Urban flood disaster early warning system and method based on 5G and automatic observation technology

Abstract

The invention relates to the technical field of disaster early warning, in particular to an urban flood disaster early warning system and method based on 5G and an automatic observation technology, based on an urban DEM map, a contour map, a land cover type map, a tunnel distribution map and a municipal road distribution map, a random forest machine learning algorithm is utilized to determine the position where a laser water depth automatic observation system needs to be installed, and the laser water depth automatic observation system is installed. Then, according to the installation height and angle of an actual instrument, by combining initial parameters of the laser water depth automatic observation system, the real-time monitoring of the water depth of the road by the laser water depth automatic observation system is realized. According to the invention, in accordance with a sustainable development concept, emphasizing green ecology, harmony of people and water and application of new technologies, a laser water depth automatic observation system is installed based on existing street lamps, real-time monitoring of the water depth of urban road surfaces is carried out in rainy weather, water query and visualization are realized, urban inland inundation can be effectively monitored, early warning and forecasting are provided, and the urban inland inundation can be effectively monitored. And convenience is provided for production and life of people.

Description

Technical Field

[0001] The present invention relates to the field of disaster warning technology, and in particular to an urban flood disaster warning system and method based on 5G and automatic observation technology. Background Art

[0002] When the rainfall is heavy, the urban road design and drainage system cannot handle the large amount of water in a timely and effective manner; the high-rise buildings in the city are densely distributed, which affects the water flow path and makes it impossible for the water to drain smoothly; urban expansion and land use changes will affect the natural hydrological cycle path, increasing the possibility of road waterlogging and flooding. In order to monitor and warn of urban waterlogging, so that people can formulate flood prevention plans and solutions in advance during heavy rains, the existing technology discloses a variety of urban waterlogging intelligent monitoring and warning methods, which can provide warning information when flood disasters occur in cities, and provide convenience and safety for the lives of urban residents.

[0003] However, the existing urban flood monitoring and early warning system has the following drawbacks: the early warning scheme is imperfect, and the medium- and long-term rainfall forecast cannot provide a more accurate range and sufficient preparation time for emergency deployment and rescue; the early warning technology is insufficiently applied, and some areas have less application of early warning technology or even no early warning technology; the early warning information sharing mechanism is not sound, the rapid information sharing and dissemination mechanism is imperfect, and there are "blind spots" in the coverage of early warning information; the existing flood early warning system is highly dependent on its cloud service and big data cluster, and has the disadvantages of insufficient rapid warning, single-point forecast limitations, data collection limitations, slow transmission speed, and high resource consumption.

[0004] Therefore, the present invention proposes an urban flood disaster early warning system and method developed based on 5G and automatic observation technology, which can conduct real-time monitoring of water accumulation on urban roads during rainy weather, realize query and visualization, and thus play the role of early warning, prevention and protection of the lives and property of urban residents. Summary of the invention

[0005] In response to the above-mentioned defects and problems, the present invention provides an urban flood disaster early warning system and method based on 5G and automatic observation technology, develops a laser water depth automatic observation system, and installs a laser water depth automatic observation system based on existing street lamps to carry out real-time monitoring of urban road surface waterlogging, realize water depth query and visualization, and thus play a role in early warning and prevention, provide convenience for the lives of urban residents, and ensure the travel safety of urban residents.

[0006] The solution adopted by the present invention to solve the technical problem is: an urban flood disaster early warning system based on 5G and automatic observation technology, including the following steps: Step 1: Modify the laser rangefinder and connect it to the CR1000 data collector. Use the LoggerNet software to set the sampling of CR1000 and transmit and view the data in real time to achieve continuous observation of road water depth, that is, develop a laser water depth automatic observation system. Step 2: Sample data were obtained through indoor and outdoor observation tests, and the measurement accuracy of the laser water depth automatic observation system was verified based on Pearson correlation analysis and paired sample T test. The results showed that the laser water depth automatic observation system has extremely high observation accuracy for road surface water depth, and the results are reliable. Step 3: For the target city, select suitable locations for installing the laser water depth automatic observation system. Based on the city DEM map, contour map, land cover type map, tunnel distribution map and municipal road distribution map, use the random forest machine learning algorithm to select and determine the appropriate location, and select the nearest street lamp for installing the laser water depth automatic observation system; Step 4: According to the installation height and angle of the laser water depth automatic observation system and the initial installation parameters, MATLAB is used to write the water depth measurement code, and the water depth is calculated by code optimization; Step five: Based on the 5G sensor network, the monitored water depth information is transmitted to the server in real time to realize data integration and mining, and a mobile port APP is developed to synchronize and update the data on the server to the APP in real time, providing users with real-time road water depth and road warning information. The work content of this step is performed in rainy weather.

