KR102219233B1 - Weather risk information system supporting collection, analysis, and disaster forecasting of snow risk information data - Google Patents

Abstract

A meteorological risk information system that supports the collection, analysis, and disaster forecasting of snow risk information data is provided. The weather risk information system is a distributed storage layer consisting of a plurality of storages for storing data, a data system layer for collecting and analyzing data, and a service layer providing a service providing weather risk information based on the collected data and analysis data. Including, the data system layer, the data collection unit for collecting the snow risk information data in a predetermined time unit; A data storage unit controlling distributed storage of the collected snowfall risk information data; And a data analysis unit generating snow disaster impact information based on the collected snow risk information data, wherein the snow risk information data includes at least snow weight data, weather data, terrain information data, and facility data.

Description

Weather risk information system supporting collection, analysis, and disaster forecasting of snow risk information data}

The present invention relates to a meteorological risk information system, and more specifically, to a meteorological risk information system that supports collection, analysis, and disaster forecasting of snow risk information data.

[Explanation of nationally supported R&D]

This study was conducted under the supervision of the Small and Medium Business Technology Information Promotion Agency (SMEs) of the SME technology innovation development (a meteorological risk information platform that supports collecting, analyzing, and predicting snow hazard information data, project specific number: 1425125276, project detail number: S2634316). It was achieved through support.

Due to the abnormal climate, local heavy snow has been frequently occurring in recent years, and the damage caused by heavy snow is increasing significantly. As local heavy snow shows an unpredictable pattern in the affected area, a lot of snow falls even in areas where it does not snow well, increasing the damage. In other words, not only a lot of property damage but also human life is incurred by a lot of unexpected snow, such as a green house complex, a factory site, a livestock house, and a gym building.

The current weather risk information system for snowfall provides information centered on meteorological phenomena based on a numerical model, and simply delivers the expected snowfall and climate information (e.g., 5-20 cm of snow is expected, 15 m A strong wind of more than /s is expected.) The meteorological risk information system providing information centered on meteorological phenomena does not efficiently and directly communicate the danger and severity of snowfall to users, and thus prevents proper preparation or evacuation for snowfall.

In addition, the above-described snow damage is damage caused by the weight of the snow, but the weather risk information system for the current snow cover was performed based on the snow height, as disclosed in Korean Patent Application 10-2015-0187189. In other words, the weight of snow, which should be substantially considered for damage prevention and evacuation, is not reflected in the weather risk information system for snow.

In addition, even if the same amount of snowfall is the same according to the structure and characteristics of the facility and the geographical environment in which the facility is located, the effect on the facility may be different. In order to effectively cope with and prepare for a snow disaster, a meteorological risk information system that provides social and economic impacts in consideration of more basic data is required.

10-2015-0187189 (2015.12.28)

The present invention has been conceived to solve the above-described problems, and provides a weather hazard information system that generates a snow disaster forecast in consideration of the structure and characteristics of facilities, and the geographical environment based on the snow weight.

The meteorological risk information system according to an embodiment of the present invention is a weather risk information system that supports collection, analysis, and disaster forecasting of snow risk information data, and the meteorological risk information system is a distributed storage consisting of a plurality of storages for storing data. It includes a layer, a data system layer that collects and analyzes data, and a service layer that provides a service that provides meteorological risk information based on the collected data and analysis data, and the data system layer includes snow risk in a preset time unit. A data collection unit for collecting information data; A data storage unit controlling distributed storage of the collected snowfall risk information data; And a data analysis unit generating snow disaster impact information based on the collected snow risk information data, wherein the snow risk information data includes at least snow weight data, weather data, terrain information data, and facility data.

In one embodiment, the snow disaster impact information includes at least a snowfall pattern, a snowfall risk according to various types, a snowfall risk map, and the data analysis unit generates a snowfall pattern prediction unit and the snowfall risk and the snowfall It may include a risk calculation unit that generates a risk map.

