Smart city waterlogging monitoring method based on Internet of Things data

Abstract

The invention relates to the technical field of urban waterlogging monitoring. The invention relates to a smart city waterlogging monitoring method based on Internet of Things data. The method comprises the following steps: S1, installing a water level monitoring device in a low-lying area in which water is easy to accumulate in a city, and establishing a water level collection module; s2, enabling a water level collection module to collect water level data collected by a water level monitoring device through the Internet of Things, and obtaining a city three-dimensional map by the water level collection module; water level data of a smart city is collected in real time through the water level monitoring device, an emergency scheme is generated through the water level collection module, water level prediction is carried out according to the position of emergency processing personnel, and then the corresponding emergency scheme is sent according to the predicted water level data. Therefore, emergency personnel can carry corresponding tools to go to the waterlogging position by referring to the emergency scheme, the city safety is improved, waterlogging monitoring and early warning are timely and accurately carried out, threats of waterlogging to lives and properties of people can be reduced, and urban losses caused by waterlogging are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of urban waterlogging monitoring, and in particular to a smart city waterlogging monitoring method based on Internet of Things data. Background Art

[0002] By deploying some water level monitoring devices in the city, it aims to timely grasp the urban waterlogging situation so as to take corresponding emergency measures to ensure the normal operation of the city and the safety of life and property of residents. The field of smart city waterlogging monitoring plays a vital role in modern urban management.

[0003] At present, the normal value is set in the water level monitoring device. When the water level exceeds the normal value, a reminder is sent to the emergency response personnel to deal with the waterlogging. However, it is often impossible to fully obtain relevant information about waterlogging by relying solely on traditional water level sensors. This makes it difficult to accurately predict the occurrence and development of waterlogging in complex meteorological and urban environments, and it is impossible to accurately evaluate the optimal treatment plan corresponding to waterlogging. Therefore, a smart city waterlogging monitoring method based on Internet of Things data is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a smart city waterlogging monitoring method based on Internet of Things data to solve the problems raised in the above background technology.

[0005] To achieve the above purpose, a smart city waterlogging monitoring method based on Internet of Things data is provided, comprising the following steps: S1. Install water level monitoring devices in low-lying areas of the city prone to waterlogging, and establish water level collection modules; S2. The water level collection module collects the water level data collected by the water level monitoring device through the Internet of Things. At the same time, the water level collection module obtains the three-dimensional map of the city, and then inputs the water level monitoring device into the three-dimensional map of the city; S3, analyzing the effective monitoring range of waterlogging for each water level monitoring device according to the three-dimensional map of the city, and then combining the monitoring range with water level data at different heights to simulate emergency plan generation, and obtaining a list of emergency plans corresponding to water level data at different heights; S4. Set a predetermined normal value for each water level monitoring device. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, intercept the historical water level data according to the water level fluctuation time, and then perform the maximum water level change rate speed analysis based on the historical water level data. S5. Obtain the geographic location of the emergency response personnel, and predict the arrival time based on the geographic location combined with the installation location of the abnormal water level monitoring device, and then analyze the predicted water level data by combining the predicted time with the real-time water level data and the maximum water level change rate; S6. Combine the predicted water level data with the emergency plan list to extract the emergency plan, and send the extracted emergency plan to the emergency handling personnel through the water level collection module.

[0006] As a further improvement of the technical solution, the water level monitoring device of S1 adopts a float type real-time continuous water level monitoring method, and a sensor is installed inside to collect water level data; A water level collection module is established through a software program, so that emergency response personnel can view the water level data of different water level monitoring devices at any time.

[0007] As a further improvement of the technical solution, the steps of S2 are as follows: S2.1. Establish a data transmission connection between the water level collection module and the water level monitoring device through the Internet of Things, so as to collect the water level data collected by the water level monitoring device in real time, obtain the installation location of the water level monitoring device at the same time, and classify the water level data according to the installation location; S2.2. Obtain a three-dimensional city map, and input the installation location of the water level monitoring device into the three-dimensional city map, thereby establishing a water level monitoring device model in the three-dimensional city map.

