Predictive Nutrient Map for Variable Rate Fertilizer Control
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Solution Overview
Problem
Current agricultural systems face inefficiencies in material application due to latency in sensor feedback and machine control, leading to suboptimal material distribution based on field conditions, and lack of predictive capabilities for nutrient levels and weed presence, which can result in wasted resources and reduced yields.
Innovation Solution
An agricultural system that generates a predictive map using in-situ sensors and information maps to predict nutrient values and weed presence, allowing for real-time adjustment of material application rates and distribution, optimizing resource use and improving yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time sensor feedback is used to control material application, then material distribution accuracy is improved, but system latency reduces responsiveness
Solution Approach 1:
The system performs preliminary actions by generating predictive maps of nutrient and weed conditions before the material application process begins. This allows the control system to pre-calculate optimal application rates and prepare control strategies in advance, eliminating the need for real-time computational delays during actual application, thus resolving the latency problem while maintaining precision.
2Productivity
If predictive mapping is implemented to forecast nutrient levels, then resource allocation efficiency is improved, but computational complexity increases
Solution Approach 1:
The predictive mapping system performs all complex computational analysis before material application begins. By generating complete predictive maps of nutrient levels, weed presence, and optimal application rates in advance, the system eliminates the need for complex real-time calculations during application, thus improving resource allocation efficiency while managing computational complexity through upfront processing.
3Loss of energy
If variable rate material application is applied based on field conditions, then material use efficiency is improved, but control system complexity increases
Solution Approach 1:
The control system receives pre-generated predictive maps and optimal application rate recommendations before material application begins. This allows the variable rate application to be executed based on predetermined strategies rather than requiring complex real-time decision-making, thus improving material use efficiency while reducing the operational complexity of the control system during actual application.
Data Source
AI summary
An information map is obtained by an agricultural system. The information map maps values of a characteristic at different geographic locations in a worksite. An in-situ sensor detects nutrient values as a mobile material application machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive nutrient values at different geographic locations in the worksite based on a relationship between values of the characteristic in the information map and nutrient values detected by the in-situ sensor. The predictive map can be output and used in automated machine control.