Agricultural Machine Controller for Variable Planting Depth
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current agricultural operations face challenges in accurately determining soil moisture levels and adjusting operations accordingly, particularly due to variations in snow accumulation and melt patterns, which affect planting timing and depth, as well as chemical application uniformity across fields with uneven topography.
Innovation Solution
An agricultural machine equipped with a communication component, controller, and controllable subsystems that receive and process data sets on soil parameters over time, generating maps and control signals to adjust operations such as planting depth and chemical application rates based on real-time soil moisture and snow depth data, utilizing unmanned aerial vehicles (UAVs) for data collection and remote source integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional uniform agricultural operations are used across the entire field, then operational simplicity is maintained, but planting depth and chemical application uniformity deteriorate due to soil moisture variations
Solution Approach 1:
The system implements local quality by creating spatially variable planting depth prescriptions based on soil moisture conditions in different field zones. The controller receives soil moisture data from multiple locations and generates location-specific control signals that adjust planting depth according to local soil conditions, ensuring each area is planted at the optimal depth for its moisture level.
Solution Approach 2:
The system applies dynamics by enabling real-time adjustment of planting depth during field operations. The controllable subsystem dynamically modifies planting depth based on live soil moisture data and the generated map, allowing the operation to adapt continuously to varying soil conditions rather than maintaining a fixed depth throughout the field.
2Measurement precision
If soil moisture monitoring is expanded to cover the entire field, then measurement precision improves, but device complexity and data processing requirements increase
Solution Approach 1:
The system segments the field into multiple monitoring zones with soil moisture sensors distributed across different locations. Rather than attempting to measure every point simultaneously, the field is divided into representative areas, each monitored by sensors that provide data for generating localized soil moisture maps and prescriptions.
Solution Approach 2:
The controller acts as an intermediary that receives soil moisture data from sensors, processes the information to generate soil moisture maps and planting depth prescriptions, and then transmits control signals to the controllable subsystem. This intermediary processing layer simplifies the system by centralizing data interpretation and control decision-making.
3Loss of information
If real-time data collection from multiple sources is implemented, then information completeness improves, but data processing time and operational delays increase
Solution Approach 1:
The system performs preliminary action by generating the soil moisture map and planting depth prescription before the actual planting operation begins. Soil moisture data is collected and processed in advance, allowing the controllable subsystem to operate with pre-determined optimal parameters for each field zone, eliminating real-time calculation delays during field work.
Solution Approach 2:
The system maintains continuity of useful action by ensuring that data collection, map generation, and control signal transmission occur seamlessly during field operations. The controllable subsystem continuously receives control signals based on the generated map, allowing uninterrupted planting operations without stopping for data processing or manual adjustments.
Data Source
AI summary
An agricultural machine has a communication component configured to receive a first data set and a second data set. The first and second data sets comprise indications of a soil parameter of a worksite. The first data set is captured at an earlier time than the second data set. The agricultural machine also has a controller configured to receive the first and second data sets and, based on the first and second data sets, generate a map of the worksite. The agricultural machine also has a controllable subsystem configured to receive a control signal from the controller. The control signal is generated based on both a position of the agricultural machine within the worksite and the generated map. The control signal is configured to control operator of the controllable subsystem.