Big data-based intelligent collection and detection method and system for urban water supply data

Abstract

The application discloses a big data-based intelligent collection and detection method and system for urban water supply data, and a big data-based intelligent collection and detection system for urban water supply data, which comprises a city water supply main pipe, intelligent water meters, a city water supply big data cloud computing platform and water meter user terminals, the city water supply main pipe is used for comprehensive water supply of all users in the city, and the intelligent water meters are installed on the pipelines of all user nodes of the city water supply main pipe; the intelligent water meters comprise a water supply data acquisition module, a multi-mode satellite positioning module, a time sequence synchronization module and a data encryption module; in the application, the intelligent water meters are used for comprehensive acquisition of water supply data on all user branch pipes of the city water supply pipeline, and the acquisition position positioning data and time synchronization records are bound during the water supply data acquisition process, wherein the acquisition of the positioning data can be positioned through multiple satellite positioning modes, including GPS positioning, Beidou positioning and QZSS positioning, so that the accuracy and safety of the positioning data are ensured.

Description

Technical Field

[0001] This invention relates to the field of urban water supply data collection and detection technology, specifically to a method and system for intelligent collection and detection of urban water supply data based on big data. Background Technology

[0002] Originating in the media field, smart cities refer to the integration and interconnection of urban systems and services through various information technologies or innovative concepts to improve resource utilization efficiency, optimize urban management and services, and enhance the quality of life for citizens. A smart city is a high-level form of urban informatization based on the next generation of innovation in a knowledge society, fully utilizing next-generation information technologies across all sectors of the city. It achieves deep integration of informatization, industrialization, and urbanization. The urban water supply system is closely integrated with smart cities by establishing a smart urban water supply management platform through informatization. It uses unified data access, management, and linkage as its core, and portal management as its link to achieve multi-system linkage. It is structured around a standard system and a security system, integrating basic sensing systems, data access platforms, hardware solutions, and business application systems.

[0003] The prerequisite for realizing a smart city is the collection of comprehensive information from various aspects of the city to form big data, followed by data processing and analysis. Water supply systems are a crucial infrastructure for urban construction, and fully understanding water consumption data at various points and time periods is a prerequisite for achieving smart water supply. Current technologies cannot comprehensively acquire urban water supply data because water usage within urban pipelines is fluctuating and unstable. Furthermore, current market methods for collecting and monitoring water supply big data do not directly obtain basic data from water meters at urban water supply points, failing to provide a detailed understanding of the water supply situation within urban pipelines. Traditional urban water supply data collection and transmission processes also lack data processing... Encryption is often necessary, but urban water supply data is easily accessible. With the development of information technology, urban water supply data has become part of national secrets. In particular, the big data collected on water usage by residents and businesses can be analyzed to reveal a great deal of valuable state secrets. Information leaks could cause incalculable harm. Traditional smart water meters used for water supply data collection have a relatively simple structure, lack self-generating power, and require regular battery replacements, which is inconvenient. Furthermore, the numerous electronic components integrated within the meters present heat dissipation challenges. Therefore, it is meaningful to propose a smart collection and detection method and system for urban water supply data based on big data. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for intelligent collection and detection of urban water supply data based on big data, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a smart collection and detection system for urban water supply data based on big data, comprising an urban water supply main pipe, smart water meters, an urban water supply big data cloud computing platform, and water meter user terminals.

[0006] The main urban water supply pipe is used for comprehensive water supply to all users in the city, and smart water meters are installed on the pipelines at each user node of the main urban water supply pipe.

[0007] The smart water meter installation includes a water supply data acquisition module, a multi-mode satellite positioning module, a time synchronization module, and a data encryption module;

[0008] The water supply data acquisition module is used by water meters to collect water supply data from each household node on the urban pipeline.

[0009] The multi-mode satellite positioning module is used for positioning the smart water meter at each household node, including a GPS positioning unit, a Beidou positioning unit, and a QZSS positioning unit, enabling the smart water meter to be positioned through multiple satellite positioning modes;

[0010] The timing synchronization module is used to bind the aforementioned collected data and timing trajectory;

[0011] The data encryption module is used to encrypt the water supply data of each household node collected above, and to manage and upload the encrypted water supply data.

