Blockchain-based Intelligent Gas AI Analysis and Diagnosis System

Abstract

The present invention discloses an intelligent gas AI analysis and diagnosis system based on blockchain, which relates to the field of gas analysis technology. It includes a construction module for constructing a gas usage model for the client based on blockchain; a collection module connected to the construction module for real-time collecting the gas usage information of the client. The gas usage information includes the gas usage amount and the time corresponding to the gas usage, and the gas usage information is built into the gas usage model; a prompt module connected to the collection module for analyzing the gas usage information based on the gas usage model to obtain an analysis result and prompting the analysis result to the client. The present invention can perform additional tasks or bear additional loads without interfering with the stability of the original system, can better analyze and sort out the subsequently collected gas usage information, can better complete the data analysis, prediction and comparison of gas usage, and obtain the prediction and diagnosis result of gas usage.

Description

Technical Field

[0001] The present invention relates to the technical field of gas analysis, and specifically relates to an intelligent gas AI analysis and diagnosis system based on blockchain. Background Art

[0002] With the development of the economy and the improvement of people's living standards, the demand for gas by residents is increasing continuously. At the same time, the demand for gas in industries, commerce and other fields is also growing continuously. Especially in the field of new industrial gas, with the increasingly strict environmental protection policies and the urgency of global climate change, the market share of new industrial gas represented by clean energy such as natural gas, liquefied petroleum gas (LPG), and biomass gas has increased significantly. This change in market demand provides a broad market space and development opportunities for gas analysis.

[0003] Intelligent gas refers to advanced information technologies such as artificial intelligence (AI), which deeply integrate the traditional urban gas system with modern digital means to achieve automated, intelligent, and remote monitoring and optimization of the entire process of gas facilities, supply, use, management, etc. At present, the use of gas is mostly concentrated in households. During the use of household gas, due to the large number of users, the complexity and intersection of data, it is difficult to conduct comparative analysis on a large amount of gas usage data, difficult to diagnose and predict based on gas usage data, and thus difficult to analyze the safe use of gas for users. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent gas AI analysis and diagnosis system based on blockchain to solve the deficiencies in the background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: An intelligent gas AI analysis and diagnosis system based on blockchain, comprising:

[0006] A construction module for constructing a gas usage model based on a client;

[0007] An acquisition module, connected to the construction module, for real-time acquisition of gas usage information of the client, wherein the gas usage information includes the gas usage amount and the time corresponding to the gas usage, and constructing the gas usage information into the gas usage model;

[0008] A prompt module, connected to the acquisition module, for analyzing the gas usage information based on the gas usage model to obtain an analysis result and prompting the analysis result to the client.

[0009] In a preferred embodiment, the construction module includes:

[0010] An acquisition unit for acquiring user information of multiple users, wherein the user information includes user residence information and user gas meter information;

[0011] A registration unit for registering a client according to user information;

[0012] A construction unit for constructing a gas usage bar corresponding to the client, and connecting the gas usage bars of multiple clients to obtain a gas usage model;

[0013] A storage unit for configuring corresponding cloud servers for multiple clients as nodes, connecting multiple nodes through a protocol to obtain a blockchain, and storing the gas usage model through the blockchain.

[0014] In a preferred embodiment, the construction unit includes:

[0015] A configuration unit for configuring a corresponding cloud space for the client, dividing the cloud space into multiple stage spaces, and connecting the multiple stage spaces to obtain a gas usage bar;

[0016] A setting unit for setting a site line corresponding to the gas usage bar, differentiating the site line to obtain multiple attached site lines, and corresponding and binding the attached site lines to the stage spaces one by one;

[0017] An entanglement unit for entangling and corresponding the gas usage bars of multiple clients through the site lines to obtain a gas usage model.

[0018] In a preferred embodiment, the configuration unit includes:

[0019] An information setting unit for setting at least two connection keys for multiple stage spaces respectively, where the connection key is an identification code;

[0020] A sorting unit for sorting the multiple stage spaces, identifying and connecting the multiple stage spaces through the connection keys according to the sorting, and binding the positions of adjacent stage spaces through the connection keys to obtain a gas usage bar.

