KR102029865B1 - Variable speed notice device system - Google Patents

Abstract

Disclosed is variable speed notifying device system which includes a variable speed notifying device. The variable speed notifying device comprises: a speed limit display unit including a display for displaying the speed limit of a road; a speed measurement unit measuring a speed of a vehicle traveling on the road; a measurement speed display unit including a display for displaying the measured speed; and a control unit collecting condition information of the road, calculating the speed limit of the road based on the condition information, and controlling to display the calculated speed limit on the speed limit display unit.

Description

Variable Speed Notification System {VARIABLE SPEED NOTICE DEVICE SYSTEM}

The present invention relates to a variable speed notification device system.

Real-time monitoring of road conditions is essential for safe and smooth vehicle operation. However, most of the existing monitoring means use expensive equipment, and it is difficult to monitor the results and feedback accordingly in real time.

Recently, various sensor devices with stable and low price have been produced and sold, and IoT technology that can connect various sensor terminals through a network has been developed and distributed.

Accordingly, the development of a system that determines the state of the road based on the sensor device and the IoT communication network, takes necessary measures, and provides feedback to the driver.

In the case of the existing speed limit signboard, only a fixed number can be displayed. Therefore, drivers must determine that the speed limit is a certain rate of the speed at the time of rainfall or snowfall according to the regulations. There is a problem that depends on the driver's knowledge level or personal judgment.

Moreover, the loop connection of the road includes a curvature section with a large curvature, so it is required to drive at a lower speed than other roads, but drivers often pass the loop connection at a high speed regardless of the possibility of a safety accident. There is this.

Therefore, the development of a system that can provide a variable speed notification based on the state of the road is required.

Patent Registration No. 10-1703001, 2017.01.31 Registration

The problem to be solved by the present invention is to provide a variable speed notification device system.

Problems to be solved by the present invention are not limited to the above-mentioned problems, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention, there is provided a variable speed notification device system including: a speed limit display unit including a display for displaying a speed limit of a road; and a speed measurement unit configured to measure a speed of a vehicle traveling on the road A measurement speed display unit including a display for displaying the measured speed and collecting state information of the road, calculating the speed limit of the road based on the state information, and calculating the speed limit as the calculated speed limit. It includes a variable speed notification device, including a control unit for controlling to display.

The variable speed notification device may be installed in a loop connection path of a road, and the controller may collect state information of the loop connection path, calculate a speed limit of the loop connection path based on the status information of the loop connection path, and The speed limit of the calculated loop connection may be controlled to be displayed on the speed limit display unit.

The apparatus may further include at least one integrated sensor module for collecting the state information of the road, and the controller may calculate the speed limit of the road based on the information collected from the integrated sensor module.

The server stores information collected from the integrated sensor module in a database, transmits the server to determine the state information of the road using the database, and transmits the information collected from the integrated sensor module to the server, and determines the server. The communication unit may further include a communication unit configured to receive a result and transmit the result to the controller.

In addition, the server learns an artificial intelligence model that can determine the state information of the road based on the information stored in the database, and by analyzing the information collected from the integrated sensor module using the artificial intelligence model of the road Status information can be determined.

In addition, the control unit obtains the artificial intelligence model learned by the server from the server, obtains information collected from the integrated sensor module, information collected from the integrated sensor module using the obtained artificial intelligence model By analyzing the state information of the road can be determined.

The apparatus may further include an intelligent deliner for outputting light corresponding to the state information of the road determined by the controller, wherein the controller is configured to obtain a speed of the vehicle measured by the speed measuring unit, The speed may be compared with the calculated speed limit, the output of the intelligent delimiter is determined based on the comparison result, and the output of the intelligent delimiter may be controlled based on the determined output.

The controller may be configured to emit light of the intelligent delineator based on a difference between the measured vehicle speed and the calculated speed limit, road state information, and a distance between the vehicle and the variable speed notification device. , Brightness and color can be determined.

The apparatus may further include a server configured to receive information from the variable speed notification device, wherein the server selects at least one vehicle driver terminal including the loop connection path on a driving route provided by a navigation application, and selects the vehicle. The information on the loop connection path may be provided to a driver terminal, wherein the information on the loop connection path may include status information of the loop connection path and a speed limit of the loop connection path.

The controller may be configured to obtain information about the type of the vehicle, obtain information about the vehicle, including information about the size, driving method, and weight of the vehicle, based on the type of the vehicle. The speed limit corresponding to the type of the vehicle may be calculated based on the vehicle information, the state information of the loop connection path, the length and curvature of the loop connection path.

Other specific details of the invention are included in the detailed description and drawings.

According to the disclosed embodiment, by providing a variable speed based on the state information of the road, and also provides the speed of the driving vehicle together with the safety speed information to the driver, as well as give an alert to the overspeed driver There is this.

In addition, there is an advantage that can provide a variety of safety information by controlling the peripheral device, such as a deliner based on the collected information, or by providing information to the user terminal.

Effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a diagram illustrating a system for determining a road situation using a surface multisensor according to an exemplary embodiment.
2 is a diagram illustrating a structure of a surface multi sensor according to an exemplary embodiment.
3 is a diagram illustrating an example in which a surface multisensor and a surface multisensor are disposed.
4 is a diagram illustrating a surface multisensor further including a motion sensor according to an exemplary embodiment.
5 is a diagram illustrating a multi-gas sensor according to an exemplary embodiment.
6 is a diagram illustrating a surface multisensor including a distance sensor according to an exemplary embodiment.
7 and 8 are views showing a surface multi-sensor installed with the expansion seam of the bridge between.
9 is a diagram illustrating an intelligent delimiter according to an embodiment.
FIG. 10 is a diagram illustrating an example of a method of determining deformation of a structure by using an intelligent delineator including a motion sensor.
11 is a diagram illustrating a variable speed notification device according to an exemplary embodiment.
12 is a diagram illustrating a variable speed notification device for obtaining information about a vehicle, according to an exemplary embodiment.
FIG. 13 is a diagram illustrating a variable speed notification device system including an intelligent delimiter, according to an exemplary embodiment.
14 is a diagram illustrating a variable speed notification device system including a server according to an exemplary embodiment.

Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be embodied in various different forms, and the present embodiments only make the disclosure of the present invention complete, and those of ordinary skill in the art to which the present invention belongs. It is provided to fully inform the skilled worker of the scope of the invention, which is defined only by the scope of the claims.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, "comprises" and / or "comprising" does not exclude the presence or addition of one or more other components in addition to the mentioned components. Like reference numerals refer to like elements throughout, and "and / or" includes each and all combinations of one or more of the mentioned components. Although "first", "second", etc. are used to describe various components, these components are of course not limited by these terms. These terms are only used to distinguish one component from another. Therefore, of course, the first component mentioned below may be a second component within the technical spirit of the present invention.

Unless otherwise defined, all terms used in the present specification (including technical and scientific terms) may be used in a sense that can be commonly understood by those skilled in the art. In addition, terms that are defined in a commonly used dictionary are not ideally or excessively interpreted unless they are specifically defined clearly.

As used herein, the term "part" or "module" refers to a hardware component such as software, FPGA, or ASIC, and the "part" or "module" plays certain roles. However, "part" or "module" is not meant to be limited to software or hardware. The “unit” or “module” may be configured to be in an addressable storage medium or may be configured to play one or more processors. Thus, as an example, a "part" or "module" may include components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, Procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. Functions provided within components and "parts" or "modules" may be combined into smaller numbers of components and "parts" or "modules" or into additional components and "parts" or "modules". Can be further separated.

The spatially relative terms " below ", " beneath ", " lower ", " above ", " upper " It can be used to easily describe a component's correlation with other components. Spatially relative terms are to be understood as including terms in different directions of components in use or operation in addition to the directions shown in the figures. For example, when flipping a component shown in the drawing, a component described as "below" or "beneath" of another component may be placed "above" the other component. Can be. Thus, the exemplary term "below" can encompass both an orientation of above and below. Components may be oriented in other directions as well, so spatially relative terms may be interpreted according to orientation.

In the present specification, the computer refers to any kind of hardware device including at least one processor, and according to an embodiment, it may be understood as a meaning encompassing a software configuration that operates on the hardware device. For example, a computer may be understood as including, but not limited to, a smartphone, a tablet PC, a desktop, a notebook, and a user client and an application running on each device.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram illustrating a system for determining a road situation using a surface multisensor according to an exemplary embodiment.

In the present specification, the kind of the road 1 is not limited. For example, the road 1 is not limited to the kind of downtown roads, national roads, highways, etc., and likewise, the material of the road 1 is not limited to such types as asphalt, soil, sand, metal (iron plate), and the like.

In addition, the road 1 may be a road in an open area, a mountain road, a tunnel, or the road 1 may be a road of a bridge.

Referring to FIG. 1, a railing 2 of a road 1 is shown. Handrail 2 is shown according to one embodiment, it may mean a guardrail of the road (1), may mean a safety separator, may mean a guardrail installed in the bridge or before the bridge. This is not restrictive.

In some embodiments, the road 1 may not have a railing 2. In this case, the structures installed on the handrail 2 may be installed on the ground or underground.

In one embodiment, one or more surface multi-sensors 100 and 200 may be installed in the roadway 1. For example, the surface multisensors 100 and 200 may be installed below the surface of the roadway 1.

