KR102661257B1 - Server and operation method to predict risk using precipitation and floating population in specific area - Google Patents

Abstract

According to various embodiments, a server includes a processor and a communication interface, and the processor: 1) acquires first precipitation data for a first region from an external server (e.g., a Korea Meteorological Administration server) through the communication interface; 2) Through the communication interface, obtain CCTV image data of an area (e.g., subway station, building, etc.) where an electric water barrier is installed within the first area, and 3) From the CCTV image data, the electric water barrier Obtain density data, velocity data, and congestion data of raindrops in the area where the plate is installed; 4) obtain second precipitation data based on the density data and velocity data of raindrops; 5) obtain the first precipitation data and the second precipitation data; Obtaining predicted rainfall data based on the average value of the rainfall data, 6) calculating a risk index based on the predicted rainfall data and the congestion data, and 7) a control signal that causes the electric windshield to rise based on the risk index. It can be set to transmit to the electric water stop plate. Various other embodiments are also possible.

Description

Server and operation method to predict risk using precipitation and floating population in a specific area {SERVER AND OPERATION METHOD TO PREDICT RISK USING PRECIPITATION AND FLOATING POPULATION IN SPECIFIC AREA}

The present invention relates to a server and operating method that predicts risk using precipitation and floating population in a specific area. Specifically, the risk is measured by measuring congestion through rainfall and floating population through images taken of a specific area or space. It is about a server that can predict the risk of a given space by deriving an index and its operation method.

Recently, flooding damage due to large amounts of precipitation due to heavy rain or typhoons is increasing.

Subway stations are also places that cannot be excluded from damage, and since most subway stations are often located underground or in low areas, it can be said that preparation for flood damage is essential.

Conventionally, various types of water barriers have been installed at the entrances of most subway stations to prevent such flood damage. However, it is necessary to determine whether the water barriers are operating by identifying the current flooding situation or directly predicting the extent of future flood damage by station personnel. In most cases, decisions are being made, so it can be said to be an inefficient system because it is difficult to respond appropriately to the situation.

Accordingly, there is a need for technology that automatically predicts future damage from precipitation by determining the level of precipitation at the entrance to the subway station or in nearby areas, and guides the installation of water barriers automatically according to the risk.

Korean Patent Publication No. 10-2410833 (2022.06.15) Korean Patent Publication No. 10-2023-0105835 (2023.07.12)

The technical problem that the present invention seeks to solve is created to solve the above-mentioned problems. By measuring congestion through precipitation and floating population through images taken of a specific area or space, a risk index is derived and the risk of the space is measured. The purpose is to provide a server that can predict and its operation method.

The technical problems to be achieved by the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below. You will be able to.

According to various embodiments, a server includes a processor and a communication interface, and the processor: 1) acquires first precipitation data for a first region from an external server (e.g., a Korea Meteorological Administration server) through the communication interface; 2) Through the communication interface, obtain CCTV image data of an area (e.g., subway station, building, etc.) where an electric water barrier is installed within the first area, and 3) From the CCTV image data, the electric water barrier Obtain density data, velocity data, and congestion data of raindrops in the area where the plate is installed; 4) obtain second precipitation data based on the density data and velocity data of raindrops; 5) obtain the first precipitation data and the second precipitation data; Obtaining predicted rainfall data based on the average value of the rainfall data, 6) calculating a risk index based on the predicted rainfall data and the congestion data, and 7) a control signal that causes the electric windshield to rise based on the risk index. It can be set to transmit to the electric water stop plate.

According to various embodiments, a method of operating a server includes: 1) acquiring first precipitation data for a first region from an external server (e.g., a Korea Meteorological Administration server) through a communication interface of the server; 2) the server An operation of acquiring CCTV image data of an area (e.g., subway station, building, etc.) where an electric water barrier is installed within the first area through a communication interface, 3) From the CCTV image data, an area where the electric water barrier is installed 4) acquiring second precipitation data based on the density data and velocity data of raindrops, 5) the first precipitation data and the second precipitation amount; An operation of acquiring predicted precipitation data based on the average value of the data, 6) An operation of calculating a risk index based on the predicted precipitation data and the congestion data, 7) Control of causing the electric water barrier to rise based on the risk index. It may include transmitting a signal to the electric water stopper.

