Property proposal system, property proposal method and property proposal program

Abstract

To provide a property proposal system for enabling a concrete sales proposal for a specific property by allowing each user to easily visualize an image of a desired property.SOLUTION: A property proposal system 1 causes a processor to execute: a presentation step of presenting a plurality of candidate images representing an image of a property; a first receiving step of receiving a user's selection from the plurality of candidate images; an instruction step of instructing a first artificial intelligence to generate specifications of a property in the selected candidate image; and an output step of outputting a contractor capable of performing construction according to the specifications of the property and an estimate of a cost required for the construction, wherein the first artificial intelligence has a learning model that receives the selected candidate image as an input and outputs the specifications of the property depicted in the selected candidate image.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a property proposal system, a property proposal method, and a property proposal program. [Background technology]

[0002] When a real estate agent proposes to sell a building that has not yet been built to a customer, it is important for the customer to have a concrete image of the property, and it is also important to make sure that there will be no inconveniences when the customer actually wants to build the property.

[0003] For example, Patent Document 1 proposes a device that allows a user to grasp a concrete image of what a building would look like on land by using a three-dimensional composite image. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-174766 Summary of the Invention [Problem to be solved by the invention]

[0005] However, for those without particular expertise in architecture, even if they have a vague image of the property they want to build or live in, it is difficult to convey this to a specialized real estate agent, and even for specialized real estate agents, it is difficult to share that image accurately, so sharing an image incurs a considerable communication cost. Also, rather than consulting a specialized real estate agent straight away, customers often want to first simply know how much it would cost to build the building they want.

[0006] Therefore, one of the objects of the present invention is to enable a user to easily concretize an image of a property desired and to make a concrete sales proposal for the property. [Means for solving the problem]

[0007] In order to achieve the above-mentioned object, a property proposal system according to one aspect of the present invention is a property proposal system in which a processor executes a presentation step of presenting a plurality of candidate images representing an image of a property, a first reception step of accepting a user's selection from the plurality of candidate images, an instruction step of instructing a first artificial intelligence to generate specifications for the property in the selected candidate image, and an output step of outputting contractors who can perform construction according to the specifications of the property and an estimate of the costs required for construction, wherein the first artificial intelligence has a learning model that takes the selected candidate image as input and outputs the specifications of the property represented in the selected candidate image.

[0008] The system may include a contractor information storage means that associates contractors with information indicating the types of work that the contractors can perform and information that serves as a basis for calculating the cost of each work, and in the output step, the second artificial intelligence may be caused to refer to the contractor information storage means and output contractors that can perform work according to the specifications of the property and an estimate of the cost required for the work.

[0009] The information indicating the types of work that the contractor can perform may be an image showing the details of the work that the contractor can perform.

[0010] The method may include a second receiving step of receiving, from a contractor terminal used by the contractor, registration of an image showing the content of the work that the contractor can perform.

[0011] The learning model may be a model that is machine-learned from a contractor and an image representing the construction work that the contractor can perform.

[0012] The image showing the construction content that the contractor can carry out may be the same image as the candidate image.

[0013] The method may also have a third reception step of receiving a request for special construction from a user, and the instruction step may instruct the first artificial intelligence to generate specifications for an item that reflects the special construction received as a request from the user, in accordance with the property in the selected candidate image.

[0014] In the instruction step, the first artificial intelligence is input with the selected image and is instructed to refer to a land information storage means that stores information on land for sale, select land for sale that matches the selected image, and generate specifications for the property in the case where the property shown in the selected image is to be built on the selected land for sale.In the output step, the first artificial intelligence may be instructed to output a contractor who can carry out construction according to the specifications of the property, the cost required for construction, and an estimate of the cost of the selected land for sale.

[0015] A property suggestion method according to another aspect of the present invention includes a computer that executes the following steps: a presentation step of presenting a plurality of candidate images representing an image of a property; a reception step of accepting a user's selection from the plurality of candidate images; an instruction step of instructing a first artificial intelligence to generate specifications for the property in the selected candidate image; and an output step of outputting contractors capable of performing construction according to the property specifications and an estimate of the cost required for the construction, wherein the first artificial intelligence has a learning model that takes the selected candidate image as input and outputs the specifications of the property represented in the selected candidate image.

