Daiwa Securities Group has filed a patent for a system that accurately estimates the deterioration of products stored in metal containers. The system utilizes a predictive model trained through storage tests and machine learning. It takes into account data related to the container, contents, storage environment, and degree of deterioration. The system allows for the estimation of deterioration based on inputted data about the target product’s container, contents, and storage environment. AiexpertInter’s report on Daiwa Securities Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to AiexpertInter’s company profile on Daiwa Securities Group, virtual banking assistant was a key innovation area identified from patents. Daiwa Securities Group's grant share as of September 2023 was 17%. Grant share is based on the ratio of number of grants to total number of patents.
Deterioration estimate system for products in metal containers
A recently filed patent (Publication Number: US20230258555A1) describes a deterioration estimate system for products contained in metal containers. The system utilizes a predictive model trained through machine learning using data obtained from storage tests of actual products. The system includes an inputter to transmit data for estimating deterioration and a transmitter to transmit the computed degree of deterioration based on the data.
The training data used for the predictive model includes container data, contents data, environmental data, and deterioration data related to the actual product. The data transmitted from the inputter includes container data, contents data, and environmental data related to the target product to estimate the degree of deterioration.
The patent also mentions that the container is made of a metal sheet with an inner coating. The deterioration data transmitted from the transmitter and included in the training data can include information such as the depth of corrosion on the inner surface of the metal sheet, the outline of the corrosion, the state of dispersion of the corrosion, and the amount of metal elution to the contents.
Additionally, the system may include an evaluator that evaluates the degree of deterioration and sorts it into multiple grades. The container data can include information about the dimensions and material of each part of the container, as well as the inner coating. The contents data can include information about the type and amount of contents, as well as the pH value. The environmental data includes the temperature of the storage environment.
The transmitter in the system is configured to transmit data while sorting the degree of deterioration into multiple grades and labeling the sorted data. The evaluator then evaluates the degree of deterioration based on the sorted and labeled data.
Overall, this patent describes a deterioration estimate system that utilizes machine learning and various data inputs to predict the degree of deterioration in products contained in metal containers. The system aims to provide accurate estimates and sorting of deterioration levels, potentially helping manufacturers and consumers make informed decisions about product quality and safety.
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