KR20170115734A - Apparatus and Method of Processing for Real Estate Information - Google Patents

Abstract

The present invention relates to a real estate information processing apparatus and method.
A method for processing real estate information according to the present invention includes a selection step of selecting a real estate object, a display step of displaying a 3D drawing of the selected real estate object, a placement step of additionally arranging an object in the 3D drawing, A recommendation step of recommending at least one vendor in correspondence with the recommendation step.

Description

[0001] APPARATUS AND METHOD FOR PROCESSING REAL ESTATE INFORMATION [0002]

The present invention relates to a real estate information processing apparatus and method.

In Korea, real estate transactions such as apartments are active nowadays.

Buyers who purchase a house, such as an apartment, can refresh the interior of the house according to their wishes. In such a case, it is common that the buyer calls the interior designer to confirm the structure of the house, and then receives a quotation from the supplier.

However, in such a case, it takes a considerable time to confirm the estimate.

An object of the present invention is to provide a real estate information processing apparatus and method capable of quickly confirming real estate information.

A method for processing real estate information according to the present invention includes a selection step of selecting a real estate object, a display step of displaying a 3D drawing of the selected real estate object, a placement step of additionally arranging an object in the 3D drawing, A recommendation step of recommending at least one vendor in correspondence with the recommendation step.

The method may further include extracting an image file of the selected real estate object, extracting coordinate data based on the extracted image file, and constructing a 3D drawing of the real estate object based on the coordinate data .

In addition, the image file may include a sketch file.

The object may also include at least one of a wall, a window, a door, a bathtub, a toilet, a washbowl, furniture, appliances, machinery, equipment, a curtain or a blind.

Also, in the recommendation step, at least one vendor may be recommended according to the order in which the estimated price is low in correspondence with the added object.

Also, in the recommendation step, at least one vendor may be recommended in the order of higher ratings corresponding to the added objects.

The method may further include the step of providing a quotation of the recommended company.

The real estate information processing apparatus according to the present invention includes a real estate server for storing information on at least one real estate article and a user terminal for connecting to the real estate server, When the user terminal selects the 3D object, provides the 3D drawing of the selected first real estate object to the user terminal, and when the user terminal further arranges the object in the 3D drawing provided, And recommendation information for recommending at least one vendor to the user terminal.

The real-estate server transmits the 3D drawing in which the object is additionally disposed to the business server, and the business server transmits a quotation corresponding to the 3D drawing received from the real- Server or at least one of the user terminals.

The business server includes the business server of the vendor, and the real estate server transmits information on an additional disposed object to the business server, and the business server transmits a quotation corresponding to the object received from the real estate server to the real estate server Or the user terminal.

In addition, the real estate server can provide the quotation received from a company server of a recommended company to the user terminal.

Also, the real estate server may receive the quotation from a plurality of the vendor servers, and may recommend the at least one vendor quotation to the user terminal in the order of the lowest quotation price.

Also, the real estate server may receive the quotation from a plurality of the vendor servers, and may recommend the at least one vendor quotation to the user terminal in the order of higher ratings.

The real estate server extracts an image file of the selected first real estate object, extracts coordinate data based on the extracted image file, and constructs a 3D drawing of the first real estate based on the coordinate data can do.

In addition, the image file may include a sketch file.

In addition, the object may include at least one of a wall, a window, a door, a bathtub, a toilet, a washbowl, furniture, a home appliance, a curtain, a machine, a device, and a blind.

The apparatus and method for real estate information processing according to the present invention have an effect of converting the image of the real estate thing into the 3D drawing and providing the user with convenient and quick confirmation of the real estate information.

1 and 2 are views for explaining a configuration of a file conversion apparatus according to an embodiment of the present invention.
FIGS. 3 to 7 are views for explaining a first embodiment of a method of detailing an image file.
FIGS. 8 to 11 are views for explaining a second embodiment of a method of detailing an image file.
Figs. 12 to 14 are diagrams for explaining a configuration and a schematic function of a real estate information processing apparatus according to the present invention. Fig.
Figs. 15 to 27 are diagrams for explaining the real estate information processing method. Fig.