In one embodiment, the surface multisensors 100 and 200 may be installed at predetermined intervals on the road 1, but the types, installation intervals, and number of the surface multisensors 100 and 200 installed on the road 1 may be provided. Is not limited.

For example, surface multisensors 100 and 200 may be embedded at a predetermined depth from the ground surface of road 1. As another example, the surface multi-sensors 100 and 200 have a predetermined space under the ground surface of the road 1 (for example, when the space provided for installing the sensor or the road 1 is covered with an iron plate or the like). It may be installed in the space.

The surface multisensors 100 and 200 are connected to each of the controllers 310 and 210 by wire or wirelessly. According to a preferred embodiment, the surface multisensors 100 and 200 are wired by wires for price, stability, and speed. It may be connected to the controllers 310 and 210.

In one embodiment, the surface multi-sensors 100 and 200 may be connected to the multi-phase sensor 300. For example, the surface multi-sensor 100 and the multi-phase sensor 300 may be connected in various configurations such as one-to-one, one-to-many, many-to-one and many-to-many, and are not limited to a specific form.

Similarly, the controllers 210 and 310 may also be connected to the surface multi-sensors 100 and 200 in various configurations such as one-to-one, one-to-many, many-to-one and many-to-many, and are not limited to specific forms. In addition, the control unit may be built in or integrated in each surface multi-sensor.

In one embodiment, the control unit 310 may be connected to one or more multi-medium sensor 300, may be built in the multi-memory sensor 300, or may be configured integrally with the multi-memory sensor 300.

In an embodiment, the controller 310 may transmit information collected from the surface multisensor 100 and the multi-medium sensor 300 to the server 10. According to an exemplary embodiment, the controller 310 may directly process information collected from the surface multisensor 100 and the multi-medium sensor 300. In this case, the controller 310 may transmit the information processing result to the server 10.

For example, processing of information collected from the surface multisensor 100 and the multi-medium sensor 300 and a method of obtaining specific information therefrom are not limited, but at least some or all of the methods may be controlled by the controller 310 and Each may be performed at the server 10.

In one embodiment, the server 10 determines the state of the road based on the information collected from the surface multi-sensor 100 and the multi-memory sensor 300, and transmits the determination result to the outside, according to an embodiment May transmit to 310. The controller 310 determines the situation of the road based on the information received from the server 10, and directly determines the situation of the road 1 instead of the server 10 according to the embodiment, or makes a data with the server 10. It is also possible to determine the situation of the road 1 by processing the information in real time directly during transmission and reception.

In addition, the controller 310 may include one or more components that can output the situation of the road (1), for example, display devices, such as displays, speakers, LEDs installed on the road (1) or railings (2) By outputting information on the state of the road by using the driver, the driver can obtain the information.

In an embodiment, the controller 310 may transmit information on the state of the road 1 to a user terminal (for example, a smartphone or a navigation device of the driver) used by the driver using Wi-Fi or beacons.

In an embodiment, the server 10 may process information collected using an artificial intelligence model. For example, the server 10 may learn about an artificial intelligence model using machine learning, input information collected from the surface multisensor 100 into the learned artificial intelligence model, and output the road 1 as its output. Information for determining the state of the "

In an embodiment, the server 10 stores information received from the controller 310 in a database, generates training data based on the information stored in the stored database, and learns an artificial intelligence model using the generated training data. You can.

In an embodiment, the server 10 classifies the information received from the controller 310, extracts one or more features from the classified information, generates one or more parameters from the extracted features, and generates the one or more parameters. Learning data may be generated by labeling a group based on previously identified information. However, the type of the training data and the method of generating the training data are not limited thereto.

In an embodiment, the server 10 may transmit information about the learned artificial intelligence model to the controller 310.

For example, the server 10 may transmit information about one or more weights used in the learned AI model to the controller 310. The controller 310 may obtain an artificial intelligence model by using the information received from the server 10.

In an embodiment, the server 10 may be understood as a kind of computer described above, and according to the embodiment, the server 10 may mean a cloud server.

Currently, in most cases, data generated from a smart device such as the controller 310 or an IoT thing is stored and processed by a main server through a cloud technology.

Cloud services have evolved to provide optimized technologies for processing and storing data in response to environmental changes that require miniaturization of devices such as smartphones and advancement of processing operations.

As a result, cloud service customers could have a reasonable cost structure through a usage-based payment structure. However, problems such as server stability, security issues, and responsiveness still remain.

In particular, the vast amount of data that needs to be processed and stored in the IoT of industrial sectors often needs to maintain urgency, accuracy and security. In this case, current cloud computing technology has its limitations in data processing.

As a result, the concept of fog computing, which extends cloud computing and services to the edges of the network, was introduced, and the concept of using edges more widely than centralized network systems was introduced.

Edge computing enables data processing directly from IoT objects, which has lower computing power but faster response speed than cloud computing, and does not require broadband communication. Edge computing means placing the processor and data near the end (endpoint) rather than sending it to the center (cloud).

Edge computing is a technology that provides instant analysis and reliability compared to the cloud by enabling immediate analysis and application of data at the edge where data is collected.

In one embodiment, edge computing may be applied to the system shown in FIG.

In other words, the controller 310 may function as an “edge” of edge computing.

However, the system according to the disclosed embodiment may utilize cloud and edge computing together. For example, the server 10 may learn an artificial intelligence model and periodically transmit the training result to the controller 310.

In addition, the server 10 may learn and update the artificial intelligence model periodically by synthesizing the information received from the controller 310.

The collected information is basically transmitted to the server 10 through the control unit 310, the server 10 stores it in a database. In addition, the server 10 may analyze the data using the artificial intelligence model, and transmit the analysis result to the controller 310.

The controller 310 may perform data processing and analysis according to an embodiment. For example, the controller 310 may analyze the collected information immediately to determine a situation of the road 1 and may be special to the road 1. When it is determined that there is no abnormal situation, the server 10 may determine the situation of the road 1 by receiving the analyzed information. According to an exemplary embodiment, the controller 310 compares the information analyzed by the controller 310 with the information analyzed by the server 10, updates itself based on the comparison result, or transmits the comparison result to the server 10. Server 10 may assist in updating the AI model.

As another example, the edge may directly analyze and process data when communication with the server 10 is unstable or impossible.

In addition, when the abnormal situation occurs on the road 1 from the server 10, or obtains information that the occurrence of the abnormal situation is predicted, the controller 310 directly analyzes and processes the data for quick response to the road (1). ) Can monitor and respond to abnormal conditions.

In one embodiment, the surface multisensor 100 may include one or more temperature sensors. For example, the surface multi sensor 100 may include two temperature sensors provided at different locations, and may be a sensor device used to determine whether the road 1 is frozen. A detailed configuration of the sensor device used to determine whether the road 1 is frozen will be described later.

At this time, it is possible to determine whether the road 1 is frozen based on the temperature information detected by the two temperature sensors included in the surface multi-sensor 100.

In one embodiment, the freezing of the road may take the form of visible white ice, but may also be difficult to see with the naked eye, such as black ice. In this case, an accident may occur due to the slipping of the vehicle. Therefore, check the location of the freezing and provide information to the driver, or transmit the information to the relevant agencies to remove the freezing or control the area. Can be.

In one embodiment, the server 10 extracts one or more parameters from the temperature information detected from the two temperature sensors included in the surface multi-sensor 100, and whether or not the extracted one or more parameters to freeze the surface of the road (1) Labeling may be performed using the information about, and learning data including the labeled information may be generated.

The server 10 may train the artificial intelligence model using the generated training data. In addition, the server 10 may transmit information about the learned artificial intelligence model to the control unit 310, and the control unit 310 may obtain the learned artificial intelligence model based thereon. The information about the learned AI model may include one or more weight information corresponding to the learning result of the AI model. In addition, the controller 310 may obtain an artificial intelligence model using weight information.

The server 10 may determine whether the road is frozen from the temperature information measured by the surface multi-sensor 100 using the trained model, and predict the freezing probability of the road and the freezing time when the road is not frozen. have.

The server 10 may transmit the determination information about whether the road is frozen or the prediction information about the freezing potential of the road and the time of freezing to the controller 310. The controller 310 receives the information that the road is frozen from the server 10 or the information that the road will be frozen soon, for example, when the possibility of freezing of the road exceeds a predetermined reference value, the freezing situation of the road 1 For real-time monitoring and quick response to the information, the controller 310 may process information collected from the surface multi-sensor 100 to monitor whether the road is frozen. For example, the controller 310 may monitor whether the road 1 is frozen using information collected from the surface multi-sensor 100 during a predetermined time range before and after the road freezing time predicted from the server 10. Can be.

According to an embodiment, when it is determined that the road 1 is frozen, the controller 310 may transmit freezing information of the road to the server 10 and the outside. For example, the controller 310 may output or transmit a message indicating that the road at the location where the surface multi-sensor 100 is installed is frozen using the output device.

In one embodiment, when it is determined that the road 1 is frozen, the controller 310 or the server 10 may determine the time when the road freezes, the degree of freezing of the road, the direction of freezing of the road, the possibility of freezing the road, and Predict when the road will freeze.

For example, when it is determined that the road 1 is frozen, the controller 310 determines whether the freezing is resolved or further progresses based on the temperature and the change in temperature measured by the surface multi-sensor 100. You can judge.

