KR102559390B1 - Meathod for controlling ageographic informationhaving a prediction function of future value of land - Google Patents

Abstract

The present invention selects the range of areas to be analyzed and predicted by referring to national land planning or land planning information managed by national institutions or local governments according to the future value prediction procedure information set by the institutional comprehensive management server, and then evaluates the area according to the evaluation item standard information to predict and calculate the future value of the land in the area. When establishing a national plan or land plan, it is possible to secure an appropriate budget by referring to the future value prediction information of the land in the area, thereby minimizing unnecessary costs due to the execution of national planning or land planning A control method for a map information service system equipped with a value prediction function is provided.

Description

Method for controlling ageographic informationhaving a prediction function of future value of land}

The present invention relates to a control method of a map information service system equipped with a predictive function of the future value of land. In particular, it relates to a control method of a map information service system equipped with a predictive function of the future value of land in which the future value of land in the corresponding zone can be predicted and calculated by selecting a range of areas to be analyzed and predicted by referring to national land planning or land planning information managed by national agencies or local governments according to the future value prediction procedure information set by the institution's comprehensive management server, and then evaluating the corresponding zone according to evaluation item standard information.

In general, a map is a term that refers to data that provides information necessary for each field where information on land, such as topography and facilities, is used as a means for obtaining information on land by humans. In particular, the state or local government uses a map that emphasizes a specific topic for land or building affairs of the state or local government. Based on this, it is indicated using a certain color or symbol. However, these thematic maps produced by the state or local governments had limitations in use because they did not properly record frequently changing contents. In particular, such a geographic information system is also commonly referred to as a GIS information system, and such a geographic information system is a computer-based application system that can collect, store, process, analyze, and output data related to geography, such as residential space, industrial space, infrastructure such as roads and railways, water supply, rivers, mountains, land, and forests. , Urban Planning Information System (UPIS) is a representative example of a geographic information system.

The above urban planning information system (abbreviated as urban planning information) is an integrated information system that can be operated on a national basis. Geographic Information System (GIS) information in which information on topographic maps, geological maps, soil maps, cadastral maps, water supply and sewage facilities, road networks, etc. is combined with a 2-dimensional or 3-dimensional coordinate location system, image data for each topographic map, geological map, image data and information for the corresponding facilities, as well as a number of hierarchically or systematically generated edicts and notification information based on various policies. It can be said to be the overall aggregate of image data and attribute information system. This urban planning information has an infrastructure structure that can integrate, converge, and support various decision-making on urban planning policy establishment and geography-based administrative work, and is implemented to further improve the efficiency of urban planning, maintenance, eco-friendly policy implementation, and facility management, etc. In addition, in the urban planning information, various types of data on various notifications, protocols, figures, POIs, approvals, reservations, permits, etc. of urban planning related to facilities, districts, areas, etc. are built into a DB. Attribute information such as notifications and documents is classified into various hierarchical items including wide areas, regions, districts, zones, and facilities in accordance with law-based city planning and converted into a DB. The urban planning information is map data that is organically combined with such attribute information and GIS information, and is configured to be interlocked with various thematic maps (administrative district map, topographical map, forest map, aerial map, military map, population distribution map, river map, soil map, etc.) created by actual surveying or comprehensively reflecting forecast results. In addition, policymakers, planners, task performers, or managers (hereinafter referred to as users) use and check one or more thematic map data of the urban planning information system to analyze and compare data or information, etc. The subject map data, etc. will be used.

In addition, such urban planning information is mainly used for land suitability evaluation, which is a basic survey to provide quantitative and systematic basis for judgment when planning various land use plans or major facility installation plans by scientifically evaluating the environmental or social values of individual lands by comprehensively considering the environmental, physical, and spatial characteristics of land in order to establish a land management system of prior planning / post-development that guarantees environmental friendliness or sustainable development and harmonizes development and preservation.

Then, referring to FIG. 1 as an example of the conventional GIS information system as described above, various subject maps created by actual surveying or comprehensively reflecting forecast results for land or building affairs of a country or local government, such as administrative district maps, topographical maps, forest maps, aerial maps, military maps, population distribution maps, river maps, soil maps, etc. are organized and stored in organic combination with attribute information and GIS information to be linked to subject map data. 70) and;

An agency management server 71 that generally manages update and input/output of national land planning or land planning information stored in the DB server 70 and produced for the affairs of the state or local government while interworking with the DB server 70;

After connecting to the institution management server 71 via the wired/wireless communication network 72, authentication through the set input/output menu, and then reading or outputting national land planning, land planning, or urban planning information prepared by the necessary state or local government It is configured to include client terminals 73a-n.

On the other hand, in the operation of the conventional GIS information system as described above, various subject maps created by actual surveying or comprehensively reflecting predicted results for land or building affairs of the country or local government transmitted through wired or wireless communication networks 72 from the survey company server 74 selected by the country or local government while interworking with the DB server 70 by the data storage menu set by the agency management server 71, for example, administrative district maps, topographical maps, forest maps, aerial maps, military maps, and population distribution maps , River map, soil quality map, administrative district map, topographic map by scale, underground facility map, national land use plan map, topographic land map, land use status map, urban planning map, road network map, etc. are received and map data is organically combined with attribute information and GIS information. Here, the subject map data of the DB server 70 includes basic attribute information such as land status, elevation, slope, land price, cadastral land, and land category, and image data for space and area. At this time, if the client terminals 73a-n scattered in each region through the wired/wireless communication network 72 want to browse and print necessary documents, for example, official documents that can confirm national land planning or land planning information, the user of the client terminals 73a-n connects to the homepage of the institution management server 71, authenticates through the set input/output menu, and then requests reading or outputting national land planning, land planning, or city planning information prepared by the necessary state or local government. Then, the institution management server 71 calls the corresponding official document requested by the user of the client terminal 73a-n through the input/output menu from the DB server 70 via the wired/wireless communication network 72, and transmits it to the client terminal 73a-n so that it can be read and output on the connected printer or screen. In addition, the agency management server 71 updates the national land planning or land planning information stored in the DB server 70 when the national or local government's national land planning or land planning information is changed and transmitted again during the above process.

However, the conventional GIS information system as described above simply inputs and outputs thematic map information created for land or buildings commissioned by the country or local governments transmitted from the survey company server to the DB server managed by the state or local government level, and no information for predicting the future value of land in areas listed on national planning or land planning information is presented. There was a problem that the project stability of the national or local government projects was also significantly reduced because it was impossible to plan in advance.

Accordingly, the present invention was invented to solve the problems of the prior art as described above. Its purpose is to provide a control method for a map information service system equipped with a function of predicting the future value of land, which can secure an appropriate budget by referring to future value prediction information for the land in the corresponding area when establishing a national plan or land plan, thereby minimizing unnecessary costs caused by the implementation of the national plan or land plan.

Another object of the present invention is to provide a control method for a map information service system equipped with a predictive function of the future value of land, which can significantly improve the business stability of national or local government projects, since long-term projects of national agencies or local governments can be planned in advance by referring to previously calculated future value forecast information for land.

An embodiment of the present invention as described above is a DB management server for registering and storing future value prediction information calculated for land related to national land or land planning together with GIS driven subject map data;

An institutional comprehensive management server that overall controls a function of calculating future values for lands listed in national land planning or land planning information stored in the DB management server while interworking with the DB management server;

It is characterized by providing a map information service system equipped with a predictive function of the future value of land, including a future value prediction server that sequentially evaluates the planned area according to the future value prediction procedure information set for the lands listed in the national land planning or land planning information stored in the DB management server or stored in the DB management server under the functional control of the comprehensive management server of the institution or via wired/wireless communication networks to calculate future value prediction information.

Another feature of the present invention according to an embodiment of the present invention as described above is that the future value prediction server further includes a procedure information setting module for setting future value prediction procedure information to calculate future value prediction information calculated for land related to national land or land planning stored in the DB management server under the functional control of the institution comprehensive management server.

Another feature of the present invention according to an embodiment of the present invention as described above is that the future value prediction server drives the procedure information setting module under the functional control of the institutional comprehensive management server to set the implementation sequence for constructing the future value prediction procedure information or the execution procedure including calculation or weighting, and further includes a function of setting evaluation criteria items to set future value prediction procedure information.

Another feature of the present invention according to an embodiment of the present invention as described above is that the future value prediction server further includes a future value AI module that calculates future value prediction information after assigning weights to lands listed in land planning or land planning information based on evaluation criteria items according to the future value prediction procedure information set by the procedure information setting module.

Another feature of the present invention according to an embodiment of the present invention as described above is that the future value prediction server compares the future value prediction information for land of national land planning or land planning or urban planning information previously stored in the DB management server with the future value prediction information for land of national land planning or land planning or urban planning information input for new or update at a set cycle, corrects the difference according to a set standard, and then transfers the newly calculated future value prediction information of the land to the DB management server. It provides a map information service system equipped with a predictive function of the future value of land, characterized in that it further includes a value comparison module for updating by putting in.