Hereinafter, an apparatus and method for processing real estate information according to the present invention will be described in detail with reference to the accompanying drawings.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood that the present invention is not intended to be limited to the specific embodiments but includes all changes, equivalents, and alternatives falling within the spirit and scope of the present invention.

In describing the present invention, the terms first, second, etc. may be used to describe various components, but the components may not be limited by the terms. The terms may only be used for the purpose of distinguishing one element from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

The term " and / or " may include any combination of a plurality of related listed items or any of a plurality of related listed items.

When an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may be present in between Can be understood. On the other hand, when it is mentioned that an element is "directly connected" or "directly connected" to another element, it can be understood that no other element exists in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions may include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used interchangeably to designate one or more of the features, numbers, steps, operations, elements, components, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries can be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are, unless expressly defined in the present application, interpreted in an ideal or overly formal sense .

The following embodiments are provided so that those skilled in the art can more fully understand the present invention. The shapes and sizes of elements in the drawings may be exaggerated for clarity.

The various embodiments described below may be implemented in a recording medium readable by a computer or similar device using software, hardware, or a combination thereof.

In accordance with a hardware implementation, embodiments of the present invention may be implemented in a processor, such as application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and electrical units for performing functions.

On the other hand, according to a software implementation, embodiments such as procedures or functions in the present invention may be implemented with separate software modules that perform at least one function or operation.

1 and 2 are views for explaining a configuration of a file conversion apparatus according to an embodiment of the present invention.

Referring to FIG. 1, the file conversion apparatus includes an input unit 10, an image file processing unit 20, and a storage unit 30.

The input unit 10 is a portion for inputting a file for drawing, and may be implemented by a USB port for receiving a file input through an external device, or a communication module for inputting or downloading a file through a network.

Here, the file for detailing may include at least one of an image file (JPG file, GIF file, PNG file, etc.) and a PDF file. The PDF file may refer to a file imaged through its own algorithm.

Alternatively, the image for detailing may mean an image of a user's hand-drawn drawing. Alternatively, it may be an image file (JPG file, GIF file, PNG file, etc.) and a PDF file created by photographing a hand-drawn drawing by the user. Here, the PDF file may mean a file imaged through its own algorithm.

On the other hand, the image file processing unit 20 plays a role of detailing a file input through the input unit 10 (2D and / or 3D) and storing the file in the storage unit 30.

2, the image file processing unit 20 includes an outline extraction module 21, a corner feature point detection module 22, a point connection module 23, a noise removal module 24, an image detection module 25, A template matching module 26, a 2D drawing generation module 27, a 3D drawing calculation module 28, an illumination influence removal module 31, a labeling module 33, a boundary detection module 34, Module 35 as shown in FIG.

The outline extraction module 21 can extract the outline from the input file. In addition, the outline extraction module 21 may extract the outline from the image from which the influence of illumination is removed, and store the resultant image.

The corner feature point detection module 22 can detect and coordinate the corner feature points based on the extracted outline.

The point connection module 230 can connect the detected corner feature points with a line.

Noise cancellation module 24 may remove noise from the connected lines.

The image detection module 25 can detect the image with the outline removed.

The template matching module 26 may template-match the noise-removed image and the outer-removed image. Alternatively, the template matching module 26 may template-match an image from which the outline has been removed and an image from which the influence of illumination is removed.

The 2D drawing generation module 27 can generate the 2D drawing for the input file by applying the stored outline coordinate information and element coordinate information to the CAD program.

The 3D drawing calculation module 28 can calculate the 3D drawing based on the generated 2D drawing.

The roughing influence removing module 31 converts the drawing information (image) into Lab channels, separates the converted Lab channels into respective channels, and removes the influence on illumination by processing the light and dark of the separated L channels .

The labeling module 33 may label the extracted image to detect blobs.

The boundary detection module 34 can detect the boundary based on the detected blobs.

The directionality determination and contour elimination module 35 samples a set of a plurality of points constituting the detected boundary to determine the directionality, detects the outline, smoothes the image by removing the influence of the illumination and the median filter, and extracts the outline And the image with the outer edge removed can be detected.

The file conversion method using the above file conversion apparatus will be described below with reference to the accompanying drawings.

FIGS. 3 to 7 are views for explaining a first embodiment of a method of detailing an image file. In the following, description of the parts described above may be omitted.

