US 11,861,567 B2
Method and internet of things system for determining gas meter measurement failure of smart gas
Zehua Shao, Chengdu (CN); Yong Li, Chengdu (CN); Junyan Zhou, Chengdu (CN); Lei Zhang, Chengdu (CN); and Guanghua Huang, Chengdu (CN)
Assigned to CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Chengdu (CN)
Filed by CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Sichuan (CN)
Filed on Nov. 14, 2022, as Appl. No. 18/054,926.
Claims priority of application No. 202211256468.8 (CN), filed on Oct. 14, 2022.
Prior Publication US 2023/0075722 A1, Mar. 9, 2023
Int. Cl. G06Q 10/20 (2023.01); G16Y 10/35 (2020.01); G01F 25/10 (2022.01); F17D 5/02 (2006.01)
CPC G06Q 10/20 (2013.01) [F17D 5/02 (2013.01); G01F 25/15 (2022.01); G16Y 10/35 (2020.01)] 11 Claims
OG exemplary drawing
 
1. A method for determining a gas meter measurement failure of a smart gas, wherein the method is implemented based on an Internet of Things (IoT) system, including: a smart gas user platform, a smart gas service platform, a smart gas device management platform, a smart gas sensing network platform, and a smart gas object platform that interact in sequence, wherein the smart gas device management platform includes an indoor smart gas device management sub-platform and a smart gas data center;
the method comprising:
by the smart gas data center, obtaining, based on the smart gas sensing network platform, gas flow information of pipelines of each level from at least one flow monitoring device, the at least one flow monitoring device being configured in the smart gas object platform;
by the indoor smart gas device management sub-platform,
based on the gas flow information, determining a flow consistency rate of an area relating to each pipeline of each level, the flow consistency rate being determined according to a ratio of the gas flows in an upper pipeline and a lower pipeline;
for each pipeline of each level,
based on environment information of a node at the level, determining an environmental feature vector by an environmental feature layer;
based on historical monitoring information, determining a historical feature vector by a historical feature layer;
based on the environmental feature vector, the historical feature vector, and a flow consistency rate of the node at the level, determining a consistency rate prediction value of the node at the level by a prediction layer;
based on the consistency rate prediction value of the node at the level, a device model, and consistency rate prediction values of nodes at an upper level and a lower level, determining a corrected flow consistency rate of the node at the level by a correction layer, wherein the environmental feature layer, the historical feature layer, the prediction layer, and the correction layer are machine learning models;
in response to the corrected flow consistency rate not satisfying a first preset condition, determining a candidate area;
determining a target gas meter based on gas meter reading information of the candidate area, and determining a maintenance plan for the target gas meter; and
sending the maintenance plan to the smart gas data center, and sending the maintenance plan to the smart gas user platform based on the smart gas service platform.