Sponge city intelligent monitoring system and method thereof

Abstract

The invention discloses a sponge city intelligent monitoring system and method, and relates to the technical field of city monitoring, and the method comprises the steps: collecting weather data and city operation data through a sensor, and carrying out the preprocessing; constructing an intelligent decision algorithm model based on the weather data and analyzing urban operation data; formulating an optimal drainage strategy according to the analysis result; and analyzing current city operation data in real time, and automatically adjusting parameters of the intelligent decision algorithm model. According to the invention, real-time and comprehensive ponding condition monitoring and intelligent decision making are realized, the occurrence frequency and severity of urban inland inundation can be effectively reduced, urban road and low-lying land ponding can be timely discharged, the travel safety of citizens and normal operation of urban infrastructures are ensured, and continuous urban operation data monitoring and dynamic adjustment of an intelligent decision making model are realized. And a city has stronger adaptive capacity when facing various emergencies or long-term climate changes.

Description

Technical Field

[0001] The present invention relates to the field of urban monitoring technology, and in particular to a sponge city smart monitoring system and method thereof. Background Art

[0002] With the acceleration of urbanization, the urban population has increased dramatically, and the scale of cities has continued to expand. The drainage and water resource management model of traditional cities faces many severe challenges. In the face of heavy rain and extreme weather, urban waterlogging occurs frequently, and a large amount of accumulated water seriously affects the travel safety and daily life of citizens. At the same time, it also causes great damage to urban infrastructure, commercial activities and the ecological environment. In drought periods, cities may face the dilemma of water shortage. The tight water use restricts industrial production and inconveniences in residents' lives. On the one hand, in the past, cities' monitoring of weather data was often relatively single, focusing only on a few key indicators of precipitation, and lacking comprehensive collection and in-depth analysis of multi-dimensional meteorological information such as temperature, humidity, wind speed and wind direction. This one-sidedness makes it difficult for urban managers to fully predict the weather. The impact of changes on all aspects of urban operation makes it impossible to formulate effective response strategies in advance. Abnormal changes in temperature and humidity may affect the fluctuation of urban water demand. If not detected in advance, it is very easy to lead to insufficient or waste water supply. On the other hand, the collection and processing of urban operation data are also insufficient. Under the traditional method, the feedback of drainage system operation data and urban waterlogging data is delayed, and it is difficult to reflect the real-time status of the urban drainage system in time. The problems of drainage network blockage and poor drainage cannot be discovered and solved in time, resulting in a high risk of urban flooding. Moreover, the monitoring of urban water demand data lacks refined management and cannot accurately adapt to the actual water demand in different regions and at different times. It is not conducive to the rational allocation of water resources, and it is difficult to ensure the stability and reliability of urban water supply.

[0003] However, the common solutions currently available have many shortcomings, including: the existing technology lacks real-time analysis and automatic adjustment mechanisms; once a drainage strategy is formulated, it is difficult to flexibly change it; even if unexpected situations occur during urban operations, the strategy cannot be optimized in a timely manner; the existing drainage strategy is extensive, and the operation of drainage facilities lacks refined regulation, usually just opening or closing drainage pumps and gates in a fixed mode, without considering the differences in waterlogging levels in different areas and the uneven distribution of drainage pressure, which can easily cause serious local waterlogging or waste of drainage resources. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above-mentioned problems existing in the existing sponge city smart monitoring system and method, the present invention is proposed.

[0006] Therefore, the purpose of the present invention is to provide a sponge city intelligent monitoring system and method, which is suitable for solving the problems that the existing drainage strategy is extensive and the operation of drainage facilities lacks refined regulation. Usually, drainage pumps and gates are only opened or closed according to a fixed mode, without considering the differences in water accumulation in different areas and the uneven distribution of drainage pressure, which can easily cause serious local waterlogging or waste of drainage resources.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In the first aspect, an embodiment of the present invention provides a smart monitoring method for a sponge city, which includes using sensors to collect weather data and urban operation data and perform preprocessing; constructing an intelligent decision-making algorithm model based on the weather data and analyzing the urban operation data; formulating an optimal drainage strategy based on the analysis results; analyzing the current urban operation data in real time, and automatically adjusting the parameters of the intelligent decision-making algorithm model.

