City drainage pipe network management method and system based on thermodynamic diagram

Abstract

The invention provides an urban drainage pipe network management method and system based on a thermodynamic diagram, and belongs to the technical field of drainage pipe network management. The method comprises the steps that S1, a server obtains urban basic data to construct a drainage pipe network management model; s2, the edge device collects drainage pipe network monitoring data through a sensor group and preprocesses the drainage pipe network monitoring data; s3, encrypting the monitoring data of the drainage pipe network into encrypted monitoring data, and uploading the encrypted monitoring data to a server; s4, the server decrypts the encrypted monitoring data to obtain drainage pipe network monitoring data, and performs big data analysis on the drainage pipe network monitoring data to obtain a drainage pipe network hidden danger analysis result; and S5, the server generates a hidden danger thermodynamic diagram based on the drainage pipe network hidden danger analysis result, and loads the hidden danger thermodynamic diagram and the drainage pipe network monitoring data on the drainage pipe network management model for display. The system has the advantages that the efficiency, quality, convenience and safety of drainage pipe network management are greatly improved, and the labor cost of drainage pipe network management is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of drainage pipe network management, and particularly to a method and system for urban drainage pipe network management based on a heat map. Background Art

[0002] Drainage pipe networks include rainwater pipe networks and sewage pipe networks; when a city faces heavy rainfall, a large amount of rainwater flows along the city's roads, and this rainwater needs to be drained through the rainwater pipe network. If it cannot be drained in time, it will cause waterlogging on the road surface, and low-lying garages, basements, overhead floors, etc. will be flooded, not only causing property losses, but also seriously leading to safety problems in severe cases; if the sewage pipe network becomes congested and the sewage of households cannot be discharged, it will seriously affect the living quality of residents; that is, drainage pipe networks belong to important urban infrastructure, so they need to be managed.

[0003] Regarding the management of drainage pipe networks, traditionally, it mainly relies on some basic drawing materials and the personal experience and memory of staff, and has the following disadvantages: 1. The efficiency and accuracy largely depend on the professional knowledge and experience of the staff, the detail and update frequency of the drawings; 2. Restricted by the non-uniformity of the construction stages of old urban blocks, there are contradictions such as incomplete data and insufficient management investment; 3. It is impossible to obtain relevant data of drainage pipe networks in a timely manner, and thus it is impossible to respond to disasters and emergencies in a timely manner; 4. It is impossible to manage drainage pipe networks intuitively, which is prone to decision-making mistakes; 5. No relevant security measures are taken for the relevant data generated during the management process, and there is a possibility of being stolen and tampered with, posing a great security risk. That is, traditionally, there are problems of low efficiency, poor management quality, high management labor cost, and poor management convenience in drainage pipe network management. Therefore, how to provide a method and system for urban drainage pipe network management based on a heat map to improve the efficiency, quality, convenience, and security of drainage pipe network management and reduce the labor cost of drainage pipe network management has become an urgent technical problem to be solved. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and system for urban drainage pipe network management based on a heat map to improve the efficiency, quality, convenience, and security of drainage pipe network management and reduce the labor cost of drainage pipe network management.

[0005] In the first aspect, the present invention provides a method for urban drainage pipe network management based on a heat map, including the following steps: Step S1, the server obtains urban basic data including drainage pipe network data and urban geographic data, and constructs a three-dimensional drainage pipe network management model based on the urban basic data through CIM technology; Step S2: The edge device collects the monitoring data of the drainage pipe network in real time through the sensor group, and preprocesses the collected monitoring data of the drainage pipe network; Step S3: The edge device encrypts the monitoring data of the drainage pipe network into encrypted monitoring data, and uploads the encrypted monitoring data to the server; Step S4: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data to obtain the monitoring data of the drainage pipe network, and performs big data analysis on the monitoring data of the drainage pipe network based on the load balancing technology and the multi-threading technology to obtain the analysis result of potential hazards in the drainage pipe network; Step S5: The server generates a heat map of potential hazards based on the analysis result of potential hazards in the drainage pipe network, and loads the heat map of potential hazards and the monitoring data of the drainage pipe network on the drainage pipe network management model for display; Step S6: The server generates a warning notice based on the heat map of potential hazards, and performs a warning operation based on the warning notice; Step S7: The server generates a management log of the drainage pipe network based on the monitoring data of the drainage pipe network, the analysis result of potential hazards in the drainage pipe network, the heat map of potential hazards, and the warning notice, and encrypts and stores the management log of the drainage pipe network; The specific content of step S4 is as follows: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through the second asymmetric encryption algorithm to obtain the third compressed sub-data, the initial vector, the MAC value, and the time stamp. After performing timeliness verification through the time stamp, integrity verification is performed on each third compressed sub-data through each MAC value, and each third compressed sub-data is decrypted through the first asymmetric encryption algorithm to obtain the second compressed sub-data. Each second compressed sub-data is decrypted through the symmetric encryption algorithm and the initial vector to obtain the first compressed sub-data. Each first compressed sub-data is spliced into compressed data, and the compressed data is decompressed through run-length encoding to obtain the monitoring data of the drainage pipe network; The server performs big data analysis on the monitoring data of the drainage pipe network based on the load balancing technology and the multi-threading technology to obtain the analysis result of potential hazards in the drainage pipe network, which at least includes the pipe section location, the flow data, and the water quality grade; The specific content of step S5 is as follows: The server respectively sets the display forms of each flow data and water quality grade, generates a corresponding two-dimensional array based on the analysis result of potential hazards in the drainage pipe network and the display form, imports the two-dimensional array into the heat map generation tool, sets the heat map parameters at least including the resolution, the heat map size, the element layout, and the label to generate the heat map of potential hazards, and asynchronously loads the heat map of potential hazards and the monitoring data of the drainage pipe network on the drainage pipe network management model for display through coordinate conversion and mapping, and adjusts the transparency of the heat map of potential hazards and the monitoring data of the drainage pipe network.

[0006] Further, step S1 is specifically as follows: The server obtains urban basic data including drainage pipe network data and urban geographical data in real time from the database through an SQL query statement; The drainage pipe network data at least includes pipe network basic data, pipe network accessory facility data, water conservancy data, and rain and sewage mixed connection data; the urban geographical data at least includes administrative division data, pipe network service area, remote sensing image, topographic map, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data; The server constructs a three-dimensional drainage pipe network management model through CIM technology and maps the latest urban basic data to the drainage pipe network management model in real time; Further, step S2 is specifically as follows: Each edge device distributed around the drainage pipe network collects drainage pipe network monitoring data in real time through a sensor group at least including a water level sensor, a flow velocity sensor, a flow meter, a water quality monitor, and a locator; the drainage pipe network monitoring data at least includes water level, flow velocity, flow rate, turbidity, pH value, and pipe segment position; Each edge device performs preprocessing on the collected drainage pipe network monitoring data at least including null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association.

[0007] Further, step S3 is specifically as follows: The edge device sets an upload period and compresses the preprocessed drainage pipe network monitoring data within the upload period into compressed data through run-length encoding; The edge device sets a segment length, segments the compressed data based on the segment length to obtain a number of first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each of the first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtains the current timestamp, and encrypts each of the third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploads the encrypted monitoring data to the server in real time through the TLS protocol.

[0008] Further, step S6 is specifically as follows: The server generates a warning notice that at least carries traffic data, water quality level, warning pipe segment location, and warning time based on the hidden danger heat map, displays each of the warning notices through pre-associated large screen carousel or split screen, encrypts the warning notice into an encrypted notice, and pushes the encrypted notice to the management terminal in real time through the TLS protocol to perform a warning operation; The specific method for encrypting the warning notice into an encrypted notice is as follows: Perform a hash calculation on the warning notice through the SHA-512 algorithm to obtain a first hash value, encrypt the warning notice and the first hash value through the RC2 algorithm to obtain first encrypted data, generate a first random string with a first length, add the first random string to a first specified position of the first encrypted data to obtain second encrypted data, encrypt the second encrypted data through the AES algorithm to obtain third encrypted data, generate a second random string with a second length, add the second random string to a second specified position of the third encrypted data to obtain fourth encrypted data, and encrypt the fourth encrypted data through the ECDSA algorithm to obtain an encrypted notice.

[0009] Further, the specific step S7 is as follows: The server generates a drainage pipe network management log in real time based on the drainage pipe network monitoring data, the drainage pipe network hidden danger analysis result, the hidden danger heat map, and the warning notice; The server creates a pair of public key and private key, performs a hash calculation on the drainage pipe network management log through the SHA-384 algorithm to obtain a second hash value, encrypts the drainage pipe network management log and the second hash value through the private key to obtain first-level encrypted data, encrypts the public key through the IDEA algorithm to obtain a first-level key, maps the first-level key based on a preset first mapping rule to obtain a second-level key, encrypts the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, maps the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and backup on the encrypted log.

