Data processing device, data processing method, and data processing program

Abstract

To provide a data processing device capable of supporting achievement of a custom-built house by a user, a data processing method, and a data processing program.SOLUTION: A data processing device comprise an input unit 292 which acquires user data, a processing unit 294 which performs specific processing using a data generation model for generating prescribed inference results according to the user data, and an output unit 296 which outputs the results of specific processing to a prescribed device. The input unit 292 acquires constraint data indicative of constraints on a custom-built house as user data from the device. The processing unit 294 performs processing for deriving building data indicative of a building subject to custom-built house as specific processing using an output of the data generation model when constraint data was input.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The technology disclosed herein relates to a data processing device, a data processing method, and a data processing program. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional technology does not take custom-built buildings into consideration, and there is room for improvement in supporting users in realizing custom-built buildings. [Means for solving the problem]

[0005] A first aspect of the technology disclosed herein is a data processing device comprising an input unit for acquiring user data, a processing unit for performing specific processing using a data generation model that generates a predetermined inference result according to the user data, and an output unit for outputting the result of the specific processing to a predetermined device, wherein the input unit acquires constraint condition data indicating constraint conditions related to custom building from the device as user data, and the processing unit performs the specific processing of deriving building data indicating the building to be custom built using the output of the data generation model when the constraint condition data is input.

[0006] A second aspect of the technology disclosed herein is a data processing method that acquires user data, performs specific processing using a data generation model that generates a predetermined inference result according to the user data, and outputs the result of the specific processing to a predetermined device, in which constraint condition data indicating constraint conditions related to custom construction is acquired as user data from the device, and the specific processing is performed by using the output of the data generation model when the constraint condition data is input to derive building data indicating the building to be custom built.

[0007] A third aspect of the technology disclosed herein is a data processing program that causes a computer to execute a process that acquires user data, performs specific processing using a data generation model that generates a predetermined inference result according to the user data, and outputs the result of the specific processing to a predetermined device, where the specific processing acquires constraint condition data indicating constraint conditions related to custom construction as user data from the device, and uses the output of the data generation model when the constraint condition data is input to derive building data indicating the building to be custom constructed. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a conceptual diagram illustrating an example of a configuration of a data processing system. [Diagram 2] FIG. 2 is a conceptual diagram showing an example of main functions of a data processing device and a smart device. [Diagram 3]2 shows a schematic functional configuration of a specific processing unit of the data processing device. [Figure 4A] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 4B] 1 shows an emotion map onto which multiple emotions are mapped. [Diagram 5] 13 illustrates an example of an operational flow of a specific process performed by a data processing device. [Figure 6] FIG. 13 is a diagram illustrating an example of constraint conditions for a building. [Figure 7] FIG. 1 is a diagram showing an example of a conventional custom-built construction process. [Figure 8] FIG. 11 is a diagram illustrating an example of data generated by a data generation model. [Figure 9] 10 is a flowchart showing an example of the flow of a first identification process executed by the data processing device. [Figure 10] FIG. 13 is a diagram showing an example of a conversation when acquiring desired condition data in a data processing device. [Figure 11] 10 is a flowchart showing an example of the flow of a second identification process executed by the data processing device. [Figure 12] FIG. 13 is a diagram illustrating an example of a proposal selection screen. [Figure 13] 13 is a flowchart showing an example of the flow of a third identification process executed by the data processing device. [Figure 14] FIG. 2 is a schematic diagram showing an overall processing flow by the data processing system. [Figure 15] FIG. 13 is a diagram for explaining the effect of the data processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an example of an embodiment of a data processing device, a data processing method, and a data processing program according to the technique of the present disclosure will be described with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0016] FIG. 1 shows an example of the configuration of a data processing system 10 according to the embodiment.

[0017] As shown in Fig. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. An example of the smart device 14 is a smartphone. In this embodiment, the data processing device 12 is an example of a "data processing device" according to the technology of the present disclosure.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by touch. The microphone 38B detects the user's voice to receive user input by voice. The processor 46 transmits data indicative of the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the processor 28 acquires the data indicative of the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to a person by outputting the data in a form of expression that the person can perceive (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "data processing program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58. The data generation model 58 is used by the identification processing unit 290. The storage 32 also stores an emotion identification model 59.

[0026] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0027] Next, the processing of the specific processing unit 290 when the data processing device 12 performs specific processing to support the realization of a custom-built house by a user will be described.

[0028] As shown in FIG. 3, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0029] The input unit 292 acquires user input received by the smart device 14. Specifically, the input unit 292 acquires at least one of text, voice, and image data of the user received by the smart device 14.

[0030] The processing unit 294 performs a specific process using the data generation model 58. Specifically, character, voice, and image data input by the user are input to the data generation model 58, and a generation result is obtained. In addition, a result of the specific process is generated based on the generation result.

