Smart city water meter reading management system based on Internet of Things

Abstract

The invention discloses a smart city water meter reading management system based on the Internet of Things, and relates to the technical field of water meter management, the smart city water meter reading management system comprises a management center, the management center is in communication connection with a meter reading end module, a data processing module, an anomaly analysis module, a monitoring troubleshooting module and an execution module; reading related data of the water meter through a plurality of water meter reading devices arranged on the meter reading end module; block chain encryption, regional data summarization and distributed storage are carried out on the water meter related data through a data processing module, and a to-be-detected data set is generated; performing abnormal value analysis on the to-be-detected data set through an abnormal analysis module to generate fault data and normal data; the monitoring troubleshooting module is used for generating a troubleshooting scheme according to the fault data and submitting the troubleshooting scheme to corresponding troubleshooting personnel for troubleshooting; and the execution module obtains normal data to generate a water fee settlement list, generates a visual report, generates an optimization scheme according to the visual report, and pushes the optimization scheme to a corresponding user.

Description

Technical Field

[0001] The present invention relates to the technical field of water meter management, and specifically to an intelligent city water meter reading management system based on the Internet of Things. Background Technique

[0002] The Internet of Things refers to various devices and technologies such as various information sensors, radio frequency identification technologies, global positioning systems, infrared sensors, laser scanners, etc., which can collect any objects or processes that need to be monitored, connected, and interacted with in real time, collect various required information such as their sound, light, heat, electricity, mechanics, chemistry, biology, location, etc., and through various possible network accesses, realize the ubiquitous connection of things to things and things to people, and realize the intelligent perception, identification, and management of items and processes. The Internet of Things is an information carrier based on the Internet, traditional telecommunications networks, etc., which enables all ordinary physical objects that can be independently addressed to form an interconnected network.

[0003] With the advent of urbanization, an intelligent management method is increasingly needed for the reading management of urban water meters. In the traditional urban water meter reading management system, when receiving the data entered by the water meter, it may be interfered by the intrusion of external illegal data, resulting in incorrect judgments. After receiving the data, the security of the data lacks guarantee. For abnormal data, a large amount of work is consumed in the fault analysis stage, and it is very difficult to analyze and eliminate the fault in a timely manner. All these problems need to be considered by us. Summary of the Invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide an intelligent city water meter reading management system based on the Internet of Things.

[0005] The purpose of the present invention can be achieved through the following technical solutions: An intelligent city water meter reading management system based on the Internet of Things includes a management center, and the management center is communicatively connected to a meter reading end module, a data processing module, an anomaly analysis module, a monitoring and troubleshooting module, and an execution module; The meter reading end module includes a number of water meter reading devices, and the relevant data of the water meter is recorded through the water meter reading devices; The data processing module is used to perform blockchain encryption, regional data aggregation, and distributed storage on the relevant data of the water meter, generate a dataset to be detected, and encrypt and send the dataset to be detected through the channel to the anomaly analysis module; The anomaly analysis module dynamically generates a receiving port number, obtains the dataset to be detected transmitted by the data processing module, and performs anomaly value analysis on the dataset to be detected to generate fault data and normal data; The monitoring and troubleshooting module is used to generate a fault troubleshooting plan according to the fault data, and push the fault troubleshooting plan to the corresponding troubleshooting personnel for troubleshooting; The execution module is provided with a cost settlement unit, a visualization unit, and a solution push unit; the cost settlement unit obtains normal data to generate a water fee settlement list and pushes it to the users corresponding to the corresponding water meter reading devices; the visualization unit obtains the historical data and current data transcribed by several water meter reading devices to generate a visualization report; the solution push unit generates an optimization solution based on the visualization report and pushes it.

[0006] Furthermore, the process of transcribing water meter related data by the water meter reading device includes: The meter reading end module includes several water meter reading devices, and each water meter reading device has a built-in database for storing water meter related data, which includes total water consumption, unit water price, period water consumption, real-time water consumption, and associated user information. A timing export period is set, and the water meter related data recorded in each database is encapsulated into a data folder, and several data folders are aggregated and transmitted to the data processing module.

