Application program, application form creation system, application form creation method, application reporting program, application form report creation system, and application form report creation method

Abstract

The present invention aims to provide an application program that can easily and accurately create an application form having multiple application items. [Solution] The application program of the present invention is an application program for creating an application form having multiple application items, which causes a computer to execute a recognition function that causes the computer to recognize the multiple application items, an application signal acquisition function that causes the computer to acquire at least one application detection signal from at least one detection device, an application signal languageization function that causes the computer to language the at least one application detection signal as at least one application detection language, and an application language selection function that causes the computer to select a phrase corresponding to each of the multiple application items from the at least one application detection language.

Description

[Technical Field]

[0001] The present invention relates to an application program, an application form creation system, an application form creation method, an application report program, an application form and report creation system, and an application form and report creation method. [Background Art]

[0002] Patent Document 1 discloses an application document creation system that automatically creates application documents when an applicant inputs required unique information. This application document creation system comprises: (1) a first terminal for inputting procedure data related to an application from a medical corporation and outputting application documents; (2) a second terminal for inputting data of designated items from an administrative agency related to said application, updating with said changed data every time a change occurs, inputting management index data required by the administrative agency in relation to said application, and updating with said changed data every time a change occurs; and (3) an application document processing device installed in a data center, which accumulates, in a file storage unit, formats of application documents related to the application of said medical corporation, the data of said designated items and said management index data transmitted from said second terminal, reads the predetermined format of said application document, the data of said designated items and said management index data from said file storage unit based on said procedure data transmitted from said first terminal, and creates said application document by directly inputting said procedure data, the read data of said designated items and said management index data into predetermined fields of the read application document, or inputting data resulting from performing a predetermined calculation, accumulates the created said application document in said file storage unit, and transmits it to said first terminal; wherein said application document processing device is connected to said first terminal and said second terminal via a data communication line. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2007-141182 [Summary of the Invention] [Problems that the invention aims to solve]

[0004] As mentioned above, in the application document creation system of Patent Document 1, the user inputs procedural data related to the application using a first terminal. Specifically, the application items required for the application are entered by the user using a keyboard or the like, in other words, by manual input. Therefore, errors such as user input mistakes on the keyboard can easily lead to deficiencies in application documents.

[0005] One of the objectives of this invention is to provide an application program that can easily and accurately create an application form having multiple application items. [Means for solving the problem]

[0006] The application program of the first embodiment is An application program for creating an application form having multiple application items, using at least one application detection signal detected from at least one detection device, On the computer, A recognition function that recognizes the aforementioned multiple application items, An application signal acquisition function that causes at least one application detection signal to be acquired from at least one of the aforementioned detection devices, An application signal languageization function that converts the aforementioned at least one application detection signal into at least one application detection language, An application language selection function that allows the user to select the appropriate wording for each of the aforementioned multiple application items from at least one of the aforementioned application detection languages, Make it run. The application program of the second embodiment is: In the application program of the first embodiment, The aforementioned computer is connected via a communication network to the receiving computer of the application form. To the aforementioned computer, If, as a result of the application language selection function, there are no deficiencies in the application requirements for any of the multiple application items, the application form containing the multiple application items is sent to the receiving computer by the application form transmission function. To execute further. The application program of the third aspect is: In the application program of the second embodiment, To the aforementioned computer, If, as a result of the application language selection function, at least one of the multiple application items has a deficiency in the application requirements, the application deficiency notification function notifies the creator of the deficiency in the application item. An application signal reacquisition function that acquires at least one other application detection signal newly detected using the aforementioned at least one detection device, After running it further, The application signal reacquisition function acquires at least one other application detection signal, which is then included in the application detection signal, and the application signal languageization function and the application language selection function are executed again. The application program of the fourth aspect is: In the application program of the second embodiment, At least one detection device includes an imaging device that detects either still images or moving images, or both, and a recording device that records sound. The application program of the fifth aspect is: In the application program of the fourth aspect, To the aforementioned computer, In the application signal language conversion function, if there is a discrepancy between the application imaging detection language converted from the application detection signal detected by the imaging device and the application recording detection language converted from the application detection signal detected by the recording device, the application imaging detection language is given priority and the application language selection function is executed. One type of application form creation system is: At least one detection device, A computer storing the application program according to any one of the first to fifth aspects, comprising: the application program causes the computer to execute at least the recognition function, the application signal acquisition function, the application signal verbalization function, and the application language selection function. An application form creation method according to one aspect, is an application form creation method for creating an application form having a plurality of application items by using at least one or more application detection signals detected from at least one or more detection devices, the method comprising: a recognition step of causing a computer to recognize the plurality of application items; an application signal acquisition step of causing the computer to acquire the at least one or more detection signals from the at least one or more detection devices; an application signal verbalization step of causing the computer to verbalize the at least one or more application detection signals as at least one or more application detection languages; an application language selection step of causing the computer to select a word corresponding to each of the plurality of application items from the at least one or more application detection languages; comprising the above steps. An application reporting program according to the first aspect, is an application reporting program for creating an application form having a plurality of application items and a report for the application form by using at least one or more application detection signals and report detection signals detected from at least one or more detection devices, the program comprising: (1) the application program according to claim 4 or 5, (2) a reporting program for creating a report, causing a computer to execute: an extraction function of extracting a plurality of report items for creating a report for the application form from the application form in which the plurality of application items are filled; a report signal acquisition function of acquiring the at least one or more report detection signals from the at least one or more detection devices; a report signal verbalization function that causes said at least one or more reporting detection signals to be verbalized as at least one or more reporting detection languages; a report language selection function that causes a wording corresponding to each of said plurality of report items to be selected from said at least one or more reporting detection languages; that is executed by a reporting program, and comprises the above. The application reporting program according to the second aspect is, in the application reporting program according to the first aspect, causing said computer to a report transmission function that, when there is no deficiency in reporting requirements for all of said plurality of report items as a result of said report language selection function, causes a report in which the plurality of report items are entered to be transmitted to said receiving computer, further executing the above. The application reporting program according to the third aspect is, in the application reporting program according to the first aspect, causing said computer to a report deficiency notification function that, when at least one of said plurality of report items has a deficiency in reporting requirements as a result of said report language selection function, causes a creator to be notified of the deficient report item; a report signal reacquisition function that causes at least one or more other reporting detection signals newly detected using said at least one or more detection devices to be acquired; after further executing the above, said at least one or more other reporting detection signals acquired by said report signal reacquisition function are included in said at least one or more reporting detection signals, and said report signal verbalization function and said report language selection function are executed again. The application reporting program according to the fourth aspect is, in the application reporting program according to the third aspect, causing said computer to In the aforementioned reporting signal language conversion function, if there is a discrepancy between the reporting imaging detection language converted from the reporting detection signal detected by the imaging device and the reporting recording detection language converted from the reporting detection signal detected by the recording device, the reporting imaging detection language is given priority and the reporting language selection function is executed. One type of application report creation system is: At least one detection device, A computer on which one of the application reporting programs for any of the first to fourth aspects is stored, Equipped with, The application reporting program causes the computer to perform at least (1) the recognition function, the application signal acquisition function, the application signal languageization function and the application language selection function, and (2) the extraction function, the report signal acquisition function, the report signal languageization function and the report language selection function. One method for preparing an application report is: An application form and report preparation method that prepares an application form having multiple application items and a report for said application form using at least one application detection signal and a reporting detection signal detected from at least one detection device, A recognition step in which the computer recognizes the aforementioned multiple application items, The application signal acquisition step involves causing the computer to acquire at least one detection signal from at least one detection device, An application signal languageization step in which the computer languageizes the at least one application detection signal as at least one application detection language, An application language selection step in which the computer selects the wording corresponding to each of the multiple application items from the at least one application detection language, The extraction process involves causing the computer to extract multiple reporting items from an application form containing the multiple application items in order to create a report for that application form. A reporting signal acquisition step involves causing the computer to acquire at least one reporting detection signal from at least one of the detection devices, A reporting signal languageization step in which the computer languageizes the at least one reporting detection signal as at least one reporting detection language, A reporting language selection step in which the computer is instructed to select a word corresponding to each of the plurality of reporting items from the at least one reporting detection language, Includes. [Effects of the Invention]