[0031] The output unit 296 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0032] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0033] The emotion identification model 59 determines the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 can determine the emotion of the user according to an emotion map (see FIG. 4A), which is a specific mapping. The emotion of the user determined by the emotion identification model 59 can be used in the identification process.

[0034] FIG. 4A is a diagram showing an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from mental states are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0035] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0036] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0037] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0038] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[0039] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple learning data that are combinations of the user input and emotion values ​​indicating each emotion shown in the emotion map 400. In addition, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 4B. FIG. 4B shows an example in which multiple emotions, "relief," "calm," and "encouraging," have similar emotion values.

[0040] Next, the operation of the data processing system 10 will be described.

[0041] An example of the flow of the identification process will be described with reference to Fig. 5. Note that the flow of the identification process shown in Fig. 5 is an example of a "data processing method" according to the technology of the present disclosure.

[0042] In step S300, the processing unit 294 determines whether a predetermined trigger condition is met.

[0043] If the trigger condition is met in step S300 (step S300; Yes), the data processing system 10 proceeds to step S301. On the other hand, if the trigger condition is not met in step S300 (step S300; No), the data processing system 10 ends the identification process.

[0044] In step S301, the processing unit 294 generates a prompt by adding an instruction for obtaining a result of a specific process to the text representing the input.

[0045] In step S303, the processing unit 294 inputs the generated prompt to the data generation model 58, and obtains the result of the specific process based on the output of the data generation model 58.

[0046] In step S304, the output unit 296 outputs the result of the specific processing to the smart device 14, and the specific processing ends.

[0047] Meanwhile, while the demand for custom-built homes, such as detached houses, has been increasing in recent years, custom-built homes have many stages and constraints, and require a great deal of work from both the client and the construction company staff, which means that a great deal of effort is required before construction can even begin on the target building (hereinafter referred to simply as the "building").

[0048] For example, as shown in FIG. 6, the constraints on a building include many conditions such as the area and shape of the land (hereinafter simply referred to as "land") on which the building is to be built, the floor area ratio, the building coverage ratio, slope restrictions, height restrictions, conditions on the structural calculation of the building, conditions on electricity, conditions on water supply and sewerage, conditions on soundproofing, etc. For example, the constraints on electricity include whether or not the house needs to be all-electric, and whether or not gas piping is required. In addition, the constraints on water supply and sewerage include the locations of water facilities such as the kitchen, bath, toilet, and washroom, and in particular, with regard to the sewerage, problems such as water not flowing well unless there is a proper slope will occur. In addition, the constraints on soundproofing include, for example, the thickness of the wall, and depending on the thickness of the wall, the soundproofing performance will be affected, which will affect the layout and budget.

[0049] These constraints, such as the land area, land shape, building coverage ratio, floor area ratio, setback regulations, and height restrictions, are uniquely determined by the land on which the building is to be constructed, but other constraints are also greatly influenced by the wishes of the client, and so the wishes of the client must also be taken into consideration. Note that the "client" referred to here includes not only the client himself, but also those related to the client, such as the client's family and relatives. In what follows, the constraints determined by the land are referred to as "land conditions," and other constraints related to the client's wishes are referred to as "request conditions."

[0050] Also, as shown in FIG. 7 as an example, many steps must be taken when carrying out custom construction. In the example shown in FIG. 7, there is the first step of considering the budget and creating an image of the building, the second step of selecting a house manufacturer (hereinafter also referred to as a "construction company") and searching for land, and the third step of proposing a plan for the building's layout and presenting a budget plan, and these steps alone take approximately 2 to 3 months. Next, in the example shown in FIG. 7, there is the fourth step of making a construction contract, and the fifth step of holding detailed meetings and deciding on the plan, and these steps alone take approximately 3 to 4 months. Furthermore, in the example shown in FIG. 7, there is the sixth step of starting construction on the building, and the seventh step of completing and handing over the building, and these steps alone take approximately 4 to 6 months.

[0051] As such, custom construction involves many steps, and it takes roughly six months just to get construction started on the building.

[0052] Therefore, in the specific processing according to this embodiment, processing is performed to support the process up to the start of construction of a building when carrying out a custom-built building.

[0053] The specific processing of this embodiment will be described more specifically below with reference to Figures 8 to 15. The specific processing of this embodiment has the following functions to achieve the following objectives.

[0054] In other words, in response to the problem that there is room for improvement in supporting users in realizing custom-built buildings, the specific process: Using a data generation model58, we support the creation of design images, blueprints, schedules, cost estimates, etc. for the custom-built house that the user desires. In this case, the goal is to design 90% of the buildings creatively while satisfying all construction conditions such as the land floor area ratio, building area ratio, setback regulations, height restrictions, budget, etc. Create a competitive environment among construction companies and assist with the contracting of actual house construction. · Improve the performance of the data generation model58 by accumulating design images, design drawings, schedules, cost estimates, etc. obtained from architectural companies as learning data. It has the following function.

