JP7383094B1 - Building structure diagnostic equipment and programs - Google Patents

Abstract

An object of the present invention is to provide a building structure diagnostic device and a program for suitably diagnosing abnormalities in buildings and structures. A building structure diagnosis device 1 includes an acquisition unit (control unit 11) that acquires image data of a predetermined structure, and a detection unit that detects an abnormality based on the image data acquired by the acquisition unit. (control unit 11), a display control unit (control unit 11) that displays the detection result by the detection unit on the display unit 34, and a reception unit (control unit 11) that receives input of the degree of abnormality detected by the detection unit. , and the display control unit displays information (judgment criteria 345d) for determining the degree on the display unit 34. [Selection diagram] Figure 2

Description

The present invention relates to a building structure diagnostic device and program.

BACKGROUND ART Building structure diagnostic systems that diagnose abnormalities (for example, cracks, etc.) occurring in the exterior and interior of buildings and structures have been known.

For example, Patent Document 1 discloses a building structure diagnosis system that creates an edited image by editing an image of a building or structure, identifies damaged parts, and diagnoses the degree of damage based on the edited image. is listed.

JP 2021-51022 Publication

However, in the invention described in Patent Document 1, the degree of damage is diagnosed by artificial intelligence, and there is a problem that if the result of the diagnosis is wrong, it cannot be corrected.
Furthermore, in cases where the accuracy of diagnosis by artificial intelligence is not high, there is a desire for humans to judge the degree of abnormality such as damage.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a building structure diagnostic device and a program for suitably diagnosing abnormalities in buildings and structures.

The invention according to claim 1 is a building structure diagnostic device 1, which includes, for example, as shown in FIGS. 2, 9, and 12.
an acquisition unit (control unit 11) that acquires image data of a predetermined structure;
a detection unit (control unit 11) that detects an abnormality based on the image data acquired by the acquisition unit;
a display control unit (control unit 11) that displays a detection result by the detection unit on a display unit 34;
a reception unit (control unit 11) that receives an input of a user's determination result of the degree of abnormality detected by the detection unit;
a trained model 121 that is subjected to machine learning using the image data as input and information regarding the abnormality as output;
Equipped with
The detection unit detects an abnormality using the learned model 121,
The display control unit displays, on the same screen displayed by the display unit 34, a criterion 345d for determining the degree of damage to the structure according to the degree, which is comprised of a plurality of stages as information for the user to judge the degree; An image of a predetermined structure is displayed, and a match rate between the abnormality included in the image data as the detection result and the abnormality machine-learned by the learned model 121 is displayed.

According to the invention described in claim 1, the user refers to the abnormality detected by the detection unit based on image data taken of a predetermined structure, and the building structure diagnosis device 1 determines the degree of the abnormality. It is possible to accept input of the degree of abnormality determined by the user based on the information provided.
This allows a more accurate degree of abnormality determined by the user to be accepted. Therefore, abnormalities in buildings and structures can be suitably diagnosed.
Further, the user can judge the degree of abnormality by referring to the criteria for determining the degree of damage to the structure, which is made up of multiple levels and depends on the degree of damage.
Further, the detection unit can detect an abnormality using a trained model such as AI (Artificial Intelligence). Thereby, an abnormality can be detected easily and accurately.
In addition, the user can check the criteria for determining the degree of damage to the structure displayed on the same screen, the image taken of the structure, and the match between the anomaly contained in the image data and the anomaly learned by the trained model. You can easily compare the rates. Therefore, the user can easily judge the degree of anomaly by considering the criteria for determining the degree of damage to the structure and the match rate between the anomaly included in the image data and the anomaly learned by the trained model. I can do it.
This allows the user to easily determine the degree of abnormality.

The invention according to claim 2 is, for example, as shown in FIGS. 9 and 12, in the building structure diagnosis device 1 according to claim 1,
The reception unit receives input of a comment regarding the detection result by the detection unit.

According to the invention set forth in claim 2 , it is possible to receive input of a comment regarding an abnormality by a user.
This allows more detailed diagnosis of abnormalities.

The invention according to claim 3 is, for example, as shown in FIG. 13, in the building structure diagnosis device 1 according to claim 1,
The display control unit displays one or more templates of comments regarding the detection result by the detection unit on the display unit 34,
The reception unit receives selection of the template.

According to the third aspect of the invention, the user can select and input a comment regarding the detection result from the template.
This saves the user the trouble of manually entering comments.

The invention according to claim 4 is, for example, as shown in FIGS. 9 and 12, in the building structure diagnosis device 1 according to claim 1,
The detection unit detects multiple types of abnormalities based on one image data acquired by the acquisition unit.

According to the fourth aspect of the invention, it is possible to detect a plurality of types of abnormalities without acquiring image data for each type of abnormality and performing abnormality detection for each type of abnormality.
This makes it possible to efficiently detect abnormalities.

