Drone Soil Probing With Multispectral Analysis for Seeding Decisions
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Solution Overview
Problem
Current drone-based soil testing methods are inefficient in capturing comprehensive soil data for ecological decision-making, particularly in agriculture, as they lack precision in moisture analysis and soil sensor deployment, and often fail to account for stress thresholds and multi-spectral imaging.
Innovation Solution
The use of AI-powered drones equipped with four probes for ground conductivity tests, frangible probes, and ribbon-line electrodes, which collect data on soil moisture and resistance, and integrate multispectral optical, radio, and acoustical imaging to correlate with agricultural inputs and outputs, enabling precise soil analysis and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional soil testing methods are used, then equipment complexity is reduced, but measurement precision and data comprehensiveness deteriorate
Solution Approach 1:
The patent combines multiple soil testing functions (conductivity testing, moisture analysis, stress threshold detection) into a single drone-based platform. The drone integrates multiple probes (four probes for conductivity, frangible probes for stress detection) and imaging systems (multispectral optical, radio, and acoustical imaging) to perform comprehensive soil analysis in one operation, thereby improving measurement precision while managing system complexity through integration.
Solution Approach 2:
The drone system is designed with multi-functionality to perform various soil testing operations including conductivity measurements, moisture content analysis, and stress threshold detection. The same drone platform can deploy different probe configurations and imaging modes depending on the specific testing requirements, making the system universally applicable to multiple soil analysis tasks and improving overall measurement capabilities.
2Loss of information
If comprehensive multi-spectral imaging is implemented, then data comprehensiveness is improved, but use of energy and device complexity worsen
Solution Approach 1:
The drone implements periodic action by capturing multispectral images at different wavelengths and intervals during flight. Instead of continuous imaging across all spectra simultaneously, the system periodically switches between different spectral bands (optical, radio, acoustical) to collect comprehensive soil data. This periodic approach reduces energy consumption compared to continuous multi-spectral imaging while still achieving complete data coverage.
3Measurement precision
If frangible probes with stress threshold detection are used, then measurement precision is improved, but device complexity and ease of operation worsen
Solution Approach 1:
The frangible probes incorporate feedback mechanisms that detect when the probe breaks due to exceeding soil stress thresholds. This breaking action provides direct feedback about soil compaction and hardness levels. The system automatically records the location and conditions when probe failure occurs, providing precise stress measurements without requiring complex manual interpretation or adjustment by the operator, thereby maintaining ease of operation despite the sophisticated measurement capability.
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 allows for accurate determination of optimal seeding locations by analyzing soil data, including resistance measurements and stress thresholds, improving agricultural practices and mitigating air pollution effects on crops through comprehensive soil measurement and data analysis.
Implementation Method 1
conducting a ground conductivity test using two or more probes coupled to respective landing pads of the drone
Implementation Method 2
receiving, using the computer, soil data, as part of the data, from the drone in response to testing the soil
Implementation Method 3
the probe is frangible and breaks off the drone when physical resistance from the soil exceeds a stress threshold
Implementation Method 4
physical contact of a probe into the soil, wherein the probe is frangible and breaks off the drone when physical resistance from the soil exceeds a stress threshold
Implementation Method 5
another probe is a ribbon-line electrode providing continual measurement data in response to being dragged along the soil
Implementation Method 6
via multispectral optical, radio, and acoustical passive imaging
Implementation Method 7
Measurements such as radio signal reflectivity to soil moisture using the present invention
Data Source
AI summary
Capturing data in a drone enabled environmental for testing soil and ecological decision making includes initiating, using a computer, collection of data from multiple sources using a drone. The data includes information about soil at a specified soil location, in response to the drone flying over air space of a physical or geographical location respective to the soil location and/or landing at the soil location. Soil data is received, as part of the data, from the drone in response to testing the soil. The testing of the soil can include conducting a ground conductivity test using two or more probes coupled to respective landing pads of the drone, and positioning the drone over the soil location such that the two or more probes contact the soil. The data is analyzed to determine a best location for seeding and growing a plant in the soil.