[0007] Furthermore, in step 1, the process of selecting street lamps for installing the laser water depth automatic observation system is as follows: 1) Apply for DEM data, preprocess and analyze DEM data, and extract required terrain parameters; 2) Use ArcGIS to create city contour maps and analyze urban geographical conditions in combination with city DEM elevation maps; 3) Apply for Landsat8 data and use object-based supervised classification methods to obtain urban land cover type maps and the latest municipal road distribution maps of the city; 4) Using the latest urban land cover type, urban DEM elevation, contour distribution and municipal roads, based on random forest machine learning technology and writing Python programs, first set the elevation change threshold, then consider the land cover type and population density, screen out the appropriate location for the deployment of the laser water depth automatic observation system, and find the corresponding street lamps for installing the laser water depth automatic observation system based on the principle of the shortest distance; 5) The street lights finally selected are then optimized based on the elevation information, and combined with the information provided by the municipal road department and field surveys, laser water depth automatic observation system stations are added in tunnels and areas prone to waterlogging.

[0008] Furthermore, in the step four, the laser water depth automatic observation system is designed as a multi-angle rotating structure, and the angle between the laser emitting direction of the laser water depth automatic observation system and the vertical direction of the street lamp pole is variable, and the angle can be specified for measurement according to actual conditions.

[0009] Furthermore, the specific installation and layout plan of the laser water depth automatic observation system is as follows: Based on the original street lamp, the distance between the street lamp pole and the ground h The laser water depth automatic observation system is installed at position 1. The signal transmitting end of the installed laser water depth automatic observation system is at a certain angle to the electric pole. When there is no water on the ground, the laser water depth automatic observation system transmits a signal to measure the distance between the ground and the signal transmitting end. a 1. When there is water on the ground, assume that the depth of the water is H , and can measure the distance between the ground and the signal transmitter a 2. According to the principle of similar triangles, we have: ; The depth of road water H for: ; Furthermore, when observing the water depth, the laser water depth automatic observation system first designs an algorithm based on the optical characteristics of the water body to determine whether it is a water surface. If it is a water surface, it directly observes it. If it is an obstacle, the laser water depth automatic observation system rotates an angle to the flooded road surface and then observes it.

[0010] Furthermore, in step five, based on the data collection of the laser water depth automatic observation system, the 5G wireless sensor network is used to update the automatically observed and collected water depth information to the mobile phone APP visualization interface through the server terminal, and communication technology is used to realize data information sharing, and an integrated early warning system of street lamp laser water depth automatic observation system - 5G wireless sensor network - APP query is established.

[0011] Furthermore, the laser water depth automatic observation system selects the red light band with a wavelength of 620-680nm, and the laser water depth automatic observation system is installed on street lamps at designated locations in the city; CR1000 data collector, which can provide automatic measurement and control. CR1000 data collector is connected with the laser water depth automatic observation system to realize continuous observation of water depth; LoggerNet software is an application software that integrates communication and data collection. LoggerNet software can set sampling for CR1000 and transmit and view data in real time; The 5G sensor network module transmits the monitored water depth information to the server in real time to achieve data integration and mining; Mobile port APP, the data on the server side is synchronized and updated to the mobile port APP in real time, providing users with road water depth and warning information.

[0012] Furthermore, a display screen is installed on the street lamp where the laser water depth automatic observation system is located, which can feed back information such as the water depth of the evacuation channel and road on the display screen to serve as an early warning.

[0013] Furthermore, solar panels are installed on the street lamps where the laser water depth automatic observation system is located, which use solar energy to store energy and perform energy-saving observations, in line with the concept of green and sustainable development.