Another feature of the present invention according to an embodiment of the present invention as described above is that the value comparison module further includes a change information display module that compares future value prediction information for land from national land planning or land planning or urban planning information, collects all of the different partial data, puts them in a separate table and stores them, and informs them externally by voice, number, or text through a display panel.

Another feature of the present invention according to one embodiment of the present invention as described above is that the future value prediction server crawls evaluation criteria items for setting future value prediction procedural information uploaded on the Internet through a wired/wireless communication network in relation to the land and building surroundings set through the deep learning function of the AI (artificial intelligence) module under the functional control of the institutional comprehensive management server, crawling, storing them in the DB management server, and transmitting them to the procedural information setting module Land, characterized in that it further comprises an information crawling module. It provides a map information service system equipped with a predictive function of future value.

Another feature of the present invention according to an embodiment of the present invention as described above is that the information crawling module is related to the land and building surroundings set in the evaluation criteria item, direct proximity data, traffic and map data, traffic facility data, pre-sale supply data, sales analysis data, population density data, population increase data, government office information data and school district data, floating population data, commercial area size and distance data, size and distance data of hateful facilities, size and distance data of buildings, roads It provides a map information service system equipped with a predictive function of the future value of land, characterized by crawling further including information and street data, land use analysis data, land area data, land use plan data, and building and land price information data.

Another feature of the present invention according to an embodiment of the present invention as described above is that the information crawling module crawls domestic and foreign real estate analysis information, domestic and foreign economic analysis information, domestic and foreign economic status information, domestic and foreign policy information, and domestic and foreign interest rate analysis information uploaded to the Internet through a wired and wireless communication network through a deep learning function of the AI module while interlocking with the AI module, stores them in a DB management server, and transmits them to a procedure information setting module. service system is provided.

Another feature of the present invention according to one embodiment of the present invention as described above is that the information crawling module works with the AI module, and through the deep learning function of the AI module, the business survey index, producer price index, consumer price index, consumption expenditure, household debt, household income, personal income, etc. Crawling domestic and foreign economic status information, storing it in the DB management server, and transmitting it to the procedure information setting module. It provides a map information service system equipped with a predictive function of the future value of land, characterized in that.

Another feature of the present invention according to an embodiment of the present invention as described above is that the procedure information setting module includes not only natural and environmental aspects due to development but also economic, social, and political issues as consideration factors in the evaluation criteria items for setting the future value prediction procedure information, and also includes opinions of interested parties in the form of digital documents.

Another feature of the present invention according to an embodiment of the present invention as described above is that the evaluation criteria items include cleanliness of the land environment, real estate market price information, water environment around the land, securing living convenience facilities, and amenity.

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the evaluation criterion item, 1) the floating population information (including the resident population) for each day of the week or season for the set land and building surroundings is included in the GIS-based map data, and 2) the distribution status and change plan of apartments, single-family houses, multi-family houses, residential-commercial complexes, shopping malls, buildings, buildings, and lands around the set lands and buildings, including apartments, single-family houses, and multi-household houses , It further includes real estate information consisting of the height, area, year, and scale of any one selected from residential/commercial complexes, commercial buildings, buildings, and buildings, and 3) further including evaluating whether or not there exists a subway station location, a subway station exit location, a tram station location, a tram station exit location, a railroad station location, a railroad station exit location, a bus stop location, a bus terminal location, a transfer center location, and a transfer center exit location around the set land and building, 3) a floating bus stop existing around the set land and building Provides a map information service system equipped with a predictive function of the future value of land, characterized in that it further includes and evaluates information such as demographics, bus stop floating population movement statistics, bus stop floating population pattern statistics, and floating demographics by bus route.

Another feature of the present invention according to an embodiment of the present invention as described above is that the agency comprehensive management server transmits and displays the future value prediction information for the land registered in the national land plan or land planning information finally calculated by the future value prediction server to a preset expert terminal through a wired or wireless communication network, and then receives an emergency correction by the expert and receives the corrected final future value prediction information in a format reset through the expert terminal to update the final future value prediction information in the corresponding land of the DB management server. It provides a map information service system equipped with a predictive function of the future value of land, characterized in that it further includes a diagnosis module.

Another feature of the present invention according to an embodiment of the present invention as described above is that, when an urgent evaluation request for a specific land registered in national land planning or land planning information is input to an administrator terminal or set Internet menu, the agency comprehensive management server executes an urgent evaluation according to the future value prediction procedure information set for the land requested for urgent evaluation through the future value prediction server, and selectively calculates the future value forecast information for the land. Provides a map information service system equipped with a prediction function of.

Another feature of the present invention according to an embodiment of the present invention as described above is that the future value prediction server further includes an emergency adjustment module that immediately reflects and updates the evaluation criteria in an emergency when an evaluation criteria item of the future value prediction procedure information applied to the procedure information setting module is urgently changed due to an emergency change in the national land or land plan or city plan.

Another feature of the present invention according to an embodiment of the present invention as described above is a land future value setting step of setting a preparation procedure for calculating future values for lands registered in GIS driven subject map data of national land or land planning through a future value prediction server;

During the land future value setting step, an evaluation area selection step in which a future value prediction server selects an area to evaluate the future value of lands registered in GIS driven subject map data of a national land or land plan under the functional control of an institutional comprehensive management server;

A land future value analysis step in which, during the evaluation area selection step, the future value prediction server conducts analysis by applying the evaluation standard items to the evaluation area according to the future value prediction procedure information under the functional control of the agency comprehensive management server;

During the land future value analysis step, the future value prediction server calculates using a deep learning method for the lands listed in the national land plan or land planning information for analysis by applying the evaluation criteria items under the functional control of the institution's comprehensive management server, assigns weights and scores, and then calculates future value prediction information and lists the results in the GIS driven subject map data of the land for each item. It provides the control method of the map information service system.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the land future value calculation step, the future value prediction server is directly connected under the functional control of the institutional comprehensive management server or via a wired or wireless communication network. Provided is a control method of a map information service system equipped with a value prediction function.

Another feature of the present invention of the present invention as described above, in the stage of the future value of the present invention as described above, the future value prediction server runs the procedure information settings module under the function control of the institutional management server, and the procedure information is set to set the future value prediction procedure information to calculate the future value prediction information calculated for the land related to the land or land plan stored in the DB management server. It provides a control method of a map information service system provided with predictive functions of the future value of the land, characterized in that it further includes a system.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the future value calculation step of the land, the future value prediction server drives the procedure information setting module under the functional control of the institutional comprehensive management server to set the implementation procedure for calculating the future value prediction procedure information, that is, the future value prediction information, such as the execution sequence or calculation or weighting, and to set the evaluation standard items to set the future value prediction procedure information. Provided is a control method of a map information service system equipped with a value prediction function.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the land future value calculation step (S5), the future value prediction server drives the future value AI module to calculate future value prediction information by assigning weights to lands listed in land planning or land planning information based on evaluation criteria items according to the future value prediction procedure information set by the manager to the procedure information setting module through an input/output device (not shown), and then calculating future value prediction information. It provides a control method of a map information service system equipped with a predictive function of the future value of the characteristic land.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the future value calculation step of the land, the future value prediction server drives a value comparison module to compare the future value prediction information of the land of national land planning or land planning or urban planning information previously stored in the DB management server with each other at a set cycle, and then correcting the difference according to the set criteria Provided is a control method of a map information service system equipped with a predictive function of the future value of land, characterized in that it further comprises a value comparison calculation step of updating the newly calculated future value prediction information of the land in the DB management server.

Another feature of the present invention according to an embodiment of the present invention as described above is that the value comparison calculation step further includes an information display step in which the value comparison module compares the future value prediction information for the land of the national land planning or land planning or urban planning information through the change information display module, collects all of the different partial data, puts them in a separate table and stores them, and informs them externally by voice, number, or text through a display panel. Provided.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the land future value calculation step, the future value prediction server crawls the information uploaded on the Internet through the wired/wireless communication network in relation to the land and building surroundings to the evaluation criteria item for setting the future value prediction procedure information through the deep learning function of the information crawling module and the AI module under the functional control of the institutional comprehensive management server. Provided is a control method of a map information service system equipped with a predictive function of the future value of land, characterized in that it further comprises the step.

Another feature of the present invention according to an embodiment of the present invention as described above is that in the information crawling step, the information crawling module is related to the set land and building surroundings in the evaluation criteria items, direct proximity data, traffic volume and map data, traffic facility data, pre-sale supply data, sales analysis data, population density data, population increase data, government office information data and school district data, floating population data, commercial area size and distance data, size and distance data of hateful facilities, It provides a control method for a map information service system equipped with a predictive function of the future value of land, characterized by crawling further including building scale, road information and distance data, land use analysis data, land area data, land use plan data, and building and land price information data.