The present invention has the effect of providing artificial intelligence recommendation standards that meet standard precipitation risk standards for each subway station/entrance.

In addition, it can provide the effect of enabling real-time response by learning an hourly precipitation prediction artificial intelligence algorithm that reflects the increasing trend of precipitation.

The effects of the present invention are not limited to the effects described above, and potential effects expected by the technical features of the present invention can be clearly understood from the description below.

1 shows a block diagram of an electronic device and a network according to various embodiments of the present disclosure.
FIG. 2 shows a flowchart of the operation of the program 140 included in a server (eg, the electronic device 101 of FIG. 1) according to various embodiments.
3A to 3D are diagrams for explaining examples of electric water shutoff plates according to various embodiments.
FIG. 4 is a diagram illustrating an example of dividing crisis stages according to risk index according to various embodiments.
Figure 5 is a diagram for explaining an example of a siren installed on a water stopper according to various embodiments.

Hereinafter, various embodiments of this document are described with reference to the attached drawings. The examples and terms used herein are not intended to limit the technology described in this document to specific embodiments, and should be understood to include various modifications, equivalents, and/or substitutes for the examples. In connection with the description of the drawings, similar reference numbers may be used for similar components. Singular expressions may include plural expressions, unless the context clearly dictates otherwise. In this document, expressions such as “A or B” or “at least one of A and/or B” may include all possible combinations of the items listed together. Expressions such as “first,” “second,” “first,” or “second,” can modify the corresponding components regardless of order or importance, and are used to distinguish one component from another. It is only used and does not limit the corresponding components. When a component (e.g., a first) component is said to be "connected (functionally or communicatively)" or "connected" to another (e.g., second) component, it means that the component is connected to the other component. It may be connected directly to the component or may be connected through another component (e.g., a third component).

In this document, “configured to” means “suitable for,” “having the ability to,” or “changed to,” depending on the situation, for example, in terms of hardware or software. ," can be used interchangeably with "made to," "capable of," or "designed to." In some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components. For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Electronic devices according to various embodiments of the present document include, for example, smartphones, tablet PCs, mobile phones, video phones, e-book readers, desktop PCs, laptop PCs, netbook computers, workstations, servers, PDAs, and PMPs. (portable multimedia player), MP3 player, medical device, camera, or wearable device. Wearable devices may be accessory (e.g., watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted-device (HMD)), fabric or clothing-integrated (e.g., electronic clothing), In some embodiments, the electronic device may include at least one of body attached (e.g., skin pad or tattoo) or bioimplantable circuitry, for example, a television, a digital video disk (DVD) player, etc. Audio, refrigerator, air conditioner, vacuum cleaner, oven, microwave, washing machine, air purifier, set-top box, home automation control panel, security control panel, media box (e.g. Samsung HomeSync ^TM , Apple TV ^TM , or Google TV ^TM ) , it may include at least one of a game console (e.g., Xbox ^TM , PlayStation ^TM ), an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

1, an electronic device 101 within a network environment 100, in various embodiments, is described. The electronic device 101 may include a bus 110, a processor 120, a memory 130, an input/output interface 150, a display 160, and a communication interface 170. In some embodiments, the electronic device 101 may omit at least one of the components or may additionally include another component. The bus 110 connects the components 110 to 170 to each other and may include circuitry that transfers communication (eg, control messages or data) between the components. The processor 120 may include one or more of a central processing unit, an application processor, or a communication processor (CP). The processor 120 may, for example, perform operations or data processing related to control and/or communication of at least one other component of the electronic device 101.