In addition, the freezing may be naturally resolved by a change in temperature, but may also be solved by pressure and friction applied by the vehicle passing through the freezing portion, and a chemical applied to solve the freezing.

When the progress or resolution of the ice is confirmed, the controller 310 may determine the cause and more accurately predict the direction of the ice based on the identified cause. In an embodiment, the control unit 310 obtains ambient temperature information from the multi-phase sensor 300. The control unit 310 is based on the temperature and the change of temperature around the surface multi-sensor 100, and based on the progress direction of freezing and freezing determined based on the information detected from the surface multi-sensor 100, The cause of the resolution can be determined.

For example, if the ambient temperature is gradually lowered or the temperature is maintained below a certain reference value, it can be predicted that freezing will proceed accordingly. If the ambient temperature and the progress of freezing coincide with each other, it may be determined that there are no other external factors, and thus the progress of freezing may be estimated based on the temperature.

On the contrary, it can be determined that freezing is resolved even when the ambient temperature is lowered. In this case, it may be determined that the ice is eliminated by a vehicle driving on the road or a chemical applied to the road, and the cause thereof may be more specifically determined based on the degree, speed, and pattern of the freezing.

In this case, the controller 310 may more accurately predict the progress of freezing based on the determined cause.

In one embodiment, the surface multisensor 100 may include at least one distance sensor. The surface multi-sensor 100 may measure the distance between different surface multi-sensors 100 and 200 by using a distance sensor, and determine the state of the road based on the distance sensor. For example, the road 1 may be a road of a bridge. In this case, the one or more surface multi-sensors 100 and 200 may be installed at different positions of the bridge, or may be installed with the expansion seam of the bridge in accordance with the embodiment.

The controller 310 or the server 10 may determine whether the bridge is expanded, contracted, distorted, and the expansion or contraction of the expansion joint according to the distance information received from the one or more surface multi-sensors 100 and 200. .

In an embodiment, the controller 310 or the server 10 may determine whether an abnormal situation occurs in the bridge by comparing the distance information between the one or more surface multi-sensors 100 and 200 with a preset reference value. In addition, based on the rate of change of the distance between the one or more surface multi-sensors (100 and 200) it can be determined whether or not the abnormal situation occurs in the bridge or the risk of occurrence.

In another embodiment, the server 10 may train an artificial intelligence model based on distance information obtained from one or more surface multi-sensors 100 and 200. The server 10 may extract one or more parameters based on the distance information obtained from the one or more surface multi-sensors 100 and 200, and learn by labeling the extracted parameters based on whether or not the previously observed bridges are abnormal. You can generate data.

According to an embodiment, the learning data may further include parameters extracted from information on vibration, movement, or weather conditions of the bridge.

The server 10 may learn an artificial intelligence model based on the generated training data, and transmit information about the learned artificial intelligence model to the controller 310. Similarly, the controller 310 may acquire the learned artificial intelligence model based on the received information.

As in the case of monitoring whether the road is frozen, the controller 310 and the server 10 may determine the situation of the bridge based on information collected from the surface multi-sensor 100, and the controller 310 monitors in real time. If necessary and when the communication with the server 10 is not smooth, it is possible to directly monitor the situation of the bridge by analyzing the data.

For example, when real-time monitoring is required, when the distance between the one or more surface multi-sensors 100 and 200 is out of a preset reference range or the distance between the one or more surface multi-sensors 100 and 200 is greater than the change in distance. And when the distance is determined to deviate from the preset reference range within a predetermined time.

In this case, the controller 310 may monitor the distance between the one or more surface multi-sensors 100 and 200 in real time, and determine whether an abnormal situation of the bridge occurs based on this.

In addition, the controller 310 may determine the cause of the abnormal situation in the bridge based on the information collected from the multi-memory sensor 300, or if the occurrence of the abnormal situation occurs. For example, the controller 310 may determine a correlation between weather information including the ambient temperature and humidity of the bridge and an abnormal situation (eg, excessive contraction or expansion of the expansion joint).

According to an embodiment, the controller 310 may obtain weather forecast information. The controller 310 may predict the progress direction of excessive contraction or expansion of the road freezing or the expansion joint of the bridge based on the weather forecast information. For example, if the weather clears up after a certain time and the temperature is expected to rise after a certain time in the freezing situation of the road, the freezing may also be resolved, and conversely, if the weather is expected to be cloudy and the temperature lowers, It can be expected that this will be strengthened. If it is predicted that the freezing will be strengthened or if the freezing is not expected to be resolved, the controller 310 may request a means for freezing the outside.

In addition, when the expansion joints of the bridge is excessively open or close to each other, similarly, information about temperature and humidity changes over time, and whether the distance between the expansion joints naturally recovers to a preset reference range and whether You can estimate the time required.

The server 10 may obtain information on whether a problem occurs in the road or a bridge and whether or not the problem is solved, based on the information obtained from the controller 310. If it is determined that the problem is not naturally solved, the server 10 may transmit a message to the agency that can solve the problem, and according to the embodiment may request the control of the road or bridge.

In one embodiment, the system may further include intelligent delinators 400 and 402 that provide the driver with notifications based on road conditions.

In one embodiment, the intelligent delimiters 400 and 402 may be installed at predetermined intervals on the road, and may be installed at both sides of the road at predetermined intervals. Intelligent deliner 400 and 402 may be installed on the railing 2 of the road 1, but is not limited thereto.

In one embodiment, the intelligent delimiter 400 and 402 may reflect the lights of the vehicle, but may include a light emitting unit capable of outputting a light of a specific color. The detailed structure and usage method of the intelligent deliner will be described later.

According to an embodiment, the intelligent delinators 400 and 402 may output lights of different colors according to whether the road 1 is frozen, which is determined based on the information collected by the surface multisensor 100. The intelligent delimiters 400 and 402 may output lights of different colors according to the state of the road determined by the controller obtaining the information collected from the surface multi-sensor 100. It may include at least one of the control unit 210 and 310 and the server 10 shown in.

The controller may transmit the information on the state of the road to the intelligent delimiters 400 and 402, and the intelligent delimiters 400 and 402 may output a color corresponding thereto.

In another embodiment, the controller may transmit the color information based on the state of the road to the intelligent delimiters 400 and 402, and the intelligent delimiters 400 and 402 may output the color received from the controller.

According to an embodiment, the intelligent delimiters 400 and 402 may output lights of different colors, respectively, depending on whether or not the ice on the road 1 in which the intelligent delimiters 400 and 402 are respectively located. For example, the intelligent determinator 402 responds to the freezing state when it is determined that the surface of the road 1 on which the surface multisensor 100 is installed is frozen based on the information collected by the surface multisensor 100. You can output the light of the color.

In an embodiment, the server 10 may obtain location information of each of the intelligent delimiters 400 and 402 and color information output from each of the intelligent delimiters 400 and 402.

The server 10 may generate map information in which a color output from each of the intelligent delimiters 400 and 402 is displayed at each location of the intelligent delimiters 400 and 402. For example, the map information may include a map image or may include navigation information. The server 10 may provide the generated map information to the driver terminal of the driver traveling on the road 1. For example, the driver terminal may include, but is not limited to, a navigation device installed in a driver's smartphone or a vehicle in which the driver drives.

In displaying the navigation information, the driver terminal may display the color information received from the server 10 together with the image of the road displayed on the navigation. Therefore, even when the driver does not look at the intelligent deliner 400 and 402, it is possible to easily determine the freezing state of the road in the traveling direction through the navigation.

In addition, the intelligent deliner 400 and 402 are installed at both sides of the structure (for example, bridges, etc.) including the road 1 at predetermined intervals, and may be used to determine the state of the structure. . Specific methods of utilizing the intelligent delimiters 400 and 402 will be described later.

Hereinafter, with reference to the drawings will be described in detail the structure and method of using the surface multi-sensor.

2 is a diagram illustrating a structure of a surface multi sensor according to an exemplary embodiment.

Referring to FIG. 2, the surface multisensor 100 is illustrated in a cylindrical shape, but the shape of the surface multisensor 100 is not limited thereto.

In one embodiment, the surface multi-sensor 100 includes a housing provided with a space therein, and one or more sensors installed in the housing and a cable for outputting sensor information.

In one embodiment, the housing may be composed of the upper housing 110 and the lower housing 120, as shown in Figure 2, it may be combined into one housing using the coupling means 112.

In one embodiment, the upper housing 110 and the lower housing 120 are coupled to each other, a space in which one or more sensors may be disposed may be provided inside the coupled housing.

In addition, the surface multisensor 100 further includes a waterproof ring 130 coupled between the upper housing 110 and the lower housing 120 to prevent water from penetrating into the surface multisensor 100.

In one embodiment, the surface multi-sensor 100 is installed below the surface of the road, it may be used to determine the freezing of the road using a temperature sensor.

In one embodiment, the surface multisensor 100 includes an external temperature sensor 150 inserted into the upper surface of the upper housing 110 and a lower surface temperature sensor 140 disposed below the upper surface of the upper housing 110. .

The surface multi sensor 100 transmits information sensed by two temperature sensors to the outside, and accordingly, the surface multi sensor 100 transmits information detected from the external temperature sensor 150 to the outside. It includes a cable 142 for transmitting the information sensed from the bottom surface temperature sensor 140 to the outside.

