Cloud-Based Spectrum Model Transfer for Agricultural Quality Monitoring
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Solution Overview
Problem
Existing agricultural product grading systems face challenges in model applicability across different spectrometers, leading to inefficient quality monitoring and evaluation, particularly in the context of fruit futures where standardization is low.
Innovation Solution
A photoelectric detection model transfer and sharing method based on a cloud service, utilizing a temperature compensation model and a spectrum transfer model built with an autoencoder neural network, enables the calibration and sharing of detection models across different detection terminals, facilitating remote monitoring and evaluation of agricultural product quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a spectrum detection model is built for a single instrument, then the model can be used for that specific instrument, but it cannot be directly applied to other instruments and requires repeated model building that wastes resources
Solution Approach 1:
The patent builds a universal detection model that can be applied across multiple spectrometers by incorporating instrument-specific parameters and calibration data into a single model framework. This allows one model to serve multiple instruments rather than requiring separate models for each device, thereby improving model adaptability while reducing the resources needed for repeated model building.
Solution Approach 2:
The patent segments the detection model into instrument-specific components (such as instrument parameters, calibration coefficients) and universal components (the core detection algorithm). This segmentation allows the universal part to be shared across instruments while accounting for instrument-specific variations, resolving the contradiction between model versatility and resource efficiency.
2Reliability
If conventional online grading devices are used, then detection can be performed, but they cannot meet monitoring requirements and modeling for each device is inefficient
Solution Approach 1:
The patent creates a universal detection model that enables monitoring capabilities across multiple devices simultaneously. Instead of requiring separate modeling for each online device, the universal model can be deployed across the entire supply chain, improving both monitoring reliability and modeling efficiency by eliminating redundant model building efforts.
3Ease of operation
If spectrum analysis is performed without model transfer capability, then detection can be done locally, but model sharing and remote updating are not possible
Solution Approach 1:
The patent introduces a cloud platform as an intermediary that enables model sharing and remote updating capabilities. The cloud platform serves as a mediator between the detection model and multiple spectrometers, allowing model transfer and updates without requiring direct connections between devices. This adds some system architecture complexity but enables remote sharing functionality that would otherwise be impossible.
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
This solution allows for the remote sharing and updating of detection models, improving the applicability and efficiency of quality monitoring across the entire supply chain, thereby enhancing consumer confidence and reducing resource waste.
Implementation Method 1
sensors include a photoelectric sensor and a temperature sensor; the photoelectric sensor is configured to acquire the spectrum information of the agricultural products
Data Source
AI summary
A photoelectric detection model transfer and sharing method and an Internet of Things monitoring and evaluation system based on a cloud service are provided. The transfer and sharing method includes: invoking a temperature compensation model and a spectrum transfer model to calibrate spectrum information of agricultural product samples, and invoking a detection model to compute the calibrated spectrum information to obtain detection results of the agricultural product samples. The Internet of Things monitoring and evaluation system calibrates spectrum information by using a spectrum transfer and sharing method, invokes a detection model for computing, and returns detection results to a detection terminal in real time, thereby realizing remote monitoring and evaluation of the quality of agricultural products.