Agricultural Implement Force Sensing for Soil Condition Mapping

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Solution Overview

Problem

Existing systems for measuring and interpreting forces on agricultural implements primarily focus on automatic control, lacking a comprehensive system for analyzing soil conditions and enhancing optical spatial mapping for improved agricultural operations.

Innovation Solution

A system comprising a working implement, force sensors, a position unit, and a data interpretation unit with machine learning capabilities, which correlates force measurements with position data to provide insights into agricultural field conditions, abnormalities, and events of interest, while also enhancing optical spatial mapping for optimized agricultural operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If force measurements are used for automatic control of working implements, then control automation is improved, but the system cannot provide comprehensive analysis of soil conditions and field abnormalities

Engineering Contradiction:

Improveautomatic controlVSAvoidsoil condition analysis

Core Design Contradiction:

Extent of automationVSLoss of information

Solution Approach 1:

The force measurement system is extended to perform multiple functions: not only automatic control of working implements but also comprehensive analysis of soil conditions, detection of field abnormalities, and generation of precision agricultural maps. The system integrates force sensors, position units, and data interpretation units with machine learning capabilities to achieve multi-functional operation.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

A data interpretation unit with machine learning capabilities is introduced as an intermediary between force sensors and the control system. This intermediary processes raw force data, correlates it with position data, and generates meaningful interpretations about soil conditions and field abnormalities, thereby preventing information loss.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If raw force data is measured by sensors, then measurement capability is improved, but manual interpretation of the data is cumbersome and difficult

Engineering Contradiction:

Improveforce measurementVSAvoiddata interpretation

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs self-service by automatically interpreting force data through a data interpretation unit with machine learning capabilities. The system correlates force measurements with position data, automatically generates interpretations about soil conditions and field abnormalities, and presents processed information to users without requiring manual analysis of raw data.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual interpretation of force data is replaced by an automated data interpretation unit using machine learning algorithms. The mechanical/manual process of analyzing force measurements is substituted with an electronic/computational system that automatically correlates force data with position data and generates meaningful interpretations.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of information

If optical measurements are taken for agricultural operations, then field monitoring capability is improved, but enhanced optical spatial mapping for optimized operations is not achieved

Engineering Contradiction:

Improvefield monitoringVSAvoidoptimized agricultural operations

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

Optical measurements are merged with force measurements and position data in a unified data interpretation system. The system combines multiple data sources (optical sensors, force sensors, position units) and uses machine learning to correlate them, generating comprehensive interpretations that enable optimized agricultural operations and enhanced spatial mapping.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system transforms optical measurements into meaningful parameters through machine learning processing. By changing the parameter representation from raw optical data to interpreted field characteristics and spatial maps, the system enables optimized agricultural operations based on comprehensive field analysis.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250040469A1System for measuring and interpreting a force

Publication Date: 2025.02.06 KUBOTA CORP

AI summary

A system for measuring and interpreting a force, comprises at least one working implement, for acting on an agricultural field and at least one force sensor, for measuring a force of the working implement. Further, a data interpretation unit calculates an interpretation of the measured force; wherein the data interpretation unit comprises a machine learning unit that calculates the interpretation of the measured force. Also, a system for controlling agricultural operations comprises at least one agricultural working means for working on an agricultural field and at least one first imaging device located at the agricultural working means for acquiring images of an environment of the agricultural working means.