[0010] In a second aspect, the present invention provides a city drainage pipe network management system based on a heat map, including the following modules: A drainage pipe network management model construction module, configured to enable the server to obtain urban basic data including drainage pipe network data and urban geographical data, and construct a three-dimensional drainage pipe network management model based on the urban basic data through the CIM technology; A drainage pipe network monitoring data acquisition module, configured to enable edge devices to collect drainage pipe network monitoring data in real time through a sensor group, and preprocess the collected drainage pipe network monitoring data; A drainage network monitoring data upload module, which is used for an edge device to encrypt the drainage network monitoring data into encrypted monitoring data and upload the encrypted monitoring data to a server; A big data analysis module, which is used for the server to receive the encrypted monitoring data in real time, decrypt the encrypted monitoring data to obtain the drainage network monitoring data, and perform big data analysis on the drainage network monitoring data based on the load balancing technology and the multi-threading technology to obtain the analysis result of potential hazards in the drainage network; A potential hazard heat map generation and display module, which is used for the server to generate a potential hazard heat map based on the analysis result of potential hazards in the drainage network, and load the potential hazard heat map and the drainage network monitoring data on the drainage network management model for display; An early warning module, which is used for the server to generate an early warning notice based on the potential hazard heat map and perform an early warning operation based on the early warning notice; A drainage network management log management module, which is used for the server to generate a drainage network management log based on the drainage network monitoring data, the analysis result of potential hazards in the drainage network, the potential hazard heat map and the early warning notice, and encrypt and store the drainage network management log; The big data analysis module is specifically used for: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through a second asymmetric encryption algorithm to obtain third compressed sub-data, an initial vector, a MAC value and a timestamp, performs timeliness verification through the timestamp, performs integrity verification on each third compressed sub-data through each MAC value respectively, decrypts each third compressed sub-data through a first asymmetric encryption algorithm to obtain second compressed sub-data, decrypts each second compressed sub-data through a symmetric encryption algorithm and the initial vector respectively to obtain first compressed sub-data, splices each first compressed sub-data into compressed data, and decompresses the compressed data through run-length encoding to obtain the drainage network monitoring data; The server performs big data analysis on the drainage network monitoring data based on the load balancing technology and the multi-threading technology to obtain the analysis result of potential hazards in the drainage network, which at least includes the pipe section position, the flow data and the water quality grade; The potential hazard heat map generation and display module is specifically used for: The server respectively sets the display forms of each flow data and water quality grade, generates a corresponding two-dimensional array based on the analysis result of potential hazards in the drainage network and the display forms, imports the two-dimensional array into a heat map generation tool, sets heat map parameters at least including the resolution, the heat map size, the element layout and the label to generate a potential hazard heat map, asynchronously loads the potential hazard heat map and the drainage network monitoring data on the drainage network management model for display through coordinate conversion and mapping, and adjusts the transparency of the potential hazard heat map and the drainage network monitoring data.

[0011] Further, the drainage network management model construction module is specifically used for: The server obtains urban basic data including drainage network data and urban geographical data from the database in real time through SQL query statements; The drainage network data at least includes network basic data, network accessory facility data, water conservancy data, and rain and sewage mixing connection data; the urban geographical data at least includes administrative division data, network service area, remote sensing image, topographic map, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pumping station business data, and flood control emergency business data; The server constructs a three-dimensional drainage network management model through CIM technology and maps the latest urban basic data to the drainage network management model in real time; The drainage network monitoring data acquisition module is specifically used for: Each edge device distributed around the drainage network collects drainage network monitoring data in real time through a sensor group including at least a water level sensor, a flow velocity sensor, a flow meter, a water quality monitor, and a locator; the drainage network monitoring data at least includes water level, flow velocity, flow rate, turbidity, pH value, and pipe section location; Each edge device performs preprocessing on the collected drainage network monitoring data including at least null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association.

[0012] Further, the drainage network monitoring data uploading module is specifically used for: The edge device sets an upload period and compresses the preprocessed drainage network monitoring data within the upload period into compressed data through run-length encoding; The edge device sets a segment length, segments the compressed data based on the segment length to obtain a number of first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtains the current timestamp, and encrypts each of the third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploads the encrypted monitoring data to the server in real time through the TLS protocol.

[0013] Further, the early warning module is specifically used for: The server generates a warning notice that at least carries traffic data, water quality level, warning pipe section location, and warning time based on the hidden danger heat map, displays each of the warning notices through pre-associated large screen carousel or split screen, encrypts the warning notice into an encrypted notice, and pushes the encrypted notice to the management terminal in real time through the TLS protocol to perform warning operations; The specific method for encrypting the warning notice into an encrypted notice is as follows: Perform a hash calculation on the warning notice through the SHA-512 algorithm to obtain a first hash value, encrypt the warning notice and the first hash value through the RC2 algorithm to obtain first encrypted data, generate a first random string with a first length, add the first random string to a first specified position of the first encrypted data to obtain second encrypted data, encrypt the second encrypted data through the AES algorithm to obtain third encrypted data, generate a second random string with a second length, add the second random string to a second specified position of the third encrypted data to obtain fourth encrypted data, and encrypt the fourth encrypted data through the ECDSA algorithm to obtain an encrypted notice.

[0014] Furthermore, the drainage pipe network management log management module is specifically used for: The server generates a drainage pipe network management log in real time based on the drainage pipe network monitoring data, drainage pipe network hidden danger analysis results, hidden danger heat map, and warning notice; The server creates a pair of public key and private key, performs a hash calculation on the drainage pipe network management log through the SHA-384 algorithm to obtain a second hash value, encrypts the drainage pipe network management log and the second hash value through the private key to obtain first-level encrypted data, encrypts the public key through the IDEA algorithm to obtain a first-level key, maps the first-level key based on a preset first mapping rule to obtain a second-level key, encrypts the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, maps the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and backup on the encrypted log.

[0015] The advantages of the present invention are: 1. Obtain urban basic data including drainage network data and urban geographical data through the server. Based on the CIM technology, construct a three-dimensional drainage network management model based on the urban basic data. Then, the edge device collects drainage network monitoring data in real time through the sensor group and preprocesses it, encrypts the drainage network monitoring data into encrypted monitoring data and uploads it to the server. The server decrypts the received encrypted monitoring data to obtain the drainage network monitoring data, performs big data analysis on the drainage network monitoring data based on the load balancing technology and multi-thread technology, obtains the analysis result of drainage network hidden dangers, generates a hidden danger heat map based on the analysis result of drainage network hidden dangers, loads the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display, generates a warning notice based on the hidden danger heat map and executes the warning operation, generates a drainage network management log based on the drainage network monitoring data, the analysis result of drainage network hidden dangers, the hidden danger heat map and the warning notice, and encrypts and stores the drainage network management log; that is, collect the drainage network monitoring data in real time through the sensor group, automatically perform big data analysis based on the set upload period and upload it to the server, ensure the timeliness of obtaining and analyzing the drainage network monitoring data. The load balancing technology and multi-thread technology are combined in the big data analysis process to further ensure the analysis speed. The big data analysis can judge hidden dangers more accurately than the traditional method relying on the personal experience of staff, and also saves a large amount of manpower. Load the hidden danger heat map and the drainage network monitoring data on the pre-created drainage network management model. Through the drainage network management model, the hidden danger levels (flow data and water quality levels) of each area and the drainage network monitoring data can be intuitively viewed, and then the operation and maintenance decisions of the drainage network can be quickly made. Combined with the real-time push of the warning notice, ultimately greatly improve the efficiency, quality and convenience of drainage network management, and greatly reduce the labor cost of drainage network management.

[0016] 2. Obtain urban basic data from the database in real time through SQL query statements, and map the latest urban basic data to the drainage network management model in real time, so that the drainage network management model is always in the latest state, ensuring the reliability of urban drainage network management, and thus effectively improving the quality of drainage network management.

[0017] 3. By collecting drainage network data including at least network basic data, network ancillary facility data, water conservancy data and rain-sewage mixing data, and urban geographical data including at least administrative division data, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data and flood control emergency business data, greatly improve the comprehensiveness of urban basic data collection, greatly improve the reliability of urban drainage network management, and thus greatly improve the quality of urban drainage network management.

[0018] 4. By performing preprocessing on the collected drainage network monitoring data, including at least null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association, the data quality is guaranteed, facilitating subsequent big data analysis, and thus greatly improving the quality of urban drainage network management.

[0019] 5. By using run-length encoding to compress the preprocessed drainage network monitoring data within the upload period into compressed data, that is, converting consecutive repeated characters into a single character and the number of repetitions, the amount of data uploaded is effectively reduced, greatly improving the timeliness of data upload, and thus greatly improving the efficiency of drainage network management.