[0016] A property proposal program according to another aspect of the present invention causes a computer to execute the following steps: a presentation step of presenting a plurality of candidate images representing an image of a property; a reception step of accepting a user's selection from the plurality of candidate images; an instruction step of instructing a first artificial intelligence to generate specifications for the property in the selected candidate image; and an output step of outputting contractors capable of carrying out construction according to the property specifications and an estimate of the cost required for construction, wherein the first artificial intelligence has a learning model that takes the selected candidate image as input and outputs the specifications of the property represented in the selected candidate image. The computer program may be provided as a non-transitory computer-readable medium, or may be provided so that it can be downloaded from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing). [Effects of the Invention]

[0017] According to the present invention, a user can easily concretize an image of a desired property and make a proposal for the sale of a specific property. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a diagram illustrating an overall configuration and a functional configuration of a property proposal system according to an embodiment of the present invention. [Figure 2] FIG. 3 is a sequence diagram showing an example of a flow of processing executed by the property proposal system. DETAILED DESCRIPTION OF THE INVENTION

[0019] A property proposal system 1 according to an embodiment of the present invention will be described below with reference to the drawings.

[0020] ●System configuration FIG. 1 shows the configuration of a property proposal system 1 and a server device 10 according to an embodiment of the present invention.

[0021] The property proposal system 1 is configured to be able to communicate with each other via a network NW and is composed of a server device 10 and a user terminal 20. The server device 10 may be configured as a hardware device, or some or all of the functions may be realized by a cloud computer. Furthermore, each component of the server device 10 may be realized by an API (Application Programming Interface). The communication between the server device 10 and the user terminal 20 may be wireless or wired. Furthermore, the server device 10 may be configured with a plurality of hardware components. In this case, the plurality of hardware components may be connected by wire or wirelessly, and may transmit and receive information to and from each other.

[0022] ●User terminal 20 The user terminal 20 is a terminal operated by a user, such as a smartphone, tablet terminal, or personal computer. The user terminal 20 is configured as functional blocks mainly consisting of an output unit 21, an operation reception unit 22, and a communication processing unit 23, with a CPU (Central Processing Unit), a computer program executed by the CPU, a RAM (Random Access Memory) and a ROM (Read Only Memory) for storing the computer program and predetermined data.

[0023] The output unit 21 is a so-called display unit realized by, for example, a display for displaying data. Information for the user received from the server device 10 is displayed on the output unit 21. The output unit 21 may also include a speaker for outputting sound.

[0024] The operation reception unit 22 is realized by a touch panel, a keyboard, a mouse, a microphone, or the like for inputting data.

[0025] The communication processing unit 23 is a processing unit that enables data transmission and reception processing to and from the server device 10 in accordance with a predetermined protocol via a network NW such as the Internet, and is realized by an application, a web browser, or the like.

[0026] Server device 10 The configuration of the server device 10 will now be described with reference to Fig. 1. The server device 10 is an information processing device that executes a property proposal process while exchanging data with a user terminal 20 via a network NW. The server device 10 stores an image database DB1, a land information database DB2, and a contractor information database DB3.

[0027] Image database DB1 stores candidate images that represent property images. The property in this case refers to land and the building constructed on that land. The property image represents the specific details of the property, such as the appearance of the land and the building constructed on that land.

[0028] The candidate images may be photographic data of actual buildings, or may be composite images, illustration images, etc. Furthermore, the candidate images may be collected from the Internet or the like, or may be provided by users. A candidate image representing an image of a property may be composed of multiple images. For example, a candidate image representing a property may be composed of two images, one representing the exterior and one representing the interior. Each candidate image may also be provided with information describing the content of the property depicted in the candidate image. The data format of the candidate images is not particularly limited as long as it is a format that can be read by the server device 10 .

[0029] The land information database DB2 stores information on land that is actually for sale. The land information includes a wide range of information required when constructing a building on the land or information that a buyer needs to confirm, such as the address, area, and shape of the land, as well as the selling price and information about the surrounding environment. It may also include two-dimensional or three-dimensional images of the land.

[0030] The contractor information database DB3 stores information about contractors who carry out various construction work according to the specifications of the building to be constructed. In addition to basic information such as the contractor's name and address, the contractor information includes information that serves as the basis for determining whether a specific task can be performed and for estimating the cost of the task, such as the types of work that each contractor can perform and the unit cost of the work that serves as the basis for calculating the cost of each task. It may also include information regarding the contractor's schedule and the time required for the work, which allows you to know when the contractor will be able to accept the work and how long it will take if you order a specific work from a contractor.

