Plant Surface Coverage Sensing With RGB-SWIR Feedback Control
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Solution Overview
Problem
Current agricultural systems lack real-time tools to effectively quantify liquid coverage on plant surfaces, leading to inefficient pesticide and foliar fertilizer application, which results in wasted resources and reduced pest control efficacy due to the inability to account for changing environmental and crop conditions.
Innovation Solution
A system utilizing cameras, including RGB and SWIR cameras, to automatically determine liquid coverage on plant surfaces by processing images and adjusting sprayer parameters in real-time, allowing for precise control of droplet distribution and retention without the need for added dyes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional spray systems are used without real-time monitoring, then pesticide application can be performed, but liquid coverage on plant surfaces cannot be accurately measured, leading to inefficient application and resource waste
Solution Approach 1:
The system implements real-time feedback by capturing images of plant surfaces with sprayed liquid, processing these images to determine liquid coverage values, and using this information to optimize subsequent spray applications. This closed-loop feedback mechanism enables accurate measurement of liquid coverage while improving spray application efficiency through data-driven decisions.
Solution Approach 2:
The patent replaces manual visual inspection and physical measurement methods with an automated optical system using cameras and image processing algorithms. This substitution of mechanical/optical systems enables precise, non-contact measurement of liquid coverage on plant surfaces, significantly improving measurement precision without reducing productivity.
2Adaptability or versatility
If farmers apply pesticides at standard rates per acre, then application can be completed efficiently, but variability in application efficiency on plants and impact of environmental conditions are not accounted for
Solution Approach 1:
The system transitions from static, fixed-rate pesticide application to dynamic, adaptive application by continuously monitoring liquid coverage on plant surfaces and adjusting spray rates in real-time based on actual coverage conditions, environmental factors, and crop characteristics. This enables the system to adapt to varying environmental conditions while optimizing pesticide quantity used.
Solution Approach 2:
The patent changes the control parameter from fixed application rate per acre to variable application rate based on real-time liquid coverage measurements and environmental conditions. By dynamically adjusting spray parameters such as flow rate, pressure, and timing, the system achieves better adaptability to environmental conditions while reducing overall pesticide usage through precision application.
3Reliability
If spray parameters are optimized without real-time coverage data, then spray application can be performed, but the effectiveness cannot be verified until season-long experiments are completed
Solution Approach 1:
The system performs preliminary verification of spray effectiveness by measuring liquid coverage on plant surfaces immediately after application, rather than waiting for season-long experiments. This preliminary action provides early feedback on whether the spray achieved adequate coverage, allowing for immediate adjustments and eliminating the need for lengthy experimental periods to verify effectiveness.
Solution Approach 2:
The patent implements real-time feedback loops where liquid coverage measurements are obtained during or immediately after spray application, providing immediate information about application effectiveness. This feedback enables rapid verification and adjustment of spray parameters, significantly reducing the time required to assess pest control effectiveness compared to traditional season-long experimental approaches.
4Difficulty of detecting and measuring
If dyes are added to sprayed liquid to enable detection, then liquid coverage can be visualized, but the system complexity and cost increase
Solution Approach 1:
The system uses light as an intermediary to detect liquid coverage on plant surfaces. By illuminating the sprayed plant surfaces with light sources and capturing the reflected or transmitted light with cameras, the system enables liquid detection without adding dyes or chemicals to the spray mixture, thereby maintaining system simplicity while achieving effective detection.
Solution Approach 2:
The patent substitutes chemical detection methods (adding dyes to the liquid) with optical detection methods using cameras and image processing. This substitution eliminates the need for additional chemicals and simplifies the system by using non-contact optical sensing to detect and measure liquid coverage on plant surfaces.
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 system enables real-time optimization of agrochemical application, reducing waste and improving pest control by accurately measuring and adjusting liquid coverage based on environmental and crop conditions, leading to more efficient use of resources and enhanced crop yields.
Implementation Method 1
A system utilizing cameras, including RGB and SWIR cameras, to automatically determine liquid coverage on plant surfaces
Data Source
AI summary
Presented herein are systems and methods for automatically determining liquid coverage on plant surfaces. More particularly, in certain embodiments, presented herein is a system for receiving an image depicting one or more plant surfaces, automatically identifying the plant surfaces in the image and distinguishing portions covered by liquid, and automatically determining a liquid coverage value. In some embodiments, the system determines changes to liquid spraying parameters to achieve desired liquid coverage values. In some embodiments, the system uses two cameras to cooperatively conduct background removal in images and determination of liquid coverage.