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the information crawling step, the information crawling module crawls domestic and foreign real estate analysis information, domestic and foreign economic analysis information, domestic and foreign economic status information, domestic and foreign policy information, and domestic and foreign interest rate analysis information uploaded to the Internet through a wired and wireless communication network through the deep learning function of the AI module while interworking with the AI module in the evaluation criteria item. Provides a control method for a map information service system equipped with a predictive function of the future value of

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the information crawling step, the information crawling module crawls domestic and foreign economic status information such as business survey index, producer price index, consumer price index, consumption expenditure, household debt, household income, personal income, etc., which are uploaded to the Internet through a wired and wireless communication network through the deep learning function of the AI module while interlocking with the AI module in the evaluation criteria items, crawling and storing them in the DB management server Provided is a control method of a map information service system equipped with a function of predicting the future value of land, characterized in that it further includes a function of transmitting to the procedural information setting module.

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the information crawling step, the information crawling module includes not only natural and environmental aspects due to development, but also economic, social, and political issues as consideration factors in the evaluation criteria items, and also includes opinions of interested parties in the form of digital documents.

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the information crawling step, the information crawling module provides a control method for a map information service system equipped with a predictive function of the future value of land, characterized in that the evaluation criteria items include cleanliness of the land environment, additional real estate market price information, water environment around the land, securing living convenience facilities, and amenity.

Another feature of the present invention according to an embodiment of the present invention as described above is that, in the information crawling step, the information crawling module includes 1) daily or seasonal floating population information (including the resident population) for the set land and building surroundings in the additional elements of the real estate market price of the evaluation criteria item in the GIS-based map data, 2) the distribution status of apartments, single-family homes, multi-households, residential-commercial complexes, shopping malls, buildings, buildings and lands around the set lands and buildings, and Including the change plan, but further including real estate information consisting of the height, area, year, and scale of any one selected from among apartments, single-family homes, multi-family homes, residential complexes, shopping malls, buildings, and buildings, 3) Evaluating whether or not there exists a subway station location, a subway station exit location, a tram station exit location, a tram station exit location, a railway station location, a railroad station exit location, a bus stop location, a bus terminal location, a transfer center location, and a transfer center exit location around the set land and building, 3) It provides a control method for a map information service system equipped with a predictive function of the future value of land, characterized by further including and evaluating bus stop floating population statistics, bus stop floating population movement line statistics, bus stop floating population pattern statistics, and floating demographic information by bus route that exist around the set land and buildings.

Another feature of the present invention according to an embodiment of the present invention as described above is that during the future value calculation step of the land, the future value prediction server drives the expert diagnosis module under the function control of the agency comprehensive management server to transmit the finally calculated future value prediction information for the land listed in the national land plan or land planning information to a preset expert terminal through a wired or wireless communication network, display it, receive an emergency correction by the expert, and then receive the corrected final future value prediction information in a format reset through the expert terminal Provided is a control method of a map information service system equipped with a predictive function of the future value of land, characterized in that it further comprises an expert additional diagnosis step of updating the corresponding land of the DB management server with final future value forecast information.

Another feature of the present invention according to an embodiment of the present invention as described above is that during the future value calculation step of the land, the future value prediction server drives the emergency evaluation execution module under the functional control of the institutional comprehensive management server, and when an urgent evaluation request for a specific land registered in the national land planning or land planning information is input to the administrator terminal or set Internet menu, the future value prediction server performs an emergency evaluation according to the future value prediction procedure information set for the land for which urgent evaluation is requested, and selectively executes the corresponding land Provided is a control method of a map information service system equipped with a predictive function of the future value of land, characterized in that it further comprises a selection request calculation step of calculating future value prediction information for.

Another feature of the present invention according to an embodiment of the present invention as described above is that, during the future value calculation step of the land, the future value prediction server drives an emergency adjustment module under the functional control of the institutional comprehensive management server to update the evaluation criteria items in the future value prediction procedure information applied to the procedure information setting module by immediately reflecting the evaluation item criteria in an emergency when an emergency change in national land or land planning or urban planning requires adjustment of the evaluation criteria. A control method for the map information service system provided is provided.

According to the present invention as described above, after selecting the range of areas to be analyzed and predicted by referring to national land planning or land planning information managed by national agencies or local governments according to the future value prediction procedure information set by the institutional comprehensive management server, the area is evaluated according to the evaluation item standard information to predict and calculate the future value of the land in the area. When establishing a national plan or land plan, it is possible to secure an appropriate budget by referring to the future value prediction information of the land in the area, thereby minimizing unnecessary costs due to the execution of national planning or land planning. There is an effect.

In addition, the present invention as described above can efficiently implement land expropriation according to the implementation of the national plan or land plan by referring to the predicted future value of the land previously calculated, so that friction with land owners can be minimized, and the project of a national agency or local government can be planned in advance in the long term by referring to the predicted future value of the previously calculated land.

1 is an explanatory diagram for explaining an example of a conventional GIS information system.
Figure 2 is an explanatory diagram explaining a map information service system equipped with a function of predicting the future value of land according to the present invention.
Figure 3 is an explanatory diagram explaining the future value prediction server provided in the map information service system of the present invention in more detail.
4 is a flowchart of the present invention.

Since the present invention can apply various transformations and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all conversions, equivalents, or substitutes included in the spirit and scope of the present invention. In describing the present invention, if it is determined that a detailed description of related known technologies may obscure the gist of the present invention, the detailed description will be omitted.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

Terms used in this specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, the terms "comprise" or "have" are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but it should be understood that the presence or addition of one or more other features or numbers, steps, operations, components, parts, or combinations thereof is not excluded in advance.

In addition, in describing the present invention, if it is determined that a detailed description of a related known technology may unnecessarily obscure the subject matter of the present invention, the detailed description will be omitted.

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

2 is an explanatory diagram explaining a map information service system equipped with a function of predicting the future value of land according to the present invention, and FIG. 3 is an explanatory diagram explaining a future value prediction server included in the map information service system of the present invention in more detail. FIG. 4 is a flowchart of the present invention.

Referring to FIG. 2, a DB management server (1) for constructing and storing map data organically combined with attribute information and GIS information to be linked with subject map data related to national land or land planning managed by the country or local government, updating these information, and registering and storing the future value prediction information calculated for the land related to the national land or land planning together with GIS-driven subject map data;

In conjunction with the DB management server 1, managing the national land planning or land planning information stored in the DB management server 1 for the affairs of the state or local government, and the land listed in the national land planning or land planning information An institutional comprehensive management server 2 that overall controls the function of calculating future values;

It is configured to include a future value prediction server 4 for calculating future value prediction information by sequentially evaluating the planned area according to the preset future value prediction procedure information for the lands listed in the national land planning or land planning information stored in the DB management server 1 under the functional control of the institutional comprehensive management server 2 or via the wired/wireless communication network 3.

Here, the future value prediction server 4, as shown in FIG. 3, is calculated for the land related to the national land or land planning stored in the DB management server 1 under the functional control of the institutional comprehensive management server 2. A procedure information setting module 5 for setting future value prediction procedure information to calculate future value prediction information.

Here, the future value prediction server 4 drives the procedure information setting module 5 under the functional control of the institutional comprehensive management server 2 to set the implementation sequence for calculating the future value prediction procedure information, that is, the future value prediction information, and the execution procedure such as calculation or weighting, and sets evaluation criteria items to set the future value prediction procedure information.

In addition, the future value prediction server 4 further includes a future value AI (artificial intelligence) module 6 that calculates future value prediction information after assigning weights to lands listed in the national land planning or land planning information based on the evaluation criteria items according to the future value prediction procedure information set by the manager through the procedure information setting module 5 through an input/output device (not shown), for example, by deep learning. For example, the future value AI module 6 It can be quantified and multiplied by a weight to calculate future value prediction information.

On the other hand, the future value prediction server 4 includes a memory and a processor-type future value AI module 6 connected to the memory. In the evaluation criteria item for setting future value prediction procedure information, land transaction information and land sales information related to the set land and building surroundings are crawled through the wired and wireless communication network 3 and stored in the memory.

That is, the future value AI module 6 generates land future prediction information about land transactions and sales prices in a specific area based on information related to land transactions and sales prices of land nationwide based on national land planning or land planning registered on a platform such as an Internet homepage, for example, a homepage of the Korea Land Corporation, set through the wired and wireless communication network 3, and transmits it to the future value prediction server 4. At this time, the future value AI module 6 generates the land future prediction information based on the national land transaction volume and average transaction price information for a specific land, which are based on national land planning or land planning,

When the land price in the specific area (or the first land area) exceeds the preset standard land price and the total transaction volume exceeds the preset standard total transaction volume, land price prediction information corresponding to the addition of the transaction volume in the first land area is generated,

When the transaction volume of the first land area exceeds the standard total transaction volume and the land price of the first land is less than or equal to the standard land price, generating forecast information corresponding to other price increase requirements other than the first land area,

When the transaction volume of the first land district is less than or equal to the standard total transaction volume and the land price of the first land exceeds the average land price, the land price prediction value of the first land district is based on the reference total transaction volume and the average land price of the corresponding land district.