[0008] As a further improvement of the technical solution, the steps of S3 are as follows: S3.1. Analyze the effective monitoring range of waterlogging for each water level monitoring device based on the three-dimensional map of the city, and obtain the corresponding monitoring range of each water level monitoring device; S3.2. Collect emergency facilities that can be used to deal with urban flooding in each monitoring range from emergency response personnel, and then conduct scenario simulation based on the monitoring range and water level data at different heights, so as to obtain the scenario status of the monitoring range at different water levels, and then generate emergency plans based on the emergency facilities and the scenario status of water levels at different heights, and obtain a list of emergency plans corresponding to water level data at different heights.

[0009] As a further improvement of this technical solution, the calculation formula of S3 is as follows: ; Among them, E is the final generated emergency plan expression, i is the monitoring range, n is the total number of monitoring ranges, P i is the emergency plan generation function for the ith monitoring range, W is the water level data, H is the set of fixed factors such as terrain within the monitoring range, and F i is the set of emergency facilities collected within the i-th monitoring range.

[0010] As a further improvement of the technical solution, the step of S4 is as follows: S4.1. Set a predetermined normal value for each water level monitoring device through emergency response personnel; S4.2. Compare the real-time water level data with the predetermined normal value. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, capture the historical water level data according to the water level fluctuation time, and then perform the maximum water level change rate analysis based on the historical water level data to obtain the maximum water level change rate. Conversely, when the real-time water level data does not exceed the predetermined normal value, continue monitoring.

[0011] As a further improvement of this technical solution, the calculation formula of S4.2 is as follows: ; Among them, ΔW is the water level change, W max is the maximum water level, W min is the minimum water level value; ; Among them, ΔT is the time change, T max is the time point corresponding to the highest water level value, T min is the time point corresponding to the lowest water level value; ; Among them, R is the maximum water level change rate.

[0012] As a further improvement of the technical solution, the step of S5 is as follows: S5.1. When the emergency response personnel are using the water level collection module, the water level collection module sends a location acquisition permission request to the emergency response personnel, thereby obtaining the geographic location of the emergency response personnel; S5.2. The arrival time is predicted based on the geographical location combined with the installation location of the abnormal water level monitoring device, so as to obtain the predicted time when the emergency response personnel will arrive at the abnormal water level monitoring device. Then the predicted time is combined with the real-time water level data and the maximum water level change rate to perform predicted water level data analysis, and obtain the predicted water level data when the emergency response personnel arrive at the abnormal water level monitoring device.

[0013] As a further improvement of the present technical solution, when an abnormal water level monitoring device appears in S6, the water level collection module automatically pushes warning information and corresponding emergency plans to the nearest emergency response personnel.

[0014] Compared with the prior art, the present invention has the following beneficial effects: In the smart city waterlogging monitoring method based on Internet of Things data, water level data of the smart city is collected in real time through a water level monitoring device, and an emergency plan is generated through a water level collection module, and water level prediction is performed according to the location of emergency response personnel, and then the corresponding emergency plan is sent according to the predicted water level data, so that emergency personnel can carry corresponding tools to the waterlogging location by referring to the emergency plan, thereby improving urban safety, timely and accurate waterlogging monitoring and early warning, reducing the threat of waterlogging to people's lives and property, and reducing the losses caused to the city by waterlogging. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is the overall flow chart of the present invention; Figure 2 A flowchart of establishing a water level monitoring device model in a three-dimensional urban map according to the present invention; Figure 3 A flowchart of the present invention for obtaining a list of emergency plans corresponding to water level data at different heights; Figure 4 It is a flowchart of the present invention in which emergency treatment personnel set a predetermined normal value for each water level monitoring device; Figure 5 The flowchart of the present invention is to obtain the geographical location of emergency response personnel. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1 - Figure 5 As shown, the purpose of this embodiment is to provide a smart city waterlogging monitoring method based on Internet of Things data, including the following steps: S1. Install water level monitoring devices in low-lying areas of the city prone to waterlogging, and establish water level collection modules; The water level monitoring device of S1 adopts a floating ball type real-time continuous water level monitoring method, and a sensor is installed inside to collect water level data; The technical parameters of the water level monitoring device are: communication mode LORA / 4G, monitoring range 0m-customized, detection accuracy ±1mm, response time 10ms, working voltage 12VDC, working temperature -40℃-85℃, protection grade IP68, installation method is one-pole vertical pole or other installation methods; At the same time, the water level monitoring device is equipped with solar panels for continuous power supply. The technical parameters of the solar panels are: solar panel monocrystalline solar cell components, conversion rate above 20%, life> 20 years, peak power: 12W18V, controller MPPT charging method, with overcharge protection, over-discharge protection and other functions, solar energy maximum charging current 1A, battery DC12V; 6AH, installation method is pole or other methods of installation.

