Tea Leaf Withering Schedule Prediction Using Spectral Imaging
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Solution Overview
Problem
The monitoring and control of the withering process in tea production is challenging due to slow moisture determination, inefficient real-time monitoring, and managing multiple withering troughs, which delays the next processing stage.
Innovation Solution
A system and method using image processing and machine learning models to estimate moisture percentage in tea leaves through spectral data analysis, generating a withering schedule based on ambient parameters, and fine-tuning the schedule for accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microwave oven is used for moisture determination, then moisture measurement is achieved, but the process is time-consuming and destructive
Solution Approach 1:
The patent replaces the mechanical/thermal microwave heating method with a non-contact optical sensing system using cameras and image processing algorithms to estimate moisture content, eliminating the need for physical sample destruction and lengthy heating processes
Solution Approach 2:
The system creates a visual copy (image) of the tea leaf and uses image analysis to infer moisture content, rather than physically processing the actual sample. This allows moisture estimation without destroying the original material or requiring time-consuming heating cycles
2Measurement precision
If multiple withering troughs are monitored using shared microwave oven, then moisture measurement is possible, but the monitoring becomes slow and complicated
Solution Approach 1:
The patent divides the monitoring system into multiple independent camera units, each capable of monitoring one or more troughs simultaneously. This eliminates the bottleneck of shared microwave oven and allows parallel monitoring of multiple troughs
Solution Approach 2:
The system replaces the centralized microwave oven with distributed optical sensors (cameras) that can independently and simultaneously monitor multiple troughs, dramatically increasing monitoring throughput and efficiency
3Measurement precision
If traditional moisture checking methods are used, then moisture level is determined, but real-time monitoring is difficult and delays processing
Solution Approach 1:
The patent replaces slow traditional moisture checking methods with rapid optical imaging and computational analysis, enabling real-time moisture estimation without physical sample processing
Solution Approach 2:
The system continuously captures images and pre-processes them in real-time, maintaining a ready stream of moisture estimation data that can immediately inform processing decisions without waiting for batch microwave analysis
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise and efficient monitoring of tea leaf moisture levels, optimizing the withering process by providing real-time scheduling and reducing delays in tea production.
Implementation Method 1
receiving a plurality of spectral images of a plurality of reference tea leaves captured using a spectral camera device
Data Source
AI summary
As the withering process of tea leaves takes a long time to reach a desired moisture level, estimating when it is time to move to the next step to reach the target tea leaf moisture is difficult and inefficient. Method and system disclosed herein provide an approach for withering schedule prediction of tea leaves. The system, by performing a spectral data analysis on an image of a plurality of tea leaves, estimates the moisture percentage in the plurality of tea leaves, for a selected time stamp. Based on the predicted moisture level, a current temperature value, a current relative humidity value, and a current time stamp, the system generates a withering schedule for the plurality of tea leaves. The generated withering schedule is fine-tuned based on a course correction of an impact of deviation in one or more ambient parameters on the prediction of the withering schedule.