[0021] In a preferred embodiment, the setting unit includes:

[0022] A corresponding configuration unit for setting a site line corresponding to the gas usage bar in the cloud space, where the site line includes a line formed by multiple site combinations;

[0023] A differentiation unit for replicating the site line to obtain multiple replicated site lines, and establishing communication connections between the multiple replicated site lines and the site line respectively to obtain multiple attached site lines;

[0024] A binding unit for corresponding and binding the attached site lines to the stage spaces one by one.

[0025] In a preferred embodiment, the entanglement unit includes:

[0026] An arrangement unit for obtaining site lines corresponding to multiple clients and arranging the sites in the site lines;

[0027] An entanglement unit for sequentially communicating and connecting the site lines in multiple clients through sites according to the arrangement order of the sites in the site lines to obtain the entanglement relationship between the gas usage bars in multiple clients;

[0028] A management unit for using the gas usage bars in multiple clients with established entanglement relationships as a gas usage model.

[0029] In a preferred embodiment, the acquisition module includes:

[0030] An acquisition setting unit for setting an acquisition stage and binding information of the acquisition stage with a corresponding stage space;

[0031] An acquisition unit for real-time acquiring the gas usage amount of a client and the time corresponding to the gas usage as gas usage information based on the acquisition stage, and storing the gas usage information into the stage space corresponding to the acquisition stage;

[0032] A data construction unit for dividing the gas usage information in the stage space into multiple data segments, binding the sites in the attached site lines bound to the stage space with the data segments, and interconnecting the data segments in multiple clients based on the gas usage model.

[0033] In a preferred embodiment, the prompt module includes:

[0034] A comparison unit for correspondingly comparing the data segments in multiple clients based on the gas usage model to obtain a predicted diagnosis result, wherein the diagnosis result includes the gas usage distribution time period and the corresponding usage amount;

[0035] A prompt unit for using the data segments corresponding to the diagnosis results that do not meet the preset conditions as prompt segments and prompting the clients corresponding to the prompt segments.

[0036] In the above technical solution, the technical effects and advantages provided by the present invention:

[0037] After establishing communication connections between multiple replication site lines of the present invention respectively and the site lines, the multiple replication site lines are used as attachment site lines. This differentiation does not represent replication, but rather the doppelgangers of the corresponding site lines. After the doppelgangers, the attachment site lines can still establish connections with the site lines. The attachment site lines not only retain the functional characteristics of the original site lines, but also can perform additional tasks or bear additional loads without disturbing the stability of the original system. They can better analyze and sort out the gas usage information collected subsequently, can better complete the data analysis, prediction and comparison of gas usage, obtain the diagnostic results of gas usage, and provide the diagnostic results for users to pay attention to and possibly take corresponding measures, such as adjusting usage habits, performing equipment maintenance or contacting professionals for inspection, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0039] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0041] Embodiment 1. Please refer to Figure 1 As shown, the blockchain-based intelligent gas AI analysis and diagnosis system in this embodiment includes:

[0042] A construction module for constructing a gas usage model based on the client.

[0043] An acquisition module, connected to the construction module, for real-time acquisition of the gas usage information of the client. Among them, the gas usage information includes the gas usage amount and the time corresponding to the gas usage, and constructs the gas usage information into the gas usage model.

[0044] A prompt module, connected to the acquisition module, for analyzing the gas usage information based on the gas usage model to obtain an analysis result, and prompting the analysis result to the client.

[0045] It should be noted that with the development of the economy and the improvement of people's living standards, residents' demand for gas is increasing. At the same time, the demand for gas in industries such as industry and commerce is also growing. Especially in the field of new industrial gas, with the increasingly stringent environmental protection policies and the urgency of global climate change, the market share of new industrial gas represented by clean energy such as natural gas, liquefied petroleum gas (LPG), and biomass gas has increased significantly. This change in market demand provides a broad market space and development opportunities for gas analysis.

[0046] At present, the use of gas is mostly concentrated in households. In the process of household gas use, due to the large number of users, the complexity and interlacing of data, it is difficult to compare and analyze a large amount of gas usage data. There is no effective data combing function, and it is difficult to analyze the safety of gas use for the corresponding users. In this application, multiple replicated site lines are used as attachment site lines after establishing communication connections with the site lines respectively. This differentiation does not represent replication, but the clone of the corresponding site line. The attachment site line after the clone can still establish a connection with the site line. The attachment site line not only retains the functional characteristics of the original site line, but also can perform additional tasks or bear additional loads without interfering with the stability of the original system. It can better analyze and comb the subsequent collected gas usage information, and can better complete the data analysis and comparison of gas use, reminding users to pay attention and possibly take corresponding measures, such as adjusting usage habits, performing equipment maintenance or contacting professionals for inspection.