[0055] That is, the input unit 292 of the data processing device 12 according to this embodiment acquires constraint condition data indicating constraint conditions related to the custom-built building as user data from the smart device 14. The processing unit 294 according to this embodiment performs, as a specific process, a process of deriving building data indicating the building to be built to order, using the output of the data generation model 58 when the constraint condition data is input. In particular, the input unit 292 according to this embodiment acquires at least a part of the constraint condition data by a conversation with the owner of the building using the data generation model 58.

[0056] In the data processing system 10 according to this embodiment, the constraint condition data includes at least one of land condition data indicating the above-mentioned land conditions regarding the land on which the building is to be constructed, and desired condition data indicating the above-mentioned desired conditions regarding the desires of the owner of the building (both in this embodiment). In the data processing system 10 according to this embodiment, the building data includes at least one of design drawing data indicating the design drawing of the building, design image data indicating the design image of the building, schedule data indicating the schedule for constructing the building, and cost estimate data indicating the estimated cost required for constructing the building (all in this embodiment).

[0057] In this embodiment, data showing the area and shape of the land in the land condition data is data showing the plan view of the land (hereinafter referred to as "land plan data"), but this is not limited to this. For example, data describing the area and shape of the land in text may be used as data showing the area and shape of the land in the land condition data.

[0058] On the other hand, as an example, as shown in FIG. 8, in the data processing system 10 according to the present embodiment, the data generation model 58 includes two data generation models, a first data generation model 58A used for the above conversation and a second data generation model 58B used for deriving building data. Specifically, the input unit 292 according to the present embodiment acquires desired condition data in the constraint condition data by talking with the user using the first data generation model 58A. In addition, the processing unit 294 according to the present embodiment derives design drawing data, design image data, schedule data, and cost estimate data using the land condition data, desired condition data, and the second data generation model 58B.

[0059] In this manner, in the present embodiment, the data generation model 58 includes two models, the first data generation model 58A and the second data generation model 58B, but is not limited to this. For example, the data generation model 58 may include these models integrally as one model.

[0060] The input unit 292 according to the present embodiment acquires land condition data by having the user input information indicating the construction site of the building (information indicating latitude and longitude in the present embodiment) and searching the external database using the information, but the present embodiment is not limited to this. For example, the user may input an address (residential address) instead of latitude and longitude, and the address may be used to search the external database to acquire the land condition data, or the user may directly input the land condition data to acquire the land condition data. The land conditions indicated by the land condition data are not limited to the above-mentioned area, shape, building coverage ratio, floor area ratio, slope regulation, and height restriction, and any condition that restricts the building on the corresponding land, such as the boundary line of the neighboring land or the distance from the road to the building, may be applied.

[0061] In addition, in the data processing system 10 according to the present embodiment, data showing a walk-through video targeting at least one of the exterior and interior of a building (both in the present embodiment) is applied as design image data, but this is not limited to this. For example, instead of the walk-through video, data showing a perspective (perspective drawing) targeting at least one of the exterior and interior of a building may be applied as design image data.

[0062] Moreover, the processing unit 294 according to this embodiment derives a plurality of building data satisfying the constraint conditions as selection candidates, the output unit 296 outputs the selection candidates to the smart device 14, and the input unit 292 further acquires a selection instruction from the selection candidates by the user. This allows the user to select a desired building data from a plurality of building data satisfying the constraint conditions, thereby improving the user satisfaction.

[0063] The processing unit 294 according to this embodiment further executes, as a specific process, a contract support process for supporting the conclusion of a construction contract between the owner of the building and the construction company that will build the building, using at least one of the above constraint conditions and the building data (both in this embodiment). Here, the processing unit 294 according to this embodiment executes the contract support process by treating a plurality of predefined construction companies as candidate companies that will conclude a construction contract with the owner.

[0064] Specifically, the processing unit 294 according to the present embodiment transmits, via the output unit 296, to the multiple construction companies, at least one of the building data derived by the specific process and the constraint conditions corresponding to the building data (both in the present embodiment) together with a request for quotation, which will be described later. In response to this, the multiple construction companies refer to the building data and the constraint conditions received from the data processing device 12, create a proposal indicating the contract conditions that satisfy the various conditions indicated by the constraint conditions as much as possible, and transmit proposal data indicating the proposal to the data processing device 12. Then, the processing unit 294 according to the present embodiment receives the proposal data transmitted from the multiple construction companies via the input unit 292. Then, the processing unit 294 causes the smart device 14 to display, via the output unit 296, a proposal selection screen that selectably displays multiple proposals presented by the multiple construction companies indicated by the received proposal data. Therefore, the user can compare and consider proposals from multiple construction companies, and as a result, the user's satisfaction can be improved.