In addition, the surface multi-sensor 100 includes a connection hose pipe 160 for wrapping and protecting the cables (142 and 152).

In one embodiment, the cables 142 and 152 are connected to the control unit 310 along the connection hose pipe (160).

3 is a diagram illustrating an example in which a surface multisensor and a surface multisensor are disposed.

Referring to FIG. 3, the surface multisensor 100 is installed below the surface of the road 1. The surface multi sensor 100 includes an external temperature sensor 150 inserted into an upper surface of the upper housing 110 and a lower surface temperature sensor 140 disposed below the upper surface of the upper housing 110.

The external temperature sensor 150 and the lower surface temperature sensor 140 have different distances from the surface of the road 1, and thus different temperatures are detected from each sensor. According to the disclosed embodiment, the freezing state of the road 1 may be determined based on the difference between the two temperature sensors.

To this end, the external temperature sensor 150 and the lower surface temperature sensor 140 are disposed at different positions of the surface multi-sensor 100, respectively. For example, the external temperature sensor 150 is disposed outside the housing 100. In one embodiment, the external temperature sensor 150 may be disposed to protrude from the top of the housing 100. However, in this case, the external temperature sensor 150 may be easily damaged by an external shock.

Accordingly, referring to FIG. 3, a groove 114 into which an external temperature sensor 150 may be inserted is provided on an upper surface of the housing 100 (that is, an upper surface of the upper housing 110), and an external temperature sensor ( 150 may be inserted into groove 114. The depth of the groove 114 may be set to be greater than the height of the external temperature sensor 150.

In addition, the opening of the groove 114 may be coated to protect the external temperature sensor 150 inserted into the groove 114 from impact or foreign matter. However, the opening of the groove 114 may be coated with a material 116 having a thermal conductivity of more than a predetermined reference value so that the external temperature can be easily transmitted to the external temperature sensor 150. For example, the opening of the groove 114 may be coated with platinum. In addition, the opening of the groove 114 may be coated with gold or silver, but is not limited to a specific material.

In addition, the lower surface temperature sensor 140 may be installed below the upper surface of the housing 100, that is, the upper housing 110. Accordingly, a predetermined distance is generated between the external temperature sensor 150 and the lower surface temperature sensor 140, and measured by the external temperature sensor 150 and the lower surface temperature sensor 140 by the thermal conductivity of the housing 100. There will be a difference in temperature.

In the disclosed embodiment, it is determined whether the road is frozen based on the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference. The external temperature change is transmitted to the surface multisensor 100 installed at the bottom of the surface of the road through the road, at which time a difference occurs in whether the surface of the road is frozen and the degree of heat transfer depending on the degree of freezing. . In addition, the difference occurs in the degree of heat transfer to the external temperature sensor 150 and the lower surface temperature sensor 140.

In one embodiment, such a difference that occurs depending on whether the road is frozen or the degree of freezing may be first analyzed based on a preset database.

For example, when there is a database in which the existing measured information about the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference depending on whether the road is frozen and the degree of freezing is recorded, the surface The control unit of the multi-sensor 100 (in which the control unit is understood as a concept encompassing both the control unit 310 directly connected to the surface multi-sensor 100 and the server 10 connected through a network) includes information stored in a database, By comparing the temperature measured by the currently measured external temperature sensor 150 and the lower surface temperature sensor 140 and the difference, it is possible to determine whether the current road freezes and the degree of freezing.

Furthermore, this difference, which occurs according to whether the road is frozen or the degree of freezing, can be analyzed by learning based on an artificial intelligence model.

For example, when there is a database in which the existing measured information about the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 according to whether the road is frozen and the degree of freezing is recorded, the controller Extracts one or more features based on the information stored in the database, extracts one or more parameters from each feature, and, based on the extracted parameters, the degree of freezing and the degree of freezing of the road observed at the time corresponding to the parameter. Learning data can be generated by labeling.

The controller may train the artificial intelligence model using the generated training data. Accordingly, the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 according to whether the road is frozen or the degree of freezing may be different. Based on the artificial intelligence model that can output whether the road freezes and the degree of freezing can be obtained.

Then, the controller extracts one or more parameters from the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference, inputs the extracted parameters into the learned artificial intelligence model, and outputs the road as the output. It is possible to obtain information on the degree of freezing and the degree of freezing.

In one embodiment, the controller may predict the freezing possibility and the freezing time of the road surface based on the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference.

For example, the controller may determine that the road surface is not currently frozen, based on the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference, the possibility of freezing and freezing of the road surface. Predict the viewpoint.

As described above, the freezing possibility and the freezing time of the road surface may also be determined by a database-based comparison or may be predicted based on the learned AI model.

In addition, if the current road is frozen, the controller may determine the freezing direction and the running speed of the road. For example, the controller may determine whether freezing of the road is to be progressed or resolved based on the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference, and the corresponding direction of travel. You can determine the speed of progress.

In an embodiment, the controller may consider the temperature measured by the external temperature sensor 150 and the lower surface temperature sensor 140 and the difference thereof, as well as weather information received from the multi-meteorological sensor 300 or an external server. It can be determined whether the freezing, the degree of freezing, the possibility of freezing, the time of freezing, the direction and speed of progress.

For example, the controller may determine that freezing is further performed when the ambient temperature received from the multi-phase sensor 300 is less than or equal to a preset reference temperature, and predict that the temperature will be further lowered according to weather information received from an external server. If yes, it can be determined that freezing will proceed further. Similarly, when the ambient temperature is greater than or equal to the preset reference temperature, it may be determined that the icing will be resolved. If the temperature is predicted to rise in the future according to the weather information received from the external server, the icing will be resolved. In this case, the controller can predict the time of elimination of the icing. For example, the prediction of the time of elimination of the ice may be determined based on the current road ice state and the speed of eliminating ice according to the ambient temperature or the predicted temperature.

In one embodiment, if it is determined that the freezing state is to be maintained or further progress, the control unit may transmit the freezing state to the server or an external related organization, and may request follow-up or entry control on the road accordingly.

4 is a diagram illustrating a surface multisensor further including a motion sensor according to an exemplary embodiment.

Referring to FIG. 4, the surface multisensor 100 may further include substrates 170 and 172 including additional sensors. In an embodiment, the substrates 170 and 172 may be disposed in a space provided inside the housing 100.

For example, the surface multisensor 100 may further include a motion sensor disposed on the substrates 170 and 172. The motion sensor is used to detect various motions of the surface multi sensor 100, and may include, for example, a vibration sensor, a gyro sensor, a compass sensor, an acceleration sensor, and the like, but is not limited thereto.

The surface multi sensor 100 may detect vibrations or movements of roads or bridges using a motion sensor.

For example, the vibration caused by the vehicle traveling on the road may be transmitted to the surface multi-sensor 100, and in the case of a bridge, movement due to shaking, contraction, or expansion of the bridge may be transmitted to the surface multi-sensor 100. .

In an embodiment, the surface multi sensor 100 may acquire information about a road, a bridge, and a vehicle driving the same using a motion detection sensor, which may be collected from two temperature sensors as described above. The information may be used together to obtain freezing conditions of the road and additional information related thereto.

According to an embodiment, the controller may recognize a vehicle traveling on a road on which the surface multi-sensor 100 is installed based on information collected from the motion detection sensor. For example, when the vibration is detected by the surface multisensor 100, the controller may determine that the vehicle is traveling on a road on which the surface multisensor 100 is installed.

In addition, the surface multi-sensor 100 may determine the position of the vehicle based on the strength of the vibration. For example, as the vibration is stronger, the vehicle may be determined to be closer to the surface multi-sensor 100, and accordingly, the direction or movement of the vehicle may be determined based on the increase and decrease of the vibration.

The controller may determine whether the vehicle is normally driven based on the vibration detected by the surface multi sensor 100. For example, the control unit may determine whether the wheels of the vehicle slip due to freezing, and may be used to determine whether the road freezes according to the degree of slipping, and whether the slip of the vehicle and an accident occurs accordingly It can also be used to judge.

In addition, the surface multi-sensor 100 may obtain additional information based on the pattern or change as well as the strength of the vibration. For example, the surface multi sensor 100 may determine whether the road freezes and the degree of freezing based on the strength of vibration. For example, when the intensity of vibration detected by the surface multisensor 100 gradually increases, it may be determined that the vehicle is approaching. At this time, the intensity of vibration will be detected the greatest when the vehicle passes over the surface multi-sensor 100, and then will decrease again. At this time, if the maximum value of the detected vibration is smaller than usual, it can be determined that the tire is slightly slippery due to freezing, thereby reducing the vibration.

That is, the controller may determine whether the road freezes and the degree of freezing based on the strength of the vibration detected by the driving vehicle. For example, the controller may determine that the ice is more severe as the maximum value of the vibration detected as the vehicle travels is smaller.

In an embodiment of the present disclosure, the controller may determine whether a slip of the vehicle occurs based on the vibration detected by the surface multi-sensor 100. For example, when the vibration increases and decreases linearly with the approach of the vehicle, it may be determined that the vehicle is driving normally, but based on the maximum value of the vibration, it is detected that some slip occurs and the It can be determined whether it is frozen.

However, when the detected vibration is sharply reduced, that is, when the vibration detected by the surface multi-sensor 100 increases linearly and is not suddenly detected, or when a small value below a predetermined reference value is detected, In the case where the vibration increases or decreases differently from the increase or decrease pattern, it may be determined that the slippage of the wheel of the vehicle greatly occurs due to the freezing of the road.