[0012] The urban water supply big data cloud computing platform includes a real-time recording module for urban water supply operation, a water network anomaly time sequence analysis module, and a database.

[0013] The urban water supply operation real-time recording module includes a data decryption unit, a water meter data acquisition unit, and a water network water meter node map generation unit.

[0014] The data decryption unit is used to decrypt the encrypted data of the water supply to each household node.

[0015] The water meter data acquisition unit is used by the computing platform to collect the decrypted water supply data of each household node.

[0016] The water network and water meter node map generation unit is used to generate a dynamic map of urban water supply data nodes based on the water supply data of each household node.

[0017] The water network anomaly time series analysis module is used for correlation analysis based on time series and water supply quality anomalies big data;

[0018] The database includes an urban water supply database, an encryption algorithm database, and a water quality anomaly event feedback database. The urban water supply database is used to collect and store big data on urban water supply. The encryption algorithm database is used to store national cryptographic encryption algorithm data. The water quality anomaly event feedback database is used to store big data on water quality anomaly event feedback.

[0019] The water meter user terminal includes a water meter display data remote acquisition module and a water network water quality feedback module. The water meter display data remote acquisition module is used by urban users to remotely acquire big data on water supply detected by the smart water meter, and the water network water quality feedback module is used by urban users to report and record abnormal water quality events.

[0020] According to the above technical solution, the water supply data acquisition module includes a water metering unit, a water pressure monitoring unit, a water quality monitoring unit, and an environmental monitoring unit; it is used by the smart water meter to detect the water supply pressure and water quality at the user node, detect the user's water consumption, and conduct video monitoring of the surrounding environment of the smart water meter for the purpose of obtaining information on abnormal water quality events.

[0021] According to the above technical solution, the data encryption module includes an algorithm calling unit, an encryption operation unit, and a data output unit;

[0022] The algorithm invocation unit is used to invoke encryption algorithms within the encryption algorithm database;

[0023] The encryption calculation unit is used to input the collected water supply data into the invoked encryption algorithm for calculation and encryption;

[0024] The data output unit is used to upload the encrypted water supply data and upload the data to the urban water supply big data cloud computing platform.

[0025] According to the above technical solution, the encryption algorithm database internally stores symmetric encryption algorithms, elliptic curve asymmetric encryption algorithms, and hash algorithms.

[0026] According to the above technical solution, an inlet pipe and an outlet pipe are connected through the outer walls of both ends of the smart water meter. An electrical control box is installed on one outer wall of the smart water meter. A CPU and a battery are installed on the bottom inner wall of the electrical control box. A power generation and heat dissipation assembly is installed on the middle inner wall of the outlet pipe. The power generation and heat dissipation assembly includes a strip fixed on the inner wall of the outlet pipe. A connecting shaft is rotatably connected to the middle of the strip. An impeller is fixed on the outer wall of one end of the connecting shaft. A first bevel gear is fixed on the outer wall of the other end of the connecting shaft. A turbine is fixed on the bottom outer wall of the outlet pipe. A drive shaft is connected to one end of the turbine's rotating shaft. A second bevel gear is connected to one end of the drive shaft, which passes through the inside of the outlet pipe. An air intake pipe is connected to the air intake end of the turbine. An air delivery pipe is connected to the air delivery end of the turbine. One end of the air delivery pipe passes through the inside of the electrical control box. A generator is installed on the bottom outer wall of the turbine. The generator and the turbine are coaxially connected.

[0027] According to the above technical solution, the electrical output terminal of the generator is electrically connected to the electrical input terminal of the battery.

[0028] According to the above technical solution, a display screen is embedded on the top outer wall of the smart water meter, and a screen-linked dust collection component is provided at the end of the air suction pipe. The screen-linked dust collection component includes an annular ring fitted outside the display screen. Dust collection holes are distributed and opened through the inner wall of the annular ring. A dust suction pipe is connected through the outer wall of one side of the annular ring. A top cover is connected through the dust suction pipe at one end. A dust collection tank is screwed onto the inner wall of the bottom end of the top cover. An air inlet is distributed and opened through the outer wall of the outer end of the air suction pipe outside the top cover, and a filter screen is provided on the outer wall of the air inlet.