[0018] A water level collection module is established through a software program so that emergency response personnel can view the water level data of different water level monitoring devices at any time. The specific steps are as follows: Design of water level monitoring device: Select a suitable float sensor to ensure that it can accurately reflect the water level changes. The float moves as the water level rises or falls, and the water level changes are converted into electrical signals through mechanical connection or magnetic induction. The sensor installed inside can be a pressure sensor, displacement sensor, etc., which measures the water level height according to the movement of the float. Water level collection module development: Design a database structure to store water level data from different water level monitoring devices. Develop a software program to achieve data communication with the water level monitoring devices and provide a user interface so that emergency response personnel can view water level data from different water level monitoring devices at any time. S2. The water level collection module collects the water level data collected by the water level monitoring device through the Internet of Things. At the same time, the water level collection module obtains the three-dimensional map of the city, and then inputs the water level monitoring device into the three-dimensional map of the city; The steps of S2 are as follows: S2.1. Establish a data transmission connection between the water level collection module and the water level monitoring device through the Internet of Things, so as to collect the water level data collected by the water level monitoring device in real time, and at the same time obtain the installation location of the water level monitoring device, and classify the water level data according to the installation location. The specific steps are as follows: Data collection frequency setting: according to actual needs, the data collection frequency of the water level monitoring device can be set. The collection frequency can be dynamically adjusted according to factors such as rainfall intensity and waterlogging risk. Then the water level monitoring device collects water level data according to the set collection frequency and sends the data to the data collection module through the Internet of Things communication module; Obtain installation location information: When installing a water level monitoring device, assign a unique code to each device and associate it with the installation location information. When the water level monitoring device sends the water level data, it also sends the installation location code to the data collection module. The data collection module queries the corresponding location information database based on the installation location code to obtain the specific installation location of the water level monitoring device.

[0019] S2.2, obtaining a three-dimensional city map, and inputting the installation location of the water level monitoring device into the three-dimensional city map, thereby establishing a water level monitoring device model in the three-dimensional city map. The specific steps are as follows: Obtain city 3D map: Obtain city 3D map data from professional geographic information service providers, and use the corresponding map API or software tools to load the city 3D map data into the application according to the selected map data source; Model design: Design the corresponding three-dimensional model according to the actual shape and size of the water level monitoring device; Model import and positioning: Place the model at the corresponding position in the city 3D map based on the measured installation location coordinates. You can use the positioning and placement functions provided by the map API, or manually adjust the position and orientation of the model to achieve accurate positioning. Model rendering and display: Ensure that the display of the model is consistent with the overall style and atmosphere of the city's 3D map so that users can clearly identify and understand the location and status of the water level monitoring devices.