[0065] Furthermore, the processing unit 294 according to this embodiment further executes, as a specific process, a process of learning the data generation model 58 using design documents (in this embodiment, design drawing data, design image data, schedule data, and cost estimate data applied as building data) created based on the building data by a construction company with which the construction contract has been concluded with the client. In particular, the processing unit 294 according to this embodiment further executes, as a specific process, a process of paying a fee for the provision of the design documents to the corresponding construction company.

[0066] Next, the operation of the data processing device 12 according to this embodiment when executing the identification process will be described with reference to Figs. 9 to 15. In the following, the identification process will be described by dividing it into three processes: an identification process that mainly supports the creation of building data (hereinafter referred to as "first identification process"), an identification process that mainly supports the conclusion of a construction contract (hereinafter referred to as "second identification process"), and an identification process that mainly learns the data generation model 58 (here, the second data generation model 58B) (hereinafter referred to as "third identification process"). The first identification process, the second identification process, and the third identification process are executed by the processor 28 executing the identification process program 56 stored in the storage 32.

[0067] First, the operation of the data processing device 12 when executing the first identification process will be described with reference to Figs. 9 and 10. Fig. 9 is a flowchart showing an example of the flow of the first identification process executed by the data processing device 12, and Fig. 10 is a diagram showing an example of a conversation when the data processing device 12 acquires desired condition data. The process flow shown in Fig. 9 is an example of a data processing method according to the technology of the present disclosure. Note that, in order to avoid confusion, a case will be described in which the first data generation model 58A and the second data generation model 58B have already been constructed. Also, a case will be described in which the owner of the building is a user of the smart device 14 (hereinafter simply referred to as "user"), and the execution of the first identification process is started when the user instructs the execution of the first identification process to be started via the smart device 14 (hereinafter referred to as "target device").

[0068] In step S10, the input unit 292 acquires land condition data as described above, and in step S12, the input unit 292 acquires desired condition data using the first data generation model 58A as described above.

[0069] When obtaining desired condition data using the first data generation model 58A, as shown in Fig. 10, for example, the user is first asked a question about what prompted him to build a building, and then further questions are asked with specific suggestions depending on the content of the answer. By repeating this exchange, desired condition data indicating the desired conditions of the owner of the building with respect to the building is obtained.

[0070] In step S14, the processing unit 294 inputs the acquired land condition data and desired condition data into the second data generation model 58B to derive building data including design drawing data, design image data, schedule data, and cost estimate data. As described above, the processing unit 294 derives a plurality of building data satisfying the constraint conditions indicated by the land condition data and desired condition data as selection candidates.

[0071] Therefore, in step S16, the output unit 296 controls the target device to display a building data selection screen (not shown) that displays the derived building data in a selectable manner. In response to this control, the target device displays the building data selection screen on the display 40A, and the user specifies desired data from the displayed building data via the touch panel 38A. In response to this, the target device transmits to the data processing device 12 identification information for identifying the building data specified by the user.

[0072] Therefore, in step S18, the input unit 292 acquires the user's selection result by receiving the identification information transmitted from the target device. In step S20, the processing unit 294 registers the building data identified by the received identification information (hereinafter referred to as "selected building data") and at least one (in this embodiment, both) of the constraint conditions (land condition data and desired condition data) corresponding to the selected building data by storing them in the storage 32, and then ends the first identification process. Note that the selected building data and constraint conditions registered here are also referred to as "registered data" below.

[0073] Incidentally, when a user wishes to obtain an estimate of the cost required to build the building indicated by the selected building data (hereinafter referred to as a "construction cost estimate"), the user requests the construction cost estimate.

[0074] Next, the operation of the data processing device 12 when executing the second identification process will be described with reference to Fig. 11 and Fig. 12. Fig. 11 is a flow chart showing an example of the flow of the second identification process executed by the data processing device 12, and Fig. 12 is a diagram showing an example of a proposal selection screen. The second identification process according to this embodiment is started when a request for the above-mentioned construction cost estimate is received from the target device by the user.

[0075] In step S30, the processing unit 294 executes a fee receiving process, which is a process for receiving a fee (in this embodiment, a fee) from the user who has requested the construction cost estimate for the presentation of the proposal.

[0076] In step S32, the output unit 296 sends a request for an estimate (hereinafter referred to as an "estimate request") for constructing a building corresponding to the registered data, together with the registered data corresponding to the user, to multiple construction companies (hereinafter referred to as "contracted construction companies") that have been contracted in advance to be construction companies to be introduced to the user.