[0029] According to the above technical solution, a camera is embedded in the top outer wall of the electrical control box, and ventilation openings are distributed on the outer wall of the electrical control box.

[0030] A smart data collection and monitoring method for urban water supply based on big data includes the following steps: Step 1, building an urban water supply big data collection system; Step 2, collecting and acquiring water supply data; Step 3, encrypting and transmitting data; Step 4, obtaining feedback on water quality anomalies; Step 5, analyzing the time series of water network anomalies; Step 6, remotely reading urban water supply data.

[0031] In step one above, smart water meters are installed on the pipelines of user nodes in the urban water supply system. The national water supply management department sets up an urban water supply big data cloud computing platform. Urban smart water meter users use water meter user terminals, which can be one or more of mobile phones, computers, and iPads.

[0032] In step two above, after the urban water supply big data collection system is built and put into operation, smart water meters are used to collect information on the location of urban water supply nodes, water supply pressure at the nodes, and water quality data, and to detect the water consumption of users.

[0033] In step three above, after the smart water meter collects big data on water supply, it calls encryption algorithms in the encryption algorithm database. The encryption algorithms include symmetric encryption algorithms, elliptic curve asymmetric encryption algorithms, and hash algorithms, specifically including SM1, SM2, SM3, etc. The smart water meter calls the SM2 elliptic curve asymmetric encryption algorithm. During the encryption process, the big data on water supply, together with the SM2 elliptic curve asymmetric encryption algorithm, performs curve calculations and modulo operations to perform encryption calculations, resulting in encrypted data. The encrypted data is uploaded and transmitted to the urban water supply big data cloud computing platform through the data transmission module. The encrypted data is collected and stored in the urban water supply database. During the subsequent data retrieval process, the encrypted data is decrypted through the data decryption unit, without affecting the intuitive reading of the data.

[0034] In step four above, when a water quality anomaly occurs at a user node of the urban water supply system, the user edits and provides feedback on the water quality anomaly through the water meter user terminal, which is then transmitted to the water quality anomaly feedback database. The surrounding environment of the water meter is monitored by a camera structure to obtain the water quality anomaly.

[0035] In step five above, the collected water quality anomaly events and corresponding water supply data are analyzed.

[0036] In step six above, users can remotely obtain water meter data from the database of the city's water supply big data cloud computing platform through the water meter user terminal.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] (1) Comprehensive collection of water supply data on each user branch of the urban water supply pipeline is carried out through smart water meters. During the water supply data collection process, the location data and time are bound and recorded synchronously. The location data can be collected through multiple satellite positioning modes, including GPS positioning, Beidou positioning and QZSS positioning, which ensures the accuracy and security of the location data. It is conducive to the later retrieval and big data analysis. Users can remotely obtain the big data of water supply through the water meter user terminal. The urban water supply big data cloud computing platform, based on time series and big data correlation analysis of water quality anomalies, enables staff to more intuitively understand the causes of water quality anomalies, constructs the time series of water supply data indicator variables, and summarizes the trend of urban water supply behavior changes represented by the series.

[0039] (2) During the process of uploading the water supply big data collected by the smart water meter to the urban water supply big data cloud computing platform, the collected water supply big data is encrypted, and the encrypted data is decrypted during the subsequent data retrieval process, so as not to affect the intuitive reading of the data; This solves the problem that the traditional urban water supply data collection process does not encrypt the data, the urban water supply data is easily obtained at will, the urban water supply data has become part of the national secrets, and a lot of valuable national secret information can be analyzed, and the information leakage is likely to cause incalculable harm.

[0040] (3) Based on the traditional smart water meter, a power generation and heat dissipation component and a screen dust collection component are set up. During the water flow in the smart water meter, the generator is driven to rotate and generate electricity to charge the battery in the smart water meter. This solves the problem that traditional smart water meters need to replace batteries regularly, which is inconvenient. The rotation of the turbine sucks up the dust above the display screen, realizing the automatic cleaning of the display screen. The turbine then blows the air into the electrical control box through the air pipe and blows it out through the vent, realizing the air blowing and heat dissipation of the components in the water meter. Attached Figure Description

[0041] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0042] Figure 1 This is a schematic diagram of the overall structure of the intelligent collection and detection system for urban water supply data based on big data, as per the present invention.

