Aerial Commodity Monitoring Route Optimization
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Solution Overview
Problem
Current methods for evaluating commodity conditions, such as crop growth and viability, are inefficient as they often waste time and energy during aircraft transit between sampling locations and lack structured data collection and analytical route planning, leading to inadequate monitoring of commodity conditions.
Innovation Solution
Implementing a method where an aircraft travels along a strategically developed route over a geographic area, using continuous image data collection and remote sensing techniques like aerial photography, with an optimization algorithm to minimize costs and maximize data usefulness, allowing for quantitative assessment of commodity conditions across the region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If aerial photography is used to monitor commodity conditions at discrete sampling locations, then commodity condition data can be collected, but time and energy are wasted during aircraft transit between locations
Solution Approach 1:
The patent implements continuous image data collection throughout the entire aircraft flight path, eliminating idle transit time. The aircraft continuously captures images of commodities along its travel route, ensuring that every moment of flight contributes to data collection rather than being wasted during transitions between discrete sampling locations.
Solution Approach 2:
The system dynamically adjusts the travel route based on real-time and historical data about commodity conditions, uncertainty levels, and forecasted values. The route is not fixed but adapts to maximize the value of data collection while minimizing transit time, allowing the aircraft to prioritize areas of highest interest.
2Loss of information
If traditional aerial photography methods are used with discrete sampling locations, then some commodity data is collected, but no analytical approach exists for optimizing the travel route
Solution Approach 1:
The system incorporates feedback loops where collected image data and commodity condition information are analyzed to update forecasts and uncertainty levels. This feedback drives iterative improvements in route optimization, with each flight's data informing subsequent route planning decisions to maximize information gain while minimizing flight time and costs.
Solution Approach 2:
The system performs preliminary analysis of available data, forecasts, and uncertainty levels before planning each flight route. By pre-processing and evaluating commodity condition data, the system can proactively identify high-priority areas for monitoring and structure routes to maximize data value before the aircraft even departs.
3Reliability
If more comprehensive image data collection is performed across geographic areas, then better commodity condition assessment is achieved, but costs and energy consumption increase
Solution Approach 1:
The system changes key parameters including travel route, altitude, speed, and imaging frequency based on commodity conditions, uncertainty levels, and forecasted values. By dynamically adjusting these parameters, the system optimizes the balance between data collection quality and energy consumption, concentrating resources on areas of highest priority rather than uniformly covering entire geographic areas.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables improved forecasting of supply and demand for commodities, facilitating better production planning, harvest decisions, and commodity trading by providing more accurate and comprehensive data on crop conditions, reducing waste and enhancing efficiency in data collection.
Implementation Method 1
An aircraft can be flown along a travel route over a geographic area containing crops, and photographs of the crops can be taken at a discrete set of sampling locations along the route of the aircraft
Data Source
AI summary
Various tools, strategies and techniques are provided for evaluating the condition of one or more commodities in one or more regions of interest. Collection of image data associated with the commodities can be facilitated through use of an aircraft traveling a predetermined travel route over the regions of interest. The collected image data may be analyzed to evaluate the condition of the commodities, forecast commodity production, and/or to perform other tasks.