Memory 130 may include volatile and/or non-volatile memory. For example, the memory 130 may store commands or data related to at least one other component of the electronic device 101. According to one embodiment, memory 130 may store software and/or program 140. The program 140 may include, for example, a kernel 141, middleware 143, an application programming interface (API) 145, and/or an application program (or “application”) 147, etc. . At least a portion of the kernel 141, middleware 143, or API 145 may be referred to as an operating system. Kernel 141, for example, provides system resources (e.g., middleware 143, API 145, or application program 147) used to execute operations or functions implemented in other programs (e.g., : Bus 110, processor 120, or memory 130, etc.) can be controlled or managed. In addition, the kernel 141 provides an interface for controlling or managing system resources by accessing individual components of the electronic device 101 in the middleware 143, API 145, or application program 147. You can.

The middleware 143 may, for example, perform an intermediary role so that the API 145 or the application program 147 can communicate with the kernel 141 to exchange data. Additionally, the middleware 143 may process one or more work requests received from the application program 147 according to priority. For example, the middleware 143 may use system resources (e.g., bus 110, processor 120, or memory 130, etc.) of the electronic device 101 for at least one of the application programs 147. Priority may be assigned and the one or more work requests may be processed. The API 145 is an interface for the application 147 to control functions provided by the kernel 141 or middleware 143, for example, at least for file control, window control, image processing, or character control. Can contain one interface or function (e.g. command). The input/output interface 150, for example, transmits commands or data input from a user or other external device to other component(s) of the electronic device 101, or to other component(s) of the electronic device 101 ( Commands or data received from (fields) can be output to the user or other external device.

Display 160 may be, for example, a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic light-emitting diode (OLED) display, a microelectromechanical system (MEMS) display, or an electronic paper display. It can be included. For example, the display 160 may display various contents (e.g., text, images, videos, icons, and/or symbols, etc.) to the user. The display 160 may include a touch screen and may receive, for example, a touch, gesture, proximity, or hovering input using an electronic pen or a part of the user's body. The communication interface 170, for example, establishes communication between the electronic device 101 and an external device (e.g., the first external electronic device 102, the second external electronic device 104, or the server 106). You can. For example, the communication interface 170 may be connected to the network 162 through wireless or wired communication to communicate with an external device (eg, the second external electronic device 104 or the server 106).

Wireless communications include, for example, LTE, LTE Advance (LTE-A), code division multiple access (CDMA), wideband CDMA (WCDMA), universal mobile telecommunications system (UMTS), Wireless Broadband (WiBro), or Global GSM (GSM). It may include cellular communication using at least one of the System for Mobile Communications). According to one embodiment, wireless communication includes, for example, wireless fidelity (WiFi), Bluetooth, Bluetooth Low Energy (BLE), Zigbee, near field communication (NFC), Magnetic Secure Transmission, and radio. It may include at least one of frequency (RF) or body area network (BAN). According to one embodiment, wireless communications may include GNSS. GNSS may be, for example, Global Positioning System (GPS), Global Navigation Satellite System (Glonass), Beidou Navigation Satellite System (hereinafter “Beidou”), or Galileo, the European global satellite-based navigation system. Hereinafter, in this document, “GPS” may be used interchangeably with “GNSS.” Wired communication may include, for example, at least one of universal serial bus (USB), high definition multimedia interface (HDMI), recommended standard 232 (RS-232), power line communication, or plain old telephone service (POTS). there is. Network 162 may include at least one of a telecommunications network, for example, a computer network (e.g., a LAN or WAN), the Internet, or a telephone network.

Each of the first and second external electronic devices 102 and 104 may be of the same or different type as the electronic device 101. According to various embodiments, all or part of the operations executed in the electronic device 101 may be executed in one or more electronic devices (e.g., the electronic devices 102 and 104, or the server 106). In one embodiment, According to this, when the electronic device 101 is to perform a certain function or service automatically or upon request, the electronic device 101 performs at least some functions associated therewith instead of or in addition to executing the function or service on its own. The other electronic device (e.g., electronic device 102, 104, or server 106) may request the requested function or The additional function may be executed and the result may be transmitted to the electronic device 101. For this purpose, the electronic device 101 may process the received result as is or additionally to provide the requested function or service. For example, cloud computing, distributed computing, or client-server computing technologies may be used.

