WO2025009185A1 - Architectural drawing creation support system - Google Patents
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- WO2025009185A1 WO2025009185A1 PCT/JP2023/032277 JP2023032277W WO2025009185A1 WO 2025009185 A1 WO2025009185 A1 WO 2025009185A1 JP 2023032277 W JP2023032277 W JP 2023032277W WO 2025009185 A1 WO2025009185 A1 WO 2025009185A1
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Definitions
- the present invention relates to a system that supports the creation of architectural drawings, and in particular to an architectural drawing creation support system that is suitable for adapting editable elements in architectural drawings to the specifications of a finishing table.
- Patent Document 1 includes a table storage unit that extracts legal judgment elements related to numerical values from laws and regulations and stores a legal judgment table composed of the legal judgment elements for each law; an assignment element extraction unit that uses AI to extract assignment elements containing numerical values that can be substituted for the legal judgment elements from the initial layout data; an appropriateness judgment unit that assigns the assignment elements extracted by the assignment element extraction unit to the legal judgment table stored in the table storage unit and judges it to be appropriate if it satisfies the conditions in the legal judgment table and judges it to be inappropriate if it does not; and an judgment result creation unit that records the judgment results made by the appropriateness judgment unit and creates a floor plan judgment document including the judgment results.
- a table storage unit that extracts legal judgment elements related to numerical values from laws and regulations and stores a legal judgment table composed of the legal judgment elements for each law
- an assignment element extraction unit that uses AI to extract assignment elements containing numerical values that can be substituted for the legal judgment elements from the initial layout data
- an appropriateness judgment unit that assigns the assignment elements extracted by the assignment element
- plans and detailed floor plans are created based on the finish table, but the dimensions and other specifications listed on the plans must match those listed on the finish table. Also, the tags listed on the detailed floor plans must match those listed on the finish table. Since the designer performs these tasks while checking the finish table, mistakes are likely to occur.
- Patent Document 1 can determine whether editable elements in architectural drawings comply with architectural laws, it cannot make the editable elements conform to the specifications of a finishing table.
- the present invention was made with a focus on these unresolved issues in the conventional technology, and aims to provide an architectural drawing creation support system that is suitable for adapting editable elements in an architectural drawing to the specifications of a finishing table.
- the architectural drawing creation support system of invention 1 comprises an element information acquisition means for acquiring finishing element information on finishing elements described in a finishing schedule and editing element information on editable editing elements in an architectural drawing, and an estimation means for estimating the matching element information from the finishing element information and editing element information acquired by the element information acquisition means, using a trained model that has been trained based on information on the finishing elements described in the finishing schedule and matching element information on matching elements described in the architectural drawing that match the specifications of the finishing elements.
- the finishing element information can be configured, for example, as information for identifying the finishing element (for example, a name, a number, an ID, a code, link information such as a URL). Also, the finishing element information can be configured, for example, as letters, numbers, figures, codes, symbols, images, sounds, and other information. Also, the finishing element information can be configured as keywords relating to the finishing element (for example, one or more keywords indicating part of the name of the finishing element). The same applies to other element information below.
- the element information acquisition means may, for example, input element information from an input device or the like, acquire or receive element information from an external terminal or the like, read element information from a storage device or storage medium or the like, or generate or calculate element information by information processing or the like. Therefore, acquisition includes at least input, acquisition, reception, reading (including search), generation and calculation. The same concept of acquisition applies below.
- this system may be realized as a single device, terminal, or other equipment, or may be realized as a network system in which multiple devices, terminals, or other equipment are communicatively connected.
- each component may belong to any one of the multiple devices, etc., as long as they are communicatively connected to each other.
- the architectural drawing creation support system of Invention 2 further includes an output means for outputting information about edited elements related to edited element information acquired by the element information acquisition means based on the matching element information estimated by the estimation means in the architectural drawing creation support system of Invention 1.
- the architectural drawing creation support system of invention 3 is an architectural drawing creation support system of either invention 1 or 2, in which the trained model has been trained based on information on the finishing elements described in the finishing table and on matching element information on matching elements and their contents described in the architectural drawing that match the specifications of the finishing elements, and is equipped with a modification means for modifying an edited element related to the edited element information acquired by the element information acquisition means based on the matching element information estimated by the estimation means.
- the architectural drawing creation support system of Invention 4 further includes an element information acquisition means for acquiring changed element information relating to an edit element that has been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the related element information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information relating to the editable edit elements in the architectural drawing and related element information relating to other edit elements that should be changed or have been changed in conjunction with the change to the edit element.
- the architectural drawing creation support system of invention 5 further includes an output means for outputting information about other edit elements related to the related element information based on the related element information estimated by the estimation means in the architectural drawing creation support system of invention 4.
- the architectural drawing creation support system of invention 6 is the architectural drawing creation support system of either invention 4 or 5, in which the trained model has been trained based on information on editable editing elements in architectural drawings, and related element information on other editing elements that should be changed or have been changed in conjunction with a change to the edit element and their contents, and is equipped with a modification means for modifying other editing elements related to the related element information based on the related element information estimated by the estimation means.
- the architectural drawing creation support system of invention 7 further comprises an element information acquisition means for acquiring changed element information on edit elements that have been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the judgment necessity information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information on the editable edit elements in the architectural drawing and judgment necessity information on whether a human judgment is required to change other edit elements that should be changed or have been changed due to the change in the edit element.
- the architectural drawing creation support system of invention 8 further includes an output means for outputting information on whether or not a change to another editing element related to the judgment necessity information is required, based on the judgment necessity information estimated by the estimation means, in the architectural drawing creation support system of invention 7.
- the architectural drawing creation support system of invention 9 further comprises an element information acquisition means for acquiring changed element information relating to an edit element that has been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the related element information and the judgment necessity information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information on the editable edit elements in the architectural drawing, related element information relating to other edit elements that should be changed or have been changed due to the change in the edit element and their contents, and judgment necessity information relating to whether or not a human judgment is required to change the other edit elements.
- the architectural drawing creation support system of invention 10 is the architectural drawing creation support system of invention 9, and when it is determined that a human judgment is required to change another edit element related to the related element information based on the judgment necessity information estimated by the estimation means, the system includes an output means for outputting information about the other edit element based on the related element information estimated by the estimation means.
- the architectural drawing creation support system of invention 11 is the architectural drawing creation support system of either invention 9 or 10, and when it is determined that no human judgment is required to change other edit elements related to the related element information based on the judgment necessity information estimated by the estimation means, the architectural drawing creation support system of invention 11 is provided with a modification means for modifying the other edit elements based on the related element information estimated by the estimation means.
- the architectural drawing creation support system of Invention 1 estimates compatible element information regarding compatible elements that correspond to the finishing elements listed in the finishing table, so it is expected that the edited elements will be adapted to the specifications of the finishing table.
- judgment necessity information is estimated as to whether or not a human judgment is required to change other edit elements related to the edit element that has been changed, so it is possible to know whether or not a human should change the other edit elements that need to be changed.
- FIG. 1 is a diagram illustrating a hardware configuration of a drawing creation support device 100.
- FIG. 13 is a diagram showing the structure of finishing list data.
- FIG. 1 is a diagram showing the structure of CAD data of a plan view.
- FIG. 13 is a diagram showing the structure of CAD data of a detailed plan view.
- Wall type diagram. 13 is a flowchart showing a trained model generation process.
- FIG. 1 is a block diagram showing the process of generating and using a trained model. 13 is a flowchart showing a matching element estimation process. This is a plan view before changing the editing element.
- FIG. 11 is a plan view after changing the editing element.
- FIG. 13 is a plan view detail before changing the editing element.
- FIG. 13 is a plan view detail after changing the editing element.
- FIG. 13 is a plan view detail after changing the editing element.
- FIG. 1 is a block diagram showing the process of generating and using a trained model. 13 is a flowchart showing a related element estimation process.
- FIG. 1 is a block diagram showing the process of generating and using a trained model. 13 is a flowchart showing a related element estimation process.
- FIG. 1 is a diagram showing a hardware configuration of a drawing creation support device 100. As shown in FIG. 1
- the drawing creation support device 100 is composed of a CPU (Central Processing Unit) 30 that controls calculations and the entire system based on a control program, a ROM (Read Only Memory) 32 in which the control program etc. of the CPU 30 is stored in advance in a specified area, a RAM (Random Access Memory) 34 for storing data read from the ROM 32 etc. and calculation results required in the calculation process of the CPU 30, and an I/F (InterFace) 38 that mediates the input and output of data to external devices.
- a bus 39 which is a signal line for transferring data.
- an input device 40 consisting of a keyboard, mouse, etc. that can input data as a human interface
- a storage device 42 that stores data, tables, etc. as files
- a display device 44 that displays a screen based on an image signal.
- the storage device 42 has installed therein CAD (Computer Aided Design) software and BIM (Building Information Modeling) software (hereinafter collectively referred to as "CAD software").
- CAD software is software that assists in the creation of drawings in response to user operations.
- the CPU 30 starts a CAD program stored in a specified area of the ROM 32 and executes processing according to the program.
- a designer can start the CAD software to create plan drawings, detailed floor plans, and other architectural drawings.
- FIG. 2 is a diagram showing the structure of finishing list data.
- the storage device 42 stores finishing table data relating to finishing tables.
- the finishing table is a table that summarizes the finishes of each part of a building. There is an exterior finishing table that shows the finishes of the roof and exterior walls, and an interior finishing table that shows the finishes of the walls, floors, ceilings, etc. of each room.
- the finishing table data one row is registered for each finishing element.
- the finishing element "internal corridor", "tile carpet (A), border” is registered as the floor finish
- "vinyl cloth (A)” is registered as the wall finish
- “vinyl cloth (A)” is registered as the ceiling finish.
- FIG. 3 is a diagram showing the structure of CAD data of a plan view.
- the storage device 42 stores CAD data and BIM data of plan views (hereinafter collectively referred to as "CAD data").
- a rectangular plan is a detailed drawing of the cross section of a building.
- CAD data for a rectangular plan is created by a designer using CAD software.
- a designer creates a rectangular plan in the CAD software by adding, editing, or deleting editable elements in the rectangular plan.
- the edit elements of the floor, wall, and ceiling of the area labeled "internal corridor" are arranged, as are the edit elements of the floor, wall, and ceiling of the area labeled "windbreak room.” These correspond to the finishing elements in the third and ninth rows of the finishing table data in Figure 2.
- Corresponding finishing elements and editing elements may be associated by setting the same ID within the finishing table data and the CAD data.
- FIG. 4 is a diagram showing the structure of CAD data of a detailed plan view.
- FIG. 5 is a diagram showing wall types.
- the storage device 42 stores CAD data of detailed plan views, as shown in FIG.
- a detailed plan drawing is a drawing that draws the plan of a building in detail.
- CAD data of the detailed plan drawing is created by a designer using CAD software.
- the designer creates the detailed plan drawing by adding, editing, or deleting editable editing elements in the detailed plan drawing in the CAD software.
- a tag is placed for the editing element of the wall so that the wall type can be identified.
- the tag is a three- or four-digit alphanumeric character surrounded by a square or ellipse, and the designer sets the value by referring to the wall type diagram in FIG. 5.
- FIG. 5 In the example of FIG.
- the tag "L4DA” is placed in the area displayed as "LD”
- the tag "L4JA” is placed in the area displayed as "Bathroom/Dressing Room”.
- the storage device 42 stores CAD data of other architectural drawings, and data of trained models.
- the trained models are trained based on information about the finishing elements listed in the finishing schedule and information about compatible elements listed in the architectural drawings that fit the specifications of those finishing elements.
- the finishing schedule data and CAD data for plan drawings, detailed floor plans, and other architectural drawings are used for AI training, so the storage device 42 stores a large amount of data that was created in the past.
- This CAD data is in which each editing element in the architectural drawings fits the specifications of the finishing schedule data, and serves as training data for the AI training.
- FIG. 6 is a flowchart showing the trained model generation process.
- FIG. 7 is a block diagram showing the process of generating and using a trained model.
- the trained model generation process is a process executed to generate a trained model, and when executed by the CPU 30, the process proceeds to step S100 to execute a finishing table data analysis process, as shown in Fig. 6.
- the finishing table data analysis process the finishing table data is read from the storage device 42, and information on the finishing elements is extracted from the read finishing table data.
- step S102 a CAD data analysis process is executed.
- CAD data analysis process CAD data of the plan, detailed floor plan, and other architectural drawings is read from the storage device 42, and information regarding the editing elements is extracted from the read CAD data.
- step S104 a training dataset is generated based on the information extracted in steps S100 and S102, and the process proceeds to step S106, where the generated training dataset is input to a training program and a trained model is generated by the training program.
- the training program includes pre-learning parameters and hyperparameters, and performs training based on the input training dataset and hyperparameters to update the pre-learning parameters.
- the trained model is then output as the training result.
- the trained model includes trained parameters in which pre-trained parameters have been updated by training, and an inference program.
- the inference program inputs finishing table data and edit elements, and based on the trained parameters, estimates the finishing elements of the finishing table data and the matching elements corresponding to the edit elements (edit elements that match the specifications of the finishing elements) from the input finishing table data and edit elements, and outputs the estimated matching elements.
- the input to the inference program is not limited to the finishing table data itself, and may be made by extracting finishing elements of the finishing table data that correspond to the input edit elements, as long as the correspondence can be specified by ID or the like.
- the relationship between the input edit elements and the matching elements is determined by AI training, and therefore, although it shows a similar tendency to the contents of past finishing table data and CAD data, there is ambiguity in that they do not necessarily match exactly. However, this ambiguity can be reduced by the amount of training data and the training accuracy.
- FIG. 8 is a flowchart showing the matching element estimation process.
- the matching element estimation process is executed in response to a request from a user, and when executed by the CPU 30, the process first proceeds to step S150 as shown in Fig. 8.
- step S150 the CAD software determines whether or not any of the editable elements in the architectural drawing has been designated by a user operation, and if it is determined that an edit element has been designated (YES), the process proceeds to step S152.