When the transaction volume of the first land district is less than or equal to the standard total transaction volume and the land price of the first land is less than or equal to the average land price, the land price prediction information for the first land district is generated and applied to the future value prediction information of the land.

In addition, the future value AI module 6 generates the future value prediction information by further including a recommended keyword for predicting the land value value, but the land transaction information and land sales information related to the set land and building surroundings registered in the platform are wired and wireless communication network (3). Extracts a first keyword excluding research from all characters included in an Internet homepage, such as a homepage of Naver Real Estate or Real Estate Association website, where information related to land transactions and selling prices is provided,

The keyword evaluation score is calculated by applying Equation 1 to the corresponding land based on the land sales price of the corresponding land zone including the first keyword, the total land transaction volume of the corresponding land zone, and the homepage providing the land price and transaction volume including the first keyword.

[Equation 1]

Here, ESG (Estimates grade) means the keyword evaluation score, NHTV (Number of Housing Transaction Value) means the land price of the corresponding area, TTA (Total Transaction Amount) means the total land transaction volume, and 1TA (Transaction Amount) means the first individual land transaction volume.

Therefore, the future value prediction server 4 calculates the future value AI module 6 by applying Equation 1 as described above, for example, as the keyword evaluation score is higher than the standard keyword evaluation score, the future value will be higher. Conversely, if the future value of the land is low, it is included in the future land price prediction information.

Here, the future value prediction server 4 may calculate an actual land price prediction in a specific area through the future value AI module 6. For example, land buyers want to know about the land in a specific area. For example, in order to calculate the appropriate price prediction of the land as described above, the future value AI module 6 of the future value prediction server 4 uses the land residual method of the appraisal theory using Equations 2 to 4. After subtracting the estimated amount for the price of the building remaining on the corresponding land from the total transaction price, the estimated land transaction price is derived.

That is, the future value AI module 6 of the future value prediction server 4 can calculate the estimated land transaction price from the total transaction price through Equation 2.

At this time, the estimated value of the building price can be calculated through Equations 2 to 3 below by multiplying the estimated depreciation amount by the re-procurement cost of the object using the cost method of appraisal theory. Here, the repurchase cost of the real estate refers to the total amount of appropriate costs required to reproduce or reacquire the existing target real estate at the price point in real estate (see Naver Encyclopedia).

[Equation 2]

[Equation 3]

[Equation 4]

Here, the depreciation amount (DA) is the depreciation amount of the building, the repurchase cost (RC) is the repurchase cost, the new building durable years (NBDY) is the expected useful life of the new building, and the building elapsed period (BEP) is the number of elapsed years of the building, PV is the estimated land transaction price, RV is the actual transaction price of the surrounding land, and BVC is the estimated building price.

At this time, the re-procurement cost (RC) can be applied based on the structure information, use information, and use approval date information of the building listed in the building ledger, and the depreciation amount (DA) can be calculated using the useful life and elapsed life (elapsed period from the use approval date to the point of transaction) by applying the straight-line method (useful life method) (see Naver Real Estate terminology for the above).

Therefore, the future value AI module 6 of the future value prediction server 4 calculates the estimated land transaction price using Equations 2 to 4, and calculates the estimated value of the land transaction price for the land in a specific area.

When the future value AI module 6 of the future value prediction server 4 calculates an appropriate price estimate of the land using Equations 2 to 4 as described above, if the actual land transaction price is a price that includes buildings remaining on the land, the land price is protected from distortion depending on the structure, use environment, and elapsed time of the remaining building, making it possible to more accurately predict the market price of real estate.

On the other hand, the future value prediction server 4 compares the future value prediction information for the land of the national land planning or land planning or urban planning information previously stored in the DB management server 1 with the future value prediction information for the land of the land (or lot number, number or lot) input for new or update at a set cycle, corrects the difference according to the set criteria, and then transfers the newly calculated future value prediction information of the land to the DB management server ( 1) and further includes a value comparison module 7 for updating. Furthermore, the value comparison module 7 compares future value forecast information for land of national land planning or land planning or urban planning information, collects all of the partial data that differs, puts them in a separate table (not shown) and stores them, and further includes a change information display module 9 that notifies them externally through the display panel 8 by voice, number, or text.

And in the future value prediction server (4), under the functional control of the institutional comprehensive management server (2), through the deep learning function of the future value AI module (6), evaluation criteria items for setting future value prediction procedure information are related to the set land and building surroundings, and are uploaded on the Internet through wired and wireless communication networks (3). Floating population data, commercial area size and distance data, size and distance data of disgusting facilities, scale of buildings, road information and distance data, land use analysis data, land area data, land use plan data, and building and land price information crawling (crawling) and stored in the DB management server (1) and further includes an information crawling module (10) for transmitting them to the procedure information setting module (5).

Furthermore, the information crawling module 10, while interlocking with the AI module 6, crawls domestic and foreign real estate analysis information, domestic and foreign economic analysis information, domestic and foreign economic status information, domestic and foreign policy information, and domestic and foreign interest rate analysis information uploaded to the Internet through the wired and wireless communication network 3 through the deep learning function of the AI module 6, and stores them in the DB management server 1, and transmits them to the procedure information setting module 5. In addition, the information crawling module 10 works in conjunction with the AI module 6, and through the deep learning function of the AI module 6, the business survey index, producer price index, consumer price index, consumption expenditure, household debt, household income, personal income, etc. are crawled, stored in the DB management server 1, and transmitted to the procedure information setting module 5. .

At this time, the procedure information setting module 5 calculates evaluation criteria items to set future value prediction procedure information. The configuration of these evaluation criteria items is configured to select the optimal alternative in a situation where a plurality of conflicting criteria exists through the AI module 6, for example, through the deep learning function, and is configured to more reasonably and reliably evaluate the environmental problems of land where the factors to be considered are diverse and interests are complicated.

Here, the procedural information setting module 5 as described above may include not only natural and environmental aspects due to development, but also economic, social, and political issues as factors to be considered in the evaluation criteria items for setting the future value prediction procedural information, and opinions of stakeholders in the form of digital documents may be included.

Meanwhile, the evaluation criterion items may include, for example, the cleanliness of the land environment, real estate market price information, water environment around the land, securing living convenience facilities, and amenities. At this time, the cleanliness of the land environment is an index indicating the state of cleanliness of the land and its surroundings, and is divided into development areas, natural areas, semi-natural areas, and garbage neglected areas, and the distribution ratio and distribution form of the cleanliness of the area can be determined. In addition, the real estate market price additional information is an indicator indicating the real estate market price requirements of the corresponding area, and indicates the ratio of road pavement, artificial green area, animal movement route, atmospheric condition, density of buildings, and additional elements of real estate market price in the corresponding area.

Here, the real estate price additional elements include, for example, 1) daily or seasonal floating population information (including resident population) for the set land and building surroundings included in the GIS (Geographic Information System)-based map data, 2) including the distribution status and change plan of apartments, detached houses, multi-household houses, residential-commercial complexes, commercial buildings, buildings, buildings, and land around the set land and buildings, but selected from among apartments, single-family houses, multi-household houses, residential-commercial complexes, shopping malls, buildings, and buildings It further includes real estate information consisting of any one height, area, year, and size, and 3) evaluates whether or not there exists a subway station location, a subway station exit location, a tram station exit location, a tram station exit location, a railway station location, a railway station exit location, a bus stop location, a bus terminal location, a transfer center location, and a transfer center exit location around the set land and building, 3) Bus stop floating demographics, bus stop floating population movement statistics, bus that exist around the set land and building It can be evaluated by further including information such as station floating population pattern statistics and floating population statistics by bus route.

In addition, the aquatic environment is an index representing the aquatic environment of the corresponding area, and the distribution, usage pattern, and water quality of the aquatic area around the land can be determined in a complex manner. Furthermore, the amenity is data for determining the utility that can be obtained by using the corresponding area, and indicates the judgment on the residence density, the existence or construction plan of a large mart, various schools, parking rates, green space rates, social and cultural programs.

Here, at another end of the agency comprehensive management server 2, the future value prediction information for the land registered in the national land plan or land planning information finally calculated by the future value prediction server 4 is transmitted to the preset expert terminal 11a-n through the wired/wireless communication network 3 for display, and after receiving an emergency modification by the corresponding expert, the final corrected future value prediction information is received in a reset format through the expert terminal 11a-n, and the corresponding DB management server 1 It further includes an expert diagnosis module 12 for updating the land with final future value prediction information. In addition, the expert terminals 11a-n may include a mobile phone 11a or a server 11b-11f connected to a PC capable of performing SNS, KakaoTalk, blog, and dedicated communication.