[0009] As a preferred solution of the sponge city smart monitoring method described in the present invention, the above-mentioned sensors include meteorological sensors, drainage system sensors and urban operation-related sensors; the weather data include precipitation data, temperature data, humidity data, wind speed and wind direction data; the urban operation data include drainage system operation data, urban water demand data and urban waterlogging data; the drainage strategy includes drainage facility operation strategy, water resource retention and reuse strategy and regional drainage priority strategy.

[0010] As a preferred solution of the sponge city smart monitoring method described in the present invention, the specific steps of constructing the intelligent decision-making algorithm model are as follows: extracting features based on the collected weather data; constructing an intelligent decision-making algorithm model based on a neural network and analyzing the city operation data; using a machine learning algorithm to further analyze the city operation data; evaluating the model and adjusting the model structure or parameters according to the evaluation results.

[0011] As a preferred solution of the sponge city smart monitoring method of the present invention, the specific formula for analyzing the city operation data is as follows:

[0012]

[0013] Among them, Z is the comprehensive analysis result of urban operation data; x ij is the city operation data collected by sensor j at a specific time; is a maximum value determined for each specific type of sensor j;jl is the influence coefficient of sensor j on urban operation characteristic l.

[0014] As a preferred solution of the sponge city smart monitoring method described in the present invention, the specific situation of the comprehensive analysis result of the city operation data is as follows: when the comprehensive analysis result Z of the city operation data is greater than the first threshold value, it indicates that the city operation status is good and the drainage system pressure is low; when the comprehensive analysis result Z of the city operation data is equal to the first threshold value, it indicates that historical data shows that the city has begun to have obvious water accumulation, the drainage system is under pressure, and the city operation status has begun to have problems. The drainage strategy should focus on drainage while taking into account the retention of water resources. It is necessary to more actively adjust the drainage facilities to deal with the water accumulation; when the comprehensive analysis result Z of the city operation data is less than the first threshold value, it indicates that the city operation status is poor, an emergency has occurred, and an emergency drainage strategy needs to be adopted.

[0015] As a preferred solution of the sponge city smart monitoring method of the present invention, the specific formula for automatically adjusting the parameters of the intelligent decision-making algorithm model is as follows:

[0016]

[0017] Where P is the probability of automatically adjusting model parameters; m is the number of sensor types; n is the number of urban operation characteristics; S ij is the comprehensive data about urban operation characteristic j collected by sensor i within a specific time interval; α is a very small positive number; t is the adjustment coefficient.

[0018] As a preferred solution of the sponge city smart monitoring method described in the present invention, the specific situation of the automatic adjustment model parameter probability is as follows: when the automatic adjustment model parameter probability is greater than the second threshold value, it indicates that the city is in good operation, drainage is smooth, there is no water accumulation, and the urban water supply and demand balance is good; when the automatic adjustment model parameter probability is less than the second threshold value, it indicates that there is a problem in the city operation, reflecting that there are problems in many aspects of the city operation, the drainage system is blocked, the water accumulation is serious, and the urban water demand is tight.

[0019] On the second aspect, in order to further solve the above-mentioned technical problems, the embodiments of the present invention provide a sponge city smart monitoring system, which includes: a data acquisition module, used to collect weather data and urban operation data and perform preprocessing; a model construction module, used to construct an intelligent decision-making algorithm model and analyze the urban operation data; a strategy formulation module, used to formulate the best drainage strategy according to the analysis results; a model optimization module, used to automatically adjust the parameters of the intelligent decision-making algorithm model.

[0020] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of a sponge city smart monitoring method as described in the first aspect of the present invention is implemented.

[0021] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of a sponge city smart monitoring method as described in the first aspect of the present invention is implemented.

[0022] The beneficial effects of the present invention are as follows: the real-time and comprehensive monitoring of waterlogging and intelligent decision-making of the present invention enable the city to respond quickly when facing rainstorms and extreme weather. The drainage system is started in advance and accurately regulated to quickly drain the accumulated water, effectively reducing the frequency and severity of urban waterlogging. Meteorological sensors warn of the coming of rainstorms in advance, and the intelligent decision-making algorithm model estimates the waterlogging area based on precipitation intensity, wind speed and direction, and allocates drainage resources to key prevention areas in advance to ensure that waterlogging in urban roads and low-lying areas is removed in time, ensuring the safety of citizens' travel and the normal operation of urban infrastructure. Continuous urban operation data monitoring and dynamic adjustment of intelligent decision-making models enable cities to have stronger adaptability when facing various emergencies or long-term climate changes. Whether it is short-term strong winds and rainstorms, sudden drainage pipe network failures, or long-term drought trends, changes in water demand caused by urban expansion, the system can detect and adjust strategies in time to ensure the stable operation of key links in urban water resource circulation and drainage systems, and maintain the normal production and living order of the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0024] Figure 1 This is a flow chart for implementing the present invention in Example 1. DETAILED DESCRIPTION

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0027] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0028] Example 1

[0029] Reference Figure 1 , which is the first embodiment of the present invention, and provides a sponge city smart monitoring method, comprising the following steps:

[0030] S1: Use sensors to collect weather data and urban operation data and perform preprocessing.