[0007] By using the application programs of the first to fifth aspects, it is possible to easily and accurately create application forms with multiple application items. Using one embodiment of the application form creation system, it is possible to easily and accurately create application forms that have multiple application items. By using one method for preparing application forms, it is possible to easily and accurately prepare application forms that have multiple application items. By using the application reporting programs of the first to fourth aspects, it is possible to easily and accurately create application forms with multiple application items and the corresponding reports. By using one embodiment of the application and report creation system, it is possible to easily and accurately create application forms with multiple application items and corresponding reports. By using one method for preparing application forms and reports, it is possible to easily and accurately prepare application forms and corresponding reports that have multiple application items. [Brief explanation of the drawing]

[0008] [Figure 1] This is a schematic diagram of the application form and report creation system of this embodiment. [Figure 2] This is a flowchart of the application program for this embodiment. [Figure 3]This is a flowchart of the reporting program of this embodiment. [Figure 4A] This is a flowchart of the application program for the first modified example. [Figure 4B] This is a flowchart of the reporting program for the first modified example. [Figure 5A] This is a flowchart of the application program for the second modified example. [Figure 5B] This is a flowchart of the reporting program for the second modified example. [Modes for carrying out the invention]

[0009] ≪Overview≫ The following describes this embodiment, several modifications, and several examples in the order they are described. Note that in the descriptions of the subsequent examples, the names and reference numerals of the earlier embodiment will be used mutatis mutandis for constituent elements that are equivalent or nearly equivalent to those described in this embodiment.

[0010] This embodiment The application form report creation system CS of this embodiment will be described below with reference to Figures 1 to 3, divided into (1) configuration and function, (2) operation, and (3) effect, in the order described below.

[0011] <Functions and Configuration of the Application Form and Report Creation System of This Embodiment> The application and report creation system CS consists of the application and report creation system CS1 (see Figure 2) and the report creation system CS2 (see Figure 3). The application form creation system CS1 has the function of creating an application form AD (see Figure 1) having multiple application items, using the application detection signal S1 detected from the imaging device 20 (an example of a detection device), the recording device 30 (another example of a detection device), etc. In contrast, the report creation system CS2 has the function of creating a report RD (see Figure 1) for the application AD using the reporting detection signal S2 detected from the imaging device 20, recording device 30, etc. Based on the above, the application and report creation system CS possesses the functions of both the application and report creation system CS1 and the report creation system CS2.

[0012] The application form and report creation system CS, as shown in Figure 1, comprises a computer 10, an imaging device 20 (an example of a detection device), a recording device 30 (another example of a detection device), and a communication network NW (the Internet is one example). Furthermore, in the application form and report creation system CS, computer 10 is connected to the recipient computer 40 (an example of a receiving computer) via the communication network NW.

[0013] 〔computer〕 Computer 10 can be connected to the imaging device 20 and the recording device 30. In Figure 1, these connections are made via a communication network NW, but the connection method, such as priority connection or wireless connection, is not limited as long as information (application detection signal S1 and reporting detection signal S2) can be transferred from the imaging device 20 and the recording device 30. The computer 10 has a processing unit 12 (a CPU (Central Processing Unit) is one example) and a storage unit 14 (a RAM (Random Access Memory) is one example). The processing unit 12 reads the data stored in the storage unit 14 and performs calculations. This data includes, as an example, an application AP. The application AP consists of an application report program PG, a data file DF, and various libraries LB. The application reporting program PG includes application program PG1 (see Figure 2) and reporting program PG2 (see Figure 3). The data file DF includes, for example, (1) information transferred from the imaging device 20 and the recording device 30 (application detection signal S1 and reporting detection signal S2), and (2) data for multiple types of application forms AD. The specific details of the application and reporting program (PG) will be described later.

[0014] [Imaging device and recording device] The imaging device 20 has the function of detecting (capturing) either still images or moving images, or both. The imaging device 20 is used by the applicant (or their representative) to capture images (for example, images of the repaired area) necessary for creating the application form AD and the report RD. In contrast, the recording device 30 has the function of recording sound. The recording device 30 is used to record conversations (interviews) between the applicant and their representative when preparing the application form AD and the report RD. The data recorded (detected) by the imaging device 20 and the recording device 30 is transmitted to the computer 10 as an application detection signal S1 (data recorded when creating application form AD) or a report detection signal S2 (data recorded when creating report RD), and is stored as synchronized data in the data file DF of the storage unit 14. In this embodiment, the imaging device 20 and the recording device 30, which are examples of detection devices, are each represented as separate hardware. However, they may be composed of a single hardware component if both functions can be realized.