[0031] Furthermore, as information indicating the types of work that each contractor can perform, images representing work that the contractor has actually performed or images representing work that the contractor can perform may be registered. Such image registration may be accepted from a terminal used by the contractor on a predetermined webpage. Furthermore, images prepared by the contractor themselves may be registered in the contractor information database DB3 via a predetermined webpage, or the contractor may be allowed to select images representing various types of work that have been prepared in advance, and the images may be associated with the selected contractor and registered. Furthermore, the same image that the user selects as a candidate image may be used as the image registered as an image representing work that the contractor can actually perform.

[0032] As shown in FIG. 1, the server device 10 is configured with functional blocks, mainly consisting of a display control unit 11, a memory control unit 12, an AI control unit 13, an artificial intelligence unit 14, and a communication processing unit 15, which are made up of a CPU (Central Processing Unit, which is an example of a processor in the claims), a computer program executed by the CPU, RAM (Random Access Memory) and ROM (Read Only Memory) for storing the computer program and predetermined data.

[0033] The display control unit 11 executes processing for displaying a screen related to the property proposal system 1 on the user terminal 20. The display control unit 11 performs processing such as generating and transmitting an HTML (Hyper Text Markup Language) file, and displays a web page on the user terminal 20 as a screen that the user views when receiving property proposals in this system. The display control unit 11 may also perform processing such as generating and transmitting display data for an application for using the property proposal system 1.

[0034] The storage control unit 12 is a functional unit that controls appropriate storage devices provided in the server device 10 and writes and reads data. The storage control unit 12 stores information received via a predetermined registration screen, for example, in each of the databases DB1, DB2, and DB3.

[0035] The AI ​​control unit 13 is a functional unit that controls input to the artificial intelligence unit 14. The AI ​​control unit 13 receives as input a candidate image representing an image of a property selected and input by a user, and generates a prompt that commands the AI ​​control unit 13 to output the specifications of the property shown in the candidate image. The AI ​​control unit 13 also generates a prompt that commands the AI ​​unit 14 to output contractors who can perform construction according to the property specifications and an estimate of the cost required for construction. The prompt is information that instructs the artificial intelligence unit 14 on the content to be generated, and is, for example, a character string written in a natural language.

[0036] The artificial intelligence unit 14 is an AI equipped with a language model such as a transformer including BART (Bidirectional and Auto-regressive Transformer), BERT (Bidirectional Encoder Representations from Transformers), or GPT (Generative Pretrained Transformer, including GPT-1, GPT-2, and GPT-3), in particular a learning model such as a large language model (LLM, Large Language Models). A learning model (also called a machine learning model) refers to a learning model based on a machine learning algorithm. Specific examples of machine learning algorithms include nearest neighbor methods, naive Bayes methods, decision trees, and support vector machines. Another example is deep learning, which uses a neural network to generate features and connection weighting coefficients for learning. The artificial intelligence unit 14 can apply the above algorithms as appropriate.

[0037] The artificial intelligence unit 14 has, as its artificial intelligence, a trained model constructed by a learning method such as supervised learning, unsupervised learning, or self-supervised learning. In supervised learning, machine learning is performed using training data (training data). The training data consists of pairs of input data and output data (correct answer data) for learning. Furthermore, the language model may not only be one trained for a specific task, but also a general-purpose model that can be used for a wide range of tasks.

[0038] The artificial intelligence included in the artificial intelligence unit 14 has previously acquired appropriate learning data, but can undergo additional learning. For example, a large amount of images representing the image of a property may be provided as input data. Fine-tuning may also be performed using a training dataset that pairs images representing the image of a property with the specifications of the property in the image. Furthermore, while the property recommendation system 1 is actually in operation, fine-tuning may be performed using a correction dataset that provides feedback on the property specifications generated by the artificial intelligence unit 14 in response to candidate images selected by the user. This optimizes the content output from the learning model. In addition, the server device 10 may refer to the contractor information database DB3 and perform machine learning on contractors and images representing the work that the contractors can perform. This allows the server device 10 to appropriately determine whether or not there are contractors who can perform the work shown in the construction image, based on the relationship between the candidate image selected by the user and the images representing the work that each contractor can perform. In particular, if the same image selected by the user as the candidate image is used as the image representing the work that the contractor can actually perform, the selection of the construction contractor becomes more reliable.

[0039] In this embodiment, the learning model included in the artificial intelligence unit 14 can input a candidate image selected by the user and output the specifications of the property depicted in the selected candidate image. As a result, in an example of function execution, the artificial intelligence unit 14 inputs a candidate image representing an image of the property selected and input by the user, and generates and outputs the specifications of the property depicted in the candidate image based on a prompt generated by the AI ​​control unit 13.