In addition, another end of the agency comprehensive management server 2 further includes an emergency evaluation execution module 14 that executes an emergency evaluation according to the future value prediction procedure information set for the land requested for urgent evaluation through the future value prediction server 4 when an urgent evaluation request for a specific land registered in the national land plan or land planning information is input to the manager terminal 13 or a set Internet menu, and selectively calculates future value prediction information for the corresponding land.

In addition, the future value prediction server 4 immediately urgency when an evaluation standard item of the future value prediction procedure information applied to the procedure information setting module 5 needs to be adjusted due to an emergency change in the national land or land plan or city plan. It further includes an emergency adjustment module 15 that reflects and updates the evaluation item standard.

At another end of the institutional comprehensive management server 2, the future value prediction information calculated by the future value prediction server 4 is composed of visual information including graphs, diagrams and topographical maps, etc., and displays through the display panel 8. Visualization module 16 is further included.

Here, the institutional comprehensive management server 2 displays each point on the map based on geographical information such as topographical maps, river maps, contour maps, administrative district boundary maps, temperature status maps, precise soil maps, etc. of buildings and roads in the region registered in the national land planning or land planning information, and indicates the location information for each point, and the national land planning or land planning information can be obtained, updated, and stored through satellites or the Internet.

Here, the subject map includes, for example, administrative district map, topographical map, forest map, aerial map, military map, population distribution map, river map, soil quality map, administrative district map, topographical map by scale, underground facility map, national land use plan map, topographic land map, land use status map, city planning map, and road network map, etc., and attribute information and GIS information are organically combined with the subject map data to form map data. In addition, the subject map data includes basic attribute information such as land status, elevation, slope, land price, cadastral land, and land category, and image data for space and area.

Next, the control method of the present invention configured as described above will be described.

The method of the present invention, as shown in FIG. 4, in the initial state (S1), the agency comprehensive management server completes GIS driven subject map data related to national land or land planning managed by the state or local government and stores it in the DB management server, and sets a future value setting step (S2) of setting a preparation procedure for calculating future values for lands listed in the GIS driven subject map data of national land or land planning through a future value prediction server;

During the land future value setting step (S2), the future value prediction server selects an area to evaluate the future value of the lands listed in the GIS driven subject map data of the national land or land plan under the functional control of the institution's comprehensive management server (S3);

During the evaluation area selection step (S3), a land future value analysis step (S4) in which the future value prediction server conducts analysis by applying the evaluation standard items to the evaluation area according to the future value prediction procedure information under the functional control of the institutional comprehensive management server;

During the land future value analysis step (S4), the future value prediction server calculates the lands listed in the national land plan or land planning information for analysis by applying the evaluation criteria items as the criterion under the functional control of the institution's comprehensive management server using a deep learning method, and then assigns weights and scores, calculates future value prediction information, and registers the results in the GIS driven subject map data for each item.

Here, in the land future value calculation step (S5), the future value prediction server is directly connected under the functional control of the institution's comprehensive management server or registered in the national land planning or land planning information stored in the DB management server via a wired or wireless communication network. A sequential prediction execution step of calculating future value prediction information by sequentially evaluating the planned area according to preset future value prediction procedure information is included.

And in the land future value calculation step (S5), the future value prediction server drives the procedure information setting module under the functional control of the institutional comprehensive management server to calculate the future value prediction information for the land related to the national land or land planning stored in the DB management server. It further includes a procedure information setting system for setting future value prediction procedure information to calculate future value prediction information.

In addition, in the future value calculation step (S5), the future value prediction server drives the procedure information setting module under the functional control of the institutional comprehensive management server, and as described above, the future value prediction procedure information, i.e., the future value prediction information. It further includes an evaluation criteria item setting step of setting execution procedures such as the execution order or calculation or weighting, and setting evaluation criteria items to set the future value prediction procedure information.

In addition, in the land future value calculation step (S5), the future value prediction server drives the future value AI module and according to the future value prediction procedure information set by the manager as the procedure information setting module through the input/output device (not shown) Based on the evaluation criteria, the lands listed in the national land plan or land planning information are weighted and scored, and then future value prediction information is calculated.

In addition, in the land future value calculation step (S5), the future value prediction server runs a value comparison module to compare the future value prediction information of the land of national land planning or land planning or urban planning information previously stored in the DB management server with the future value prediction information of the land of the land planning or land planning or urban planning information of the land input for new or update at a set cycle, correcting the difference according to the set criteria, and then managing the newly calculated future value prediction information of the land. It further includes a value comparison calculation step of updating by putting in the server.

Furthermore, in the value comparison calculation step, the value comparison module compares the future value prediction information for the land of the land planning or land planning or urban planning information through the change information display module, and then collects all the different partial data, puts them in a separate table (not shown) and stores them, and then notifies them by voice, numbers, or text through the display panel.

On the other hand, in the land future value calculation step (S5), the future value AI module of the future value prediction server generates prediction information based on the national land transaction volume and average transaction price information for a specific land based on the national land plan or land plan. A first step of generating land price prediction information corresponding to the addition of the transaction volume of the land district; a second step of generating forecast information corresponding to other price increase requirements other than the first land district when the transaction volume of the first land district exceeds the reference total transaction volume and the land price of the first land is less than or equal to the standard land price during the prediction information generation step; In this case, a third step of generating land price increase prediction information in which the predicted land price of the first land district is adjusted upward by an adjustment value calculated based on the reference total transaction volume and the average land price of the corresponding land district; A fourth step of generating land price decline prediction information that is adjusted downward by the adjustment value calculated based on and applying it to the future value prediction information of the land is further included.

In addition, in the land future value calculation step (S5), the future value AI module of the future value prediction server generates the future value prediction information by further including a recommended keyword for land value prediction, and extracts the first keyword excluding search from all characters included in the homepage of an Internet homepage, such as Naver Real Estate or Real Estate Association website, where land transaction information and land sale information related to the set land and building surroundings registered in the platform are provided with information related to land transactions and sales prices in the country through a wired or wireless communication network. steps,

After the first extraction step, a keyword evaluation score calculation step of calculating a keyword evaluation score by applying Equation 1 to the corresponding land based on the homepage providing the land sale price of the corresponding land district including the first keyword, the total land transaction volume of the corresponding land district, and the land price and transaction volume including the first keyword.

[Equation 1]

Here, ESG (Estimates grade) means the keyword evaluation score, NHTV (Number of Housing Transaction Value) means the land price of the corresponding area, TTA (Total Transaction Amount) means the total land transaction volume, and 1TA (Transaction Amount) means the first individual land transaction volume.

That is, the future value prediction server 4 calculates the future value AI module 6 by applying Equation 1, such as the above, the keyword evaluation score, for example, the higher the keyword evaluation score is than the standard keyword evaluation score, the higher the future value. On the contrary, if the future value of the land is low, it is included in the future land price prediction information.

Here, the land future value calculation step (S5) further includes a land transaction price estimation step in which the future value prediction server 4 calculates an estimated land transaction price using Equations 2 to 4 below through the future value AI module 6, and calculates an appropriate estimate of the land price of the land in a specific area including the calculated land transaction price estimate.

[Equation 2]

[Equation 3]

[Equation 4]

Here, the depreciation amount (DA) is the depreciation amount of the building, the repurchase cost (RC) is the repurchase cost, the new building durable years (NBDY) is the expected useful life of the new building, and the building elapsed period (BEP) is the number of elapsed years of the building, PV is the estimated land transaction price, RV is the actual transaction price of the surrounding land, and BVC is the estimated building price.

At this time, the re-procurement cost (RC) can be applied based on the structure information, use information, and use approval date information of the building listed in the building ledger, and the depreciation amount (DA) can be calculated using the useful life and elapsed life (elapsed period from the use approval date to the point of transaction) by applying the straight-line method (useful life method) (see Naver Real Estate terminology for the above).

And in the land future value calculation step (S5), the future value prediction server is under the functional control of the institutional comprehensive management server, the information crawling module and the deep learning function of the AI (artificial intelligence) module. In the evaluation criteria item for setting the future value prediction procedure information, direct access data, traffic volume and map data, traffic facility data, sales supply data, sales analysis data, population density data, population increase data, An information crawling step of crawling and storing the information data and school district data, floating population data, commercial area size and distance data, size and distance data of disgusting facilities, size of buildings, road information and distance data, land use analysis data, land area data, land use plan data, and building and land price information data by crawling, storing them in the DB management server, and transmitting them to the procedural information setting module.

