Agricultural Harvester Feeder Imaging for Crop Population Counting
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Solution Overview
Problem
Modern agricultural harvesters are unable to accurately quantify crop population within a field during harvesting operations, which is crucial for assessing the effectiveness of planting operations.
Innovation Solution
An agricultural harvester equipped with an imaging device to capture images of harvested material and a computing system to analyze these images for crop ears, determining crop population by comparing with planting data, and adjusting ground speed for optimal harvesting efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If modern harvesters use traditional monitoring systems, then yield per unit area can be determined, but crop population cannot be quantified
Solution Approach 1:
The patent replaces traditional mechanical yield monitoring systems with an optical imaging system using cameras and image processing algorithms. The imaging device captures images of harvested material, and computer vision algorithms automatically identify and count crop ears, enabling crop population quantification without complex mechanical sensors.
Solution Approach 2:
The system creates optical copies (images) of the harvested material and processes these copies to extract population data. By capturing images of crop ears during harvesting and analyzing them through image processing, the system determines crop population without direct physical measurement of each plant.
2Measurement precision
If imaging devices are used to capture harvested material, then crop population can be determined, but computing resources increase
Solution Approach 1:
The system extracts only the essential information needed for population counting from the full images - specifically identifying crop ear features and their positions. The image processing focuses on detecting and counting crop ears rather than analyzing all visual data, reducing computational load while maintaining measurement precision.
Solution Approach 2:
The system processes images at appropriate resolution and detail levels needed for accurate counting without unnecessary over-processing. By applying image processing algorithms that identify crop ears with sufficient accuracy but without excessive computational overhead, the system achieves precise population measurement with reasonable computing resource usage.
3Loss of information
If crop population data is collected during harvesting, then planting effectiveness can be assessed, but harvesting operation time increases
Solution Approach 1:
The imaging and counting processes are performed during the harvesting operation itself, utilizing the natural flow of harvested material through the feeder. By integrating population measurement with the harvesting process rather than conducting separate surveys, the system collects planting effectiveness data without adding significant time to the operation.
Solution Approach 2:
The system continuously captures images and processes population data throughout the harvesting operation. The imaging device operates continuously as material passes through the feeder, and image processing occurs in real-time or near-real-time, maintaining continuous useful action for both harvesting and population measurement simultaneously.
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
Accurately determines crop population without significant computing resources, providing insights into planting effectiveness and optimizing harvesting efficiency.
Implementation Method 1
an imaging device positioned within feeder, with the imaging device configured to generate image data depicting the harvested material entering or being conveyed through the feeder
Data Source
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AI summary
An agricultural harvester (10) includes a feeder (42) configured to convey harvested material from a harvesting implement (36) to a threshing and separating assembly (50). Furthermore, the agricultural harvester (10) includes an imaging device (102) positioned within feeder (42), with the imaging device (102) configured to generate image data depicting the harvested material entering or being conveyed through the feeder (42) during the harvesting operation. Additionally, the agricultural harvester (10) includes a computing system (110) communicatively coupled to the imaging device (102). In this respect, the computing system (110) is configured to analyze the generated image data to identify crop ears present within the harvested material entering or being conveyed through the feeder (42). Moreover, the computing system (110) is configured to determine the crop population within at least a portion of the field based on the identified crop ears present within the harvested material.