Plant Spray Coverage Imaging for Real-Time Parameter Control
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Solution Overview
Problem
Current agricultural spray systems lack real-time tools to accurately quantify liquid coverage on plant surfaces, leading to inefficiencies in pesticide and foliar fertilizer application due to environmental and crop condition variability, and reliance on suboptimal application rates per acre.
Innovation Solution
A system using two cameras, one RGB and one SWIR, with image processing algorithms to automatically determine liquid coverage on plant surfaces, enabling real-time adjustments of sprayer parameters for improved coverage and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 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 patent replaces mechanical coverage assessment methods with an optical imaging system using cameras to capture and analyze liquid coverage on plant surfaces. The system uses image processing algorithms to automatically quantify coverage metrics, eliminating the need for manual assessment and providing precise real-time measurement data.
Solution Approach 2:
The patent introduces a crop-compatible dye as an intermediary substance mixed with the pesticide solution. This dye enhances the visibility of sprayed liquid on plant surfaces, allowing the imaging system to accurately detect and measure coverage. The dye acts as a mediator between the pesticide and the detection system without compromising crop safety.
2Adaptability or versatility
If spray parameters are adjusted based on seasonal experiments rather than real-time data, then some optimization can be achieved, but the system cannot adapt to changing environmental and crop conditions
Solution Approach 1:
The patent implements a real-time feedback system where the imaging system continuously monitors liquid coverage on plant surfaces during spraying operations. The system processes images to calculate coverage metrics and provides immediate feedback to operators, enabling them to adjust spray parameters on-the-spot to achieve optimal coverage under current environmental and crop conditions.
Solution Approach 2:
The patent performs preliminary image capture of plant surfaces before spraying to establish baseline coverage patterns. This preliminary action allows the system to compare pre-spray and post-spray images, accurately measuring the actual liquid deposition and enabling rapid adaptation to varying field conditions without time-consuming seasonal experiments.
3Reliability
If high application rates per acre are used to ensure adequate coverage, then pest control efficacy may be maintained, but resource waste increases and environmental pollution worsens
Solution Approach 1:
The patent enables operators to apply pesticide at precise coverage levels rather than using excessive application rates. By providing real-time visual feedback on liquid distribution, the system allows application of just enough pesticide to achieve adequate coverage, eliminating the need to over-apply to ensure sufficient penetration and retention on plant surfaces.
Solution Approach 2:
The patent utilizes color changes in the crop-compatible dye to indicate liquid coverage levels on plant surfaces. The dye changes appearance when deposited, providing visual cues that help operators assess coverage adequacy and adjust application rates accordingly, ensuring reliable pest control while minimizing pesticide waste and environmental pollution.
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
Enables real-time measurement and control of liquid coverage, optimizing spray parameters to enhance pest control and crop yield by reducing pesticide use and accounting for changing conditions.
Implementation Method 1
A system utilizing cameras, including RGB and SWIR cameras, to automatically determine liquid coverage on plant surfaces by receiving images, identifying liquid-covered areas
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.