[0020] 6. By setting the segment length, segmenting the compressed data based on the segment length to obtain a number of first compressed sub-data, randomly assigning an initial vector to each first compressed sub-data, encrypting each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypting each second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculating the MAC value of each third compressed sub-data through the HMAC algorithm, obtaining the current timestamp, and encrypting each third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploading the encrypted monitoring data to the server in real time through the TLS protocol; by segmenting the compressed data, the memory occupation during the encryption process is effectively reduced, greatly improving the processing efficiency; by encrypting the first compressed sub-data through a symmetric encryption algorithm and the initial vector, it is ensured that even the same first compressed sub-data can generate different ciphertexts during multiple encryptions; the HMAC algorithm is a mechanism for message authentication using a hash function in cryptography, with higher security than ordinary hash calculations; subsequent timeliness verification can be performed through the timestamp, and the TLS protocol can prevent eavesdropping and tampering during data exchange. At least 8 security measures are taken before and after (segmentation, initial vector, symmetric encryption algorithm, first asymmetric encryption algorithm, HMAC algorithm, timestamp, second asymmetric encryption algorithm, TLS protocol), greatly improving the security of compressed data upload, and thus greatly improving the security of urban drainage network management.

[0021] 7. By setting the display forms of each flow data and water quality level, generating a hidden danger heat map based on the analysis results of drainage network hidden dangers and the display forms, asynchronously loading the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display, and subsequently, the urban drainage network can be intuitively managed through the drainage network management model, greatly improving the convenience and reliability of urban drainage network management.

[0022] 8. By generating warning notifications that at least carry traffic data, water quality levels, the locations of warning pipe sections, and warning times, it enables staff to quickly grasp important information and respond in a timely manner, greatly enhancing the timeliness of urban drainage pipe network management.

[0023] 9. By scrolling through the screen or displaying each warning notification in split screens and pushing the warning notifications to the management terminal in real time, it enables relevant staff to obtain and respond to the warning notifications in a timely manner, greatly enhancing the efficiency and convenience of drainage pipe network management.

[0024] 10. Calculate the first hash value by performing a hash calculation on the warning notification using the SHA-512 algorithm, encrypt the warning notification and the first hash value using the RC2 algorithm to obtain the first encrypted data, generate a first random string of the first length, add the first random string to the first specified position of the first encrypted data to obtain the second encrypted data, encrypt the second encrypted data using the AES algorithm to obtain the third encrypted data, generate a second random string of the second length, add the second random string to the second specified position of the third encrypted data to obtain the fourth encrypted data, encrypt the fourth encrypted data using the ECDSA algorithm to obtain the encrypted notification, and push the encrypted notification to the management terminal in real time through the TLS protocol to perform warning operations; subsequently, integrity verification can be performed through the first hash value, and the TLS protocol can prevent eavesdropping and tampering during data exchange. Without knowing the corresponding encryption algorithms or data transformation rules, it will be impossible to crack the encrypted notification. At least 11 security measures are taken before and after (SHA-512 algorithm, RC2 algorithm, first length, first random string, first specified position, AES algorithm, second length, second random string, second specified position, ECDSA algorithm, TLS protocol), greatly enhancing the security of warning notification pushing, avoiding the tampering of warning notifications, and thus greatly enhancing the security of urban drainage pipe network management.

[0025] 11. By creating a pair of public key and private key, calculating the hash value of the drainage network management log through the SHA-384 algorithm to obtain the second hash value, encrypting the drainage network management log and the second hash value through the private key to obtain the first-level encrypted data, encrypting the public key through the IDEA algorithm to obtain the first-level key, mapping the first-level key based on the preset first mapping rule to obtain the second-level key, encrypting the first-level encrypted data and the second-level key through the RSA algorithm to obtain the second-level encrypted data, mapping the second-level encrypted data based on the preset second mapping rule to obtain the third-level encrypted data, encrypting the third-level encrypted data through the ECDSA algorithm to obtain the encrypted log, and performing distributed storage and backup on the encrypted log; since the data encrypted by the private key can only be decrypted by the public key, and the public key undergoes multi-level encryption, it will be impossible to crack the encrypted log without knowing the corresponding encryption algorithm or data transformation rule. At least 8 security measures are taken before and after (public and private keys, SHA-384 algorithm, IDEA algorithm, first mapping rule, RSA algorithm, second mapping rule, ECDSA algorithm, distributed storage), which greatly improves the security of the drainage network management log storage, and thus greatly improves the security of the urban drainage network management.

[0026] 12. By taking security measures in each link of data upload, notification push, and log storage, and adopting different encryption schemes, it is possible to prevent relevant data from being stolen and tampered with, which greatly improves the security of the urban drainage network management. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below with reference to the accompanying drawings in conjunction with the embodiments.

[0028] Figure 1 It is a flowchart of a method for managing an urban drainage network based on a heat map according to the present invention.

[0029] Figure 2 It is a schematic structural diagram of a system for managing an urban drainage network based on a heat map according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The technical solution in the embodiments of this application has the following general idea: The sensor group is used to collect the monitoring data of the drainage pipe network in real time, and based on the set upload period, it is uploaded to the server for automatic big data analysis, ensuring the timeliness of obtaining and analyzing the monitoring data of the drainage pipe network. The load balancing technology and multi-thread technology are combined in the big data analysis process to further ensure the analysis speed. The big data analysis can more accurately judge potential hazards compared with the traditional method relying on the personal experience of staff, and also saves a large amount of manpower. The potential hazard heat map and the monitoring data of the drainage pipe network are loaded on the pre-created drainage pipe network management model, and through the drainage pipe network management model, the potential hazard levels and the monitoring data of the drainage pipe network in each area can be intuitively viewed. Combined with the real-time push of warning notifications, the efficiency, quality, and convenience of drainage pipe network management are improved, and the labor cost of drainage pipe network management is reduced; Security measures are taken in each link of data upload, notification push, and log storage, and different encryption schemes are adopted to prevent relevant data from being stolen and tampered with, so as to improve the security of urban drainage pipe network management.

[0031] Please refer to Figures 1 to 2 As shown in the figure, a preferred embodiment of a method for managing an urban drainage pipe network based on a heat map of the present invention includes the following steps: Step S1: The server obtains the urban basic data including the drainage pipe network data and the urban geographical data, and constructs a three-dimensional drainage pipe network management model based on the urban basic data through the CIM technology; Step S2: The edge device collects the monitoring data of the drainage pipe network in real time through the sensor group, and preprocesses the collected monitoring data of the drainage pipe network; Step S3: The edge device encrypts the monitoring data of the drainage pipe network into encrypted monitoring data, and uploads the encrypted monitoring data to the server; Step S4: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data to obtain the monitoring data of the drainage pipe network, and performs big data analysis on the monitoring data of the drainage pipe network based on the load balancing technology and the multi-thread technology to obtain the analysis result of the potential hazards of the drainage pipe network; Step S5: The server generates a potential hazard heat map based on the analysis result of the potential hazards of the drainage pipe network, and loads the potential hazard heat map and the monitoring data of the drainage pipe network on the drainage pipe network management model for display; Step S6: The server generates a warning notification based on the potential hazard heat map, and performs a warning operation based on the warning notification; Step S7: The server generates a drainage pipe network management log based on the monitoring data of the drainage pipe network, the analysis result of the potential hazards of the drainage pipe network, the potential hazard heat map, and the warning notification, and encrypts and stores the drainage pipe network management log; The specific content of step S1 is as follows: The server obtains urban basic data including drainage network data and urban geographic data in real time from the database through SQL query statements; The drainage network data at least includes network basic data, network accessory facility data, water conservancy data, and rain-sewage mixed connection data; the urban geographic data at least includes administrative division data, network service area, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data; The server constructs a three-dimensional drainage network management model through CIM technology and maps the latest urban basic data to the drainage network management model in real time; Obtaining urban basic data in real time from the database through SQL query statements and mapping the latest urban basic data to the drainage network management model in real time makes the drainage network management model always in the latest state, ensuring the reliability of urban drainage network management.

[0032] By collecting drainage network data at least including network basic data, network accessory facility data, water conservancy data, and rain-sewage mixed connection data, and urban geographic data at least including administrative division data, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data, the comprehensiveness of urban basic data collection is greatly improved, and further the reliability of urban drainage network management is greatly improved.

[0033] The specific content of step S2 is as follows: Each edge device distributed around the drainage network collects drainage network monitoring data in real time through a sensor group at least including a water level sensor, a flow velocity sensor, a flow meter, a water quality monitor, and a locator; the drainage network monitoring data at least includes water level, flow velocity, flow rate, turbidity, pH value, and pipe section position; Each edge device performs preprocessing on the collected drainage network monitoring data, including at least null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association; By performing preprocessing on the collected drainage network monitoring data, including at least null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association, the data quality is ensured, which is convenient for subsequent big data analysis.

[0034] The specific content of step S3 is as follows: The edge device sets an upload period and compresses the preprocessed drainage network monitoring data within the upload period into compressed data through run-length encoding; The drainage network monitoring data preprocessed during the upload period is compressed into compressed data through run-length encoding, that is, consecutive repeated characters are converted into the representation of a single character and the number of repetitions, effectively reducing the amount of data uploaded, and thus greatly improving the timeliness of data upload.