- step S152 the finishing table data corresponding to the CAD data currently being edited is read from the memory device 42, the edit elements specified in step S150 are obtained, and the process proceeds to step S154, where the trained model in the memory device 42 is used to estimate matching elements from the read finishing table data and the obtained edit elements.
- the estimation is performed by inputting the finishing table data and edit elements into the trained model and obtaining the matching elements output from the trained model.
- step S156 it is determined whether the edited element specified in step S150 and the matching element estimated in step S154 are inconsistent in terms of identification or content. If it is determined that they are inconsistent (YES), the process proceeds to step S158, where a message is displayed on the display device 44 indicating that there is a defect in the edited element, and the process ends.
- step S156 if it is determined in step S156 that the edit element and the matching element do not mismatch (NO), or if it is determined in step S150 that an edit element is not specified (NO), the process ends.
- FIG. 9 is a plan view before the editing elements are changed.
- FIG. 10 is a plan view after the editing element has been changed.
- edit element 400 for the floor of the area marked "internal corridor" in the plan of FIG. 9.
- edit element 400 is set as "vinyl floor tile (C),” whereas the corresponding specification element (third line) in the finishing schedule data of FIG. 2 is "tile carpet (A), bordered.” Therefore, when the finishing schedule data of FIG. 2 and edit element 400 are input into the trained model, the matching element "tile carpet (A), bordered” is estimated, and a message 402 is displayed indicating that there is a defect in edit element 400. Following the message 402, the designer changes edit element 400 to "tile carpet (A), bordered," as shown in FIG. 10.
- edit element 404 for the wall of the area marked "internal corridor" in the plan of FIG. 9.
- edit element 404 is set to "vinyl cross (B)," whereas the corresponding specification element (third line) in the finishing schedule data of FIG. 2 is “vinyl cross (A).” Therefore, when the finishing schedule data of FIG. 2 and edit element 404 are input into the trained model, the matching element "vinyl cross (A)" is estimated, and a message 406 is displayed indicating that there is a defect in edit element 404. The designer follows the message 406 and changes edit element 404 to "vinyl cross (A)," as shown in FIG. 10.
- edit element 408 for the ceiling of the area marked "internal corridor" in the plan of FIG. 9.
- edit element 408 is set as “vinyl cloth (B),” whereas the corresponding specification element (third line) in the finishing schedule data of FIG. 2 is “vinyl cloth (A).” Therefore, when the finishing schedule data of FIG. 2 and edit element 408 are input into the trained model, the matching element "vinyl cloth (A)” is estimated, and a message 406 is displayed indicating that there is a defect in edit element 408. The designer follows the message 406 and changes edit element 408 to "vinyl cloth (A)," as shown in FIG. 10.
- the designer specifies the ceiling height (edit element) 410 of the ceiling in the area marked "Windbreak" in the plan of Figure 9. Since the ceiling height 410 also does not conform to the specifications of the finishing schedule data in Figure 2, a message 412 is displayed indicating that there is a defect in the ceiling height 410. Following the message 412, the designer changes the ceiling height 410 to 2450 [mm], as shown in Figure 10.
- the designer specifies the effective dimension 414 of the area marked "shared corridor" in the plan of FIG. 9 in the CAD software. Since the effective dimension 414 does not comply with building-related laws and regulations, a message 416 is displayed indicating that the effective dimension 414 is incomplete. Whether or not it complies with building-related laws and regulations can be determined, for example, by the technology of Patent Document 1.
- the effective dimension 414 can be changed by adjusting the position of the right wall or the left wall, but since it is difficult for AI to determine which should be prioritized, such editing elements 414 are editing elements that require human judgment to change, and are not changed automatically by AI, but are left to the designer's judgment and the designer changes the position of the right or left wall.
- FIG. 11 is a detailed plan view before the editing element is changed.
- FIG. 12 is a plan view detail after the editing element has been changed.
- the designer specifies the tag (edit element) 420 of the area displayed as "Bathroom/Dressing Room” in the detailed floor plan of FIG. 11.
- the tag 420 is set as “L4JB”
- the designer specifies the wall tag 424 of the area displayed as "LD” in the detailed plan view of FIG. 11.
- the tag 424 is set as "L4LA”
- the corresponding specification element (line 13) in the finishing table data of FIG. 2 is "L4"
- "GBt12.5 * Surface base is waterproof GB”
- finishing schedule data and edited elements are acquired, and a trained model is used to estimate suitable elements from the acquired finishing schedule data and edited elements, which has been trained based on information about the finishing elements listed in the finishing schedule and information about suitable elements listed in the architectural drawings that match the specifications of the finishing elements. If there is a mismatch between the acquired edited elements and the estimated suitable elements, a message is displayed indicating that there is a defect in the edited elements.
- step S152 corresponds to the element information acquisition means of the first or second invention
- step S154 corresponds to the estimation means of the first or second invention
- step S158 corresponds to the output means of the second invention.
- This embodiment differs from the first embodiment in that it displays other edit elements that should be changed when an edit element is changed.
- other edit elements may no longer conform to the specifications of the finishing table.
- the ceiling height 410 in FIG. 9 is changed, it becomes necessary to change the height of the space above the ceiling, etc.
- the other edit elements that should be changed when an edit element is changed are displayed, thereby aiming to support the designer in making changes to the other edit elements that should be changed as well.
- the memory device 42 stores CAD data for plan views, detailed floor plans, and other architectural drawings, including CAD data before an editing element is changed (hereinafter referred to as "CAD data before change”) and CAD data after an editing element is changed (hereinafter referred to as "CAD data after change").
- CAD data before change CAD data before an editing element is changed
- CAD data after change CAD data after an editing element is changed
- the storage device 42 stores data of the trained model.
- the trained model is trained based on information about editable elements in architectural drawings and information about other editable elements that have been changed as a result of changing those editable elements.
- the pre-change CAD data and post-change CAD data are used for training the AI, so the storage device 42 stores a large amount of data that has been created in the past.
- FIG. 13 is a block diagram showing the process of generating and using a trained model.
- the trained model generation process is a process executed to generate a trained model, and when executed by the CPU 30, the pre-change CAD data and the post-change CAD data are read from the storage device 42, and information regarding the edited elements is extracted from the read CAD data.
- a learning dataset is generated based on the extracted information, the generated learning dataset is input to a learning program, and a trained model is generated by the learning program.
- the inference program of the trained model inputs an edit element that has been changed among the editable edit elements in the architectural drawing, estimates from the input edit element other edit elements that should be changed in conjunction with the change to that edit element based on the trained parameters, and outputs the estimated edit elements as related elements.
- FIG. 14 is a flowchart showing the related element estimation process.
- the related element estimation process is executed in response to a request from a user, and when executed by the CPU 30, the process first proceeds to step S200 as shown in Fig. 14.
- step S200 it is determined whether or not any of the editable elements in the architectural drawing has been changed in the CAD software, and if it is determined that the edit element has been changed (YES), the process proceeds to step S202.
- step S202 the changed edited element is acquired, and the process proceeds to step S204, where the related element is estimated from the acquired edited element using the trained model in the storage device 42.
- the estimation is performed by inputting the edited element into the trained model and acquiring the related element output from the trained model.
- step S206 where other editing elements to be changed are displayed in a specific manner (e.g., highlighted) based on the estimated related elements, and the process ends.
- step S200 determines whether the edit element has not been changed (NO). If it is determined in step S200 that the edit element has not been changed (NO), the process ends.
- the edited element that has been changed is obtained, and related elements are estimated from the obtained edited element using a trained model that has been trained based on information about editable edited elements in an architectural drawing and information about other edited elements that have been changed as a result of the change to that edited element, and the other edited elements that should be changed are displayed in a specific manner based on the estimated related elements.
- step S202 corresponds to the element information acquisition means of invention 4
- step S204 corresponds to the estimation means of invention 4 or 5
- step S206 corresponds to the output means of invention 5.
- This embodiment differs from the second embodiment in that it estimates editing elements that require human judgment to change.
- an editing element is changed, it is desirable to automatically change other editing elements in conjunction with the change, but editing elements that require human judgment to change must be excluded from the targets of automatic change.
- the designer decides whether to change the right or left wall position.
- other editing elements that should be changed in conjunction with a change in an editing element are automatically changed, and editing elements that require human judgment to change are excluded from the targets of automatic change, with the aim of supporting the user in understanding whether or not other editing elements and their contents should be changed by a human.
- the storage device 42 stores judgment necessity data in which edit elements are registered in association with information on whether a change requires human judgment. Edit elements that require human judgment for change may be set by human judgment. Also, edit elements that have two or more change patterns before and after the change may be extracted based on the pre-change CAD data and the post-change CAD data, and the extracted edit elements may be set as edit elements that require human judgment for change.
- the storage device 42 stores data of the trained model.
- the trained model is trained based on information about editable editing elements in architectural drawings, information about other editing elements and their contents that have been changed as a result of changing the editing elements, and judgment necessity information about whether or not a human judgment is required to change the other editing elements.
- the pre-change CAD data, post-change CAD data, and judgment necessity data are used for training the AI, so the storage device 42 stores a large amount of data created in the past.
- FIG. 15 is a block diagram showing the process of generating and using a trained model.
- the trained model generation process is a process executed to generate a trained model, and when executed by the CPU 30, the pre-change CAD data, post-change CAD data, and judgment necessity data are read from the storage device 42, and information regarding the edit elements and judgment necessity information are extracted from the read CAD data and judgment necessity data.
- a learning dataset is generated based on the extracted information
- the generated learning dataset is input to a learning program
- a trained model is generated by the learning program.
- the inference program of the trained model inputs an edit element that has been changed among the editable edit elements in the architectural drawing, and estimates from the input edit element, based on the trained parameters, other edit elements that should be changed in conjunction with the change to that edit element and information on whether or not a decision is required, and outputs the estimated edit elements as related elements.
- FIG. 16 is a flowchart showing the related element estimation process.
- the related element estimation process is executed in response to a request from a user, and when executed by the CPU 30, the process first proceeds to step S250 as shown in Fig. 16.
- step S250 it is determined whether or not any of the editable elements in the architectural drawing has been changed in the CAD software, and if it is determined that the edit element has been changed (YES), the process proceeds to step S252.
- step S252 the changed edited element is acquired, and the process proceeds to step S254, where the related elements and the decision necessity information are estimated from the acquired edited element using the trained model in the storage device 42.
- the estimation is performed by inputting the edited element into the trained model, and acquiring the related elements and the decision necessity information output from the trained model.
- step S256 it is determined based on the estimated judgment necessity information whether or not human judgment is required to change the estimated related elements. If it is determined that human judgment is not required to change the related elements (NO), the process proceeds to step S258, where the other edited elements to be changed are changed based on the estimated related elements so that their contents become the contents of the related elements, and the process ends.
- step S256 determines whether changing the related elements requires human judgment (YES)
- step S260 determines whether changing the related elements requires human judgment.
- step S250 determines whether the edit element has been changed (NO). If it is determined in step S250 that the edit element has not been changed (NO), the process ends.
- an edit element that has been changed among editable edit elements in an architectural drawing is obtained, and related elements and judgment necessity information are estimated from the obtained edit element using a trained model that has been trained based on information about the editable edit element in the architectural drawing, information about other edit elements and their contents that have been changed as a result of the change to that edit element, and judgment necessity information regarding whether human judgment is required to change the other edit elements. If it is determined based on the estimated judgment necessity information that human judgment is required to change the related element, the other edit elements are displayed in a specific manner based on the estimated related elements, and if it is determined that human judgment is not required to change the related elements, the other edit elements are changed based on the estimated related elements.
- step S252 corresponds to the element information acquisition means of invention 7 or 9
- step S254 corresponds to the estimation means of inventions 7 to 11
- step S258 corresponds to the change means of invention 11
- step S260 corresponds to the output means of invention 8 or 10.
- defects were displayed for edit elements specified by user operation, but this is not limited to this. It is also possible to adopt a configuration in which all edit elements in the drawing are scanned and defects are displayed all at once for edit elements that have defects.
- a message is displayed indicating that there is a defect in the edited element, but this is not limiting, and a configuration can also be adopted in which the indicated edited element is changed based on the estimated matching element.
- the trained model used is one that has been trained based on information about the finishing element listed in the finishing table, as well as information about matching elements and their contents that are listed in the architectural drawing and that match the specifications of the finishing element.
- the other edit elements to be changed are displayed in a specific manner based on the estimated related elements, but this is not limiting, and a configuration in which the other edit elements to be changed are changed based on the estimated related elements can also be adopted.
- the trained model used is one that has been trained using a trained model that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements and their contents that have been changed as a result of the change in the edit element.
- the trained model can be one that has been trained based on information about editable edit elements in architectural drawings, information about other edit elements that have been changed as a result of the change to that edit element, and judgment necessity information regarding whether or not human judgment is required to change the other edit elements.
- the trained model can be one that has been trained based on information about editable edit elements in architectural drawings and judgment necessity information regarding whether or not human judgment is required to change the other edit elements that have been changed as a result of the change to that edit element).
- a trained model is used that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements that have been changed as a result of changes to those edit elements.
- this is not limiting, and a trained model that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements that should be changed as a result of changes to those edit elements can also be used.
- correspondence information such as changing edit element B when edit element A is changed, can be used to train the AI.
- a trained model is generated and the trained model is used, but this is not limiting, and a configuration that utilizes a large language model can also be adopted. Specifically, for example, the following configuration can be adopted.
- the drawing creation support device 100 is connected to a large-scale language model server having a large-scale language model via a network.
- the large-scale language model server is configured with the same hardware configuration as the drawing creation support device 100.
- the large-scale language model is a deep learning model that pre-learns from a huge amount of data what is called a language model that models human spoken words based on their occurrence probability.
- the large-scale language model server receives a request, it uses the large-scale language model to statistically estimate the generation probability of the next word from the sentence included in the received request, and transmits the estimation result to the request source.
