Monitoring management method and system for smart sponge city

Abstract

The invention discloses a monitoring management method and system for a smart sponge city, and relates to the technical field of smart city management, and the method comprises the steps: collecting urban water resource information in real time, including rainfall intensity, drainage capacity, earth surface permeability and a historical hydrological data set; constructing an intelligent analysis mechanism, automatically calculating the ponding condition of each region through an algorithm based on the collected urban water resource information, and predicting possible risks in combination with historical data; according to the predicted possible risk, a multi-objective optimization algorithm is combined to calculate an optimal water resource scheduling scheme; and according to a specified scheme, the scheduling of water resources is automatically adjusted. According to the method, the drainage and water storage ratio is adjusted in real time through the constructed multi-objective optimization algorithm, the drainage safety is guaranteed, meanwhile, the cyclic utilization efficiency of water resources is improved, the scheduling strength is controlled through index normalization, and the unstable condition caused by extreme scheduling is avoided.

Description

Technical Field

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

[0002] In recent years, with the intensification of global climate change, extreme precipitation events in cities have occurred frequently. The traditional urban drainage system often has the following technical problems when dealing with sudden heavy rainfall:

[0003] Traditional methods usually rely on empirical models and cannot perform dynamic calculations by combining real-time urban hydrological data, resulting in low prediction accuracy and insufficient timeliness.

[0004] Insufficient emergency dispatching ability: When heavy precipitation occurs in a short period of time, it is impossible to quickly adjust the drainage strategy according to the water accumulation situation in different regions, which is likely to cause the risk of urban waterlogging.

[0005] Existing methods only focus on a single goal, such as maximizing drainage capacity, but do not consider how to improve the urban water resource utilization efficiency while ensuring flood control safety.

[0006] In view of the above technical problems, the present invention proposes a monitoring and management method for a smart sponge city based on intelligent analysis and multi-objective optimal dispatching. Summary of the Invention

[0007] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0008] In view of the problems existing in the above-mentioned prior art, the present invention is proposed.

[0009] To solve the above technical problems, the present invention provides the following technical solutions:

[0010] A monitoring and management method for a smart sponge city, comprising the following steps:

[0011] Step 1: Collect real-time urban water resource information, including: precipitation intensity, drainage capacity, surface permeability, and historical hydrological data sets;

[0012] Step 2: Construct an intelligent analysis mechanism. Based on the collected urban water resource information, automatically calculate the water accumulation situation in each region through algorithms, and combine historical data to predict possible risks;

[0013] Step 3: According to the predicted possible risks, combined with the multi-objective optimization algorithm, calculate the optimal water resource scheduling plan; and automatically adjust the water resource scheduling according to the specified plan.

[0014] As a preferred solution of the monitoring and management method of the intelligent sponge city described in the present invention, wherein: the water resource scheduling plan includes:

[0015] Priority drainage: If the drainage pressure in a certain area is very high, it is recommended to open the drainage gate to accelerate the drainage speed;

[0016] Priority water storage: If the rainfall is not large, but there may be drought in the future, it is recommended to let some rainwater enter the water storage facilities, such as underground reservoirs and permeable ground in parks;

[0017] Intelligent adjustment: Some areas are not prone to waterlogging, but due to excessive drainage in other places, it may cause waterlogging in these areas. Then consider these factors and make the optimal adjustment.

[0018] As a preferred solution of the monitoring and management method of the intelligent sponge city described in the present invention, wherein: the intelligent analysis mechanism includes:

[0019] S201: Define the urban water resource information as follows: precipitation intensity P t (x,y) represents the rainfall at position (x,y) at time t; drainage capacity D(x,y) represents the maximum drainage capacity at this position; surface permeability R(x,y represents the infiltration capacity of the soil and surface in this position area; historical hydrological data set: H(x,y) records the waterlogging depth in this area in the past T time moments;

[0020] S202: Combine the influence of precipitation, drainage and infiltration capacity on the waterlogging depth in the above data, and calculate the current waterlogging depth. The calculation formula is:

[0021]

[0022] where, S t (x,y) represents the waterlogging depth at position (x,y) at time t;

[0023] S203: Combine historical data to predict the waterlogging trend after Δt time in the future. Based on the exponential decay model, the expression is:

[0024] S t+Δt (x,y) = S t (x,y) + e -λΔt ·Φ(H, P t )

[0025] where, λ represents the empirical decay coefficient, and Φ(H, P t ) represents the intelligent prediction value.