[0035] The edge device sets a segmentation length, segments the compressed data based on the segmentation length to obtain a number of first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtains the current timestamp, and encrypts each of the third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploads the encrypted monitoring data to the server in real time through the TLS protocol. Specifically, in implementation, the symmetric encryption algorithm can be selected as the AES algorithm, the first asymmetric encryption algorithm can be selected as the RSA algorithm, and the second asymmetric encryption algorithm can be selected as the DSA algorithm.

[0036] By setting a segmentation length, segmenting the compressed data based on the segmentation length to obtain a number of first compressed sub-data, randomly assigning an initial vector to each first compressed sub-data, encrypting each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypting each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculating the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtaining the current timestamp, and encrypting each of the third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploading the encrypted monitoring data to the server in real time through the TLS protocol; by segmenting the compressed data, the memory occupation during the encryption process is effectively reduced, and the processing efficiency is greatly improved; by encrypting the first compressed sub-data through a symmetric encryption algorithm and an initial vector, it is ensured that even the same first compressed sub-data can generate different ciphertexts during multiple encryptions; the HMAC algorithm is a mechanism that uses a hash function in cryptography for message authentication, which is more secure than ordinary hash calculations; subsequent aging verification can be performed through the timestamp, and the TLS protocol can prevent eavesdropping and tampering during data exchange. At least 8 security measures are taken before and after (segmentation, initial vector, symmetric encryption algorithm, first asymmetric encryption algorithm, HMAC algorithm, timestamp, second asymmetric encryption algorithm, TLS protocol), greatly improving the security of compressed data upload.

[0037] The specific step S4 is as follows: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through the second asymmetric encryption algorithm to obtain the third compressed sub-data, the initial vector, the MAC value and the time stamp. After performing timeliness verification through the time stamp, integrity verification is performed on each third compressed sub-data through each MAC value respectively. Each third compressed sub-data is decrypted through the first asymmetric encryption algorithm to obtain the second compressed sub-data. Each second compressed sub-data is decrypted through the symmetric encryption algorithm and the initial vector respectively to obtain the first compressed sub-data. Each of the first compressed sub-data is spliced into compressed data, and the compressed data is decompressed through run-length encoding to obtain the drainage network monitoring data; The server performs big data analysis on the drainage network monitoring data based on the load balancing technology and the multi-threading technology to obtain the drainage network hidden danger analysis result including at least the pipe section position, the flow data and the water quality grade.

[0038] For example, through big data analysis, if it is judged that the water level of a certain pipe section exceeds the historical highest water level, it is judged that the drainage pressure of the current pipe section is very high and there is a risk of pipe bursting; when the flow rate is too fast, it may be raining heavily currently, or there is a fault in a certain dam or water pipe; when the turbidity suddenly becomes high, it may be that the sewage mixed with mud flows into the drainage network. In specific implementation, the flow data can be set to five levels: "less than once in 1 year", "once in 1 - 2 years", "once in 2 - 3 years", "once in 3 - 5 years" and "greater than or equal to once in 5 years".

[0039] The specific content of step S5 is as follows: The server respectively sets the display forms of each flow data and water quality grade, generates a corresponding two-dimensional array based on the drainage network hidden danger analysis result and the display form, imports the two-dimensional array into the heat map generation tool, sets the heat map parameters including at least the resolution, the heat map size, the element layout and the label to generate the hidden danger heat map, and asynchronously loads the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display through coordinate transformation and mapping, and adjusts the transparency of the hidden danger heat map and the drainage network monitoring data. For example, different flow data are distinguished by different colors, and different water quality grades are distinguished by different graphics.

[0040] By setting the display forms of each flow data and water quality grade, generating the hidden danger heat map based on the drainage network hidden danger analysis result and the display form, and asynchronously loading the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display, the urban drainage network can be intuitively managed through the drainage network management model in the future, greatly improving the convenience and reliability of urban drainage network management.

[0041] In specific implementation, an aggregation algorithm can be applied to generate the hidden danger heat map, that is, the prepared data is input into the selected aggregation algorithm for calculation and processing, a hidden danger heat map is generated according to the output results of the aggregation algorithm, and the calculated hidden danger values ​​are mapped to colors, using color depth to represent different densities or weights.

[0042] The step S6 is specifically as follows: The server generates an early warning notification carrying at least flow data, water quality level, early warning pipe section location and early warning time based on the hidden danger heat map, displays each early warning notification through a pre-associated large-screen carousel or split-screen, encrypts the early warning notification into an encrypted notification, and pushes the encrypted notification to the management terminal in real time through the TLS protocol to execute the early warning operation; By generating early warning notifications that carry at least flow data, water quality level, location of the early warning pipe section, and early warning time, staff can quickly grasp important information and respond in a timely manner, greatly improving the timeliness of urban drainage network management.

[0043] In specific implementation, the monitoring data set in the hidden danger heat map can be converted and reduced, and feature selection technology can be used to reduce feature dimensions. A predictive heat map model can be constructed based on the extracted features and target prediction values. By intuitively displaying the relationships and trends between data, strong support can be provided for decision-making.

[0044] Each warning notification is displayed on a large screen in a carousel or split screen, and is pushed to the management terminal in real time, so that relevant staff can obtain and respond to the warning notification in a timely manner.

[0045] The step of encrypting the warning notification into an encrypted notification specifically includes: Perform hash calculation on the warning notification using the SHA-512 algorithm to obtain a first hash value, encrypt the warning notification and the first hash value using the RC2 algorithm to obtain first encrypted data, generate a first random string of a first length, add the first random string to a first designated position of the first encrypted data to obtain second encrypted data, encrypt the second encrypted data using the AES algorithm to obtain third encrypted data, generate a second random string of a second length, add the second random string to a second designated position of the third encrypted data to obtain fourth encrypted data, and encrypt the fourth encrypted data using the ECDSA algorithm to obtain an encrypted notification.

[0046] The first hash value is obtained by performing a hash calculation on the warning notice through the SHA-512 algorithm. The warning notice and the first hash value are encrypted through the RC2 algorithm to obtain the first encrypted data. A first random string with a first length is generated, and the first random string is added to a first specified position of the first encrypted data to obtain the second encrypted data. The second encrypted data is encrypted through the AES algorithm to obtain the third encrypted data. A second random string with a second length is generated, and the second random string is added to a second specified position of the third encrypted data to obtain the fourth encrypted data. The fourth encrypted data is encrypted through the ECDSA algorithm to obtain the encrypted notice, and the encrypted notice is pushed to the management terminal in real time through the TLS protocol to perform the warning operation; subsequently, integrity verification can be performed through the first hash value. The TLS protocol can prevent eavesdropping and tampering when exchanging data. Without knowing the corresponding encryption algorithm or data transformation rule, the encrypted notice cannot be cracked. At least 11 security measures are taken before and after (SHA-512 algorithm, RC2 algorithm, first length, first random string, first specified position, AES algorithm, second length, second random string, second specified position, ECDSA algorithm, TLS protocol), which greatly improves the security of the warning notice push, avoids the warning notice being tampered with, and thus greatly improves the security of urban drainage pipe network management.

[0047] The decryption process of the encrypted notice is as follows: The encrypted notice is decrypted through the ECDSA algorithm to obtain the fourth encrypted data. Based on the second length and the second specified position, the second random string is located in the fourth encrypted data, and the second random string is removed from the fourth encrypted data to obtain the third encrypted data. The third encrypted data is decrypted through the AES algorithm to obtain the second encrypted data. Based on the first length and the first specified position, the first random string is located in the second encrypted data, and the first random string is removed from the second encrypted data to obtain the first encrypted data. The first encrypted data is decrypted through the RC2 algorithm to obtain the warning notice and the first hash value, and the integrity of the warning notice is verified through the first hash value.

[0048] The specific step S7 is as follows: The server generates a drainage pipe network management log in real time based on the drainage pipe network monitoring data, the drainage pipe network hidden danger analysis result, the hidden danger heat map, and the warning notice; The server creates a pair of public and private keys, calculates the second hash value by performing a hash calculation on the drainage network management log through the SHA-384 algorithm, encrypts the drainage network management log and the second hash value through the private key to obtain first-level encrypted data, encrypts the public key through the IDEA algorithm to obtain a first-level key, maps the first-level key based on a preset first mapping rule to obtain a second-level key, encrypts the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, maps the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and backup on the encrypted log.

[0049] By creating a pair of public and private keys, calculating the second hash value by performing a hash calculation on the drainage network management log through the SHA-384 algorithm, encrypting the drainage network management log and the second hash value through the private key to obtain first-level encrypted data, encrypting the public key through the IDEA algorithm to obtain a first-level key, mapping the first-level key based on a preset first mapping rule to obtain a second-level key, encrypting the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, mapping the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypting the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performing distributed storage and backup on the encrypted log; since the data encrypted by the private key can only be decrypted by the public key, and the public key is encrypted at multiple levels, it will be impossible to crack the encrypted log without knowing the corresponding encryption algorithm or data transformation rule. At least 8 layers of security measures are taken before and after (public and private keys, SHA-384 algorithm, IDEA algorithm, first mapping rule, RSA algorithm, second mapping rule, ECDSA algorithm, distributed storage), which greatly improves the security of the storage of the drainage network management log.

