Cultivation Data Platform Dynamic Recipe Optimization
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Solution Overview
Problem
Smart farm technologies face limitations in improving crop quality and productivity due to reliance on proprietary farming know-how and a focus on general growth environments, neglecting regional characteristics and expert knowledge sharing.
Innovation Solution
A cultivation data managing platform with a dynamic output function generates and distributes plant cultivation recipes based on plant cultivation data and control data through a community application, allowing optimization and fine-tuning of cultivation algorithms by expert collaboration and feedback, enabling the sharing of agricultural expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If farming knowhow is kept confidential by individual farm families, then each farm maintains its proprietary technology, but technological development and improvement are limited
Solution Approach 1:
The patent merges individual farm knowhow with expert knowledge by creating a platform that integrates cultivation data from multiple sources. The system combines proprietary farming techniques with scientific expertise to generate optimized cultivation recipes that benefit all users while protecting individual IP through controlled access and attribution mechanisms.
Solution Approach 2:
The cultivation recipe management system serves multiple functions: it preserves individual farm knowhow, incorporates expert knowledge, optimizes cultivation parameters, and distributes improved techniques across the community. This multi-functional platform resolves the contradiction by simultaneously protecting proprietary interests and enabling widespread technological improvement.
2Productivity
If cultivation control is based on general growth environment without considering regional characteristics, then productivity is focused on, but quality improvement and reasonable profits are limited
Solution Approach 1:
The system applies local quality by incorporating regional characteristics into cultivation recipes. The platform collects and analyzes data specific to different regions (climate, soil, local practices) and generates customized cultivation recommendations that adapt general principles to local conditions, thereby improving both quality and profitability for each region.
Solution Approach 2:
The cultivation recipes are made dynamic rather than static. The system continuously updates and refines cultivation parameters based on real-time data, expert feedback, and regional variations. This dynamic approach allows the system to adapt to changing conditions and optimize both productivity and quality simultaneously.
3Manufacturing precision
If cultivation algorithms are optimized for specific purposes, then crop quality and productivity improve, but system complexity increases
Solution Approach 1:
The platform acts as an intermediary that manages algorithmic complexity. Instead of requiring individual farms to develop complex optimization algorithms, the system provides a centralized platform that handles data analysis, expert consultation, and recipe generation. This mediator approach delivers sophisticated optimization capabilities while keeping the user interface simple and accessible.
Solution Approach 2:
The system creates and distributes optimized cultivation recipes as reusable templates. Once an optimization algorithm generates an effective cultivation plan for a specific purpose, that recipe can be copied and adapted for similar situations, avoiding the need to re-run complex algorithms for each individual case and reducing overall system complexity.
Data Source
AI summary
Disclosed are a cultivation data managing platform and a managing method using a dynamic output function. The present invention can generate a plant cultivation recipe on the basis of plant cultivation data and control data by using a communication application, and trade and distribute the generated plant cultivation recipe.