[0020] S3, analyzing the effective monitoring range of waterlogging for each water level monitoring device according to the three-dimensional map of the city, and then combining the monitoring range with water level data at different heights to simulate emergency plan generation, and obtaining a list of emergency plans corresponding to water level data at different heights; The steps of S3 are as follows; S3.1. Analyze the effective monitoring range of each water level monitoring device based on the three-dimensional urban map to obtain the corresponding monitoring range of each water level monitoring device. The specific steps are as follows: Collect data: In addition to the city's three-dimensional map and the location information of water level monitoring devices, some related data needs to be collected, such as terrain data (including elevation information), drainage network distribution, historical waterlogging data, etc. Determine the influencing factors: Analyze which factors will affect the effective monitoring range of the water level monitoring device. The main factors may include terrain, drainage network, etc. Establishing an analysis model: Based on the determined influencing factors, an analysis model for the effective monitoring range of waterlogging is established. The terrain data, drainage network data and location information of water level monitoring devices can be imported into GIS software, and the monitoring range can be determined through spatial analysis functions; Simulation analysis: Using the established model for simulation analysis, we can consider different rainfall intensities and scenarios, simulate the occurrence and diffusion process of waterlogging, and through simulation, we can observe the response of the water level monitoring device under different conditions, so as to determine its effective monitoring range. The formula is as follows: ; Among them, D flowis the distance based on water flow diffusion, V is the average water flow velocity, which can be estimated using Manning's formula combined with parameters such as terrain slope and hydraulic radius, t is time, α and β are adjustment coefficients, and A is the upstream water accumulation area; ; Among them, D accuracy is the effective distance based on accuracy, Δh is the measurement accuracy of the water level monitoring device, and γ is the adjustment coefficient; ; Among them, D effective For comprehensive effective monitoring range; The adjustment coefficients α, β, and γ can be determined by fitting actual data or empirical judgment. These coefficients can be adjusted to make them more in line with the actual situation by analyzing the water flow diffusion in historical waterlogging events and the actual monitoring effect of the monitoring device. S3.2. Collect emergency facilities that can be used to deal with waterlogging in each monitoring range from emergency response personnel, and then simulate the scene of the monitoring range in combination with water level data at different heights, so as to obtain the scene status of the monitoring range at different water levels, and then generate emergency plans based on the emergency facilities in combination with the scene status of water levels at different heights, and obtain a list of emergency plans corresponding to water level data at different heights. The specific steps are as follows: Emergency facility collection: communicate and investigate with emergency response personnel to understand the emergency facilities that can be used within each monitoring range, such as sandbags, drainage pumps, temporary water retaining boards, etc., and record them; Scenario simulation: Combine the terrain data, drainage network data, etc. of the monitoring range, and water level data at different heights, and use a hydrodynamic model or simulation software to simulate the scenario. Through simulation, we can understand the flow direction, water accumulation range, submerged area and other scenario conditions at different water levels; Generation of emergency plans: According to the collected emergency facilities and the simulated scene states of different water levels, formulate corresponding emergency plans. If the water level is low, sandbags can be used for local blocking; if the water level is high, it may be necessary to start the drainage pump for forced drainage, etc. Generate emergency plan list: Generate corresponding emergency plans for water level data at different heights and organize them into emergency plan lists for quick reference and implementation in actual waterlogging events. The formula is as follows: ; Among them, E is the final generated emergency plan expression, i is the monitoring range, n is the total number of monitoring ranges, P i is the emergency plan generation function for the ith monitoring range, W is the water level data, H is the set of fixed factors such as terrain within the monitoring range, and F i is the set of emergency facilities collected within the i-th monitoring range.

[0021] S4. Set a predetermined normal value for each water level monitoring device. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, intercept the historical water level data according to the water level fluctuation time, and then perform the maximum water level change rate speed analysis based on the historical water level data. The steps of S4 are as follows: S4.1. Set a predetermined normal value for each water level monitoring device through emergency response personnel; S4.2. Compare the real-time water level data with the predetermined normal value. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, intercept the historical water level data according to the water level fluctuation time, and then analyze the maximum water level change rate based on the historical water level data to obtain the maximum water level change rate. On the contrary, when the real-time water level data does not exceed the predetermined normal value, continue to monitor. The specific steps are as follows: Setting a predetermined normal value: Emergency response personnel set a predetermined normal value for each water level monitoring device based on experience, historical data, and the characteristics of the monitoring area; Value comparison: continuously obtain real-time water level data and compare it with the predetermined normal value. If the real-time water level data exceeds the predetermined normal value, enter the abnormal processing process; if it does not exceed the normal value, continue monitoring; Abnormal marking: When the real-time water level data exceeds the preset normal value, the water level monitoring device is marked as abnormal, and then the historical water level data within a certain period of time is intercepted according to the water level fluctuation time. This time period can be determined according to the actual situation, such as the period from the beginning of the water level fluctuation to the current time; Analysis of the maximum water level change rate: Analyze the intercepted historical water level data and calculate the maximum water level change rate. The formula is as follows: ; Among them, ΔW is the water level change, W max is the maximum water level, W min is the minimum water level value; ; Among them, ΔT is the time change, T max is the time point corresponding to the highest water level value, T min is the time point corresponding to the lowest water level value; ; Among them, R is the maximum water level change rate.