[0031] Preferably, Figure 1 The figure shows the implementation process of the present invention. First, sensors are used to collect weather data and urban operation data and perform preprocessing. Then, an intelligent decision-making algorithm model is constructed based on the weather data and the urban operation data is analyzed. Subsequently, the best drainage strategy is formulated according to the analysis results. Finally, the current urban operation data is analyzed in real time, and the parameters of the intelligent decision-making algorithm model are automatically adjusted.

[0032] Furthermore, the above-mentioned sensors include meteorological sensors, drainage system sensors and urban operation related sensors.

[0033] Furthermore, the weather data includes precipitation data, temperature data, humidity data, and wind speed and direction data.

[0034] Furthermore, the urban operation data includes drainage system operation data, urban water demand data and urban waterlogging data.

[0035] Specifically, preprocessing ensures the quality and consistency of data by performing real-time preprocessing of weather data and urban operation data on data nodes, including data cleaning, noise reduction and standardization.

[0036] S2: Build an intelligent decision-making algorithm model based on weather data and analyze urban operation data.

[0037] Specifically, the steps for building an intelligent decision-making algorithm model are as follows: Extract features based on the collected weather data.

[0038] Build an intelligent decision-making algorithm model based on neural networks and analyze urban operation data.

[0039] Use machine learning algorithms to further analyze urban operation data.

[0040] Evaluate the model and adjust the model structure or parameters based on the evaluation results.

[0041] Specifically, the specific formula for analyzing urban operation data is as follows:

[0042]

[0043] Among them, Z is the comprehensive analysis result of urban operation data; x ij is the city operation data collected by sensor j at a specific time; is a maximum value determined for each specific type of sensor j; jl is the influence coefficient of sensor j on urban operation characteristic l.

[0044] Preferably, breaking the limitations of traditional empirical decision-making and conducting scientific analysis based on data-driven can more objectively evaluate the city's operating status and predict potential risks in advance. By continuously analyzing real-time urban operation data and automatically adjusting model parameters, decisions can always adapt to the dynamic changes of the city, improve the accuracy and timeliness of decisions, and adjust water supply strategies in time during peak water use periods to ensure that residents' daily water use is not affected.

[0045] S3: Develop the best drainage strategy based on the analysis results.

[0046] Furthermore, the drainage strategy includes drainage facility operation strategy, water resource retention and reuse strategy, and regional drainage priority strategy.

[0047] Preferably, the specific situation of the comprehensive analysis result of the city operation data is as follows: when the comprehensive analysis result Z of the city operation data is greater than the first threshold, it indicates that the city operation state is good and the drainage system pressure is low.

[0048] When the comprehensive analysis result Z of urban operation data is equal to the first threshold, it means that historical data shows that the city has begun to experience obvious waterlogging, the drainage system is under pressure, and problems have begun to appear in the city's operation status. The drainage strategy should focus on drainage while taking into account the retention of water resources. It is necessary to more actively adjust the drainage facilities to deal with the waterlogging.

[0049] When the comprehensive analysis result Z of the urban operation data is less than the first threshold, it indicates that the urban operation status is poor, an emergency has occurred, and an emergency drainage strategy needs to be adopted.

[0050] Furthermore, the first threshold is determined based on historical data and statistical analysis, urban infrastructure characteristics and drainage capacity, and the impact of different seasons and weather patterns.

[0051] Preferably, the drainage facility operation strategy realizes refined regulation, improves drainage efficiency, reduces local waterlogging, ensures the normal operation of urban transportation and infrastructure, and accurately controls the number of drainage pumps opened and the operating power according to the real-time waterlogging depth and drainage network flow conditions to quickly drain the accumulated water.

[0052] The water resource retention and reuse strategy promotes the recycling of water resources, alleviates urban water use pressure, improves the overall utilization efficiency of water resources, achieves sustainable development, collects rainwater in the rainy season for urban greening irrigation, and reduces dependence on municipal water supply.