[0014] Beneficial effects of the invention: Based on the frequent occurrence of urban waterlogging, the invention combines the needs of urban waterlogging warning, adheres to the concept of sustainable development, widely selects street lamps in suitable locations in the city, installs a laser water depth automatic observation system based on the street lamp circuit, and conducts real-time monitoring, query and visualization of urban road surface waterlogging through an automated collection program, thereby playing the role of early warning, prevention and protection of the safety of life and property of urban residents, providing decision-making support for urban flood control, traffic management, etc., and reducing the inconvenience caused by road surface waterlogging to life and production; Real-time monitoring and recording of urban waterlogging depth data, uploading the data to the server cloud platform through the 5G network to realize real-time data analysis and processing, and then transmitting the road surface waterlogging depth information to the mobile user APP in real time through the 5G network. Users can make real-time inquiries on road surface waterlogging, thereby planning safe travel routes and avoiding risks on rainy days, and improving the timeliness of residents' response to urban waterlogging disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is the technical roadmap of the present invention; Figure 2 This is a schematic diagram of the installation of the street lamp laser water depth automatic observation system of the present invention; Figure 3 It is the city DEM map of the present invention; Figure 4 The city contour map of the present invention; Figure 5 The urban municipal road distribution map of the present invention; Figure 6 The urban land cover type map of the present invention; Figure 7 A distribution diagram of street lamps for installing the automatic laser water depth observation system of the present invention; Figure 8 It is a correlation analysis diagram of the water depth measured by the laser water depth automatic observation system of the present invention and the reference water depth; Fig. 9 This is the mobile APP interface developed for the project.

[0016] In the picture: 1. Street light; 2. Laser water depth automatic observation system; 3. Solar panel; 4. Display screen. DETAILED DESCRIPTION

[0017] In order to reduce the losses caused by heavy rainfall like the one in Zhengzhou (July 20), an urban flood warning system was developed to monitor the depth of urban road waterlogging in real time on rainy days, provide emergency guidance for municipal departments, and provide early warning information for citizens traveling on rainy days, thus reducing unnecessary casualties and property losses. Figure 1-9 The present invention is further illustrated by the following embodiments. Example

[0018] The present invention proposes a smart water conservancy urban flood warning method based on 5G and automatic observation technology. The technical route is as follows: Figure 1 As shown, the specific steps include: Step 1: In order to enable the laser rangefinder to have the function of automatically and continuously measuring and collecting water depth data, the laser rangefinder is modified. The present invention adopts the CR1000 data collector and the supporting LoggerNet software produced by Campbell Scientific Company of the United States. The modified laser rangefinder is connected to the CR1000 data collector, and a program is compiled using LoggerNet to achieve continuous monitoring and data collection at a certain time interval (such as 10 minutes, 30 minutes, etc.), and a laser water depth automatic observation system is developed.

[0019] Step 2: Verify the accuracy of the laser water depth automatic observation system.

[0020] Step three, using the latest land cover type, DEM elevation, contour lines, tunnel distribution location, municipal roads and other multi-source data of the city (Zhengzhou is taken as an example here) as the criterion layer, and setting a variety of constraints based on the optimal location selection algorithm of random forest machine learning, screen out the appropriate location for deploying the laser water depth automatic observation system, and find the corresponding street lamp 1 based on the principle of shortest distance. On the determined street lamp pole, based on the concept of green environmental protection, use the existing street lamp circuit to install the laser water depth automatic observation system 2 to realize real-time observation of road water depth.

[0021] Using the existing street lamps 1 to install the laser water depth automatic observation system can not only achieve the purpose of real-time monitoring of water depth, but also reduce costs by utilizing the existing street lamp circuits. Due to the huge number of street lamps, according to actual research needs and costs, the laser water depth automatic observation system only needs to be installed on some street lamps.