FIG. 3 is a flowchart of a file conversion method according to the first embodiment of the present invention. It is a method of converting a document file such as an image file such as a JPG file, a GIF file, or a PNG file, or a PDF file into an available file such as a CAD file And shows the method of drawing.

Referring to FIG. 3, the file conversion method according to the first embodiment of the present invention includes: (a) receiving a file to be displayed (S101); (b) extracting an outline from the input file (S102 to S104); (c) detecting coordinates of a corner feature point based on the extracted outline and making coordinates (S105); (d) connecting the detected corner feature points by a line (S106); (e) removing noise from the lines connected in the step (d) (S107); (f) detecting (S108) an image from which an outline has been removed from the input file; (g) a step (S109) of template-matching the noise-removed image in step (e) and the image detected in step (f); (h) generating (S110) a 2D drawing for the input file by applying the stored outline coordinate information and element coordinate information after template matching in the step (g) to the CAD program; (i) calculating a 3D drawing based on the 2D drawing generated in the step (h) (S111).

The step (b) includes the steps of: (b1) converting the input image file information into a gray scale (S102); (b2) truncation coding by bit-plane slicing the information converted into gray scale, storing the most significant bit information image among the truncated information, and transmitting the truncated information to the median (S103 to S104) of extracting an outline by smoothing using a filter (Median Filter) and storing the resultant image.

In the step (f), information about a linear component that is effective in the noise-removed image is stored, and when the detection of the outline is completed, the element is detected, and the extracted image is smoothed using the converted gray-scale image and median filter, And the image with the outer edge removed can be detected.

In the step (h), the positional value of the matched element in the template matching is stored, the element coordinate information is extracted by calculating the image of the outer edge and the position of the stored element, and the outer coordinate information and the element coordinate information Can be applied to a CAD program to make an input file (image file, PDF file) 2D.

Hereinafter, the file conversion method according to the first embodiment of the present invention will be described in detail.

First, the file to be drawn is input through the input unit 10 (S101). The file to be drawn here includes at least one of an image file (JPG file, GIF file, PNG file, etc.) and a PDF file. 4 is an exemplary diagram of a case where an input file is an image file.

When the image file is inputted, the image file processing unit 20 processes the inputted image file and displays it. For example, the input image file information is converted into a gray scale (image 1) (S102). A digital image refers to an image in which the value of each pixel is one sample, and can transmit only the information of luminosity. These types of images, also known as black and white, are made up of gray shadows, ranging from the "black" of the most luminous intensity to the "white" of the lightest intensity. Therefore, the brightness of each pixel can be determined by converting image file information to gray scale.

Next, the image information converted into the gray scale is truncation-coded by a bit-plane slicing method. Loss compression.

For example, one pixel of an 8-bit gray image is composed of 8 bits, and the most significant bit among the 8 bits is called MSB and the least significant bit is called LSB. The lower 4 bits are cut off to perform loss compression.

Thereafter, the most significant bit information image (image 2) of the cut-encoded information is stored in the storage unit 30, the cut-encoded image information is smoothed using a median filter to extract an outline, Save the image (image 3).

Here, the smoothing using the median filter means that the intensity of each pixel is replaced with the intermediate value of the intensities in the surrounding points of the pixel instead of the average value. This smoothing method is particularly effective when the noise form is strong and consists of elongated elements such as elongated lines, and corner sharpening is well preserved.

FIG. 4 shows an example of an image file to be converted into a drawing file by the file conversion method according to the first embodiment. FIG. 5 shows an example of a result of extracting an outline from the image file shown in FIG. 4 .

Next, in step S105, corner feature points are detected based on the extracted outline and converted into coordinates.

6 shows an example of the result of extracting corner feature points from the image file.

For example, edge information (image 4) is detected through Harris corner detection, edge line detection image (image 3), and corner image (image 4) Can be detected.

Here, when generating an arbitrary region (window) in the image, the Harris corner detection detects a point at which a change occurs in all directions, not only in a direction not changing in all directions or in a certain direction along an edge, It is an algorithm to recognize as a point (edge).

Next, in step S106, the detected corner feature points are connected by a line (image 5). Thereafter, noise is removed from the connected lines in step S107.