Furthermore, during the information crawling step, an economic information crawling and collection step of crawling domestic and foreign real estate analysis information, domestic and foreign economic analysis information, domestic and foreign economic status information, domestic and foreign policy information, and domestic and foreign interest rate analysis information uploaded to the Internet through wired and wireless communication networks through the deep learning function of the AI module while interlocking with the AI module during the information crawling step, and storing them in the DB management server and transmitting them to the procedure information setting module.

In addition, during the information crawling step, the information crawling module works in conjunction with the AI module, and through the deep learning function of the AI module, the real economy information crawling and collecting step of crawling domestic and foreign economic status information such as business survey index, producer price index, consumer price index, consumption expenditure, household debt, household income, and personal income uploaded to the Internet through wired and wireless communication networks, storing them in a DB management server, and transmitting them to a procedure information setting module.

Here, during the land future value calculation step (S5), the procedure information setting module sets the future value prediction procedure information. In addition to the natural and environmental aspects due to development, economic, social, and political issues can be included as factors to be considered in the evaluation criteria items, and opinions of stakeholders in the form of digital documents can be included.

On the other hand, in the step of calculating the future value of the land (S5), the procedure information setting module may include, for example, cleanliness of the land environment, additional real estate market price information, water environment around the land, securing living convenience facilities, and amenities as evaluation criteria items. Can be configured. At this time, the cleanliness of the land environment is an index indicating the state of cleanliness of the land and its surroundings, and is divided into development areas, natural areas, semi-natural areas, and garbage neglected areas, and the distribution ratio and distribution form of the cleanliness of the area can be determined. In addition, the real estate market price additional information is an index indicating the real estate market price requirements of the corresponding area, and indicates the road pavement ratio, artificial green space ratio, animal movement route, atmospheric condition, building density, and additional real estate market price elements in the corresponding area.

Here, during the land future value calculation step (S5), the procedure information setting module includes, for example, 1) day-of-week or seasonal floating population information (including resident population) for the set land and building surroundings in the map data based on the GIS (Geographic Information System) in the real estate market price additional elements of the evaluation criteria item, 2) including the distribution status and change plan of apartments, detached houses, multi-family houses, residential complexes, shopping malls, buildings, buildings, and land around the set lands and buildings However, it further includes real estate information consisting of the height, area, year, and scale of any one selected from apartments, detached houses, multi-family houses, residential complexes, shopping malls, buildings, and buildings, and 3) Evaluating whether or not there exists a subway station location, subway station exit location, tram station location, tram station exit location, railway station location, railroad station exit location, bus stop location, bus terminal location, transfer center location, and transfer center exit location around the set land and building, 3) Established land and building Information such as floating demographics of bus stops, floating population flow statistics of bus stops, pattern statistics of bus stops, floating demographics of each bus route, etc., which exist in the vicinity may be further included in the evaluation.

In addition, during the land future value calculation step (S5), the procedure information setting module complexly determines the distribution of aquatic areas around the land, usage patterns, and water quality as indicators of the aquatic environment of the area in the water environment of the evaluation standard item.

Furthermore, during the land future value calculation step (S5), the procedure information setting module is data for determining the utility that can be obtained by using the area in the amenity of the evaluation criteria item. It represents the decision on the existence or construction plan of a large mart, various schools, parking rates, green space rates, society, and cultural programs.

Here, during the land future value calculation step (S5), the future value prediction server runs the expert diagnosis module under the function control of the institutional comprehensive management server, transmits and displays the final calculated future value prediction information for the land registered in the national land planning or land planning information to a preset expert terminal through a wired or wireless communication network, receives an emergency correction by the expert, receives the corrected final future value prediction information in a reset format through the expert terminal, and updates the final future value prediction information in the corresponding land of the DB management server. It further includes an additional diagnostic step by an expert.

In addition, during the land future value calculation step (S5), the future value prediction server drives the emergency evaluation execution module under the functional control of the institution's comprehensive management server, and when an emergency evaluation request for a specific land listed in the national land plan or land planning information is entered into the manager terminal or set Internet menu, the future value prediction server executes an emergency evaluation according to the future value prediction procedure information set for the land requested for urgent evaluation through the selection request calculation step of selectively calculating future value forecast information for the land contains more

In addition, during the land future value calculation step (S5), the future value prediction server drives the emergency adjustment module under the functional control of the institutional comprehensive management server, and the evaluation standard items of the future value prediction procedure information applied to the procedure information setting module. If adjustment of the evaluation standard value is necessary due to an emergency change in land planning or urban planning, an emergency adjustment step of immediately reflecting and updating the evaluation item criteria is included.

In addition, during the land future value calculation step (S5), the future value prediction server drives the visualization module under the functional control of the institutional comprehensive management server to display the future value prediction information calculated by the future value prediction server as visual information including graphs, diagrams and topographical maps, and displays it through a display panel.

In other words, in the map information service system equipped with the predictive function of the future value of land according to the present invention, the comprehensive management server 2 of the institution completes the GIS-driven subject map data related to national land or land planning managed by the state or local government, and stores it in the DB management server 1. In the process of setting the future value of land, the future value prediction server 4 sets up a preparation procedure for calculating the future value of lands registered in the GIS-driven subject map data of the national land or land plan. At this time, during the land future value setting process, the future value prediction server 4 selects an area to evaluate the future value of lands listed in the GIS driven subject map data of the national land or land plan under the functional control of the institutional comprehensive management server 2. And, if the area to evaluate the future value is set as described above, the future value prediction server 4 performs analysis by applying the evaluation standard items to the evaluation area according to the future value prediction procedure information set by the procedure information setting module 5 under the functional control of the institution comprehensive management server 2. In addition, while the future value prediction server 4 executes the land future value analysis process as described above, under the functional control of the institutional comprehensive management server 2, the analysis is applied based on the evaluation criteria items. After calculating the lands listed in the national land planning or land planning information using a deep learning method, assigning weights to scores, calculating the future value prediction information, and listing the results in the GIS driven subject map data of the relevant land for each item.

In other words, during the process of calculating the future value of the land as described above, the future value prediction server 4 is directly connected to the DB management server 1 under the functional control of the institutional comprehensive management server 2, or via wired and wireless communication networks 3. For the lands stored in the national land planning or land planning information stored in the DB management server 1, the planned area is sequentially evaluated according to the preset future value prediction procedure information to calculate future value prediction information.

Here, the future value prediction server 4 drives the procedure information setting module 5 under the functional control of the institution comprehensive management server 2 during the process of calculating the future value of the land as described above, and sets the future value prediction procedure information to calculate the future value prediction information calculated for land related to national land or land planning stored in the DB management server 1.

In addition, during the process of calculating the future value of land, the future value prediction server 4 drives the procedure information setting module 5 under the functional control of the institutional comprehensive management server 2 as described above, that is, the implementation sequence for calculating the future value prediction information, the execution procedure such as calculation or weighting, and the process of setting evaluation criteria items to set the future value prediction procedure information.

In addition, the future value prediction server 4 drives the future value AI module 6 during the process of calculating the future value of the land as described above, and according to the future value prediction procedure information set by the manager to the procedure information setting module 5 through the input/output device (not shown) Based on the evaluation criteria items, the lands listed in the national land planning or land planning information are scored by giving weights, for example, by a deep learning method, and then calculating future value prediction information. For example, in the actual calculation step of the predicted information, the future value AI module 6 calculates future value predicted information by digitizing each of the evaluation criteria items and multiplying them by a weight.

Meanwhile, the future value prediction server 4 includes a memory and a processor-type future value AI module 6 connected to the memory.

In the evaluation criteria item for setting future value forecasting process information,

Land transaction information and land sale information related to the set land and building surroundings are crawled through the wired/wireless communication network (3) and stored in the memory.

That is, the future value AI module 6 under the functional control of the future value prediction server 4 generates land future prediction information on land transactions and sales prices in a specific area based on information related to national land transactions and sales prices registered on a platform such as an Internet homepage, such as a homepage of a land corporation, set through a wired/wireless communication network 3 through a wired or wireless communication network 3. At this time, the future value AI module 6 generates the future prediction information of the land based on the nationwide land transaction volume and average transaction price information for a specific land based on the national land plan or land plan. At this time, if the land price in the specific area (or the first land area) exceeds the preset standard land price and the total transaction volume exceeds the preset standard total transaction volume, land price prediction information corresponding to the addition of the transaction volume in the first land area is generated. However, the future value AI module 6 generates prediction information corresponding to price increase requirements other than the first land area when the transaction volume of the first land area exceeds the standard total transaction amount and the land price of the first land is less than or equal to the standard land price, and when the transaction amount of the first land area is less than or equal to the standard total transaction amount and the land price of the first land exceeds the average land price, the predicted land price of the first land area is calculated by dividing the sales price into the total standard transaction amount and the corresponding land area It generates land price increase prediction information that is upwardly adjusted by the adjustment value calculated based on the average land price of . On the other hand, the future value AI module 6 generates land price decline prediction information for lowering the sales price by an adjustment value calculated based on the reference total transaction volume and the average land price of the corresponding land district, and applies it to the future value prediction information of the land, when the transaction volume of the first land district is less than or equal to the reference total transaction volume and the land price of the first land is less than or equal to the average land price.