[0077] The contracted construction company that has received the quotation request creates the above-mentioned design documents and proposal documents by referring to the constraint conditions and building data indicated in the registered data received together with the quotation request, and transmits the design documents data indicating the design documents and the proposal data indicating the proposal documents to the data processing device 12. At this time, the contracted construction company makes adjustments to the design drawings indicated by the selected building data in the received registered data so that they fit the building components that it can provide, and then creates the design documents data and proposal data that satisfy the received constraint conditions.

[0078] Therefore, in step S34, the input unit 292 waits until it receives combinations of proposal data and design document data from all contracted construction companies. In step S36, the output unit 296 controls the target device to display a proposal selection screen having a predetermined configuration for presenting proposals indicated by the proposal data in a selectable manner, using the combinations of proposal data and design document data received from the multiple contracted construction companies. In response to this control, the target device displays the proposal selection screen shown in FIG. 12, for example, on the display 40A.

[0079] As shown in FIG. 12, the proposal selection screen according to this embodiment displays a message prompting the user to select a desired proposal from among the proposals displayed, or the name of a construction company corresponding to the proposal. In addition, the proposal selection screen according to this embodiment displays proposals indicated by the proposal data received from the multiple contracted construction companies, together with information indicating the names of the corresponding construction companies. When the proposal selection screen is displayed on the display 40A, the user specifies, via the touch panel 38A, a display area of ​​a desired proposal from among the displayed proposals, or a display area of ​​the name of a contracted construction company corresponding to the proposal. In response to this, the target device transmits to the data processing device 12 specific information for identifying the proposal specified by the user. Thus, in this embodiment, only the proposals indicated by the proposal data received from the multiple contracted construction companies are displayed, but this is not limited to this form. For example, in addition to the proposal, the design documents indicated by the design document data corresponding to the proposal may also be displayed.

[0080] Therefore, in step S38, the input unit 292 acquires the selection result by the user by receiving the specific information transmitted from the target device. In step S40, the output unit 296 transmits, to the target construction company (hereinafter referred to as the "adopting construction company") corresponding to the proposal indicated by the received specific information, employment information indicating that the proposal submitted by the adopting construction company has been adopted by the user. By receiving this employment information, the adopting construction company can know that its proposal has been adopted by the user.

[0081] In step S42, the processing unit 294 executes a contract support process that is predetermined to support the conclusion of a construction contract between the user and the adopting construction company, and then ends the second specific process. In this embodiment, the contract support process is a process that supports the adopting construction company and the user to directly enter into a contract based on a construction contract document while they are face-to-face, but is not limited to this. For example, the contract support process may be a process that supports the adopting construction company and the user to electronically enter into a contract based on a construction contract document via the Internet or the like without meeting face-to-face. In this embodiment, the contract support process includes a process of having the adopting construction company pay and receive a fee (in this embodiment, a commission) for supporting the construction contract, but it goes without saying that it is not limited to this.

[0082] Next, the operation of the data processing device 12 when executing the third identification process will be described with reference to Fig. 13. Fig. 13 is a flow chart showing an example of the flow of the third identification process executed by the data processing device 12. The third identification process according to this embodiment is started when an administrator of the data processing device 12 issues an instruction to start the execution of the third identification process in order to have the adopted construction company provide the created design documents. Also, here, a case will be described in which the target adopted construction company is specified in advance to avoid confusion.

[0083] In step S50, the processing unit 294 executes a data usage contract process, which is a process of making a contract with the target adopting construction company to provide design document data showing the created design document for a fee by paying a fee. At this time, the processing unit 294 may determine the fee for the design document data depending on the type, amount, accuracy, etc. of the design document data to be provided, or may apply a flat fee.

[0084] In step S52, the input unit 292 acquires design document data by receiving it from the target adopting construction company, and in step S54, the processing unit 294 registers the received design document data by storing it in the storage 32.

[0085] In step S56, the processing unit 294 judges whether the number of design document data (hereinafter, referred to as "unlearned design document data") registered in the storage 32 and not used for learning the second data generation model 58B is equal to or greater than a predetermined number. If the judgment is negative, the third identification process is terminated, whereas if the judgment is positive, the process proceeds to step S58. In this embodiment, the predetermined number is a number preset by the administrator of the data processing device 12 or the like according to the accuracy required for the second data generation model 58B and the registration frequency of the design document data, but is not limited to this form. For example, a fixed number may be applied as the predetermined number.

[0086] In step S58, the processing unit 294 learns the second data generation model 58B using all unlearned design document data and the constraint conditions corresponding to the unlearned design document data, and then ends the third identification process. Note that, as the constraint conditions used in this learning, the constraint conditions in the registered data registered by the process of step S20 of the first identification process are applied.

[0087] An overall flow of the processes executed by the above first to third identification processes will be described below with reference to Fig. 14. Fig. 14 is a schematic diagram showing an overall flow of the processes by the data processing system 10.