For example, the controller may determine whether the road is frozen based on the information collected from the two temperature sensors included in the surface multi-sensor 100, and according to an embodiment, the road may be determined based on the information collected from the motion sensor. It can help determine whether the ice is frozen or whether the road is frozen based on information collected from the temperature sensor. When it is determined that the road is frozen, the surface multi-sensor 100 may determine whether slip occurs in a vehicle traveling on the road.

According to an embodiment, when it is determined that slip has occurred, the surface multi-sensor 100 may determine whether an accident has occurred accordingly. For example, when a slip generation is detected in the first surface multi sensor, the first surface multi sensor may transmit a slip generation fact to a surrounding surface multi sensor through a server or other communication means. Subsequently, when detecting the vibration by the first surface multi sensor or another surface multi sensor in the vicinity, it may be determined whether an accident occurs based on the pattern of the vibration.

For example, when the vibration is short and large, it can be estimated as the vibration caused by the collision, and the position of the surface multisensor where the vibration is detected is located toward the traveling direction of the vehicle where it is determined that slip has occurred from the first surface multisensor. In this case, and when the vibration is detected within a predetermined time from the slip occurrence time, the controller may determine that an accident due to the slip has occurred.

In this case, the control unit may notify the fact of the accident through the server, the server requests the camera device installed in the location where the accident is determined to occur to take an image, and obtains the captured image to determine whether the accident occurred and the accident situation can do.

The camera device may be a CCTV installed at a corresponding position, or may be a camera device for accident shooting provided in the multi-memory sensor 300, but is not limited thereto.

5 is a diagram illustrating a multi-gas sensor according to an exemplary embodiment.

In one embodiment, the multi-phase sensor 300 may be installed on the railing 2 of the road 1 as shown in FIG. 1, may be installed on the ground around the road 1, and the installation position may be It is not limited.

Referring to FIG. 5, the multi-phase sensor 300 may include a solar panel 310, a wind speed and wind vane 320, a lightning rod 330, and a drop and drop design 340. The type of the meteorological measurement device and peripheral devices included in the) is not limited thereto. For example, the multi-phase sensor 300 may include a thermo-hygrometer, a camera device, a display, an LED, a motion sensor, an infrared sensor, an ultrasonic sensor, a speed gun module, and the like, but is not limited thereto.

In one embodiment, the multi-phase sensor 300 may further include a battery capable of storing power generated from the solar panel 310.

In addition, the multi-phase sensor 300 may include an IoT wireless communication module that can communicate with the server 10. For example, the multi-memory sensor 300 may include the controller 310 described above.

In addition, the multi-phase sensor 300 may be connected to the surface multi-sensor 100, or may be connected through the control unit 310. The controller 310 may transmit the information collected by the multi-phase sensor 300 and the surface multi-sensor 100 to the server 10, and may function as an IoT edge to process the collected information directly.

In one embodiment, the multi-phase sensor 300 may further include a Bluetooth (beacon) or a Wi-Fi module that can communicate with the driver's terminal (smartphone, navigation, etc.). For example, the multi-memory sensor 300 may output information about a road situation using a display or LED, or may provide information to a driver's terminal using a communication module.

6 is a diagram illustrating a surface multisensor including a distance sensor according to an exemplary embodiment.

In one embodiment, the surface multisensor 100 shown in FIG. 6 measures the distance between different surface multisensors, and may be used to determine a state of a bridge based on the distance multisensor. That is, the surface multisensor 100 shown in FIG. 6 may be installed in a bridge including a road.

Referring to FIG. 6, the surface multi sensor 100 may further include a distance sensor 180 capable of measuring a distance. In one embodiment, the distance sensor 180 may be an ultrasonic sensor. In another embodiment, the distance sensor 180 may be an infrared ranging sensor. In another embodiment, the distance sensor 180 may be a distance sensor in the form of a signal generator and a signal receiver for measuring a distance by receiving a signal generated from the signal generator, but is not limited to a specific type.

In one embodiment, the distance sensor 180 is disposed in the space inside the housing, the housing may be provided with an opening 190 to allow the distance sensor 180 to be exposed to the outside.

Although the surface multi sensor 100 shown in FIG. 6 is shown to include both a temperature sensor, a motion sensor, and a distance sensor, the surface multi sensor 100 according to the disclosed embodiment includes a temperature sensor, a motion sensor, and a distance. One or more of the sensors may be included and the configuration is not limited.

In one embodiment, the distance sensor 180 is used to measure the distance between the surface multi-sensors 100 and 200 installed at different positions.

In one embodiment, when the distance sensor 180 is composed of a signal generator and a signal receiver, the signal generator and the signal receiver may be provided in different surface multi-sensors, respectively, in this case the signal generator and the signal receiver Surface multi-sensors may be installed to face each other.

When the distance sensor 180 is an ultrasonic or infrared sensor, each of the surface multi-sensors 100 and 200 in a direction in which the distance sensor 180 included in the surface multi-sensor 100 faces the other surface multi-sensor 200. Can be installed.

In the case of the surface multisensor 100 including the distance sensor 180, the surface multisensor 100 may be installed at a lower end of the bridge to allow distance measurement between different surface multisensors, or may be installed in a specific space inside the bridge.

For example, the bridge has a space in the form of an empty space covered with an iron plate, in this case, it is possible to install the surface multi-sensor 100 at the bottom of the iron plate.

In one embodiment, the controller may determine the state of the bridge based on the distance information received from the surface multi-sensor 100. For example, if the distance between the surface multi-sensors installed at different locations of the bridge is reduced or increased, this may mean that the bridge is contracted or expanded.

7 and 8 are views showing a surface multi-sensor installed with the expansion seam of the bridge between.

In the case of a bridge, the expansion seam 3 is included, which means a device that can be elastically tightened to compensate for the expansion or contraction of concrete on both sides of the bridge due to the surrounding conditions (weather, etc.) of the bridge.

In one embodiment, the plurality of surface multi-sensors 100 and 200 are installed with the expansion joint 3 interposed therebetween, and the distance between the surface multi-sensors 100 and 200 can be measured using the distance sensor 180. Can be.

The position at which the surface multi-sensors 100 and 200 are installed is not limited, and may be installed above the expansion joint 3 as shown in FIG. 7, and below the expansion joint 3 as shown in FIG. 8. It may be installed as.

That is, the distance between the surface multi-sensors 100 and 200 installed with the expansion and contraction seam 3 interposed by the contraction or expansion of the bridge will vary, and the control unit is based on the distance between the surface multi-sensors 100 and 200. It is possible to determine whether there is a problem with the bridge.

For example, when the distance between the surface multi-sensors 100 and 200 is outside the preset range, the controller may determine that there is a problem with the bridge.

For example, when the distance between the surface multi-sensors 100 and 200 is equal to or less than a predetermined reference value, the controller may determine that the expansion joint 3 is excessively compressed due to the expansion of the bridge. Indeed, when the expansion joint 3 is excessively compressed, the concrete of the expansion joint 3 or the road around the expansion joint 3 may protrude over the road due to pressure.

In this case, not only can interfere with the driving of the vehicle, but also may cause the tire to burst or cause an accident, so it is necessary to quickly identify and take measures.

That is, when the distance between the surface multi-sensors 100 and 200 is outside the preset range, the controller may determine that an abnormal situation has occurred in the bridge and transmit the determination result to the outside. For example, the controller may transmit a determination result to the server 10.

According to an embodiment, the controller transmits the distance information between the surface multi-sensors 100 and 200 to the server 10, the server 10 determines the state of the bridge based on the distance information, and controls the determined information. Can be sent to.

As described above, the server 10 acts as a cloud and the controller operates as an edge, and according to circumstances, the server 10 or the controller analyzes distance information between the surface multi-sensors 100 and 200 to determine the state of the bridge. can do.

In one embodiment, the range which becomes an abnormal condition determination standard of the bridge based on the distance between the surface multi-sensors 100 and 200 may be determined based on the distance that can actually cause a problem in the bridge, In order to prevent this, it may actually be set to a smaller range than the distance at which problems may occur in the bridge.

In an embodiment, the controller determines whether the bridge is problematic based on the distance between the surface multi-sensors 100 and 200 and the change of the distance, and according to the embodiment, may predict the possibility of the bridge and the timing thereof. .

For example, the control unit may determine and predict this by using a comparison or learned AI model based on a database, and the method is similar to the above-described ice determination method.

For example, the controller may collect distance information between the surface multi-sensors 100 and 200 and store the state information of the bridge according to the database. Thereafter, the controller may compare the distance information between the surface multi-sensors 100 and 200 with the information stored in the database to determine whether there is a problem with the bridge.

In addition, the controller may determine the possibility of a problem occurring in the bridge after a predetermined time, based on the information on the change in the distance between the surface multi-sensors 100 and 200.

In addition, when it is determined that there is a problem with the bridge, the controller may predict whether or not the problem should be solved. For example, when the distance between the surface multisensors 100 and 200 is less than or equal to a preset reference value, when the distance between the surface multisensors 100 and 200 tends to increase, it can be predicted that the problem will be solved. In addition, it is possible to predict when the problem will be solved based on the increase speed of the distance.