[0015] [Application Reporting Program] The application and reporting programs PG (Application Program PG1 and Reporting Program PG2) have the function of causing the computer 10 to perform the following multiple functions in order to (1) create an application form AD having multiple application items, and (2) create a report RD for the application form AD, which also has multiple reporting items. Each function works in conjunction with the others to exert an organic technical significance as a whole. For more information on this point, please refer to the explanation of the operation of the application and reporting system CS described later. The following describes several functions of the application reporting program (PG).

[0016] (Recognition function) The recognition function allows computer 10 to recognize multiple application items in application form AD.

[0017] (Application signal acquisition function) The application signal acquisition function is a function that causes the computer 10 to acquire the application detection signal S1 from the imaging device 20 and / or the recording device 30.

[0018] (Application signal verbalization function) The application signal language conversion function causes the computer 10 to convert the application detection signal S1 into at least one application detection language. In other words, the application signal language conversion function converts the application detection signal S1, which is an image or sound signal, into language. This conversion is performed, for example, by large-scale language processing using a large-scale language model. This model may be stored as part of the application reporting program PG, or it may be made operational by the application reporting program PG via an external server (not shown) through a communication network NW.

[0019] (Application language selection function) The application language selection function allows computer 10 to select the appropriate wording for each of the multiple application items from the application detection languages.

[0020] (Application form submission function) The application form submission function causes computer 10 to send application form AD, with all application fields filled in, to the receiving computer 40, provided that all application fields are filled in correctly as a result of the application language selection function.

[0021] (Application omission notification function (Application deficiency notification function)) The application omission notification function is a function that causes the computer 10 to notify the user, such as the creator (applicant), of the application item with deficiencies in the application requirements (e.g., missing information) as a result of the application language selection function. The method of notification may be, for example, by displaying a message on the computer 10's display (not shown). Here, to determine whether or not there are any deficiencies in the application requirements, for example, computer 10 may be made to obtain information such as the application conditions from the website of the application destination via a communication network NW and make a judgment based on that information, or it may be made to make a judgment based on the information at the time of application of a similar application form AD in the past.

[0022] (Application signal reacquisition function) The application signal reacquisition function is a function that causes the computer 10 to acquire a newly detected application detection signal S1 using the imaging device 20 and / or recording device 30.

[0023] (Extraction function) The extraction function causes computer 10 to extract multiple reporting items from application form AD, which contains multiple application items, in order to create a report RD for that application form AD. This extraction is performed, for example, by large-scale language processing using a large-scale language model.

[0024] (Report signal acquisition function) The reporting signal acquisition function is a function that causes the computer 10 to acquire a detection signal S2 for reporting from the imaging device 20 and / or the recording device 30. This extraction is performed, for example, by large-scale language processing using a large-scale language model.

[0025] (Report signal language conversion function) The reporting signal language conversion function causes the computer 10 to convert the reporting detection signal S2 into at least one reporting detection language. In other words, the reporting signal language conversion function converts the reporting detection signal S2, which is an image or sound signal, into language. This conversion is performed, for example, by large-scale language processing using a large-scale language model, similar to the application signal language conversion function described above.

[0026] (Reporting language selection function) The reporting language selection function allows computer 10 to select the appropriate wording for each of the multiple reporting items from the reporting detection languages.

[0027] (Report submission function) The report submission function causes computer 10 to send a report RD with all report items filled in to the recipient computer 40, provided that all report items are filled in as a result of the application language selection function.

[0028] (Reporting omission notification function (Reporting deficiency notification function)) The reporting omission notification function is a function that allows the computer 10 to notify the user, such as the creator (applicant (reporter)), of the reporting item with deficiencies in reporting requirements (e.g., missing information) as a result of the reporting language selection function. The notification method may be, for example, by displaying a message on the computer 10's display (not shown). In determining whether or not there are deficiencies in the reporting requirements, for example, computer 10 may be made to obtain information such as reporting conditions from the website of the application recipient (reporting recipient) via the communication network NW and make a judgment based on that information, or it may be made to make a judgment based on the information provided at the time of reporting of a similar report RD in the past.

[0029] (Report signal reacquisition function) The report signal reacquisition function is a function that causes the computer 10 to acquire a newly detected report signal S2 using the imaging device 20 and / or recording device 30.

[0030] The above describes the functions and configuration of the application report creation system CS of this embodiment.

[0031] <Operation of the application form and report creation system of this embodiment> Next, we will explain the operation of the application and report creation system CS. First, we will explain the application creation operation flow S10 (see Figure 2) by the application and report creation system CS, and then we will explain the report creation operation flow S20 (see Figure 3) by the application and report creation system CS. Here, in the application form creation operation flow S10 and report creation operation flow S20 described later, the term "process" will not be used in particular, but please note that the terms such as recognition function, application signal acquisition function, application signal languageization function, application language selection function, extraction function, report signal acquisition function, report signal languageization function, and report language selection function can be interpreted by replacing the "function" part with "process".

[0032] [Application Form Creation Flowchart S10] The application form creation operation flow S10 corresponds to the flow resulting from the execution of the application program PG1.

[0033] (S11) First, in S11, the computer 10 identifies the application target and recognizes (or understands) the multiple application items contained in application form AD. Specifically, the computer 10 is operated by the user to select application form AD from the storage unit 14. Then, the application program PG1 causes the computer 10 to perform the recognition function. As a result, the computer 10 recognizes the multiple application items contained in application form AD.

[0034] (S12) Next, in S12, the computer 10 acquires the application detection signal S1 and then translates the application detection signal S1 into language. Specifically, the user connects the imaging device 20 and the recording device 30 to the computer 10, and the application detection signals S1 recorded on each are transferred to the storage unit 14 and stored synchronously. In other words, the application program PG1 causes the computer 10 to execute the application signal acquisition function. Furthermore, the application detection signal S1 stored in the memory unit 14 by the application signal acquisition function is converted into an application detection language by the application signal language conversion function. As a result, the application detection signal S1, which is the image signal detected by the imaging device 20 and the sound signal detected by the recording device 30, is converted into language as synchronized information. Specifically, the image signal detected by the imaging device 20 is converted into language, for example, geometric information such as the volume of space, and the sound signal detected by the recording device 30 is converted into language, which is information about the status of the object to be applied for (defect status, current problems, etc.). In this embodiment, S12 is executed after S11 (see Figure 2), but S11 may be executed after S12, or they may be executed simultaneously or almost simultaneously.