Furthermore, the future value AI module 6 generates the future value prediction information by further including a recommended keyword for land value prediction, and extracts the first keyword excluding research from all characters included in the homepage of an Internet homepage, such as Naver Real Estate or Real Estate Association website, where information related to transactions and selling prices of lands across the country is provided through wired and wireless communication networks (3). At this time, the future value AI module 6 calculates the keyword evaluation score by applying Equation 1 to the corresponding land and applies it to the future value prediction information of the land according to the homepage provided with the land sale price of the corresponding land district including the first keyword, the total land transaction volume of the corresponding land district, and the land price and transaction volume including the first keyword.

[Equation 1]

Here, ESG (Estimates grade) means the keyword evaluation score, NHTV (Number of Housing Transaction Value) means the land price of the corresponding area, TTA (Total Transaction Amount) means the total land transaction volume, and 1TA (Transaction Amount) means the first individual land transaction volume.

Therefore, the future value prediction server 4 calculates the future value AI module 6 by applying Equation 1 as described above, for example, as the keyword evaluation score is higher than the standard keyword evaluation score, the future value will be higher. Conversely, if the future value of the land is low, it is included in the future land price prediction information.

For example, a high keyword evaluation score calculated by applying Equation 1 means that the transaction and sales price of the land area through the Internet homepage, for example, the homepage of Naver Real Estate or the Real Estate Association website, where information related to the transaction and sale price of land across the country is provided.

If the keyword evaluation score is low, it is preferable to calculate the future value of the land based on this, since the frequency of inquiries about the transaction and sale price of the land area or related interest is quite low through the Internet homepage, for example, Naver Real Estate or the homepage of the Real Estate Association website, where information related to the transaction and sale price of land is provided across the country.

In addition, the future value prediction server 4 drives the value comparison module 7 during the process of calculating the future value of the land as described above, compares the future value prediction information for the land of national land planning or land planning or urban planning information previously stored in the DB management server 1 with the future value prediction information for the land of the land (or lot number, number or parcel) input for new or update at a set cycle, and then compares the difference After correcting according to the set criteria, the newly calculated future value prediction information of the land is put into the DB management server (1) and updated.

At this time, during the value comparison calculation process as described above, the value comparison module 7 compares the future value prediction information for the land of national land planning or land planning or urban planning information through the change information display module 9, and then collects all of the partial data that differs, puts them in a separate table (not shown) and stores them, and then notifies them to the outside through the display panel 8 by voice, number, or text.

For example, in the process of calculating the future value of the land, the future value AI module 6 of the future value prediction server 4 uses Equations 2 to 4 to calculate the predicted value of the proper price of the land. Using the land residual method of appraisal theory, after deducting the estimated value of the price of the building remaining on the relevant land from the total transaction price, the estimated value of the land transaction price is derived.

That is, the future value AI module 6 of the future value prediction server 4 can calculate the estimated land transaction price from the total transaction price through Equations 2 to 4.

At this time, the estimated value of the building price can be calculated through Equations 2 to 3 below by multiplying the estimated depreciation amount by the re-procurement cost of the object using the cost method of appraisal theory. Here, the repurchase cost of the real estate refers to the total amount of appropriate costs required to reproduce or reacquire the existing target real estate at the price point in real estate (see Naver Encyclopedia).

[Equation 2]

[Equation 3]

[Equation 4]

Here, the depreciation amount (DA) is the depreciation amount of the building, the repurchase cost (RC) is the repurchase cost, the new building durable years (NBDY) is the expected useful life of the new building, and the building elapsed period (BEP) is the number of elapsed years of the building, PV is the estimated land transaction price, RV is the actual transaction price of the surrounding land, and BVC is the estimated building price.

At this time, the re-procurement cost (RC) can be applied based on the structure information, use information, and use approval date information of the building listed in the building ledger, and the depreciation amount (DA) can be calculated using the useful life and elapsed life (elapsed period from the use approval date to the point of transaction) by applying the straight-line method (useful life method) (see Naver Real Estate terminology for the above).

Therefore, the future value AI module 6 of the future value prediction server 4 calculates the estimated land transaction price using Equations 2 to 4, and calculates the estimated value of the land transaction price for the land in a specific area. In addition, the future value AI module 6 of the future value prediction server 4 puts the estimated land price in a specific area into the DB management server 1 and manages the estimated land transaction price calculated as described above.

When the future value AI module 6 of the future value prediction server 4 calculates an appropriate price estimate of the land using Equations 2 to 4 as described above, if the actual land transaction price is a price that includes buildings remaining on the land, the land price is protected from distortion depending on the structure, use environment, and elapsed time of the remaining building, making it possible to more accurately predict the market price of real estate.

On the other hand, the future value prediction server 4 is to set future value prediction procedure information through the deep learning function of the information crawling module 10 and the future value AI module 6 under the functional control of the institutional comprehensive management server 2 during the process of calculating the future value of the land as described above. Sales analysis data, population density data, population growth data, government office information data and school district data, floating population data, commercial area size and distance data, size and distance data of disgusting facilities, building size, road information and distance data, land use analysis data, land area data, land use planning data, building and land price information data are crawled, stored in the DB management server (1), and transmitted to the procedure information setting module (5). At this time, in the information crawling process, the information crawling module 10 interlocks with the future value AI module 6, crawls domestic and foreign real estate analysis information, domestic and foreign economic analysis information, domestic and foreign economic status information, domestic and foreign policy information, and domestic and foreign interest rate analysis information uploaded to the Internet through the wired and wireless communication network 3 through the deep learning function of the future value AI module 6, crawls, stores them in the DB management server 1, and transmits them to the procedure information setting module 5. carry out Furthermore, in the information crawling process, the information crawling module 10 works in conjunction with the future value AI module 6, and through the deep learning function of the future value AI module 6, the business survey index, producer price index, consumer price index, consumption expenditure, household debt, household income, personal income, etc. The real economy information crawling collection process transmitted to the setting module 5 is further performed.

On the other hand, during the process of calculating the future value of the land as described above, the procedure information setting module 5 calculates evaluation criteria items to set future value prediction procedure information. The composition of these evaluation criteria items is configured to select the optimal alternative in a situation where a plurality of conflicting criteria exists through the deep learning function of the future value AI module 6, and to evaluate the environmental problems of land with various factors to be considered and complicated interests more rationally and reliably. In addition, the procedure information setting module 5 may include not only natural and environmental aspects due to development, but also economic, social, and political issues as factors to be considered in the evaluation criteria items to set future value prediction procedure information. Opinions of stakeholders in the form of digital documents may also be included. In addition, the procedure information setting module 5 may include, for example, cleanliness of the land environment, additional real estate market price information, water environment around the land, securing living convenience facilities, and amenities as evaluation criteria items. At this time, the cleanliness of the land environment is an index indicating the state of cleanliness of the land and its surroundings, and is divided into development areas, natural areas, semi-natural areas, and garbage neglected areas, and the distribution ratio and distribution form of the cleanliness of the area can be determined. In addition, the real estate market price additional information is an index indicating the real estate market price requirements of the corresponding area, and is set including road pavement ratio, artificial green area ratio, animal movement route, atmospheric condition, building density, and real estate market price additional elements in the corresponding area.

In particular, during the process of calculating the future value of the land as described above, the procedure information setting module 5 also includes, for example, 1) daily or seasonal floating population information (including the resident population) for the set land and building surroundings in the map data based on the GIS (Geographic Information System) as an additional element of the real estate market price of the evaluation standard item, 2) the distribution status of apartments, detached houses, multi-households, residential-commercial complexes, shopping malls, buildings, buildings and lands around the set lands and buildings; Including the change plan, but further including real estate information consisting of the height, area, year, and scale of any one selected from among apartments, single-family homes, multi-family homes, residential complexes, shopping malls, buildings, and buildings, 3) Evaluating whether or not there exists a subway station location, a subway station exit location, a tram station exit location, a tram station exit location, a railway station location, a railroad station exit location, a bus stop location, a bus terminal location, a transfer center location, and a transfer center exit location around the set land and building, 3) Information such as bus stop floating population statistics, bus stop floating population movement line statistics, bus stop floating population pattern statistics, and floating population statistics by bus route existing around the set land and building may be further included in the evaluation. In addition, the procedure information setting module 5 can determine the distribution of aquatic areas around the land, usage patterns, and water quality as an indicator of the aquatic environment of the corresponding area in the aquatic environment of the evaluation standard item. In addition, during the land future value calculation process, the procedural information setting module 5 is data for determining the utility that can be obtained by using the corresponding area in the amenity of the evaluation criteria item. It shows judgments on residence density, existence or construction plan of large marts, various schools, parking ratios, green space ratios, social and cultural programs, etc.