In addition, the controller may determine whether a problem occurs faster, a problem worsens, or the problem is resolved based on the surrounding weather information and the weather forecast information. For example, when the weather is hot, the concrete expands, and thus the distance between the surface multi-sensors 100 and 200 may be shortened.

In this case, the controller may obtain information on future temperature change based on the obtained weather information, and for example, may predict that the problem due to the expansion of the concrete will also be solved if it is determined that the temperature will decrease.

In addition, when the distance between the surface multi-sensors 100 and 200 is less than or equal to a predetermined threshold, a problem (for example, seams or protrusions of concrete) that cannot be naturally restored to the bridge may occur. In this case, even when the distance between the surface multi-sensors 100 and 200 is not naturally eliminated, the control unit may transmit a recovery request signal and an entry control request signal for the road.

In another embodiment, the controller may determine whether there is a problem with the bridge according to the distance between the surface multi-sensors 100 and 200 using the artificial intelligence model.

For example, the controller extracts one or more parameters from the distance information between the surface multi-sensors 100 and 200, inputs the extracted parameters into the learned AI model, and outputs a bridge problem, that is, expansion joints. It is possible to determine whether or not the problem of (3) occurs.

In addition, the controller may determine the problem occurrence potential and problem occurrence time of the bridge as a output of the AI model, and furthermore, the problem solving potential and problem solving timing.

As the learning method of the AI model, the above-described AI model learning method for freezing detection may be used. For example, the controller may collect distance information between the surface multi-sensors 100 and 200, extract one or more features from the collected information, and extract one or more parameters from each feature. The controller may acquire information on whether an abnormality occurs in the bridge at a time corresponding to each parameter, and generate the learning data by labeling the parameter.

The controller may train the artificial intelligence model using the generated training data. The AI model can be used to determine whether the bridge is in trouble, the likelihood of the problem, the time of the problem, the possibility of solving the problem and the time of the solution.

In one embodiment, the controller may obtain additional information by using a motion sensor included in the surface multi-sensor.

For example, the surface multi sensor 100 may determine the vibration and the movement of the bridge by using the motion detection sensor. For example, the surface multi-sensor 100 can determine the movement due to the expansion or contraction of the bridge, and when a problem occurs in the expansion joint (3), the concrete or seam protrudes, it can also detect the vibration caused by this have.

The controller may determine whether the expansion joint 3 has an abnormality, the likelihood of occurrence of the abnormality, and the timing of the occurrence of abnormality, based on the information detected by the motion detection sensor as described above, and based on the information detected by the motion detection sensor. The result may be compared, verified, and corrected with the result determined based on the distance between the surface multi-sensors 100 and 200.

According to an embodiment of the present disclosure, the surface multi sensor 100 may acquire information about a vehicle driving on a road using a motion detection sensor. As described above, when the vehicle travels on the road, the vibration detected by the surface multi-sensor 100 gradually increases, and then gradually decreases after the maximum value.

In one embodiment, the controller may determine the driving state of the vehicle based on the vibration detected by the surface multi-sensor 100. For example, the controller may determine whether the vehicle travels on a flat surface or on a road with irregularities. In this case, the unevenness may mean a seam or concrete that protrudes due to the expansion of the bridge.

In an embodiment, when the distance between the surface multi-sensors 100 and 200 is equal to or less than a preset reference value, the controller may perform a monitoring operation to confirm whether an actual problem occurs.

For example, the monitoring operation may include determining a driving state of vehicles traveling on a bridge using a motion sensor. For example, it is normal that vibration increases and decreases and disappears due to driving of a vehicle, whereas vibration caused by driving of a vehicle decreases momentarily, when vibration is not detected at one moment, or vibration is irregularly detected. In this case, the controller may determine that irregularities are generated in the bridge, so that the vehicle travels over the irregularities and does not generate vibrations instantaneously or emits vibrations that are not linear and have irregular changes.

The vibration pattern according to the state of the road and the driving state of the vehicle may be collected through experiments or observations, and may be stored in a database. In one embodiment, the controller may determine the state of the road and the driving state of the vehicle according to the simple comparison with the database or the similar range comparison. In another embodiment, the controller may learn an artificial intelligence model based on a database and use the same to train the artificial intelligence model from information collected by the surface multisensor.

In one embodiment, the vibration sensed by the surface multi-sensor 100 may be due to the driving of one vehicle, but may be a combination of the vibrations generated by the driving of a plurality of vehicles are overlapped and received. The above-described embodiments have been described based on the case in which one vehicle travels on the surface multi-sensor 100 for convenience of description, but vibrations due to driving of a plurality of vehicles may be received according to a situation.

In this case, the controller may determine the driving state of the vehicle traveling on the road based on the change in the vibration received from the surface multi-sensor 100. For example, when vibrations caused by driving are simultaneously received by two vehicles, the entire vibration may be drastically reduced even when slip is generated for one of the vehicles. For example, in this case, the vibration of one vehicle or a part thereof may be reduced while the vibration of two vehicles is received, and the controller may determine the slip occurrence based on the vibration of the two vehicles.

In an embodiment, the controller may separate the respective vibrations based on the characteristics of the vibrations generated by each vehicle. For example, different vibration patterns may occur according to the type of the vehicle, the shape of the wheel, the weight of the vehicle, the traveling speed, and the like, and the increase and decrease of the vibration may occur differently according to the position of the vehicle. The controller may separate the vibration signal for each vehicle from the vibration signal in which different vibration patterns overlap. In an embodiment, the controller may compare the vibration signals obtained from the plurality of surface multi-sensors and separate the vibration signals for each vehicle from the vibration signals.

In one embodiment, a method of extracting the vibration signal for each vehicle from the vibration signal superimposed on the vibration signal according to the driving of the plurality of vehicles may also be performed based on the artificial intelligence model.

In another embodiment, an artificial intelligence model capable of determining whether the above-described slip, slip, disturbance of travel due to unevenness, or the like may be learned from a vibration signal in which vibrations of a plurality of vehicles are superimposed.

For example, learning data may be generated by extracting one or more features and parameters according to a vibration signal in which vibrations of a plurality of vehicles are superimposed, and labeling whether or not a problem occurs according to an actual observation. have. The controller may train the artificial intelligence model based on the generated training data, and the learned artificial intelligence model generates the above-described problem situations based on a parameter extracted from a vibration signal in which vibrations of a plurality of vehicles are superimposed. It can be determined whether or not, the type, or the likelihood of occurrence.

9 is a diagram illustrating an intelligent delimiter according to an embodiment.

Referring to FIG. 9, an intelligent delimiter 400 is shown. As shown in FIG. 1, the intelligent delimiter 400 may be installed at a predetermined interval on the railing 2 of the road 1, but is not limited thereto.

Referring to FIG. 9, the intelligent delimiter 400 includes a solar film 410. In one embodiment, the intelligent delimiter 400 may be driven using power generated from the solar film 410. The intelligent delimiter 400 stores a power generated from the solar film 410, and includes a power supply and a battery for supplying power to the intelligent delimiter 400.

In one embodiment, intelligent delimiter 400 includes LED module 420. LED module 420 includes one or more LEDs that can output one or more colors.

According to an embodiment, the intelligent deliner 400 may output light of different colors according to the icing state of the road 1. For example, the intelligent delimiter 400 may output a red color when the road 1 is frozen, a yellow color when the freezing of the road 1 is expected or a risk of freezing, and a green color when there is no freezing risk. It is not limited to this.

In one embodiment, the intelligent delimiter 400 may include reflecting means for reflecting the light of the vehicle. For example, the LED module 420 may include a reflector capable of reflecting light of a vehicle, and the reflector may be provided with one or more through holes or lenses for transmitting the light of the LED to the outside.

In another embodiment, the housing of the intelligent delimiter 400 may serve as a reflector. That is, the housing of the intelligent delimiter 400 may be made of a material that is easy to reflect the light of the vehicle.

In one embodiment, the angle of the LED module 420 may be changed according to the situation. The intelligent delimiter 400 may include a power unit that may change the angle of the LED module 420.

For example, when the surroundings are bright (daytime, etc.), the LED module 420 may be arranged to face the driving car. Therefore, the LED module 420 may emit light of color according to the freezing state of the road toward the driver of the driving car.

As another example, when the surroundings are dark (night, etc.), the LED module 420 may be disposed in an oblique direction with the driving car, or may be disposed in the direction of the surface of the road. When the LED light is emitted in the direction of the driver when the surroundings are dark, the visual field may be obstructed. Therefore, the LED module 420 may be disposed in an oblique direction with the driving car. As another example, the LED module 420 may be arranged to emit light toward the surface of the road. When the surrounding is dark, the road reflects the light emitted from the LED module 420 to produce a state in which the road shines in the corresponding color. In this way, it is possible to intuitively convey information about whether the road freezes to the driver.

In addition, when the road is frozen, the light of the LED module 420 is better reflected, thereby transmitting the freezing state of the road more clearly and intuitively.

In one embodiment, intelligent delimiter 400 includes a communication module. For example, the intelligent delimiter 400 may include an IoT communication module. In this specification, the IoT communication module may include Cat.M, RoLa, LTE-M, and the like, but is not limited thereto.