[0088] Through the first identification process, the data processing device 12 acquires land condition data including land plan data and the like, and acquires desired condition data through a conversation with the user using the first data generation model 58A. Then, the data processing device 12 according to this embodiment inputs the acquired land condition data and desired condition data into the second data generation model 58B. As a result, the data processing device 12 derives multiple building data including design plan data as data that satisfies the constraint conditions indicated by the land condition data and the desired condition data, and presents the data to the user. In response to this, the user selects the desired building data from the multiple building data presented, and makes the above-mentioned estimate request as necessary.

[0089] When the user requests an estimate, the data processing device 12 executes the second specification process to request an estimate from each of the contracted construction companies. In response, each of the contracted construction companies creates proposal data including design document data and transmits it to the data processing device 12.

[0090] When the proposal data and design document data are acquired from each of the contracted construction companies, the data processing device 12 presents the proposals of each of the multiple contracted construction companies indicated by the acquired proposal data to the user. In response, the user refers to the proposals and selects the contracted construction company corresponding to the desired proposal. In response, the data processing device 12 notifies the contracted construction company selected by the user (the hiring construction company) of the selection result.

[0091] The data processing device 12 then performs processing to assist in the conclusion of a construction contract between the user and the adopting construction company, and collects a fee (compensation) from the adopting construction company.

[0092] Furthermore, the data processing system 10 uses the design document data provided by the adopting construction company as learning data to train the second data generation model 58B, thereby making it possible to effectively use the design document data.

[0093] By carrying out the above first to third specific processing steps, as shown diagrammatically in Figure 15 as an example, it is possible to significantly reduce the amount of labor required compared to carrying out current custom-built buildings, resulting in the realization of more custom-built buildings.

[0094] As described above, the data processing system 10 according to this embodiment includes an input unit 292 that acquires user data, a processing unit 294 that performs a specific process using the data generation model 58 that generates a predetermined inference result according to the user data, and an output unit 296 that outputs the result of the specific process to a predetermined device, the input unit 292 acquires constraint condition data indicating constraint conditions related to custom-built buildings as user data from the device, and the processing unit 294 performs a specific process of deriving building data indicating the building to be custom-built using the output of the data generation model 58 when the constraint condition data is input. Therefore, it is possible to support the realization of custom-built buildings by users.

[0095] Furthermore, in the data processing system 10 according to this embodiment, the input unit 292 acquires at least a part of the constraint condition data through a conversation with the building owner using the data generation model 58. Therefore, the data can be acquired in a more natural state compared to a case where at least a part of the constraint condition data is not acquired through the conversation.

[0096] In addition, in the data processing system 10 according to the present embodiment, two data generation models, a first data generation model 58A for carrying out a conversation and a second data generation model 58B used in a specific process, are applied as the data generation model 58. Therefore, compared to the case where these models are configured by a single data generation model, each function can be performed with higher accuracy.

[0097] In the data processing system 10 according to the present embodiment, the constraint condition data includes land condition data on the land on which the building is to be constructed, and desired condition data on the wishes of the building owner. Therefore, the building data can be derived as one that satisfies the constraint conditions indicated by these data.

[0098] In the data processing system 10 according to the present embodiment, the building data includes design drawing data showing the design drawing of the building, design image data showing the design image of the building, schedule data showing the schedule for constructing the building, and cost estimate data showing the estimate of the cost required for constructing the building. Therefore, these data can be derived as the building data.

[0099] In the data processing system 10 according to the present embodiment, the design image data is data showing a walk-through video of at least one of the exterior and interior of a building. Therefore, the design image data can be made more realistic than when the design image data is data showing the design using still images.

[0100] In addition, in the data processing system 10 according to the present embodiment, a plurality of building data satisfying the constraint conditions are derived as selection candidates, and the selection candidates are output to the device, while a selection instruction from the selection candidates by the user is further acquired. Therefore, compared to the case where only one building data is derived, the satisfaction of the user can be improved.

[0101] In addition, the data processing system 10 according to the present embodiment further executes, as a specific process, a contract support process for supporting the conclusion of a construction contract between a building owner and a construction company that will build the building, using at least one of the constraint conditions and the building data. Therefore, the construction contract can be concluded efficiently.

[0102] In addition, in the data processing system 10 according to the present embodiment, a contract support process is executed by selecting a plurality of predefined construction companies as candidate companies for concluding a construction contract with the client. This can improve the user's satisfaction compared to the case where only a single construction company is selected as the candidate company for concluding a construction contract.

[0103] In addition, the data processing system 10 according to this embodiment further executes, as a specific process, a process of learning the data generation model 58 using design documents created based on building data by a construction company that has concluded a construction contract with a client. Therefore, the design documents created by this system can be effectively used for learning the data generation model 58.