The invention according to claim 5 is, for example, as shown in FIGS. 2, 9, and 16 to 17B, in the building structure diagnosis device 1 according to claim 1,
The apparatus includes a report creation section (control section 11) that creates a report based on the detection result by the detection section and the degree of abnormality received by the reception section.

According to the invention set forth in claim 5 , the detection results and the degree of abnormality can be automatically input into the report (by the control unit 11).
This allows reports to be created efficiently.

The invention according to claim 6 is a program, for example, as shown in FIGS. 2, 9, and 12,
The computer (control unit 11) of the building structure diagnosis device 1 is equipped with a trained model 121 that is machine-learned using image data taken of a predetermined structure as input and information regarding abnormalities as output.
an acquisition unit that acquires the image data;
a detection unit that detects an abnormality based on the image data acquired by the acquisition unit;
a display control unit that displays the detection result by the detection unit on the display unit 34;
a reception unit that receives an input of a user's determination result of the degree of abnormality detected by the detection unit;
function as
The detection unit detects an abnormality using the learned model,
The display control unit displays, on the same screen displayed by the display unit 34, a criterion 345d for determining the degree of damage to the structure according to the degree, which is comprised of a plurality of stages as information for the user to judge the degree; An image of a predetermined structure is displayed, and a match rate between the abnormality included in the image data as the detection result and the abnormality machine-learned by the learned model 121 is displayed.

According to the invention set forth in claim 6 , the user refers to the abnormality detected by the detection unit based on the image data of the predetermined structure, and the building structure diagnosis device 1 determines the degree of the abnormality. It is possible to accept input of the degree of abnormality determined by the user based on the information provided.
This allows a more accurate degree of abnormality determined by the user to be accepted. Therefore, abnormalities in buildings and structures can be suitably diagnosed.
Further, the user can judge the degree of abnormality by referring to the criteria for determining the degree of damage to the structure, which is made up of multiple levels and depends on the degree of damage.
Further, the detection unit can detect an abnormality using a trained model such as AI (Artificial Intelligence). Thereby, an abnormality can be detected easily and accurately.
In addition, the user can check the criteria for determining the degree of damage to the structure displayed on the same screen, the image taken of the structure, and the match between the anomaly contained in the image data and the anomaly learned by the trained model. You can easily compare the rates. Therefore, the user can easily judge the degree of anomaly by considering the criteria for determining the degree of damage to the structure and the match rate between the anomaly included in the image data and the anomaly learned by the trained model. I can do it.
This allows the user to easily determine the degree of abnormality.

According to the present invention, abnormalities in buildings and structures can be suitably diagnosed.

FIG. 1 is a diagram showing the configuration of a building structure diagnosis system. FIG. 1 is a block diagram showing the configuration of a building structure diagnosis device. FIG. 2 is a block diagram showing the configuration of an information management device. FIG. 2 is a block diagram showing the configuration of a terminal device. 3 is a flowchart showing the flow of durability diagnosis. It is a flowchart which shows the flow of a diagnosis registration process. It is a figure showing an example of a diagnosis registration screen displayed by a terminal device. It is a figure showing an example of a diagnosis list screen displayed by a terminal device. It is a flowchart which shows the flow of diagnostic processing. It is a figure showing an example of a diagnosis main screen displayed by a terminal device. It is a figure showing an example of a building questionnaire screen displayed by a terminal device. It is a figure showing an example of a diagnosis details screen displayed by a terminal device. It is a figure showing an example of a diagnosis details screen displayed by a terminal device. It is a figure showing an example of a diagnosis main screen displayed by a terminal device. FIG. 6 is a diagram illustrating an example of a special notes details screen displayed by the terminal device. It is a figure showing an example of a diagnosis main screen displayed by a terminal device. FIG. 3 is a diagram showing an example of a report. FIG. 3 is a diagram showing an example of a report.

Embodiments of the present invention will be described below with reference to the drawings. However, although the embodiments described below have various limitations that are technically preferable for implementing the present invention, the technical scope of the present invention is not limited to the embodiments and illustrated examples below. do not have.

[1. Configuration description]
[1-1. Description of system configuration]
FIG. 1 is a diagram showing a building structure diagnosis system 100.
The building structure diagnosis system 100 includes a building structure diagnosis device (hereinafter referred to as a diagnosis device) 1, an information management device 2, and a terminal device 3.

The diagnostic device 1, the information management device 2, and the terminal device 3 that constitute the building structure diagnostic system 100 can communicate with each other via a communication network N, for example.
The communication network N includes various communication networks such as telephone lines, ISDN lines, optical fibers, mobile communication networks, communication satellite lines, CATV lines, and other leased lines, as well as Internet service providers that connect them. In other words, it may include the Internet), etc. In addition, various communication networks such as LAN (Local Area Network), WAN (Wide Area Network), WiFi (Wireless Fidelity), Bluetooth (registered trademark), and NFC (Near Field Communication) are connected to enable communication with each other. It may be a communication network. Furthermore, the form of connection may be wired, wireless, or a combination of wired and wireless.