[0047] In one embodiment, the building blocks include:

[0048] A collection unit, used to collect user information of multiple users, wherein the user information includes user residence information and user gas meter information;

[0049] A registration unit, used to register and obtain a client according to user information;

[0050] A construction unit, used to construct a gas usage bar corresponding to a client, and to associate gas usage bars of multiple clients to obtain a gas usage model;

[0051] A storage unit is used to configure a plurality of clients with corresponding cloud servers as nodes, connect the plurality of nodes through a protocol to obtain a blockchain, and store the gas usage model through the blockchain;

[0052] It should be noted that in the use of gas, it is more targeted at household users. Taking housing as a unit, the information of the house owners of the housing is collected, including the user residence information and the user gas meter information as user information. Here, the user residence information includes the housing address and the gas usage, where the gas usage includes cooking usage and domestic hot water generation usage, such as gas water heaters and other appliances. The user gas meter information includes the gas meter coding information corresponding to the user residence. After that, a client is registered according to the user information. The client represents the gas collection port of a residence. The registration method of the client is as follows: construct a user registration form interface, including input fields, submit buttons, etc.; after the user fills in the registration information, the data is sent to the server through form submission. This can be achieved through AJAX (Asynchronous JavaScript and XML) to send data without reloading the page, and a registration request is made through a backend framework such as Node.js, Python (Django / Flask), Java (Spring Boot), etc., to process the registration request sent by the frontend; the backend sets up an API interface to receive the registration data, and after validating the data, saves the user information to the database; after successful registration, the backend can return a response containing user information or an authentication token to the frontend; Database: such as MySQL, PostgreSQL, MongoDB, etc., is used to store user information. After that, a gas usage bar is constructed corresponding to the client, and the gas usage bars of multiple clients are connected correspondingly to obtain a gas usage model. Multiple clients are configured with corresponding cloud servers as nodes, and multiple nodes are connected through a protocol to obtain a blockchain. The gas usage model is stored through the blockchain. Through the blockchain, the stability and security of the storage of the gas usage model can be guaranteed, and the analysis and prediction of gas usage can be better carried out to obtain the analysis diagnosis result. Through the gas usage model, a health analysis of domestic gas usage can be carried out to assist users in the reasonable use of gas;

[0053] In one embodiment, the construction unit includes:

[0054] A configuration unit, used to configure a corresponding cloud space for the client, divide the cloud space into multiple stage spaces, and connect the multiple stage spaces to obtain a gas usage bar;

[0055] A setting unit, used to set a site line corresponding to the gas usage bar, divide the site line to obtain multiple attached site lines, and correspond and bind the attached site lines to the stage spaces one by one;

[0056] An entanglement unit, used to entangle and correspond the gas usage bars of multiple clients through the site lines to obtain a gas usage model;

[0057] It should be noted that the cloud space corresponding to the client configuration is divided by virtualization technology (such as VMware, Hyper-V, etc.) to obtain multiple logically independent stage spaces, each of which can be regarded as an independent storage or computing unit for storing and managing gas usage data at different stages; then, database technology (such as MySQL, Oracle, etc.) or distributed file systems (such as HDFS, Ceph, etc.) are used to connect and manage multiple stage spaces; gas usage data at different stages are associated through database tables or file system directories to form gas usage bars; site lines are set on the gas usage bars, which can be regarded as setting marking points or indexes on the data sequence; these site lines can be used to identify different gas usage stages, events or abnormal points; data segmentation or clustering algorithms (such as K-means, DBSCAN, etc.) are used to differentiate the site lines to obtain multiple attachment site lines, which can further refine the gas usage data to make it more accurate and detailed; data mapping technology (such as database foreign keys, data table associations, etc.) is used to implicate and correspond the gas usage bars of multiple clients through site lines; In this way, a unified gas usage model can be formed to analyze and predict the gas usage of different clients; using big data analysis and mining technology (such as Hadoop, Spark, etc.) to deeply analyze and mine the gas usage model, the rules, trends and abnormal behaviors of gas usage can be discovered, and decision support can be provided for gas management and optimization. The cloud space is used to store the client's gas usage data in the future. Then, the cloud space is spatially divided to obtain multiple stage spaces. The multiple stage spaces are relatively independent, so the multiple stage spaces are connected to obtain gas usage bars. The stage space is used to store the client's gas usage information according to the stage. The site line is set in the cloud space, and the site line is differentiated to obtain multiple attachment site lines. The attachment site lines are matched and bound to the stage space one by one. Then, in order to better compare and sort out the data, the gas usage bars of multiple clients are implicated and matched through their respective site lines to obtain a gas usage model, which can better associate the clients in the same area, better understand the user-end gas usage in the area, and conduct better data sorting and analysis to facilitate subsequent gas supply preparation and client gas planning;

