Camera-Based Seed Rate Measurement for Planting Machines
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Solution Overview
Problem
Existing planting machines rely on open loop control schemes that set seed rates based on ground speed and estimated tons per acre, leading to inefficiencies and challenges in maintaining optimal seed or node rates, which affect plant population and yield in sugarcane cultivation.
Innovation Solution
A system that uses cameras to capture images of crop material, determines the seed rate by identifying attributes such as billet number, nodes, and eyes, and adjusts the planting machine's operating conditions, including travel speed and seed distribution rate, to maintain a target seed rate envelope, utilizing GPS data and real-time monitoring to optimize planting performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If open loop control schemes are used to set seed rates based on ground speed and estimated tons per acre, then the planting machine can operate with simple control mechanisms, but the seed rate accuracy and planting precision deteriorate
Solution Approach 1:
The patent implements a closed-loop control system that uses cameras to capture images of crop material, identifies attributes such as billet number, nodes, and eyes, and feeds this information back to automatically adjust the seed distribution rate. This feedback mechanism resolves the contradiction by enabling high seed rate accuracy through real-time monitoring and adjustment, eliminating the need for simple open-loop control while maintaining planting precision.
Solution Approach 2:
The patent replaces traditional mechanical seed rate control mechanisms with an optical-based vision system and automated control algorithm. Cameras and image processing algorithms substitute for mechanical adjustment devices, enabling precise seed rate control through digital measurement and automated adjustment, thereby resolving the contradiction between control simplicity and planting precision.
2Manufacturing precision
If real-time monitoring and adjustment systems are implemented to maintain target seed rate, then the planting precision and crop yield are improved, but the device complexity and cost increase
Solution Approach 1:
The patent employs a multi-functional integrated system where cameras serve multiple purposes: capturing images for seed rate measurement, monitoring crop material flow, and providing data for both control adjustment and record-keeping. This universal approach reduces overall system complexity by consolidating functions into single components, thereby resolving the contradiction between planting precision and device complexity.
Solution Approach 2:
The system implements self-adjustment capabilities where the control algorithm automatically modifies seed distribution rates based on real-time image analysis without requiring constant manual intervention. The system serves itself by autonomously detecting deviations from target seed rate and correcting them, reducing the need for complex external monitoring and control infrastructure.
3Measurement precision
If camera-based vision systems are used to identify crop material attributes, then the measurement precision of seed rate is improved, but the use of energy and device complexity increase
Solution Approach 1:
The patent processes image data selectively by focusing on key attributes such as billet number, nodes, and eyes that are most critical for seed rate determination. Rather than analyzing every pixel or feature in the image, the system performs partial processing on the most relevant characteristics, thereby reducing computational energy consumption while maintaining high measurement precision for seed rate.
Data Source
AI summary
A system for measuring crop seed rate of a planting machine, the system including a camera having a first field of view through which crop material may pass, and one or more electronic controllers in operable communication with the camera and the planting machine. The one or more electronic controls are configured to receive image data from the camera, identify one or more attributes of the crop material positioned in the field of view of the camera, determine a speed associated with the planting machine, determine a current crop seed rate of the planting machine based at least in part on the one or more attributes of the crop material in the field of view and the speed of the planting machine, and output one or more recommended operating conditions to the planting machine based at least in part on the determined crop seed rate.