[1-2. Description of building structure diagnosis device]
Next, the configuration of the diagnostic device 1 will be explained.
The diagnostic device 1 includes a PC, a dedicated device/terminal, and the like.

The diagnostic device 1 includes a control section 11, a storage section 12, and a communication section 13, as shown in FIG.
Each section 11 to 13 is electrically connected by a bus or the like.
Note that the diagnostic device 1 may include at least one of a display section and an operation section.

The control unit 11 includes a CPU, a RAM (Random Access Memory), a ROM (Read Only Memory), and the like.
The ROM stores various programs executed by the CPU.
Then, the CPU of the control unit 11 reads various programs stored in the storage unit 12, expands them into the RAM, executes various processes according to the expanded programs, and centrally controls the operation of the diagnostic device 1. It has become.

The storage unit 12 includes a nonvolatile memory, a hard disk, and the like.
The storage unit 12 stores various programs executed by the control unit 11 and various data necessary for executing the programs.
The various programs include, for example, a diagnostic registration program that executes a diagnostic registration process that will be described later, a diagnostic program that executes a diagnostic process that will be described later, and the like. It is assumed that other programs necessary for the operation of this system are included as appropriate.
Further, the various data include, for example, template data for report 4, which will be described later. In addition, data and parameters necessary for the operation of this system shall be included as appropriate.

Furthermore, the storage unit 12 stores a trained model 121 used in diagnostic processing to be described later.
The trained model 121 is machine-trained using image data obtained by photographing a predetermined structure as input and information regarding abnormalities as output. The information regarding the abnormality is the presence or absence of the abnormality and the content of the abnormality. In other words, the learned model 121 detects an abnormality in a predetermined structure from an image taken of the structure. The abnormality of the structure includes, for example, decay, deformation, deterioration, damage, etc. of the structure.
The trained model 121 may be an AI (Artificial Intelligence) having a deep learned neural network.

The storage unit 12 also includes a diagnostic database (hereinafter referred to as diagnostic DB) 122.
The diagnosis DB 122 stores information regarding durability diagnosis for diagnosing the durability of a predetermined structure. Information regarding the durability diagnosis includes the date and time when the durability diagnosis was requested, information regarding the building that includes the specified structure that is the subject of diagnosis, the scheduled date of visit to the building that includes the specified structure that is the subject of diagnosis, and Memorizes the person in charge of durability diagnosis, etc.

The communication section 13 is composed of a communication module and the like.
The communication unit 13 transmits and receives various signals and data to and from other devices (information management device 2, terminal device 3, etc.) connected by wire or wirelessly via the communication network N. There is.

[1-3. Description of information management device]
Next, the configuration of the information management device 2 will be explained.
The information management device 2 includes a PC, a dedicated device/terminal, and the like.

The information management device 2 includes a control section 21, a storage section 22, and a communication section 23, as shown in FIG.
Each section 21 to 23 is electrically connected by a bus or the like.
Note that the information management device 2 may include at least one of a display section and an operation section.

The control unit 21 is a part that controls the operation of the information management device 2, and is configured to include, for example, a CPU, ROM, RAM, etc., and by cooperation between the CPU and program data stored in the storage unit 22, It centrally controls each part of the information management device 2.

The storage unit 22 includes a nonvolatile memory, a hard disk, and the like.
The storage unit 22 stores various programs executed by the control unit 21 and various data necessary for executing the programs.

The storage unit 22 also includes a building database (hereinafter referred to as building DB) 221.
The building DB 221 contains information regarding buildings equipped with predetermined structures (building owner information (owner's name, address, contact information, etc.), location, type, structure/number of floors, building age, delivery date, drawings, building history information, etc.) ).

The communication section 23 is composed of a communication module and the like.
The communication unit 23 is configured to transmit and receive various signals and various data to and from other devices (such as the diagnostic device 1) connected by wire or wirelessly via the communication network N.

[1-4. Description of terminal device]
Next, the configuration of the terminal device 3 will be explained.
As the terminal device 3, there is no need to use a dedicated device, and a general-purpose mobile terminal such as a smartphone or a tablet terminal can be used.

As shown in FIG. 4, the terminal device 3 includes a control section 31, a storage section 32, a communication section 33, a display section 34, an operation section 35, and an imaging section 36.
Each section 31 to 36 is electrically connected by a bus or the like.
Note that the imaging unit 36 does not need to be provided within the terminal device 3. A camera included in an external device configured to be able to communicate with the terminal device 3 may be used as the imaging unit.