FIG. 2 shows a flowchart of the operation of the program 140 included in a server (eg, the electronic device 101 of FIG. 1) according to various embodiments.

3A to 3D are diagrams for explaining examples of electric water shutoff plates according to various embodiments.

FIG. 4 is a diagram illustrating an example of dividing crisis stages according to risk index according to various embodiments.

Figure 5 is a diagram for explaining an example of a siren installed on a water stopper according to various embodiments.

In operation 201, the server 106 may obtain first precipitation data for the first region from an external server through the communication interface 170, according to various embodiments.

According to one embodiment, the external server may include a Korea Meteorological Administration server or any other server that can measure precipitation and provide information.

According to one embodiment, the precipitation data and the nth precipitation data in the present invention may include data expressed in the form of 'k [mm] per hour' (n, k are natural numbers).

In operation 203, according to various embodiments, the server 106 may acquire, through the communication interface 170, CCTV image data captured in an area where an electric water barrier is installed within the first area.

According to one embodiment, the area where the electric water barrier is installed may include the entrance to a space where a large number of people can enter, such as the entrance of a subway station or the entrance of a building.

According to one embodiment, the electric water barrier is installed to prevent flood damage, and includes an automatic water barrier with adjustable height, such as SWBS (Smart Vehicle Waterproof System), hydraulic automatic water barrier, buoyancy-type automatic water barrier, and stationary automatic water barrier. It can include all types of water blocking plates used.

Referring to FIGS. 3A to 3D, another example of the electric water stop plate described above can be shown.

Figure 3a shows a raised floor water stopper 310 installed at the entrance of a subway station. The process of operating the floor-rising water stopper 310 can be briefly shown through processes (a) to (e) of FIG. 3B.

Figure 3c shows a roll-type water stopper 320 installed at the entrance of a subway station. The process of operating the roll-type water stop plate 320 can be briefly shown through the processes (a) to (e) of FIG. 3D.

In operation 205, according to various embodiments, the server 106 may obtain, from CCTV image data, density data and velocity data and congestion data of raindrops within an area where the electric water barrier is installed.

According to one embodiment, raindrop density data may be obtained based on the ratio of raindrops to the total CCTV image data at a specific point in time obtained from CCTV image data.

For example, among CCTV video data, the total screen area and the area occupied by raindrops can be calculated on a still image at a specific point in time, and the ratio of the area occupied by raindrops to the total area can be expressed as a percentage. Specifically, assuming that the total area of the screen is 100, if the area of the raindrop at the first viewpoint is 50, the density data of the raindrop at the first viewpoint is 50%, and the area of the raindrop at the second viewpoint is 30. , the density data of raindrops at the second time point can be expressed as 30%.

According to one embodiment, the raindrop speed data is obtained by obtaining the first position of the first raindrop at the first time point and the second position of the first raindrop at the second time point after the first time point obtained from CCTV image data, It can be obtained based on the time difference between the first and second viewpoints and the position difference between the first and second locations.

For example, by specifying one raindrop among the CCTV image data, the first position of the raindrop at the first point in time is obtained, and the second position at the second point in time is obtained after a certain time has passed from the first point in time. , the speed of the raindrop can be calculated using the commonly known speed formula using the distance difference between the first and second positions and the time difference between the first and second time points. Specifically, assuming that one raindrop moves 10 cm after 10 seconds, the speed of the raindrop can be expressed as 1 cm/s or 0.01 m/s.

According to one embodiment, the congestion data includes the first number of people moving in the first direction at the first time point, the second number of people moving in the second direction, and the number of people moving in the first direction at the second time point obtained from CCTV image data. Obtain the number of the third person moving and the number of the fourth person moving in the second direction, and obtain the time difference between the first and second time points and the number of the first person, the second person, the third person, and the fourth person. It can be obtained based on . According to one embodiment, congestion data may be determined within the range of 0 to 100.

