CN113259483B - Intelligent gas cross-regional data interaction method and system - Google Patents
Intelligent gas cross-regional data interaction method and system Download PDFInfo
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- CN113259483B CN113259483B CN202110682928.2A CN202110682928A CN113259483B CN 113259483 B CN113259483 B CN 113259483B CN 202110682928 A CN202110682928 A CN 202110682928A CN 113259483 B CN113259483 B CN 113259483B
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- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
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Abstract
The invention discloses an intelligent gas cross-regional data interaction method, which comprises the following steps: establishing an intelligent gas Internet of things; sensing the first data by the sensing network platform; the management platform forms an in-network cloud platform; the method comprises the steps that an off-network cloud platform collects first data during off-network operation and generates a first database; when a user platform initiates a gas meter calibration request, a management platform generates first calibration data and sends the first calibration data to the user platform through a service platform; and the user platform calibrates the intelligent gas meter according to the first calibration data. The invention discloses an intelligent gas cross-regional data interaction system. The intelligent gas cross-regional data interaction method and the intelligent gas cross-regional data interaction system realize unmanned and automatic calibration of the intelligent gas meter, save manpower and material resources for intelligent gas meter calibration on one hand, and form industrial big data on the other hand, thereby providing references for governments and related resource departments.
Description
Technical Field
The invention relates to the intelligent gas system technology, in particular to an intelligent gas cross-region data interaction method and system.
Background
With the improvement of living standard, various intelligent gas meters are gradually on the market, so that the problem of headache in the operation of gas companies is solved. The IC card meter, the CPU card intelligent gas meter, the wired remote gas meter, the wireless remote gas meter, the network type infrared data transmission gas meter and the like appear in succession.
Along with the large-scale popularization of intelligent gas meters, a plurality of old districts also start to replace and install the intelligent gas meters, the gas meters need to be checked after the intelligent gas meters are replaced and installed, the checking work of the intelligent gas meters reconstructed by the old districts is very complicated, and personnel are needed to go on the door to carry out field adjustment on the gas meters.
Disclosure of Invention
The invention aims to solve the technical problem that adjustment and check work of an intelligent gas meter in the prior art requires a large amount of labor expenditure, and aims to provide an intelligent gas cross-region data interaction method and system to solve the problem.
The invention is realized by the following technical scheme:
the intelligent gas cross-region data interaction method comprises the following steps:
establishing an intelligent gas Internet of things; the intelligent gas Internet of things comprises a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
and the user platform calibrates the intelligent gas meter according to the first calibration data.
The invention discloses a remote processing method for abnormal data acquisition of a gas meter, and relates to a remote processing method for the gas meter, in particular to a remote processing method for the gas meter, which is disclosed by the Chinese patent with the application number of 201811400620.9 in the prior art. At present, the operation and maintenance of the intelligent gas meter are generally responsible for a local management unit such as a gas company and the like, and the operation and maintenance of the intelligent gas meter can not be remotely processed by the local management unit of corresponding equipment. The invention comprises the following steps: 1) acquiring data of a gas meter, and monitoring the data of the gas meter; 2) when the indication value data of the running gas meter of the low-pressure user can not be collected continuously, analyzing and judging: 3) carrying out data-free fault diagnosis processing on the intelligent gas meter for multiple days; 4) remote processing, including checking marketing files; checking the electric energy meter/alternating current sampling parameters of the terminal; checking a terminal task; checking a terminal clock; the meter is calibrated. The method only discloses remote monitoring and data processing of the intelligent gas meter, and the monitoring standard is only related to the master station, so that the data cannot be corrected according to different environments, for example, when the air temperature and the air pressure of the master station fluctuate, the data of the intelligent gas meter adopting the ultrasonic volume detection technology also fluctuates in precision.
When the method is applied, the off-network cloud platform obtains data of the intelligent gas Internet of things by providing computing service for the intelligent gas Internet of things, the data comprises calibrated data of the intelligent gas meter, fluctuation data of the intelligent gas meter under different environments, gas consumption data of the intelligent gas meter at different time intervals and the like, and a first database can be formed through the data.
By the five-platform structure, the intelligent gas meter can be calibrated in a mode that the user platform initiates a calibration request to the management platform. As a preferred scheme, after the intelligent gas meter is installed, the user platform automatically sends a calibration request to the management platform, at this time, the management platform may match corresponding calibration data from the first database as first calibration data in an intra-network operation or an extra-network operation manner, the matching process may adopt regional matching, or may match based on a basic model set in the intra-network cloud platform or the extra-network cloud platform, such as a model of a classifier, and the user platform may perform calibration operation according to a matching result, thereby providing an unmanned operation space for the calibration operation of the intelligent gas meter. Through the steps, the unmanned and automatic calibration of the intelligent gas meter is realized, on one hand, the manpower and material resources for the calibration of the intelligent gas meter are saved, on the other hand, the industrial big data is formed, and the reference is provided for governments and related resource departments.