[0058] In one embodiment, the configuration unit includes:

[0059] An information setting unit, used to set at least two connection keys corresponding to the multiple stage spaces respectively, wherein the connection keys are identification codes;

[0060] A sorting unit for sorting multiple stage spaces, identifying and connecting the multiple stage spaces according to the sorting through connection keys, and binding the positions of adjacent stage spaces through connection keys to obtain a gas usage bar;

[0061] It should be noted that at least two connection keys are respectively set for the multiple stage spaces. The connection key is an identification code carried on the stage space. Each stage space carries at least two connection keys. The connection key, as an identification code, can be regarded as the unique identifier or index of the stage space. A hash function or UUID (Universally Unique Identifier) generation algorithm can be used to generate at least two connection keys for each stage space. The connection keys will be used for subsequent sorting and connection of the stage spaces; then a sorting algorithm (such as quicksort, mergesort, heapsort, etc.) can be used to sort the stage spaces. The basis for sorting can be the creation time of the stage space, gas usage, or other relevant attributes; after sorting, the connection keys are used to identify and connect adjacent stage spaces, which can be achieved by storing the mapping relationship between the stage space and its connection key in a data structure. The connection of adjacent stage spaces can be represented by establishing pointer, linked list, or graph relationships in the data structure; according to the sorting and connection results, the adjacent stage spaces are positionally bound through the connection keys to form a continuous gas usage bar, where each stage space is connected to its adjacent space through the connection key. The gas usage bar can be regarded as a time series or event series for recording the gas usage information of the client; the sorting here is not limited to multiple stage spaces. The arrangement here is a virtual arrangement of the stage spaces for listing the positional relationships of the stage spaces. Then, according to the sorting, the multiple stage spaces are identified and connected through the connection keys, and the adjacent stage spaces are positionally bound through the connection keys to obtain the gas usage bar. The gas usage bar here is used to record the gas usage information of the client, has a good periodic recording effect, and is convenient for the analysis and prediction of gas usage information;

[0062] In one embodiment, the setting unit includes:

[0063] A corresponding configuration unit for setting a site line corresponding to the gas usage bar in the cloud space, where the site line includes a line formed by connecting multiple site combinations;

[0064] A differentiation unit for replicating the site line to obtain multiple replicated site lines, and establishing communication links between the multiple replicated site lines and the site line to obtain multiple attached site lines;

[0065] A binding unit for corresponding and binding the attached site lines to the stage spaces one by one;

[0066] It should be noted that a site line corresponding to a gas bar is set in the cloud space, and the site line includes a line formed by combining and connecting multiple sites. The site serves as a management port, and multiple management ports are connected in a linear combination. The combination connection is a communication connection. The specific operation method of setting a management port in the cloud space and connecting multiple management ports is as follows: In SAN, each storage device (or storage location) can be configured with one or more management ports, which are interconnected through the SAN network to achieve communication and data transmission. The site line is then differentiated to obtain multiple attached site lines. The differentiation process is to first copy multiple copy site lines. The copying process is not a simple data copy, but a copy that is almost identical to the original site line in structure and function. These copies are given a new identity as a replication site line at the moment of replication. After multiple replication site lines establish communication with the site line, the multiple replication site lines serve as attachment site lines. This differentiation does not represent replication, but the doppelganger of the corresponding site line. The attachment site line after the doppelganger can still establish a connection with the site line. The attachment site line not only retains the functional characteristics of the original site line, but also can perform additional tasks or bear additional loads without interfering with the stability of the original system, so as to better analyze and sort out the gas usage information collected subsequently, and better complete the data analysis of gas usage;