- the following inventions A1 to A3 or B1 to B8 can be applied to the drawing creation support device 100.
- the language model further includes an element information acquiring means for acquiring matching element information output from the large-scale language model in response to the request.
- invention A2 In Invention A1, The system further comprises an output means for outputting information on an edited element related to the edited element information based on the adapted element information acquired by the element information acquisition means.
- the drawing creation support device 100 sends a request to the large-scale language model server.
- the request includes the finishing schedule data and edit element 400 of FIG. 2, and also includes a request to generate a matching element for the edit element 400.
- the large-scale language model server outputs matching element information.
- a message 402 is displayed indicating that there is a defect in the edit element 400 based on the received matching element information.
- the request includes finish element information on a finish element described in a finish schedule and edit element information on an editable edit element in an architectural drawing, and includes a request to generate conforming element information on a conforming element and its contents that conforms to the specifications of the finish element and is described in the architectural drawing;
- the system further includes a change means for changing an edit element related to the edit element information based on the suitable element information acquired by the element information acquisition means.
- the drawing creation support device 100 sends a request to the large-scale language model server.
- the request includes the finishing schedule data and edit element 400 of FIG. 2, and also includes a request to generate a matching element for the edit element 400.
- the large-scale language model server outputs matching element information.
- the drawing creation support device 100 receives the matching element information, it changes the edit element 400 based on the received matching element information.
- the method further comprises: acquiring element information about the related elements output from the large-scale language model in response to the request.
- the device further comprises an output means for outputting information on other edit elements related to the related element information based on the related element information acquired by the element information acquisition means.
- the drawing creation support device 100 sends a request to the large-scale language model server.
- the request includes the edit element 400, and also includes a request to generate related elements of the edit element 400.
- the large-scale language model server outputs related element information.
- the drawing creation support device 100 receives the related element information, other edit elements that should be changed in conjunction with the change to the edit element 400 are displayed in a specific manner based on the received related element information.
- the request includes changed element information on an edit element that has been changed among editable edit elements in the architectural drawing, and includes a request to generate other edit elements that should be changed in conjunction with the change in the edit element and related element information on the contents of the other edit elements;
- the editing device further includes a change means for changing, based on the related element information acquired by the element information acquisition means, another edit element related to the related element information.
- the drawing creation support device 100 sends a request to the large-scale language model server.
- the request includes the edit element 400, and also includes a request to generate related elements of the edit element 400.
- the large-scale language model server outputs related element information.
- the drawing creation support device 100 receives the related element information, it changes other edit elements that should be changed in conjunction with the change to the edit element 400 based on the received related element information.
- a request input means for inputting a request including changed element information on an edited element among editable edit elements in an architectural drawing that has been changed, and a request for generating judgment necessity information on whether a human judgment is required for changing other edit elements that should be changed in conjunction with the change of the edited element, into a large-scale language model;
- the system further comprises a judgment necessity information acquisition means for acquiring judgment necessity information output from the large-scale language model in response to the request.
- the apparatus further comprises an output means for outputting information on whether or not a human judgment is required for changing another editing element related to the judgment necessity information, based on the judgment necessity information acquired by the judgment necessity information acquisition means.
- a request input means for inputting a request including changed element information on an edited element that has been changed among editable edit elements in an architectural drawing, and also including a request for generating other edit elements that should be changed in conjunction with the change in the edited element and related element information on the contents of the other edit elements, and judgment necessity information on whether or not human judgment is required to change the other edit elements, into the large-scale language model;
- the method further comprises an element information acquiring means for acquiring related element information and judgment necessity information outputted from the large-scale language model in response to the request.
- Invention B7 Invention B6, If it is determined based on the judgment necessity information acquired by the element information acquisition means that human judgment is required to change other editing elements related to the related element information, the device is provided with an output means for outputting information regarding the other editing elements based on the related element information acquired by the element information acquisition means.
- Invention B8 Invention B6 or B7, If it is determined based on the judgment necessity information acquired by the element information acquisition means that no human judgment is required to change other editing elements related to the related element information, a modification means is provided for changing the other editing elements based on the related element information acquired by the element information acquisition means.
- step S254 is replaced with a process of acquiring related element information and judgment necessity information from a large-scale language model server.
- the drawing creation support device 100 sends a request to the large-scale language model server.
- the request includes the edit element 400, and also includes a request to generate related elements of the edit element 400 and judgment necessity information regarding whether human judgment is required to change the related elements.
- the large-scale language model server outputs the related element information and the judgment necessity information.
- the drawing creation support device 100 receives the related element information and the judgment necessity information, it determines whether human judgment is required to change the related elements based on the received related element information. As a result, if it is determined that human judgment is required, the related elements are displayed in a specific manner based on the received related element information. On the other hand, if it is determined that human judgment is not required, the related elements are changed based on the received related element information.
- the device is realized as a single device, but the present invention is not limited to this and can also be realized as a network system.
- a network system some or all of the functions of the drawing creation support device 100 can be configured as a virtual server on a server that provides cloud computing services.
- the drawing creation support device 100 is configured to use the storage device 42, but this is not limiting, and it can also be configured to use an external storage device such as a database server.
- storage media refers to semiconductor storage media such as RAM and ROM, magnetic storage media such as FD and HD, optically readable storage media such as CD, CDV, LD and DVD, and magnetic storage/optically readable storage media such as MO, and includes any storage media that can be read by a computer, regardless of the reading method (electronic, magnetic, optical, etc.).
- first to third embodiments and the modifications thereof can be applied to each other.
- present invention is not limited to the above-described first to third embodiments and their modifications, but can also be applied to other cases without departing from the spirit of the present invention.
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Abstract
Description
本発明は、建築図面の作成を支援するシステムに係り、特に、建築図面中の編集可能な編集要素を仕上表の仕様に適合させるのに好適な建築図面作成支援システムに関する。 The present invention relates to a system that supports the creation of architectural drawings, and in particular to an architectural drawing creation support system that is suitable for adapting editable elements in architectural drawings to the specifications of a finishing table.
従来、AI(Artificial Intelligence)を用いて建築図面の作成を支援する技術としては、例えば、特許文献1記載の技術が知られている。
Conventionally, one known technology that uses AI (Artificial Intelligence) to assist in the creation of architectural drawings is the technology described in
特許文献1記載の技術は、法令から数値に関連する法令判定要素を抽出し法令判定要素から構成される法令判定テーブルを、法令ごとに記憶するテーブル記憶部と、法令判定要素に代入可能な数値を含む代入要素を、初期間取データからAIを用いて抽出する代入要素抽出部と、代入要素抽出部が抽出した代入要素を、テーブル記憶部に記憶された法令判定テーブルに代入し、法令判定テーブルの条件を満足している場合に適正と判定し、満足していない場合に不適正と判定する適正判定部と、適正判定部による判定結果を記録し、判定結果を含む間取判定書を作成する判定結果作成部とを備える。
The technology described in
ところで、建物の設計では、仕上表をもとに矩計図や平面詳細図を作成するが、矩計図に記載される寸法その他の仕様は、仕上表に記載のものと適合させなければならない。また、平面詳細図に記載されるタグは、仕上表に記載のものと適合させなければならない。これらの作業は設計者が仕上表を確認しながら行うため、ミスが生じやすい。 When designing a building, plans and detailed floor plans are created based on the finish table, but the dimensions and other specifications listed on the plans must match those listed on the finish table. Also, the tags listed on the detailed floor plans must match those listed on the finish table. Since the designer performs these tasks while checking the finish table, mistakes are likely to occur.
しかしながら、特許文献1記載の技術にあっては、建築図面中の編集可能な編集要素が建築関連の法令に適合している否かを判定することはできるが、編集要素を仕上表の仕様に適合させることはできない。
However, while the technology described in
そこで、本発明は、このような従来の技術の有する未解決の課題に着目してなされたものであって、建築図面中の編集可能な編集要素を仕上表の仕様に適合させるのに好適な建築図面作成支援システムを提供することを目的としている。 The present invention was made with a focus on these unresolved issues in the conventional technology, and aims to provide an architectural drawing creation support system that is suitable for adapting editable elements in an architectural drawing to the specifications of a finishing table.
〔発明1〕 上記目的を達成するために、発明1の建築図面作成支援システムは、仕上表に記載される仕上要素に関する仕上要素情報及び建築図面中の編集可能な編集要素に関する編集要素情報を取得する要素情報取得手段と、仕上表に記載された仕上要素に関する情報及び当該仕上要素の仕様に適合し建築図面に記載された適合要素に関する適合要素情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した仕上要素情報及び編集要素情報から前記適合要素情報を推定する推定手段とを備える。
[Invention 1] In order to achieve the above object, the architectural drawing creation support system of
ここで、仕上要素情報は、例えば、仕上要素を識別するための情報(例えば、名称、番号、ID、コード、URL等のリンク情報)として構成することができる。また、仕上要素情報は、例えば、文字、数字、図形、符合、記号、画像、音声その他の情報として構成することができる。また、仕上要素情報は、仕上要素に関するキーワード(例えば、仕上要素の名称の一部を示す1又は複数のキーワード)として構成することができる。以下、その他の要素情報についても同じである。 Here, the finishing element information can be configured, for example, as information for identifying the finishing element (for example, a name, a number, an ID, a code, link information such as a URL). Also, the finishing element information can be configured, for example, as letters, numbers, figures, codes, symbols, images, sounds, and other information. Also, the finishing element information can be configured as keywords relating to the finishing element (for example, one or more keywords indicating part of the name of the finishing element). The same applies to other element information below.
また、要素情報取得手段は、例えば、入力装置等から要素情報を入力してもよいし、外部の端末等から要素情報を獲得又は受信してもよいし、記憶装置や記憶媒体等から要素情報を読み出してもよいし、情報処理等により要素情報を生成し又は算出してもよい。したがって、取得には、少なくとも入力、獲得、受信、読出(検索を含む。)、生成及び算出が含まれる。以下、取得の概念については同じである。 The element information acquisition means may, for example, input element information from an input device or the like, acquire or receive element information from an external terminal or the like, read element information from a storage device or storage medium or the like, or generate or calculate element information by information processing or the like. Therefore, acquisition includes at least input, acquisition, reception, reading (including search), generation and calculation. The same concept of acquisition applies below.
また、本システムは、単一の装置、端末その他の機器として実現するようにしてもよいし、複数の装置、端末その他の機器を通信可能に接続したネットワークシステムとして実現するようにしてもよい。後者の場合、各構成要素は、それぞれ通信可能に接続されていれば、複数の機器等のうちいずれに属していてもよい。以下、発明4、7及び9の建築図面作成支援システムにおいて同じである。 Furthermore, this system may be realized as a single device, terminal, or other equipment, or may be realized as a network system in which multiple devices, terminals, or other equipment are communicatively connected. In the latter case, each component may belong to any one of the multiple devices, etc., as long as they are communicatively connected to each other. The same applies below to the architectural drawing creation support systems of inventions 4, 7, and 9.
〔発明2〕 さらに、発明2の建築図面作成支援システムは、発明1の建築図面作成支援システムにおいて、前記推定手段で推定した適合要素情報に基づいて、前記要素情報取得手段で取得した編集要素情報に係る編集要素に関する情報を出力する出力手段とを備える。
[Invention 2] The architectural drawing creation support system of
〔発明3〕 さらに、発明3の建築図面作成支援システムは、発明1及び2のいずれか1の建築図面作成支援システムにおいて、前記学習済みモデルは、仕上表に記載された仕上要素に関する情報並びに当該仕上要素の仕様に適合し建築図面に記載された適合要素及びその内容に関する適合要素情報に基づいて学習を行ったものであり、前記推定手段で推定した適合要素情報に基づいて、前記要素情報取得手段で取得した編集要素情報に係る編集要素を変更する変更手段を備える。
[Invention 3] Furthermore, the architectural drawing creation support system of invention 3 is an architectural drawing creation support system of either
〔発明4〕 さらに、発明4の建築図面作成支援システムは、建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を取得する要素情報取得手段と、建築図面中の編集可能な編集要素に関する情報及び当該編集要素の変更に伴い変更すべき又は変更された他の編集要素に関する関連要素情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記関連要素情報を推定する推定手段とを備える。 [Invention 4] The architectural drawing creation support system of Invention 4 further includes an element information acquisition means for acquiring changed element information relating to an edit element that has been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the related element information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information relating to the editable edit elements in the architectural drawing and related element information relating to other edit elements that should be changed or have been changed in conjunction with the change to the edit element.
〔発明5〕 さらに、発明5の建築図面作成支援システムは、発明4の建築図面作成支援システムにおいて、前記推定手段で推定した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素に関する情報を出力する出力手段を備える。
[Invention 5] The architectural drawing creation support system of
〔発明6〕 さらに、発明6の建築図面作成支援システムは、発明4及び5のいずれか1の建築図面作成支援システムにおいて、前記学習済みモデルは、建築図面中の編集可能な編集要素に関する情報、並びに当該編集要素の変更に伴い変更すべき又は変更された他の編集要素及びその内容に関する関連要素情報に基づいて学習を行ったものであり、前記推定手段で推定した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素を変更する変更手段を備える。
[Invention 6] Furthermore, the architectural drawing creation support system of
〔発明7〕 さらに、発明7の建築図面作成支援システムは、建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を取得する要素情報取得手段と、建築図面中の編集可能な編集要素に関する情報及び当該編集要素の変更に伴い変更すべき又は変更された他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記判断要否情報を推定する推定手段とを備える。 [Invention 7] The architectural drawing creation support system of invention 7 further comprises an element information acquisition means for acquiring changed element information on edit elements that have been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the judgment necessity information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information on the editable edit elements in the architectural drawing and judgment necessity information on whether a human judgment is required to change other edit elements that should be changed or have been changed due to the change in the edit element.