In one embodiment, the risk level calculation unit sets a risk level for each region or each facility based on the snow risk level, and the snow risk map reflects the risk level for each area or facility on a GIS-based map Can be created.

In one embodiment, the risk calculation unit calculates a single snowfall risk rate based on snowfall weight data, and further considers at least one of the weather data, the terrain information data, the facility data, and the snowfall pattern to the single snowfall risk rate. The snowfall risk can be calculated.

In an embodiment, the snowfall pattern includes an expected amount of snowfall and characteristics of snow, and the snowfall pattern prediction unit may determine the expected snowfall amount and characteristics of the snow based on at least the snowfall weight data and the weather data.

In an embodiment, the weather risk information provided by the service layer may include weather prediction information, a predicted snow amount, and a snow disaster forecast generated based on the snow disaster impact information.

In one embodiment, the service layer may provide a query function for the weather risk information by filtering and providing weather risk information of a user's desired condition.

In one embodiment, the meteorological risk information system is interlocked with an expert crowd system, and the service layer may provide expert weather risk information provided by the expert crowd system together with the snowfall disaster forecast.

In one embodiment, the expert crowd system is configured to perform weather forecasting or weather-related consulting for a specific region and company from an expert group, and selected from an expert database having experts suitable for the requested weather forecast or meteorological consulting. Thus, a curation service that provides the service may be included.

In one embodiment, the expert meteorological risk information may be generated based on an opinion of a group of experts on the collected snow risk information data and the snow disaster impact information.

In one embodiment, the snowfall weight data is data calculated based on the snowfall weight, and is collected from a weighted design already installed at the national meteorological agency or major local government offices, and the weighted design is a lower plate, the lower plate and It may be a snowfall weight data logger that includes an upper plate positioned opposite to each other, and a weight detection sensor positioned between the upper plate and the lower plate, and measures the weight of snow accumulated on the upper plate.

In one embodiment, the meteorological data is collected from an automatic weather observation equipment (AWS) operated by the Meteorological Agency or a device separately installed in a specific area to collect meteorological information of the site, and the terrain data is GIS data and a digital topographic map. The facility data is public data and open data provided by each government office, and may include information on the location, basic structure, material, and year of the facility.

The meteorological hazard information system according to an embodiment of the present invention is based on the snow weight, and generates a snow disaster forecast in consideration of the structure and characteristics of the facility and the geographical environment in which the facility is located. That is, it is more objective and it is possible to predict the weather risk for snowfall based on the damage and direct data of users.

In addition, the meteorological risk information system according to an embodiment of the present invention provides a degree of risk to an area or facility as a visualized data such as a snowfall risk map, so that the risk of snowfall can be more effectively provided to users.

In addition, the meteorological risk information system according to an embodiment of the present invention first provides a snow disaster forecast for areas and facilities with high risk levels, so that coping in a disaster situation and resource use are more efficiently performed.

In addition, the meteorological risk information system according to an embodiment of the present invention may provide a query function for meteorological risk information to filter and provide weather risk information of a user's desired condition.

Furthermore, the meteorological risk information system according to an embodiment of the present invention may provide more reliable information to users by providing expert meteorological risk information provided by the expert crowd system together with a snow disaster forecast to users.

1 shows a schematic system architecture of a meteorological risk information system supporting collection, analysis, and disaster forecasting of snow risk information data according to an embodiment of the present invention.
2 is a block diagram showing the configuration of a data system layer.
3 is a block diagram showing the configuration of a data analysis unit.
4A is an exemplary diagram of a GIS satellite image.
4B is an exemplary diagram of a snowfall risk map reflecting the snowfall risk of the present invention on a GIS basis.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. Throughout the specification, when a part "includes" a certain component, it means that other components may be further included rather than excluding other components unless otherwise stated.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be analyzed as having a meaning consistent with the meaning in the context of the related technology, and should not be analyzed in an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

1 shows a schematic system architecture of a weather risk information system 10 that supports collection, analysis, and disaster forecasting of snow risk information data according to an embodiment of the present invention. The meteorological risk information system 10 according to the present embodiment may collect snowfall risk information data based on heavy snowfall measurement, and provide a snowfall disaster forecast obtained by analyzing the data to related organizations and companies.