Further, forming an in-network cloud platform includes the following sub-steps:
establishing a service platform A, a management platform A and a sensing network platform A on the in-network cloud platform; respectively establishing a user platform A and an object platform A on two platforms interacted with the in-network cloud platform;
the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; and the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A.
Further, the step of interacting the plurality of in-network cloud platforms with at least one out-of-network cloud platform and completing the out-of-network operation through the out-of-network cloud platform comprises the following substeps:
establishing a user platform B and an object platform B on the management platform A, and establishing a service platform B, a management platform B and a sensing network platform B on the off-network cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted.
Further, the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
and the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B.
Further, the management platform B is further configured to use a gas usage time period and a gas usage duration corresponding to the gas usage parameter in the first data as second data, and the management platform B performs classification calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
Wisdom gas is data interaction system across region includes:
the intelligent gas Internet of things system comprises an intelligent gas Internet of things, a gas sensor and a gas sensor, wherein the intelligent gas Internet of things is configured to comprise a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
and the user platform calibrates the intelligent gas meter according to the first calibration data.
Further, a service platform A, a management platform A and a sensing network platform A are established on the in-network cloud platform; a user platform A and an object platform A are respectively established on two platforms of the cloud platform in the network in an interactive mode;
the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; and the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A.
Further, a user platform B and an object platform B are established on the management platform A, and a service platform B, a management platform B and a sensing network platform B are established on the off-network cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted.
Further, the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
and the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B.
Further, the management platform B is further configured to use a gas usage time period and a gas usage duration corresponding to the gas usage parameter in the first data as second data, and the management platform B performs classification calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the intelligent gas cross-regional data interaction method and the intelligent gas cross-regional data interaction system realize unmanned and automatic calibration of the intelligent gas meter, save manpower and material resources for intelligent gas meter calibration on one hand, and form industrial big data on the other hand, thereby providing references for governments and related resource departments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a schematic diagram illustrating a method for intelligent gas cross-region data interaction according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating steps of an in-network cloud platform construction method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating steps of a method for constructing an extranet cloud platform according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of interaction between different systems via an extranet cloud platform according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an in-network cloud platform system architecture according to an embodiment of the present invention;
fig. 6 is a schematic diagram of interaction between different management platforms through an extranet cloud platform according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Examples
For convenience of explaining the intelligent gas cross-regional data interaction method, please refer to fig. 1, which shows a flow chart of the intelligent gas cross-regional data interaction method provided by the embodiment of the present invention, the intelligent gas cross-regional data interaction method may be applied to the communication architecture in fig. 4, and further, the intelligent gas cross-regional data interaction method may specifically include the following contents described in steps S1-S6:
s1: establishing an intelligent gas Internet of things; the intelligent gas Internet of things comprises a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
s2: the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
s3: the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
s4: the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
s5: the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
s6: and the user platform calibrates the intelligent gas meter according to the first calibration data.
When the embodiment is implemented, the off-network cloud platform acquires data of the intelligent gas internet of things by providing computing service for the intelligent gas internet of things, the data comprise calibrated data of the intelligent gas meter, fluctuation data of the intelligent gas meter in different environments, gas use data of the intelligent gas meter in different time periods and the like, and a first database can be formed through the data.
By the five-platform structure of the embodiment, the intelligent gas meter can be calibrated in a mode that the user platform initiates a calibration request to the management platform. As a preferred scheme, after the intelligent gas meter is installed, the user platform automatically sends a calibration request to the management platform, at this time, the management platform may match corresponding calibration data from the first database as first calibration data in an intra-network operation or an extra-network operation manner, the matching process may adopt regional matching, or may match based on a basic model set in the intra-network cloud platform or the extra-network cloud platform, such as a model of a classifier, and the user platform may perform calibration operation according to a matching result, thereby providing an unmanned operation space for the calibration operation of the intelligent gas meter. According to the method, unmanned and automatic calibration of the intelligent gas meter is achieved, on one hand, manpower and material resources for intelligent gas meter calibration are saved, on the other hand, industry big data are formed, and references are provided for governments and related resource departments.
In one embodiment, referring to fig. 2, step S3 includes the following sub-steps:
s31: establishing a service platform A, a management platform A and a sensing network platform A on the in-network cloud platform; respectively establishing a user platform A and an object platform A on two platforms interacted with the in-network cloud platform;
s32: the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; and the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A.