The control unit 31 is a part that controls the operation of the terminal device 3, and is configured to include, for example, a CPU, ROM, RAM, etc. It centrally controls each part of the device 3.

The storage unit 32 is a part in which various information necessary for the operation of the terminal device 3 is stored, and is composed of, for example, a non-volatile memory, a hard disk, etc., and is necessary for the operation of the terminal device 3 such as program data. Data is stored so that it can be read and written by the control unit 31.

The storage unit 32 also stores a diagnostic application program (hereinafter referred to as a diagnostic application) 321.
The control unit 31 generates and displays a display screen on the diagnostic application 321 by itself based on the information received from the diagnostic device 1.
Note that when the terminal device 3 has a browser, the control unit 31 may display various web pages generated by the diagnostic device 1 on the display unit 34 according to operations performed on the operation unit 35 by the user.

The communication section 33 is composed of a communication module and the like.
The communication unit 33 is configured to transmit and receive various signals and various data to and from other devices (such as the diagnostic device 1) connected by wire or wirelessly via the communication network N.

The display unit 34 includes, for example, a display such as an LCD (Liquid Crystal Display), and displays an image based on a display control signal output from the control unit 31 on the display.

The operation unit 35 includes, for example, a touch panel formed integrally with the display unit 34, receives operation input from a user, and outputs an operation signal to the control unit 31 in accordance with the operation input.
The operation unit 35 may be, for example, a keyboard having character input keys, number input keys, and keys associated with various other functions.

The imaging unit 36 is a digital camera unit that has an optical system and an imaging element such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor). is generated and output to the control section 31.
The imaging unit 36 photographs, for example, a predetermined structure such as an entire building, a nameplate, a foundation, a frame, a roof, an outer wall, external equipment, an inner wall, a bathroom, water supply and drainage equipment, etc. as a subject.

[2. [Explanation of operation of building structure diagnosis system]
Next, the operation of the building structure diagnosis system 100 according to this embodiment will be explained.
FIG. 5 shows a flowchart of durability diagnosis performed using the building structure diagnosis system 100.

(Durability diagnosis)
First, when the user instructs durability diagnosis registration in the diagnosis application 321 via the operation unit 35 of the terminal device 3, the control unit 11 of the diagnostic device 1 executes the diagnosis registration process shown in FIG. S1).

(Diagnosis registration process)
In the diagnosis registration process, the control unit 11 causes the diagnosis registration screen 341 (FIG. 7) to be displayed on the diagnosis application 321 (displayed on the display unit 34 of the terminal device 3) (step A1).
Next, the control unit 11 acquires information regarding a building including a predetermined structure to be diagnosed, which is specified by the user via the operation unit 35, from the building DB 221 of the information management device 2, and displays the information on the diagnosis registration screen 341. Display (Step A2). Note that the control unit 11 may display only part of the acquired information regarding the building on the diagnosis registration screen 341.
In the example shown in FIG. 7, the control unit 11 displays building owner information (owner's name, address, and contact information), building location (site address), and delivery date as information regarding the building.

Next, the control unit 11 receives, from the terminal device 3, information regarding durability diagnosis other than the information acquired in step A2, which is input into the diagnosis registration screen 341 (step A3).
In the example shown in FIG. 7, the control unit 11 provides information such as the date and time when the durability diagnosis was requested, the scheduled date of visiting the building that includes the predetermined structure to be diagnosed, and the person in charge of the durability diagnosis. receive.
Note that when the diagnostic device 1 includes a display unit and an operation unit, the control unit 11 displays a diagnosis registration screen on the display unit of the diagnostic device 1 according to the operation performed by the user on the operation unit of the diagnostic device 1, and performs step A2. Information regarding durability diagnosis other than the information acquired in step 1 may be acquired.

Next, when the user presses the registration button 341a on the diagnosis registration screen 341, the control unit 11 stores information regarding durability diagnosis (the information acquired in step A2 and the information received in step A3) in the diagnosis DB 122. Accordingly, the durability diagnosis is registered (step A4), and this process is ended. Note that when registering the durability diagnosis, the control unit 11 may add a diagnosis number (diagnosis No.) to the durability diagnosis.

The control unit 11 also lists the durability diagnoses registered in step S1 for each person in charge, and causes the diagnosis list screen 342 (FIG. 8) that displays the list to be displayed on the diagnosis application 321 (displayed on the display unit 34). ).
In the example shown in FIG. 8, the control unit 11 displays registered durability diagnoses for each month of the scheduled visit date.