〔発明8〕 さらに、発明8の建築図面作成支援システムは、発明7の建築図面作成支援システムにおいて、前記推定手段で推定した判断要否情報に基づいて、当該判断要否情報に係る他の編集要素の変更に人の判断を要するか否かに関する情報を出力する出力手段を備える。 [Invention 8] The architectural drawing creation support system of invention 8 further includes an output means for outputting information on whether or not a change to another editing element related to the judgment necessity information is required, based on the judgment necessity information estimated by the estimation means, in the architectural drawing creation support system of invention 7.
〔発明9〕 さらに、発明9の建築図面作成支援システムは、建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を取得する要素情報取得手段と、建築図面中の編集可能な編集要素に関する情報、当該編集要素の変更に伴い変更すべき又は変更された他の編集要素及びその内容に関する関連要素情報、並びに当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記関連要素情報及び前記判断要否情報を推定する推定手段とを備える。 [Invention 9] The architectural drawing creation support system of invention 9 further comprises an element information acquisition means for acquiring changed element information relating to an edit element that has been changed among editable edit elements in an architectural drawing, and an estimation means for estimating the related element information and the judgment necessity information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information on the editable edit elements in the architectural drawing, related element information relating to other edit elements that should be changed or have been changed due to the change in the edit element and their contents, and judgment necessity information relating to whether or not a human judgment is required to change the other edit elements.
〔発明10〕 さらに、発明10の建築図面作成支援システムは、発明9の建築図面作成支援システムにおいて、前記推定手段で推定した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要すると判定した場合は、前記推定手段で推定した関連要素情報に基づいて、当該他の編集要素に関する情報を出力する出力手段を備える。
[Invention 10] Furthermore, the architectural drawing creation support system of
〔発明11〕 さらに、発明11の建築図面作成支援システムは、発明9及び10のいずれか1の建築図面作成支援システムにおいて、前記推定手段で推定した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要しないと判定した場合は、前記推定手段で推定した関連要素情報に基づいて、当該他の編集要素を変更する変更手段を備える。
[Invention 11] Furthermore, the architectural drawing creation support system of invention 11 is the architectural drawing creation support system of either
以上説明したように、発明1の建築図面作成支援システムによれば、仕上表に記載された仕上要素に対応する適合要素に関する適合要素情報が推定されるので、編集要素を仕上表の仕様に適合させることが期待できる。 As described above, the architectural drawing creation support system of Invention 1 estimates compatible element information regarding compatible elements that correspond to the finishing elements listed in the finishing table, so it is expected that the edited elements will be adapted to the specifications of the finishing table.
さらに、発明3の建築図面作成支援システムによれば、仕上表に記載された仕上要素に対応する適合要素及びその内容に関する適合要素情報が推定されるので、編集要素及びその内容を仕上表の仕様に適合させることが期待できる。 Furthermore, according to the architectural drawing creation support system of Invention 3, compatible elements corresponding to the finishing elements described in the finishing table and compatible element information related to the contents thereof are estimated, so it is expected that the edited elements and their contents will be adapted to the specifications of the finishing table.
さらに、発明4の建築図面作成支援システムによれば、変更を行った編集要素に係る他の編集要素に関する関連要素情報が推定されるので、変更すべき他の編集要素も併せて変更を行うことができる。 Furthermore, according to the architectural drawing creation support system of Invention 4, related element information regarding other edit elements related to the edit element that has been changed is estimated, so that other edit elements that should be changed can also be changed at the same time.
さらに、発明6の建築図面作成支援システムによれば、変更を行った編集要素に係る他の編集要素及びその内容に関する関連要素情報が推定されるので、変更すべき他の編集要素及びその内容も併せて変更を行うことができる。 Furthermore, according to the architectural drawing creation support system of Invention 6, related element information regarding other edit elements related to the edit element that has been changed and their contents is estimated, so that other edit elements that should be changed and their contents can also be changed at the same time.
さらに、発明7の建築図面作成支援システムによれば、変更を行った編集要素に係る他の編集要素の変更に人の判断を要するか否かに関する判断要否情報が推定されるので、変更すべき他の編集要素について人が変更すべきか否かを把握することができる。 Furthermore, according to the architectural drawing creation support system of Invention 7, judgment necessity information is estimated as to whether or not a human judgment is required to change other edit elements related to the edit element that has been changed, so it is possible to know whether or not a human should change the other edit elements that need to be changed.
さらに、発明9の建築図面作成支援システムによれば、変更を行った編集要素に係る他の編集要素及びその内容に関する関連要素情報並びに他の編集要素の変更に人の判断を要するか否かに関する判断要否情報が推定されるので、変更すべき他の編集要素及び内容について人が変更すべきか否かを把握することができる。 Furthermore, according to the architectural drawing creation support system of Invention 9, related element information on other edit elements related to the edit element that has been changed and their contents, as well as judgment necessity information on whether or not a human judgment is required to change the other edit elements, are estimated, so that it is possible to grasp whether or not a human should change the other edit elements and their contents that need to be changed.
〔第1の実施の形態〕
以下、本発明の第1の実施の形態を説明する。図1乃至図12は、本実施の形態を示す図である。
First Embodiment
A first embodiment of the present invention will now be described with reference to Figures 1 to 12.
まず、本実施の形態の構成を説明する。
図1は、図面作成支援装置100のハードウェア構成を示す図である。
First, the configuration of this embodiment will be described.
FIG. 1 is a diagram showing a hardware configuration of a drawing
図面作成支援装置100は、図1に示すように、制御プログラムに基づいて演算及びシステム全体を制御するCPU(Central Processing Unit)30と、所定領域に予めCPU30の制御プログラム等を格納しているROM(Read Only Memory)32と、ROM32等から読み出したデータやCPU30の演算過程で必要な演算結果を格納するためのRAM(Random Access Memory)34と、外部装置に対してデータの入出力を媒介するI/F(InterFace)38とで構成されており、これらは、データを転送するための信号線であるバス39で相互に且つデータ授受可能に接続されている。
As shown in FIG. 1, the drawing
I/F38には、外部装置として、ヒューマンインターフェースとしてデータの入力が可能なキーボードやマウス等からなる入力装置40と、データやテーブル等をファイルとして格納する記憶装置42と、画像信号に基づいて画面を表示する表示装置44とが接続されている。
Connected to the I/
記憶装置42には、CAD(Computer Aided Design)ソフトウェアやBIM(Building Information Modeling)ソフトウェア(以下これらを総称して「CADソフトウェア」という。)がインストールされている。CADソフトウェアは、ユーザの操作に応じて図面の作成を支援するソフトウェアである。CADソフトウェアの起動が要求されると、CPU30は、ROM32の所定領域に格納されているCADプログラムを起動させ、そのプログラムに従って処理を実行する。設計者は、CADソフトウェアを起動し、矩計図、平面詳細図その他の建築図面を作成することができる。
The storage device 42 has installed therein CAD (Computer Aided Design) software and BIM (Building Information Modeling) software (hereinafter collectively referred to as "CAD software"). CAD software is software that assists in the creation of drawings in response to user operations. When a request is made to start the CAD software, the
次に、記憶装置42のデータ構造を説明する。
図2は、仕上表データの構造を示す図である。
Next, the data structure of the storage device 42 will be described.
FIG. 2 is a diagram showing the structure of finishing list data.
記憶装置42は、図2に示すように、仕上表に関する仕上表データを記憶している。
仕上表は、建物各所の仕上げをまとめた表であり、屋根・外壁等の仕上げを示す外部仕上表と、各室内の壁・床・天井等の仕上げを示す内部仕上表がある。仕上表データには、仕上要素ごとに1つの行が登録されている。図2中3行目には、仕上要素「内部廊下」について、床の仕上げとして「タイルカーペット(A)、ボーダー張り」が、壁の仕上げとして「ビニルクロス(A)」が、天井の仕上げとして「ビニルクロス(A)がそれぞれ登録されている。これは、内部廊下の床を「タイルカーペット(A)、ボーダー張り」で、内部廊下の壁及び天井を「ビニルクロス(A)」で仕上げることを示している。また、図2中9行目には、仕上要素「風除室」について、天井高として「2450」が登録されている。これは、風除室の天井高を2450[mm]に仕上げることを示している。
As shown in FIG. 2, the storage device 42 stores finishing table data relating to finishing tables.
The finishing table is a table that summarizes the finishes of each part of a building. There is an exterior finishing table that shows the finishes of the roof and exterior walls, and an interior finishing table that shows the finishes of the walls, floors, ceilings, etc. of each room. In the finishing table data, one row is registered for each finishing element. In the third row in Figure 2, for the finishing element "internal corridor", "tile carpet (A), border" is registered as the floor finish, "vinyl cloth (A)" is registered as the wall finish, and "vinyl cloth (A)" is registered as the ceiling finish. This indicates that the floor of the internal corridor is finished with "tile carpet (A), border", and the walls and ceiling of the internal corridor are finished with "vinyl cloth (A)". In addition, in the ninth row in Figure 2, "2450" is registered as the ceiling height for the finishing element "windbreak room". This indicates that the ceiling height of the windbreak room is finished to 2450 [mm].
図3は、矩計図のCADデータの構造を示す図である。
記憶装置42は、図3に示すように、矩計図のCADデータやBIMデータ(以下これらを総称して「CADデータ」という。)を記憶している。
FIG. 3 is a diagram showing the structure of CAD data of a plan view.
As shown in FIG. 3, the storage device 42 stores CAD data and BIM data of plan views (hereinafter collectively referred to as "CAD data").
矩計図は、建物の断面を詳細に作図した図面である。矩計図のCADデータは、設計者がCADソフトウェアを利用して作成するものである。設計者は、CADソフトウェアにおいて、矩計図中の編集可能な編集要素を追加、編集又は削除することにより矩計図を作成する。図3の例では、「内部廊下」と表示された領域の床、壁及び天井の各編集要素が、「風除室」と表示された領域の床、壁及び天井の各編集要素がそれぞれ配置されている。これらは、図2の仕上表データにおいて3行目及び9行目の仕上要素に対応している。対応する仕上要素及び編集要素に対しては、仕上表データ及びCADデータの内部で同一のIDが設定されることにより対応づけが行われていてもよい。 A rectangular plan is a detailed drawing of the cross section of a building. CAD data for a rectangular plan is created by a designer using CAD software. A designer creates a rectangular plan in the CAD software by adding, editing, or deleting editable elements in the rectangular plan. In the example of Figure 3, the edit elements of the floor, wall, and ceiling of the area labeled "internal corridor" are arranged, as are the edit elements of the floor, wall, and ceiling of the area labeled "windbreak room." These correspond to the finishing elements in the third and ninth rows of the finishing table data in Figure 2. Corresponding finishing elements and editing elements may be associated by setting the same ID within the finishing table data and the CAD data.
図4は、平面詳細図のCADデータの構造を示す図である。
図5は、壁種別図である。
FIG. 4 is a diagram showing the structure of CAD data of a detailed plan view.
FIG. 5 is a diagram showing wall types.
記憶装置42は、図4に示すように、平面詳細図のCADデータを記憶している。
平面詳細図は、建物の平面を詳細に作図した図面である。平面詳細図のCADデータは、設計者がCADソフトウェアを利用して作成するものである。設計者は、CADソフトウェアにおいて、平面詳細図中の編集可能な編集要素を追加、編集又は削除することにより平面詳細図を作成する。平面詳細図において壁の編集要素に対しては壁種類が分かるようタグを配置する。タグは、英数字3桁又は4桁で四角又は楕円で囲まれたものであり、設計者は、図5の壁種別図を参考にして値を設定する。図4の例では、「LD」と表示された領域にタグ「L4DA」が、「洗面脱衣室」と表示された領域にタグ「L4JA」がそれぞれ配置されている。これらは、図2の仕上表データにおいて13行目及び17行目の仕上要素に対応している。対応する仕上要素及び編集要素に対しては、仕上表データ及びCADデータの内部で同一のIDが設定されることにより対応づけが行われていてもよい。
The storage device 42 stores CAD data of detailed plan views, as shown in FIG.
A detailed plan drawing is a drawing that draws the plan of a building in detail. CAD data of the detailed plan drawing is created by a designer using CAD software. The designer creates the detailed plan drawing by adding, editing, or deleting editable editing elements in the detailed plan drawing in the CAD software. In the detailed plan drawing, a tag is placed for the editing element of the wall so that the wall type can be identified. The tag is a three- or four-digit alphanumeric character surrounded by a square or ellipse, and the designer sets the value by referring to the wall type diagram in FIG. 5. In the example of FIG. 4, the tag "L4DA" is placed in the area displayed as "LD", and the tag "L4JA" is placed in the area displayed as "Bathroom/Dressing Room". These correspond to the finishing elements in the 13th and 17th rows of the finishing table data in FIG. 2. The corresponding finishing elements and editing elements may be associated with each other by setting the same ID in the finishing table data and the CAD data.
記憶装置42は、その他の建築図面のCADデータ、及び、学習済みモデルのデータを記憶している。学習済みモデルは、仕上表に記載された仕上要素に関する情報及びその仕上要素の仕様に適合し建築図面に記載された適合要素に関する情報に基づいて学習が行われている。仕上表データ及び矩計図、平面詳細図その他の建築図面のCADデータは、AIの学習に用いるため、記憶装置42には、過去に作成された多数のデータが記憶されている。これらのCADデータは、建築図面中の各編集要素が仕上表データの仕様に適合したものであり、AIの学習における教師データとなる。 The storage device 42 stores CAD data of other architectural drawings, and data of trained models. The trained models are trained based on information about the finishing elements listed in the finishing schedule and information about compatible elements listed in the architectural drawings that fit the specifications of those finishing elements. The finishing schedule data and CAD data for plan drawings, detailed floor plans, and other architectural drawings are used for AI training, so the storage device 42 stores a large amount of data that was created in the past. This CAD data is in which each editing element in the architectural drawings fits the specifications of the finishing schedule data, and serves as training data for the AI training.
次に、本実施の形態の動作を説明する。
図6は、学習済みモデル生成処理を示すフローチャートである。
Next, the operation of this embodiment will be described.
FIG. 6 is a flowchart showing the trained model generation process.