[0026] As a preferred solution of the monitoring and management method of a smart sponge city described in the present invention, wherein: the intelligent prediction value Φ(H, P t ) is calculated from historical data and current precipitation input, and the expression is:

[0027]

[0028] wherein, w i represents the historical weight factor, and α represents the precipitation influence factor.

[0029] As a preferred solution of the monitoring and management method of a smart sponge city described in the present invention, wherein: the calculation formula of the multi-objective optimization algorithm is:

[0030]

[0031] wherein, Q final represents the final optimized scheduling volume of the area, β represents the drainage priority coefficient of the area, Q P represents the maximum adjustable drainage volume of the area; γ represents the water storage priority coefficient of the area; Q S represents the maximum water storage volume of the area; represents the intelligent adjustment factor; δ represents the adjustment sensitivity coefficient.

[0032] As a preferred solution of the monitoring and management method of a smart sponge city described in the present invention, wherein: the final optimized scheduling volume is dynamically adjusted through the intelligent adjustment factor to avoid excessive drainage or water storage in a certain area, and its expression is:

[0033]

[0034] wherein, W i represents the weight factor for considering the influence of adjacent areas.

[0035] As a preferred solution of the monitoring and management method of a smart sponge city described in the present invention, wherein: when S t+Δt (x, y) of a certain area is greater than the waterlogging threshold for a long time, it is determined that the area is in long-term over-waterlogging, and then the weight factor W i of the area is increased to ensure the priority of optimizing the drainage strategy;

[0036] When S t+Δt (x, y) of a certain area is lower than the waterlogging threshold for a long time, it is determined that the area is in long-term drought, and then the weight factor W i of the area is decreased, and the water storage ratio is increased.

[0037] A system applied to the above monitoring and management method for an intelligent sponge city, the system comprising:

[0038] A data collection and sensing monitoring module that collects urban water resource information in real time, including: precipitation intensity, drainage capacity, surface permeability, and historical hydrological data sets as the basic inputs for system calculation and optimization; an intelligent analysis and calculation module that calculates the current water accumulation situation using the collected data and predicts future trends; a multi-objective optimization scheduling module that optimizes drainage, water storage, and regulation schemes according to the future trends predicted by the intelligent analysis and calculation module; and a real-time monitoring and visualization module that dynamically visualizes information such as water accumulation status and drainage capacity in different areas of the city; an emergency response and linkage control module that, under extreme weather conditions, links relevant departments for emergency handling, pushes real-time data to the municipal department, and assists in decision-making.

[0039] The present invention also discloses a computer device, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the above monitoring and management method for an intelligent sponge city when executing the computer program.

[0040] The present invention also discloses a computer-readable storage medium, having stored thereon a computer program, and the computer program implementing the steps of the above monitoring and management method for an intelligent sponge city when executed by a processor.

[0041] Advantages of the present invention:

[0042] 1. Through the integral equation and the exponential decay prediction model, combined with precipitation, drainage capacity, and surface permeability, this solution realizes accurate calculation of water accumulation depth and trend prediction. Moreover, through the constructed multi-objective optimization algorithm, it adjusts the drainage and water storage ratio in real time, improves the recycling efficiency of water resources while ensuring drainage safety, and normalizes the control scheduling intensity by exponentiation to avoid instability caused by extreme scheduling, thereby enhancing the safety and robustness of the scheduling system.

[0043] 2. By introducing an intelligent adjustment factor, the present invention can be dynamically adjusted according to the global water resource status, thereby realizing multi-region collaborative optimization, ensuring reasonable distribution of drainage and water storage scheduling in different regions, avoiding local excessive drainage or water resource waste, dynamically adapting to precipitation changes, and enhancing the city's response ability under heavy rainfall conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts. Among them:

[0045] Figure 1 This is a schematic diagram of the overall process of a monitoring and management method for a smart sponge city proposed by the present invention. Specific embodiments

[0046] To make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings of the specification.