[0104] Furthermore, the data processing system 10 according to this embodiment further executes, as a specific process, a process of paying the corresponding construction company for the provision of the design documents. Therefore, the construction company can also make a profit.

[0105] Furthermore, the data processing system 10 of this embodiment is designed to provide a wide range of support for custom construction as described above. If the application of this system makes it possible to omit at least some of the work currently performed by government authorities to carry out building inspections, it will be possible to reduce the enormous amount of labor (=taxes) required for such building inspections.

[0106] In addition, although the data processing system 10 of this embodiment is primarily intended for application to fully custom-built homes, this is not limited to this, and the data processing system 10 of this embodiment can also be applied to semi-custom-built homes, custom-built homes that reflect customer preferences, condominiums, and the like.

[0107] In the above embodiment, the second identification process is described as being performed before the fee receiving process is performed before the proposal is presented to the user, but the present invention is not limited to this. For example, the fee receiving process may be performed after the proposal is presented to the user.

[0108] In the above embodiment, the case where each contracted construction company creates only one set of proposal data and design document data has been described, but the present invention is not limited to this form. For example, each contracted construction company may create multiple sets of proposal data and design document data that each satisfy the constraint conditions. This form can further improve user satisfaction.

[0109] In the above embodiment, the case where the design drawing data, the design image data, the schedule data, and the cost estimate data are all derived simultaneously by the second data generation model 58B has been described, but the present invention is not limited to this form. For example, in the first step, only the design drawing data is derived by the first data generation model, and in the second step, the derived design document data is input to the second data generation model to derive the remaining design image data, the schedule data, and the cost estimate data.

[0110] In the above embodiment, the design drawing data, design image data, schedule data, and cost estimate data are derived by the second data generation model 58B, but the present invention is not limited to this embodiment. For example, in addition to these data, structural calculation sheet data indicating a structural calculation sheet may be derived by the second data generation model 58B. As a modified example of this embodiment, the structural calculation sheet data may be derived by using 3D CAD (Computer Aided Design) software capable of structural calculation, which is currently widely used.

[0111] In addition, although the system according to the present disclosure has been described mainly with respect to the function of the specific processing unit 290 of the data processing device 12, the system according to the present disclosure is not necessarily implemented in a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program that runs on a personal computer, or an application that runs on a smartphone, etc. The method according to the present disclosure may be provided to a user in the form of SaaS (Software as a Service).

[0112] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers, including computer 22.

[0113] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable computer-readable non-transitory storage medium such as a Universal Serial Bus (USB) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0114] In addition, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 upon request from the data processing device 12.

[0115] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0116] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing the specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0117] The hardware resource that executes the specific process may be one of these various processors, or may be a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0118] As an example of a configuration using one processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a configuration in which a processor is used that realizes the functions of the entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0119] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0120] The above description and illustrations are detailed descriptions of the parts related to the technology of the present disclosure, and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, function, action, and effect is an example of the configuration, function, action, and effect of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above description and illustrations, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above description and illustrations omit explanations of technical common sense that do not require explanation in order to enable the implementation of the technology of the present disclosure.

[0121] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or standard was specifically and individually indicated to be incorporated by reference.

[0122] In relation to the above, the following supplementary notes are further disclosed.

[0123] <Appendix 1> an input unit for acquiring user data; a processing unit that performs a specific process using a data generation model that generates a predetermined inference result according to the user data; an output unit that outputs a result of the specific processing to a predetermined device, The input unit acquires, as the user data, constraint condition data indicating constraint conditions related to custom-built buildings from the device, The processing unit performs, as the identification process, a process of deriving building data indicating a building to be built to order, using an output of the data generation model when the constraint condition data is input. Data processing device. <Appendix 2> The input unit acquires at least a part of the constraint condition data through a conversation with an owner of the building using the data generation model. 2. A data processing device according to claim 1. <Appendix 3> The data generation model includes two data generation models: a first data generation model for conducting the conversation, and a second data generation model used in the specific process. 3. A data processing device according to claim 2. <Appendix 4> The constraint condition data includes at least one of land condition data regarding the land on which the building is to be constructed and desired condition data regarding the desires of an owner of the building. 4. A data processing device according to any one of claims 1 to 3. <Appendix 5> The building data includes at least one of design drawing data showing design drawings of the building, design image data showing a design image of the building, schedule data showing a schedule for constructing the building, and cost estimate data showing an estimate of the cost required for constructing the building. 5. A data processing device according to any one of claims 1 to 4. <Appendix 6> The design image data is data showing a walk-through video of at least one of the exterior and the interior of the building. 6. A data processing device according to claim 5. <Appendix 7> The processing unit derives, as the building data, a plurality of building data satisfying the constraint conditions as selection candidates; The output unit outputs the selection candidates to the device; The input unit further acquires a selection instruction from the selection candidates by a user. 7. A data processing device according to any one of claims 1 to 6. <Appendix 8> The processing unit further executes, as the specific processing, a contract support processing for supporting the conclusion of a construction contract between an owner of the building and a construction company that will build the building, by using at least one of the constraint conditions and the building data. 8. A data processing device according to any one of claims 1 to 7. <Appendix 9> The processing unit executes the contract support process by selecting a predetermined number of the construction companies as candidate companies for concluding the construction contract with the client. 9. A data processing device according to claim 8. <Appendix 10> The processing unit further executes, as the specific processing, a process of learning the data generation model using design documents created based on the building data by the construction company with which the construction contract has been concluded with the client. 10. A data processing device according to claim 8 or 9. <Appendix 11> The processing unit further executes, as the specific process, a process of paying a fee for the provision of the design documents to the corresponding construction company. 11. A data processing device according to claim 10. [Explanation of symbols]