[0022] The street lights for installing the laser water depth automatic observation system need to be selected reasonably. The specific steps are as follows: 1) Apply for DEM data, preprocess and analyze DEM data, and extract required terrain parameters such as elevation, slope, etc.; 2) Use ArcGIS to create city contour maps and analyze the city's geographical conditions in combination with the Zhengzhou DEM elevation map; 3) Apply for the Landsat8 data of Zhengzhou City, and use object-based supervised classification to obtain the land cover type map of Zhengzhou City and the latest municipal road distribution map of Zhengzhou City; 4) Using the latest land cover type, urban DEM elevation, contour distribution and municipal roads in Zhengzhou, a Python program was written based on random forest machine learning technology. First, the elevation change threshold was set (the initial value was 10 meters, which needs to be adjusted according to actual conditions). Secondly, considering the land cover type and population density, the appropriate location for the automatic laser water depth observation system was selected, and the corresponding street lights were found based on the principle of the closest distance. 5) The street lights to be finally selected must be optimized based on the elevation information, and combined with the information provided by the municipal road department and field surveys, additional laser water depth automatic observation system stations should be set up in tunnel areas and areas prone to waterlogging.

[0023] The street lamps that will eventually be equipped with the laser water depth automatic observation system have the following characteristics: ① In the northeastern region with flat terrain, the number of sites is small and the density is low; ② In the middle area, stations are evenly distributed along the contour lines and between the contour lines; ③ Deploy more stations in the southwest region where the terrain is more undulating; ④ Densely populated urban areas require dense deployment of stations; ⑤ Take into account tunnels and areas prone to water accumulation, and add more stations.

[0024] Zhengzhou DEM, contour lines (50m intervals), municipal roads and land cover type maps are shown below: Figure 3 - Figure 6 As shown, the initial selection of street lamp distribution is as follows Figure 7 .

[0025] Step 4: According to the instrument installation height, angle and other information, combined with the initial installation parameters of the laser water depth automatic observation system, the laser water depth automatic observation system is used to realize automatic observation, and the water depth measurement code is written using MATLAB, and the code is optimized to obtain the water depth.

[0026] If the laser emitted by the laser water depth automatic observation system hits an obstacle below, it will directly affect the measurement result. Therefore, it is necessary to design the laser water depth automatic observation system to rotate at multiple angles. First, an algorithm is designed based on the optical characteristics of the water body to determine whether it is a waterlogged surface. If it is a waterlogged surface, observation is performed directly; if it is an obstacle, the laser water depth automatic observation system rotates to the waterlogged road surface. The angle between the laser emission direction of the laser water depth automatic observation system and the vertical direction is variable, and the angle can be selected for measurement according to the actual situation.

[0027] The specific installation and layout plan of the laser water depth automatic observation system is as follows: On the basis of the original street lamp, the distance between the street lamp pole and the ground is increased. h 1, the laser water depth automatic observation system is installed. The signal transmitting end of the laser water depth automatic observation system is at a certain angle to the electric pole, and the angle can be adjusted according to the actual situation. When there is no water on the ground, the laser water depth automatic observation system transmits a signal to measure the distance between the ground and the signal transmitting end, which is set as a 1; When there is water on the ground, assume that the depth of the water is H , and the distance between the ground and the signal transmitter can be measured, set as a 2. Installing laser water depth automatic observation system on street lamp poles Figure 2 , according to the principle of similar triangles, we have: ; Then the depth of water accumulation is: ; Step 5: Based on the data collection of the laser water depth automatic observation system, the water depth information automatically observed and collected is transmitted to the server terminal in real time based on the 5G wireless sensor network to realize data integration, data mining and data analysis; a mobile port APP is developed based on H builder X, and the data on the server side is synchronized and updated in real time to the mobile phone APP visualization interface, and data information sharing is realized by using communication technology. An integrated early warning system of street lamp laser water depth automatic observation system - 5G wireless sensor network - APP query is established. Users can remotely query the water depth through the APP and plan the optimal travel route.

[0028] Based on the above scheme, real-time monitoring and early warning of road water depth can be achieved, which can greatly improve the convenience and safety of people's travel on rainy days and provide support for the sustainable and high-quality development of cities. Example

[0029] Based on Example 1, the present invention proposes an urban flood disaster warning system based on 5G and automatic observation technology, including a street lamp 1, a laser water depth automatic observation system 2, a CR1000 data collector, LoggerNet software, a 5G sensor network module and a mobile port APP.

