infrastructure, balancing information completeness with automation extent.
3Measurement precision
If more buoys are deployed to improve data coverage, then measurement precision increases, but system cost and complexity increase
Solution Approach 1:
The drone buoy is designed as a multi-functional platform that can serve multiple purposes: collecting meteorological data, tracking storm movement, predicting intensity regions, and guiding other buoy placements. This universal buoy performs several functions that would otherwise require multiple separate systems, reducing the total number of buoys needed while maintaining forecast accuracy.
Data Source
AI summary
A computer-implemented method, computer program product, and computer system may include determining, by a computing device, a first location on a body of water. The first location may be transmitted to a drone buoy. Data may be received from the drone buoy. A second location on the body of water to send to the drone buoy may be determined based upon, at least in part, the data received from the drone buoy.