Specifically, congestion data refers to congestion data at a second time point, which is the same time point as the current time point, and can represent the congestion level at the second time point when the congestion level at the first time point is set to 50.

For example, assuming that subway congestion data is obtained, the first direction can be designated as the direction of the subway entrance, and the second direction can be designated as the direction opposite to the subway entrance. In addition, the number of people A and the number of people heading in the second direction B can be obtained from the first viewpoint through the CCTV image. Likewise, at a second time point after a specific time point from the first time point, the number C of people heading in the first direction and the number of people heading in the second direction D can be obtained. Here, the congestion level can be obtained through the change in the number of people entering and leaving at the second time point compared to the first time point through the E(A-B) value, F(C-D) value, and time difference between the first and second time points.

At operation 207, according to various embodiments, server 106 may obtain second precipitation data based on density data and velocity data of raindrops.

According to one embodiment, the second precipitation data includes the difference between the raindrop density data at the first time point and the raindrop density data at the second time point, and the raindrop velocity data at the first time point and the raindrop velocity data at the second time point. It can be obtained based on the difference between .

Specifically, using the change in the raindrop density data at the second time point compared to the raindrop density data at the first time point and the change in raindrop speed data at the second time point compared to the raindrop speed data at the first time point, Assuming this change is in the form of a linear function, applying it to a linear regression model can predict the density and velocity data of raindrops after a certain point in time to obtain second precipitation data at a specific point in time. According to one embodiment, the server 106 determines the amount of change in the density data of raindrops at a second time point compared to the density data of raindrops at a first time point and the change in raindrop density data at a second time point compared to the speed data of raindrops at a first time point. By inputting the change in velocity data into an artificial intelligence model (e.g., neural network-based prediction model, linear regression model, etc.), the second rainfall data at a certain point can be predicted as the density data and velocity data of raindrops after a certain point in time. You can. In this case, the artificial intelligence model can be learned based on the change in raindrop density data and the change in raindrop speed data over time, and the correlation between the change in raindrop density data and the change in raindrop speed data By learning the correlation, second precipitation data (e.g., density data and/or velocity data of raindrops) after a specific point in time corresponding to the input raindrop density data and/or velocity data can be predicted.

In operation 209, according to various embodiments, the server 106 may obtain predicted precipitation data based on an average value of the first precipitation data and the second precipitation data.

Specifically, it can be said that both the first precipitation data and the second precipitation data represent predicted precipitation data at a specific point in time, and represent the same value with only a difference in the measurement method. Therefore, highly accurate predicted precipitation data can be obtained using the average value of the first precipitation data and the second precipitation data.

In operation 211, according to various embodiments, server 106 may calculate a risk index based on predicted precipitation data and congestion data.

According to one embodiment, the risk index can be calculated from [Equation 1] below according to predicted precipitation data and congestion data.

[Equation 1]

Here, a and b represent weight values determined by user input,

R may represent the risk index, P may represent the predicted precipitation data, and C may represent the congestion data.

For example, the risk index can be calculated by substituting the previously calculated predicted precipitation data and congestion data into [Equation 1] above. The weight in [Equation 1] may be entered directly by the user or may refer to a value that varies depending on the prediction model.

In operation 213, according to various embodiments, the server 106 may transmit a control signal to the electric water barrier to cause the electric water barrier to rise based on the risk index.

For example, referring to Figure 4, the crisis stage according to the risk index can be divided into four stages: serious, dangerous, caution, and general. These steps are only examples, and the user can divide them into more or fewer steps depending on the situation, and the risk index value corresponding to each step can also be adjusted at the user's discretion.

By transmitting a control signal appropriate for the stage of crisis according to the risk index described above to the electric water barrier, it is possible to adjust whether or not to install the electric water barrier or the height of the water barrier to suit the situation.

