Weed Sprayer Refill Estimation Using Field Distribution Models
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Solution Overview
Problem
Existing agricultural sprayers face challenges in predicting the exact amount of herbicides needed for targeted weed treatment, especially when completing a field with less than a full tank load, leading to potential economic losses from leftover product.
Innovation Solution
The use of a weed distribution model to estimate the required quantity of herbicides based on geographic location within the field, allowing tanks to be refilled only to a threshold level before completing the spraying task, combined with an imaging system to identify and selectively apply herbicides to specific weed types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tanks are refilled to full capacity before completing spraying, then sufficient product is available for treatment, but economic loss occurs from leftover product
Solution Approach 1:
The system performs preliminary estimation of the remaining herbicide needed by analyzing the weed distribution model and the area already sprayed. This allows the operator to refill tanks with the precise amount needed to complete the task, avoiding both shortages and excesses that would lead to economic loss.
Solution Approach 2:
The system continuously monitors spraying progress and compares it against the weed distribution model to provide real-time feedback on herbicide consumption. This feedback loop enables dynamic adjustment of refill quantities, ensuring that tanks are refilled with exactly the amount needed to complete the remaining unsprayed areas.
2Measurement precision
If selective spraying is implemented for different weed types, then herbicide application precision is improved, but system complexity increases
Solution Approach 1:
The system uses a single integrated imaging system and control unit that can identify multiple weed types and automatically select the appropriate herbicide. This multi-functional approach achieves selective spraying precision without requiring separate manual systems for each weed type, thereby limiting the increase in operational complexity.
Solution Approach 2:
The control system automatically processes imaging data, identifies weed types, selects appropriate herbicides, and controls spray application without requiring manual intervention. This automation handles the complexity internally while presenting a simplified interface to the operator, maintaining measurement precision without proportionally increasing operational complexity.
Data Source
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AI summary
A system for spraying an agricultural field provides a weed distribution model including information corresponding to a weed distribution as a function of geographic location within the field. An initial portion of the field is sprayed with a first product from a first tank leaving a remaining portion of the field to be sprayed. A quantity of the first product from the first tank required to complete the spraying of the remaining portion of the field is estimated based at least in part on the weed distribution model, the estimated quantity being less than the first tank capacity. The estimated quantity of the first product is loaded into the first tank so that the remaining portion of the field may be sprayed with the first tank being empty, at least to a threshold level, at the end of the spraying of the remaining portion of the field.