図7は、学習済みモデルの生成及び利用の工程を示すブロック図である。
学習済みモデル生成処理は、学習済みモデルを生成するために実行される処理であって、CPU30において実行されると、図6に示すように、ステップS100に移行して、仕上表データ解析処理を実行する。仕上表データ解析処理では、仕上表データを記憶装置42から読み出し、読み出した仕上表データから仕上要素に関する情報を抽出する。
FIG. 7 is a block diagram showing the process of generating and using a trained model.
The trained model generation process is a process executed to generate a trained model, and when executed by the
次いで、ステップS102に移行する。ステップS102では、CADデータ解析処理を実行する。CADデータ解析処理では、矩計図、平面詳細図その他の建築図面のCADデータを記憶装置42から読み出し、読み出したCADデータから編集要素に関する情報を抽出する。 Then, the process proceeds to step S102. In step S102, a CAD data analysis process is executed. In the CAD data analysis process, CAD data of the plan, detailed floor plan, and other architectural drawings is read from the storage device 42, and information regarding the editing elements is extracted from the read CAD data.
次いで、ステップS104に移行する。ステップS104では、図7に示すように、ステップS100、S102で抽出した情報に基づいて学習用データセットを生成し、ステップS106に移行して、生成した学習用データセットを学習用プログラムに入力し、学習用プログラムにより学習済みモデルを生成する。学習用プログラムは、学習前パラメータ及びハイパーパラメータを備え、入力した学習用データセット及びハイパーパラメータに基づいて学習を行い、学習前パラメータを更新する。そして、学習結果として学習済みモデルを出力する。 Then, the process proceeds to step S104. In step S104, as shown in FIG. 7, a training dataset is generated based on the information extracted in steps S100 and S102, and the process proceeds to step S106, where the generated training dataset is input to a training program and a trained model is generated by the training program. The training program includes pre-learning parameters and hyperparameters, and performs training based on the input training dataset and hyperparameters to update the pre-learning parameters. The trained model is then output as the training result.
学習済みモデルは、学習前パラメータが学習により更新された学習済みパラメータ及び推論プログラムを備える。推論プログラムは、仕上表データ及び編集要素を入力し、学習済みパラメータに基づいて、入力した仕上表データ及び編集要素から、その仕上表データの仕上要素及びその編集要素に対応する適合要素(仕上要素の仕様に適合する編集要素)を推定し、推定した適合要素を出力する。推論プログラムへの入力は、仕上表データそのものに限らず、ID等で対応関係が特定できれば、仕上表データの仕上要素のうち入力する編集要素に対応するものを抽出して行ってもよい。なお、入力した編集要素と適合要素の関係は、AIの学習により決まるものであるので、過去の仕上表データ及びCADデータの内容と同様の傾向を示すものの、必ずしも正確には一致しない曖昧さがある。ただし、この曖昧さは、学習データ量及び学習精度により小さくすることができる。 The trained model includes trained parameters in which pre-trained parameters have been updated by training, and an inference program. The inference program inputs finishing table data and edit elements, and based on the trained parameters, estimates the finishing elements of the finishing table data and the matching elements corresponding to the edit elements (edit elements that match the specifications of the finishing elements) from the input finishing table data and edit elements, and outputs the estimated matching elements. The input to the inference program is not limited to the finishing table data itself, and may be made by extracting finishing elements of the finishing table data that correspond to the input edit elements, as long as the correspondence can be specified by ID or the like. Note that the relationship between the input edit elements and the matching elements is determined by AI training, and therefore, although it shows a similar tendency to the contents of past finishing table data and CAD data, there is ambiguity in that they do not necessarily match exactly. However, this ambiguity can be reduced by the amount of training data and the training accuracy.
図8は、適合要素推定処理を示すフローチャートである。
適合要素推定処理は、ユーザからの要求に応じて実行される処理であって、CPU30において実行されると、図8に示すように、まず、ステップS150に移行する。ステップS150では、CADソフトウェアにおいて、建築図面中の編集可能な編集要素のうちいずれかがユーザの操作により指示されたか否かを判定し、編集要素が指示されたと判定した場合(YES)は、ステップS152に移行する。
FIG. 8 is a flowchart showing the matching element estimation process.
The matching element estimation process is executed in response to a request from a user, and when executed by the
ステップS152では、現在編集中のCADデータに対応する仕上表データを記憶装置42から読み出し、ステップS150で指示された編集要素を取得し、ステップS154に移行して、記憶装置42の学習済みモデルを用いて、読み出した仕上表データ及び取得した編集要素から適合要素を推定する。推定は、仕上表データ及び編集要素を学習済みモデルに入力し、学習済みモデルから出力される適合要素を取得することにより行う。 In step S152, the finishing table data corresponding to the CAD data currently being edited is read from the memory device 42, the edit elements specified in step S150 are obtained, and the process proceeds to step S154, where the trained model in the memory device 42 is used to estimate matching elements from the read finishing table data and the obtained edit elements. The estimation is performed by inputting the finishing table data and edit elements into the trained model and obtaining the matching elements output from the trained model.
そして、ステップS156に移行して、ステップS150で指示された編集要素とステップS154で推定された適合要素が識別や内容の点で不一致であるか否かを判定し、不一致であると判定した場合(YES)は、ステップS158に移行して、編集要素に不備がある旨を表示装置44に表示し、一連の処理を終了する。
Then, the process proceeds to step S156, where it is determined whether the edited element specified in step S150 and the matching element estimated in step S154 are inconsistent in terms of identification or content. If it is determined that they are inconsistent (YES), the process proceeds to step S158, where a message is displayed on the
一方、ステップS156で、編集要素と適合要素が不一致でないと判定した場合(NO)、及び、ステップS150で、編集要素が指示されないと判定した場合(NO)はいずれも、一連の処理を終了する。 On the other hand, if it is determined in step S156 that the edit element and the matching element do not mismatch (NO), or if it is determined in step S150 that an edit element is not specified (NO), the process ends.
〔矩計図の作成例〕
次に、矩計図を作成する場合を例に編集要素を変更する動作を説明する。なお、現在編集中の矩計図のCADデータに対応する仕上表データが図2に示す内容であるとする。
[Example of creating a plan drawing]
Next, the operation of changing the editing elements will be described taking the case of creating a plan view as an example. It is assumed that the finishing table data corresponding to the CAD data of the plan view currently being edited is the content shown in FIG.
図9は、編集要素を変更する前の矩計図である。
図10は、編集要素を変更した後の矩計図である。
FIG. 9 is a plan view before the editing elements are changed.
FIG. 10 is a plan view after the editing element has been changed.
設計者は、CADソフトウェアにおいて、図9の矩計図中「内部廊下」と表示された領域の床の編集要素400を指示する。このとき、編集要素400は、「ビニル床タイル(C)」と設定されているのに対し、図2の仕上表データにおいて対応する仕様要素(3行目)は、「タイルカーペット(A)、ボーダー張り」となっている。このため、図2の仕上表データ及び編集要素400が学習済みモデルに入力されると、適合要素「タイルカーペット(A)、ボーダー張り」が推定されるので、編集要素400に不備がある旨402が表示される。設計者は、表示402に従い、図10に示すように、編集要素400を「タイルカーペット(A)、ボーダー張り」に変更する。
In the CAD software, the designer specifies
続いて、設計者は、CADソフトウェアにおいて、図9の矩計図中「内部廊下」と表示された領域の壁の編集要素404を指示する。このとき、編集要素404は、「ビニルクロス(B)」と設定されているのに対し、図2の仕上表データにおいて対応する仕様要素(3行目)は、「ビニルクロス(A)」となっている。このため、図2の仕上表データ及び編集要素404が学習済みモデルに入力されると、適合要素「ビニルクロス(A)」が推定されるので、編集要素404に不備がある旨406が表示される。設計者は、表示406に従い、図10に示すように、編集要素404を「ビニルクロス(A)」に変更する。
Next, in the CAD software, the designer specifies
続いて、設計者は、CADソフトウェアにおいて、図9の矩計図中「内部廊下」と表示された領域の天井の編集要素408を指示する。このとき、編集要素408は、「ビニルクロス(B)」と設定されているのに対し、図2の仕上表データにおいて対応する仕様要素(3行目)は、「ビニルクロス(A)」となっている。このため、図2の仕上表データ及び編集要素408が学習済みモデルに入力されると、適合要素「ビニルクロス(A)」が推定されるので、編集要素408に不備がある旨406が表示される。設計者は、表示406に従い、図10に示すように、編集要素408を「ビニルクロス(A)」に変更する。
Next, in the CAD software, the designer specifies
同様に、設計者は、CADソフトウェアにおいて、図9の矩計図中「風除室」と表示された領域の天井の天井高(編集要素)410を指示する。天井高410も図2の仕上表データの仕様に適合しないので、天井高410に不備がある旨412が表示される。設計者は、表示412に従い、図10に示すように、天井高410を2450[mm]に変更する。
Similarly, in the CAD software, the designer specifies the ceiling height (edit element) 410 of the ceiling in the area marked "Windbreak" in the plan of Figure 9. Since the
なお、設計者は、CADソフトウェアにおいて、図9の矩計図中「共用廊下」と表示された領域の有効寸法414を指示する。有効寸法414は、建築関連の法令に適合しないので、有効寸法414に不備がある旨416が表示される。建築関連の法令に適合するか否かの判定は、例えば、特許文献1の技術により行うことができる。有効寸法414を変更する方法としては、右側の壁位置を調整するか左側の壁位置を調整することにより行うことができるが、AIでは、どちらを優先すべきかを判定することが難しいので、このような編集要素414については、変更に人の判断を要する編集要素として、AIにより自動で変更せず、設計者の判断に委ね設計者が右側又は左側の壁位置を変更する。
In addition, the designer specifies the
〔平面詳細図の作成例〕
次に、平面詳細図を作成する場合を例に編集要素を変更する動作を説明する。なお、現在編集中の平面詳細図のCADデータに対応する仕上表データが図2に示す内容であるとする。
[Example of detailed floor plan drawing]
Next, the operation of changing the editing elements will be described taking the case of creating a detailed plan view as an example. It is assumed that the finishing table data corresponding to the CAD data of the detailed plan view currently being edited is the content shown in FIG.
図11は、編集要素を変更する前の平面詳細図である。
図12は、編集要素を変更した後の平面詳細図である。
FIG. 11 is a detailed plan view before the editing element is changed.
FIG. 12 is a plan view detail after the editing element has been changed.
設計者は、CADソフトウェアにおいて、図11の平面詳細図中「洗面脱衣室」と表示された領域のタグ(編集要素)420を指示する。このとき、タグ420は、「L4JB」と設定されているのに対し、図2の仕上表データにおいて対応する仕様要素(17行目)は、「L4」「GBt12.5」「ビニルクロス(C)」(=図5の壁種別図より「L4JA」のこと)となっている。このため、図2の仕上表データ及びタグ420が学習済みモデルに入力されると、適合要素「L4JA」が推定されるので、タグ420に不備がある旨422が表示される。設計者は、表示422に従い、図12に示すように、タグ420を「L4JA」に変更する。
In the CAD software, the designer specifies the tag (edit element) 420 of the area displayed as "Bathroom/Dressing Room" in the detailed floor plan of FIG. 11. At this time, the
続いて、設計者は、CADソフトウェアにおいて、図11の平面詳細図中「LD」と表示された領域の壁のタグ424を指示する。このとき、タグ424は、「L4LA」と設定されているのに対し、図2の仕上表データにおいて対応する仕様要素(13行目)は、「L4」「GBt12.5※表面下地は防水GB」「ビニルクロス(C)」(=図5の壁種別図より「L4DA」のこと)となっている。このため、図2の仕上表データ及びタグ424が学習済みモデルに入力されると、適合要素「L4DA」が推定されるので、タグ424に不備がある旨426が表示される。設計者は、表示426に従い、図12に示すように、タグ424を「L4DA」に変更する。
Next, in the CAD software, the designer specifies the
次に、本実施の形態の効果を説明する。
本実施の形態では、仕上表データ及び編集要素を取得し、仕上表に記載された仕上要素に関する情報及びその仕上要素の仕様に適合し建築図面に記載された適合要素に関する情報に基づいて学習を行った学習済みモデルを用いて、取得した仕上表データ及び編集要素から適合要素を推定し、取得した編集要素と推定された適合要素が不一致である場合は、編集要素に不備がある旨を表示する。
Next, the effects of this embodiment will be described.
In this embodiment, finishing schedule data and edited elements are acquired, and a trained model is used to estimate suitable elements from the acquired finishing schedule data and edited elements, which has been trained based on information about the finishing elements listed in the finishing schedule and information about suitable elements listed in the architectural drawings that match the specifications of the finishing elements.If there is a mismatch between the acquired edited elements and the estimated suitable elements, a message is displayed indicating that there is a defect in the edited elements.
これにより、編集要素を仕上表の仕様に適合させることが期待できる。
本実施の形態において、ステップS152は、発明1又は2の要素情報取得手段に対応し、ステップS154は、発明1又は2の推定手段に対応し、ステップS158は、発明2の出力手段に対応している。
This is expected to allow editing elements to conform to the specifications of the finishing list.
In this embodiment, step S152 corresponds to the element information acquisition means of the first or second invention, step S154 corresponds to the estimation means of the first or second invention, and step S158 corresponds to the output means of the second invention.
〔第2の実施の形態〕
次に、本発明の第2の実施の形態を説明する。図13及び図14は、本実施の形態を示す図である。
Second Embodiment
Next, a second embodiment of the present invention will be described with reference to Figures 13 and 14.