In the example shown in FIG. 8, the control unit 11 displays a diagnosis number (diagnosis No.), list type, owner information, undiagnosed/completed, and others on the diagnosis list screen 342 as display items of the durability diagnosis list. let

The control unit 11 displays a "not yet" button 342d or a "completed" button 342e for the undiagnosed/diagnosed item.
A durability diagnosis for which an "unfinished" button 342d is displayed indicates that the diagnostic process is not completed. Furthermore, the durability diagnosis for which the "Completed" button 342e is displayed indicates that the diagnosis process has been completed.
Further, in the durability diagnosis for which the diagnostic processing is not yet completed, the control unit 11 displays the schedule change button 342a, and when the user presses the schedule change button 342a, accepts a change in the scheduled visit date.
Furthermore, in the durability diagnosis for which the diagnostic process has been completed, the control unit 11 causes the "completed" button 342e to display the date on which the diagnostic process was executed (diagnosis date).
The case where the user presses the "Not done" button 342d or the "Done" button 342e will be described later.

Further, the control unit 11 displays a details button 342b and a map button 342c in other items.
When the user presses the details button 342b, the control unit 11 causes the diagnostic application 321 to display a details screen (not shown) that displays information regarding durability diagnosis (displays it on the display unit 34).
When the user presses the Map button 342c, the control unit 11 causes the diagnosis application 321 to display a Map screen (not shown) that displays a map showing the location of the building included in the information regarding durability diagnosis. section 34).

Furthermore, the control unit 11 keeps the durability diagnosis for which the diagnostic process has been completed displayed on the diagnosis list screen 342 until a predetermined period (for example, one week) has elapsed from the time the diagnostic process was completed. It is then deleted from the diagnosis list screen 342 after a predetermined period of time has elapsed.

Returning to FIG. 5, the person in charge of durability diagnosis (user) visits a building equipped with a predetermined structure to be diagnosed based on the information regarding durability diagnosis saved in step S1, and evaluates the predetermined structure. Photographing is performed using the imaging unit 36 of the terminal device 3. The person in charge of the durability diagnosis photographs a predetermined structure, such as the entire building, the nameplate of the building, the foundation, the frame, the roof, the outer wall, the external equipment, the inner wall, the bathroom, the water supply and drainage equipment, and the like. The photographed image is used as a diagnostic image.
Furthermore, the person in charge of the durability diagnosis interviews the building owner and obtains building history information (step S2). Building history information includes, for example, building maintenance/renovation history (extension, renovation, repair/reinforcement, presence of termite compensation), damage history (flood damage, earthquake, fire), defect history (uneven subsidence, termite damage, rain leaks), These include differences between the actual building and the design documents.

Next, when the user presses the "Not yet" button 342d for any durability diagnosis on the diagnosis list screen 342, and a durability diagnosis for which the diagnostic process has not been completed is selected, the control unit 11 , executes the diagnostic process shown in FIG. 9 (step S3).

(Diagnostic processing)
In the diagnosis process, the control unit 11 causes the diagnosis list screen 342 to transition to the diagnosis main screen 343 shown in FIG. 10 (step B1).
The control unit 11 displays information regarding durability diagnosis on the diagnosis main screen 343.
In the example shown in FIG. 10, the control unit 11 provides information regarding the building including the predetermined structure to be diagnosed (owner information (owner's name, contact information), building type, structure/ The number of floors, delivery date, drawings) and the person in charge of durability diagnosis are displayed.
Note that the control unit 11 causes the drawing of the building to be displayed on the diagnosis main screen 343 when the user presses the drawing viewing button 343a.
Further, the control unit 11 may receive a change in the number of floors of the building in the number of floors column 343b of the building.
Further, the control unit 11 displays the scheduled date of the visit in the implementation date column 343c as the implementation date. Note that the control unit 11 may accept changes to the implementation date in the implementation date column 343c. Further, the control unit 11 accepts a user's selection as to whether or not to display the implementation date on the cover of the report 4, which will be described later.
Further, the control unit 11 displays the scheduled visit date in the report creation date column 343d as the report creation date. Note that the control unit 11 may accept a change in the report creation date in the report creation date field 343d. Further, the control unit 11 accepts a user's selection as to whether or not to display the report creation date on the cover of the report 4.

Furthermore, when the user presses the return button 343h on the diagnosis main screen 343, the control unit 11 returns to the diagnosis list screen 342 without saving the changes and selections accepted on the diagnosis main screen 343.
Furthermore, when the user presses the save button 343i on the diagnosis main screen 343, the control unit 11 saves the changes and selections received on the diagnosis main screen 343 in the diagnosis DB 122.

