Agricultural Product Label Parsing for Field Application Prescriptions
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Solution Overview
Problem
Conventional crop protection and enhancement product labeling is complex, non-standardized, and voluminous, leading to inefficient and often misapplied treatments, posing risks to crop yield and environmental safety, especially for growers without access to dedicated agronomists.
Innovation Solution
A computer-implemented method and system that analyzes crop protection and enhancement product labels to generate machine-readable procedures, creating an electronic prescription object with map layers for systematic application, ensuring accurate and efficient product application through a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional voluminous product labels with detailed written procedures are used, then comprehensive product information is provided, but the complexity and difficulty of understanding and compliance increase significantly for growers
Solution Approach 1:
The patent segments the complex product label information into structured, machine-readable components including application procedures, environmental requirements, crop-specific instructions, and safety guidelines. This segmentation transforms the voluminous unstructured text into organized data elements that can be systematically processed and presented to growers, reducing the perceived complexity while maintaining information completeness.
Solution Approach 2:
The patent introduces an intermediary computing system that acts as a mediator between the product label and the grower. This system automatically parses, analyzes, and translates the complex label information into user-friendly recommendations and compliance checks, eliminating the need for growers to directly interpret voluminous technical documents while ensuring no critical information is lost.
2Loss of information
If growers manually read and interpret voluminous product labels, then they can access product information, but the time required to understand and comply with procedures increases significantly
Solution Approach 1:
The patent replaces the manual mechanical process of reading and interpreting text labels with an automated computing system that uses optical character recognition (OCR), natural language processing, and rule-based engines to extract and analyze product information. This substitution eliminates the time-consuming human effort of manually navigating voluminous labels while ensuring accurate information retrieval and interpretation.
Solution Approach 2:
The patent performs preliminary analysis and structuring of product label information before the grower needs to use it. The system pre-processes the label data, organizes it by crop type, application scenario, and compliance requirements, and makes it readily accessible in a structured format, eliminating the need for growers to spend time interpreting raw label text during the application decision-making process.
3Adaptability or versatility
If conventional non-standardized label formats are used, then product-specific information is conveyed, but the difficulty of systematic application and compliance tracking increases
Solution Approach 1:
The patent creates a universal computing system that can process and standardize information from multiple different product labels with varying formats and structures. The system uses standardized data models and schemas to represent product information consistently across different products, enabling growers to access product-specific information through a unified interface while maintaining the ability to handle diverse label formats from different manufacturers.
4Loss of information
If growers without dedicated agronomists rely on complex product labels, then they can access product information, but the risk of misapplication and environmental damage increases
Solution Approach 1:
The patent implements feedback mechanisms where the computing system continuously monitors the application process, compares actual application parameters against the parsed product label requirements, and provides real-time alerts or corrections to the grower. This feedback loop ensures that even growers without dedicated agronomists can receive guidance on proper application techniques and compliance requirements, significantly reducing the risk of misapplication and environmental damage.
Data Source
AI summary
A method for systematic application of agricultural products includes receiving a label, analyzing the label to generate procedures, receiving a product and field selection, generating a prescription including a map and the procedures, executing the procedures in the field, and displaying the map. A computing system includes a processor and a memory storing instructions that, when executed by the processor, cause the computing system to: receive a label, analyze the label to generate procedures, receive a product and field selection, generate a prescription including a map and the procedures, execute the procedures in the field, and display the map. A non-transitory computer readable medium stores program instructions that when executed, cause a computer to receive a label, analyze the label to generate procedures, receive a product and field selection, generate a prescription including a map and the procedures, execute the procedures in the field, and display the map.