[0022] S5. Obtain the geographic location of the emergency response personnel, and predict the arrival time based on the geographic location combined with the installation location of the abnormal water level monitoring device, and then analyze the predicted water level data by combining the predicted time with the real-time water level data and the maximum water level change rate; The steps of S5 are as follows: S5.1. When the emergency response personnel are using the water level collection module, the water level collection module sends a location acquisition permission request to the emergency response personnel, thereby obtaining the geographic location of the emergency response personnel; S5.2. The arrival time is predicted based on the geographical location combined with the installation location of the abnormal water level monitoring device, so as to obtain the predicted time when the emergency response personnel arrive at the abnormal water level monitoring device. Then, the predicted time is combined with the real-time water level data and the maximum water level change rate to perform predicted water level data analysis, and the predicted water level data when the emergency response personnel arrive at the abnormal water level monitoring device is obtained. The specific steps are as follows: Location acquisition permission request: When the emergency response personnel use the water level collection module, the water level collection module sends a location acquisition permission request to the emergency response personnel. The emergency response personnel choose to agree, so that the water level collection module will be able to obtain the geographic location information of the emergency response personnel; Arrival time prediction: based on the geographical location of the emergency response personnel and the installation location of the abnormal water level monitoring device, combined with factors such as traffic conditions and road network, the arrival time can be predicted. The API of the map navigation software or other path planning algorithms can be used to estimate the arrival time; Predicted water level data analysis: The predicted arrival time is combined with the real-time water level data and the maximum water level change rate for predicted water level data analysis. First, the change in water level during this period is calculated based on the maximum water level change rate and the predicted arrival time, that is, predicted water level change = maximum water level change rate × predicted arrival time. Then, the real-time water level data is added to the predicted water level change to obtain the predicted water level data when the emergency response personnel arrive at the abnormal water level monitoring device.

[0023] S6. Combine the predicted water level data with the emergency plan list to extract the emergency plan, and send the extracted emergency plan to the emergency handling personnel through the water level collection module.

[0024] S6 When an abnormal water level monitoring device appears, the water level collection module automatically pushes warning information and corresponding emergency plans to the nearest emergency response personnel. The specific steps are as follows: Combine the predicted water level data with the emergency plan list to extract the emergency plan: match the predicted water level data with each emergency plan in the emergency plan list. Usually, the matching can be based on the preset water level range and the corresponding emergency plan. If the predicted water level data falls within a specific water level interval, the emergency plan corresponding to the interval is extracted. Sending emergency plans to emergency response personnel: Sending the emergency plans extracted by the water level collection module to emergency response personnel by means of push notifications, SMS, in-app messages, etc.; Abnormal water level monitoring device warning and solution push: When an abnormal water level monitoring device appears, the water level collection module automatically identifies the nearest emergency response personnel. The nearest personnel can be determined by calculating the distance between the geographical location of the emergency response personnel and the installation location of the abnormal water level monitoring device, and then the warning information and the corresponding emergency plan are pushed to the nearest emergency response personnel so that they can take action as soon as possible.

[0025] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A smart city waterlogging monitoring method based on Internet of Things data, characterized by: The following steps are involved: S1. Install water level monitoring devices in low-lying areas of the city prone to waterlogging, and establish water level collection modules; S2. The water level collection module collects the water level data collected by the water level monitoring device through the Internet of Things. At the same time, the water level collection module obtains the three-dimensional map of the city, and then inputs the water level monitoring device into the three-dimensional map of the city; S3, analyzing the effective monitoring range of waterlogging for each water level monitoring device according to the three-dimensional map of the city, and then simulating emergency plans based on the monitoring range and water level data at different heights to obtain a list of emergency plans corresponding to water level data at different heights; S4. Set a predetermined normal value for each water level monitoring device. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, intercept the historical water level data according to the water level fluctuation time, and then perform the maximum water level change rate speed analysis based on the historical water level data. S5. Obtain the geographic location of the emergency response personnel, and predict the arrival time based on the geographic location combined with the installation location of the abnormal water level monitoring device, and then analyze the predicted water level data by combining the predicted time with the real-time water level data and the maximum water level change rate; S6. Combine the predicted water level data with the emergency plan list to extract the emergency plan, and send the extracted emergency plan to the emergency handling personnel through the water level collection module.