Meanwhile, during the process of calculating the future value of the land as described above, the future value prediction server 4 drives the expert diagnosis module 12 under the function control of the institutional comprehensive management server 2 to transmit the final calculated future value prediction information for the land listed in the national land plan or land planning information to the preset expert terminal 11a-n through the wired and wireless communication network 3, display it, receive emergency correction by the expert, and display the corrected final future value prediction information to the expert terminal 11a-n. ) It may be received in a format set again through the DB management server 1 to be updated with the final future value prediction information on the corresponding land.

Furthermore, during the process of calculating the future value of the land as described above, the future value prediction server 4 runs the emergency evaluation execution module 14 under the functional control of the institutional comprehensive management server 2, and when an urgent evaluation request for a specific land registered in the national land planning or land planning information is entered into the administrator terminal 13 or the set Internet menu, the future value prediction server 4 executes an emergency evaluation according to the future value prediction procedure information set for the land for which urgent evaluation is requested, and selectively executes the corresponding land The process of calculating future value forecast information for is also performed further.

Here, during the process of calculating the future value of the land as described above, the future value prediction server 4 drives the emergency adjustment module 15 under the functional control of the institutional comprehensive management server 2 to apply to the procedure information setting module 5. If the evaluation standard item of the future value prediction procedure information needs to be adjusted due to an emergency change in national land or land planning or urban planning, it can be updated by immediately reflecting the evaluation item standard.

And, during the process of calculating the future value of the land as described above, the future value prediction server 4 drives the visualization module 16 under the functional control of the institutional comprehensive management server 2, so that the future value prediction information calculated by the future value prediction server 4 is composed of visual information including graphs, diagrams and topographical maps, etc. and displayed through the display panel 8, so that all involved can visually check the future value prediction information.

Although various embodiments of the present invention have been shown and described above, the present invention is not limited to the specific embodiments described above, and the above-described embodiments can be variously modified and implemented by those skilled in the art without departing from the gist of the present invention claimed in the appended claims, and these modified embodiments should not be understood separately from the technical spirit or scope of the present invention. Therefore, the technical scope of the present invention should be defined only by the appended claims.

1: DB management server 2: Institution comprehensive management server
3: wired/wireless communication network 4: future value prediction server
5: Procedure information setting module 6: Future value AI module
7: Value comparison module 8: Display panel
9: change information display module 10: information crawling module
11a-n: expert terminal 12: expert diagnosis module
13: manager terminal 14: emergency evaluation execution module
15: emergency adjustment module 16: visualization module

Claims (3)

A DB management server that registers and stores attribute information on land related to national territory or land planning and future value prediction information calculated thereon in GIS-driven subject map data;
An institutional comprehensive management server that manages national land planning and land planning information stored in the DB management server while interworking with the DB management server, and overall controls the future value calculation function for lands registered in the national land planning and land planning information;
A future value prediction server for calculating future value prediction information by sequentially evaluating the planned area according to predetermined future value prediction procedure information for the land listed in the national land planning and land planning information stored in the DB management server under the functional control of the institutional comprehensive management server or via a wired/wireless communication network;
The future value prediction server includes a procedure information setting module for setting procedure information related thereto to calculate future value prediction information for land corresponding to the national land planning and land planning information stored in the DB management server under the functional control of the institutional comprehensive management server,
Based on the evaluation criteria items according to the future value prediction procedure information set in the procedure information setting module, the lands listed in the land planning and land planning information are weighted and scored to calculate future value prediction information.
A land future value setting step of setting a preparation procedure for calculating the future value of lands registered in the GIS driven subject map data of national land planning and land planning through the future value prediction server;
In the land future value setting step, the future value prediction server selects a future value evaluation area for lands registered in the GIS driven subject map data of national land planning and land planning under the function control of the institution comprehensive management server;
a land future value analysis step in which the future value prediction server conducts analysis by applying the evaluation criterion items to the evaluation district under the function control of the agency comprehensive management server in the evaluation area selection step;
In the land future value analysis step, the future value prediction server assigns weights to the lands registered in the land plan and land planning information analyzed by applying the evaluation criteria items as criteria under the function control of the institutional comprehensive management server, and then calculates future value prediction information, and a land future value calculation step of listing the calculated results in the GIS driven subject map data of the land for each item,
In the land future value calculation step, the future value prediction server is connected directly under the functional control of the institutional comprehensive management server or via a wired or wireless communication network to the land listed in the national land planning and land planning information stored in the DB management server. A sequential prediction execution step of sequentially evaluating planned areas according to predetermined future value prediction procedure information;
The land future value calculation step further includes a procedure information setting step of driving the procedure information setting module to set the future value prediction procedure information to calculate the future value prediction information calculated for the land related to the land planning and land planning stored in the DB management server;
The future value calculation step of the land further comprises an evaluation criterion item setting step of driving the procedure information setting module to set a transition sequence for calculating the future value prediction information according to the future value prediction procedure information, an execution procedure for calculation and weighting therefor, and setting the evaluation criteria item for the future value prediction procedure information;
The land future value calculation step further includes a prediction information actual calculation step in which the future value prediction server drives the future value AI module to calculate the next future value prediction information obtained by assigning weights to the lands listed in the land planning information based on the evaluation criteria item according to the future value prediction procedure information set as a procedure information setting module,
In the land future value calculation step, the future value prediction server drives a value comparison module to compare the future value prediction information of the land corresponding to the national land planning, land planning, and urban planning information input for updating the future value prediction information of the land corresponding to the national land planning, land planning, and urban planning information previously stored in the DB management server at a set cycle, correcting the difference according to a set standard, and then storing and updating the newly calculated future value prediction information of the corresponding land in the DB management server. In the value comparison calculation step, in the value comparison calculation step, the value comparison module compares the future value prediction information for the land of the land planning, land planning, and urban planning information through the change information display module, and then collects and stores the difference in partial data in a separate table, and further includes an information display step of notifying them externally by voice, number, or text through a display panel;
The land future value calculation step further includes an information crawling step in which the information crawling module crawls information related to the land and building surroundings of the evaluation standard item, stores it in the DB management server, and transmits it to the procedure information setting module,
The information related to the land and building surroundings of the above evaluation criteria includes data on the traffic volume, pre-sale supply, population density, population growth, school district, floating population, commercial district size and size of hate facilities around the land and building set above,
The information crawling step crawls economic information including real estate-related analysis information, economic status information, policy information, and interest rate analysis information, stores it in the DB management server, and transmits it to the procedure information setting module,
The land future value calculation step calculates the next future value prediction information including additional element information included in the additional elements of the real estate market price in the evaluation standard items,
The additional element information is
GIS-based map data for floating population information (including resident population) by day or season around the preset land and building
Distribution status and change plan of apartments, detached houses, multi-household houses, residential/commercial complexes, shopping malls, buildings, buildings, and land around the land and buildings set above
Evaluating whether there is a subway station location, a subway station exit location, a tram station location, a tram station exit location, a railroad station location, a railroad station exit location, a bus stop location, a bus terminal location, a transfer center location, and a transfer center exit location around the preset land and building
includes statistics on floating demographics of bus stops around the preset land and buildings, statistics on floating population movements at bus stops, statistics on patterns of floating population at bus stops, and statistics on floating demographics by bus route;
The future value calculation step of the land further includes an expert additional diagnosis step of driving an expert diagnosis module to transmit the finally calculated future value prediction information for the land registered in the national land plan and land planning information to a preset expert terminal, and receiving emergency correction by the expert through the expert terminal to update the final future value prediction information to the DB management server;
[Equation 1]

The future value AI module includes recommended keywords, generates the future value prediction information, and calculates a keyword evaluation score based on a website and Equation 1 that provides information on land including a first keyword among the recommended keywords, and includes it in future land price prediction information for determining future value based on the calculated keyword evaluation score,
In Equation 1, ESG (Estimates grade) means the keyword evaluation score, NHTV (Number of Housing Transaction Value) means the price of land including the first keyword among the recommended keywords, TTA (Total Transaction Amount) means the total land transaction volume, 1TA (Transaction Amount) means the transaction volume of land including the first keyword,
[Equation 2]

[Equation 3]

[Equation 4]

The future value AI module utilizes the residual land method of appraisal theory to derive an estimate of the land transaction price by deducting an estimate of the residual building price of the land including the first keyword from the total transaction price Based on Equations 2 to 4,
In Equations 2 to 4, DA (depreciation amount) is the building depreciation amount, RC (repurchase cost) is the repurchase cost, NBDY (new building durable years) is the expected use life of the new building, BEP (Building Elapsed period) is the building elapsed years, PV is the estimated land transaction price, RV is the actual transaction price of the surrounding land, and BVC is the estimated building price. A control method of a map information service system equipped with functions.
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