In-Row Weed Identification for Selective Sprayer Nozzle Control
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Solution Overview
Problem
Traditional agricultural spraying methods lack the ability to selectively identify and target weeds within crop rows, leading to inefficient use of agricultural fluids and potential misidentification of weeds as crops.
Innovation Solution
A system comprising an imaging device and a computing system that captures images of a field, identifies plant stalks, determines associated parameters, and classifies plants as crops or weeds, thereby controlling the agricultural sprayer to selectively dispense fluids based on these identifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional spraying methods are used to apply herbicide across the entire field, then weed coverage is reduced, but a much larger volume of agricultural fluid is dispensed than necessary
Solution Approach 1:
The system applies different spraying actions to different locations within the field by identifying individual plants and selectively activating nozzles based on whether they are crops or weeds. This local differentiation allows herbicide to be applied only where needed (on weeds) rather than uniformly across the entire field, reducing overall fluid consumption while maintaining effective weed control.
Solution Approach 2:
The field is segmented into individual plant positions, with each plant identified and classified separately. The boom assembly is divided into multiple nozzle sections that can be independently controlled. This segmentation enables selective spraying at the plant level, allowing the system to dispense agricultural fluid only on identified weeds while skipping crops, thereby reducing total fluid volume required.
2Loss of substance
If selective spraying systems are used to target only weeds or crops, then agricultural fluid usage is optimized, but difficulty identifying weeds present within a crop row increases
Solution Approach 1:
The system transitions from two-dimensional image data to three-dimensional plant characterization by identifying stalks and determining parameters such as height, orientation, and position. This dimensional transformation provides additional discriminatory information that enables accurate differentiation between crops and weeds even when they are in close proximity within the same crop row, thereby improving identification precision while maintaining selective spraying efficiency.
Solution Approach 2:
The imaging and identification process is performed in advance of the spraying operation, allowing the system to pre-classify plants as crops or weeds before herbicide application begins. This preliminary classification enables the control system to pre-program which nozzles should be activated, ensuring accurate weed identification and targeted spraying without compromising fluid usage efficiency.
3Measurement precision
If imaging devices and computing systems are used to identify plant stalks and classify plants, then weed identification precision is improved, but device complexity increases
Solution Approach 1:
The system replaces manual or mechanical plant identification methods with an automated imaging and computing system. The imaging device captures visual data of plants, and the computing system automatically processes this data to identify stalks and classify plants based on determined parameters. This substitution of mechanical processes with automated optical and computational processes improves classification accuracy while managing system complexity through automation.
Solution Approach 2:
The computing system autonomously performs plant identification and classification without requiring external intervention. The system self-processes the image data, automatically identifies plant characteristics, determines parameters, and classifies plants as crops or weeds. This self-service capability improves measurement precision while containing complexity within the automated system rather than requiring complex external operational procedures.
Data Source
AI summary
A system for identifying weeds present within a field includes an imaging device configured to capture an image depicting a plurality of plants present within the field. Furthermore, the system includes a computing system communicatively coupled to the imaging device, with the computing system configured to receive the image captured by the imaging device. Additionally, the computing system is configured to identify a stalk of each of the plurality of the plants depicted within the received image. Moreover, the computing system is configured to determine a parameter associated with each identified stalk. In addition, the computing system is configured to identify each plant of the plurality of plants as a crop or a weed based on the corresponding determined parameter.