[0007] Furthermore, the process of blockchain encryption and regional data aggregation includes: The data processing module obtains the data folder, deconstructs it into water meter related data, generates an authorization ID and the corresponding authorized device according to the associated user information, generates a request instruction and sends it to the management center. The management center receives the request instruction and generates a key pair, which includes a public key and a private key. Each data folder is used as a block node, aggregated to generate a blockchain, and the key pair is sent to each block node. The private key is obtained and written into the block node to generate a digital signature; the block hash value corresponding to each block node is obtained through the hash algorithm, and the corresponding block node is encrypted with the public key to be converted into an encrypted block, and the private key is used as the decryption key of the encrypted block; a regional form is set to store several different authorization IDs, and the water meter related data of the authorized devices corresponding to different authorization IDs in the regional form is aggregated to generate several regional data sets.

[0008] Furthermore, the process of distributed storage of water meter related data and generation of a data set to be detected includes: Set up a total database and distributed databases, obtain several regional data sets and transfer them to the total database. Perform data backup in the total database to generate backup data one and backup data two, and transfer backup data one and backup data two to different distributed databases for storage. When the corresponding backup data one or backup data two is damaged, generate a backup data instruction in the distributed database, obtain its own distributed database number, and upload the distributed database number and the backup data instruction to the total database. The total database performs data backup to generate new backup data one or backup data two and transmits it to the damaged distributed database; Use the backup data one or backup data two stored in the distributed database as the data set to be processed, and input it into a preset format conversion program to convert it into a unified data format and mark it as the data set to be detected. Establish several channels, and encrypt and send the data set to be detected through the channels to the anomaly analysis module.

[0009] Further, the process of generating the fault data and normal data includes: The anomaly analysis module dynamically generates a receiving port number. The channel has a corresponding sending port number. The sending port number and the receiving port number construct a one-to-one mapping relationship to obtain the data set to be detected. There are corresponding alarm thresholds preset for the total water consumption, period water consumption, and real-time water consumption in the water meter-related data corresponding to the data set to be detected. According to the magnitude relationship between the total water consumption, period water consumption, and real-time water consumption and the alarm thresholds, generate corresponding fault data and normal data, and establish a temporary interaction space to input the fault data and normal data to generate corresponding encrypted data packet one and encrypted data packet two respectively.

[0010] Further, the process of generating a fault troubleshooting plan based on the fault data and troubleshooting the fault includes: Obtain encrypted data packet one and decrypt it to restore the fault data. The fault data includes abnormal data one, abnormal data two, and abnormal data three, which respectively correspond to the primary response plan, secondary response plan, and tertiary response plan in the fault troubleshooting plan. The management center presets a historical troubleshooting database, which stores several historical response plans; Mark the primary response plan, secondary response plan, and tertiary response plan as the current response plan. The current response plan and the historical response plan include several fault keywords. Take the historical response plan and the current response plan with the highest coincidence degree of fault keywords as strongly similar associated objects; Obtain the historical response plan in the strongly similar associated objects. The historical response plan has corresponding troubleshooting personnel information and specific troubleshooting measures. Obtain the current response plan and push it to the troubleshooting personnel associated with the troubleshooting personnel information, and perform fault troubleshooting according to the specific troubleshooting measures.

[0011] Further, the process of generating the water fee settlement list and pushing it to the corresponding user includes: The water fee settlement list includes a historical water fee settlement list and a current water fee settlement list. Obtain the encrypted data packet two and decrypt it into corresponding normal data. The fee settlement unit obtains the normal data, obtains the historical water consumption based on the total water consumption and the real-time water consumption, obtains the unit price of water use, and then obtains the historical water fee amount. Obtain the current water fee amount based on the real-time water consumption. Take the historical water fee amount and the current water fee amount as the settlement amounts respectively, and then generate a historical water fee settlement list and a current water fee settlement list, and fill in the corresponding settlement amounts. Obtain the authorization ID generated by associating user information, and push the water fee settlement list to the user corresponding to the water meter reading device associated with the authorization ID.