[0043] Figure 2 This is a system flowchart of the intelligent collection and detection system for urban water supply data based on big data, as described in this invention.

[0044] Figure 3 This is a three-dimensional cross-sectional structural diagram of the smart water meter in this invention;

[0045] Figure 4 This is the present invention. Figure 3 Enlarged view of the structure of region A in the middle;

[0046] Figure 5 This is a three-dimensional cross-sectional view of the water outlet pipe in the smart water meter of the present invention;

[0047] Figure 6 This is the present invention. Figure 3 Enlarged view of the structure of region B in the middle;

[0048] Figure 7 This is a flowchart of the power grid big data mining method for smart city operation and management according to the present invention;

[0049] In the diagram: 1. Main water supply pipe; 2. Smart water meter; 3. Urban water supply big data cloud computing platform; 4. Water meter user terminal; 5. Inlet pipe; 6. Outlet pipe; 7. Electrical control box; 8. CPU; 9. Battery; 10. Power generation and heat dissipation component; 11. Linked screen dust collection component; 12. Display screen; 13. Camera; 14. Ventilation outlet; 21. Water supply data acquisition module; 211. Water metering unit; 212. Water pressure monitoring unit; 213. Water quality monitoring unit; 214. Environmental monitoring unit; 22. Multi-mode satellite positioning module; 23. Time synchronization module; 24. Data encryption module; 241. Algorithm calling unit; 242. Encryption calculation unit; 243. Data output unit; 31. Real-time recording module for urban water supply operation; 311. Data decryption... 312. Water meter data acquisition unit; 313. Water network water meter node map generation unit; 32. Water network anomaly time sequence analysis module; 33. Database; 331. Urban water supply database; 332. Encryption algorithm database; 333. Water quality anomaly event feedback database; 41. Water meter display data remote acquisition module; 42. Water network water quality feedback module; 101. Strip block; 102. Connecting shaft; 103. Impeller; 104. First bevel gear; 105. Turbine; 106. Drive shaft; 107. Second bevel gear; 108. Air supply pipe; 109. Air intake pipe; 1010. Generator; 111. Ring ring; 112. Dust suction hole; 113. Dust suction pipe; 114. Top cover; 115. Dust collection tank; 116. Air inlet; 117. Filter screen. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Please see Figure 1-7 This invention provides a technical solution: a smart collection and detection system for urban water supply data based on big data, comprising an urban water supply main pipe 1, a smart water meter 2, an urban water supply big data cloud computing platform 3, and a water meter user terminal 4.

[0052] The city water supply main 1 is used for the comprehensive water supply to all users in the city. Smart water meters 2 are installed on the pipelines of each user node of the city water supply main 1.

[0053] The smart water meter 2 includes a water supply data acquisition module 21, a multi-mode satellite positioning module 22, a time synchronization module 23, and a data encryption module 24;

[0054] The water supply data acquisition module 21 is used to collect water supply data from each household node on the urban pipeline by water meters;

[0055] The multi-mode satellite positioning module 22 is used for positioning of the smart water meter 2 at each household node, including GPS positioning unit, Beidou positioning unit and QZSS positioning unit, so that the smart water meter 2 can be positioned through multiple satellite positioning modes;

[0056] The timing synchronization module 23 is used to bind the aforementioned collected data and timing trajectory;

[0057] The data encryption module 24 is used to encrypt the water supply data of each household node collected above, and to manage and upload the encrypted water supply data.

[0058] The urban water supply big data cloud computing platform 3 includes an urban water supply operation real-time recording module 31, a water network anomaly time sequence analysis module 32, and a database 33;

[0059] The real-time recording module 31 for urban water supply operation includes a data decryption unit 311, a water meter data acquisition unit 312, and a water network water meter node map generation unit 313.

[0060] The data decryption unit 311 is used to decrypt the encrypted data of water supply to each household node;

[0061] The water meter data acquisition unit 312 is used by the computing platform to collect the decrypted water supply data of each household node;

[0062] The water network and water meter node map generation unit 313 is used to generate a dynamic map of urban water supply data nodes based on the water supply data of each household node.

[0063] The water network anomaly time series analysis module 32 is used for correlation analysis of time series and water supply quality anomalies based on big data.

