Patent ID: 11867548
Assignee: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
Field: Measurement (Instruments)
Classification: CPC G | IPC G

Claim 5:
6. An Internet of Things (IoT) system for correcting a smart gas flow, wherein the system includes a user platform, a service platform, a management platform, a sensor network platform, and an object platform, wherein the management platform is configured to:
obtain reading data of a gas meter;
determine a first confidence level of the reading data based on the reading data; wherein the reading data includes first reading data and second reading data, the first reading data being historical reading data of the gas meter, and the second reading data being current reading data corresponding to a current time point, and to determine a first confidence level of the reading data based on the reading data, the management platform is further configured to:
predict, based on the first reading data, a distribution interval of third reading data and a distribution probability corresponding to the third reading data; the third reading data being a theoretical value of the current reading data, and the current reading data being a gas consumption from time when the gas meter starts metering to the current time point; and
take a distribution probability corresponding to the second reading data in the distribution interval of the third reading data as the first confidence level;

in response to a determination that the first confidence level is smaller than a confidence level threshold, obtain a working condition parameter; the confidence level threshold being determined through an experience value; and
determine, based on the working condition parameter, a gas meter correction manner; the working condition parameter including a standard temperature and pressure and a current temperature and pressure, and to determine, based on the working condition parameter, a gas meter correction manner, the management platform is further configured to:
determine, based on second reading data, the standard temperature and pressure, and the current temperature and pressure, a correction value of the second reading data through a reading data correction model, wherein the reading data correction model is a machine learning model.