[0053] The regional drainage priority strategy ensures priority drainage in key areas when flood disasters occur, reduces the impact of disasters on the core functions of the city, and protects the safety of citizens' lives and property and the basic operation of the city.

[0054] S4: Analyze the current city operation data in real time and automatically adjust the parameters of the intelligent decision-making algorithm model.

[0055] Preferably, the specific formula for automatically adjusting the parameters of the intelligent decision-making algorithm model is as follows:

[0056]

[0057] Where P is the probability of automatically adjusting model parameters; m is the number of sensor types; n is the number of urban operation characteristics; S ij is the comprehensive data about urban operation characteristic j collected by sensor i within a specific time interval; α is a very small positive number; t is the adjustment coefficient.

[0058] Specifically, the specific situation of the probability of automatically adjusting the model parameters is as follows: when the probability of automatically adjusting the model parameters is greater than the second threshold, it indicates that the city is operating well, drainage is smooth, there is no water accumulation, and the urban water supply and demand balance is good.

[0059] When the probability of automatically adjusting the model parameters is less than the second threshold, it indicates that there is a problem in the city's operation, reflecting that there are problems in many aspects of the city's operation, the drainage system is blocked, the waterlogging is serious, and the city's water demand is tight.

[0060] Furthermore, the second threshold needs to be determined based on experience, historical data, and specific application scenarios and target adjustments.

[0061] This embodiment also provides a sponge city smart monitoring system, including: a data acquisition module, used to collect weather data and urban operation data and perform preprocessing; a model construction module, used to build an intelligent decision-making algorithm model and analyze the urban operation data; a strategy formulation module, used to formulate the best drainage strategy based on the analysis results; a model optimization module, used to automatically adjust the parameters of the intelligent decision-making algorithm model.

[0062] This embodiment also provides a computer device, which is applicable to a sponge city smart monitoring method, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a sponge city smart monitoring method proposed in the above embodiment.

[0063] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0064] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a method for smart monitoring of a sponge city as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, disk or optical disk.

[0065] In summary, the real-time and comprehensive waterlogging monitoring and intelligent decision-making of the present invention enable the city to respond quickly when facing rainstorms and extreme weather. The drainage system can be started in advance and accurately regulated to quickly drain the accumulated water, effectively reducing the frequency and severity of urban waterlogging. Meteorological sensors warn of the coming of rainstorms in advance, and the intelligent decision-making algorithm model estimates the waterlogging area based on precipitation intensity, wind speed and direction, and allocates drainage resources to key prevention areas in advance to ensure that waterlogging in urban roads and low-lying areas is removed in time, ensuring the safety of citizens' travel and the normal operation of urban infrastructure. Continuous urban operation data monitoring and dynamic adjustment of intelligent decision-making models enable cities to have stronger adaptability when facing various emergencies or long-term climate changes. Whether it is short-term strong winds and rainstorms, sudden drainage pipe network failures, or long-term drought trends, changes in water demand caused by urban expansion, the system can detect and adjust strategies in time to ensure the stable operation of key links in the urban water resource cycle and drainage system, and maintain the normal production and living order of the city.

[0066] Example 2

[0067] Referring to Tables 1 to 3, the second embodiment of the present invention is shown. This embodiment is different from the first embodiment in that, in order to verify its beneficial effects, operating data and related instructions of the present invention in an actual environment are provided.

[0068] Tables 1 to 3 show the meteorological data, drainage system operation data and urban water use data collected in this example, and are comparison tables comparing the prior art with the present invention.

[0069] Table 1 Comparison of meteorological data

[0070] Compare Projects Existing technical data Technical data of the present invention Precipitation data measurement accuracy (mm / h) ±2.0 ±0.5 Temperature data accuracy (℃) ±0.5 ±0.2 Humidity data accuracy (%RH) ±5 ±3 Wind speed and direction data accuracy (m / s) ±0.5 ±0.3

[0071] Table 2 Drainage system operation data comparison table

[0072] Compare Projects Existing technical data Technical data of the present invention Drainage network pressure measurement accuracy (MPa) ±0.05 ±0.01 <![CDATA[Drainage flow measurement accuracy (m 3 / s)]]> ±0.2 ±0.1 Number of waterlogging incidents (times / year) 5 1 Number of reports of drainage network blockage (times / year) 8 2 Number of pump station failures (times / year) 3 0.5

[0073] Table 3 Comparison of urban water use data

[0074] Compare Projects Existing technical data Technical data of the present invention <![CDATA[Water flow monitoring accuracy (m 3 / h)]]> ±0.1 ±0.05 Water resource utilization rate (%) 30 60 Water shortage days (days / year) 15 5 Proportion of rainwater in non-drinking water use (%) 5 30 Industrial downtime due to water shortage (hours / year) 100 20

[0075] As can be seen from the above table, the present invention demonstrates outstanding innovation and advantages in meteorological data collection, drainage system operation management, and urban water use management. It provides strong technical support for sponge city construction, effectively solves many problems existing in the existing technology, and has extremely high value for promotion and application.