For example, an image (image 5) obtained by connecting the detected image (image 3) and a corner feature point by a line may be calculated (logical AND) and the noise of the lines may be removed.

Next, in step S108, an image in which the outline has been removed from the image file is detected.

For example, it is possible to store information about the effective straight line component in the noise-free image, and to detect the element in the image that has undergone edge detection (image 6).

Here, the element may mean an image other than an outline in an image file as shown in FIG. For example, a door, a window, a washstand, and the like may be said elements.

Then, the converted image is smoothed using the gray scale image (image 1) and the median filter, and the image (image 3) obtained by extracting the outline is calculated to detect the image with the outline removed.

Thereafter, in step S109, the noise-removed image and the image in which the element is detected are subjected to template matching.

FIG. 7 shows an example of a template-matching state between an image in which noise is removed and an image in which an element is detected.

For example, the noise-removed image and the element-detected image can be superimposed.

Here, the template matching may be template matching using a statement, a window, a washstand as a priority order.

Next, in step S110, the 2D coordinate system of the input file can be generated by applying the stored outline coordinate information and element coordinate information after the template matching to the CAD program.

For example, the location value of the matched element in the template matching is stored (image 7), the element image information (image 6) and the stored position value (image 7) of the stored element are calculated , And the outline coordinate information and the element coordinate information are applied to the CAD program to make the 2D image of the image file.

Thereafter, in step S111, the 3D drawing is calculated based on the generated 2D drawing. Here, a method of calculating a 2D drawing as a 3D drawing can be performed using Rhino, 3D MAX, AutoCad, Archicad program, or the like.

According to an embodiment of the present invention, a document file such as an image file such as a JPG file, a GIF file, or a PNG file, or a PDF file, can be drawn, so that an image file can be reused, It is possible to make the use of the automatic program without manual operation of the user, thereby making it convenient for use.

On the other hand, an image file (JPG file, GIF file, PNG file, etc.) and / or a PDF file created by photographing a hand-drawn drawing by a user, It is also possible to process and convert to 3D drawing. Hereinafter, the present invention will be described with reference to the accompanying drawings.

FIGS. 8 to 11 are views for explaining a second embodiment of a method of detailing an image file. In the following, the description of the parts described above may be omitted.

8 is a flowchart illustrating a method of drawing an image according to a second embodiment of the present invention, including the steps of: (a) converting drawn drawing information into Lab channels (S201 to S202); (b) separating the Lab channel converted in the step (a) into individual channels and processing the light and dark of the separated L channels to eliminate the influence on illumination (S203); (c) extracting an outline from the image in which the influence of illumination is removed in the step (b) and storing the resultant image (S204); (d) performing labeling of the image stored in the step (c) to detect a blob (S205); (e) detecting and storing a boundary line based on the detected blob (S206); (f) sampling a set of a plurality of points constituting the detected boundary line to determine directionality and detecting an outline (S207); (g) performing a smoothing process using an image from which the influence of illumination is removed and a median filter in step (b), and calculating an image from which the outline is extracted, thereby detecting an image with the outline removed (S208); (h) a step (S209) of template-matching an image in which the outer edge is removed and an image in which the element is detected in step (g); (i) generating (S210) a 2D drawing for an input image by applying the stored outline coordinate information and element coordinate information after template matching in the step (h) to a CAD program; (j) calculating a 3D drawing based on the 2D drawing generated in the step (i) (S211).

The drawing conversion method according to the second embodiment will be described below with reference to FIGS. 1 and 2. FIG.

First, an image to be displayed is input through the input unit 10 (S201). Here, the image to be drawn is a drawing drawn by a user with a hand (sketched drawing). For example, a user draws a drawing by hand to calculate a design drawing. Then, the drawn drawing is photographed using a photographing means such as a camera to generate image information. That is, the drawing is photographed to generate image information such as a JPG file, a GIF file, and a PNG file.

When the image information is inputted, the image file processing unit 20 processes the input image information and displays it. For example, the drawing information (image information) drawn by the illumination effect removal module 31 is converted into a Lab channel (image 1) (S202). That is, the drawn information is converted into the L channel having the brightness information, and the a channel and the b channel having the color information.