[0012] Further, the process of obtaining and pushing the optimization plan according to the visualization report includes: The historical water fee list corresponds to historical data, and the current water fee list corresponds to current data. The visualization report includes a historical water use trend report, a historical fault visualization report, and a current water use real-time visualization report. The historical water use trend report is generated based on historical data and corresponds to a trend characteristic curve. The historical fault visualization report is generated based on fault data and corresponds to several fault inspection items. The current water use real-time visualization report is generated based on current data and corresponds to a real-time characteristic curve; Establish a two-dimensional coordinate system, map the trend characteristic curve and the real-time characteristic curve to the two-dimensional coordinate system, compare and generate a coincident curve segment and a non-coincident curve segment, mark the non-coincident curve segment as data to be optimized and transmit it to the plan push unit; The plan push unit obtains the data to be optimized and adjusts it to the preset standard segment data, and synchronously generates an optimization plan after adjusting it to the standard segment data.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: A white list of meter reading devices is set at the meter reading end. The white list of meter reading devices stores legal water meter reading devices, that is, authorized devices. When other water meter-related data is uploaded later, it is judged whether it is an authorized device corresponding to the authorization ID in the white list of meter reading devices, and it is judged whether it carries illegal data that causes interference, which reduces the data interference caused by illegal data to a certain extent; Through blockchain encryption and distributed storage of water meter-related data, the data security is enhanced to a certain extent; Obtain fault data to generate a fault troubleshooting plan, and compare it with the historical response plans stored in the historical troubleshooting database to obtain the historical response plan with the highest similarity, which can quickly determine the fault type and eliminate the fault to a certain extent, reducing the workload of fault analysis; Obtain normal data to generate an optimization plan and push it to the user, which improves the user's water use experience to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] As Figure 1 shown, an intelligent city water meter reading management system based on the Internet of Things includes a management center, and the management center is communicatively connected to a meter reading end module, a data processing module, an anomaly analysis module, a monitoring and troubleshooting module, and an execution module; The meter reading end module includes a number of water meter reading devices for recording water meter related data through the water meter reading devices; The data processing module is used for blockchain encryption, regional data aggregation and distributed storage of water meter related data, generating a dataset to be detected, and performing channel transmission encryption on the dataset to be detected and sending it to the anomaly analysis module; The anomaly analysis module dynamically generates a receiving port number, obtains the dataset to be detected transmitted by the data processing module, and performs anomaly value analysis on the dataset to be detected to generate fault data and normal data; The monitoring and troubleshooting module is used for generating a fault troubleshooting plan according to the fault data, and pushing the fault troubleshooting plan to the corresponding troubleshooting personnel for fault troubleshooting; The execution module is provided with a fee settlement unit, a visualization unit and a plan pushing unit; the fee settlement unit obtains normal data to generate a water fee settlement list and pushes it to the users corresponding to the corresponding water meter reading devices; the visualization unit obtains the historical data and current data recorded by a number of water meter reading devices to generate a visualization report; the plan pushing unit generates an optimization plan according to the visualization report and pushes it.