[0064] Database 33 includes urban water supply database 331, encryption algorithm database 332 and water quality anomaly event feedback database 333. Urban water supply database 331 is used for the storage of big data on urban water supply, encryption algorithm database 332 is used for the storage of national cryptographic encryption algorithm data, and water quality anomaly event feedback database 333 is used for the storage of big data on water quality anomaly event feedback.

[0065] The water meter user terminal 4 includes a water meter display data remote acquisition module 41 and a water network water quality feedback module 42. The water meter display data remote acquisition module 41 is used by urban users to remotely acquire big data of water supply detected by the smart water meter 2, and the water network water quality feedback module 42 is used by urban users to report and record abnormal water quality events.

[0066] It should be noted that smart water meters 2 are installed at the user pipeline nodes of the main urban water supply line 1. These smart water meters comprehensively collect water supply data from all user branch pipes within the urban water supply pipeline. During data collection, location data and time are recorded synchronously. The location data collection utilizes multiple satellite positioning modes, including GPS, BeiDou, and QZSS, ensuring the accuracy and security of the location data. This facilitates subsequent retrieval and big data analysis. The basic data from the nodes is uploaded to the urban water supply big data cloud computing platform 3, enabling the detection and collection of urban water supply big data. Urban users can remotely acquire big data on water supply detected by smart water meters 2 through water meter user terminal 4. Users at each node can also edit and record abnormal water quality events during the water supply process through water meter user terminal 4. The urban water supply big data cloud computing platform 3, based on time series and correlation analysis of abnormal water quality big data, enables staff to more intuitively understand the causes of abnormal water quality problems, constructs time series of water supply data indicator variables, and then conducts correlation and dissimilarity analysis on the trend, periodicity and randomness of indicator variables between different series. Based on this, the trend of urban water supply behavior change represented by the series is summarized.

[0067] The water supply data acquisition module 21 includes a water metering unit 211, a water pressure monitoring unit 212, a water quality monitoring unit 213, and an environmental monitoring unit 214; it is used by the smart water meter 2 to detect the water supply pressure and water quality at the user node, detect the user's water consumption, and conduct video monitoring of the surrounding environment of the smart water meter 2 for the purpose of obtaining information on abnormal water quality events.

[0068] It should be noted that the basic structure of the smart water meter 2 is based on existing technology, which can be found in relevant patents for smart water meters. The smart water meter 2 collects and acquires urban water supply pressure and water quality data, detects users' water consumption, and conducts video monitoring of water quality anomalies through the cooperation of the environmental monitoring unit 214 and the camera 13.

[0069] The data encryption module 24 includes an algorithm calling unit 241, an encryption operation unit 242, and a data output unit 243;

[0070] The algorithm calling unit 241 is used to call encryption algorithms within the encryption algorithm database 332;

[0071] The encryption operation unit 242 is used to input the collected water supply data into the invoked encryption algorithm for operation and encryption;

[0072] The data output unit 243 is used to upload the encrypted water supply data and upload the data to the urban water supply big data cloud computing platform 3.

[0073] The internal storage of the encryption algorithm database 332 contains symmetric encryption algorithms, elliptic curve asymmetric encryption algorithms, and hash algorithms.

[0074] It should be noted that during the process of uploading the water supply big data collected by the smart water meter 2 to the urban water supply big data cloud computing platform 3, the encryption algorithm is first called in the encryption algorithm database 332 of the urban water supply big data cloud computing platform 3. Then, the collected water supply data is fed into the called encryption algorithm for processing and encryption to obtain encrypted data. The encrypted data is then uploaded to the urban water supply big data cloud computing platform 3. During the subsequent data retrieval process, the encrypted data is decrypted without affecting the intuitive reading of the data. This solves the problem that the traditional urban water supply data collection process does not encrypt the data, making urban water supply data easy to obtain at will. Urban water supply data has become part of national secrets, and a lot of valuable national secret information can be analyzed. The leakage of information can easily cause incalculable harm.