Next, the influence of the illumination on the converted Lab channel is removed. That is, the influence of illumination generated when photographing the drawn image information is removed, and only the image information of the actually drawn drawing is extracted.

9, the converted Lab channels are separated into respective channels (L channel, a channel, and b channel) (S301), and the separated L channels are filtered by the median filter to remove the jitter S302). Here, the higher the order of the median filter is, the better, but in the present invention, it is set to 51. [ This is because the higher the order, the lower the performance. Therefore, the optimal order value for achieving the performance is 51. When the L channel image is filtered by the median filter, the surrounding neural information is blurred, so that only the light flow can be left. Therefore, in order to remove the illumination effect of the image, the L channel is filtered by the median filter to extract the light flow from the image. Thereafter, in step S303, the L channel having no pixels is removed (L_channel_not) (S303), and the influence of the illumination is removed by merging the L channel image with the L channel image (Merge).

Next, in step S304, the most significant bit information is received through bit slicing in the image from which the influence of illumination is removed, and the image (image 2) in which only the outline information is expressed is extracted and stored in the storage unit 30. [

Thereafter, the stored image is labeled to detect a blob (S205).

Here, since labeling is a video processing technique that is basically applied to image processing, a detailed description thereof will be omitted. Next, a boundary vector is detected and stored based on the detected blob (image 3) (S206). Here, the boundary line is the process of detecting the largest image in the detected blob.

Then, a set of a number of points constituting the detected boundary line is sampled to determine directionality and an outline is detected (image 4) (S207).

For example, as shown in FIGS. 10 and 11, a Y-axis normal vector and a vector for two points on the x and z axes are externally calculated (B = T ㅧ N) in a three-dimensional environment based on the detected boundary image, (S301). Then, the result of the outer product operation is normalized to a vector having a magnitude value of 1 for each point, and the magnitude values of the vectors are compared (S302). In addition, the correlation of each point is analyzed based on the result of comparing the magnitude values of the vectors (S303), directionality is determined for each set of points based on the analyzed correlation (S304), and the outline is extracted .

Here, the outline extraction means a task of sampling the points by acquiring N in the drawing as shown in FIG. 11 and grasping the correlation with each other. Correlation with each other means a relation to whether it is the same direction or the other direction. If the set of points is defined as a straight line, the direction of N is almost the same direction.

Thereafter, the sampled points are stored as outlines.

If the outline detection is completed through this process, the process proceeds to step S208, where the image with the outline removed is detected and stored (image 5). For example, information on a straight line component effective in a noise-removed image is stored as an outline, and an element is detected when the outline detection is completed. The element detection is performed by smoothing the image by removing the influence of the illumination and the median filter, and then calculating the image by extracting the outline, thereby detecting the image with the outline removed.

Next, template matching is performed for an image in which the outer edge is removed and an image in which the detected element is detected (S109). For example, an image in which an outline is removed and an image in which an element is detected are superimposed. In this case, it is preferable that template matching is performed by prioritizing the door / window / washstand or the like.

Then, in step S210, the outline coordinate information and the element coordinate information stored after the template matching are applied to the CAD program to generate a 2D drawing for the input file. For example, the position value of the matched element in the template matching is stored, the element coordinate information is extracted by calculating the image of the outer edge and the position of the stored element, and the outer coordinate information and the element coordinate information are applied to the CAD program And 2D image of the image file.

Then, in step S211, the 3D drawing is calculated based on the generated 2D drawing. Here you can use the usual Rhino, 3D MAX, AutoCad, and Archicad programs to calculate 2D drawings as 3D drawings.

As described above, according to the present invention, it is possible to simplify drawing of a hand-drawn drawing to a design drawing, thereby allowing a user to conveniently and freely calculate various design drawings. In particular, the image information is automatically handled by the user without manual operation, thereby making it very convenient.

It is possible to use the converted 3D drawing according to the method described above as real estate information. Hereinafter, the present invention will be described with reference to the accompanying drawings.

Figs. 12 to 14 are diagrams for explaining a configuration and a schematic function of a real estate information processing apparatus according to the present invention. Fig. In the following, description of the parts described above may be omitted.