[0050] By adopting different encryption schemes in each link of data upload, notification push, and log storage, it is avoided that relevant data is stolen and tampered with, further improving the security of urban drainage network management.

[0051] The decryption process of the encrypted log is as follows: Decrypt the encrypted log through the ECDSA algorithm to obtain the three - level encrypted data, map the three - level encrypted data based on the second mapping rule to obtain the two - level encrypted data, decrypt the two - level encrypted data through the RSA algorithm to obtain the one - level encrypted data and the two - level key, map the two - level key based on the first mapping rule to obtain the one - level key, decrypt the one - level key through the IDEA algorithm to obtain the public key, decrypt the one - level encrypted data through the public key to obtain the drainage network management log and the second hash value, and perform integrity verification on the drainage network management log through the second hash value.

[0052] A preferred embodiment of a city drainage network management system based on a heat map of the present invention includes the following modules: A drainage network management model construction module, configured to enable the server to obtain urban basic data including drainage network data and urban geographical data, and construct a three - dimensional drainage network management model based on the urban basic data through CIM technology; A drainage network monitoring data collection module, configured to enable edge devices to collect drainage network monitoring data in real time through a sensor group, and pre - process the collected drainage network monitoring data; A drainage network monitoring data uploading module, configured to enable edge devices to encrypt the drainage network monitoring data into encrypted monitoring data and upload the encrypted monitoring data to the server; A big data analysis module, configured to enable the server to receive the encrypted monitoring data in real time, decrypt the encrypted monitoring data to obtain the drainage network monitoring data, and perform big data analysis on the drainage network monitoring data based on load balancing technology and multi - threading technology to obtain a drainage network hidden danger analysis result; A hidden danger heat map generation and display module, configured to enable the server to generate a hidden danger heat map based on the drainage network hidden danger analysis result, and load the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display; An early warning module, configured to enable the server to generate an early warning notice based on the hidden danger heat map and perform an early warning operation based on the early warning notice; A drainage network management log management module, configured to enable the server to generate a drainage network management log based on the drainage network monitoring data, the drainage network hidden danger analysis result, the hidden danger heat map, and the early warning notice, and encrypt and store the drainage network management log; The drainage network management model construction module is specifically configured to: The server obtains urban basic data including drainage network data and urban geographical data from the database in real time through an SQL query statement; The drainage pipe network data at least includes pipe network basic data, pipe network accessory facility data, hydraulic data, and rain and sewage mixing connection data; the urban geographic data at least includes administrative division data, pipe network service area, remote sensing image, topographic map, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data; The server constructs a three-dimensional drainage pipe network management model through CIM technology, and maps the latest urban basic data to the drainage pipe network management model in real time; The urban basic data is obtained from the database in real time through SQL query statements, and the latest urban basic data is mapped to the drainage pipe network management model in real time, so that the drainage pipe network management model is always in the latest state, ensuring the reliability of urban drainage pipe network management.

[0053] By collecting drainage pipe network data that at least includes pipe network basic data, pipe network accessory facility data, hydraulic data, and rain and sewage mixing connection data, and urban geographic data that at least includes administrative division data, remote sensing image, topographic map, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data, the comprehensiveness of urban basic data collection is greatly improved, and thus the reliability of urban drainage pipe network management is greatly improved.

[0054] The drainage pipe network monitoring data acquisition module is specifically used for: Each edge device distributed around the drainage pipe network collects drainage pipe network monitoring data in real time through a sensor group that at least includes a water level sensor, a flow velocity sensor, a flow meter, a water quality monitor, and a locator; the drainage pipe network monitoring data at least includes water level, flow velocity, flow rate, turbidity, pH value, and pipe segment position; Each edge device performs preprocessing on the collected drainage pipe network monitoring data that at least includes null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association; By performing preprocessing on the collected drainage pipe network monitoring data that at least includes null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association, the data quality is ensured, which is convenient for subsequent big data analysis.

[0055] The drainage pipe network monitoring data uploading module is specifically used for: The edge device sets an uploading period, and compresses the preprocessed drainage pipe network monitoring data within the uploading period into compressed data through run-length encoding; By compressing the preprocessed drainage pipe network monitoring data within the uploading period into compressed data through run-length encoding, that is, converting continuously repeated characters into the representation of a single character and the number of repetitions, the amount of data uploaded is effectively reduced, and thus the timeliness of data uploading is greatly improved.

[0056] The edge device sets a segmentation length, segments the compressed data based on the segmentation length to obtain a number of first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtains the current timestamp, encrypts each of the third compressed sub-data, the initial vector, the MAC value and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploads the encrypted monitoring data to the server in real time through the TLS protocol. Specifically, when implemented, the symmetric encryption algorithm can be selected as the AES algorithm, the first asymmetric encryption algorithm can be selected as the RSA algorithm, and the second asymmetric encryption algorithm can be selected as the DSA algorithm.

[0057] By setting the segmentation length, segmenting the compressed data based on the segmentation length to obtain a number of first compressed sub-data, randomly assigning an initial vector to each first compressed sub-data, encrypting each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypting each of the second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data, calculating the MAC value of each of the third compressed sub-data through the HMAC algorithm, obtaining the current timestamp, encrypting each of the third compressed sub-data, the initial vector, the MAC value and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm, and uploading the encrypted monitoring data to the server in real time through the TLS protocol; by segmenting the compressed data, the memory occupation during the encryption process is effectively reduced, and the processing efficiency is greatly improved; by encrypting the first compressed sub-data through a symmetric encryption algorithm and an initial vector, it is ensured that even the same first compressed sub-data can generate different ciphertexts during multiple encryptions; the HMAC algorithm is a mechanism for message authentication using a hash function in cryptography, and it has higher security than ordinary hash calculations; subsequent timeliness verification can be performed through the timestamp, and the TLS protocol can prevent eavesdropping and tampering when exchanging data. At least eight security measures are taken before and after (segmentation, initial vector, symmetric encryption algorithm, first asymmetric encryption algorithm, HMAC algorithm, timestamp, second asymmetric encryption algorithm, TLS protocol), which greatly improves the security of uploading compressed data.

[0058] The big data analysis module is specifically used for: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through the second asymmetric encryption algorithm to obtain the third compressed sub-data, the initial vector, the MAC value, and the time stamp. After performing timeliness verification through the time stamp, integrity verification is performed on each third compressed sub-data through each MAC value. Each third compressed sub-data is decrypted through the first asymmetric encryption algorithm to obtain the second compressed sub-data. Each second compressed sub-data is decrypted through the symmetric encryption algorithm and the initial vector to obtain the first compressed sub-data. Each of the first compressed sub-data is concatenated into compressed data, and the compressed data is decompressed through run-length encoding to obtain the drainage pipe network monitoring data; The server performs big data analysis on the drainage pipe network monitoring data based on the load balancing technology and the multi-threading technology to obtain the drainage pipe network hidden danger analysis result including at least the pipe section location, the flow data, and the water quality grade.

[0059] For example, through big data analysis, if it is determined that the water level of a certain pipe section exceeds the historical highest water level, it is determined that the drainage pressure of the current pipe section is very high and there is a risk of pipe bursting; when the flow rate is too fast, it may be raining heavily currently, or there is a fault in a certain dam or water pipe; when the turbidity suddenly becomes high, it may be that sewage mixed with mud flows into the drainage pipe network. In specific implementation, the flow data can be set to five levels: "less than once in a year", "once in 1 - 2 years", "once in 2 - 3 years", "once in 3 - 5 years", and "greater than or equal to once in 5 years".

[0060] The hidden danger heat map generation and display module is specifically used for: The server respectively sets the display forms of each flow data and water quality grade, generates a corresponding two-dimensional array based on the drainage pipe network hidden danger analysis result and the display form, imports the two-dimensional array into a heat map generation tool, sets heat map parameters including at least the resolution, the heat map size, the element layout, and the label to generate a hidden danger heat map, and asynchronously loads the hidden danger heat map and the drainage pipe network monitoring data on the drainage pipe network management model through coordinate conversion and mapping for display, and adjusts the transparency of the hidden danger heat map and the drainage pipe network monitoring data. For example, different colors are used to distinguish different flow data, and different graphics are used to distinguish different water quality grades.

[0061] By setting the display forms of each flow data and water quality grade, generating a hidden danger heat map based on the drainage pipe network hidden danger analysis result and the display form, and asynchronously loading the hidden danger heat map and the drainage pipe network monitoring data on the drainage pipe network management model for display, the urban drainage pipe network can be intuitively managed through the drainage pipe network management model subsequently, greatly improving the convenience and reliability of the urban drainage pipe network management.

[0062] In specific implementation, an aggregation algorithm can be applied to generate the hidden danger heat map, that is, the prepared data is input into the selected aggregation algorithm for calculation and processing. According to the output result of the aggregation algorithm, a hidden danger heat map is generated, and the calculated hidden danger values are mapped to colors, and the color shades are used to represent different densities or weights.