[0035] (S13) Next, in S13, the computer 10 selects (fills in) the appropriate wording (in other words, the required appropriate wording) for each of the multiple application items of application form AD recognized in S11 from the application detection language language that was verbalized in S12, and fills in the appropriate wording for the multiple application items. In other words, the application program PG1 causes the computer 10 to execute the application language selection function. As a result, in S13, a draft application form is created. Furthermore, if any of the application items in application form AD require the attachment of photographs or other images, the computer 10 may use the image signal detected by the imaging device 20 directly (without verbalizing it). Furthermore, when filling in the appropriate wording (or, in other words, the required appropriate wording) for each of the multiple application items in application form AD, for example, in S12 (application signal languageization function), if there is a discrepancy between the application imaging detection language language that is languageized from the application detection signal S1 detected by the imaging device 20 and the application recording detection language that is languageized from the application detection signal S1 detected by the recording device 30, the computer 10 should prioritize the application imaging detection language and execute the application language selection function.

[0036] (S14, S15 and S16) Next, in S14, it is determined whether the draft application prepared in S13 has any deficiencies in meeting the application requirements (i.e., whether there are any missing fields). If the result (the result of executing the application language selection function) is negative (No in S14), that is, if there are no missing entries, the application program PG1 instructs the computer 10 to consider the application form AD, which has multiple application items filled in, as a formal application form AD and send it to the receiving computer 40 (see S15). In other words, the application program PG1 instructs the computer 10 to execute the application form transmission function. The computer 10 then receives an acknowledgment AK from the receiving computer 40 to indicate that it has received the application form AD. The application form creation operation flow S10 then ends. In contrast, if the result of executing the application language selection function is an affirmative judgment (Yes in S14), that is, if there are missing entries, the application program PG1 causes the computer 10 to display a message to that effect (that there are missing entries) on its display (not shown in the illustration) to notify the user, such as the creator (applicant) (see S16). In other words, the application program PG1 causes the computer 10 to execute the application omission notification function (declaration deficiency notification function). In the previous explanation, it was stated that if the result of executing the application language selection function is negative (No in S14), the application AD is sent to the application destination computer 40 (see S15). However, instead of executing S15 immediately after No in S14, the application AD may be displayed on the computer 10's display (not shown) or the like for the user to review. If the user reviews the application and finds that corrections are necessary, the application AD may be corrected by providing specific correction instructions for the necessary parts via the computer 10's user interface (not shown), and then S15 may be executed. Alternatively, if the user reviews the application and finds that corrections are necessary, the process may proceed to S17, which will be described later.

[0037] (S17) If the execution of S14 as described above results in a positive judgment, and after the execution of the application omission notification function in S16, S17 is executed. In S17, the application program PG1, upon obtaining a newly detected application detection signal S1 (an example of another application detection signal) using the imaging device 20 and / or recording device 30 by the computer 10 (application signal reacquisition function), executes the flow from S12 again. Here, S12 (Application Signal Language Conversion Function) and S13 (Application Language Selection Function) are executed again by incorporating the newly detected application detection signal S1 acquired in S17 (Application Signal Reacquisition Function) into the application detection signal S1 that was verbalized in the previous S12 (Application Signal Language Conversion Function). Subsequently, if the result of executing S14 is negative, that is, if there are no omissions in filling out any application items, the application creation operation flow S10 ends after proceeding to S15.

[0038] [Report creation workflow S20] Next, the report creation operation flow S20 will be explained with reference to Figure 3. The report creation operation flow S20 corresponds to the flow resulting from the execution of the reporting program PG2.

[0039] (S21) First, in S21, the computer 10 reads the submitted application AD, which was created in the aforementioned application creation operation flow S10, from the storage unit 14.

[0040] (S22) Next, in S22, the computer 10 extracts several reporting items from the application form AD read in S21 to create a report RD for the application form AD. In other words, the reporting program PG2 causes the computer 10 to perform the extraction function.

[0041] (S23) Next, in S23, the computer 10 acquires the reporting detection signal S2 and then verbalizes the reporting detection signal S2. Specifically, the user connects the imaging device 20 and the recording device 30 to the computer 10, and the detection signals S2 for reporting recorded on each are transferred to the storage unit 14 and stored synchronously. In other words, the reporting program PG2 causes the computer 10 to execute the reporting signal acquisition function. Furthermore, the reporting detection signals S2 stored in the memory unit 14 by the reporting signal acquisition function are converted into a reporting detection language by the reporting signal language conversion function. As a result, the reporting detection signals S2, which are the image signals detected by the imaging device 20 and the sound signals detected by the recording device 30, are converted into language as synchronized information. Specifically, the image signals detected by the imaging device 20 are converted into language for geometric information such as the volume of the requested space, and the sound signals detected by the recording device 30 are converted into language for status information of the requested object (status of improvement of defects, current improvement points, etc.). In this embodiment, S22 and S23 are executed in the order they are described (see Figure 3), but their execution order can be reversed, simultaneous, or nearly simultaneous.

[0042] (S24) Next, in S24, the computer 10 selects (fills in) the appropriate wording (in other words, the required appropriate wording) for each of the multiple application items of application form AD recognized in S22 from the reporting detection language language that was verbalized in S23, and fills in the appropriate wording for the multiple reporting items. In other words, the reporting program PG2 causes the computer 10 to execute the reporting language selection function. As a result, a draft report is created in S24. Furthermore, if any of the reporting items in the report RD require the attachment of photographs or other images, the computer 10 may use the image signals detected by the imaging device 20 directly (without verbalizing them). Furthermore, when filling in the appropriate wording (or, in other words, the required appropriate wording) for each of the multiple reporting items in the report RD, for example, in S23 (report signal language function), if there is a discrepancy between the reporting imaging detection language language languageed from the reporting detection signal S2 detected by the imaging device 20 and the reporting recording detection language language language languageed from the reporting detection signal S2 detected by the recording device 30, the computer 10 should prioritize the reporting imaging detection language and execute the reporting language selection function.