Next, when the user presses the mark 343e attached to "Building Questionnaire" on the diagnosis main screen 343, the control unit 11 displays the building questionnaire screen 344 shown in FIG. 11 and inputs building history information. (Step B2).
The user inputs the building history information obtained by interviewing the building owner in step S2 of the durability diagnosis on the building questionnaire screen 344.
In the example shown in FIG. 11, the control unit 11 stores the building's maintenance/renovation history (extension, reconstruction, repair/reinforcement, presence of termite compensation), damage history (flood damage, earthquake, fire), defect history ( We accept input of differences between the actual building and the design documents (uneven subsidence, termite damage, rain leaks), and differences between the actual building and the design documents.
Furthermore, if the building history information acquired from the building DB 221 in step A2 of the diagnosis registration process already includes building history information, the control unit 11 may cause the building history information to be displayed on the building questionnaire screen 344. good.

Further, when the user presses the save button 344a on the building questionnaire screen 344, the control unit 11 saves the building history information input on the building questionnaire screen 344 in the diagnosis DB 122 and the building DB 221, and saves the building history information input on the building questionnaire screen 344 to the diagnosis main screen. Return to 343.
Further, when the user presses the return button 344b on the building questionnaire screen 344, the control unit 11 returns to the diagnosis main screen 343 without saving the building history information input on the building questionnaire screen 344.

Returning to FIG. 10, when the user presses the mark 343f attached to any structure on the diagnosis main screen 343, the control unit 11 displays the diagnosis details screen 345 shown in FIG. 12 and registers the diagnostic image. A diagnostic image is obtained by accepting the image (step B3). That is, the control unit 11 acquires image data of a predetermined structure. Here, the control unit 11 functions as an acquisition unit.
The example shown in FIG. 12 is a case where the user selects an outer wall as the predetermined structure.
The user registers the selected structure by uploading the diagnostic image taken in the durability diagnosis step S2 on the diagnosis details screen 345.

Next, the control unit 11 uses the learned model 121 to detect an abnormality in the structure photographed in the diagnostic image 345a from the registered diagnostic image 345a (step B4). That is, the control unit 11 detects an abnormality based on the image data acquired by the acquisition unit. Here, the control section 11 functions as a detection section.
The example shown in FIG. 12 is a case where "cracking, lifting, and peeling of wet type (mortar) (large panel) exterior wall material" is detected as an abnormality in the structure. In this case, the control unit 11 displays the detection result of the abnormality detection in the item column 345b of "cracks, lifting, and peeling of wet type (mortar) (large panel) exterior wall material". Specifically, the control unit 11 causes the display area 345c to display the classification: Abnormality and matching rate. That is, the control unit 11 displays the detection result by the detection unit on the display unit 34. Here, the control section 11 functions as a display control section.

Next, the control unit 11 receives input of the level (degree) of the abnormality and comments from the user (step B5). That is, the control unit 11 receives an input of the degree of abnormality detected by the detection unit. Here, the control unit 11 functions as a reception unit.
The control unit 11 displays determination criteria 345d (information for determining the degree of abnormality) for determining the level of abnormality in the item column 345b for each level of abnormality. That is, the control unit 11 serving as a display control unit displays, in the item field 345b, the content of the degree of damage to the structure according to a plurality of levels (levels) as information for determining the level of abnormality.
The user refers to the detection results and determination criteria 345d of abnormality detection and selects the level of abnormality of the structure in the selection field 345e.
The user also inputs a comment regarding the abnormality of the structure in the input field 345f.

Further, when the sample input button 345i is pressed by the user, the control unit 11 causes the display area 345j to display one or more comment candidates or templates to be written in the input field 345f, as shown in FIG. 13. The control unit 11 then receives the user's selection of the comment candidate or template. When the user selects any of the comment candidates or templates, the control unit 11 displays the contents of the selected comment candidates or templates in the input field 345f.
This saves the user the trouble of manually entering comments.

In the example shown in FIG. 12, only "cracking, lifting, and peeling of wet type (mortar) (large panel) exterior wall material" was detected as an abnormality in the structure, but the present invention is not limited to this. From a single diagnostic image (for example, diagnostic image 345a), multiple types of abnormalities such as "cracks, lifting, and peeling of wet (mortar) (large panel) exterior wall material" and "damage to dry (siding) exterior wall material" can be detected. may be detected.

In addition, when the user presses the save button 345g on the diagnosis details screen 345, the control unit 11 saves the diagnostic image 345a acquired in step B3, the detection result of the abnormality detection in step B4, and the abnormality input received in step B5. The level and comment are saved in the diagnosis DB 122, and the screen returns to the diagnosis main screen 343.
Further, when the user presses the return button 345h of the diagnosis details screen 345, the control unit 11 returns the diagnosis main screen 343 without saving the diagnosis image 345a, the detection result of abnormality detection, the abnormality level, and the comment. return.