In addition, the meteorological risk information system 10 according to the present embodiment may be linked with the expert crowd system 20 built through expert crowd sourcing, and the expert weather risk information generated by the expert crowd system 20 is stored in the snow. It can be provided to users along with the forecast.

Referring to FIG. 1, a weather hazard information system 10 supporting collection, analysis, and disaster forecasting of snow hazard information data according to the present invention includes three layers, for example, a distributed storage layer 100, a data system layer. It consists of 110 and a service layer 120.

The distributed storage layer 100, which is the lowest layer, distributes and stores collected or analyzed information in distributed storage, and performs a function of providing inquired information. A storage system constituting such a distributed storage layer may include a plurality of storage devices in which data is stored. In this case, the storage device may include a plurality of storages (eg, local storage, network storage, etc.) for physically storing data, and each storage device may include a plurality of storage locations.

The data system layer 110 collects data, analyzes and infers data by applying data mining, etc. to generate analysis information, manages (supervises) distributed storage, and analyzes by receiving a request from a service server within the service layer. One or more modules (units) that perform a gateway function that collects and transmits information may be configured.

Some of the plurality of modules (units) constituting the data system layer 110 may be connected to at least one configuration of the service layer 120, and another part of the plurality of modules (units) is the aforementioned storage layer ( 100) may be connected to at least one component.

The service layer 120, which is the highest layer, performs a function of providing various services based on analysis information through web, server, API, and the like. The service layer 120 may provide a service that provides weather risk information based on collected data and analyzed data. That is, the service system constituting the service layer can provide a variety of services based on data analysis to customers according to the customer's request.

Hereinafter, focusing on the configuration of the data system layer, a process in which the meteorological risk information system according to an embodiment of the present invention collects, analyzes, and predicts snowfall risk information will be described in more detail.

2 is a block diagram showing the configuration of a data system layer. 3 is a block diagram showing the configuration of a data analysis unit. 4A is an exemplary diagram of a GIS satellite image. 4B is an exemplary diagram of a snowfall risk map reflecting the snowfall risk of the present invention on a GIS basis.

2 and 3, the data system layer 110 of the weather hazard information system 10 according to an embodiment of the present invention includes a data collection unit 111, a data storage unit 112, and a data analysis unit ( 113).

The data collection unit 111 may collect snow risk information data. The snow risk information data may be basic data for calculating weather risk information according to snowfall. The snow hazard information data may include at least snow weight data, weather data, terrain information data, and facility data.

The snow weight data may be data calculated based on the snow weight, not the snow height. The snow weight data can be collected from the national meteorological agency or the heavy design already installed in the government offices of major local governments. The gravimetric design includes a lower plate, an upper plate positioned opposite to the lower plate, and a weight detection sensor positioned between the lower plate and the upper plate, and may be a snow weight data logger that measures the weight of snow accumulated on the upper plate. The data collection unit 111 may collect snowfall weight data from at least one heavy weighted design in a preset time unit.

The meteorological data may be collected from an automatic weather observation equipment (AWS) operated by the Meteorological Agency or a device separately installed in a specific area to collect weather information of a site. Weather data is information such as temperature (average temperature, maximum temperature, minimum temperature), wind direction, wind speed (average wind speed, maximum wind speed, minimum wind speed), humidity (effective humidity, maximum humidity, minimum humidity), air pressure and precipitation in a specific region. It may include. In addition, the meteorological data may include electric wires, air pressure pattern data, radar image data, and the like of the entire region requiring weather forecasting (eg, all regions of Korea, including both land and sea). In addition, the meteorological data may include not only current data but also future weather prediction information. The data collection unit 111 may collect weather data in a preset time unit.

The topographic information data corresponds to data capable of grasping the topographic characteristics of the observed area. The topographic information data may include GIS data. Here, the GIS data corresponds to a geographic information system generated by collecting information on topographic information such as a general map and related facilities through an artificial satellite. The data collection unit 111 may collect GIS data in a preset time unit.

