Adaptive Query Tool for Real-Time Agricultural Data Collection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for collecting agricultural data are inefficient and imprecise, as they rely on end-of-season market research, making it difficult to gather current and relevant information from farmers, which is no longer applicable by the time data is collected.
Innovation Solution
A system and method using a server platform with a query tool that integrates data collection into agricultural processes, allowing farmers to provide data in real-time or near real-time through an input routine, with adaptive questioning based on process parameters and boundary conditions, minimizing unnecessary queries and enhancing data precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data collection is performed at the end of the agricultural period using market research institutes, then data collection coverage is achieved, but data timeliness and relevance deteriorate as farmers are no longer aware of relevant factors
Solution Approach 1:
The system performs data collection during the agricultural process itself rather than after completion. The query tool integrates with input routines to capture data at the moment when farmers are actively engaged in agricultural activities, ensuring both timeliness and relevance of the collected information.
Solution Approach 2:
The system establishes a continuous feedback loop where data is collected, processed, and made available for immediate use. The query tool continuously queries farmers during ongoing agricultural processes, ensuring data remains current and actionable throughout the agricultural period.
2Loss of information
If comprehensive data collection queries are presented to farmers, then data completeness improves, but farmer effort and response burden increase
Solution Approach 1:
The system applies local quality by customizing queries based on specific agricultural processes and contexts. The query tool analyzes input routine data and presents only relevant questions tailored to the farmer's current activity, rather than presenting a uniform comprehensive questionnaire to all farmers.
Solution Approach 2:
The system implements partial action by selectively querying only the necessary data points relevant to the current agricultural context. The query tool filters and presents a subset of potential questions based on the specific input routine being executed, avoiding unnecessary queries while maintaining data completeness.
3Loss of information
If data collection is integrated into input routines with adaptive questioning, then data relevance improves, but system complexity increases
Solution Approach 1:
The system merges the query tool with the existing input routine infrastructure. By integrating data collection functionality into the agricultural input routines that farmers already use, the system leverages existing technical frameworks rather than creating separate complex data collection systems.
Solution Approach 2:
The query tool is designed with universal functionality to adapt to various agricultural processes and input routines. It can dynamically adjust its questioning based on the context while maintaining a consistent underlying architecture, reducing overall system complexity through multi-functionality.
Data Source
AI summary
A method and a system for the process-related generation of agricultural data is disclosed. A server platform includes an input tool and a query tool, wherein the user uses the input tool to executes a process-related agricultural input routine, such as a documentation routine to document an agricultural process, or a planning routine for planning an agricultural process, and wherein the query tool is linked through IT to the input tool. The user provides agricultural process parameters in the input routine to the server platform. Further, the server platform includes data memory with query data comprising different lists of agricultural questions with boundary conditions associated therewith. The query tool compares the process parameters and the boundary conditions, and based on the comparison, the query tool selects a list of agricultural questions and queries the user about questions from the selected list.