本実施の形態では、上記第1の実施の形態に対し、編集要素の変更に伴い変更すべき他の編集要素を表示する点が異なる。ある編集要素を変更した場合に、その変更に伴って他の編集要素が仕上表の仕様に適合しなくなることがある。例えば、図9の天井高410を変更した場合、天井裏スペースの高さ等を変更する必要が生じる。本実施の形態では、編集要素の変更に伴い変更すべき他の編集要素を表示することにより、変更すべき他の編集要素も併せて設計者が変更を行えるように支援することを目的とする。以下、上記第1の実施の形態と異なる部分についてのみ説明し、重複する部分については説明を省略する。
This embodiment differs from the first embodiment in that it displays other edit elements that should be changed when an edit element is changed. When an edit element is changed, other edit elements may no longer conform to the specifications of the finishing table. For example, when the
まず、記憶装置42のデータ構造を説明する。
記憶装置42は、矩計図、平面詳細図その他の建築図面のCADデータであって、編集要素を変更する前のCADデータ(以下「変更前CADデータ」という。)及び編集要素を変更した後のCADデータ(以下「変更後CADデータ」という。)を記憶している。
First, the data structure of the storage device 42 will be described.
The memory device 42 stores CAD data for plan views, detailed floor plans, and other architectural drawings, including CAD data before an editing element is changed (hereinafter referred to as "CAD data before change") and CAD data after an editing element is changed (hereinafter referred to as "CAD data after change").
記憶装置42は、学習済みモデルのデータを記憶している。学習済みモデルは、建築図面中の編集可能な編集要素に関する情報及びその編集要素の変更に伴い変更された他の編集要素に関する情報に基づいて学習が行われている。変更前CADデータ及び変更後CADデータは、AIの学習に用いるため、記憶装置42には、過去に作成された多数のデータが記憶されている。 The storage device 42 stores data of the trained model. The trained model is trained based on information about editable elements in architectural drawings and information about other editable elements that have been changed as a result of changing those editable elements. The pre-change CAD data and post-change CAD data are used for training the AI, so the storage device 42 stores a large amount of data that has been created in the past.
次に、本実施の形態の動作を説明する。
図13は、学習済みモデルの生成及び利用の工程を示すブロック図である。
Next, the operation of this embodiment will be described.
FIG. 13 is a block diagram showing the process of generating and using a trained model.
学習済みモデル生成処理は、学習済みモデルを生成するために実行される処理であって、CPU30において実行されると、変更前CADデータ及び変更後CADデータを記憶装置42から読み出し、読み出したCADデータから編集要素に関する情報を抽出する。
The trained model generation process is a process executed to generate a trained model, and when executed by the
そして、図13に示すように、抽出した情報に基づいて学習用データセットを生成し、生成した学習用データセットを学習用プログラムに入力し、学習用プログラムにより学習済みモデルを生成する。学習済みモデルの推論プログラムは、建築図面中の編集可能な編集要素のうち変更を行った編集要素を入力し、学習済みパラメータに基づいて、入力した編集要素から、その編集要素の変更に伴い変更すべき他の編集要素を推定し、推定した編集要素を関連要素として出力する。 Then, as shown in FIG. 13, a learning dataset is generated based on the extracted information, the generated learning dataset is input to a learning program, and a trained model is generated by the learning program. The inference program of the trained model inputs an edit element that has been changed among the editable edit elements in the architectural drawing, estimates from the input edit element other edit elements that should be changed in conjunction with the change to that edit element based on the trained parameters, and outputs the estimated edit elements as related elements.
図14は、関連要素推定処理を示すフローチャートである。
関連要素推定処理は、ユーザからの要求に応じて実行される処理であって、CPU30において実行されると、図14に示すように、まず、ステップS200に移行する。ステップS200では、CADソフトウェアにおいて、建築図面中の編集可能な編集要素のうちいずれかが変更されたか否かを判定し、編集要素が変更されたと判定した場合(YES)は、ステップS202に移行する。
FIG. 14 is a flowchart showing the related element estimation process.
The related element estimation process is executed in response to a request from a user, and when executed by the
ステップS202では、変更された編集要素を取得し、ステップS204に移行して、記憶装置42の学習済みモデルを用いて、取得した編集要素から関連要素を推定する。推定は、編集要素を学習済みモデルに入力し、学習済みモデルから出力される関連要素を取得することにより行う。 In step S202, the changed edited element is acquired, and the process proceeds to step S204, where the related element is estimated from the acquired edited element using the trained model in the storage device 42. The estimation is performed by inputting the edited element into the trained model and acquiring the related element output from the trained model.
そして、ステップS206に移行して、推定した関連要素に基づいて、変更すべき他の編集要素を特定の態様(例えばハイライト)で表示し、一連の処理を終了する。 Then, the process proceeds to step S206, where other editing elements to be changed are displayed in a specific manner (e.g., highlighted) based on the estimated related elements, and the process ends.
一方、ステップS200で、編集要素が変更されないと判定した場合(NO)は、一連の処理を終了する。 On the other hand, if it is determined in step S200 that the edit element has not been changed (NO), the process ends.
次に、本実施の形態の効果を説明する。
本実施の形態では、変更を行った編集要素を取得し、建築図面中の編集可能な編集要素に関する情報及びその編集要素の変更に伴い変更された他の編集要素に関する情報に基づいて学習を行った学習済みモデルを用いて、取得した編集要素から関連要素を推定し、推定した関連要素に基づいて、変更すべき他の編集要素を特定の態様で表示する。
Next, the effects of this embodiment will be described.
In this embodiment, the edited element that has been changed is obtained, and related elements are estimated from the obtained edited element using a trained model that has been trained based on information about editable edited elements in an architectural drawing and information about other edited elements that have been changed as a result of the change to that edited element, and the other edited elements that should be changed are displayed in a specific manner based on the estimated related elements.
これにより、変更すべき他の編集要素も併せて変更を行うことができる。
本実施の形態において、ステップS202は、発明4の要素情報取得手段に対応し、ステップS204は、発明4又は5の推定手段に対応し、ステップS206は、発明5の出力手段に対応している。
This allows other editing elements that need to be changed to also be changed.
In this embodiment, step S202 corresponds to the element information acquisition means of invention 4, step S204 corresponds to the estimation means of
〔第3の実施の形態〕
次に、本発明の第3の実施の形態を説明する。図15及び図16は、本実施の形態を示す図である。
Third embodiment
Next, a third embodiment of the present invention will be described with reference to Figures 15 and 16.
本実施の形態では、上記第2の実施の形態に対し、変更に人の判断を要する編集要素を推定する点が異なる。ある編集要素を変更した場合に、その変更に伴って他の編集要素を自動で変更することが望ましいが、変更に人の判断を要する編集要素については自動変更の対象から除外することが必要である。例えば、図9の有効寸法414を変更する場合、右側又は左側の壁位置のどちらを変更するかは設計者が行う。本実施の形態では、編集要素の変更に伴い変更すべき他の編集要素を自動で変更するとともに、変更に人の判断を要する編集要素については自動変更の対象から除外することにより、変更すべき他の編集要素及び内容について人が変更すべきか否かを把握できるように支援することを目的とする。以下、上記第1及び第2の実施の形態と異なる部分についてのみ説明し、重複する部分については説明を省略する。
This embodiment differs from the second embodiment in that it estimates editing elements that require human judgment to change. When an editing element is changed, it is desirable to automatically change other editing elements in conjunction with the change, but editing elements that require human judgment to change must be excluded from the targets of automatic change. For example, when changing the
まず、記憶装置42のデータ構造を説明する。
記憶装置42は、変更に人の判断を要するか否かの情報と対応づけて編集要素を登録した判断要否データを記憶している。変更に人の判断を要する編集要素は、人の判断により設定してもよい。また、変更前CADデータ及び変更後CADデータに基づいて、変更前後で変更パターンが2以上ある編集要素を抽出し、抽出した編集要素を、変更に人の判断を要する編集要素として設定してもよい。
First, the data structure of the storage device 42 will be described.
The storage device 42 stores judgment necessity data in which edit elements are registered in association with information on whether a change requires human judgment. Edit elements that require human judgment for change may be set by human judgment. Also, edit elements that have two or more change patterns before and after the change may be extracted based on the pre-change CAD data and the post-change CAD data, and the extracted edit elements may be set as edit elements that require human judgment for change.
記憶装置42は、学習済みモデルのデータを記憶している。学習済みモデルは、建築図面中の編集可能な編集要素に関する情報、その編集要素の変更に伴い変更された他の編集要素及びその内容に関する情報、並びに当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習が行われている。変更前CADデータ、変更後CADデータ及び判断要否データは、AIの学習に用いるため、記憶装置42には、過去に作成された多数のデータが記憶されている。 The storage device 42 stores data of the trained model. The trained model is trained based on information about editable editing elements in architectural drawings, information about other editing elements and their contents that have been changed as a result of changing the editing elements, and judgment necessity information about whether or not a human judgment is required to change the other editing elements. The pre-change CAD data, post-change CAD data, and judgment necessity data are used for training the AI, so the storage device 42 stores a large amount of data created in the past.
次に、本実施の形態の動作を説明する。
図15は、学習済みモデルの生成及び利用の工程を示すブロック図である。
Next, the operation of this embodiment will be described.
FIG. 15 is a block diagram showing the process of generating and using a trained model.
学習済みモデル生成処理は、学習済みモデルを生成するために実行される処理であって、CPU30において実行されると、変更前CADデータ、変更後CADデータ及び判断要否データを記憶装置42から読み出し、読み出したCADデータ及び判断要否データから編集要素に関する情報及び判断要否情報を抽出する。
The trained model generation process is a process executed to generate a trained model, and when executed by the
そして、図15に示すように、抽出した情報に基づいて学習用データセットを生成し、生成した学習用データセットを学習用プログラムに入力し、学習用プログラムにより学習済みモデルを生成する。学習済みモデルの推論プログラムは、建築図面中の編集可能な編集要素のうち変更を行った編集要素を入力し、学習済みパラメータに基づいて、入力した編集要素から、その編集要素の変更に伴い変更すべき他の編集要素及び判断要否情報を推定し、推定した編集要素を関連要素として出力する。 Then, as shown in FIG. 15, a learning dataset is generated based on the extracted information, the generated learning dataset is input to a learning program, and a trained model is generated by the learning program. The inference program of the trained model inputs an edit element that has been changed among the editable edit elements in the architectural drawing, and estimates from the input edit element, based on the trained parameters, other edit elements that should be changed in conjunction with the change to that edit element and information on whether or not a decision is required, and outputs the estimated edit elements as related elements.
図16は、関連要素推定処理を示すフローチャートである。
関連要素推定処理は、ユーザからの要求に応じて実行される処理であって、CPU30において実行されると、図16に示すように、まず、ステップS250に移行する。ステップS250では、CADソフトウェアにおいて、建築図面中の編集可能な編集要素のうちいずれかが変更されたか否かを判定し、編集要素が変更されたと判定した場合(YES)は、ステップS252に移行する。
FIG. 16 is a flowchart showing the related element estimation process.
The related element estimation process is executed in response to a request from a user, and when executed by the
ステップS252では、変更された編集要素を取得し、ステップS254に移行して、記憶装置42の学習済みモデルを用いて、取得した編集要素から関連要素及び判断要否情報を推定する。推定は、編集要素を学習済みモデルに入力し、学習済みモデルから出力される関連要素及び判断要否情報を取得することにより行う。 In step S252, the changed edited element is acquired, and the process proceeds to step S254, where the related elements and the decision necessity information are estimated from the acquired edited element using the trained model in the storage device 42. The estimation is performed by inputting the edited element into the trained model, and acquiring the related elements and the decision necessity information output from the trained model.
そして、ステップS256に移行して、推定した判断要否情報に基づいて、推定した関連要素の変更に人の判断を要するか否かを判定し、関連要素の変更に人の判断を要しないと判定した場合(NO)は、ステップS258に移行して、推定した関連要素に基づいて、変更すべき他の編集要素の内容が関連要素の内容となるように当該他の編集要素を変更し、一連の処理を終了する。 Then, the process proceeds to step S256, where it is determined based on the estimated judgment necessity information whether or not human judgment is required to change the estimated related elements. If it is determined that human judgment is not required to change the related elements (NO), the process proceeds to step S258, where the other edited elements to be changed are changed based on the estimated related elements so that their contents become the contents of the related elements, and the process ends.
一方、ステップS256で、関連要素の変更に人の判断を要すると判定した場合(YES)は、ステップS260に移行して、推定した関連要素に基づいて、変更すべき他の編集要素を特定の態様(例えばハイライト)で表示し、一連の処理を終了する。 On the other hand, if it is determined in step S256 that changing the related elements requires human judgment (YES), the process proceeds to step S260, where other edited elements to be changed based on the estimated related elements are displayed in a specific manner (e.g., highlighted), and the process ends.
一方、ステップS250で、編集要素が変更されないと判定した場合(NO)は、一連の処理を終了する。 On the other hand, if it is determined in step S250 that the edit element has not been changed (NO), the process ends.
次に、本実施の形態の効果を説明する。
本実施の形態では、建築図面中の編集可能な編集要素のうち変更を行った編集要素を取得し、建築図面中の編集可能な編集要素に関する情報、その編集要素の変更に伴い変更された他の編集要素及びその内容に関する情報、並びに当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行った学習済みモデルを用いて、取得した編集要素から関連要素及び判断要否情報を推定し、推定した判断要否情報に基づいて関連要素の変更に人の判断を要すると判定した場合は、推定した関連要素に基づいて他の編集要素を特定の態様で表示し、関連要素の変更に人の判断を要しないと判定した場合は、推定した関連要素に基づいて他の編集要素を変更する。
Next, the effects of this embodiment will be described.
In this embodiment, an edit element that has been changed among editable edit elements in an architectural drawing is obtained, and related elements and judgment necessity information are estimated from the obtained edit element using a trained model that has been trained based on information about the editable edit element in the architectural drawing, information about other edit elements and their contents that have been changed as a result of the change to that edit element, and judgment necessity information regarding whether human judgment is required to change the other edit elements.If it is determined based on the estimated judgment necessity information that human judgment is required to change the related element, the other edit elements are displayed in a specific manner based on the estimated related elements, and if it is determined that human judgment is not required to change the related elements, the other edit elements are changed based on the estimated related elements.
これにより、変更すべき他の編集要素及び内容について人が変更すべきか否かを把握することができる。 This allows the person to understand whether other editing elements and content need to be changed or not.