In addition, the topographic information data may include a 1/25,000-scale digital topographic map issued by the National Geographic Information Institute, and the topographic map is the slope distributed within the unit grid (e.g., the lower end of the foot, the upper end of the foot, the lower end of the mountain, the upper end of the mountain, and the lower end of the mountain. Etc.) and heading (for example, north, northeast, east, southeast, southwest, west, northwest).

Facility data may be public data and open data provided by each government office. Here, the facilities may include buildings that are directly affected by snow, such as plastic houses, factories, livestock houses, gymnasiums, and cultural properties. In addition, the facilities may include road facilities, railroad facilities, and aviation facilities. The facility data may include information on the location, basic structure, characteristics, material, and age (degree of aging) of the facility.

The data collection unit 111 may include a transmission/reception unit (not shown) for collecting the above-described data. The transmission/reception unit (not shown) may collect data from various objects through a communication method through a network. The communication method through the network may be wired communication, wireless communication, 3G, 4G, wired Internet, or wireless Internet. In addition, it may be a core network integrated with a wired public network, a wireless mobile communication network, or a portable Internet, and the TCP/IP protocol and its It may be an open computer network that provides several services that exist in the upper layer, such as HTTP (Hyper Text Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), etc. , Is not limited thereto.

As described above, the data collection unit 111 may collect snowfall risk information data from distributed objects. That is, the automatic weather observation equipment (AWS) and snow weight data are located in physically distributed places, and the data collection unit 111 may collect data from them. The data collection unit 111 may be configured based on a flexible streaming data flow architecture in order to effectively collect a large amount of data in a distributed environment, combine it, and transmit it to another place. The data collection unit 111 may be implemented as, for example, a plume, but is not limited thereto. The data collection unit 111 may provide the currently collected snowfall risk information data to the data storage unit 112 and the data analysis unit 113.

The data storage unit 112 may control distributed storage of collected snowfall risk information data. The snow risk information data may be big data corresponding to a set of large amounts of structured, unstructured, or semi-structured data that exceeds the ability to collect and analyze data with existing database management tools. Here, the structured data is data stored in a fixed field, which can be stored in a relational database such as snow data or weather data, a spreadsheet, or the like. In addition, unstructured data is data that is not stored in a fixed field, such as text documents, images, moving pictures, and audio data. In addition, the semi-structured data is not stored in a fixed field, but includes metadata or schema, such as XML, HTML, text, and the like.

The data storage unit 112 is configured to distribute and manage the collected snowfall risk information data in a plurality of storages. In addition, the data storage unit 112 is configured to distribute and manage the analysis data of the data analysis unit 113 to be described later.

The data storage unit 112 may be implemented as Hadoop, a distributed framework capable of processing a large amount of data in a cluster computer in order to efficiently distribute processing large-scale unstructured/structured data, and a distributed file system HDFS ( Hadoop Distributed File System) and MapReduce framework that can process large volumes of data quickly. However, the present invention is not limited thereto, and other big data integrated management methods may be applied according to data types.

In addition, the data storage unit 112 may store the collected snowfall risk information data so as to be searchable according to the type, characteristic, and time of the collected snowfall risk information data. In addition, the data storage unit 112 may monitor operation states of a plurality of distributed storages.

The data analysis unit 113 may analyze the snow disaster impact information in real time based on the collected snow risk information data. That is, the data analysis unit 113 may calculate snow disaster impact information based on the collected snow weight data, weather data, terrain information data, and facility data. The snow disaster impact information may at least include a snow pattern, a snow risk according to various types, and a snow risk map indicating the snow risk.

Specifically, the data analysis unit 113 includes a snowfall pattern prediction unit 113A and a risk calculation unit 113B.