[0047] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0048] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that excludes other embodiments.

[0049] Referring to Figure 1 , for an embodiment of the present invention, a monitoring and management method for a smart sponge city is provided. This method includes the following steps:

[0050] Step 1: Collect urban water resource information in real time, including: precipitation intensity, drainage capacity, surface permeability, and historical hydrological data sets.

[0051] Step 2: Construct an intelligent analysis mechanism. Based on the collected urban water resource information, automatically calculate the water accumulation situation in each area through algorithms, and combine historical data to predict possible risks.

[0052] Specifically, the intelligent analysis mechanism includes:

[0053] S201: Define urban water resource information as follows: precipitation intensity P t (x, y) represents the rainfall at time t at position (x, y); the drainage capacity D(x, y) represents the maximum drainage capacity at this position; the surface permeability R(x, y) represents the infiltration capacity of the soil and surface in this position area; the historical hydrological data set: H(x, y) records the water accumulation depth in this area at the past T time moments;

[0054] S202: Combine the influence of precipitation, drainage, and infiltration capacity on the water accumulation depth in the above data, and calculate the current water accumulation depth. The calculation formula is:

[0055]

[0056] Among them, S t (x, y) represents the water accumulation depth at the position (x, y) at time t;

[0057] S203: Predict the water accumulation trend after the future Δt time in combination with historical data. Based on the exponential decay model, the expression is:

[0058] S t+Δt (x, y) = S t (x, y) + e -λΔt ·Φ(H, P t )

[0059] Among them, λ represents the empirical decay coefficient, and φ(H, P t ) represents the intelligent prediction value. The intelligent prediction value φ(H, P t ) is calculated from historical data and current precipitation input. The expression is:

[0060]

[0061] Among them, w i represents the historical weight factor, and α represents the precipitation influence factor.

[0062] Step 3: According to the predicted possible risks, in combination with the multi-objective optimization algorithm, calculate the best water resource scheduling plan; and automatically adjust the water resource scheduling according to the specified plan.

[0063] The water resource scheduling plan includes:

[0064] Priority drainage: If the drainage pressure in a certain area is very high, it is recommended to open the drainage gate to speed up the drainage speed; Priority water storage: If the rainfall is not large, but there may be drought in the future, it is recommended to let some rainwater enter the water storage facilities, such as underground reservoirs and permeable ground in parks; Intelligent adjustment: Some areas are not prone to water accumulation, but due to excessive drainage in other places, it will cause water accumulation in it. Then consider these factors and make the optimal adjustment.

[0065] It should be further noted that the calculation formula of the multi-objective optimization algorithm is:

[0066]

[0067] Among them, Q final represents the final optimized scheduling volume of this area, β represents the drainage priority coefficient of this area, Q P represents the maximum adjustable drainage volume of this area; γ represents the water storage priority coefficient of this area; Q S represents the maximum water storage volume of this area; represents the intelligent adjustment factor; δ represents the adjustment sensitivity coefficient.

[0068] For the distance, assume the observed data in Area A of the current city is as follows:

[0069] Current waterlogging depth: S t (A) = 35 cm. And the predicted waterlogging depth for the next Δt = 2 hours: S t+Δt (A) = 50 cm (expected to continue rising).

[0070] The maximum drainage capacity of this area: Q P (A) = 3000 m 3 / h.

[0071] The maximum water storage capacity of this area: Q S (A) = 2000 m 3 / h.

[0072] Let the safety threshold for urban waterlogging be 40 cm, then S t+Δt (A) exceeds this threshold, and priority should be given to drainage to reduce the risk of waterlogging. However, there may be a drought risk in Area B of this city, and water can be appropriately stored and dispatched to Area B. Let the drainage priority coefficient β = 0.7 (70% of the resources are used for drainage) and the water storage priority coefficient: γ = 0.3 (30% of the resources are used for water storage), and the initial intelligent factor

[0073] Let the sensitivity coefficient δ = 0.05, and calculate based on the above data:

[0074] Then 70% (about 1618 m 3 / h) of this area A is used for drainage, and 30% (about 693 m 3 / h) is used for water storage.