[0063] The warning module is specifically used for: The server generates warning notifications carrying at least traffic data, water quality level, warning pipe section location, and warning time based on the hidden danger heat map, displays each warning notification through pre-associated large-screen carousel or split-screen display, encrypts the warning notification into an encrypted notification, and pushes the encrypted notification to the management terminal in real time through the TLS protocol to perform warning operations; By generating warning notifications carrying at least traffic data, water quality level, warning pipe section location, and warning time, the staff can quickly master important information and respond in a timely manner, greatly improving the timeliness of urban drainage pipe network management.

[0064] In specific implementation, the monitoring data set in the hidden danger heat map can be converted and standardized, and feature selection technology can be used to reduce the feature dimension. According to the extracted features and target prediction values, a prediction heat map model is constructed, and by intuitively displaying the relationship and trend between data, it provides strong support for decision-making.

[0065] By displaying each warning notification through large-screen carousel or split-screen display and pushing the warning notification to the management terminal in real time, relevant staff can obtain the warning notification and respond in a timely manner.

[0066] The specific method of encrypting the warning notification into an encrypted notification is as follows: The warning notification is hashed by the SHA-512 algorithm to obtain a first hash value, the warning notification and the first hash value are encrypted by the RC2 algorithm to obtain first encrypted data, a first random string with a first length is generated, the first random string is added to a first specified position of the first encrypted data to obtain second encrypted data, the second encrypted data is encrypted by the AES algorithm to obtain third encrypted data, a second random string with a second length is generated, the second random string is added to a second specified position of the third encrypted data to obtain fourth encrypted data, and the fourth encrypted data is encrypted by the ECDSA algorithm to obtain an encrypted notification.

[0067] The first hash value is obtained by performing a hash calculation on the warning notice through the SHA-512 algorithm. The warning notice and the first hash value are encrypted through the RC2 algorithm to obtain the first encrypted data. A first random string with a first length is generated, and the first random string is added to a first specified position of the first encrypted data to obtain the second encrypted data. The second encrypted data is encrypted through the AES algorithm to obtain the third encrypted data. A second random string with a second length is generated, and the second random string is added to a second specified position of the third encrypted data to obtain the fourth encrypted data. The fourth encrypted data is encrypted through the ECDSA algorithm to obtain the encrypted notice, and the encrypted notice is pushed to the management terminal in real time through the TLS protocol to perform the warning operation; subsequently, integrity verification can be performed through the first hash value, and the TLS protocol can prevent eavesdropping and tampering during data exchange. Without knowing the corresponding encryption algorithm or data transformation rule, the encrypted notice cannot be cracked. At least 11 security measures are taken before and after (SHA-512 algorithm, RC2 algorithm, first length, first random string, first specified position, AES algorithm, second length, second random string, second specified position, ECDSA algorithm, TLS protocol), which greatly improves the security of the warning notice push, avoids the warning notice from being tampered with, and thus greatly improves the security of urban drainage pipe network management.

[0068] The decryption process of the encrypted notice is as follows: The encrypted notice is decrypted through the ECDSA algorithm to obtain the fourth encrypted data. Based on the second length and the second specified position, the second random string is located in the fourth encrypted data, and the second random string is removed from the fourth encrypted data to obtain the third encrypted data. The third encrypted data is decrypted through the AES algorithm to obtain the second encrypted data. Based on the first length and the first specified position, the first random string is located in the second encrypted data, and the first random string is removed from the second encrypted data to obtain the first encrypted data. The first encrypted data is decrypted through the RC2 algorithm to obtain the warning notice and the first hash value, and the integrity of the warning notice is verified through the first hash value.

[0069] The drainage pipe network management log management module is specifically used for: The server generates a drainage pipe network management log in real time based on the drainage pipe network monitoring data, the drainage pipe network hidden danger analysis result, the hidden danger heat map, and the warning notice; The server creates a pair of public and private keys, calculates the second hash value by performing a hash calculation on the drainage network management log through the SHA-384 algorithm, encrypts the drainage network management log and the second hash value through the private key to obtain first-level encrypted data, encrypts the public key through the IDEA algorithm to obtain a first-level key, maps the first-level key based on a preset first mapping rule to obtain a second-level key, encrypts the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, maps the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and backup on the encrypted log.

[0070] By creating a pair of public and private keys, calculating the second hash value by performing a hash calculation on the drainage network management log through the SHA-384 algorithm, encrypting the drainage network management log and the second hash value through the private key to obtain first-level encrypted data, encrypting the public key through the IDEA algorithm to obtain a first-level key, mapping the first-level key based on a preset first mapping rule to obtain a second-level key, encrypting the first-level encrypted data and the second-level key through the RSA algorithm to obtain second-level encrypted data, mapping the second-level encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypting the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performing distributed storage and backup on the encrypted log; since the data encrypted by the private key can only be decrypted by the public key, and the public key undergoes multiple levels of encryption, it will be impossible to crack the encrypted log without knowing the corresponding encryption algorithm or data transformation rule. At least 8 layers of security measures are taken before and after (public and private keys, SHA-384 algorithm, IDEA algorithm, first mapping rule, RSA algorithm, second mapping rule, ECDSA algorithm, distributed storage), which greatly improves the security of the storage of the drainage network management log.

[0071] By adopting different encryption schemes in each link of data upload, notification push, and log storage, it is possible to prevent relevant data from being stolen and tampered with, further improving the security of urban drainage network management.

[0072] The decryption process of the encrypted log is as follows: Decrypt the encrypted log through the ECDSA algorithm to obtain the three - level encrypted data, map the three - level encrypted data based on the second mapping rule to obtain the two - level encrypted data, decrypt the two - level encrypted data through the RSA algorithm to obtain the first - level encrypted data and the second - level key, map the second - level key based on the first mapping rule to obtain the first - level key, decrypt the first - level key through the IDEA algorithm to obtain the public key, decrypt the first - level encrypted data through the public key to obtain the drainage network management log and the second hash value, and perform integrity verification on the drainage network management log through the second hash value.

[0073] In summary, the advantages of the present invention are as follows: 1. Obtain urban basic data including drainage network data and urban geographical data through the server, and build a three - dimensional drainage network management model based on the urban basic data through CIM technology; then the edge device collects drainage network monitoring data in real time through the sensor group and pre - processes it, encrypts the drainage network monitoring data into encrypted monitoring data and uploads it to the server; the server decrypts the received encrypted monitoring data to obtain the drainage network monitoring data, performs big data analysis on the drainage network monitoring data based on load - balancing technology and multi - threading technology to obtain the drainage network hidden danger analysis result, generates a hidden danger heat map based on the drainage network hidden danger analysis result, loads the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display, generates a warning notice based on the hidden danger heat map and executes a warning operation, generates a drainage network management log based on the drainage network monitoring data, drainage network hidden danger analysis result, hidden danger heat map and warning notice, and encrypts and stores the drainage network management log; that is, collect drainage network monitoring data in real time through the sensor group, upload it to the server automatically for big data analysis based on the set upload period, ensure the timeliness of obtaining and analyzing drainage network monitoring data, the load - balancing technology and multi - threading technology are combined in the big data analysis process to further ensure the analysis speed, the big data analysis can judge hidden dangers more accurately than the traditional method relying on the personal experience of staff, and also saves a large amount of manpower. Load the hidden danger heat map and the drainage network monitoring data on the pre - created drainage network management model, and the hidden danger level (flow data and water quality level) and drainage network monitoring data of each area can be intuitively viewed through the drainage network management model, so as to quickly make operation and maintenance decisions for the drainage network. Combined with the real - time push of warning notices, ultimately greatly improve the efficiency, quality and convenience of drainage network management, and greatly reduce the labor cost of drainage network management.

[0074] 2. Obtain urban basic data from the database in real time through SQL query statements, and map the latest urban basic data to the drainage pipe network management model in real time, so that the drainage pipe network management model is always in the latest state, ensuring the reliability of urban drainage pipe network management, and thus effectively improving the quality of drainage pipe network management.

[0075] 3. By collecting drainage pipe network data including at least pipe network basic data, pipe network ancillary facility data, water conservancy data, and rain and sewage mixing connection data, and urban geographic data including at least administrative division data, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage treatment plant business data, drainage household business data, pump station business data, and flood control emergency business data, the comprehensiveness of urban basic data collection is greatly improved, the reliability of urban drainage pipe network management is greatly improved, and thus the quality of urban drainage pipe network management is greatly improved.

[0076] 4. By performing preprocessing on the collected drainage pipe network monitoring data including at least null value processing, missing value processing, outlier processing, data standardization processing, data merging, and data association, the data quality is ensured, facilitating subsequent big data analysis, and thus greatly improving the quality of urban drainage pipe network management.

[0077] 5. Compress the preprocessed drainage pipe network monitoring data during the upload period into compressed data through run-length encoding, that is, convert consecutive repeated characters into the representation of a single character and the number of repetitions, effectively reducing the amount of data uploaded, greatly improving the timeliness of data upload, and thus greatly improving the efficiency of drainage pipe network management.