The snowfall pattern prediction unit 113A may predict a snowfall pattern in real time based on snowfall risk information data. Snowfall patterns correspond to future forecast data for the current snowfall. That is, the snowfall pattern prediction unit 113A may determine how and how much more snow will fall in each area and each facility after the current time. Such a snowfall pattern may include at least an expected amount of snowfall and characteristics of snow to be snowed.

The snow pattern prediction unit 113A may predict a snow amount based on the collected snow weight data and meteorological data. Exemplarily, the snow pattern prediction unit 113A includes a weather-snow load regression model that reflects the collected weather data (temperature, humidity, wind speed, etc.), and calculates the snow amount based on the current snow weight data and weather prediction information. It is predictable. In addition, the snowfall pattern prediction unit 113A may predict the amount of snowfall by further considering at least one of topographic information data or facility data. The amount of snowfall may vary depending on the terrain, and the amount of snowfall may vary depending on the structure of the facility. For example, in highlands and mountainous regions, snowfall can be predicted by setting weights for snowfall, and weights can be set for a corresponding area by setting an area where snowfall occurs more in consideration of the influence of wind. In addition, the snowfall pattern prediction unit 113A may determine the predicted snowfall by comparing current snowfall weight data and weather data with past snowfall weight data and meteorological data.

In addition, the snowfall pattern prediction unit 113A may determine the characteristic (degree of wet snow) of snow to be snowed according to regions or facilities based on the snow risk information data. Depending on the nature of the snow, especially the degree of wetness, the damage caused by the snow cover may differ. Wet snow corresponds to snow with moisture, and it is snow that falls when the temperature is high and has a lot of moisture and strong cohesion. Therefore, damage to facilities occurs more when wet snow occurs than in construction. The snowfall pattern prediction unit 113A may determine the characteristics of snow to be snowed in the future, and the snow characteristics may be applied to future analysis.

The risk calculation unit 113B may calculate a snowfall risk based on snowfall risk information data and snowfall patterns. The risk calculation unit 113B calculates a single snow risk rate based on the snow weight data by the data analysis unit 113. A single snowfall risk rate may be the risk of a snow disaster considering only the snow weight. The data analysis unit 113 may calculate snowfall risk for various types by further considering at least one of weather data, terrain information data, facility data, and snowfall patterns, which are different snowfall risk information data in addition to a single snowfall risk rate.

For example, the risk calculation unit 113B may calculate a snowfall risk according to a building type by further considering facility data to a single snowfall risk rate. For example, in the case of a plastic house building, the risk may be increased compared to a general building.

In addition, the data analysis unit 113 may calculate a snowfall risk according to the terrain characteristics by further considering the terrain characteristics according to the location of the facility. The risk for a specific terrain can be increased by taking into account the influence of the mountain topography, basin type, and sea (East Sea, West Sea, South Sea).

In addition, the risk calculation unit 113B may calculate a snowfall risk according to weather characteristics by further considering weather data. When it is determined that wet snow continues to occur in consideration of the weather data, the risk calculation unit 113B may further increase the risk.

In addition, the risk calculation unit 113B may further calculate a risk of freezing for road facilities, a risk of use of an airport or railroad facility, and the like, based on the snow risk information data and the predicted snowfall.

In addition, the risk calculation unit 113B may estimate the expected time of the collapse of the building and the expected time of the highest risk of the facility by further considering the predicted snowfall to the collapse risk according to the type of building.

The risk calculation unit 113B may set a risk level for each region or each facility based on the calculated snowfall risk. For each facility, the risk level can be set by taking into account the various types of snowfall risk described above. For example, the higher the risk of snowfall, the higher the risk level.

In addition, the risk calculation unit 113B may generate a snowfall risk map in which the snowfall risk according to various types is reflected on a GIS-based map. The snow risk map may be generated by reflecting the risk level in each region or each facility on a GIS-based map. 4B corresponds to an exemplary screen of a snow risk map. In the snow hazard map, each area or each facility can be marked with a different color depending on the current level of risk. For example, an area or facility with a high risk level may be displayed in red color, so that direct risk information on the facility or area may be provided to users. The snow risk map can provide snow risk according to various types. For example, the snowfall risk map may provide a snowfall risk according to a weather environment, a snowfall risk according to a building type, and a snowfall risk according to time, respectively.