[0016] It should be further noted that in the specific implementation process, the process of recording water meter related data through the water meter reading devices includes: The meter reading end module includes a number of water meter reading devices, and the water meter reading devices have corresponding numbers, denoted as i, then i = 1, 2, 3,..., n, where n is a natural number greater than 0, and each water meter reading device has a built-in database; The database is used to store the water meter related data recorded when the water meter works, and the water meter related data includes total water consumption, unit water price, period water consumption, real-time water consumption and associated user information; Set a timing export period, denoted as T`, and every time the timing export period arrives, the water meter related data recorded in the database built in each water meter reading device is encapsulated into a data folder, and the associated user information is converted into a binary sequence as the identity recognition sequence of the corresponding data folder; Aggregate a number of data folders and transmit them to the data processing module, and back up and upload the data folders to the management center for storage; It should be further noted that in the specific implementation process, the process of blockchain encryption and regional data aggregation for water meter related data includes: The data processing module obtains the data folder and synchronously generates a white list of meter reading devices within the data processing module. The white list of meter reading devices obtains the corresponding associated user information in the data folder corresponding to the identity recognition sequence. The associated user information includes a user serial number and a user name. Taking the user serial number as the pre-connection element and the user name as the post-connection element, an authorization ID is formed according to the pre-connection element and the post-connection element. Taking several authorization IDs as the filling content, the filling content is filled into the white list of meter reading devices, and the water meter reading devices corresponding to each authorization ID are marked as authorized devices. It should be noted that the white list of meter reading devices stores legal water meter reading devices, that is, authorized devices. According to the associated user information in the data folder corresponding to each identity recognition sequence, a unique authorization ID is generated. When subsequent other water meter related data is uploaded, it is judged whether it is an authorized device corresponding to the authorization ID in the white list of meter reading devices. If so, it is directly allowed to be received. Otherwise, it is judged whether it carries illegal data that causes interference. If it carries such data, it is rejected and then received after being removed, which reduces the data interference caused by illegal data to a certain extent. After obtaining the data folder, the data folder is deconstructed into the original corresponding water meter related data. The data processing module generates a request instruction, denoted as P1, and sends the request instruction to the management center. The management center receives the request instruction P1 and generates a key pair, denoted as Key, where Key = <K1, K2>, and K1 is the public key and K2 is the private key. Taking the water meter related data included in each data folder as a block node, several block nodes are aggregated and linked to generate a blockchain. The key pair is sent to each corresponding block node, and the private key is obtained and written into the block node to generate a digital signature. Several block nodes are numbered, denoted as j, where j is a natural number greater than 0. The block hash value corresponding to each block node is obtained through the hash algorithm, denoted as Hash <j>After the block hash value is generated, it is fixed. Obtain the upload permission of the blockchain, update the subsequent water meter related data through the upload permission, obtain the public key in the key pair to encrypt the corresponding block node, convert the encrypted block node into an encrypted block, use the private key corresponding to the public key used by the encrypted block as the only decryption key, and the content of the encrypted block can be obtained through the decryption key; Set up a regional form, in which several different authorization IDs are stored. Summarize the water meter related data of the authorized devices corresponding to the different authorization IDs represented in the regional form to generate several regional data sets. Connect the several authorization IDs corresponding to the regional data sets in sequence as an identification ID sequence, and store the regional data sets distributively; It should be further noted that in the specific implementation process, the process of distributively storing the water meter related data and generating the data set to be detected includes: The regional data set stores the water meter related data corresponding to several authorized devices. Set up a total database and a distributed database, obtain several regional data sets and transfer them to the total database; Perform two data backups on several regional data sets in the total database to generate backup data one and backup data two respectively, and transfer backup data one and backup data two to different distributed databases for storage; When the corresponding backup data one or backup data two is damaged, generate a backup data instruction in the distributed database, obtain its own distributed database number, upload the distributed database number and the backup data instruction to the total database, and the total database performs data backup to generate new backup data one or backup data two and transmits it to the damaged distributed database; Use the backup data one or backup data two stored in the distributed database as the data set to be processed, input the data set to be processed into a preset format conversion program, convert it into a unified data format through the format conversion program, mark the converted data set to be processed as the data set to be detected, establish several channels numbered k, where k = 1, 2, 3,..., q, and q is a natural number greater than 0. Send the data set to be detected to the anomaly analysis module through the channel. Set an encryption period, and in the encryption period, obtain the data in the channel in real time. If attack data is detected, encapsulate it as an error data packet and upload it to the management center; It should be further noted that in the specific implementation process, the process of generating fault data and normal data by the anomaly value analysis includes: The anomaly analysis module dynamically generates a receiving port number, which is non-repetitive and unique. The channel has a corresponding sending port number, and a one-to-one mapping relationship is constructed between the sending port number and the receiving port number; After successfully constructing a one-to-one mapping relationship, obtain the dataset to be detected, and decompose the dataset to be detected into several pieces of water meter-related data. There are corresponding alarm thresholds preset for the total water consumption, period water consumption, and real-time water consumption in the water meter-related data; Denote the total water consumption, period water consumption, and real-time water consumption as D1, D2, and D3 respectively, and denote the corresponding alarm thresholds as D1`, D2`, and D3` respectively; When D1≥D1`, generate abnormal data one correspondingly. When D1<D1`, generate normal data one correspondingly; When D2≥D2`, generate abnormal data two correspondingly. When D2<D2`, generate normal data two correspondingly; When D3≥D3`, generate abnormal data three correspondingly. When D3<D3`, generate normal data three correspondingly; Summarize abnormal data one, abnormal data two, and abnormal data three to generate fault data, and summarize normal data one, normal data two, and normal data three to generate normal data; Establish a temporary interaction space, input the fault data and normal data into the temporary interaction space for encryption respectively, and after encryption, package them into encrypted data packets. The encrypted data packet generated according to the fault data is denoted as encrypted data packet one, and the encrypted data packet generated according to the normal data is denoted as encrypted data packet two; It should be