Agricultural Optical Spatial Mapping for Precision Control
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Solution Overview
Problem
Current agricultural control systems lack enhanced optical spatial mapping capabilities, which limits their ability to optimize operations such as plowing speed and depth, soil analysis, and fuel efficiency.
Innovation Solution
A system integrating an agricultural working means with a first imaging device for optical data acquisition, sensors for data collection, and a position unit for spatial data processing, allowing for real-time correlation and processing of optical, sensor, and positional data to generate enhanced 2D and 3D maps for improved operational control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical measurements and sensor data are correlated in real-time for enhanced spatial mapping, then measurement precision and operational control are improved, but device complexity increases
Solution Approach 1:
The patent combines multiple data sources (optical measurements from cameras, sensor data from soil moisture and temperature sensors, and positional data from GPS) into a unified spatial mapping system. The data processing unit integrates these diverse inputs to create comprehensive field maps, resolving the contradiction by merging separate measurement systems into a coordinated whole that achieves high precision without requiring each individual component to be overly complex
Solution Approach 2:
The data processing unit serves multiple functions simultaneously: it processes optical data from imaging devices, integrates sensor measurements, correlates positional information, generates spatial maps, and provides real-time operational control. This multi-functional approach allows the system to achieve high measurement precision across multiple parameters while avoiding the need for separate dedicated systems for each function, thereby managing overall system complexity
2Productivity
If real-time data processing and correlation is implemented for operational control, then productivity and efficiency are improved, but use of energy increases
Solution Approach 1:
The system performs preliminary spatial mapping and field analysis before actual agricultural operations begin. By pre-processing optical and sensor data to create detailed field maps identifying soil variations, moisture levels, and optimal planting zones, the system enables farmers to plan operations in advance. This preliminary action reduces the need for real-time energy-intensive processing during actual field work, as decisions are based on pre-analyzed data
Solution Approach 2:
The system implements feedback loops where sensor data from ongoing operations is continuously correlated with spatial maps and operational parameters. This feedback mechanism allows real-time adjustments to planting depth, irrigation rates, and fertilizer application based on actual field conditions, improving operational efficiency and productivity while optimizing energy use by making adjustments only when and where needed rather than applying uniform treatments across entire fields
3Manufacturing precision
If detailed optical spatial mapping is performed for soil analysis and anomaly detection, then manufacturing precision of agricultural operations is improved, but loss of time in data processing increases
Solution Approach 1:
The data processing system divides the field into discrete zones or segments based on optical measurements and sensor data. Each segment is analyzed independently for specific characteristics such as soil type, moisture content, and vegetation health. This segmentation allows parallel processing of different field areas, reducing overall processing time while maintaining detailed precision for each individual zone. The system can process one segment while simultaneously analyzing another, rather than sequentially analyzing the entire field
Data Source
Figure 1
AI summary
A system 1 for controlling agricultural operations comprising an agricultural working means 10 for working on an agricultural field 100; a first imaging device 20 attached to the agricultural working means 10 for acquiring images of an environment of the agricultural working means 10, wherein the first imaging device 20 is adapted to provide optical data; an agricultural implement 16 comprised by the agricultural working means 10; a sensor 18 at or for the agricultural implement 18, wherein the sensor 18 is adapted to provide sensor data; a position unit 30 for determining the absolute position of the agricultural working means 10, wherein the position unit 30 is adapted to provide position data; and a data processing unit 50 for processing optical data received at least from the first imaging device 20 in relation to position data received from the position unit 30 and the sensor data.