Here, installing a water barrier means the process of the water barrier rising and blocking the entrance, and conversely, it can also go down to reopen the blocked doorway. In addition, a siren as shown in FIG. 5 is installed on the water barrier, so that safety warning messages such as a siren and a voice guidance can be output when going up or down.

According to various embodiments, a server that predicts risk using rainfall and floating population in a specific area includes a processor and a communication interface, and the processor: 1) sends a message to the first area from an external server through the communication interface; 2) Obtain first rainfall data for the area through the communication interface, obtain CCTV image data of the area where the electric water barrier is installed within the first area, and 3) From the CCTV image data, the electric water barrier Obtain density data, velocity data, and congestion data of raindrops in the installed area; 4) obtain second precipitation data based on the density data and velocity data of raindrops; 5) obtain the first precipitation data and the second precipitation amount; Obtain predicted rainfall data based on the data, 6) calculate a risk index based on the predicted rainfall data and the congestion data, and 7) send a control signal to cause the electric windshield to rise based on the risk index. It can be set to transmit to the water board.

According to various embodiments, the density data of the raindrops is obtained based on the ratio of the raindrops to the entire CCTV image data at a specific point in time obtained from the CCTV image data, and the speed data of the raindrops is , the first position of the first raindrop at the first point in time obtained from the CCTV image data and the second position of the first raindrop at the second point in time after the first point in time are obtained, and the first point in time and the second point in time are obtained. It can be obtained based on the time difference and the position difference between the first location and the second location.

According to various embodiments, the congestion data includes the first number of people moving in the first direction at the first time point, the second number of people moving in the second direction, and the second number of people at the second time point obtained from the CCTV image data. Obtain the third number of people moving in one direction and the fourth number of people moving in the second direction, and obtain the time difference between the first time point and the second time point, the first number of people, the second number of people, and the It can be obtained based on the third person number and the fourth person number above.

According to various embodiments, the second precipitation data includes the difference between the density data of the raindrops at a first time point and the density data of the raindrops at a second time point, the velocity data of the raindrops at the first time point, and the second time point. It can be obtained based on the difference in the speed data of the raindrops at the time.

According to various embodiments, the predicted precipitation data may be obtained based on an average value of the first precipitation data and the second precipitation data.

According to various embodiments, a risk index can be calculated from [Equation 1] below according to the predicted precipitation data and the congestion data.

[Equation 1]

According to one embodiment, a and b may represent weight values determined by user input, R may represent the risk index, P may represent the predicted precipitation data, and C may represent the congestion data.

According to various embodiments, a method of operating a server that predicts risk using precipitation and floating population in a specific area includes: 1) sending data from an external server (e.g., a Korea Meteorological Administration server) to a first area through a communication interface of the server; 2) an operation of acquiring first rainfall data for the server, 2) an operation of acquiring CCTV image data taken of an area (e.g. subway station, building, etc.) where an electric water barrier is installed within the first area through the communication interface of the server, 3) Obtaining raindrop density data, speed data, and congestion data in the area where the electric water barrier is installed from the CCTV image data, 4) Obtaining second precipitation data based on the raindrop density data and speed data 5) acquiring predicted precipitation data based on the first precipitation data and the second precipitation data, 6) calculating a risk index based on the predicted precipitation data and the congestion data, 7) the risk It may include transmitting a control signal that causes the electric water barrier to rise based on the index to the electric water barrier.

As used in this document, the term “module” or “unit” includes a unit comprised of hardware, software, or firmware, and can be used interchangeably with terms such as logic, logic block, component, or circuit, etc. there is. A “module” or “unit” may be an integral part, a minimum unit that performs one or more functions, or a part thereof. A “module” or “unit” may be implemented mechanically or electronically, e.g., known or to be developed application-specific integrated circuit (ASIC) chips, field-programmable FPGAs (FPGAs), that perform certain operations. gate arrays), or programmable logic devices, and may be executed by the processor 120. At least a portion of the device (e.g., modules or functions thereof) or method (e.g., operations) according to various embodiments includes instructions stored in a computer-readable storage medium (e.g., memory 130) in the form of a program module. It can be implemented as: When the instruction is executed by a processor (eg, processor 120), the processor may perform the function corresponding to the instruction. Computer-readable recording media include hard disks, floppy disks, magnetic media (e.g. magnetic tape), optical recording media (e.g. CD-ROM, DVD, magneto-optical media (e.g. floptical disks), built-in memory, etc. The instruction may include code generated by a compiler or code that can be executed by an interpreter. A module or program module according to various embodiments may include at least one of the above-described components. , some parts may be omitted, or other components may be further included. Operations performed by modules, program modules, or other components may be executed sequentially, parallel, iteratively, or heuristically. Some operations may be executed in a different order, omitted, or other operations may be added.