Snowfall disaster impact information, which is analysis data generated by the data analysis unit 113, for example, a snowfall pattern, a snowfall risk, and a snowfall risk map may be stored in a plurality of storages through the data storage unit 112.

The data storage unit 112 may provide data constituting a service provided by the service layer 120. In addition, data according to a request of a user using the service layer 120 may be filtered and provided.

The service layer 120 may provide meteorological risk information based on collected data and analysis data. Weather risk information may include snow disaster forecasts generated based on snow disaster impact information. That is, the service layer 120 may provide a snow disaster forecast to users.

Here, the users may be a plastic house, a factory, a livestock house, a gymnasium, a cultural property, etc., which are directly affected by snowfall, and an organization, a government, a local government, a corporation, etc. that must perform a snowfall warning.

As described above, the snow disaster forecast is based on the snow weight, and corresponds to data in consideration of the structure and characteristics of the facility and the geographical environment in which the facility is located. That is, the service layer 120 according to the present embodiment may directly provide the users with the risk of snow cover based on objective data. For example, in a form such as “A plastic house located in a specific area currently has 15 kg of snow, and if the current shape is maintained, there is a possibility of collapse after 3 hours.” By presenting it, you can highlight the dangers of snow.

In addition, since the service layer 120 provides a risk to an area or facility as visualized data such as a snow risk map, the risk of snowfall may be more effectively provided to users.

In addition, snow disaster forecasts can be provided first for areas and facilities with high risk levels. Accordingly, evacuation and relief activities can be performed first for areas and facilities where a disaster will occur, and coping and use of resources in a disaster situation can be performed more efficiently.

In addition, the service layer 120 may provide not only the risk of snowfall, but also meteorological prediction information and predicted snowfall generated based on collected meteorological data and analysis data as the meteorological risk information. In addition, the service layer 120 may provide a query function for meteorological hazard information to filter and provide meteorological hazard information under conditions desired by the user.

Furthermore, the service layer 120 according to the present embodiment may provide expert weather risk information provided by the expert crowd system 20 to users along with the snow disaster forecast and/or weather prediction information.

Here, the expert crowd system 20 may be configured to be included in the meteorological risk information system 10 of the present invention, but is not limited thereto, and is configured as a separate system to include the meteorological risk information system 10 of the present invention. Can be linked.

The expert crowd system 20 may be configured to perform weather forecasting and weather-related consulting for a specific region and company from a group of experts. The expert crowd system 20 may include a curation service that provides a corresponding service by selecting from an expert database having experts suitable for requested weather forecasting and meteorological consulting. Here, the expert database may include experts in various fields, such as a meteorological expert, a facility expert, a topographic expert, and a cultural property building expert. The expert crowd system 20 may select a group of experts specialized in the requested weather forecast and weather-related consulting, and provide more specialized weather forecast and weather-related consulting to users. For example, when a meteorological consulting for a cultural heritage building is requested, a meteorological expert and a cultural heritage building expert may be selected to provide a consulting service for this.

The expert crowd system 20 can share data stored in the distributed storage layer 100 through the data storage unit 112 and provide the weather forecast service and weather-related consulting service based on the stored data and analysis data. I can.

In addition, the expert crowd system 20 may generate expert meteorological risk information based on opinions on weather prediction and/or weather analysis results provided from expert groups in various fields. Specifically, the expert crowd system 20 may collect the opinions of the expert group on the data and analyzed data (snow disaster impact information) collected by the meteorological risk information system 10 of the present invention, and based on this Weather risk information can be created. The data storage unit 112 provides collected data and analyzed data to the expert crowd system 20, and may receive expert meteorological hazard information corresponding thereto. The service layer 120 may provide the provided expert weather risk information to users together with the snow disaster forecast and/or weather forecast information. In other words, it is possible to provide a snow disaster forecast for a specific facility together with an expert's opinion. The meteorological risk information system 10 of the present invention provides expert meteorological risk information together with a snowfall disaster forecast, and can provide more reliable information to users.