[0030] The laser water depth automatic observation system 2 selects red light with a wavelength of 620-680nm as the detection band. The system filtering algorithm can effectively filter up to 99% of scattered waves. The free-form surface lens is used, and the effective emissivity and effective receiving rates are increased by more than 20%. The measurement is more accurate and can achieve millimeter-level accuracy. The laser water depth automatic observation system is installed on a street lamp 1 at a designated location in the city.

[0031] The CR1000 data collector is a measurement sensor that can provide automatic measurement and control. It is often used in experiments and practices including meteorological stations, hydrological and meteorological stations, hydrological systems, water quality monitoring, wind profiles, air quality monitoring, etc. It can drive direct communication, analyze data, control external devices, and store data and programs in onboard non-volatile memory. The CR1000 data collector can provide automatic measurement and control. In the present invention, the CR1000 data collector is connected to a laser rangefinder to achieve continuous observation of water depth.

[0032] LoggerNet software is an application software developed by Campbell Company that integrates communication and data acquisition. It runs in Windows 95, 98, Windows NT 4.0, Windows 2000 or Windows XP environment. Users can configure the software, establish a connection between a PC and a data collector, send a collection program, collect data, observe real-time data, and perform data analysis. It is an application software that integrates communication and data acquisition. In the present invention, LoggerNet software performs sampling settings for CR1000 and real-time data transmission and viewing.

[0033] The 5G sensor network module can transmit the monitored water depth information to the server in real time to achieve data integration and mining, and update the automatically observed and collected water depth information to the visual interface of the mobile phone mobile port APP in real time through the server terminal, using communication technology to achieve data information sharing, and establish a street lamp laser water depth automatic observation system - 5G wireless sensor network - APP query integrated early warning system to provide users with early warning information. The preliminary developed mobile terminal APP interface is as follows Fig. 9 .

[0034] The APP developed by the present invention on the mobile port takes the convenience of residents' use and path query analysis as the primary goal. The functions realized by the APP developed by the present invention are: ① Water depth query and early warning function Through the APP interface, the depth of road waterlogging can be displayed in real time and accurately. This function will be presented in clear and intuitive numbers and eye-catching color labels. For example, green indicates shallow waterlogging, yellow indicates moderate waterlogging, and red indicates severe waterlogging. At the same time, specific water depth values, such as 10cm, 20cm, etc., will be attached to provide a reference for residents' travel.

[0035] ②Optimal path planning function For residents with travel needs, under the premise that the departure and destination are determined, a machine learning algorithm is used to plan the optimal travel route under the premise of safe water depth based on the constraints of safe water depth and the nearest distance.

[0036] ③Multi-source data integration function The APP can integrate multi-source hydrological data, for example, cooperate with the meteorological department to provide real-time display of rainfall, show the current rainfall intensity, such as light rain, moderate rain, heavy rain, rainstorm, etc., and dynamically present the changing trend of rainfall. The combination of water depth data and rainfall data will provide users with a better user experience.

[0037] ④Water depth estimation function in areas without monitoring stations Based on the long-term rainfall and water accumulation depth data of the observation station, wavelet analysis, trend test and other methods are used to analyze the relationship between the rainfall process line and the road surface water accumulation process line. Based on this, the hydrological analogy method is used to infer the water accumulation depth of similar areas (without laser water depth automatic observation system). As the observation data accumulates, the program is continuously optimized to provide more scientific, reasonable and feasible suggestions for urban flood disaster warning.

[0038] ⑤ Emergency call function By adding an emergency call function to the APP, people can call for help with one click in an emergency. The button will simultaneously send the exact location information of the affected people and automatically play the corresponding self-rescue methods.

