Cultivation Management Device Using Learning Model for Fruit Tree Shape Control

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Solution Overview

Problem

Conventional methods for managing fruit vegetable plant cultivation lack guidance on adjusting cultivation plans when desired growth states are not achieved, particularly for complex parameters like nutritious and tasteful fruit production, and do not provide instructions for corrective actions.

Innovation Solution

A cultivation and management device that utilizes a learning model trained on environment state information, cultivation evaluation indices, and work history to determine and output appropriate shape change works for fruit vegetable plants and trees, enabling accurate predictions and corrective actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional work plan management is used, then simple growth prediction can be achieved, but no corrective work instructions are provided when desired growth states are not achieved

Engineering Contradiction:

Improvework adjustment guidanceVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system compares predicted growth states with desired growth states and provides feedback in the form of corrective work instructions. The learning model continuously learns from the differences between predicted and desired outcomes, adjusting work plans to achieve target growth states.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

A learning model serves as an intermediary between the work plan management system and the cultivation process. This intermediary analyzes growth predictions, compares them with desired states, and generates appropriate work instructions to bridge the gap.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If simple cultivation methods are used, then basic growth can be achieved, but complicated parameters for nutritious and tasteful fruit production cannot be controlled

Engineering Contradiction:

Improvefruit quality controlVSAvoidcultivation complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system manages multiple cultivation parameters simultaneously (environmental conditions, work timing, plant shape) to control complex fruit quality attributes. The learning model adjusts these parameters based on predicted growth outcomes to achieve desired nutrition and taste.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The cultivation process is segmented into multiple controllable factors (environmental parameters, work operations, plant morphology). Each factor is managed independently but coordinated through the learning model to achieve comprehensive quality control.

Inventive Principle:

Principle #1Segmentation

3Reliability

If work plans are executed without adjustment guidance, then basic cultivation tasks can be performed, but desired growth states cannot be achieved when predictions fall outside manageable ranges

Engineering Contradiction:

Improvegrowth outcome reliabilityVSAvoidoperation simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system automatically generates corrective work instructions without requiring manual intervention. The learning model self-adjusts the work plan based on predicted growth outcomes, providing self-service functionality that improves reliability while maintaining operational simplicity.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12250910B2Management device for cultivation of fruit vegetable plants and fruit trees, learning device, management method for cultivation of fruit vegetable plants and fruit trees, learning model generation method, management program for cultivation of fruit vegetable plants and fruit trees, and learning model generation program

Publication Date: 2025.03.18 OMRON CORP

AI summary

A cultivation and management device for fruit vegetable plants and fruit trees includes environment state information on an environment state of a fruit vegetable plant or a fruit tree to be cultivated, planned cultivation evaluation index information on a preplanned cultivation evaluation index of the fruit vegetable plant or the fruit tree, a calculation unit configured to determine and output a work including a shape change work for the fruit vegetable plant or the fruit tree with respect to inputs of the environment state information and the planned cultivation evaluation index information with a learning model, and an output unit configured to output the work including the shape change work for the fruit vegetable plant or the fruit tree.