[0067] In one embodiment, the connection unit comprises:

[0068] An arrangement unit, used for obtaining the site lines corresponding to the plurality of clients and arranging the sites in the site lines;

[0069] The connection unit is used to sequentially connect the site lines in the plurality of clients to communicate with each other through the sites according to the arrangement order of the sites in the site line, so as to obtain the connection relationship between the gas usage strips in the plurality of clients;

[0070] A management unit, used to use the gas usage items in the multiple clients with established involvement as a gas usage model;

[0071] It should be noted that the sites equipped on the site line are organized and arranged in an orderly manner. Since the sites on the site line already have a sorted communication relationship, it can be virtually sorted into a clear order. The purpose is to construct a clear and orderly communication structure foundation; following the set arrangement order of the sites, the interconnection of site lines among multiple clients is achieved one by one; this process is connected through their respective sites, aiming to construct an interconnected network of gas usage entries among clients, that is, to establish the pattern of their implicated relationship; based on the successfully established implicated relationship network, the gas usage entries in these interconnected clients are further integrated into a unified gas usage model; this model not only reflects the gas usage of each client, but also includes the dynamically changing mutual influence relationship among them, providing strong support for subsequent monitoring, analysis and management.

[0072] In one embodiment, the acquisition module includes:

[0073] An acquisition setting unit, configured to set the acquisition stage and bind the acquisition stage with the corresponding stage space for information;

[0074] An acquisition unit, configured to collect the gas usage amount of the client and the time corresponding to the gas usage in real time based on the acquisition stage as gas usage information, and store the gas usage information in the stage space corresponding to the acquisition stage;

[0075] A data construction unit, configured to divide the gas usage information in the stage space to obtain multiple data segments, bind the sites in the attached site line bound to the stage space with the data segments, and interconnect the data segments in multiple clients based on the gas usage model;

[0076] It should be noted that the acquisition stage is set. For example, the acquisition stage can be a time period of one day, a time period of one quarter or a time period of one year, etc. After that, the acquisition stage is bound with the corresponding stage space for information. There are multiple stage spaces. For example, if the acquisition stage is a time period of one day, then the first stage space is the gas usage information of the first day of acquisition, and the second stage space in order is the gas usage information of the second day of acquisition, and so on for subsequent acquisitions. The gas usage information in the stage space is divided to obtain multiple data segments. Here, the division can be carried out according to the time in the acquisition stage. Then, based on the gas usage model, the data segments in multiple clients are interconnected. It can interconnect the gas data segments of multiple clients in the same acquisition stage through sites, which can be used for subsequent comparison and comprehensive analysis, or for individual analysis of clients, or for comprehensive analysis among multiple clients. It has a good information sorting effect and can better predict the gas usage information of clients and complete the diagnosis of gas usage.

[0077] In one embodiment, the prompting module includes:

[0078] A comparison unit for correspondingly comparing data segments in multiple clients based on a gas usage model to obtain a predicted diagnosis result, where the diagnosis result includes a gas usage distribution time period and the corresponding usage amount;

[0079] A prompting unit that uses the data segment corresponding to the diagnosis result that does not meet the preset conditions as a prompting segment and prompts the client corresponding to the prompting segment;

[0080] It should be noted that in order to optimize the efficiency and safety of gas usage, an advanced gas usage data analysis model has been constructed; this model aims to reveal the gas usage distribution patterns and specific usage amounts during different time periods by deeply comparing and analyzing the gas usage data segments uploaded by multiple clients; this process not only helps us understand the gas consumption characteristics of each client, but also provides a scientific basis for the rational allocation and management of energy. During the comparison process, a series of preset conditions based on energy efficiency, safety standards or historical average levels are set, where the preset conditions are concentrated gas usage distribution time periods and preset usage amounts. Here, the concentrated gas usage distribution time period is the concentrated gas usage distribution time period with the highest proportion among multiple clients, serving as a benchmark for evaluating the rationality of data segments; based on AI, the gas usage distribution time period and its corresponding usage amount in each diagnosis result are automatically compared with these preset conditions one by one; for those diagnosis results that fail to meet the preset standards, they are marked as prompting segments. This prompting segment is a predicted information of a diagnosis, and the specific problems need to be monitored by the client itself. Here, it is a predicted gas usage diagnosis. Finally, the prompt information will be immediately pushed to the client user to whom the corresponding data segment belongs, such as equipment aging, improper usage habits or potential leakage risks, etc., to remind the user to pay attention and possibly take corresponding measures, such as adjusting usage habits, performing equipment maintenance or contacting professionals for inspection, etc. Through such an intelligent and automated gas usage analysis and prompting system, not only can the effective utilization of gas resources be promoted, but also the safety awareness and energy-saving awareness of users can be significantly improved, jointly promoting the construction of a more green and safe energy usage environment.