[0039] A display screen 4 is installed on the street lamp where the laser water depth automatic observation system is located, and the information such as the evacuation channel and the road water depth is fed back on the display screen to play the role of early warning. In order to save energy and prevent sudden power outages when heavy rain comes, the laser water depth automatic observation system needs to be installed with a solar panel 3 after installation, which uses solar energy to store energy, which can save energy and cope with sudden power outages, ensuring that the laser water depth automatic observation system can play a role at critical moments and protect people's lives and property. Example

[0040] Based on the first embodiment, the present invention provides a method for verifying the accuracy of a laser water depth automatic observation system. (1) Measurement test of laser water depth automatic observation system Collect rainwater to be measured on rainy days, install the laser water depth automatic observation system on the wall, and keep a certain angle α with the wall. In order to ensure the stability of the measurement and eliminate external interference as much as possible, the measurement is completed by a member who is proficient in measurement skills. After the initial state is adjusted, mark the position of the bucket.

[0041] The following are the specific steps: ① Turn on the laser water depth automatic observation system, place an empty bucket at the bucket mark, and measure the distance between the laser water depth automatic observation system and the bottom of the empty bucket; ② Add a certain amount of rainwater into the bucket and measure the distance between the laser water depth automatic observation system and the water surface; ③ Calculate the water depth (test water depth) according to the program algorithm provided by the project, and use a ruler to measure the actual water depth of the bucket (reference water depth); ④ Increase the amount of water in the basin gradually every 1 minute, start the laser water depth automatic observation system (observation interval is 1 minute), complete the automatic water depth measurement, and measure 20 times in total; Table 1 gives the test data including the installation angle, installation height, distance between the ground and the laser water depth automatic observation system, reference water depth, and calculates the test water depth.

[0042]

[0043] (2) Verification of the measurement accuracy of the laser water depth automatic observation system The following is the accuracy verification and evaluation of the water depth results measured by the laser water depth automatic observation system. The reference water depth and the water depth measured by the laser water depth automatic observation system are analyzed for correlation. The results are as follows Figure 8 As shown by Figure 8 It can be seen that the measured water depth is highly correlated with the reference water depth, with a determination coefficient of over 0.99, indicating that the water depth measured by the laser water depth automatic observation system is highly accurate and reliable.

[0044] In order to further verify the reliability of the results, a paired sample T test was performed on the reference water depth and the water depth measured by the laser water depth automatic observation system. The results are shown in Table 2:

[0045]

[0046] It can be seen from the table that at the 95% confidence interval, the Sig (two-tailed) value is 0.733, which is greater than 0.05, rejecting the null hypothesis. There is no significant difference between the two paired samples, indicating that there is no difference between the water depth measured by the laser water depth automatic observation system and the reference water depth measured by the ruler. Therefore, the laser water depth automatic observation system developed in this project is an effective way to realize the measurement of road surface water depth.

[0047] The above description is only a preferred embodiment of the present invention and does not limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for early warning of urban flood disasters based on 5G and automatic observation technology, characterized in that: The following steps are involved: Step 1: Modify the laser rangefinder and connect it to the CR1000 data collector. Use the LoggerNet software to set the sampling of CR1000 and transmit and view the data in real time to achieve continuous observation of road water depth, that is, develop a laser water depth automatic observation system. Step 2: Sample data were obtained through indoor and outdoor observation tests, and the measurement accuracy of the laser water depth automatic observation system was verified based on Pearson correlation analysis and paired sample T test. The results showed that the laser water depth automatic observation system has extremely high observation accuracy for road surface water depth, and the results are reliable. Step 3: For the target city, select suitable locations for installing the laser water depth automatic observation system. Based on the city DEM map, contour map, land cover type map, tunnel distribution map and municipal road distribution map, use the random forest machine learning algorithm to select and determine the appropriate location, and select the nearest street lamp for installing the laser water depth automatic observation system; Step 4: According to the installation height and angle of the laser water depth automatic observation system and the initial installation parameters, use MATLAB to write the water depth measurement code, optimize the code and calculate the water depth; Step five: Based on the 5G sensor network, the monitored water depth information is transmitted to the server in real time to realize data integration and mining, and a mobile port APP is developed to synchronize and update the data on the server to the APP in real time, providing users with real-time road water depth and road warning information. The work content of this step is performed in rainy weather.