[0043] (S25, S26, and S27) Next, in S25, it is determined whether the draft report prepared in S24 has any deficiencies in meeting the reporting requirements (i.e., whether there are any missing items). If the result (the result of executing the reporting language selection function) is negative (No in S25), that is, if there are no missing entries, the reporting program PG2 instructs computer 10 to consider the report RD with multiple reporting items filled in as a formal report RD and send it to the recipient computer 40 (see S26). In other words, the reporting program PG2 instructs computer 10 to execute the report sending function. Then, computer 10 receives an acknowledgment AK from the recipient computer 40 to indicate that it has received the report RD. The report creation operation flow S20 then ends. In contrast, if the result of executing the reporting language selection function is an affirmative judgment (Yes in S25), that is, if there are missing entries, the reporting program PG2 causes the computer 10 to display a message to that effect (that there are missing entries) on its display (not shown in the diagram) to inform the creator (applicant) or other user (see S27). In other words, the reporting program PG2 causes the computer 10 to execute the reporting omission notification function (reporting deficiency notification function). In the explanation above, if the result of executing the reporting language selection function is a negative judgment (No in S25), the report RD is sent to the application computer 40 (see S26). However, instead of executing S26 immediately after No in S25, the report RD may be displayed on the computer 10's display (not shown) or the like for the user to review. If the user reviews the report RD and corrections are necessary, the user may, for example, provide specific correction instructions for the necessary corrections via the computer 10's user interface (not shown) to correct the report RD before executing S26. Alternatively, if the user reviews the report RD and corrections are necessary, the process may proceed to S28, which will be described later.

[0044] (S28) If the execution of S25 as described above results in a positive judgment, and after the execution of the reporting omission notification function in S27, S28 is executed. In S28, the reporting program PG2, upon obtaining a newly detected reporting detection signal S2 (an example of another reporting detection signal) detected by the computer 10 using the imaging device 20 and / or recording device 30 (report signal reacquisition function), causes the flow from S23 to be executed again. Here, S23 (report signal language conversion function) and S24 (report language selection function) are executed again by incorporating the newly detected report detection signal S1 acquired in S28 (report signal reacquisition function) into the report detection signal S2 that was languaged in the previous S23 (report signal language conversion function). Subsequently, if the result of execution S25 is a negative judgment, that is, if there are no omissions in filling in any of the reporting items, the report creation operation flow S20 is completed after proceeding to S26.

[0045] The above describes the operation of the application form and report creation system CS of this embodiment.

[0046] <Effects of this embodiment> Next, the effects of this embodiment will be described. By using the application program PG1 of this embodiment, an application form AD with multiple application items can be easily and accurately created without or with minimal use of manual input such as a keyboard. Accordingly, by using the application form creation system CS1 of this embodiment, an application form AD with multiple application items can be easily and accurately created without or with minimal use of manual input such as a keyboard. Furthermore, by using the application form creation method of this embodiment, an application form AD with multiple application items can be easily and accurately created. Furthermore, by using the reporting program PG2 of this embodiment, a report RD with multiple reporting items can be easily and accurately created without or with minimal use of manual input such as a keyboard. Accordingly, by using the report creation system CS2 of this embodiment, a report RD with multiple reporting items can be easily and accurately created without or with minimal use of manual input such as a keyboard. Moreover, by using the report creation method of this embodiment, a report RD with multiple reporting items can be easily and accurately created. Furthermore, by using the application reporting program PG of this embodiment, an application form AD having multiple application items and a corresponding report RD can be easily and accurately created. Accordingly, by using the application and report creation system CS of this embodiment, an application form AD having multiple application items and a corresponding report RD can be easily and accurately created. Furthermore, by using the application and report creation method of this embodiment, an application form AD having multiple application items and a corresponding report RD can be easily and accurately created.

[0047] The above describes the effects of this embodiment. The above also describes this embodiment.

[0048] ≪Multiple Variations≫ Next, we will describe several variations.

[0049] <First variation> The combination of Figure 4A and Figure 4B is a flowchart of the application reporting program for the application report creation system CSa of the first modified example. Specifically, Figure 4A shows the operation flow S10a of application creation by the application program PG1a of the application creation system CS1a. Figure 4B shows the operation flow S20a of report creation by the reporting program PG2a of the report creation system CS2a. The following description will only cover the differences between the first modified example and this embodiment (Figures 1 to 3).

[0050] In the application form creation operation flow S10a of the first modified example, S14, S16, and S17 of this embodiment are changed to S14a, S16a, and S17a, respectively. In S14a, it is determined whether the draft application created after the execution of S13 has any deficiencies in the application requirements. If the judgment in S14a is negative, the process proceeds to S15 (submit as application AD); if the judgment is positive, the process proceeds to S16a. In S16a, application items that have deficiencies in the application requirements are reported (for example, displayed on the computer 10's screen). Next, in S17a, correction information is re-obtained using a method similar to that of S17 to correct any deficiencies in the application requirements.

[0051] Furthermore, in the report creation operation flow S10a of the first modified example, S25, S27, and S28 of this embodiment are changed to S25a, S27a, and S28a, respectively. In S25a, it is determined whether the draft report created after the execution of S24 has any deficiencies in the reporting requirements. If the judgment in S25a is negative, the process proceeds to S26 (submit as report RD); if the judgment is positive, the process proceeds to S27a. In S27a, any reporting items that are incomplete in meeting the reporting requirements are reported (for example, displayed on the computer 10's screen). Next, in S28a, corrective information is re-obtained in a manner similar to S28 to correct any deficiencies in the reporting requirements.

[0052] The effect of the first modified example is basically the same as that of this embodiment. However, the first modified example is superior in that the judgment step S14a (see Figure 4A) performed after S13 and the judgment step S25a performed after S24 allow for the detection of deficiencies in the draft application or report over a wider range than in this embodiment.

[0053] <Second variation> Next, we will explain the second modified example with reference to Figures 5A and 5B. The combination of Figure 5A and Figure 5B is a flowchart of the application reporting program for the application report creation system CSb of the second modified example. Specifically, Figure 5A shows the application creation operation flow S10b by the application program PG1b of the application creation system CS1b. Figure 5B shows the report creation operation flow S20b by the report program PG2b of the report creation system CS2b. The following description will only cover the differences between the second modified example and this embodiment (Figures 1 to 3).

[0054] In the application form creation operation flow S10b of the second modified example, the steps from after S13 to S15 in this embodiment have been changed. First, in the application creation operation flow S10b, S19b is executed after S13. In S19b, the draft application created in S13 is displayed on the computer 10's display, etc. The applicant (user) is then given the opportunity to check the contents of the draft application by looking at the display. As a result, for example, if the applicant determines that there are no problems (no deficiencies) in the draft application, the applicant can choose to send the draft application as the official application AD to the recipient via the user interface (Yes in S14b). If sending is selected in S14b, that is, if the judgment in S14b is positive, the process proceeds to S15. In contrast, if the applicant determines that there are problems (deficiencies) in the draft application, the applicant can choose not to submit the draft application to the recipient via the user interface (No in S14b). If No is selected in S14b, the process proceeds to S17b. In S17b, the applicant is given the opportunity to revise the draft application via the user interface. Once the revisions are complete, the process proceeds back to S14b.

