Selective Spray Nozzle Control via Per-Nozzle Weed Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current agricultural spray systems lack precision in targeting weeds, often leading to unnecessary chemical application and inefficiencies due to the inability to differentiate between crops and weeds in real-time.
Innovation Solution
A selective-spray system equipped with cameras and microprocessors that capture images of the agricultural field, analyze them for weed presence, and automatically activate nozzles to apply chemicals only where weeds are detected, adjusting for distance and travel speed to ensure accurate targeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If traditional spray systems apply chemicals uniformly across the field, then all areas receive treatment, but this leads to unnecessary chemical application and waste
Solution Approach 1:
The spray boom is divided into multiple independently controllable nozzle sections, each corresponding to a specific camera field of view. This segmentation allows selective activation of individual nozzles based on weed detection in their respective zones, preventing chemical application in weed-free areas and reducing overall chemical waste.
Solution Approach 2:
The system applies chemicals with localized precision by activating only the specific nozzles corresponding to areas where weeds are detected. Each nozzle operates independently based on local weed presence in its associated camera zone, ensuring chemicals are applied only where needed rather than uniformly across the entire field.
2Reliability
If the system processes multiple images simultaneously for each nozzle, then comprehensive weed detection is achieved, but system complexity increases
Solution Approach 1:
The image processing system is segmented into dedicated processing pipelines, with each camera's image processed independently by its corresponding nozzle controller. This segmentation allows parallel processing of multiple images without requiring complex centralized coordination, reducing overall system complexity while maintaining comprehensive weed detection across all zones.
3Measurement precision
If the spray response time is delayed to allow complete image analysis, then accurate weed identification is achieved, but the vehicle must slow down reducing productivity
Solution Approach 1:
Image capture and preliminary analysis are performed continuously as the vehicle moves through the field, with processing initiated before the vehicle reaches the optimal spray position. This preliminary action allows sufficient analysis time without requiring speed reduction, as the system is already processing images in advance of when spray activation is needed.
Solution Approach 2:
The system implements real-time image processing pipelines that rapidly analyze captured frames and generate spray commands within milliseconds. This rushing through the processing sequence enables accurate weed identification and spray activation without delaying the vehicle's forward motion or reducing field coverage productivity.
Data Source
AI summary
A method of selective spraying in a selective-spray system that includes a spray boom attached to an agricultural vehicle, the spray boom including a plurality of cameras and a plurality of selective-spray nozzles. The method includes capturing, with each camera, a respective image of a respective region of an agricultural field, each region at a predetermined distance from the spray boom, each image associated with a respective selective-spray nozzle; automatically analyzing, with a computer, each image for a presence of at least one weed; automatically detecting, with the computer, the at least one weed in one or more images; and automatically selectively spraying one or more of the respective regions of the agricultural field using one or more of the selective-spray nozzles according to the one or more images where the at least one weed is detected.