[0075] A water inlet pipe 5 and a water outlet pipe 6 are connected through the outer walls of both ends of the smart water meter 2. An electrical control box 7 is installed on one outer wall of the smart water meter 2. A CPU 8 and a battery 9 are installed on the inner wall of the bottom of the electrical control box 7. A power generation and heat dissipation assembly 10 is installed on the inner wall of the middle part of the water outlet pipe 6. The power generation and heat dissipation assembly 10 includes a strip 101 fixed to the inner wall of the water outlet pipe 6. A connecting shaft 102 is rotatably connected to the middle of the strip 101. An impeller 103 is fixed on the outer wall of one end of the connecting shaft 102, and a first impeller 103 is fixed on the outer wall of the other end of the connecting shaft 102. A bevel gear 104 is attached to a turbine 105 fixed on the bottom outer wall of the water outlet pipe 6. One end of the turbine 105's rotating shaft is connected to a drive shaft 106, which passes through the inside of the water outlet pipe 6 and is connected to a second bevel gear 107. The turbine 105's intake end is connected to an intake pipe 109, and the turbine 105's output end is connected to an output pipe 108. One end of the output pipe 108 passes through the inside of the electrical control box 7. A generator 1010 is installed on the bottom outer wall of the turbine 105, and the generator 1010 and the turbine 105 are coaxially connected.

[0076] The output terminal of the generator 1010 is electrically connected to the input terminal of the battery 9.

[0077] The smart water meter 2 has a display screen 12 embedded on its top outer wall. The end of the suction pipe 109 is equipped with a screen-linked dust collection component 11. The screen-linked dust collection component 11 includes an annular ring 111 fitted outside the display screen 12. Dust collection holes 112 are distributed and opened through the inner wall of the annular ring 111. A dust collection pipe 113 is connected through the outer wall of one side of the annular ring 111. One end of the dust collection pipe 113 is connected through the top cover 114. A dust collection tank 115 is screwed onto the inner wall of the bottom end of the top cover 114. The suction pipe 109 passes through the outer wall of one end of the top cover 114 and has air inlets 116 distributed and opened through the outer wall. A filter screen 117 is provided on the outer wall of the air inlets 116.

[0078] A camera 13 is embedded in the top outer wall of the electrical control box 7, and ventilation openings 14 are distributed on the outer wall of the electrical control box 7.

[0079] It should be noted that during the use of the aforementioned smart water meter 2, water is transmitted through the inlet pipe 5 and the outlet pipe 6. This process impacts the impeller 103, causing the connecting shaft 102 and the first bevel gear 104 to rotate. The first bevel gear 104 and the second bevel gear 107, in turn, drive the transmission shaft 106 to rotate. This, in turn, drives the turbine 105 and the generator 1010 to rotate. The generator 1010 generates electricity to charge the battery 9 inside the smart water meter 2, thus solving the problem of the need for periodic battery replacements in traditional smart water meters 2. To address the issue of airflow, the turbine 105 rotates at the intake pipe 109 to draw in air. Dust above the display screen 12 is drawn in through the dust collection tank 115 and the suction pipe 113 at the suction hole 112 of the annular ring 111. Dust and air are collected in the dust collection tank 115 through the suction pipe 113. Dust is filtered by the filter screen 117 and collected in the dust collection tank 115. Air enters the turbine 105 through the intake pipe 109, and is then blown into the electrical control box 7 through the air delivery pipe 108, and blown out through the vent 14 to achieve heat dissipation for the components inside the water meter.

[0080] A smart data collection and monitoring method for urban water supply based on big data includes the following steps: Step 1, building an urban water supply big data collection system; Step 2, collecting and acquiring water supply data; Step 3, encrypting and transmitting data; Step 4, obtaining feedback on water quality anomalies; Step 5, analyzing the time series of water network anomalies; Step 6, remotely reading urban water supply data.

[0081] In step one above, smart water meters 2 are installed on the pipelines of user nodes in the urban water supply system, the national water supply management department sets up an urban water supply big data cloud computing platform 3, and the users of the urban smart water meters 2 use water meter user terminals 4, which can be one or more of mobile phones, computers, and iPads.

[0082] In step two above, after the urban water supply big data collection system is built and put into operation, the smart water meter 2 collects information on the location of urban water supply nodes, water supply pressure at the nodes, and water quality data, and detects the water consumption of users.