Referring to FIG. 12, the real estate information processing apparatus 1 according to the present invention may include a user terminal 100 and a real estate server 200. In addition, the real estate information processing apparatus 1 may further include a business server 300.

The real estate server 200 may store information on at least one real estate item.

The user can access the real estate server 200 using the user terminal 100. [ The user terminal 100 may be a mobile communication terminal such as a smart phone or a fixed terminal such as a desktop.

The real estate server 200 may provide the 3D drawing of the selected first real estate item to the user terminal 100, for example, when the user terminal 100 selects at least the first real estate thing. In addition, when the user terminal 100 adds an object in the 3D drawing, the real estate server 200 provides the user terminal 100 with recommendation information recommending at least one company corresponding to the added object can do.

The vendor server 300 may provide a quotation. Here, the vendor server 300 may be a server of various vendors. For example, the vendor server 300 may be a server of an interior company, a server of a furniture maker, or a server of a maker of a machine. Hereinafter, for convenience of explanation and understanding, the vendor server 300 will be described as an example of a server of an interior vendor.

Referring to FIG. 13, the real estate server 200 may include an image file processing unit 20 and a storage unit 210.

The storage unit 210 may store information on real estate objects. For example, the storage unit 210 may store an image file of a real estate object. Here, the image file for the real estate object may include a sketch file. The sketch file may be a file for an image drawn manually by the user.

The function of the image file processing unit 20 will be described below with reference to FIG. 14 attached hereto.

As shown in FIG. 14, the image file processing unit 20 may extract an image file of the real estate object stored in the storage unit 210 (S500).

Thereafter, the coordinate data is extracted based on the extracted image file (S510), and the 3D drawing of the real property is constructed based on the coordinate data (S520).

Here, the method of extracting the coordinate data based on the image file has been described in detail with reference to FIG. 1 to FIG. 11, so that further explanation is omitted.

The real estate information processing method using the real estate information processing apparatus 10 described above will be described below.

Figs. 15 to 27 are diagrams for explaining the real estate information processing method. Fig. In the following, description of the parts described above may be omitted.

Referring to FIG. 15, when the user terminal 100 accesses the real estate server 200, the real estate information may be displayed on the screen of the user terminal 100 (S600). For example, as in the case of FIG. 16, the real estate information based on the map can be displayed on the screen of the user terminal 100. Here, the real estate information can include information on at least one real estate object.

Thereafter, it may be determined whether the user terminal 100 selects a real estate item (S610).

As a result of the determination, if a real estate object is selected, the 3D drawing of the selected real estate object may be displayed on the screen of the user terminal 100 (S620). An example of a 3D drawing for a real estate item is shown in Fig.

In this way, displaying the real estate objects in a 3D drawing makes it possible for the user to more easily and accurately check the information of desired real estate objects.

In this document, a residential apartment is described as an example of an estate, but the present invention is not limited thereto. For example, real estate goods can be varied in shops, factories, and the like.

Thereafter, it is judged whether or not the object (Object) is added in the 3D drawing displayed on the screen (S630).

Hereinafter, the object is described by taking a television (TV) as an example, but the present invention is not limited thereto. Objects in this document may include at least one of a wall, a window, a door, a bathtub, a toilet, a washbowl, furniture, a home appliance, a curtain, a machine, a machine, or a blind.

The object may be added according to the determination result (S640).

For example, as in the case of FIG. 18, the user can further arrange the TV 300 in the living room in the 3D drawing of the real property using the user terminal 100.

Thus, the user can add / place a desired object (e.g., TV) on a desired position on a 3D drawing of a real estate object, thereby predicting and confirming the result without actually placing the object.

Thereafter, the real estate server 200 may determine whether the user requests the real estate server 200 to provide recommendation information for the real estate item using the user terminal 100 (S650).

Thereafter, the real estate server 200 may provide the recommendation information to the user terminal 100 according to the determination result (S660).

For example, the user can satisfy the requirement that the TV 300 is further placed in the living room as shown in FIG. 18, and can request recommendation information. In response to the addition of the TV 300, the real estate server 200 can provide the user terminal 100 with recommendation information recommending the company as shown in FIG. FIG. 19 shows recommendation information including a meaning that the TV 300 of 60 inches size arranged in the living room is suitable for purchase in the A electronics store.