[0124] 10 Data Processing System 12 Data Processing Device 14 Smart Devices 22 Computers 24 Database 26 Communication I / F 28 processors 30 RAM 32 Storage 34 Bus 36 Computer 38 Reception equipment 38A Touch Panel 38B Microphone 40 Output Device 40A Display 40B Speaker 42 Camera 44 Communication I / F 46 processors 46A Control Unit 48 RAM 50 Storage 52 Bus 54 Network 56 Specific Processing Program 58 Data Generation Model 58A First Data Generation Model 58B Second Data Generation Model 59 Emotion Identification Model 60 Reception Output Program 290 Specific Processing Department 292 Input section 294 Processing section 296 Output section 400 Emotion Map 900 Emotion Map

Claims

1. an input unit for acquiring user data; a processing unit that performs a specific process using a data generation model that generates a predetermined inference result according to the user data; an output unit that outputs a result of the specific processing to a predetermined device, The input unit acquires, as the user data, constraint condition data indicating constraint conditions related to custom-built buildings from the device, The processing unit performs, as the identification process, a process of deriving building data indicating a building to be built to order, using an output of the data generation model when the constraint condition data is input. Data processing device.

2. The input unit acquires at least a part of the constraint condition data through a conversation with an owner of the building using the data generation model.

2. A data processing apparatus according to claim 1.

3. The data generation model includes two data generation models: a first data generation model for conducting the conversation; and a second data generation model used in the specific process.

3. A data processing apparatus according to claim 2.

4. The constraint condition data includes at least one of land condition data regarding the land on which the building is to be constructed and desired condition data regarding the desires of an owner of the building. A data processing device according to any one of claims 1 to 3.

5. The building data includes at least one of design drawing data showing design drawings of the building, design image data showing a design image of the building, schedule data showing a schedule for constructing the building, and cost estimate data showing an estimate of the cost required for constructing the building.

2. A data processing apparatus according to claim 1.

6. The design image data is data showing a walk-through video of at least one of the exterior and the interior of the building.

6. A data processing apparatus according to claim 5.

7. The processing unit derives, as the building data, a plurality of building data satisfying the constraint conditions as selection candidates; The output unit outputs the selection candidates to the device; The input unit further acquires a selection instruction from the selection candidates by a user.

2. A data processing apparatus according to claim 1.

8. The processing unit further executes, as the specific processing, a contract support processing for supporting the conclusion of a construction contract between an owner of the building and a construction company that will build the building, by using at least one of the constraint conditions and the building data.

2. A data processing apparatus according to claim 1.

9. The processing unit executes the contract support process by selecting a predetermined number of the construction companies as candidate companies for concluding the construction contract with the client.

9. A data processing apparatus according to claim 8.

10. The processing unit further executes, as the specific processing, a process of learning the data generation model using design documents created based on the building data by the construction company with which the construction contract has been concluded with the client.

10. A data processing device according to claim 8 or claim 9.

11. The processing unit further executes, as the specific process, a process of paying a fee for the provision of the design documents to the corresponding construction company.

11. A data processing apparatus according to claim 10.

12. Get user data, performing a determination process using a data generation model that generates a predetermined inference result according to the user data; A data processing method for outputting a result of the specific processing to a predetermined device, comprising: Obtaining constraint data indicating constraints on custom-built buildings as the user data from the device; The specification process includes a process of deriving building data representing a building to be custom-built using an output of the data generation model when the constraint condition data is input. Data processing methods.

13. Get user data, performing a determination process using a data generation model that generates a predetermined inference result according to the user data; A process of outputting a result of the specific process to a predetermined device, Obtaining constraint data indicating constraints on custom-built buildings as the user data from the device; The specification process includes a process of deriving building data representing a building to be custom-built using an output of the data generation model when the constraint condition data is input. A data processing program that causes a computer to carry out processing.

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