The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 25, 2025

Filed:

Sep. 10, 2024
Applicant:

Chengdu Qinchuan Iot Technology Co., Ltd., Sichuan, CN;

Inventors:

Zehua Shao, Chengdu, CN;

Yong Li, Chengdu, CN;

Bin Liu, Chengdu, CN;

Guanghua Huang, Chengdu, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 67/1097 (2022.01); G16Y 10/35 (2020.01); G16Y 40/35 (2020.01); H04L 67/1004 (2022.01); H04L 67/1095 (2022.01); H04L 67/568 (2022.01);
U.S. Cl.
CPC ...
H04L 67/1097 (2013.01); G16Y 10/35 (2020.01); G16Y 40/35 (2020.01); H04L 67/1004 (2013.01); H04L 67/1095 (2013.01); H04L 67/568 (2022.05);
Abstract

Disclosed is a method for managing gas data, which is implemented by at least one processor of an Internet of Things (IoT) system for managing the gas data. The method comprises: obtaining to-be-stored-gas data and downstream user features; determining a user importance level based on the downstream user features; determining accessing frequency distribution features of the to-be-stored-gas data; determining a risk degree of data through a second prediction model; constructing query feature vectors based on pipeline data, and determining a risk degree of the gas pipeline based on the query feature vectors; determining a gas data level; determining a data redundancy level; generating redundant data blocks of the to-be-stored-gas data; and storing the to-be-stored gas data and the redundant data blocks in the at least one storage node of the at least one sub-data center based on loading distribution features.


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