公开(公告)号：US20210182518A1

公开(公告)日：2021-06-17

申请号：US17037630

申请日：2020-09-29

Applicant: GUANGDONG UNIVERSITY OF TECHNOLOGY

Inventor： Jiewu LENG ,  Man ZHOU ,  Qiang LIU ,  Longzhang LI ,  Jianbo JING ,  Shide YE ,  Zhangyi WANG

IPC: G06K7/14 ,  G06F16/955 ,  G06F16/953 ,  G06F21/60 ,  G06K19/06

Abstract: A product anti-counterfeiting method based on a material signature blockchain. The method includes chaining of signature information and product information, QR code generation, query of on-chain information, and offline inspection. Also disclosed is an anti-counterfeiting system of the product anti-counterfeiting method based on a material signature blockchain. The system includes a product material signature module, a module of chaining signature information and product information, a module of generating a QR code, a module of querying on-chain information, and an offline inspecting module. The present invention proposes a product anti-counterfeiting method and a system based on a material signature blockchain according to the above content, which uses the material signature technology to solve the problem of the authenticity of the off-chain product.

公开(公告)号：US20210326974A1

公开(公告)日：2021-10-21

申请号：US17134366

申请日：2020-12-26

Applicant: GUANGDONG UNIVERSITY OF TECHNOLOGY

Inventor： Jiewu LENG ,  Man ZHOU ,  Yuxuan XIAO ,  Longzhang LI ,  Qiang LIU ,  Haochi PAN ,  Zihan LI ,  Zhangyi WANG ,  Jingyi CAI ,  Shuer LIN

IPC: G06Q30/08 ,  G06F30/20 ,  H04L9/08 ,  H04L9/06

Abstract: The disclosure relates to a blockchain-based outsourcing processing method, including the steps of: transmitting, by a demander, product demand information to a network data server to form a demand order, and transmitting, by a supplier, self-processing capability information to the network data server; performing, by the network data server, matching according to the demand information and the processing capability information, and transmitting the demand order to the supplier; selecting, by the supplier, the demand order to quote; confirming, by the two parties, quotation, establishing transaction and generating a smart contract, and writing the smart contract into a blockchain for storage; and after completing goods delivery, automatically executing account transfer according to the smart contract to complete outsourcing processing transaction.

公开(公告)号：US20220215246A1

公开(公告)日：2022-07-07

申请号：US17529311

申请日：2021-11-18

Applicant: GUANGDONG UNIVERSITY OF TECHNOLOGY

Inventor： Jiewu LENG ,  Weinan SHA ,  Zisheng LIN ,  Dewen WANG ,  Man ZHOU ,  Guolei RUAN ,  Qiang LIU ,  Hu ZHANG ,  Qianyi SU

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G05B13/02

Abstract: A method for constructing and training a Decentralized Migration Diagram Neutral Network (DMDNN) model for a production process, including: determining a production task input management node, distributed management nodes and a granularity of each of the distributed management nodes, and constructing a production system network; constructing network calculation nodes on each of the distributed management nodes; constructing and training a DMDNN model; and applying the trained DMDNN model in management and control of the production process.

公开(公告)号：US20210256438A1

公开(公告)日：2021-08-19

申请号：US17060148

申请日：2020-10-01

Applicant: GUANGDONG UNIVERSITY OF TECHNOLOGY

Inventor： Jiewu LENG ,  Man ZHOU ,  Qiang LIU ,  Guolei RUAN ,  Shide YE ,  Jianbo JING ,  Hu ZHANG

IPC: G06Q10/06 ,  G16Y10/25 ,  G16Y40/35 ,  G06Q50/04

Abstract: Disclosed is a blockchain-enabled edge computing method for production scheduling. The method includes modeling a smart contract between a device and a manufacturing unit, and using the smart contract to perform production scheduling on the device inside the manufacturing unit; one of the manufacturing units includes multiple devices; mounting each device on the blockchain operating node, the MES issues production instructions to the nodes of each manufacturing unit, at the same time, the nodes acquire production data of the device through multiple data sources of the device, the operating state data and process parameter data of each device are acquired in real time, and the data is directly chained from the device level; according to the production instructions and device parameters obtained by the manufacturing unit, using edge computing to dynamically adjust the device load, efficiency, and utilization.