[0055] Furthermore, in the report creation operation flow S20b of the second modified example, the steps from after S24 to S26 in this embodiment have been changed. First, in the report creation operation flow S20b, S29b is executed after S24. In S29b, the draft report created in S24 is displayed on the computer 10's display, etc. The reporter (user) is then given the opportunity to review (check) the contents of the draft report by looking at the display. As a result, for example, if the reporter determines that there are no problems (no deficiencies) in the draft report, the reporter can choose to send the draft report as an official report RD to the reporting destination (application destination) via the user interface (Yes in S24b). If sending is selected in S24b, that is, if the judgment in S24b is positive, the process proceeds to S26. In response to this, if the reporter determines that there are problems (deficiencies) in the draft report, the reporter can choose not to send the draft report to the recipient (application recipient) via the user interface (No in S24b). If No is selected in S24b, the process proceeds to S28b. In S28b, the reporter is given the opportunity to revise the draft report via the user interface. Once the revisions are complete, the process proceeds back to S24b.

[0056] The effects of the second modified example are basically the same as those of the first modified example.

[0057] Multiple Examples Several embodiments are described below. These are practical examples that further elaborate on the embodiments described above.

[0058] <Summary of Multiple Examples> Multiple examples relate to a system that automatically generates application documents for submission to government agencies and various organizations, and centrally manages everything from the submission process to managing deficiency corrections and creating performance reports. In particular, it belongs to the technology field of efficiently documenting the results of on-site surveys using sensors such as cameras, voice input devices, and LiDAR. Administrative procedures, subsidy applications, and obtaining various permits and licenses require the creation and verification of a vast amount of documentation. Traditionally, in many cases, the person in charge would survey the site, take photographs, and create drawings manually before compiling the documents. However, this process is prone to human error and carries the risk of resubmission due to deficiencies or exceeding deadlines. Furthermore, for subsidies related to CO2 reduction and energy conservation, even after actually installing equipment, complex comparative data must be created to demonstrate consistency with the submitted documents. Furthermore, while the online processing of administrative procedures has progressed in recent years and the number of electronic application portals has increased, the creation of the documents themselves still largely relies on manual text input and document verification. In particular, attempts to automatically analyze on-site information and generate necessary documents using sensor technology or AI technology are limited. The following examples each aim to provide a system that reduces the complexity of such document creation and contributes to deterring fraud and reducing errors.

[0059] Multiple implementations demonstrate a system that comprehensively supports the entire application process, from generating application documents and managing deficiencies to submission and performance reporting. By combining automatic spatial information acquisition using 360-degree cameras and LiDAR, text conversion via voice input, and AI-powered natural language processing, the system significantly reduces the human burden associated with document creation. Furthermore, it features a variety of functions, such as deterring fraud by attaching timestamps and geotags to recorded data, and presenting the optimal application plan by centrally matching multiple subsidy requirements.

[0060] <Basic configuration of multiple embodiments> The hardware of the multiple embodiments consists of, for example, (1) a sensor unit, (2) a generation unit, (3) a deficiency management unit, (4) a document creation unit, (5) a database, (6) a user interface, (7) an electronic application linkage unit, etc. The sensor unit (corresponding to the detection device in the embodiment) integrates, for example, a 360-degree camera, LiDAR, and a voice microphone to acquire spatial data and conversational data from the site. The generation means (corresponding to computer 10 in the embodiment) performs AI analysis on the data obtained from the sensor and creates a draft of the application documents. The deficiency management means (corresponding to computer 10 in the embodiment) compares the draft created by the generation means with multiple application requirements and detects and points out any deficiencies. The document creation means (corresponding to computer 10 in the embodiment) completes the document according to the final format after any deficiencies have been resolved. The database (corresponding to the storage unit 14 in the embodiment) stores information on the requirements for various subsidies and permits, entered document data, and photographic records. The user interface (corresponding to the display (not shown) in the embodiment) is a screen that displays error notifications and suggestions, and allows the user to input or modify additional information. The Electronic Application Integration Unit (corresponding to computer 10 in the embodiment) performs automatic transmission and status updates according to the administrative portal and designated submission methods.

[0061] <Example 1> This embodiment assumes a scenario where a restaurant applies for a sanitation permit from the prefectural government or a permit from the public health center. It provides a system that measures the restaurant's kitchen equipment and ventilation system using a 360-degree camera and a CO2 sensor (gas sensor), and automatically reflects the results in the application form. First, the applicant launches the system's user interface and clicks the "New Application" button. The system then prompts the applicant to input or automatically retrieve store details (area, number of seats, business hours, etc.). At this time, a 360-degree camera is used to capture photos and videos of the store's interior and exterior, and if a LiDAR sensor is installed, it maps the locations of walls, countertops, and customer seating to generate store layout information. Furthermore, real-time measurements from gas sensors are also acquired, providing initial data on ventilation conditions. Next, the system transmits this sensor information to the AI ​​analysis unit. The AI ​​analysis unit detects the installation locations of kitchen and handwashing equipment from the camera images and applies algorithms that estimate values ​​obtained from gas sensors and the ventilation rate inside the store to calculate how well it meets the standards required by the public health center (e.g., the required ventilation rate per hour and the size of the ventilation equipment). The AI ​​displays an interface that prompts the user to input additional information (e.g., the material of the cooking counter, the performance of the washing equipment) as needed. When a user enters additional information, the system automatically generates a draft of the hygiene permit application. This draft includes not only basic information such as the store name, address, and representative's name, but also a "kitchen equipment list," "ventilation equipment specifications," and "estimated ventilation capacity based on gas sensor measurement data," all arranged in a prescribed format. The health department guidelines have detailed requirements, such as kitchen walls being made of cleanable materials and whether the doors are sliding doors. The AI ​​analysis unit checks whether these requirements are met using camera footage, and if there are any deficiencies, it notifies the user through a deficiency management system. Furthermore, the deficiency management system detects not only physical equipment requirements but also operational management requirements. If copies of the hygiene manager's qualification certificate or staff health check results are required, a checklist will automatically appear asking whether or not to upload those documents. If the user has not uploaded the "staff health check results," specific instructions such as "Not uploaded" and "X more results needed" will be displayed. Once all deficiencies are resolved, the application form is complete, and a final preview can be viewed on the user interface. If electronic signatures or seals are required at this stage, the system will link with the electronic application portal and submit the application after conforming to the file format and electronic signature method specified by the public health center. After submission, if the public health center notifies the user of any deficiencies, the system will notify the user again, and any additional documents or corrections can be reflected in the management screen. The above process significantly streamlines document creation and verification, which were previously done manually and on paper, and has the advantage of enabling earlier approval by preventing users from submitting incomplete documents. In addition, since measurement records from gas sensors and other sources are kept, the possibility of fraud is also reduced.