[0075] Through the intelligent adjustment factor dynamically adjust the final optimized dispatching volume to avoid excessive drainage or water storage in a certain area, and its expression is:

[0076]

[0077] where, W i represents the weight factor for considering the influence of adjacent areas.

[0078] Assume: There will be no rainfall in Area B (adjacent area to Area A) in the next 3 hours in the city, but the water storage volume in the past 5 hours is relatively low, and the intelligent adjustment factor needs to be dynamically adjusted to dispatch some water to Area B.

[0079] Assume: The predicted future waterlogging depth in Area B is S t+Δt (B) == 5 cm (no waterlogging);

[0080] Adjacent area C area S t+Δt (C) = 30 cm (low water accumulation);

[0081] Assign weight, W C = 0.6, W B = 0.4.

[0082] At this time, according to the formula

[0083] Then according to the changed Substitute into Q final (A) calculation formula, and recalculate to get Q final (A) ≈ 2940.6 m 3 / h;

[0084] At this time, the total adjusted scheduling water volume in Area A increases to 2940.6 m 3 / h, where:

[0085] 70% (about 2058 m 3 / h) is used for drainage.

[0086] 30% (about 882 m 3 / h) is used for water storage and part of it is scheduled to Area B.

[0087] In addition, when the S t+Δt (x, y) of a certain area is greater than the water accumulation threshold for a long time, it is determined that the area is in long-term over-water accumulation, and then the weight factor W of this area is increased i , to ensure that the drainage strategy is preferentially optimized;

[0088] When the S t+Δt (x, y) of a certain area is lower than the water accumulation threshold for a long time, it is determined that the area is in long-term drought, and then the weight factor W of this area is reduced i , and the proportion of water storage is increased.

[0089] This embodiment further includes: A monitoring and management method for a smart sponge city, characterized in that: The system includes:

[0090] The data collection and sensing monitoring module collects urban water resource information in real time, including: precipitation intensity, drainage capacity, surface permeability, and historical hydrological data sets as the basic inputs for system calculation and optimization; the intelligent analysis and calculation module calculates the current waterlogging situation using the collected data and predicts future trends; the multi-objective optimization scheduling module optimizes drainage, water storage, and regulation schemes according to the future trends predicted by the intelligent analysis and calculation module; and the real-time monitoring and visualization module dynamically visualizes information such as waterlogging conditions and drainage capacities in different areas of the city; the emergency response and linkage control module, under extreme weather conditions, links relevant departments for emergency handling, pushes real-time data to the municipal department, and assists in decision-making.

[0091] This embodiment also provides a computer device applicable to a situation of a monitoring and management method for a smart sponge city, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement a monitoring and management method for a smart sponge city as proposed in the above embodiment.

[0092] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, 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, a carrier network, NFC (near-field communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0093] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the monitoring and management method of a smart sponge city as proposed in the above embodiment; 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 (SRAM for short), electrically erasable programmable read-only memory (EEPROM for short), erasable programmable read-only memory (EPROM for short), programmable read-only memory (PROM for short), read-only memory (ROM for short), magnetic memory, flash memory, magnetic disk or optical disc.

[0094] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A monitoring and management method for a smart sponge city, characterized in that: The following steps are involved: Step 1: Collect urban water resources information in real time, including precipitation intensity, drainage capacity, surface infiltration rate, and historical hydrological data sets; Step 2: Build an intelligent analysis mechanism to automatically calculate the waterlogging situation in each area through algorithms based on the collected urban water resources information, and combine historical data to predict possible risks; Step 3: Based on the predicted possible risks and combined with the multi-objective optimization algorithm, the optimal water resource scheduling plan is calculated; and the water resource scheduling is automatically adjusted according to the specified plan.

