Environmental Factor Control Model for Real-Time Cultivation
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Solution Overview
Problem
Current environmental factor control systems in microorganism cultivation apparatuses require human operator expertise for real-time monitoring and control, making real-time adjustments impossible.
Innovation Solution
A method and apparatus for transforming discontinuous training data into continuous form using serialization points and interpolation methods to train an environmental factor control automation model, enabling real-time control through a computer device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human operator control is used for environmental factor monitoring and control, then control accuracy based on expertise is improved, but real-time control capability deteriorates
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the microorganism cultivation apparatus that replicates its operational characteristics. This virtual model is trained to mimic the decision-making patterns of expert human operators, enabling the system to copy human expertise while operating in real-time without requiring actual human presence for each control decision.
Solution Approach 2:
The patent replaces the mechanical human operator system with an automated artificial intelligence system. The AI model processes sensor data and generates control commands automatically, substituting the human operator's manual monitoring and adjustment actions with an automated computational system that operates continuously in real-time.
2Ease of manufacture
If discontinuous training data is used for AI model training, then data processing simplicity is improved, but model training effectiveness deteriorates
Solution Approach 1:
The patent transforms discontinuous training data into continuous form by generating intermediate data points between existing measurements. This continuity transformation ensures that the AI model receives comprehensive temporal information about environmental factor changes, improving training effectiveness while maintaining the simplicity of using existing measurement data as the foundation.
Data Source
AI summary
Disclosed is a non-transitory computer readable medium storing a computer program, wherein the computer program includes instructions to perform following steps for data processing when the computer program is executed by one or more processors, the steps including: recognizing at least one continuous section from each raw data subset; determining at least one serialization point, based on a start point and an end point of each of the at least one continuous section for each of the raw data subset; and generating a training data set by generating serialized training data, based on the at least one serialization point.