In addition, the real estate server 200 may provide a quotation of the recommended company to the user terminal 100. 20 shows an example of a quote. As shown in FIG. 20, the quotation may include information on the vendor and information on the price (cost).

Thereafter, the user can evaluate the satisfaction of the company recommended by the user terminal 100 (S670).

On the other hand, the real estate server 200 can request a quotation from the company. This is described below.

Referring to FIG. 21, the real estate server 200 may transmit a 3D drawing having an object (e.g., a TV 300) to the business server 300 as shown in FIG. 18 and request a quotation (S667) have. That is, the real estate server 200 sends the 3D drawing including the object added by the user to the business, and requests a quotation corresponding to the 3D drawing sent.

Thereafter, the real estate server 200 can receive a quotation from the business server 300 (S662).

Thereafter, the real estate server 200 can recommend / provide (S663) the quotation received from the company server 300 to the user terminal 100 as recommendation information.

Alternatively, in the vendor server 300, it is possible to transmit a quotation corresponding to the information received from the real estate server 200 to at least one of the real estate server 200 and the user terminal 100. That is, in the business server 300, it is possible to transmit the quotation directly to the user terminal 100 without going through the real estate server 200.

Alternatively, as in the case of FIG. 22, the real estate server 200 does not transmit the 3D drawings to the company server 300, but transmits only the changed contents, for example, information about the added objects to the company server 300, It is possible to request a quote (S664).

In this case, the vendor can create a quotation with only the information on the added object and transmit it to the real estate server 200.

In this case, it is also possible for the vendor server 300 to transmit the quotation corresponding to the information received from the real estate server 200 to at least one of the real estate server 200 and the user terminal 100.

Meanwhile, the real estate server 200 is capable of transmitting information to a plurality of company servers 300 and receiving a quotation from a plurality of company servers 300.

In this case, the real estate server 200 is capable of transmitting all quotes to the user terminal 100. [ Alternatively, the real estate server 200 can classify the plurality of received quotations and provide only a predetermined number of quotations to the user terminal 100.

For example, as in the case of FIG. 23, the real estate server 200 can analyze the received quotation (S665) after receiving the quotation from the business server 300 (S662).

Thereafter, the cost can be confirmed (S666) in each quotation.

In addition, the quotation can be classified according to the cost (S667).

For example, as in the case of FIG. 24, each of the estimates received from the electronic stores A, B, C, and D can be analyzed to analyze the cost of each vendor. In addition, each quotation can be categorized as recommendation and non-recommendation. In detail, the real estate server 200 can recommend at least one company in the order of low price (cost) in the received quotation corresponding to the added object. For example, it is possible to recommend one vendor (electronic store) with the lowest price of a 60-inch TV. Alternatively, it may be possible to select a lowest cost company by considering the shipping and installation cost of the TV together with the TV price.

On the other hand, in the real estate server 200, it is possible to provide recommendation information in consideration of the evaluation score (rating) given to each company. Hereinafter, the present invention will be described with reference to the accompanying drawings.

Referring to FIG. 25, in the recommendation step, a vendor may be selected according to a rating (S668). For example, if the user wishes to further arrange a 60-inch TV 300 in the living room, as in the case of FIG. 18 above, the real estate server 200 will have a high order of ratings for the living room 60 inch TV 300 A predetermined number of companies can be selected.

Thereafter, the real estate server 200 transmits a 3D file including the object added to the selected company server 300, transmits information about the added object, and requests a quotation (S661, S664) have.

Thereafter, the real estate server 200 receives the quotation from the business server 300 (S662), and provides the received quotation to the user terminal 100 as recommendation information (S663).

For example, as in the case of FIG. 26, the recommendation information provided to the user terminal 100 may include rating information allocated to each vendor (A, B, C, and D electronic stores). In addition, it is possible to set a company with a reference score of a predetermined rating as a recommendation company.

As described above, in the recommendation step, it is possible to recommend at least one company in the order of higher scores corresponding to the objects whose attributes have been changed.

Alternatively, in the real estate server 200, it is possible to select a recommending company by considering the price (cost) on the quotation and the rating of the company.

For example, as in the case of FIG. 27, suppose that the sub-verbal server 200 receives estimates from the A, B, C, and D electronic stores for the 60-inch TV 300, respectively.