In one embodiment, referring to fig. 3, step S3 further includes the following sub-steps:
s33: establishing a user platform B and an object platform B on the management platform A, and establishing a service platform B, a management platform B and a sensing network platform B on the off-network cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted.
In one embodiment, the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
and the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B.
In the implementation process of the embodiment, the inventor finds that, for ultrasonic volume detection equipment used in the existing intelligent gas meter, the change of the gas pressure is an important parameter, but the aging degrees of gas transmission equipment in different areas are different, so that the gas supply pressure facing different areas actually is different, and meanwhile, the general temperature and the atmospheric pressure of the area where the intelligent gas meter is located are similar, so that the integration of the data of the intelligent gas meter in one gas supply area and the calibration of a new intelligent gas meter in the area are feasible and high in precision.
In this embodiment, the management platform B needs to acquire data of pipeline arrangement through an authorization authority, and form a dendrogram for subsequent partitioning, and the dendrogram has a plurality of root nodes, where the root node of the dendrogram should be a main air supply outlet in an air supply region, and based on the root node, the management platform B performs classification processing on the first data, and an algorithm of the classification processing is relatively simple, and may be performed in a manner of traversing the dendrogram, which is not repeated herein;
after classification is formed, all intelligent gas meters corresponding to one class in one classification class data can be determined to have similar atmospheric enterprises, temperatures and gas supply pressures, so that reference can be provided for a newly received calibration request based on the classification class data.
In one embodiment, the management platform B is further configured to use a gas usage period and a gas usage duration corresponding to the gas usage parameter in the first data as second data, and the management platform B performs classification calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
In the implementation process of the above embodiment, the inventor also finds that although the ultrasonic volume sensing technology has many advantages compared with the conventional film sensor, in the household process, different gas usage modes have great difference in the detected gas usage results, for example, in the process of turning on the gas stove, when cooking, the gas usage mode is switched from small fire to large fire, and because the gas output amount of the gas changes greatly, the gas flow rate in the pipeline is affected by the gas compression, the echo change of the ultrasonic wave also has delay and error; the gas consumption of the water heater generally only has sudden change or seasonal change; the gas consumption for floor heating is typical seasonal change, the duration is strong, and the gas consumption change is relatively slow
The inventor classifies and calculates the first database to generate a second database based on the gas consumption duration and the gas consumption time period, the classification process can be carried out by adopting a general clustering algorithm, the classification radius data of the inventor adopts two data of the gas consumption duration and the gas consumption time period, the clustered result can be mainly divided into a gas range gas class, a water heater gas class and a floor heating gas class, and other data are taken as noise to be removed.
In the calibration process of the gas meter, different calibrations corresponding to different types of gas using processes can be determined through the matching of the third data, so that the accuracy of calibration data is improved. For example:
the method comprises the following steps that real-time detection can be carried out on floor heating gas, detected data need to be corrected when the data are matched with gas type of a gas stove, and correction parameters correspond to difference functions; similarly, in the present embodiment, there is also calibration of a new gas meter, and the new gas meter generally does not have third calibration data, so on this basis, the present embodiment can not consider the influence of the third calibration data on the calibration of the new gas meter.
Based on the same inventive concept, referring to fig. 4, an embodiment of the present invention further provides an intelligent gas cross-region data interaction system, including:
the intelligent gas Internet of things system comprises an intelligent gas Internet of things, a gas sensor and a gas sensor, wherein the intelligent gas Internet of things is configured to comprise a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
and the user platform calibrates the intelligent gas meter according to the first calibration data.
In one embodiment, referring to fig. 5, a service platform a, a management platform a and a sensing network platform a are established on the in-network cloud platform; a user platform A and an object platform A are respectively established on two platforms of the cloud platform in the network in an interactive mode;
the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; and the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A.
In an embodiment, referring to fig. 6, a user platform B and an object platform B are established on the management platform a, and a service platform B, a management platform B and a sensing network platform B are established on the extranet cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted.
Fig. 6 also shows a more specific implementation manner, where the management platform a1 and the management platform C are both in-network cloud platforms interacting with out-of-network cloud platforms, the management platform a1 interacts with the out-of-network cloud platforms by means of the object platform B1 → the sensor network platform B1 → the management platform B1 → the service platform B1 → the user platform B1, and the same management platform C interacts with the out-of-network cloud platforms by means of the object platform B2 → the sensor network platform B2 → the management platform B2 → the service platform B2 → the user platform B2; the management platform C and the management platform A1 share the same sensing network platform, the same management platform and the same service platform to realize interaction, and are also beneficial to sharing data.
In one embodiment, the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
and the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B.