[0078] 6. By setting the segmentation length, segment the compressed data based on the segmentation length to obtain a number of first compressed sub-data. Randomly assign an initial vector to each first compressed sub-data. Encrypt each first compressed sub-data through a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data. Encrypt each second compressed sub-data through a first asymmetric encryption algorithm to obtain third compressed sub-data. Calculate the MAC value of each third compressed sub-data through the HMAC algorithm. Obtain the current timestamp. Encrypt each third compressed sub-data, the initial vector, the MAC value, and the timestamp into encrypted monitoring data through a second asymmetric encryption algorithm. Upload the encrypted monitoring data to the server in real time through the TLS protocol. By segmenting the compressed data, the memory occupation during the encryption process is effectively reduced, and the processing efficiency is greatly improved. By encrypting the first compressed sub-data through the symmetric encryption algorithm and the initial vector, it is ensured that even the same first compressed sub-data can generate different ciphertexts during multiple encryptions. The HMAC algorithm is a mechanism for message authentication using a hash function in cryptography, which is more secure than ordinary hash calculations. Subsequently, aging verification can be performed through the timestamp. The TLS protocol can prevent eavesdropping and tampering during data exchange. At least eight security measures are taken before and after (segmentation, initial vector, symmetric encryption algorithm, first asymmetric encryption algorithm, HMAC algorithm, timestamp, second asymmetric encryption algorithm, TLS protocol), which greatly improves the security of uploading compressed data, and thus greatly improves the security of urban drainage pipe network management.

[0079] 7. By setting the display forms of each flow data and water quality level, generate a hidden danger heat map based on the analysis results of drainage pipe network hidden dangers and the display forms. Asynchronously load the hidden danger heat map and the drainage pipe network monitoring data on the drainage pipe network management model for display. Subsequently, the urban drainage pipe network can be intuitively managed through the drainage pipe network management model, which greatly improves the convenience and reliability of urban drainage pipe network management.

[0080] 8. By generating at least an early warning notice carrying flow data, water quality level, early warning pipe section location, and early warning time, the staff can quickly master important information and respond in a timely manner, which greatly improves the timeliness of urban drainage pipe network management.

[0081] 9. By scrolling the large screen or displaying each early warning notice in a split screen, push the early warning notice to the management terminal in real time, so that the relevant staff can obtain the early warning notice and respond in a timely manner, which greatly improves the efficiency and convenience of drainage pipe network management.

[0082] 10. Calculate the hash value of the warning notice through the SHA-512 algorithm to obtain the first hash value. Encrypt the warning notice and the first hash value through the RC2 algorithm to obtain the first encrypted data. Generate a first random string with a first length, and add the first random string to the first specified position of the first encrypted data to obtain the second encrypted data. Encrypt the second encrypted data through the AES algorithm to obtain the third encrypted data. Generate a second random string with a second length, and add the second random string to the second specified position of the third encrypted data to obtain the fourth encrypted data. Encrypt the fourth encrypted data through the ECDSA algorithm to obtain the encrypted notice, and push the encrypted notice to the management terminal in real time through the TLS protocol to execute the warning operation. Subsequently, integrity verification can be performed through the first hash value. The TLS protocol can prevent eavesdropping and tampering when exchanging data. If the corresponding encryption algorithm or data transformation rule is not known, the encrypted notice cannot be cracked. At least 11 security measures are taken before and after (SHA-512 algorithm, RC2 algorithm, first length, first random string, first specified position, AES algorithm, second length, second random string, second specified position, ECDSA algorithm, TLS protocol), which greatly improves the security of the warning notice push, avoids the warning notice being tampered with, and thus greatly improves the security of urban drainage pipe network management.

[0083] 11. Create a pair of public and private keys. Calculate the hash value of the drainage pipe network management log through the SHA-384 algorithm to obtain the second hash value. Encrypt the drainage pipe network management log and the second hash value through the private key to obtain the first-level encrypted data. Encrypt the public key through the IDEA algorithm to obtain the first-level key. Map the first-level key based on the preset first mapping rule to obtain the second-level key. Encrypt the first-level encrypted data and the second-level key through the RSA algorithm to obtain the second-level encrypted data. Map the second-level encrypted data based on the preset second mapping rule to obtain the third-level encrypted data. Encrypt the third-level encrypted data through the ECDSA algorithm to obtain the encrypted log, and perform distributed storage and backup on the encrypted log. Since the data encrypted by the private key can only be decrypted by the public key, and the public key is encrypted at multiple levels, if the corresponding encryption algorithm or data transformation rule is not known, the encrypted log cannot be cracked. At least 8 security measures are taken before and after (public and private keys, SHA-384 algorithm, IDEA algorithm, first mapping rule, RSA algorithm, second mapping rule, ECDSA algorithm, distributed storage), which greatly improves the security of the drainage pipe network management log storage, and thus greatly improves the security of urban drainage pipe network management.

[0084] 12. Take security measures in each link of data upload, notice push, and log storage, and different encryption schemes are adopted to avoid relevant data being stolen and tampered with, which greatly improves the security of urban drainage pipe network management.

[0085] Although the specific embodiments of the present invention have been described above, those skilled in the art should understand that the specific embodiments we described are illustrative rather than used to limit the scope of the present invention. Equivalent modifications and variations made by those skilled in the art in accordance with the spirit of the present invention should be covered by the scope protected by the claims of the present invention.

Claims

1. A method for managing an urban drainage network based on a heat map, characterized in that: The steps include: Step S1: The server obtains basic urban data including drainage pipe network data and urban geographic data, and constructs a three-dimensional drainage pipe network management model based on the basic urban data by using CIM technology; Step S2: The edge device collects drainage network monitoring data in real time through the sensor group, and pre-processes the collected drainage network monitoring data; Step S3: The edge device encrypts the drainage network monitoring data into encrypted monitoring data, and uploads the encrypted monitoring data to a server; Step S4: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data to obtain drainage network monitoring data, and performs big data analysis on the drainage network monitoring data based on load balancing technology and multi-threading technology to obtain drainage network hidden danger analysis results; Step S5: The server generates a hidden danger heat map based on the hidden danger analysis result of the drainage network, and loads the hidden danger heat map and the drainage network monitoring data on the drainage network management model for display; Step S6: The server generates a warning notification based on the hidden danger heat map, and performs a warning operation based on the warning notification; Step S7: The server generates a drainage network management log based on the drainage network monitoring data, drainage network hidden danger analysis results, hidden danger heat map and early warning notification, and encrypts and stores the drainage network management log; The step S4 is specifically as follows: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through the second asymmetric encryption algorithm to obtain third compressed sub-data, an initial vector, a MAC value and a timestamp, performs a timeliness check through the timestamp, performs integrity check on each third compressed sub-data through each MAC value, decrypts each third compressed sub-data through the first asymmetric encryption algorithm to obtain second compressed sub-data, decrypts each second compressed sub-data through the symmetric encryption algorithm and the initial vector to obtain first compressed sub-data, splices each first compressed sub-data into compressed data, and decompresses the compressed data through run-length encoding to obtain drainage network monitoring data; The server performs big data analysis on the drainage network monitoring data based on load balancing technology and multi-threading technology to obtain drainage network hidden danger analysis results including at least pipe section location, flow data and water quality level; The step S5 is specifically as follows: The server sets the display forms of each flow data and water quality level respectively, generates a corresponding two-dimensional array based on the drainage network hidden danger analysis results and the display form, imports the two-dimensional array into the heat map generation tool, sets the heat map parameters including at least resolution, heat map size, element layout and label to generate a hidden danger heat map, and asynchronously loads the hidden danger heat map and drainage network monitoring data on the drainage network management model for display through coordinate conversion and mapping, and adjusts the transparency of the hidden danger heat map and drainage network monitoring data.

2. The urban drainage network management method based on heat map according to claim 1, characterized in that: The step S1 is specifically as follows: The server obtains urban basic data including drainage network data and urban geographic data from the database in real time through SQL query statements; The drainage network data at least includes basic network data, network ancillary facilities data, water conservancy data and rainwater and sewage mixed connection data; the urban geographic data at least includes administrative division data, network service area, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage plant business data, drainage household business data, pump station business data and flood control emergency business data; The server constructs a three-dimensional drainage network management model through CIM technology, and maps the latest urban basic data to the drainage network management model in real time; The step S2 is specifically as follows: Each edge device distributed around the drainage network collects drainage network monitoring data in real time through a sensor group including at least a water level sensor, a flow rate sensor, a flow meter, a water quality monitor, and a locator; the drainage network monitoring data includes at least water level, flow rate, flow, turbidity, pH value, and pipe section location; Each edge device performs preprocessing on the collected drainage network monitoring data, including at least null value processing, missing value processing, abnormal value processing, data standardization processing, data merging and data association.