FIG. 14 shows an example of the diagnosis main screen 343 when the user presses the save button 345g on the diagnosis details screen 345.
In the example shown in FIG. 14, the control unit 11 displays, on the diagnosis main screen 343, the diagnostic image 345a acquired in step B3, the detection result of the abnormality detection in step B4, and the level and comment of the abnormality received as input in step B5. Display.
In the example shown in Figure 14, "cracks" are detected as an abnormality in the diagnostic image of the foundation, "rot and deformation due to leakage of sloped roof" are detected as abnormalities in the diagnostic image of the roof, and "wet (mortar)" is detected in the diagnostic image of the exterior wall. ) (Large panel) When cracks, lifting, or peeling of the exterior wall material is detected.

Further, when the user presses the mark 343g attached to "Special notes, consideration, conditions for re-warranty/warranty extension" on the diagnosis main screen 343, the control unit 11 displays the special notes details screen 346 shown in FIG. Display and accept input of special notes, considerations, and conditions for re-guarantee/warranty extension (step B6).
In the example shown in FIG. 15, the control unit 11 receives input of special notes or supplementary notes regarding building history information in the input field 346a.
Further, the control unit 11 receives input of the detection result of the abnormality detection and the consideration regarding determination of the abnormality level in the input field 346b.
Further, the control unit 11 accepts selection of conditions for re-guarantee/warranty extension in the selection field 346c.

In addition, when the user presses the save button 346d on the special notes details screen 346, the control unit 11 saves the input special notes, considerations, and re-warranty/warranty extension conditions in the diagnosis DB 122, and displays the diagnosis main screen. Return to 343.
Further, when the user presses the return button 346e on the special notes details screen 346, the control unit 11 displays the diagnosis main screen 346 without saving the input special notes, considerations, and conditions for re-assurance/warranty extension. Return to

Returning to FIG. 14, when the user presses the completion button 343j on the diagnosis main screen 343, the control unit 11 assumes that the durability diagnosis is completed. Then, the control unit 11 displays a report creation button 343k on the diagnosis main screen 343, as shown in FIG.
Note that the control unit 11 selects a durability diagnosis for which the diagnostic process has been completed by pressing the "Done" button 342e of any durability diagnosis on the diagnosis list screen 342 (FIG. 8) by the user. In this case, the screen transitions to a diagnosis main screen 343 on which a report creation button 343k as shown in FIG. 16 is displayed.

When the user presses the report creation button 343k on the diagnosis main screen 343, the control unit 11 creates and outputs the report 4 shown in FIGS. 17A and 17B (step B7).
The control unit 11 writes in the report 4 the detection result of the abnormality detection in step B4 of the diagnostic process and the level of the abnormality for which the input was received in step B5.
That is, the control unit 11 creates the report 4 based on the detection result by the detection unit and the degree of abnormality received by the reception unit. Here, the control section 11 functions as a report creation section.

In the example shown in FIGS. 17A and 17B, the control unit 11 records detected abnormalities for each structure to be diagnosed as an item (foundation, frame, roof, exterior wall, exterior equipment, bathroom, water supply and drainage equipment).
Further, the control unit 11 writes a black circle next to the level of abnormality for which the input has been received as a determination.
Further, the control unit 11 writes a determination criterion 345d shown in FIG. 12 as a determination criterion.

Note that the control unit 11 includes, as information regarding the durability diagnosis, information regarding the building that includes the predetermined structure to be diagnosed (owner information, building age, delivery date), the person in charge of the durability diagnosis, The implementation date, report creation date, etc. may also be stated.
Further, the control unit 11 may write in the report 4 the building history information inputted in step B2 of the diagnosis process.
Further, the control unit 11 may write in the report 4 the special notes, considerations, and conditions for re-guarantee/warranty extension that were input in step B6 of the diagnostic process.

Note that such a report 4 is created, for example, in a PDF format, but may also be created in a web page format or other formats.
Note that the control unit 11 may execute the report creation process in step B7 in a predetermined system outside the diagnostic application 321.
The control unit 11 then ends the diagnostic process.
Returning to FIG. 5, the durability diagnosis is completed.

[3. effect]
As described above, according to the present embodiment, the building structure diagnosis device 1 includes an acquisition unit (control unit 11) that acquires image data of a predetermined structure, and an image data acquired by the acquisition unit. a detection unit (control unit 11) that detects an abnormality based on the detection unit; a display control unit (control unit 11) that displays the detection result by the detection unit on the display unit 34; A reception unit (control unit 11) that receives the information is provided, and the display control unit displays information (judgment criteria 345d) for determining the degree on the display unit 34.
According to this, the user refers to an abnormality detected by the detection unit based on image data taken of a predetermined structure, and the building structure diagnosis device 1 detects an abnormality based on information for determining the degree of abnormality. It is possible to accept input of the degree of abnormality determined by the user.
Therefore, a more accurate degree of abnormality determined by the user can be accepted. Therefore, abnormalities in buildings and structures can be suitably diagnosed.