Although the above has been described with reference to the embodiments, the present invention should not be analyzed as being limited by these embodiments or drawings, and those skilled in the art will have the spirit and scope of the present invention described in the following claims. It will be understood that various modifications and changes can be made to the present invention within the range not departing from.

10: Weather hazard information system
11: Expert crowd system
100: distributed storage layer
110: data system layer
111: data collection unit
112: data storage unit
113: data analysis unit
120: service layer

Claims (12)

A weather risk information system that supports collection, analysis, and disaster forecasting of snow risk information data.The weather risk information system is a distributed storage layer consisting of a plurality of storages to store data, a data system layer to collect and analyze data, It includes a service layer that provides a service that provides weather risk information based on the collected data and analysis data,
The data system layer,
A data collection unit for collecting snowfall risk information data in a preset time unit;
A data storage unit controlling distributed storage of the collected snowfall risk information data; And
Includes a data analysis unit for generating snow disaster impact information based on the collected snow risk information data,
The snow risk information data includes at least snow weight data, weather data, terrain information data, and facility data,
The snow weight data is data calculated based on the snow weight, and is collected from heavy design installed in the national meteorological office or major local government offices,
The gravimetric design includes a lower plate, an upper plate positioned opposite to the lower plate, and a weight detection sensor positioned between the upper plate and the lower plate, and is a snow weight data logger that measures the weight of snow accumulated on the upper plate,
The data storage unit is implemented as a Hadoop Distributed File System (HDFS) for distributed storage of the collected snow risk information data, and processes the data through MapReduce. The method of claim 1,
The snow disaster impact information includes at least a snow pattern, snow risk according to various types, and snow risk map,
And the data analysis unit includes a snowfall pattern prediction unit that generates the snowfall pattern, and a risk level calculation unit that generates the snowfall risk and the snowfall risk map. The method of claim 2,
The risk level calculation unit sets a risk level for each area or each facility based on the snow risk level,
The snow risk map is a meteorological risk information system, characterized in that the risk level for each region or facility is reflected in a GIS-based map to be generated. The method of claim 2,
The risk calculation unit calculates a single snowfall risk rate based on snowfall weight data, and calculates the snowfall risk by further considering at least one of the weather data, the terrain information data, the facility data, and the snowfall pattern in the single snowfall risk rate. Weather risk information system, characterized in that. The method of claim 2,
The snow pattern includes an expected amount of snow and snow characteristics,
The snowfall pattern prediction unit determines the predicted snowfall and the snow characteristics based on at least the snowfall weight data and the meteorological data. The method of claim 1,
The meteorological risk information provided by the service layer includes weather prediction information, predicted snowfall, and a snowfall disaster forecast generated based on the snow disaster impact information. The method of claim 1,
And the service layer provides a query function for the weather risk information to filter and provide weather risk information under conditions desired by a user. The method of claim 7,
The meteorological risk information system is linked with the expert crowd system,
And the service layer provides expert meteorological risk information provided by the expert crowd system together with the snowfall disaster forecast. The method of claim 8,
The expert crowd system is configured to perform weather forecasting or weather-related consulting for specific regions and companies from expert groups,
The expert crowd system,
A meteorological risk information system comprising a curation service that selects and provides a service by selecting an expert corresponding to a weather forecast or weather-related consulting requested from an expert database. The method of claim 8,
The expert weather risk information is generated based on the collected snow risk information data and an opinion of a group of experts on the snow disaster impact information. delete The method of claim 1,
The meteorological data is collected from an automatic meteorological observation equipment (AWS) operated by the Meteorological Agency or a device separately installed in a specific area to collect meteorological information of the site,
The topographic information data includes GIS data and a digital topographic map,
The facility data is public data and open data provided by each government office, and includes information on the location, basic structure, material, and year of the facility.

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