further noted that in the specific implementation process, the process of generating a fault troubleshooting plan according to the fault data and having the corresponding troubleshooting personnel perform fault troubleshooting includes: Obtain encrypted data packet one, decrypt encrypted data packet one, and restore encrypted data packet one to fault data. The fault data includes abnormal data one, abnormal data two, and abnormal data three. Different fault data have corresponding fault troubleshooting plans; The corresponding relationship between the fault data and the fault troubleshooting plan is as follows: Abnormal data one corresponds to the primary response plan in the fault troubleshooting plan, abnormal data two corresponds to the secondary response plan in the fault troubleshooting plan, and abnormal data three corresponds to the tertiary response plan in the fault troubleshooting plan; Upload the primary response plan, secondary response plan, and tertiary response plan to the management center. The management center has a historical troubleshooting database, and several historical response plans are stored in the historical troubleshooting database; Collectively call the primary response plan, secondary response plan, and tertiary response plan the current response plan. The current response plan and the historical response plan include several fault keywords. Take the two historical response plans and the current response plan with the highest coincidence degree of the fault keywords as strongly similar associated objects; Obtain the historical countermeasures in the strongly similar associated objects. The historical countermeasures have corresponding troubleshooting personnel information and specific troubleshooting measures. Take the above two as the input information for the current countermeasures in the strongly similar associated objects, input the input information into the corresponding current countermeasures, and push the current countermeasures to the troubleshooting personnel associated with the troubleshooting personnel information. The troubleshooting personnel perform troubleshooting according to the specific troubleshooting measures and generate a troubleshooting record form; It should be noted that by comparing the current countermeasures with a number of historical countermeasures in the historical troubleshooting database in sequence, and inferring the similarity between the current countermeasures and the historical countermeasures based on the number of fault keywords, it serves the purpose of quickly determining the fault type to a certain extent and arranging the corresponding troubleshooting personnel to carry out troubleshooting. It also reduces the workload of fault analysis. The specific troubleshooting measures include checking whether the water pump and sluice of the water supply source are operating normally, checking whether the pipeline is leaking, blocked or damaged, verifying whether the valve status is open (when the valve is closed, it will cause the water supply to be interrupted), and checking whether there is a fault in the power system related to the water supply; The execution module is provided with a cost settlement unit, a visualization unit and a solution push unit; The cost settlement unit obtains the normal data to generate a water fee settlement list and pushes it to the user corresponding to the corresponding water meter reading device; The visualization unit obtains the historical data and current data transcribed by a number of water meter reading devices to generate a visualization report; The solution push unit generates an optimization solution based on the visualization report and pushes it; It should be further noted that in the specific implementation process, the process of generating the water fee settlement list and pushing it to the corresponding user includes: The water fee settlement list includes a historical water fee settlement list and a current water fee settlement list; Obtain the encrypted data packet two and decrypt the encrypted data packet two into the corresponding normal data. The cost settlement unit obtains the normal data and obtains the corresponding total water consumption, unit water price, period water consumption and real-time water consumption according to the normal data; Denote the total water consumption, unit water price and real-time water consumption as Sum, Pr and Sum` respectively; Obtain the historical water consumption according to the total water consumption and real-time water consumption, denoted as Data1, then Data1 = Sum - Sum`, and further obtain the historical water fee amount, denoted as P1, with P1 = Data1 × Pr. Obtain the current water fee amount according to the real-time water consumption, denoted as P2, then P2 = Sum` × Pr; The historical water fee amount P1 and the current water fee amount P2 are used as the settlement amount respectively, and then the historical water fee settlement list and the current water fee settlement list are generated, and the corresponding settlement amount is filled in, and the authorization ID generated by the associated user information is obtained, and the water fee settlement list is pushed to the user corresponding to the water meter reading device associated with the authorization ID; The historical water fee settlement list is synchronized and backed up to the management center for storage. When the user completes the payment and pays in full, the water fee settlement list is given a "1" mark. When the user pays but does not pay in full, the mark "Null" is given. If the user does not pay, the water fee settlement list is given a "0" mark, and the mark generation time is synchronously recorded, recorded as T 标 , when T 标 ≥T 阈 When the user's water supply is suspended, a payment reminder bill is generated and sent to the user. After the user completes the payment and pays in full, the water supply is resumed. 标 <T 阈 When no processing is done, T 阈 The critical water bill delinquency period is set; It should be further explained that, in the specific implementation process, the process of obtaining and pushing the optimization plan based on the generated visualization report includes: The historical water fee list corresponds to the historical data recorded by the water meter reading device, and the current water fee list corresponds to the current data recorded by the water meter reading device; The visualization report includes a historical water consumption trend report, a historical fault visualization report, and a current water consumption real-time visualization report. The historical water consumption trend report is generated based on historical data and has a corresponding trend characteristic curve. The historical fault visualization report is generated by acquiring fault data and has several corresponding fault inspection items. The current water consumption real-time visualization report is generated based on current data and has a corresponding real-time characteristic curve. Establish a two-dimensional coordinate system, map the trend characteristic curve and the real-time characteristic curve to the two-dimensional coordinate system, compare the two to generate overlapping curve segments and non-overlapping curve segments, mark the non-overlapping curve segments as segment data to be optimized, and transmit the segment data to be optimized to the solution push unit; The solution push unit obtains the segment data to be optimized, and adjusts the segment data to be optimized to the preset standard segment data, synchronously generates an optimization solution after adjusting to the standard segment data, performs corresponding optimization adjustments according to the optimization solution, and backs up and stores the optimization solution in the management center; It should be noted that the optimization scheme includes adjusting the unit price of water consumption and setting corresponding sectional prices according to the water consumption in different time periods, analyzing the water consumption peaks and valleys. During the time periods corresponding to the water consumption peaks, the sectional prices are increased, and during the time periods corresponding to the water consumption valleys, the sectional prices are decreased. Through the above adjustments, the number of segments to be optimized corresponding to the non-coincident curve segments is reduced, making the real-time feature curve approach the trend feature curve, and the trend feature curve is generated based on historical data, which are data of normal operation, and to a certain extent, it plays a role in optimizing the user's water consumption experience.