Further, in the building structure diagnosis device 1, the display control unit displays the details of the degree of damage to the structure according to the degree consisting of a plurality of stages, as information for determining the degree.
According to this, the user can judge the degree of abnormality by referring to the details of the degree of damage to the structure according to the degree consisting of a plurality of levels.
Therefore, the degree of abnormality can be easily determined.

Further, in the building structure diagnosis device 1, the reception section receives input of comments regarding the detection results by the detection section.
According to this, it is possible to receive comments from the user regarding the abnormality.
Therefore, it is possible to perform a more detailed diagnosis regarding the abnormality.

Further, in the building structure diagnosis device 1, the display control unit displays one or more templates for comments regarding the detection results by the detection unit on the display unit 34, and the reception unit receives template selection.
According to this, the user can select and input a comment regarding the detection result from the template.
Therefore, the user can save the trouble of manually inputting comments.

Furthermore, in the building structure diagnosis device 1, the detection unit detects multiple types of abnormalities based on one image data acquired by the acquisition unit.
According to this, multiple types of abnormalities can be detected without acquiring image data for each type of abnormality and performing abnormality detection for each type of abnormality.
Therefore, abnormalities can be detected efficiently.

Furthermore, the building structure diagnostic device 1 includes a learned model 121 that is subjected to machine learning using image data as input and information regarding an abnormality as output, and the detection unit uses the learned model 121 to detect an abnormality.
According to this, an abnormality can be detected using a trained model such as AI (Artificial Intelligence).
Therefore, abnormalities can be detected easily and accurately.

Furthermore, the building structure diagnosis device 1 includes a report creation section (control section 11) that creates a report 4 based on the detection result by the detection section and the degree of abnormality received by the reception section.
According to this, the detection result and the degree of abnormality can be automatically input into the report (by the control unit 11).
Therefore, reports can be created efficiently.

Note that the embodiments to which the present invention is applicable are not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of the present invention. For example, in the above embodiment, the building structure diagnosis system 100 includes the building structure diagnosis device 1 and the information management device 2, but the present invention is not limited to this. The information management device 2 may be omitted in the building structure diagnosis system 100, and instead, a building structure diagnosis device including a building database storing information regarding buildings may be provided.

100 Building structure diagnosis system 1 Building structure diagnosis device 11 Control unit (acquisition unit, detection unit, display control unit, reception unit, report creation unit)
12 Storage unit 121 Learned model 122 Diagnosis database 13 Communication unit 2 Information management device 21 Control unit 22 Storage unit 221 Building database 23 Communication unit 3 Terminal device 31 Control unit 32 Storage unit 321 Diagnosis application 33 Communication unit 34 Display unit 35 Operation unit 36 Imaging unit 4 report

Claims (6)

an acquisition unit that acquires image data of a predetermined structure;
a detection unit that detects an abnormality based on the image data acquired by the acquisition unit;
a display control unit that displays a detection result by the detection unit on a display unit;
a reception unit that receives an input of a user's determination result of the degree of abnormality detected by the detection unit;
a trained model that is subjected to machine learning using the image data as input and information regarding the abnormality as output;
Equipped with
The detection unit detects an abnormality using the learned model,
The display control unit displays, on the same screen displayed by the display unit, a criterion for determining the degree of damage to the structure according to the degree, which is comprised of a plurality of stages, as information for the user to judge the degree , and the predetermined information. A building structure diagnostic device that displays an image of a structure and a match rate between an abnormality included in the image data as the detection result and an abnormality machine-learned by the learned model. The building structure diagnostic device according to claim 1, wherein the reception unit accepts input of a comment regarding the detection result by the detection unit. The display control unit displays one or more templates for comments regarding the detection result by the detection unit on the display unit,
The building structure diagnosis device according to claim 1, wherein the reception unit accepts selection of the template. The building structure diagnostic device according to claim 1, wherein the detection unit detects a plurality of types of abnormalities based on one image data acquired by the acquisition unit. The building structure diagnosis device according to claim 1, further comprising a report creation unit that creates a report based on the detection result by the detection unit and the degree of abnormality received by the reception unit. The computer of the building structure diagnosis system is equipped with a trained model that is machine-learned by inputting image data taken of a predetermined structure and outputting abnormality information.
an acquisition unit that acquires the image data;
a detection unit that detects an abnormality based on the image data acquired by the acquisition unit;
a display control unit that displays the detection result by the detection unit on a display unit;
a reception unit that receives an input of a user's determination result of the degree of abnormality detected by the detection unit;
function as
The detection unit detects an abnormality using the learned model,
The display control unit displays, on the same screen displayed by the display unit, a criterion for determining the degree of damage to the structure according to the degree, which is comprised of a plurality of stages, as information for the user to judge the degree , and the predetermined information. A program for displaying an image of a structure, and a match rate between an anomaly included in the image data as the detection result and an anomaly machine-learned by the learned model.

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