[0076] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A sponge city smart monitoring method, characterized by: include: Use sensors to collect weather data and urban operation data and pre-process them; Building an intelligent decision-making algorithm model based on the weather data and analyzing the city operation data; formulating an optimal drainage strategy based on the analysis results; Analyze current city operation data in real time and automatically adjust the parameters of the intelligent decision-making algorithm model.

2. The sponge city smart monitoring method according to claim 1, characterized in that: The above-mentioned sensors include meteorological sensors, drainage system sensors and city operation related sensors; The weather data includes precipitation data, temperature data, humidity data, and wind speed and direction data; The urban operation data includes drainage system operation data, urban water demand data and urban waterlogging situation data; The drainage strategy includes drainage facility operation strategy, water resource retention and reuse strategy and regional drainage priority strategy.

3. The sponge city smart monitoring method according to claim 1, characterized in that: The specific steps of constructing the intelligent decision-making algorithm model are as follows: Extract features based on the collected weather data; Build intelligent decision-making algorithm models based on neural networks and analyze urban operation data; Use machine learning algorithms to further analyze city operation data; Evaluate the model and adjust the model structure or parameters based on the evaluation results.

4. The sponge city smart monitoring method according to claim 3, characterized in that: The specific formula for analyzing the urban operation data is as follows: Among them, Z is the comprehensive analysis result of urban operation data; x ij is the city operation data collected by sensor j at a specific time; is a maximum value determined for each specific type of sensor j; jl is the influence coefficient of sensor j on urban operation characteristic l.

5. The sponge city smart monitoring method according to claim 4, characterized in that: The specific results of the comprehensive analysis of the urban operation data are as follows: When the comprehensive analysis result Z of the city operation data is greater than the first threshold, it indicates that the city operation is in good condition and the drainage system pressure is low; When the comprehensive analysis result Z of the urban operation data is equal to the first threshold, it means that the historical data shows that the city has begun to experience obvious waterlogging, the drainage system is under pressure, and the urban operation status has begun to have problems. The drainage strategy should focus on drainage while taking into account the retention of water resources. It is necessary to more actively adjust the drainage facilities to deal with the waterlogging. When the comprehensive analysis result Z of the urban operation data is less than the first threshold, it indicates that the urban operation status is poor, an emergency has occurred, and an emergency drainage strategy needs to be adopted.

6. The sponge city smart monitoring method according to claim 1, characterized in that: The specific formula for automatically adjusting the parameters of the intelligent decision-making algorithm model is as follows: Where P is the probability of automatically adjusting model parameters; m is the number of sensor types; n is the number of urban operation characteristics; S ij is the comprehensive data about urban operation characteristic j collected by sensor i within a specific time interval; α is a very small positive number; t is the adjustment coefficient.

7. The sponge city smart monitoring method according to claim 6, characterized in that: The specific situation of the automatic adjustment of the model parameter probability is as follows: When the probability of automatically adjusting the model parameters is greater than the second threshold, it indicates that the city is in good operation, drainage is smooth, there is no water accumulation, and the urban water supply and demand are well balanced; When the probability of automatically adjusting the model parameters is less than the second threshold, it indicates that there is a problem in the city's operation, reflecting that there are problems in many aspects of the city's operation, the drainage system is blocked, the waterlogging is serious, and the city's water demand is tight.

8. A sponge city smart monitoring system, based on a sponge city smart monitoring method according to any one of claims 1 to 7, characterized in that: include, Data collection module, used to collect weather data and urban operation data and perform pre-processing; Model building module, used to build intelligent decision-making algorithm models and analyze urban operation data; Strategy formulation module, used to formulate the best drainage strategy based on the analysis results; Model optimization module, used to automatically adjust the parameters of the intelligent decision-making algorithm model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a sponge city smart monitoring method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a sponge city smart monitoring method described in any one of claims 1 to 7 are implemented.

Images