3. The urban drainage network management method based on heat map according to claim 1, characterized in that: The step S3 is specifically as follows: The edge device sets an upload cycle, and compresses the drainage network monitoring data preprocessed in the upload cycle into compressed data through run-length encoding; The edge device sets a segment length, segments the compressed data based on the segment length to obtain several first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each of the first compressed sub-data by a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data by a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data by an HMAC algorithm, obtains the current timestamp, encrypts each of the third compressed sub-data, the initial vector, the MAC value and the timestamp by a second asymmetric encryption algorithm into encrypted monitoring data, and uploads the encrypted monitoring data to a server in real time through the TLS protocol.

4. The urban drainage network management method based on heat map according to claim 1, characterized in that: The step S6 is specifically as follows: The server generates an early warning notification carrying at least flow data, water quality level, early warning pipe section location and early warning time based on the hidden danger heat map, displays each early warning notification through a pre-associated large-screen carousel or split-screen, encrypts the early warning notification into an encrypted notification, and pushes the encrypted notification to the management terminal in real time through the TLS protocol to execute the early warning operation; The step of encrypting the warning notification into an encrypted notification specifically includes: Perform hash calculation on the warning notification using the SHA-512 algorithm to obtain a first hash value, encrypt the warning notification and the first hash value using the RC2 algorithm to obtain first encrypted data, generate a first random string of a first length, add the first random string to a first designated position of the first encrypted data to obtain second encrypted data, encrypt the second encrypted data using the AES algorithm to obtain third encrypted data, generate a second random string of a second length, add the second random string to a second designated position of the third encrypted data to obtain fourth encrypted data, and encrypt the fourth encrypted data using the ECDSA algorithm to obtain an encrypted notification.

5. The urban drainage network management method based on heat map according to claim 1, characterized in that: The step S7 is specifically as follows: The server generates a drainage network management log in real time based on the drainage network monitoring data, drainage network hidden danger analysis results, hidden danger heat map and early warning notification; The server creates a pair of public keys and private keys, performs hash calculation on the drainage network management log through the SHA-384 algorithm to obtain a second hash value, encrypts the drainage network management log and the second hash value through the private key to obtain primary encrypted data, encrypts the public key through the IDEA algorithm to obtain a primary key, maps the primary key based on a preset first mapping rule to obtain a secondary key, encrypts the primary encrypted data and the secondary key through the RSA algorithm to obtain secondary encrypted data, maps the secondary encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and back up of the encrypted log.

6. An urban drainage network management system based on a heat map, characterized in that: Includes the following modules: A drainage network management model building module is used for the server to obtain urban basic data including drainage network data and urban geographic data, and to build a three-dimensional drainage network management model based on the urban basic data through CIM technology; A drainage network monitoring data acquisition module is used for edge devices to collect drainage network monitoring data in real time through a sensor group, and to pre-process the collected drainage network monitoring data; A drainage network monitoring data uploading module is used for the edge device to encrypt the drainage network monitoring data into encrypted monitoring data, and upload the encrypted monitoring data to a server; A big data analysis module is used for the server to receive the encrypted monitoring data in real time, decrypt the encrypted monitoring data to obtain drainage network monitoring data, and perform big data analysis on the drainage network monitoring data based on load balancing technology and multi-threading technology to obtain drainage network hidden danger analysis results; A hidden danger heat map generation and display module is used for the server to generate a hidden danger heat map based on the hidden danger analysis results of the drainage network, and load the hidden danger heat map and drainage network monitoring data on the drainage network management model for display; An early warning module, used for the server to generate an early warning notification based on the hidden danger heat map, and perform an early warning operation based on the early warning notification; A drainage network management log management module is used for the server to generate a drainage network management log based on the drainage network monitoring data, drainage network hidden danger analysis results, hidden danger heat map and early warning notification, and encrypt and store the drainage network management log; The big data analysis module is specifically used for: The server receives the encrypted monitoring data in real time, decrypts the encrypted monitoring data through the second asymmetric encryption algorithm to obtain third compressed sub-data, an initial vector, a MAC value and a timestamp, performs a timeliness check through the timestamp, performs integrity check on each third compressed sub-data through each MAC value, decrypts each third compressed sub-data through the first asymmetric encryption algorithm to obtain second compressed sub-data, decrypts each second compressed sub-data through the symmetric encryption algorithm and the initial vector to obtain first compressed sub-data, splices each first compressed sub-data into compressed data, and decompresses the compressed data through run-length encoding to obtain drainage network monitoring data; The server performs big data analysis on the drainage network monitoring data based on load balancing technology and multi-threading technology to obtain drainage network hidden danger analysis results including at least pipe section location, flow data and water quality level; The hidden danger heat map generation and display module is specifically used for: The server sets the display forms of each flow data and water quality level respectively, generates a corresponding two-dimensional array based on the drainage network hidden danger analysis results and the display form, imports the two-dimensional array into the heat map generation tool, sets the heat map parameters including at least resolution, heat map size, element layout and label to generate a hidden danger heat map, and asynchronously loads the hidden danger heat map and drainage network monitoring data on the drainage network management model for display through coordinate conversion and mapping, and adjusts the transparency of the hidden danger heat map and drainage network monitoring data.

7. The urban drainage pipe network management system based on heat map according to claim 6, characterized in that: The drainage network management model construction module is specifically used for: The server obtains urban basic data including drainage network data and urban geographic data from the database in real time through SQL query statements; The drainage network data at least includes basic network data, network ancillary facilities data, water conservancy data and rainwater and sewage mixed connection data; the urban geographic data at least includes administrative division data, network service area, remote sensing images, topographic maps, vegetation data, water system data, mountain data, sewage plant business data, drainage household business data, pump station business data and flood control emergency business data; The server constructs a three-dimensional drainage network management model through CIM technology, and maps the latest urban basic data to the drainage network management model in real time; The drainage network monitoring data acquisition module is specifically used for: Each edge device distributed around the drainage network collects drainage network monitoring data in real time through a sensor group including at least a water level sensor, a flow rate sensor, a flow meter, a water quality monitor, and a locator; the drainage network monitoring data includes at least water level, flow rate, flow, turbidity, pH value, and pipe section location; Each edge device performs preprocessing on the collected drainage network monitoring data, including at least null value processing, missing value processing, abnormal value processing, data standardization processing, data merging and data association.

8. The urban drainage pipe network management system based on thermal map according to claim 6, characterized in that: The drainage network monitoring data uploading module is specifically used for: The edge device sets an upload cycle, and compresses the drainage network monitoring data preprocessed in the upload cycle into compressed data through run-length encoding; The edge device sets a segment length, segments the compressed data based on the segment length to obtain several first compressed sub-data, randomly assigns an initial vector to each of the first compressed sub-data, encrypts each of the first compressed sub-data by a symmetric encryption algorithm and the initial vector to obtain second compressed sub-data, encrypts each of the second compressed sub-data by a first asymmetric encryption algorithm to obtain third compressed sub-data, calculates the MAC value of each of the third compressed sub-data by an HMAC algorithm, obtains the current timestamp, encrypts each of the third compressed sub-data, the initial vector, the MAC value and the timestamp by a second asymmetric encryption algorithm into encrypted monitoring data, and uploads the encrypted monitoring data to a server in real time through the TLS protocol.

9. The urban drainage pipe network management system based on thermal map according to claim 6, characterized in that: The early warning module is specifically used for: The server generates an early warning notification carrying at least flow data, water quality level, early warning pipe section location and early warning time based on the hidden danger heat map, displays each early warning notification through a pre-associated large-screen carousel or split-screen, encrypts the early warning notification into an encrypted notification, and pushes the encrypted notification to the management terminal in real time through the TLS protocol to execute the early warning operation; The step of encrypting the warning notification into an encrypted notification specifically includes: Perform hash calculation on the warning notification using the SHA-512 algorithm to obtain a first hash value, encrypt the warning notification and the first hash value using the RC2 algorithm to obtain first encrypted data, generate a first random string of a first length, add the first random string to a first designated position of the first encrypted data to obtain second encrypted data, encrypt the second encrypted data using the AES algorithm to obtain third encrypted data, generate a second random string of a second length, add the second random string to a second designated position of the third encrypted data to obtain fourth encrypted data, and encrypt the fourth encrypted data using the ECDSA algorithm to obtain an encrypted notification.

10. The urban drainage pipe network management system based on heat map according to claim 6, characterized in that: The drainage network management log management module is specifically used for: The server generates a drainage network management log in real time based on the drainage network monitoring data, drainage network hidden danger analysis results, hidden danger heat map and early warning notification; The server creates a pair of public keys and private keys, performs hash calculation on the drainage network management log through the SHA-384 algorithm to obtain a second hash value, encrypts the drainage network management log and the second hash value through the private key to obtain primary encrypted data, encrypts the public key through the IDEA algorithm to obtain a primary key, maps the primary key based on a preset first mapping rule to obtain a secondary key, encrypts the primary encrypted data and the secondary key through the RSA algorithm to obtain secondary encrypted data, maps the secondary encrypted data based on a preset second mapping rule to obtain third-level encrypted data, encrypts the third-level encrypted data through the ECDSA algorithm to obtain an encrypted log, and performs distributed storage and back up of the encrypted log.

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