本実施の形態において、ステップS252は、発明7又は9の要素情報取得手段に対応し、ステップS254は、発明7乃至11の推定手段に対応し、ステップS258は、発明11の変更手段に対応し、ステップS260は、発明8又は10の出力手段に対応している。
In this embodiment, step S252 corresponds to the element information acquisition means of invention 7 or 9, step S254 corresponds to the estimation means of inventions 7 to 11, step S258 corresponds to the change means of invention 11, and step S260 corresponds to the output means of
〔変形例〕
なお、上記第1の実施の形態においては、ユーザの操作により指示された編集要素について不備を表示したが、これに限らず、図面中のすべての編集要素をスキャンし、不備のある編集要素については一括で不備を表示する構成を採用することもできる。
[Modifications]
In the first embodiment described above, defects were displayed for edit elements specified by user operation, but this is not limited to this. It is also possible to adopt a configuration in which all edit elements in the drawing are scanned and defects are displayed all at once for edit elements that have defects.
また、上記第1の実施の形態及びその変形例においては、編集要素に不備がある旨を表示したが、これに限らず、推定した適合要素に基づいて、指示された編集要素を変更する構成を採用することもできる。この場合、学習済みモデルは、仕上表に記載された仕上要素に関する情報並びにその仕上要素の仕様に適合し建築図面に記載された適合要素及びその内容に関する情報に基づいて学習を行ったものを用いる。 In addition, in the first embodiment and its modified example, a message is displayed indicating that there is a defect in the edited element, but this is not limiting, and a configuration can also be adopted in which the indicated edited element is changed based on the estimated matching element. In this case, the trained model used is one that has been trained based on information about the finishing element listed in the finishing table, as well as information about matching elements and their contents that are listed in the architectural drawing and that match the specifications of the finishing element.
また、上記第2の実施の形態及びその変形例においては、推定した関連要素に基づいて、変更すべき他の編集要素を特定の態様で表示したが、これに限らず、推定した関連要素に基づいて、変更すべき他の編集要素を変更する構成を採用することもできる。この場合、学習済みモデルは、建築図面中の編集可能な編集要素に関する情報並びにその編集要素の変更に伴い変更された他の編集要素及びその内容に関する情報に基づいて学習を行った学習済みモデルを用いて学習を行ったものを用いる。 In addition, in the second embodiment and its modified example, the other edit elements to be changed are displayed in a specific manner based on the estimated related elements, but this is not limiting, and a configuration in which the other edit elements to be changed are changed based on the estimated related elements can also be adopted. In this case, the trained model used is one that has been trained using a trained model that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements and their contents that have been changed as a result of the change in the edit element.
また、上記第3の実施の形態及びその変形例においては、推定した関連要素に基づいて、変更すべき他の編集要素を変更し又は特定の態様で表示したが、これに限らず、変更を行わない構成であれば、学習済みモデルは、建築図面中の編集可能な編集要素に関する情報、その編集要素の変更に伴い変更された他の編集要素に関する情報、及び当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行ったものを用いることもできる。また、特定の態様での表示も行わない構成(例えば、人の判断の要否だけを推定する構成)であれば、建築図面中の編集可能な編集要素に関する情報及びその編集要素の変更に伴い変更された他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行ったものを用いることもできる。 In addition, in the third embodiment and its modified examples, other edit elements that should be changed are changed or displayed in a specific manner based on the estimated related elements, but this is not limited to the above. If the configuration does not involve changes, the trained model can be one that has been trained based on information about editable edit elements in architectural drawings, information about other edit elements that have been changed as a result of the change to that edit element, and judgment necessity information regarding whether or not human judgment is required to change the other edit elements. Also, if the configuration does not involve display in a specific manner (for example, a configuration that only estimates whether or not human judgment is required), the trained model can be one that has been trained based on information about editable edit elements in architectural drawings and judgment necessity information regarding whether or not human judgment is required to change the other edit elements that have been changed as a result of the change to that edit element).
また、上記第2及び第3の実施の形態並びにその変形例においては、建築図面中の編集可能な編集要素に関する情報及びその編集要素の変更に伴い変更された他の編集要素に関する情報に基づいて学習を行った学習済みモデルを用いたが、これに限らず、建築図面中の編集可能な編集要素に関する情報及びその編集要素の変更に伴い変更すべき他の編集要素に関する情報に基づいて学習を行った学習済みモデルを用いることもできる。すなわち、変更前CADデータ及び変更後CADデータに代えて、編集要素Aが変更された場合に編集要素Bも変更するといった対応情報をAIの学習に用いることができる。 In addition, in the second and third embodiments and their variations, a trained model is used that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements that have been changed as a result of changes to those edit elements. However, this is not limiting, and a trained model that has been trained based on information about editable edit elements in architectural drawings and information about other edit elements that should be changed as a result of changes to those edit elements can also be used. In other words, instead of pre-change CAD data and post-change CAD data, correspondence information, such as changing edit element B when edit element A is changed, can be used to train the AI.
また、上記第1乃至第3の実施の形態及びその変形例においては、学習済みモデルを生成し、生成した学習済みモデルを用いたが、これに限らず、大規模言語モデル(Large Language Model)を利用する構成を採用することもできる。具体的には、例えば、次の構成を採用することができる。 In addition, in the first to third embodiments and their variations, a trained model is generated and the trained model is used, but this is not limiting, and a configuration that utilizes a large language model can also be adopted. Specifically, for example, the following configuration can be adopted.
図面作成支援装置100は、大規模言語モデルを有する大規模言語モデルサーバにネットワークを介して接続している。大規模言語モデルサーバは、図面作成支援装置100と同様のハードウェア構成を有して構成されている。大規模言語モデルとは、人間の話す言葉をその出現確率でモデル化した言語モデルと呼ばれるものを、膨大なデータから事前学習する深層学習モデルである。大規模言語モデルサーバは、リクエストを受信すると、大規模言語モデルを用いて、受信されたリクエストに含まれる文章から次の単語の生成確率を統計的に推定し、推定結果をリクエスト元に送信する。大規模言語モデルとしては、例えば、インターネットサイト「https://chatgpt-lab.com/n/n418d3aa56f0b」「https://agirobots.com/chatgpt-mechanism-and-problem/」に記載されている公知の技術を採用することができる。
The drawing
そして、図面作成支援装置100に対しては、次の発明A1~A3又はB1~B8を適用することができる。
The following inventions A1 to A3 or B1 to B8 can be applied to the drawing
〔発明A1〕 仕上表に記載される仕上要素に関する仕上要素情報及び建築図面中の編集可能な編集要素に関する編集要素情報を含み、且つ、当該仕上要素の仕様に適合し建築図面に記載される適合要素に関する適合要素情報を生成する要求を含むリクエストを大規模言語モデルに入力するリクエスト入力手段と、
前記リクエストに対して前記大規模言語モデルから出力される適合要素情報を取得する要素情報取得手段とを備える。
[Invention A1] A request input means for inputting a request including finishing element information on finishing elements described in a finishing table and editing element information on editable editing elements in an architectural drawing, and including a request for generating matching element information on matching elements described in the architectural drawing that match the specifications of the finishing elements, into a large-scale language model;
The language model further includes an element information acquiring means for acquiring matching element information output from the large-scale language model in response to the request.
〔発明A2〕 発明A1において、
前記要素情報取得手段で取得した適合要素情報に基づいて、前記編集要素情報に係る編集要素に関する情報を出力する出力手段とを備える。
[Invention A2] In Invention A1,
The system further comprises an output means for outputting information on an edited element related to the edited element information based on the adapted element information acquired by the element information acquisition means.
図9を例に発明A1、A2の実施の形態を説明する。上記第1の実施の形態の変形例であって、ステップS154の処理が、大規模言語モデルサーバから適合要素情報を取得する処理に置き換わる。 The embodiments of inventions A1 and A2 will be described with reference to FIG. 9. This is a modification of the first embodiment, in which the process of step S154 is replaced with a process of acquiring matching element information from a large-scale language model server.
設計者は、CADソフトウェアにおいて、図9の矩計図中「内部廊下」と表示された領域の床の編集要素400を指示すると、図面作成支援装置100では、大規模言語モデルサーバにリクエストが送信される。リクエストは、図2の仕上表データ及び編集要素400を含み、且つ、編集要素400の適合要素を生成する要求を含む。このリクエストに対し、大規模言語モデルサーバからは適合要素情報が出力される。図面作成支援装置100では、適合要素情報を受信すると、受信した適合要素情報に基づいて編集要素400に不備がある旨402が表示される。
When the designer designates, in the CAD software, an
〔発明A3〕 発明A1又はA2において、
前記リクエストは、仕上表に記載される仕上要素に関する仕上要素情報及び建築図面中の編集可能な編集要素に関する編集要素情報を含み、且つ、当該仕上要素の仕様に適合し建築図面に記載される適合要素及びその内容に関する適合要素情報を生成する要求を含むものであり、
前記要素情報取得手段で取得した適合要素情報に基づいて、前記編集要素情報に係る編集要素を変更する変更手段を備える。
[Invention A3] In Invention A1 or A2,
The request includes finish element information on a finish element described in a finish schedule and edit element information on an editable edit element in an architectural drawing, and includes a request to generate conforming element information on a conforming element and its contents that conforms to the specifications of the finish element and is described in the architectural drawing;
The system further includes a change means for changing an edit element related to the edit element information based on the suitable element information acquired by the element information acquisition means.
図9を例に発明A1、A3の実施の形態を説明する。上記第1の実施の形態の変形例である。 The following describes the embodiments of inventions A1 and A3 using FIG. 9 as an example. These are modifications of the first embodiment described above.
設計者は、CADソフトウェアにおいて、図9の矩計図中「内部廊下」と表示された領域の床の編集要素400を指示すると、図面作成支援装置100では、大規模言語モデルサーバにリクエストが送信される。リクエストは、図2の仕上表データ及び編集要素400を含み、且つ、編集要素400の適合要素を生成する要求を含む。このリクエストに対し、大規模言語モデルサーバからは適合要素情報が出力される。図面作成支援装置100では、適合要素情報を受信すると、受信した適合要素情報に基づいて編集要素400が変更される。
When the designer designates, in the CAD software, an
〔発明B1〕 建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を含み、且つ、当該編集要素の変更に伴い変更すべき他の編集要素に関する関連要素情報を生成する要求を含むリクエストを大規模言語モデルに入力するリクエスト入力手段と、
前記リクエストに対して前記大規模言語モデルから出力される関連要素情報を取得する要素情報取得手段とを備える。
[Invention B1] A request input means for inputting a request including changed element information on an edited element among editable edit elements in an architectural drawing that has been changed, and including a request for generating related element information on other edit elements that should be changed in conjunction with the change in the edited element, into a large-scale language model;
The method further comprises: acquiring element information about the related elements output from the large-scale language model in response to the request.
〔発明B2〕 発明B1において、
前記要素情報取得手段で取得した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素に関する情報を出力する出力手段を備える。
[Invention B2] In Invention B1,
The device further comprises an output means for outputting information on other edit elements related to the related element information based on the related element information acquired by the element information acquisition means.
図9を例に発明B1、B2の実施の形態を説明する。上記第2の実施の形態の変形例であって、ステップS202の処理が、大規模言語モデルサーバから関連要素情報を取得する処理に置き換わる。 The embodiments of inventions B1 and B2 will be described with reference to FIG. 9. This is a modification of the second embodiment, in which the process of step S202 is replaced with a process of acquiring related element information from a large-scale language model server.
図9の矩計図中「内部廊下」と表示された領域の床の編集要素400が設計者により変更されると、図面作成支援装置100では、大規模言語モデルサーバにリクエストが送信される。リクエストは、編集要素400を含み、且つ、編集要素400の関連要素を生成する要求を含む。このリクエストに対し、大規模言語モデルサーバからは関連要素情報が出力される。図面作成支援装置100では、関連要素情報を受信すると、受信した関連要素情報に基づいて、編集要素400の変更に伴い変更すべき他の編集要素が特定の態様で表示される。
When the designer changes the
〔発明B3〕 発明B1又はB2において、
前記リクエストは、建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を含み、且つ、当該編集要素の変更に伴い変更すべき他の編集要素及びその内容に関する関連要素情報を生成する要求を含むものであり、
前記要素情報取得手段で取得した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素を変更する変更手段を備える。
[Invention B3] In Invention B1 or B2,
the request includes changed element information on an edit element that has been changed among editable edit elements in the architectural drawing, and includes a request to generate other edit elements that should be changed in conjunction with the change in the edit element and related element information on the contents of the other edit elements;
The editing device further includes a change means for changing, based on the related element information acquired by the element information acquisition means, another edit element related to the related element information.
図9を例に発明B1、B3の実施の形態を説明する。上記第2の実施の形態の変形例である。 The following describes the embodiments of inventions B1 and B3 using FIG. 9 as an example. These are modifications of the second embodiment described above.
図9の矩計図中「内部廊下」と表示された領域の床の編集要素400が設計者により変更されると、図面作成支援装置100では、大規模言語モデルサーバにリクエストが送信される。リクエストは、編集要素400を含み、且つ、編集要素400の関連要素を生成する要求を含む。このリクエストに対し、大規模言語モデルサーバからは関連要素情報が出力される。図面作成支援装置100では、関連要素情報を受信すると、受信した関連要素情報に基づいて、編集要素400の変更に伴い変更すべき他の編集要素が変更される。
When the designer changes the
〔発明B4〕 建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を含み、且つ、当該編集要素の変更に伴い変更すべき他の編集要素の変更に人の判断を要するか否かに関する判断要否情報を生成する要求を含むリクエストを大規模言語モデルに入力するリクエスト入力手段と、
前記リクエストに対して前記大規模言語モデルから出力される判断要否情報を取得する判断要否情報取得手段とを備える。
[Invention B4] A request input means for inputting a request including changed element information on an edited element among editable edit elements in an architectural drawing that has been changed, and a request for generating judgment necessity information on whether a human judgment is required for changing other edit elements that should be changed in conjunction with the change of the edited element, into a large-scale language model;
The system further comprises a judgment necessity information acquisition means for acquiring judgment necessity information output from the large-scale language model in response to the request.