[0083] In step three above, after the smart water meter 2 collects big data on water supply, it calls the encryption algorithm in the encryption algorithm database 332. The encryption algorithms include symmetric encryption algorithms, elliptic curve asymmetric encryption algorithms, and hash algorithms, specifically including SM1, SM2, SM3, etc. The smart water meter 2 calls the SM2 elliptic curve asymmetric encryption algorithm. During the encryption process, the big data on water supply, together with the SM2 elliptic curve asymmetric encryption algorithm, performs curve calculations and modulo operations to perform encryption calculations and obtain encrypted data. The encrypted data is uploaded and transmitted to the urban water supply big data cloud computing platform 3 through the data transmission module. The encrypted data is collected and stored in the urban water supply database 331. During the subsequent data retrieval process, the encrypted data is decrypted through the data decryption unit 311 without affecting the intuitive reading of the data.

[0084] In step four above, when a water quality anomaly occurs at a user node of the urban water supply system, the user edits and provides feedback on the water quality anomaly through the water meter user terminal 4, which is then transmitted to the water quality anomaly feedback database 333. The camera structure performs video monitoring of the surrounding environment at the water meter to obtain the water quality anomaly.

[0085] In step five above, the collected water quality anomaly events and corresponding water supply data are analyzed.

[0086] In step six above, the user can remotely obtain water meter data from the database 33 of the urban water supply big data cloud computing platform 3 through the water meter user terminal 4.

[0087] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0088] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A big data-based intelligent collection and detection system for urban water supply data, characterized in that, The utility model relates to a city water supply system, which comprises a city water supply main pipe (1), an intelligent water meter (2), a city water supply big data cloud computing platform (3) and a water meter user terminal (4). The city water supply main pipe (1) is used for overall water supply for users in the city, and an intelligent water meter (2) is installed on a pipeline of each user node of the city water supply main pipe (1). The intelligent water meter (2) comprises a water supply data acquisition module (21), a multi-mode satellite positioning module (22), a time sequence synchronization module (23) and a data encryption module (24). The water supply data acquisition module (21) is used for collecting water supply data of each household node on a city pipeline by the water meter. The multi-mode satellite positioning module (22) is used for positioning the intelligent water meter (2) on each household node, and comprises a GPS positioning unit, a Beidou positioning unit and a QZSS positioning unit, so that the intelligent water meter (2) can be positioned by multiple satellite positioning modes. The time sequence synchronization module (23) is used for binding collected data and a time sequence track. The data encryption module (24) is used for encrypting collected water supply data of each household node, and managing and uploading the encrypted water supply data. The city water supply big data cloud computing platform (3) comprises a city water supply operation real-time recording module (31), a water network abnormal time sequence analysis module (32) and a database (33). The city water supply operation real-time recording module (31) comprises a data decryption unit (311), a water meter data acquisition unit (312) and a water network water meter node map generation unit (313). The data decryption unit (311) is used for decrypting acquired encrypted data of water supply of each household node. The water meter data acquisition unit (312) is used for collecting water supply data of each household node by the computing platform after decryption. The water network water meter node map generation unit (313) is used for generating a city water supply data node dynamic map according to the water supply data of each household node. The water network abnormal time sequence analysis module (32) is used for time sequence and water supply water quality abnormal big data correlation analysis. The database (33) comprises a city water supply database (331), an encryption algorithm database (332) and a water quality abnormal event feedback database (333), the city water supply database (331) is used for storing city water supply big data, the encryption algorithm database (332) is used for storing national encryption algorithm data, and the water quality abnormal event feedback database (333) is used for storing water quality abnormal event feedback big data. The water meter user terminal (4) comprises a water meter display data remote acquisition module (41) and a water network water quality feedback module (42), the water meter display data remote acquisition module (41) is used for remotely acquiring intelligent water meter (2) detection water supply big data by a city user, and the water network water quality feedback module (42) is used for feedback filing of a city user on a water quality abnormal event.

