KR-102962004-B1 - The carbon reduction amount predicting system according to the reuse and recycle of the lungs ICT instrument using the artificial intelligence and method thereof

KR102962004B1KR 102962004 B1KR102962004 B1KR 102962004B1KR-102962004-B1

Abstract

The present invention relates to data processing technology, and more specifically, to a system and method for quantitatively predicting the amount of carbon reduction generated during the reuse or recycling of waste information and communication technology (ICT) devices using an artificial intelligence (AI) model. The carbon reduction amount prediction system for the reuse and recycling of waste ICT devices using artificial intelligence according to the present invention comprises: a resource information collection unit (10) that collects specification information and substrate images of waste ICT devices; a resource classification unit (20) that classifies waste ICT devices into reusable resources and recyclable resources based on the information collected by the resource information collection unit; a reusable resource calculation unit (30) that calculates the carbon reduction amount of waste ICT devices classified as reusable resources by the resource classification unit; and a recyclable resource calculation unit (40) that receives substrate images of devices classified as recyclable resources by the resource classification unit and predicts the carbon reduction amount resulting from recycling through a pre-trained artificial intelligence (AI) model. The artificial intelligence (AI) model is characterized by being trained using a plurality of substrate images and a label for the precious metal content of individual substrates estimated from the total amount of precious metals measured by physically melting all of the plurality of substrates.

Inventors

최백남

Assignees

(주)그리니시스템

Dates

Publication Date: 20260508
Application Date: 20250909

Claims (4)

A resource information collection unit (10) that collects specification information and circuit board images of waste ICT devices; A resource classification unit (20) that classifies the waste ICT device into reusable resources and recyclable resources based on the information collected by the resource information collection unit; A reusable resource calculation unit (30) that calculates the carbon reduction amount of waste ICT devices classified as reusable resources in the resource classification unit above; and It includes a recycling resource calculation unit (40) that receives an image of a substrate of a device classified as a recycling resource in the above resource classification unit and predicts the amount of carbon reduction due to recycling through a previously trained artificial intelligence (AI) model. A system for predicting carbon reduction in the reuse and recycling of waste ICT devices using artificial intelligence, characterized in that the above artificial intelligence (AI) model is trained using a plurality of substrate images and a label for the precious metal content of individual substrates estimated from the total amount of precious metals measured by physically melting the entire plurality of substrates.
In Article 1, A carbon reduction prediction system for waste ICT devices using artificial intelligence, characterized by further including a report generation unit (50) that generates a carbon reduction certificate supporting an ESG management report using carbon reduction amount data calculated from the above-mentioned reuse resource calculation unit (30) and recycling resource calculation unit (40).
In Article 1 or Article 2, A system for predicting carbon reduction resulting from the reuse and recycling of waste ICT devices using artificial intelligence, characterized in that the above artificial intelligence (AI) model is a deep learning model including a Convolutional Neural Network (CNN) for extracting visual features of an image.
A resource information collection step for collecting specification information and circuit board images of discarded ICT devices; A resource classification step for classifying the waste ICT devices into reusable resources and recyclable resources based on the information collected in the resource information collection step above; A reusable resource calculation step for calculating the carbon reduction amount of waste ICT devices classified as reusable resources in the above resource classification step; A recycling resource calculation step that receives an image of the substrate of a device classified as a recycling resource in the above resource classification step and predicts the amount of carbon reduction resulting from recycling through a pre-trained artificial intelligence (AI) model; A method for predicting carbon reduction amount resulting from the reuse and recycling of waste ICT devices using artificial intelligence, characterized in that the above artificial intelligence (AI) model is trained using a plurality of substrate images and a label for the precious metal content of individual substrates estimated from the total amount of precious metals measured by physically melting the entire plurality of substrates.

Description

System and method for predicting carbon reduction amount according to the reuse and recycling of waste ICT instruments using artificial intelligence The present invention relates to data processing technology, and more specifically, to a system and method for quantitatively predicting the amount of carbon reduction generated during the reuse or recycling of waste information and communication technology (ICT) devices using an artificial intelligence (AI) model. In modern society, as the adoption of information and communication technology (ICT) devices expands and replacement cycles shorten, the amount of electronic waste generated and the production of new products are simultaneously surging. Accordingly, the need to reduce carbon emissions to address environmental issues such as global warming is emerging worldwide, and this is being treated as a key task in corporate ESG management. Against this backdrop, resource circulation activities, such as repairing and reusing waste ICT devices or extracting and recycling valuable metals and components from them, are attracting attention as an effective means of carbon reduction. In particular, as carbon reductions achieved through reuse and recycling can be recognized as carbon emission trading or corporate eco-friendly activity achievements, it has become important to accurately calculate their value. However, most currently used methods for calculating carbon reduction rely on manual processes, making them inefficient and difficult to derive objective and consistent results. In particular, unlike reuse, which can be calculated relatively easily based on the extension of the product's remaining lifespan, recycling requires taking into account the complex component configuration of waste ICT devices, various types of materials, and different recycling process efficiencies, making it very difficult to accurately predict the amount of carbon reduction. As prior art, Korean published patent No. 10-2024-0166180 discloses a 'system for automatically calculating carbon reduction amount,' and registered patent No. 10-2689276 discloses a 'method for determining carbon emissions reduced by second-hand trading.' However, these prior art technologies had limitations in accurately predicting carbon reduction amounts by reflecting the unique complex material composition of each waste ICT device or the characteristics of various recycling processes. In other words, there was a problem of reduced prediction accuracy due to the use of comprehensive calculation methods that did not consider the characteristics of individual devices, or the failure to apply artificial intelligence models suitable for handling multiple variables in the recycling process. FIG. 1 is a configuration diagram of a system for predicting carbon reduction amount based on the reuse and recycling of waste ICT devices using artificial intelligence according to the present invention. FIG. 2 is a flowchart of a method for automatically predicting carbon emission reduction through the reuse and recycling of waste ICTS resources according to the present invention. FIG. 3 is a schematic diagram of the configuration of a resource information collection unit according to the present invention. FIG. 4 is a drawing illustrating the vibration-damping structure of a mounting stand according to the present invention. Hereinafter, a system and method for predicting carbon reduction amount based on the reuse and recycling of waste ICT devices using artificial intelligence according to the present invention will be described in more detail with reference to the drawings. Before describing in more detail the system and method for predicting carbon reduction amounts resulting from the reuse and recycling of waste ICT devices using artificial intelligence according to the present invention, The present invention is capable of various modifications and may take various forms, and embodiments (aspects or examples) are to be described in detail in the text. However, this is not intended to limit the present invention to the specific disclosed forms, and it should be understood that it includes all modifications, equivalents, and substitutions that fall within the spirit and scope of the invention. As shown in FIG. 1, the carbon reduction amount prediction system for the reuse and recycling of waste ICT devices using artificial intelligence according to the present invention comprises a resource information collection unit (10), a resource classification unit (20), a reusable resource calculation unit (30), a recycled resource calculation unit (40), and a report generation unit (50). The resource information collection unit (10) above is configured to collect information regarding waste ICT devices to be processed. Specifically, the information may include structured data such as the type of device, year of manufacture, specifications, etc., and unstructured data such as images of the device and internal circuit boards (PCB). The