2. According to claim 1, a smart city waterlogging monitoring method based on Internet of Things data is characterized by: The water level monitoring device of S1 adopts a floating ball type real-time continuous water level monitoring method, and a sensor is installed inside to collect water level data; A water level collection module is established through a software program, so that emergency response personnel can view the water level data of different water level monitoring devices at any time.

3. The method for monitoring waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: The steps of S2 are as follows: S2.

1. Establish a data transmission connection between the water level collection module and the water level monitoring device through the Internet of Things, so as to collect the water level data collected by the water level monitoring device in real time, obtain the installation location of the water level monitoring device at the same time, and classify the water level data according to the installation location; S2.

2. Obtain a three-dimensional city map, and input the installation location of the water level monitoring device into the three-dimensional city map, thereby establishing a water level monitoring device model in the three-dimensional city map.

4. The method for monitoring waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. Analyze the effective monitoring range of waterlogging for each water level monitoring device based on the three-dimensional map of the city, and obtain the corresponding monitoring range of each water level monitoring device; S3.

2. Collect emergency facilities that can be used to deal with urban flooding in each monitoring range from emergency response personnel, and then conduct scenario simulation based on the monitoring range and water level data at different heights, so as to obtain the scenario status of the monitoring range at different water levels, and then generate emergency plans based on the emergency facilities and the scenario status of water levels at different heights, and obtain a list of emergency plans corresponding to water level data at different heights.

5. The method for monitoring waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: The calculation formula of S3 is as follows: ； Among them, E is the final generated emergency plan expression, i is the monitoring range, n is the total number of monitoring ranges, P i is the emergency plan generation function for the ith monitoring range, W is the water level data, H is the set of fixed factors such as terrain within the monitoring range, and F i is the set of emergency facilities collected within the i-th monitoring range.

6. The method for monitoring waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Set a predetermined normal value for each water level monitoring device through emergency response personnel; S4.

2. Compare the real-time water level data with the predetermined normal value. When the real-time water level data exceeds the predetermined normal value, mark the water level monitoring device as abnormal. At the same time, capture the historical water level data according to the water level fluctuation time, and then perform the maximum water level change rate analysis based on the historical water level data to obtain the maximum water level change rate. Conversely, when the real-time water level data does not exceed the predetermined normal value, continue monitoring.

7. A smart city waterlogging monitoring method based on Internet of Things data according to claim 6, characterized in that: The calculation formula of S4.2 is as follows: ； Among them, ΔW is the water level change, W max is the maximum water level, W min is the minimum water level value; ； Among them, ΔT is the time change, T max is the time point corresponding to the highest water level, T min is the time point corresponding to the lowest water level value; ； Among them, R is the maximum water level change rate.

8. The method for monitoring urban waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. When the emergency response personnel are using the water level collection module, the water level collection module sends a location acquisition permission request to the emergency response personnel, thereby obtaining the geographic location of the emergency response personnel; S5.

2. The arrival time is predicted based on the geographical location combined with the installation location of the abnormal water level monitoring device, so as to obtain the predicted time when the emergency response personnel will arrive at the abnormal water level monitoring device. Then the predicted time is combined with the real-time water level data and the maximum water level change rate to perform predicted water level data analysis, and obtain the predicted water level data when the emergency response personnel arrive at the abnormal water level monitoring device.

9. The method for monitoring urban waterlogging in a smart city based on Internet of Things data according to claim 1, characterized in that: In S6, when an abnormal water level monitoring device appears, the water level collection module automatically pushes warning information and corresponding emergency plans to the nearest emergency response personnel.

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