In an embodiment, the intelligent deliner 400 may further include an icing sensor, a temperature sensor, a humidity sensor, a fog sensor, and the like, and the multi-phase sensor 300 and the surface multi-sensor 100 described herein. It may also include one or more sensors included in. In this case, the intelligent delimiter 400 may directly collect information without a separate sensor device and control the LED module 420 based on the collected information to output a light of a color corresponding to the state of the road.

In one embodiment, the intelligent delimiter 400 may further include a motion detection sensor. As described above, the motion detection sensor may include a vibration sensor, a gyro sensor, a compass sensor, and the like, and may include an altitude sensor according to an embodiment.

FIG. 10 is a diagram illustrating an example of a method of determining deformation of a structure by using an intelligent delineator including a motion detection sensor.

Referring to FIG. 10, an intelligent determinator 400, 402, and 404 installed at predetermined intervals on a structure including the road 1 and an example of determining deformation of the structure using the intelligent deliner 400 are illustrated.

Referring to FIGS. 10A to 10C, examples in which deformation of a structure is generated and examples of determining it by using intelligent delimiters 400, 402, 404, 406, and 408 are illustrated.

In one embodiment, intelligent delimiters 400, 402, and 404 are installed at predetermined intervals on one side of the structure, and the control unit is an intelligent delineator from the motion detection sensor provided in the intelligent delineators 400, 402, and 404. 400, 402, and 404 may collect information about each location and movement.

For example, the controller may obtain information about the height and the movement of the intelligent delimiters 400, 402, and 404 from the altitude sensor provided in the intelligent delimiters 400, 402, and 404. An acceleration sensor, a gyro sensor, or the like may be used to determine the movement of the intelligent delimiters 400, 402, and 404.

As shown in FIG. 10A, when a change occurs in the heights of the intelligent deliners 400, 402, and 404, the controller may determine that the structure is bent. For example, when the height of the intelligent delimiter 402 in the middle of the intelligent deliner 400, 402 and 404 is increased, the controller may determine that the corresponding position of the structure is bent.

In addition, the intelligent delimiters 400, 404, 406 and 408 are installed on both sides of the structure at predetermined intervals, and the control unit is intelligent from the motion detection sensor provided in the intelligent delinators 400, 404, 406 and 408 Information about the position and the movement of each of the naators 400, 404, 406, and 408 may be collected.

For example, as shown in (b) of FIG. 10, the height difference between the intelligent delimiters 400, 406, 404, and 408 facing each other among the intelligent delimiters 400, 404, 406, and 408. Alternatively, if a change occurs, the controller may determine that the structure is distorted.

In addition, the intelligent delimiters 400, 402, 404, 406 and 408 are installed on both sides of the structure at predetermined intervals, and the control unit detects the movements provided in the intelligent delimiters 400, 402, 404, 406 and 408. Information about the position and movement of each of the intelligent delimiters 400, 402, 404, 406, and 408 may be collected from the sensor.

For example, as shown in (c) of FIG. 10, the height of the intelligent delimiter 402 in the middle of the intelligent delimiters 400, 402, 404, 406, and 408 rises and faces each other. When a difference or change in height occurs between the naators 400 and 406, 404 and 408, the controller may determine that the structure is bent and twisted.

11 is a diagram illustrating a variable speed notification device according to an exemplary embodiment.

Referring to FIG. 11, the variable speed notification device 500 includes a speed limit display unit 510 including a display 512 for displaying a speed limit of a road.

In the present specification, the display is understood as a concept including all kinds of output devices capable of visually outputting various information by control. For example, all kinds of output devices capable of outputting different numbers including one or more light emitting means may be included in the display according to the disclosed embodiment.

In addition, the variable speed notification device 500 includes a speed measuring unit 530 for measuring the speed of the vehicle traveling on the road (1).

In one embodiment, the speed measuring unit 530 may include a kind of speed gun for measuring the speed of the object using the Doppler effect, but is not limited thereto.

According to an embodiment, the speed measuring unit 530 may include information about a vehicle traveling on the road 1 including at least one imaging sensor, and also based on an image or an image captured according to an embodiment. You can also measure the speed of the vehicle.

In addition, the variable speed notification device 500 includes a measurement speed display unit 520 including a display 522 for displaying the measured speed. When the measured speed changes as the vehicle travels, the measurement speed display unit 520 may display the measured speed in real time on the display 522.

In one embodiment, the variable speed notification device 500 collects the state information of the road (1), calculates the speed limit of the road (1) based on the state information, and calculates the calculated speed limit And a control unit (not shown) for controlling to display the speed limit display unit.

In one embodiment, the control unit is understood as a meaning encompassing all kinds of devices capable of controlling the operation of the variable speed notification device 500 according to the disclosed embodiment including at least one processor.

In one embodiment, the control unit may be provided inside or outside the variable speed notification device 500, may be combined with the variable speed notification device 500, but wired or wireless with the variable speed notification device 500. The variable speed notification device 500 may be controlled by communicating with the controller.

In one embodiment, the variable speed notification device 500 may further include at least one integrated sensor module 540 for collecting the state information of the road.

For example, the integrated sensor module 540 may include, but is not limited to, a speed sensor, a vibration sensor, a temperature and humidity sensor, a raindrop sensor, and a wind speed sensor.

In one embodiment, the integrated sensor module 540 may include at least some or all of the surface multi-sensor 100 and the multi-phase sensor 300 shown in FIG. 1, but is not limited thereto.

In addition, the controller may obtain the state information of the road based on the information collected from the integrated sensor module 540, and calculate the speed limit of the road.

For example, the state information of the road may include weather conditions such as freezing, rain, fog, wind speed, and earthquake of the road, and information about vehicles driving on the road (including normal situations and dangerous situations such as accidents). May be, but is not limited thereto.

In one embodiment, the control unit may calculate the speed limit of the road based on not only the state information of the road but also information on the road itself. For example, the control unit may calculate the speed limit of the corner section (turn section) lower than the straight section of the road, and also calculate the speed limit of each road based on the characteristics of the road, the accident history, or other restrictions. can do.

In addition, the control unit may calculate the speed limit of the road based on the state information of the road, for example, it is possible to lower the speed limit of the road when it rains, and to further lower the speed limit of the road when the road is frozen. It is not limited thereto.

In the disclosed embodiment, the variable speed notification device 500 may include at least one solar panel 550. For example, the variable speed notification device 500 may be driven using the power generated by the solar panel 550, but is not limited thereto.

In the disclosed embodiment, the variable speed notification device 500 may include at least one lightning rod 560.

12 is a diagram illustrating a variable speed notification device for obtaining information about a vehicle, according to an exemplary embodiment.

In one embodiment, the variable speed notification device 500 may be installed in a loop connection road of the road. Loop connection path is a kind of connection road, unlike the direct connection road is connected to the road through the loop is characterized in that the curvature of the curve is larger than the other connection road.

Accordingly, in the case of a loop connection road, it is required to slow down compared to other roads, so the speed limit is often lower than that of other roads, and the speed limit also needs to be appropriately adjusted according to the road condition information.

Accordingly, the variable speed notification device 500 according to the disclosed embodiment is installed in the loop connection path, collects the status information of the loop connection path, calculates the speed limit of the loop connection path based on the status information of the loop connection path, and calculated The speed limit of the loop connection may be displayed on the speed limit display unit 510.

In addition, the speed of the vehicle 4 driving on the loop connection path may be measured, and the measured speed may be displayed on the measurement speed display unit 520.

According to an embodiment of the present disclosure, the controller may obtain information about the type of the vehicle 4 driving on the loop connection path. For example, the controller may photograph the vehicle 4 using at least one imaging sensor provided in the variable speed notification device 500, and analyze the photographed image to obtain information about the vehicle 4. As another example, the controller photographs the vehicle 4 using at least one imaging sensor provided in the variable speed notification device 500, and recognizes the license plate of the vehicle 4 from the photographed image, thereby registering the license plate corresponding to the license plate. Information on the type of the vehicle 4 can be obtained.

The controller may obtain information about the vehicle 4, including information about the size, driving method, and weight of the vehicle 4, based on the type of the vehicle 4.

For example, the controller may obtain information about the size, driving method (two wheels, front wheels, rear wheels, four wheels) and weight of the vehicle 4 based on the information on the type of the vehicle 4. For example, if there is tuning information or option information registered for the vehicle 4, the controller may reflect the information to obtain information about the vehicle 4.

The control unit corresponds to the vehicle 4 traveling on the road based on the obtained information about the vehicle 4, the state information of the loop connection path on which the vehicle 4 travels, and general information such as the length and curvature of the loop connection path. The speed limit can be calculated.

For example, the degree of slipping on the curve road may be different according to the driving method of the vehicle 4, and the degree of slipping due to the curve driving may be different even when the surface of the road is frozen.

In addition, according to the weight of the vehicle 4 can calculate the degree of sliding due to the centrifugal force applied to the vehicle 4 as well as the frictional force between the vehicle 4 and the road surface, the control unit and the information about the vehicle 4, The speed limit for each vehicle 4 may be calculated based on various information about the loop connection path.

The controller may display the calculated speed limit using the speed limit display unit 510 of the variable speed notification device 500.

FIG. 13 is a diagram illustrating a variable speed notification device system including an intelligent delimiter, according to an exemplary embodiment.

In an embodiment, the intelligent delimiter 400 illustrated in FIG. 13 may correspond to the intelligent delimiter 400 described above with reference to FIGS. 1, 9, and 10.