The price (cost) on the estimate of A electronic store is 1,000 won and the rating is 95. The price on the estimate of B electronic store is 1,200,000 won and the rating is 98. The price on the estimate of C electronic store is 2,500,000 won and the score is 92 , D The price on the e-store quotation is 1 million won and the rating can be 65 points.

Assuming that the reference cost is equal to or less than 1,500,000 won and the reference score is equal to or more than 90 points, the real estate server 200 selects A and B electronic stores among the A, B, C, and D electronic stores, It is possible to provide the quotation received from the vendor server 300 of the electronic shop B to the user terminal 100 as recommendation information.

Here, a company (electronic store) that sells the object to the object, for example, the electronic product (TV 300) is selected and recommended as a recommending company, but the present invention is not limited thereto. For example, in this document, it is also possible to set a company corresponding to an object (electronic product) as a manufacturer of an object, not a sales store.

As described above, it is to be understood that the technical structure of the present invention can be embodied in other specific forms without departing from the spirit and essential characteristics of the present invention.

It should be understood, therefore, that the embodiments described above are to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than the foregoing description, And all changes or modifications derived from equivalents thereof should be construed as being included within the scope of the present invention.

Claims (16)

A selection step to select a real estate item;
Displaying a 3D drawing of the selected real estate object;
A placement step of additionally arranging objects in the 3D drawing; And
A recommendation step of recommending at least one vendor corresponding to the disposed objects;
The real estate information processing method comprising the steps of: The method according to claim 1,
Extracting an image file of the selected real estate object;
Extracting coordinate data based on the extracted image file; And
Constructing a 3D drawing of the real estate object based on the coordinate data;
≪ / RTI > 3. The method of claim 2,
Wherein the image file includes a sketch file. The method according to claim 1,
Wherein the object comprises at least one of a wall, a window, a door, a bathtub, a toilet, a washbowl, furniture, a household appliance, a machine, a kit, a curtain or a blind. The method according to claim 1,
And recommending at least one vendor in the recommendation step in order of decreasing price in accordance with the added object. The method according to claim 1,
And recommending at least one vendor in the recommendation order according to the order of the highest rating in correspondence with the added object. The method according to claim 1,
And providing a quotation of the recommended vendor. A real estate server for storing information about at least one property; And
A user terminal connected to the real estate server;
Lt; / RTI >
Wherein the real estate server provides a 3D drawing of the selected first real estate to the user terminal when the user terminal selects at least the first real estate,
Wherein the real estate server further includes a property information processing unit for providing recommendation information for recommending at least one business entity to the user terminal in response to the disposed object in the case where the object is additionally disposed in the 3D drawing provided by the user terminal, Device. 9. The method of claim 8,
Including the vendor's server of the vendor,
The real estate server transmits a 3D drawing in which objects are additionally arranged to the business server,
And the vendor server transmits the quotation corresponding to the 3D drawing received from the real estate server to at least one of the real estate server and the user terminal. 9. The method of claim 8,
Including the vendor's server of the vendor,
The real estate server transmits information on an additional disposed object to the business server,
And the business server transmits the quotation corresponding to the object received from the real estate server to at least one of the real estate server and the user terminal. 11. The method according to claim 9 or 10,
Wherein the real estate server provides the quotation received from a company server of a recommended company to the user terminal. 11. The method according to claim 9 or 10,
The real estate server receives the quotation from a plurality of the vendor servers,
And recommends at least one manufacturer's quotation to the user terminal according to the order of the lowest estimated price. 11. The method according to claim 9 or 10,
The real estate server receives the quotation from a plurality of the vendor servers,
And recommends at least one vendor quotation to the user terminal according to the order of high ratings. 9. The method of claim 8,
The real estate server
Extracts an image file of the selected first real estate object,
Extracts coordinate data based on the extracted image file,
And constructs a 3D drawing of the first real estate object based on the coordinate data. 15. The method of claim 14,
Wherein the image file comprises a sketch file. 9. The method of claim 8,
Wherein the object comprises at least one of a wall, a window, a door, a bathtub, a toilet, a washbowl, furniture, an appliance, a curtain, a machine, a machine, a blind.

Images