[0062] <Example 2> This embodiment demonstrates a method for automatically generating application documents by combining LiDAR-based scanning of building equipment, analysis of air conditioner model numbers, and voice interviews, assuming a scenario where a small or medium-sized enterprise applies for energy-saving renovation subsidies. Applicants will use this system to develop an energy-saving renovation plan for their building while consulting online with a subsidy specialist. First, they will carry a device equipped with a LiDAR scanner (an example of an imaging device) and scan the walls, ceilings, and installed equipment on each floor of the building. From the LiDAR data, accurate floor plans and elevations of the building are automatically generated, and the location, number, and model number of air conditioning equipment (air conditioners) are identified. The air conditioner model number is acquired using image recognition or OCR functionality, and information such as "This air conditioner has been in use for 10 years" and "This room has poor cooling efficiency in the summer" is added as text data through voice interviews (application signal language conversion function). The AI ​​module of the generation method comprehensively analyzes this information and calculates a "list of equipment that should be replaced" and "expected energy saving effects." Specifically, it integrates the year of manufacture of the air conditioner, the manufacturer's power consumption reference value, and room volume data obtained from LiDAR, and quantifies and displays the amount of CO2 reduction that would occur if a new air conditioner were installed. Next, the system cross-references multiple subsidy databases and visualizes information such as a 1 / 2 subsidy rate for national program A and a 2 / 3 subsidy rate for prefectural program B. Furthermore, it lists the required documents for each program (e.g., building registration certificate, utility bill receipts from the previous year), and the deficiency management system displays errors indicating "what is missing." Users can supplement the information by uploading missing documents, rescanning, or conducting additional interviews. The completed "Energy-Saving Renovation Subsidy Application Form" includes building plans, a summary of the construction plan, a list of equipment replacements, estimated energy-saving effects, and a budget plan that meets the subsidy rate. After reviewing the final preview, the user can upload the entire document to the relevant local government or national electronic application site by clicking the "Submit" button. After submission, a review is conducted, and if the official in charge has any further inquiries during the document review, this system will automatically notify the user and summarize any deficiencies or questions in an easy-to-understand manner. If the subsidy is approved, this system will also handle the preparation phase of the performance report. After the renovation work is completed, LiDAR scans and photographs will be taken again to visualize the differences before and after construction, and the "equipment installed" and "measurement results of energy-saving effects" will be automatically recorded in the performance report. This will significantly reduce the administrative burden when creating the report and also speed up the process until the subsidy is approved.

[0063] <Example 3> This embodiment is an approach to almost automatically create application forms for subsidy applications related to store renovations by combining interior and exterior photography using a 360-degree camera with audio interviews. When a store owner activates this system, they first select their intention to "apply for a store renovation subsidy" and enter basic information such as location and business type. Next, they use a mobile device equipped with a 360-degree camera to walk around the store and take pictures. During this process, data is obtained that visualizes the location of ceilings, floors, walls, entrances, lighting, and piping. The camera generates a panoramic image of the store in real time, and the system classifies objects using a spatial recognition algorithm. At the same time, the owner explains via voice, "I want to renovate this area and create a bar counter," or "I want to change the layout of the kitchen." This voice information is automatically converted into text and generated as a list of renovation requests. The AI ​​used for generation identifies the requested areas within the 360-degree video and categorizes them as "removal of existing equipment" or "content of new installations." These results are compiled into a "renovation plan draft," which simultaneously presents structural considerations and cost estimates. Next, the deficiency management system refers to the renovation subsidy requirements of the municipality where the store is located, and lists the eligible construction items, maximum amounts, and required documents. For example, it displays information on relevant permits, such as, "In addition to exterior renovations, interior seating area renovations are also permitted, but in that case, prior permission from the fire department is required." The user uploads fire department-related documents and renovation contractor estimates according to the displayed checklist. If there are any further deficiencies, errors such as "Estimate lacks details" or "Construction period is vague" are output. After any deficiencies are resolved, the system automatically creates a final application form integrating "renovation details and costs, scope of subsidy eligibility, subsidy application amount, and store information," and generates a PDF or electronic application data with a formatted layout and tables. Users can digitally sign the required sections and submit the application, and the review results can be tracked within the system after submission. If additional questions arise during the review process, such as "Is there any discrepancy in the planned renovation area?", the system will re-examine the 360-degree camera footage and LiDAR information, make corrections as necessary, and resubmit the application. After the renovation is complete, the system automatically generates "before and after" photos and videos of the store interior. Because documents proving the reasonableness of the expenses are created based on the area and design changes of the renovated sections, it has the advantage of ensuring a smooth final subsidy payment. This significantly reduces the need to separately organize photos, attach them to documents, and write individual descriptions, making it an efficient system for both store owners and local governments.