2. The urban flood disaster early warning method based on 5G and automatic observation technology according to claim 1 is characterized in that: In step 3, the installation location of the laser water depth automatic observation system is determined by the following process: 1) Apply for DEM data, preprocess and analyze DEM data, and extract required terrain parameters; 2) Use ArcGIS to create city contour maps and analyze urban geographical conditions in combination with city DEM elevation maps; 3) Apply for Landsat8 data and use object-based supervised classification methods to obtain urban land cover type maps and the latest municipal road distribution maps of the city; 4) Based on the latest urban land cover type, urban DEM elevation, contour distribution and municipal roads, random forest machine learning technology and Python programming were used to first set the elevation change threshold, then consider the land cover type and population density, screen out the appropriate location for the laser water depth automatic observation system, and find the corresponding street lamps for installing the laser water depth automatic observation system based on the principle of the shortest distance; 5) The street lights finally selected need to be optimized based on the elevation information, and combined with the information provided by the municipal department and field investigations, additional laser water depth automatic observation system stations should be set up in tunnel distribution areas and areas prone to water accumulation.

3. The urban flood disaster early warning method based on 5G and automatic observation technology according to claim 1 is characterized in that: In the step 4, the laser water depth automatic observation system is designed to be a multi-angle rotating structure. The angle between the laser emitting direction of the laser water depth automatic observation system and the street lamp pole is variable, and the angle can be specified for measurement according to actual conditions.

4. The urban flood disaster early warning method based on 5G and automatic observation technology according to claim 3 is characterized in that: The specific installation and layout plan of the laser water depth automatic observation system is as follows: Based on the original street lamp, the distance between the street lamp pole and the ground h The laser water depth automatic observation system is installed at position 1. The signal transmitting end of the laser water depth automatic observation system is at a certain angle to the light pole. When there is no water on the ground, the laser water depth automatic observation system transmits a signal to measure the distance between the ground and the signal transmitting end. a 1. When there is water on the ground, assume that the depth of the water is H , and can measure the distance between the water surface and the signal transmitter a 2. According to the principle of similar triangles, we have: ； The depth of road water H for: ； In the formula, h 1. a 1 and a 2 Known, there is only one value to be evaluated H .

5. The urban flood disaster early warning method based on 5G and automatic observation technology according to claim 4 is characterized in that: When observing the water depth, the laser water depth automatic observation system first designs an algorithm based on the optical characteristics of the water body to determine whether it is a water surface. If it is a water surface, it will be observed directly. If it is an obstacle, the laser water depth automatic observation system will rotate to the flooded road surface and then observe again.

6. The urban flood disaster early warning method based on 5G and automatic observation technology according to claim 1 is characterized in that: In the step five, based on the data collection of the laser water depth automatic observation system, the 5G wireless sensor network is used to transmit the automatically observed and collected water depth information to the server terminal, and then updated to the mobile phone APP visualization interface through the server terminal. Communication technology is used to realize data information sharing, and an integrated early warning system of laser water depth automatic observation system - 5G wireless sensor network - APP query is established.

7. An urban flood disaster early warning system based on 5G and automatic observation technology, characterized in that: include: Street lamps and laser water depth automatic observation system. The laser water depth automatic observation system selects the red light band with a wavelength of 620-680nm, and the laser water depth automatic observation system is installed on street lamps at designated locations in the city; CR1000 data collector, which can provide automatic measurement and control. CR1000 data collector is connected with the laser water depth automatic observation system to realize continuous observation of water depth; LoggerNet software is an application software that integrates communication and data collection. LoggerNet software can set sampling for CR1000 and transmit and view data in real time; The 5G sensor network module transmits the monitored water depth information to the server in real time to achieve data integration and mining; Mobile port APP, the data on the server side is synchronized and updated to the mobile port APP in real time, providing users with road water depth and warning information.

8. The urban flood disaster early warning system based on 5G and automatic observation technology according to claim 7 is characterized in that: A display screen is installed on the street lamp where the laser water depth automatic observation system is located, which can feed back information such as evacuation channels and road water depth on the screen to serve as an early warning.

9. The urban flood disaster early warning system based on 5G and automatic observation technology according to claim 7 is characterized in that: Solar panels are installed on the street lamps where the laser water depth automatic observation system is located, which use solar energy to store energy and perform energy-saving observations, in line with the concept of green and sustainable development.

Images