2. The big data-based urban water supply data intelligent collection and detection system according to claim 1, characterized in that, The water supply data acquisition module (21) comprises a water consumption metering unit (211), a water pressure monitoring unit (212), a water quality monitoring unit (213) and an environment monitoring unit (214). The intelligent water meter (2) detects the water supply pressure and water quality at the user node, detects the user water consumption, and monitors the surrounding environment of the intelligent water meter (2) to obtain water quality abnormal event problems. 3.The big data-based intelligent collection and detection system for urban water supply data according to claim 1, wherein, The data encryption module (24) includes an algorithm calling unit (241), an encryption operation unit (242), and a data output unit (243). The algorithm calling unit (241) is used to call encryption algorithms in the encryption algorithm database (332). The encryption operation unit (242) is used to bring the collected water supply data into the called encryption algorithm for operation encryption. The data output unit (243) is used to upload the encrypted water supply data and output the data to the city water supply big data cloud computing platform (3). 4.The big data-based intelligent collection and detection system for urban water supply data according to claim 1, wherein, The encryption algorithm database (332) internally stores symmetric encryption algorithms, elliptic curve asymmetric encryption algorithms, and hash algorithms. 5.The big data-based intelligent collection and detection system for urban water supply data according to claim 1, wherein, Both ends of the outer wall of the intelligent water meter (2) are connected with the water inlet pipe (5) and the water outlet pipe (6), and the outer wall of one side of the intelligent water meter (2) is provided with an electric control box (7). The bottom inner wall of the electric control box (7) is installed with a CPU (8) and a storage battery (9). The middle inner wall of the water outlet pipe (6) is provided with a power generation and heat dissipation assembly (10). The power generation and heat dissipation assembly (10) includes a strip block (101) fixed on the inner wall of the water outlet pipe (6). The middle part of the strip block (101) is rotatably connected with a connecting shaft (102). The outer wall of one end of the connecting shaft (102) is fixed with an impeller (103). The outer wall of the other end of the connecting shaft (102) is fixed with a first bevel gear (104). The bottom outer wall of the water outlet pipe (6) is fixed with a turbine (105). The rotating shaft of the turbine (105) is connected with a transmission shaft (106). The transmission shaft (106) penetrates the inner end of the water outlet pipe (6) and is connected with a second bevel gear (107). The suction end of the turbine (105) is connected with a suction pipe (109). The gas delivery end of the turbine (105) is connected with a gas delivery pipe (108). One end of the gas delivery pipe (108) penetrates the inside of the electric control box (7). The bottom outer wall of the turbine (105) is installed with a generator (1010), and the generator (1010) and the turbine (105) are coaxially connected. 6.The big data-based intelligent collection and detection system for urban water supply data according to claim 5, wherein, The electric output end of the generator (1010) is electrically connected with the electric input end of the storage battery (9). 7.The big data-based intelligent collection and detection system for urban water supply data according to claim 5, characterized in that, The top outer wall of the intelligent water meter (2) is inlaid with a display screen (12), and the end of the air suction pipe (109) is provided with a linkage screen dust suction assembly (11), which comprises an annular ring (111) arranged outside the display screen (12), a plurality of dust suction holes (112) are distributed and penetratingly formed in the inner wall of the annular ring (111), a dust suction pipe (113) is connected to one side of the outer wall of the annular ring (111), a top cover (114) is connected to one end of the dust suction pipe (113), a dust collecting tank (115) is screw-connected to the bottom end inner wall of the top cover (114), and a plurality of air inlet holes (116) are distributed and penetratingly formed in the outer wall of the top cover (114), and a filter screen (117) is arranged on the outer wall of the air inlet hole (116). 8.The big data-based intelligent collection and detection system for urban water supply data according to claim 5, wherein, A camera (13) is inlaid and mounted on the top outer wall of the electric control box (7), and a plurality of ventilation openings (14) are distributed and formed in the outer wall of the electric control box (7).

9. A method for intelligent collection and detection of urban water supply data based on big data, comprising the following steps, Step one, city water supply big data collection system construction; step two, water supply data acquisition; step three, data encryption transmission; step four, water quality abnormal event feedback acquisition; step five, water network abnormal timing analysis; step six, remote reading of city water supply data, characterized in that: In step one, the intelligent water meter (2) is installed on the pipeline of the city water supply system user node, the city water supply big data cloud computing platform (3) is erected and constructed, and the city intelligent water meter (2) user uses the water meter user terminal (4), which is one or more of a mobile phone, a computer and an ipad; In step two, after the city water supply big data collection system is constructed and runs, the city water supply node position information, node water supply pressure and 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