〔発明B5〕 発明B4において、
前記判断要否情報取得手段で取得した判断要否情報に基づいて、当該判断要否情報に係る他の編集要素の変更に人の判断を要するか否かに関する情報を出力する出力手段を備える。
[Invention B5] In Invention B4,
The apparatus further comprises an output means for outputting information on whether or not a human judgment is required for changing another editing element related to the judgment necessity information, based on the judgment necessity information acquired by the judgment necessity information acquisition means.
〔発明B6〕 建築図面中の編集可能な編集要素のうち変更を行った編集要素に関する変更要素情報を含み、且つ、当該編集要素の変更に伴い変更すべき他の編集要素及びその内容に関する関連要素情報並びに当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報を生成する要求を含むリクエストを大規模言語モデルに入力するリクエスト入力手段と、
前記リクエストに対して前記大規模言語モデルから出力される関連要素情報及び判断要否情報を取得する要素情報取得手段とを備える。
[Invention B6] A request input means for inputting a request including changed element information on an edited element that has been changed among editable edit elements in an architectural drawing, and also including a request for generating other edit elements that should be changed in conjunction with the change in the edited element and related element information on the contents of the other edit elements, and judgment necessity information on whether or not human judgment is required to change the other edit elements, into the large-scale language model;
The method further comprises an element information acquiring means for acquiring related element information and judgment necessity information outputted from the large-scale language model in response to the request.
〔発明B7〕 発明B6において、
前記要素情報取得手段で取得した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要すると判定した場合は、前記要素情報取得手段で取得した関連要素情報に基づいて、当該他の編集要素に関する情報を出力する出力手段を備える。
[Invention B7] In Invention B6,
If it is determined based on the judgment necessity information acquired by the element information acquisition means that human judgment is required to change other editing elements related to the related element information, the device is provided with an output means for outputting information regarding the other editing elements based on the related element information acquired by the element information acquisition means.
〔発明B8〕 発明B6又はB7において、
前記要素情報取得手段で取得した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要しないと判定した場合は、前記要素情報取得手段で取得した関連要素情報に基づいて、当該他の編集要素を変更する変更手段を備える。
[Invention B8] In Invention B6 or B7,
If it is determined based on the judgment necessity information acquired by the element information acquisition means that no human judgment is required to change other editing elements related to the related element information, a modification means is provided for changing the other editing elements based on the related element information acquired by the element information acquisition means.
図9を例に発明B4~B8の実施の形態を説明する。上記第3の実施の形態の変形例であって、ステップS254の処理が、大規模言語モデルサーバから関連要素情報及び判断要否情報を取得する処理に置き換わる。 The following describes embodiments of inventions B4 to B8 using FIG. 9 as an example. This is a modification of the third embodiment, in which the process of step S254 is replaced with a process of acquiring related element information and judgment necessity information from a large-scale language model server.
図9の矩計図中「内部廊下」と表示された領域の床の編集要素400が設計者により変更されると、図面作成支援装置100では、大規模言語モデルサーバにリクエストが送信される。リクエストは、編集要素400を含み、且つ、編集要素400の関連要素及びその関連要素の変更に人の判断を要するか否かに関する判断要否情報を生成する要求を含む。このリクエストに対し、大規模言語モデルサーバからは関連要素情報及び判断要否情報が出力される。図面作成支援装置100では、関連要素情報及び判断要否情報を受信すると、受信した関連要素情報に基づいて関連要素の変更に人の判断を要するか否かが判定される。その結果、人の判断を要すると判定されると、受信した関連要素情報に基づいて関連要素が特定の態様で表示される。これに対し、人の判断を要しないと判定されると、受信した関連要素情報に基づいて関連要素が変更される。
When the designer changes the
また、上記第1乃至第3の実施の形態及びその変形例においては、単一の装置として実現したが、これに限らず、ネットワークシステムとして実現することもできる。ネットワークシステムの例として、図面作成支援装置100の機能の一部又は全部を、クラウドコンピューティングサービスを提供するサーバ上の仮想サーバとして構成することができる。
In addition, in the first to third embodiments and their variations, the device is realized as a single device, but the present invention is not limited to this and can also be realized as a network system. As an example of a network system, some or all of the functions of the drawing
また、上記第1乃至第3の実施の形態及びその変形例において、図面作成支援装置100は、記憶装置42を利用するように構成したが、これに限らず、データベースサーバ等の外部の記憶装置を利用するように構成することもできる。
In addition, in the first to third embodiments and their variations, the drawing
また、上記第1乃至第3の実施の形態及びその変形例において、図6、図8、図14及び図16のフローチャートに示す処理を実行するにあたってはいずれも、ROM32に予め格納されているプログラムを実行する場合について説明したが、これに限らず、これらの手順を示したプログラムが記憶された記憶媒体から、そのプログラムをRAM34に読み込んで実行するようにしてもよい。
In addition, in the above first to third embodiments and their modifications, the processes shown in the flowcharts of Figures 6, 8, 14, and 16 are executed by executing a program that is pre-stored in
ここで、記憶媒体とは、RAM、ROM等の半導体記憶媒体、FD、HD等の磁気記憶型記憶媒体、CD、CDV、LD、DVD等の光学的読取方式記憶媒体、MO等の磁気記憶型/光学的読取方式記憶媒体であって、電子的、磁気的、光学的等の読み取り方法のいかんにかかわらず、コンピュータで読み取り可能な記憶媒体であれば、あらゆる記憶媒体を含むものである。 Here, storage media refers to semiconductor storage media such as RAM and ROM, magnetic storage media such as FD and HD, optically readable storage media such as CD, CDV, LD and DVD, and magnetic storage/optically readable storage media such as MO, and includes any storage media that can be read by a computer, regardless of the reading method (electronic, magnetic, optical, etc.).
また、上記第1乃至第3の実施の形態及びその変形例は相互に適用することができる。
また、上記第1乃至第3の実施の形態及びその変形例に限らず、本発明の主旨を逸脱しない範囲で他の場合にも適用可能である。
Moreover, the first to third embodiments and the modifications thereof can be applied to each other.
Furthermore, the present invention is not limited to the above-described first to third embodiments and their modifications, but can also be applied to other cases without departing from the spirit of the present invention.
100…図面作成支援装置、 30…CPU、 32…ROM、 34…RAM、 38…I/F、 39…バス、 40…入力装置、 42…記憶装置、 44…表示装置、 400,404,408,410…編集要素、 402,406,412,416,422,426…不備表示、 414…有効寸法、 420,424…タグ 100...Drawing creation support device, 30...CPU, 32...ROM, 34...RAM, 38...I/F, 39...bus, 40...input device, 42...storage device, 44...display device, 400, 404, 408, 410...editing elements, 402, 406, 412, 416, 422, 426...defect display, 414...effective dimensions, 420, 424...tags
Claims (11)
仕上表に記載された仕上要素に関する情報及び当該仕上要素の仕様に適合し建築図面に記載された適合要素に関する適合要素情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した仕上要素情報及び編集要素情報から前記適合要素情報を推定する推定手段とを備えることを特徴とする建築図面作成支援システム。 An element information acquiring means for acquiring finishing element information relating to finishing elements described in a finishing table and editing element information relating to editable editing elements in an architectural drawing;
An architectural drawing creation support system comprising: an estimation means for estimating the suitable element information from the finishing element information and edited element information acquired by the element information acquisition means using a trained model that has been trained based on information regarding the finishing elements described in the finishing table and suitable element information regarding suitable elements that are compatible with the specifications of the finishing elements and are described in the architectural drawing.
前記推定手段で推定した適合要素情報に基づいて、前記要素情報取得手段で取得した編集要素情報に係る編集要素に関する情報を出力する出力手段とを備えることを特徴とする建築図面作成支援システム。 In claim 1,
An architectural drawing creation support system comprising: an output means for outputting information regarding edited elements related to edited element information acquired by the element information acquisition means based on the compatible element information estimated by the estimation means.
前記学習済みモデルは、仕上表に記載された仕上要素に関する情報並びに当該仕上要素の仕様に適合し建築図面に記載された適合要素及びその内容に関する適合要素情報に基づいて学習を行ったものであり、
前記推定手段で推定した適合要素情報に基づいて、前記要素情報取得手段で取得した編集要素情報に係る編集要素を変更する変更手段を備えることを特徴とする建築図面作成支援システム。 In any one of claims 1 and 2,
The trained model is trained based on information on the finishing elements described in the finishing table and information on the matching elements and their contents described in the architectural drawings that conform to the specifications of the finishing elements,
An architectural drawing creation support system comprising a modification means for modifying an edit element related to the edit element information acquired by the element information acquisition means based on the suitable element information estimated by the estimation means.
建築図面中の編集可能な編集要素に関する情報及び当該編集要素の変更に伴い変更すべき又は変更された他の編集要素に関する関連要素情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記関連要素情報を推定する推定手段とを備えることを特徴とする建築図面作成支援システム。 An element information acquisition means for acquiring changed element information regarding an edit element that has been changed among editable edit elements in an architectural drawing;
An architectural drawing creation support system comprising: an estimation means for estimating the related element information from the changed element information acquired by the element information acquisition means using a trained model that has been trained based on information regarding editable edit elements in an architectural drawing and related element information regarding other edit elements that should be changed or have been changed due to a change to the edit element.
前記推定手段で推定した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素に関する情報を出力する出力手段を備えることを特徴とする建築図面作成支援システム。 In claim 4,
An architectural drawing production support system comprising: an output means for outputting information regarding other edit elements related to the related element information based on the related element information estimated by the estimation means.
前記学習済みモデルは、建築図面中の編集可能な編集要素に関する情報、並びに当該編集要素の変更に伴い変更すべき又は変更された他の編集要素及びその内容に関する関連要素情報に基づいて学習を行ったものであり、
前記推定手段で推定した関連要素情報に基づいて、当該関連要素情報に係る他の編集要素を変更する変更手段を備えることを特徴とする建築図面作成支援システム。 In any one of claims 4 and 5,
The trained model is trained based on information about editable edit elements in architectural drawings, and related element information about other edit elements that should be changed or have been changed due to a change in the edit element and their contents,
An architectural drawing production support system comprising: a change means for changing other edit elements related to the related element information based on the related element information estimated by the estimation means.
建築図面中の編集可能な編集要素に関する情報及び当該編集要素の変更に伴い変更すべき又は変更された他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記判断要否情報を推定する推定手段とを備えることを特徴とする建築図面作成支援システム。 An element information acquisition means for acquiring changed element information regarding an edit element that has been changed among editable edit elements in an architectural drawing;
An architectural drawing creation support system comprising: an estimation means for estimating judgment necessity information from changed element information acquired by the element information acquisition means using a trained model that has been trained based on information regarding editable edit elements in an architectural drawing and judgment necessity information regarding whether human judgment is required to change other edit elements that should be changed or have been changed due to a change to the edit element.
前記推定手段で推定した判断要否情報に基づいて、当該判断要否情報に係る他の編集要素の変更に人の判断を要するか否かに関する情報を出力する出力手段を備えることを特徴とする建築図面作成支援システム。 In claim 7,
An architectural drawing creation support system characterized by comprising an output means for outputting information regarding whether or not human judgment is required to change other editing elements related to the judgment necessity information estimated by the estimation means, based on the judgment necessity information estimated by the estimation means.
建築図面中の編集可能な編集要素に関する情報、当該編集要素の変更に伴い変更すべき又は変更された他の編集要素及びその内容に関する関連要素情報、並びに当該他の編集要素の変更に人の判断を要するか否かに関する判断要否情報に基づいて学習を行った学習済みモデルを用いて、前記要素情報取得手段で取得した変更要素情報から前記関連要素情報及び前記判断要否情報を推定する推定手段とを備えることを特徴とする建築図面作成支援システム。 An element information acquisition means for acquiring changed element information regarding an edit element that has been changed among editable edit elements in an architectural drawing;
An architectural drawing creation support system comprising: an estimation means for estimating the related element information and the judgment necessity information from the changed element information acquired by the element information acquisition means, using a trained model that has been trained based on information regarding editable edit elements in an architectural drawing, related element information regarding other edit elements and their contents that should be changed or have been changed due to a change to the edit element, and judgment necessity information regarding whether human judgment is required to change the other edit elements.
前記推定手段で推定した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要すると判定した場合は、前記推定手段で推定した関連要素情報に基づいて、当該他の編集要素に関する情報を出力する出力手段を備えることを特徴とする建築図面作成支援システム。 In claim 9,
An architectural drawing creation support system characterized by having an output means for outputting information regarding the other edited elements based on the related element information estimated by the estimation means when it is determined that human judgment is required to change other edited elements related to the related element information based on the judgment necessity information estimated by the estimation means.
前記推定手段で推定した判断要否情報に基づいて当該関連要素情報に係る他の編集要素の変更に人の判断を要しないと判定した場合は、前記推定手段で推定した関連要素情報に基づいて、当該他の編集要素を変更する変更手段を備えることを特徴とする建築図面作成支援システム。 In any one of claims 9 and 10,
An architectural drawing creation support system characterized by having a modification means for modifying other editing elements related to the related element information based on the related element information estimated by the estimation means when it is determined that no human judgment is required to change the other editing elements related to the related element information based on the judgment necessity information estimated by the estimation means.
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JP2015162025A (en) * | 2014-02-26 | 2015-09-07 | 株式会社コンピュータシステム研究所 | Construction plan support system, construction plan support program, and storage medium |
JP2019215761A (en) * | 2018-06-13 | 2019-12-19 | 株式会社竹中工務店 | Design support device and design support model learning device |
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JP2015162025A (en) * | 2014-02-26 | 2015-09-07 | 株式会社コンピュータシステム研究所 | Construction plan support system, construction plan support program, and storage medium |
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