[0081] As described above, it is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. The intelligent gas AI analysis and diagnosis system based on blockchain is characterized in that Including: A construction module for constructing a gas usage model based on a blockchain corresponding to a client; A configuration unit for configuring a corresponding cloud space for the client, dividing the cloud space into multiple stage spaces, and connecting the multiple stage spaces to obtain a gas usage bar; A setting unit for setting a site line corresponding to the gas usage bar, differentiating the site line to obtain multiple attached site lines, and corresponding and binding the attached site lines to the stage spaces one by one; An implicated unit for implicating and corresponding the gas usage bars of multiple clients through the site lines to obtain a gas usage model; The configuration unit includes: An information setting unit for respectively setting at least two connection keys for the multiple stage spaces, where the connection key is an identification code; A sorting unit for sorting the multiple stage spaces, and identifying and connecting the multiple stage spaces through the connection keys according to the sorting, and binding the positions of adjacent stage spaces through the connection keys to obtain a gas usage bar; The setting unit includes: A corresponding configuration unit for setting a site line corresponding to the gas usage bar in the cloud space, where the site line includes a line formed by connecting multiple site combinations, the sites in the site line serve as a management port, and the multiple management ports are linearly combined and connected, and the combined connection is a communication connection; A differentiation unit for replicating the site line to obtain multiple replicated site lines, and establishing communication connections between the multiple replicated site lines and the site line respectively to obtain multiple attached site lines; A binding unit for corresponding and binding the attached site lines to the stage spaces one by one; The implicated unit includes: An arrangement unit for obtaining the site lines corresponding to multiple clients and arranging the sites in the site lines; An implicated unit for sequentially communicating and connecting the site lines in multiple clients through the sites according to the arrangement order of the sites in the site line to obtain the implicated relationship between the gas usage bars in multiple clients; A management unit for using the gas usage bars in multiple clients with an established implicated relationship as a gas usage model; A collection module, connected to the construction module, for real-time collecting the gas usage information of the client, where the gas usage information includes the gas usage amount and the time corresponding to the gas usage, and constructing the gas usage information into the gas usage model; The collection module includes: A collection setting unit for setting a collection stage and binding the collection stage with the corresponding stage space for information; A collection unit for real-time collecting the gas usage amount of the client and the time corresponding to the gas usage as gas usage information based on the collection stage, and storing the gas usage information in the stage space corresponding to the collection stage; A data construction unit for dividing the gas usage information in the stage space into multiple data segments, binding the sites in the attached site lines bound to the stage space with the data segments, interconnecting the data segments of the gas of the same collection stage in multiple clients through the sites, and interconnecting the data segments in multiple clients based on the gas usage model; A prompt module, connected to the collection module, for analyzing the gas usage information based on the gas usage model to obtain an analysis result, and prompting the analysis result to the client.

2. The intelligent gas AI analysis and diagnosis system based on blockchain according to claim 1, wherein: The building blocks include: A collection unit, used to collect user information of multiple users, wherein the user information includes user residence information and user gas meter information; A registration unit, used to register and obtain a client according to user information; A construction unit, used to construct a gas usage bar corresponding to a client, and to associate gas usage bars of multiple clients to obtain a gas usage model; The storage unit is used to configure the corresponding cloud servers of multiple clients as nodes, connect the multiple nodes through the protocol to obtain the blockchain, and store the gas usage model through the blockchain.

3. The intelligent gas AI analysis and diagnosis system based on blockchain according to claim 1, characterized in that: The prompt module comprises: A comparison unit, configured to compare the data segments in the plurality of clients correspondingly based on the gas usage model to obtain a predicted diagnosis result, wherein the diagnosis result includes a gas usage distribution time period and a corresponding usage amount; The prompt unit uses the data segment corresponding to the diagnosis result that does not meet the preset condition as a prompt segment, and prompts the client corresponding to the prompt segment.

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