2. The monitoring and management method of a smart sponge city according to claim 1 is characterized in that: The water resources scheduling plan includes: Priority drainage: If the drainage pressure in a certain area is very high, it is recommended to open the drainage gate to speed up the drainage; Prioritize water storage: If the rainfall is not heavy, but there is a possibility of drought in the future, it is recommended to allow some rainwater to enter water storage facilities, such as underground reservoirs and permeable surfaces in parks; Intelligent adjustment: Some areas are not prone to water accumulation, but due to excessive drainage in other places, water may accumulate in them. Consider these factors and make the best adjustment.

3. A monitoring and management method for a smart sponge city according to claim 2, characterized in that: The intelligent analysis mechanism includes: S201: Define the urban water resources information as follows: Precipitation intensity P t (x,y) represents the rainfall at time t at the location (x,y); the drainage capacity D(x,y) represents the maximum drainage capacity of the location; the surface permeability R(x,y) represents the permeability of the soil and surface in the location area; the historical hydrological data set: H(x,y) records the water depth of the area at the past T times; S202: Based on the above data, the current water depth is calculated by combining the influence of precipitation, drainage and infiltration capacity on the water depth. The calculation formula is: Among them, S t (x,y) represents the depth of water at the position (x,y) at time t; S203: Combine historical data to predict the trend of water accumulation after Δt time in the future, based on the exponential decay model, the expression is: S t+Δt (x,y)=S t (x,y)+e -λΔt ·Φ(H,P t ) Among them, λ represents the empirical decay coefficient, Φ(H, P t ) represents the intelligent prediction value.

4. A monitoring and management method for a smart sponge city according to claim 3, characterized in that: The intelligent prediction value Φ(H, P t ) is calculated from historical data and current precipitation input, and the expression is: Among them, w i represents the historical weight factor, and α represents the precipitation impact factor.

5. A monitoring and management method for a smart sponge city according to claim 4, characterized in that: The calculation formula of the multi-objective optimization algorithm is: Among them, Q final represents the final optimal dispatching amount of the area, β represents the drainage priority coefficient of the area, Q P represents the maximum adjustable drainage volume of the area; γ represents the water storage priority coefficient of the area; Q S Indicates the maximum amount of water that can be stored in the area; represents the intelligent adjustment factor; δ represents the adjustment sensitivity coefficient.

6. A monitoring and management method for a smart sponge city according to claim 5, characterized in that: Through intelligent adjustment factors Dynamically adjust the final optimal dispatching amount to avoid excessive drainage or water storage in a certain area. The expression is: Among them, W i Represents the weight factor used to consider the influence of neighboring regions.

7. A monitoring and management method for a smart sponge city according to claim 6, characterized in that: When S in a certain area t+Δt If (x,y) is greater than the waterlogging threshold for a long time, the area is judged to be in long-term over-waterlogging, and the weight factor W of the area is increased. i , ensuring that drainage strategies are prioritized and optimized; When S in a certain area t+Δt If (x, y) is below the water accumulation threshold for a long time, the area is judged to be in a long-term drought, and the weight factor W of the area is reduced. i , and increase the water storage ratio.

8. The system of the monitoring and management method of a smart sponge city according to claim 7 is characterized in that: The system includes: Data acquisition and sensor monitoring module, which collects urban water resources information in real time, including precipitation intensity, drainage capacity, surface infiltration rate, and historical hydrological data sets as basic inputs for system calculation and optimization; Intelligent analysis and calculation module, which uses the collected data to calculate the current water accumulation situation and predict future trends; The multi-objective optimization scheduling module optimizes drainage, water storage and regulation schemes according to the future trends predicted by the intelligent analysis and calculation module; As well as the real-time monitoring and visualization module, it dynamically visualizes the water accumulation conditions, drainage capacity and other information in different areas of the city; the emergency response and linkage control module links relevant departments to handle emergencies under extreme weather conditions, and pushes real-time data to municipal departments to assist in decision-making.

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 the monitoring and management method of a smart sponge city as 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 monitoring and management method for a smart sponge city as described in any one of claims 1 to 7 are implemented.

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