In one embodiment, the management platform B is further configured to use a gas usage period and a gas usage duration corresponding to the gas usage parameter in the first data as second data, and the management platform B performs classification calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
As shown in fig. 4 to 6, the management cloud platform in the figures is a management platform built on the cloud platform, and the sensing network platform includes a sensing network management platform, a telecommunication operator communication platform, a gateway and a wireless communication module, which are sequentially interacted, wherein the sensing network management platform is used for network transmission management, the telecommunication operator communication platform is used for internet data communication, the gateway is used for data interaction, and the wireless communication module is used for wireless data interaction.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (2)
1. An intelligent gas cross-region data interaction method is characterized by comprising the following steps:
establishing an intelligent gas Internet of things; the intelligent gas Internet of things comprises a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
the user platform calibrates the intelligent gas meter according to the first calibration data;
forming an in-network cloud platform includes the following substeps:
establishing a service platform A, a management platform A and a sensing network platform A on the in-network cloud platform; respectively establishing a user platform A and an object platform A on two platforms interacted with the in-network cloud platform;
the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A;
the method comprises the following steps that a plurality of in-network cloud platforms are further interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platforms, and the method comprises the following substeps:
establishing a user platform B and an object platform B on the management platform A, and establishing a service platform B, a management platform B and a sensing network platform B on the off-network cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted;
the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B;
the management platform B is further used for taking the gas using time period and the gas using duration corresponding to the gas using parameters in the first data as second data, and the management platform B performs classified calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
2. Wisdom gas is data interaction system across region, its characterized in that includes:
the intelligent gas Internet of things system comprises an intelligent gas Internet of things, a gas sensor and a gas sensor, wherein the intelligent gas Internet of things is configured to comprise a user platform, a service platform, a management platform, a sensing network platform and an object platform which are sequentially interacted;
the object platform senses data of the intelligent gas meter as first data and sends the first data to the management platform through the sensing network platform;
the management platform is arranged on the cloud platform to form an in-network cloud platform; the plurality of in-network cloud platforms are also interacted with at least one out-of-network cloud platform, and the out-of-network operation is completed through the out-of-network cloud platform;
the method comprises the steps that the off-line cloud platform collects operation data of a plurality of intelligent gas Internet of things as first data during off-line operation, and generates a first database by using a plurality of groups of first data;
the user platform is arranged on an intelligent control mechanism of the intelligent gas meter; when the user platform initiates a gas meter calibration request to the management platform through the service platform, the management platform generates first calibration data according to a first database and the gas meter calibration request through an in-network cloud platform and/or an out-network cloud platform, and sends the first calibration data to the user platform through the service platform;
the user platform calibrates the intelligent gas meter according to the first calibration data;
a service platform A, a management platform A and a sensing network platform A are established on the in-network cloud platform; a user platform A and an object platform A are respectively established on two platforms of the cloud platform in the network in an interactive mode;
the user platform A, the service platform A, the management platform A, the sensing network platform A and the object platform A are sequentially interacted, and the sensing network platform A senses and receives data of the object platform A and sends the data to the management platform A; the management platform A performs operation processing on the data of the object platform A and sends the data to the user platform A through the service platform A;
a user platform B and an object platform B are established on the management platform A, and a service platform B, a management platform B and a sensing network platform B are established on the off-network cloud platform; the user platform B, the service platform B, the management platform B, the sensing network platform B and the object platform B are sequentially interacted;
the management platform B acquires pipeline layout data corresponding to the first data in all the first databases to generate a tree diagram;
the management platform B classifies the first data in the first database according to the tree diagram to generate classified data; the first data in the same class corresponds to the same root node in the tree diagram;
when the management platform B acquires a gas meter calibration request, selecting classification type data matched with the gas meter calibration request from the classification type data, and extracting basic calibration data from the classification type data;
the management platform B sends the basic calibration data serving as second calibration data to the in-network cloud platform through the service platform B;
the management platform B is further used for taking the gas using time period and the gas using duration corresponding to the gas using parameters in the first data as second data, and the management platform B performs classified calculation on the first database according to the second data to generate a second database; the second database comprises gas for a gas stove, gas for a water heater and gas for a floor heating;
when the management platform B acquires a gas meter calibration request, extracting a gas use time period and a gas use duration corresponding to a gas use parameter from the gas meter calibration request as third data; the management platform B matches the third data with the second database, and sends the matched difference function serving as third calibration data to the in-network cloud platform through the service platform B;
when the management platform A detects that the third calibration data is empty, the management platform A takes the second calibration data as the first calibration data;
and when the management platform A detects that the third calibration data is not empty, the management platform A processes the second calibration data and the third calibration data to generate first calibration data.
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