According to an embodiment, the intelligent deliner 400 may output light corresponding to the state information of the road determined by the controller.

For example, the controller may acquire the speed of the vehicle measured by the speed measuring unit 530 and compare the measured speed of the vehicle with the calculated speed limit.

The controller may determine the output of the intelligent delimiter 400 based on the comparison result, and control the output of the intelligent delimiter 400 based on the determined output.

In one embodiment, the control unit is based on the difference between the measured speed of the vehicle 4 and the calculated speed limit, road status information and the distance between the vehicle 4 and the variable speed notification device 500, the intelligent deliner ( Whether to emit light 400, the light emission pattern, the brightness, and the color may be determined.

For example, the controller may control the intelligent delimiter as the difference between the speed limit displayed on the speed limit display 510 of the variable speed notification device 500 and the speed of the vehicle 4 displayed on the measurement speed display 520 increases. The driver may be alerted by making the light emitting 400 brighter, flashing faster, or flashing red light.

Similarly, if the difference between the speed limit displayed on the speed limit display unit 510 of the variable speed notification device 500 and the speed of the vehicle 4 displayed on the measurement speed display unit 520 is small, the intelligent deliner 400 ) Can be emitted in yellow.

In addition, the controller may control the intelligent delimiter 400 when the speed of the vehicle 4 displayed on the measurement speed display unit 520 is lower than the speed limit displayed on the speed limit display unit 510 of the variable speed notification device 500. It can emit light in green.

The light emitting method of the intelligent delimiter 400 is provided only as an example, and the light emitting method using the intelligent delimiter 400 is not limited thereto.

14 is a diagram illustrating a variable speed notification device system including a server according to an exemplary embodiment.

Referring to FIG. 14, the system including the variable speed notification device 500 may further include a server 10.

In one embodiment, the server 10 may store the information collected from the integrated sensor module 540 described above in a database, and determine the state information of the road using the database.

In one embodiment, the system transmits the information collected from the integrated sensor module 540 to the server 10, a communication unit (not shown) for receiving the determination result of the server 10 and delivers it to the control unit It may further include.

In one embodiment, the communication unit may be provided inside or outside the integrated sensor module 540 or the variable speed notification device 500, and may be integrated as an integrated sensor module 540 or the variable speed notification device 500. Alternatively, the wired or wireless communication with the integrated sensor module 540 or the variable speed notification device 500 may transmit the information collected from the integrated sensor module 540 to the server 10.

In an embodiment, the server 10 may estimate or specifically determine road state information based on information received from the integrated sensor module 540 in the future by using big data accumulated in a database. In accordance with the information measured by the speed measuring unit, it is possible to accurately calculate the speed of the vehicle curve-driving the loop connection path.

In one embodiment, the server 10 may be configured as a cloud server to facilitate real-time information collection and providing the determination result.

In one embodiment, the server 10 may learn an artificial intelligence model that may determine the state information of the road based on the information stored in the database.

For example, the server 10 may extract training data from a database and train the artificial intelligence model using a machine learning method. Thereafter, the server 10 may determine the state information of the road by analyzing the information collected from the integrated sensor module 540 using an artificial intelligence model.

In one embodiment, the artificial intelligence model may also be used to calculate the speed limit of the roadway. For example, the server 10 may use an artificial intelligence model to calculate the speed limit according to the state information of the road, and may specifically adjust the speed limit according to the degree of freezing or precipitation of the road.

In an embodiment of the present disclosure, the controller may obtain an artificial intelligence model learned by the server 10 from the server.

The controller may store the acquired AI model, and the stored AI model may be updated at predetermined intervals.

In an embodiment, the controller acquires information collected from the integrated sensor module 540 and analyzes the information collected from the integrated sensor module 540 by using an artificial intelligence model obtained from a server. The information can be judged and the speed limit calculated.

In one embodiment, the control unit does not transmit information to the server 10 when it is impossible to communicate with the server 10, when the communication with the server 10 is not smooth, or when it is determined that the emergency situation is other, You can analyze the information, process it, and output the results. That is, the controller and the variable speed notification device 500 may function as an IoT edge.

According to an embodiment, the server 10 may provide information to a vehicle driver terminal driving on a road.

For example, the server 10 may provide state information, speed limit information, and the like of various roads processed by the server 10 to a driver terminal of a vehicle traveling on a road, and the method is not limited.

According to an embodiment, the server 10 may select at least one vehicle driver terminal including a loop connection path in which the variable speed notification device 500 is installed on a driving route provided by a certain navigation application.

In an embodiment, the server 10 may provide the vehicle driver terminal with information on the loop connection path, and the information on the loop connection path may include state information of the loop connection path and a speed limit of the loop connection path. .

In one embodiment, the server 10 is connected to the driver terminal of the vehicle within a predetermined distance from the loop connection path in which the variable speed notification device 500 is installed, the status information of the corresponding loop connection path, and according to the speed limit and other precautions accordingly. By providing information in advance, the driver can be guided to prepare before entering the loop connection.

The steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, in a software module executed by hardware, or by a combination thereof. The software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any form of computer readable recording medium well known in the art.

The components of the present invention may be implemented in a program (or an application) and stored in a medium to be executed in combination with a computer which is hardware. The components of the present invention may be implemented as software programming or software elements, and likewise, embodiments may include various algorithms implemented in combinations of data structures, processes, routines or other programming constructs, such as C, C ++. It may be implemented in a programming or scripting language such as Java, an assembler, or the like. The functional aspects may be implemented with an algorithm running on one or more processors.

In the above, embodiments of the present invention have been described with reference to the accompanying drawings, but those skilled in the art to which the present invention pertains may implement the present invention in other specific forms without changing the technical spirit or essential features. I can understand that. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

1: road
2: handrail
10: server
100: surface multi sensor
200: surface multi sensor
210: control unit
300: multi weather sensor
310: control unit

Claims (10)

A variable speed notification device installed in a loop connection road of the road; And
An integrated sensor module for collecting state information of the loop connection path; Including,
The variable speed notification device,
A speed limit display unit including a display for displaying a speed limit to the loop connection;
A speed measuring unit measuring a speed of a vehicle traveling on the loop connection path;
A measurement speed display unit including a display for displaying the measured speed; And
A controller configured to collect state information of the loop connection path from the integrated sensor module, calculate a speed limit of the loop connection path based on the state information, and control to display the calculated speed limit on the speed limit display unit; Including,
The integrated sensor module,
housing;
An external temperature sensor inserted into an upper surface of the housing; And
A lower surface temperature sensor disposed below the upper surface of the housing; Including,
The upper surface of the housing is provided with a groove into which an external temperature sensor is inserted, the external temperature sensor is inserted into the groove, and the opening of the groove is coated with a material having a thermal conductivity of a predetermined reference value or more. Including,
The control unit,
Extracting at least one parameter from the information collected by the surface detection multi-sensor, and inputting the extracted parameter to the artificial intelligence model to determine whether the freezing path to the loop connection,
The artificial intelligence model,
First temperature information detected by the external temperature sensor, second temperature information detected by the lower surface temperature sensor, and information on whether the road surface freezes when the first temperature information and the second temperature information are detected; Characterized in that the learning based on the learning data, including,
Variable speed alarm system. delete delete The method of claim 1,
A server storing information collected from the integrated sensor module in a database and determining state information of the road using the database; And
A communication unit which transmits the information collected from the integrated sensor module to the server, receives the determination result of the server, and transmits the result to the controller; Further comprising,
Variable speed alarm system. The method of claim 4, wherein
The server learns an artificial intelligence model that can determine the state information of the road based on the information stored in the database, and analyzes the information collected from the integrated sensor module using the artificial intelligence model to analyze the state information of the road. To judge,
Variable speed alarm system. The method of claim 5,
The controller acquires an artificial intelligence model learned by the server from the server, obtains information collected from the integrated sensor module, and analyzes the information collected from the integrated sensor module using the acquired artificial intelligence model. By determining the state information of the road by
Variable speed alarm system. The method of claim 1,
An intelligent delineator for outputting light corresponding to the state information of the road determined by the controller; More,
The control unit,
Obtaining the speed of the vehicle measured by the speed measuring unit, comparing the measured speed of the vehicle with the calculated speed limit, and determines the output of the intelligent deliner based on the comparison result, and to the determined output To control the output of the intelligent delimiter based on
Variable speed alarm system. The method of claim 7, wherein
The control unit,
Determine whether the intelligent deliner emits light, light emission pattern, brightness and color based on the measured difference between the speed of the vehicle and the calculated speed limit, the state information of the road, and the distance between the vehicle and the variable speed notification device. doing,
Variable speed alarm system. The method of claim 1,
A server for receiving information from the variable speed notification device; More,
The server,
Select at least one vehicle driver terminal including the loop connection path on a driving route provided by a navigation application, and provide information about the loop connection path to the vehicle driver terminal, wherein the information on the loop connection path is the loop. Characterized in that it comprises the status information of the connection path and the speed limit of the loop connection,
Variable speed alarm system. The method of claim 1,
The control unit,
Acquiring information about the type of the vehicle, acquiring information about the vehicle, including information about the size, driving method, and weight of the vehicle based on the type of the vehicle;
Calculating a speed limit corresponding to the type of the vehicle based on the information on the vehicle, the state information of the loop connection path, the length and curvature of the loop connection path,
Variable speed alarm system.

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