[0017] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.< / j>

Claims

1. A smart city water meter reading management system based on the Internet of Things, including a management center, characterized in that: The management center is communicatively connected with a meter reading terminal module, a data processing module, an abnormality analysis module, a monitoring and troubleshooting module, and an execution module; The meter reading terminal module includes a plurality of water meter reading devices, and records water meter related data through the water meter reading devices; The data processing module is used to perform blockchain encryption, regional data aggregation and distributed storage on water meter related data, and generate a data set to be detected, and encrypt the data set to be detected through a channel and send it to the abnormality analysis module; The abnormality analysis module dynamically generates a receiving port number and obtains the data set to be detected transmitted by the data processing module, and performs abnormal value analysis on the data set to be detected to generate fault data and normal data; The monitoring and troubleshooting module is used to generate a troubleshooting plan based on the fault data, and push the troubleshooting plan to the corresponding troubleshooting personnel, who then perform troubleshooting; The execution module is provided with a fee settlement unit, a visualization unit and a solution push unit; the fee settlement unit obtains normal data to generate a water fee settlement list, and pushes it to the user corresponding to the corresponding water meter reading device; the visualization unit obtains historical data and current data recorded by several water meter reading devices, and generates a visualization report; the solution push unit generates an optimization plan according to the visualization report and pushes it.

2. According to the Internet of Things-based smart city water meter reading management system according to claim 1, it is characterized in that: The process of recording water meter related data by the water meter reading device includes: The meter reading end module includes several water meter reading devices, each of which has a built-in database. The database is used to store water meter related data, including total water consumption, unit water price, time period water consumption, real-time water consumption and associated user information. A timed export cycle is set, and the water meter related data recorded in each database is encapsulated into a data folder, and several data folders are summarized and transmitted to the data processing module.

3. According to the Internet of Things-based smart city water meter reading management system according to claim 2, it is characterized in that: The process of blockchain encryption and regional data aggregation includes: The data processing module obtains a data folder, deconstructs it into water meter related data, generates an authorization ID and a corresponding authorization device according to the associated user information, generates a request instruction and sends it to the management center, the management center receives the request instruction and generates a key pair, the key pair includes a public key and a private key, takes each data folder as a block node, aggregates and generates a blockchain, sends the key pair to each block node, obtains the private key and writes it into the block node to generate a digital signature; obtains the block hash value corresponding to each block node through a hash algorithm, obtains the public key to encrypt the corresponding block node and converts it into an encrypted block, and uses the private key as the decryption key of the encrypted block; sets a regional form to store several different authorization IDs, aggregates the water meter related data of the authorization devices corresponding to different authorization IDs in the regional form, and generates several regional data sets.