Additionally, the embodiments disclosed in this document are presented for explanation and understanding of the disclosed technical content, and do not limit the scope of the present disclosure. Accordingly, the scope of the present disclosure should be interpreted as including all changes or various other embodiments based on the technical idea of the present disclosure.

Claims (6)

In a server that predicts risk using precipitation and floating population in a specific area,
processor,
Includes a communication interface,
The processor,
1) Obtain first precipitation data for the first region from an external server through the communication interface,
2) Through the communication interface, acquire CCTV image data of the area where the electric water barrier is installed in the first area,
3) From the CCTV image data, obtain raindrop density data, speed data, and congestion data in the area where the electric water barrier is installed,
4) Based on the density data and velocity data of the raindrops, obtain second precipitation data,
5) Obtain predicted precipitation data based on the average value of the first precipitation data and the second precipitation data,
6) Calculate the risk index according to [Equation 1] below based on the predicted precipitation data and the congestion data,
7) Set to transmit a control signal to the electric water barrier to raise the electric water barrier based on the risk index,
server.
[Equation 1]

Here, a and b represent weight values determined by user input,
R represents the risk index, P represents the predicted precipitation data, and C represents the congestion data.
According to clause 1,
The density data of the raindrops is obtained based on the ratio of the raindrops to the total CCTV image data at a specific point in time obtained from the CCTV image data,
The raindrop speed data is obtained by obtaining the first position of the first raindrop at the first point in time obtained from the CCTV image data and the second position of the first raindrop at the second point in time after the first point in time, and the first position Obtained based on the time difference between the viewpoint and the second viewpoint and the position difference between the first location and the second location,
server.
According to clause 1,
The congestion data includes the first number of people moving in the first direction at the first time point, the second number of people moving in the second direction, and the third number moving in the first direction at the second time point obtained from the CCTV image data. Obtain the number of people and the number of fourth people moving in the second direction, and obtain the time difference between the first time point and the second time point and the first number of people, the second number of people, the third number of people, and the first number of people. 4 Acquired based on the number of people,
server.
According to clause 1,
The second precipitation data includes the difference between the raindrop density data at a first time point and the raindrop density data at a second time point, and the raindrop speed data at the first time point and the raindrop speed data at the second time point. Obtained based on the difference between
server.

delete In the method of operating a server that predicts risk using precipitation and floating population in a specific area,
1) Obtaining first precipitation data for a first region from an external server (e.g., Korea Meteorological Administration server) through the communication interface of the server,
2) An operation of acquiring CCTV image data captured in an area where an electric water barrier is installed (e.g., subway station, building, etc.) within the first area through the communication interface of the server,
3) Obtaining raindrop density data, speed data, and congestion data in the area where the electric water barrier is installed from the CCTV image data,
4) An operation of acquiring second precipitation data based on the density data and velocity data of the raindrops,
5) Obtaining predicted precipitation data based on the average value of the first precipitation data and the second precipitation data,
6) Calculating a risk index according to [Equation 1] below based on the predicted precipitation data and the congestion data,
7) Comprising the operation of transmitting a control signal to the electric water barrier to raise the electric water barrier based on the risk index,
How the server operates.
[Equation 1]

Here, a and b represent weight values determined by user input,
R represents the risk index, P represents the predicted precipitation data, and C represents the congestion data.