[0040] Property specifications are information about the building that is required when constructing a building on land, such as the property's layout, the building's orientation relative to the land, construction details, etc. This information about property specifications allows you to understand what type of work will be required when constructing a building, as well as the shape and area of ​​the land required to build a building with those specifications.

[0041] In another example of function execution, the artificial intelligence unit 14 receives information related to the specifications of a property as input, generates and outputs property proposal information based on a prompt generated by the AI ​​control unit 13. The property proposal information is simulation information for when the property shown in the selected candidate image is actually offered, and includes information on actual land for sale similar to the property, contractors who can construct properties similar to the property, estimates of the costs of the land for sale and construction, etc. By referring to the proposal information generated by the artificial intelligence unit 14, the user can understand the actual cost and location at which the property they want can be purchased.

[0042] The generation of property proposal information can be performed using a learning model possessed by the AI ​​unit 14, or it can be optimized by referencing information in the land information database DB2 and / or the contractor information database DB3 using RAG (Retrieval Augmented Generation). That is, when proposing properties based on candidate images selected by the user, the AI ​​unit 14 is prompted to reference the land information database DB2 to select land from those registered in the land information database DB2. This allows the AI ​​unit 14 to propose properties based on the user's desired properties, based on available land rather than fictitious land or land not for sale, and to understand the cost and contractors available for the property. Similarly, the AI ​​unit 14 is prompted to reference the contractor information database DB3 to obtain contractor information based on information registered in the contractor information database DB3. This allows for more realistic estimates and construction details, and by referencing the contractor schedule, the construction time and other factors can be estimated.

[0043] The communication processing unit 15 is a processing unit that can execute data transmission and reception processing according to a predetermined protocol with the user terminal 20 via a network NW such as the Internet. The communication processing unit 15 receives requests for proposals from the user terminal 20, and transmits information related to property proposals generated by the artificial intelligence unit 14 to the user terminal 20.

[0044] The communication processing unit 15 allows the server device 10 to present a plurality of candidate images representing the image of the property to the user via the user terminal 20.

[0045] Furthermore, the communication processing unit 15 allows the server device 10 to receive the following information from the user terminal 20: That is, in one example, the communication processing unit 15 receives, from the user terminal 20, a user's selection from a plurality of candidate images representing properties.

[0046] In another example, the communication processing unit 15 accepts registration of an image showing the content of work that the contractor can perform from the contractor terminal used by the contractor, etc., from the user terminal 20. The image showing the content of work that the contractor can perform may be registered in, for example, the contractor information database DB3.

[0047] In another example, the communication processing unit 15 accepts additional requests for a property from the user terminal 20. The additional requests for a property are requests for additional construction work for the property shown in the candidate image selected by the user, such as a request for special construction work. There are cases where the user's detailed wishes cannot be fully reflected by selecting a candidate image alone, and in such cases, it would be convenient if the additional requests could be added separately from the selection of the candidate image. The additional requests may be provided, for example, separately from the selection of the candidate image, and provided to the user as arbitrarily selectable items. The arbitrarily selectable items may be presented in text format or in image format. In addition, it may be possible to input other additional requirements such as location, building or land area, budget, etc. These additional requests constitute part of the prompts generated by the AI ​​control unit 13 for the artificial intelligence unit 14, thereby making it possible to request the server device 10 to generate and output property specifications that take the additional requests into account.

[0048] ●Processing flow 2, first, the server device 10 refers to the image database DB1 and transmits a plurality of candidate images to the user terminal 20, requesting the selection of a desired property (step S101). In response, the user selects a candidate image representing a property that matches their desires (step S102). Note that the user may be able to input additional requests for the property along with the selection of the candidate image.

[0049] The AI ​​control unit 13 inputs the candidate image selected by the user to the artificial intelligence unit 14 and causes it to output the specifications of the property appearing in the candidate image (step S103). The AI ​​control unit 13 causes the artificial intelligence unit 14 to refer to the land information database DB2 and the contractor information database DB3 (steps S104, S105), select land for sale that matches the image of the property represented by the candidate image, and output specific construction details and cost estimates according to the property specifications, as well as information on contractors who can carry out the construction (step S106). The output information is transmitted to the user terminal 20 as property proposal information (step S107).

[0050] As described above, the property proposal system 1 according to the present invention can make the property desired by the user specific even from a vague image, and can propose a practical property.