4. According to the Internet of Things-based smart city water meter reading management system of claim 3, it is characterized in that: The process of distributing and storing water meter related data and generating the data set to be tested includes: A general database and a distributed database are set up, several regional data sets are obtained and transferred to the general database, data backup is performed in the general database to generate backup data 1 and backup data 2, and backup data 1 and backup data 2 are transferred to different distributed databases for storage, when the corresponding backup data 1 or backup data 2 is damaged, a backup data instruction is generated in the distributed database, and the distributed database number itself is obtained, the distributed database number and the backup data instruction are uploaded to the general database, and the general database performs data backup to generate new backup data 1 or backup data 2, and transmits it to the damaged distributed database; the backup data 1 or backup data 2 stored in the distributed database is used as a data set to be processed, and is input into a preset format conversion program to be converted into a unified data format and then marked as a data set to be detected, and several channels are established, and the data set to be detected is sent to the abnormality analysis module through channel encryption.

5. According to the Internet of Things-based smart city water meter reading management system of claim 4, it is characterized in that: The process of generating the fault data and normal data includes: The abnormal analysis module dynamically generates a receiving port number, and the channel has a corresponding sending port number. A one-to-one mapping relationship is established between the sending port number and the receiving port number to obtain a data set to be detected. The total water consumption, time period water consumption and real-time water consumption in the water meter related data corresponding to the data set to be detected are preset with corresponding alarm thresholds. According to the relationship between the total water consumption, time period water consumption and real-time water consumption and the alarm threshold, corresponding fault data and normal data are generated, and a temporary interactive space is established to input the fault data and normal data to generate corresponding encrypted data packet one and encrypted data packet two respectively.

6. The smart city water meter reading management system based on the Internet of Things according to claim 5 is characterized in that: The process of generating a troubleshooting plan based on the fault data and troubleshooting the fault includes: Obtain an encrypted data packet and decrypt it to restore it to fault data, the fault data includes abnormal data one, abnormal data two and abnormal data three, which respectively correspond to the first-level response plan, the second-level response plan and the third-level response plan in the fault troubleshooting plan. The management center has a preset historical troubleshooting database, which stores several historical response plans; mark the first-level response plan, the second-level response plan and the third-level response plan as current response plans, the current response plan and the historical response plan include several fault keywords, and the historical response plan and the current response plan with the highest overlap of fault keywords are taken as strongly similar associated objects; obtain the historical response plans in the strongly similar associated objects, the historical response plans have corresponding troubleshooting personnel information and specific troubleshooting measures, obtain the current response plan and push it to the troubleshooting personnel associated with the troubleshooting personnel information, and perform troubleshooting according to the specific troubleshooting measures.

7. The smart city water meter reading management system based on the Internet of Things according to claim 6 is characterized in that: The process of generating the water fee settlement list and pushing it to the corresponding user includes: The water fee settlement list includes a historical water fee settlement list and a current water fee settlement list. The encrypted data packet 2 is obtained and decrypted into corresponding normal data. The fee settlement unit obtains normal data, obtains historical water consumption according to total water consumption and real-time water consumption, obtains water unit price, and then obtains historical water fee amount, obtains current water fee amount according to real-time water consumption, uses historical water fee amount and current water fee amount as settlement amount respectively, and then generates historical water fee settlement list and current water fee settlement list, fills in corresponding settlement amount, obtains authorization ID generated by associated user information, and pushes the water fee settlement list to the user corresponding to the water meter reading device associated with the authorization ID.

8. The smart city water meter reading management system based on the Internet of Things according to claim 1 is characterized in that: The process of obtaining and pushing the optimization plan according to the visualization report includes: The historical water fee list corresponds to historical data, the current water fee list corresponds to current data, the visualization report includes a historical water use trend report, a historical fault visualization report and a current water use real-time visualization report, the historical water use trend report is generated based on historical data and corresponds to a trend characteristic curve, the historical fault visualization report is generated based on fault data and corresponds to a number of fault inspection items, and the current water use real-time visualization report is generated based on current data and corresponds to a real-time characteristic curve; A two-dimensional coordinate system is established, and the trend characteristic curve and the real-time characteristic curve are mapped to the two-dimensional coordinate system. The overlapping curve segments and the non-overlapping curve segments are generated by comparison, and the non-overlapping curve segments are marked as the segment data to be optimized and transmitted to the solution pushing unit; the solution pushing unit obtains the segment data to be optimized and adjusts it to the preset standard segment data, and after adjusting to the standard segment data, the optimization solution is synchronously generated.

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