[0051] In this embodiment, more detailed requests may be incorporated as one of the user's additional requests or as a separate additional request as conditions on the user's side and reflected in the property proposal. For example, when a user selects a candidate image, the user may be allowed to input conditions such as a budget, construction time, or construction period. In this case, for example, the AI ​​control unit 13 may incorporate an instruction to generate a result that reflects the conditions into a prompt for the artificial intelligence unit 14. Such an instruction may request that a result be generated based on learned data, or may request that a result be generated by referring to the contractor information database DB3. Furthermore, it may be possible to narrow down the property proposal information generated by the artificial intelligence unit 14 based on the user's budget and construction period. Furthermore, the server device 10 may transmit a request for the user's desired budget and construction period to the contractor terminal of a contractor who is capable of construction and is included in the property proposal information, and may transmit a response to the request received from the contractor terminal to the user terminal 20.

[0052] The server device 10 may also be provided with a discrimination processing unit that refers to the contractor information database DB3 based on the property specification information generated by the artificial intelligence unit 14 and discriminates contractors who can perform construction work in accordance with the specification information. In this case, the discrimination processing unit may discriminate contractors who can perform construction work based not only on the specification information but also on conditions such as the budget, construction time, or construction period separately received from the user. For example, the budget is determined based on the unit price set by the contractor, and the construction time and construction period are determined from the contractor's schedule information. [Explanation of symbols]

[0053] 1. Property proposal system 10 Server device 11 Display control unit 12 Memory control unit 13 AI control section 14 Artificial Intelligence Department 15. Communication processing section DB1 Image Information Database DB2 Vendor Information Database DB3 Land Information Database 20 User terminal

Claims

1. A property proposal system, a contractor information storage means for associating contractors with information indicating the types of work that the contractors can perform and information that serves as a basis for calculating the cost of each work; The processor: a presentation step of presenting a plurality of candidate images representing images of the constructed property to the user; a first receiving step of receiving a user's selection from the plurality of candidate images; a first instruction step of instructing the first artificial intelligence to extract construction details of the property in the selected candidate image; a second instruction step of instructing the second artificial intelligence to select and estimate a contractor capable of constructing the property in the selected candidate image by referring to the contractor information storage means; an estimation step of referring to the contractor information storage means, inputting the construction details of the property extracted by the first artificial intelligence, referring to the contractor information storage means, and outputting a contractor who can perform the construction of the property and an estimate; The first artificial intelligence has a learning model that receives the candidate image as an input and outputs the construction details of the property shown in the candidate image. Property proposal system.

2. a land selection step of selecting a land for sale that matches the selected candidate image by referring to a land information storage means that stores information on land that is up for sale, based on the selected candidate image; In the estimation step, an estimate including the cost of the selected land for sale is output. The property suggestion system according to claim 1.

3. A property proposal method comprising: a contractor information storage means for associating contractors with information indicating the types of work that the contractors can perform and information that serves as a basis for calculating the cost of each work; By computer, a presentation step of presenting a plurality of candidate images representing images of the constructed property to the user; a first receiving step of receiving a user's selection from the plurality of candidate images; a first instruction step of instructing the first artificial intelligence to extract construction details of the property in the selected candidate image; a second instruction step of instructing the second artificial intelligence to select and estimate a contractor capable of constructing the property in the selected candidate image by referring to the contractor information storage means; an estimation step of referring to the contractor information storage means, inputting the construction details of the property extracted by the first artificial intelligence, referring to the contractor information storage means, and outputting a contractor who can perform the construction of the property and an estimate; The first artificial intelligence has a learning model that receives the candidate image as an input and outputs the construction details of the property shown in the candidate image. Property proposal method.

4. A property proposal program, a contractor information storage means for associating contractors with information indicating the types of work that the contractors can perform and information that serves as a basis for calculating the cost of each work; For computers, a presentation step of presenting a plurality of candidate images representing images of the constructed property to the user; a first receiving step of receiving a user's selection from the plurality of candidate images; a first instruction step of instructing the first artificial intelligence to extract construction details of the property in the selected candidate image; a second instruction step of instructing the second artificial intelligence to select and estimate a contractor capable of constructing the property in the selected candidate image by referring to the contractor information storage means; an estimation step of referring to the contractor information storage means, inputting the construction details of the property extracted by the first artificial intelligence, referring to the contractor information storage means, and outputting a contractor who can perform the construction of the property and an estimate; The first artificial intelligence has a learning model that receives the candidate image as an input and outputs the construction details of the property shown in the candidate image. Property proposal program.

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