[0064] <Example 4> This example illustrates a system operation for the introduction of agricultural greenhouses and applications for subsidies. It utilizes LiDAR measurements at the planned greenhouse site and environmental sensors (temperature, humidity, CO2, etc.) to create application documents and performance reports in a coordinated manner. When farmers introduce new greenhouses to increase yields, they sometimes apply for agricultural and fisheries subsidies. In this case, they need to describe in detail the size of the greenhouse, the land area, the amount of equipment investment, and the CO2 emission reduction effect in the application form. This system first measures the farmland where the greenhouse is planned to be installed using a LiDAR scanner, and grasps the slope and area of ​​the land, as well as the distance to surrounding structures, in three dimensions. During measurement, users also use voice input to verbally explain information such as "The greenhouse is planned to be 10m wide x 50m long" and "We plan to install a ventilation system." The system analyzes this and combines it with on-site data to generate a draft of the necessary documents. The subsidy requirements for the agricultural sector include "a planned area of ​​1,000m²." 2 The requirements include a wide range of conditions, such as "if it exceeds a certain limit," "if a specific environmental control device is installed," and "attaching a rainwater drainage plan is mandatory." This system compares these requirements registered in the database and alerts the user if any items are not met. Next, temperature, humidity, and CO2 sensors are temporarily installed at the planned locations to collect data experimentally. This data will be reflected in the subsidy application as supporting evidence for the "Plan for Introducing Energy-Saving Equipment to Optimize the Crop Growth Environment." For example, the plan section of the application will detail things like considering double covering in areas with large temperature differences, or anticipating increased yields through CO2 concentration management. The AI ​​analysis unit will automatically generate a logically consistent plan document by comparing it with past cases and literature data. The deficiency management system accurately points out issues such as "missing drainage plan drawings" and "incomplete details of the soil improvement plan." Users can then upload the contractor's estimate and drainage plan drawings, at which point the deficiency indication disappears and the application is completed. The completed document clearly states the implementation cost, self-funded amount, estimated subsidy amount, and expected effects. The electronic application linkage function automatically sends the document to the Agricultural Policy Bureau's online application window, completing the submission process. After installation, the same sensors are used for full-scale operation, and the performance report compares the actual temperature, humidity, and CO2 values ​​measured during greenhouse operation with those in the plan. The system automatically generates comparison graphs and comments such as "Assumed temperature range in the plan → Actual temperature range" and "Assumed CO2 concentration → Actual value," forming the "Implementation Effects" section of the report. In this way, the final subsidy payment procedure is carried out smoothly, and farmers are freed from the burden of preparing detailed documents.

[0065] <Example 5> This embodiment demonstrates how to generate documents in bulk using multiple video sensors and audio interviews when a local tourism business applies for permits and subsidies necessary for holding an event. When organizing an event to revitalize a local community, a wide range of documents must be submitted, including road use permits, noise regulations, notifications to the fire department, and even tourism promotion subsidies from the Japan Tourism Agency and local governments. Traditionally, the person in charge would visit each government office and create documents by hand or in Word files, resulting in a chaotic mess. Using this system, information such as "event scale," "venue location," "event dates," "estimated number of attendees," and "stage equipment usage" is initially entered or obtained via voice description. Furthermore, the event venue is photographed with a 360-degree camera to visually capture spatial divisions such as the stage area, audience seating area, and vendor booth area. The AI ​​analysis unit estimates the capacity of the audience seating area, understands the flow of people, and automatically suggests areas where safety measures are needed. For example, it issues alerts based on multiple local government regulations, such as "another evacuation route is needed to accommodate this many people" or "failure to install additional temporary toilets may violate hygiene management requirements." When a user responds to an alert and enters additional safety plans or security guard arrangement plans, the deficiencies are resolved, and the system generates all necessary forms in bulk, such as "Road Use Permit Application," "Fire Safety Plan Notification," and "Subsidy Application (Tourism Promotion Category)." The deficiency management system checks even the format requirements of each government office (e.g., standardization to A4 paper, placement of signature field, etc.) and the submission method (electronic application or postal mail) to prevent misdelivery. After an event, a results report and settlement report are required. The system compiles information such as "360-degree video of the stage layout on the day," "attendance figures measured by crowd sensors," and "breakdown of expenses and income," and automatically generates an "expense report" and a "business report with photos." This significantly reduces the effort required for the person in charge to attach a large number of photos one by one or calculate attendance statistics. It can also automatically generate reports that visualize the results compared to past events, making it easier to identify areas for improvement for future events.

[0066] <Example 6> This example illustrates how service businesses other than restaurants (such as hair salons, beauty salons, etc.) can utilize this system for obtaining necessary permits when opening a new business, or for applying for subsidies to cover renovation costs. In the case of hair salons, standards are set for store area, equipment, water supply and drainage, and hygiene management. For beauty salons, fire safety regulations and infectious disease control measures are added, making the situation even more complex. In this system, when the user acquires or renovates a store, they take photos using a 360-degree camera, separate the counseling booths and treatment booths, and send the data to the AI ​​analysis unit. A LiDAR sensor captures the precise size of the space and the layout of the wall partitions, and staff members input information via voice in an interview format, such as "I want to renovate this area to make it a treatment room" or "I will install new water supply and drainage in the wall." The generation method combines these elements and compares them with requirements for opening a hair salon or beauty parlor, as well as standards set by the public health center. The deficiency management method checks whether "the qualification certificate for the hygiene manager has been uploaded," "whether the number of handwashing facilities meets the required number," and "whether the area of ​​the individual rooms is 5m²." 2 Details such as "Does it meet the above requirements?" are automatically verified. The user can add documents, photos, or renovation contractor plans to resolve errors, and a complete application form is automatically generated. Furthermore, some regions have programs that subsidize renovation costs. For example, if there is a "Renovation Grant to Support Female Entrepreneurs," the system will automatically suggest the program from its database and simultaneously check the requirements. After confirming eligible expenses and application deadlines, it is also possible to create application documents at the same time. This offers the advantage of being able to complete multiple applications with a single data entry. Once construction at the store is complete, sensors are used to take photos again, and the results are reflected in the performance report to ensure that the construction was carried out according to plan. If the wall partitions are different from what was planned, the system will detect the discrepancy and propose a revised explanation. If there are no deficiencies, the store will ultimately receive the subsidy and obtain the official business license. By utilizing such a system, even small businesses in the hair and beauty industry can smoothly handle administrative procedures.

[0067] <Example 7> This embodiment demonstrates a method for acquiring the floor layout of an entire facility using LiDAR and incorporating large-scale drawing data into application forms, targeting "subsidies for disaster prevention training" and "subsidies for the installation of safety equipment" conducted in large-scale commercial facilities. Large-scale commercial facilities have traditionally been subject to numerous regulations, including fire safety laws and building codes. Furthermore, in recent years, each tenant is required to submit plans to the local government, including the regular implementation of disaster prevention drills. To utilize subsidy programs, it is necessary to calculate the costs of disaster prevention equipment (such as emergency broadcasting systems and exit signs) and evacuation route installation, and submit these plans. When implementing this system, the facility manager first scans the building's corridors, common areas, and tenant spaces using a LiDAR scanner. In large facilities, multiple LiDAR devices are used simultaneously, and their data is integrated. The AI ​​analysis unit generates a map-like floor layout from the scan results and also detects the location of fire safety equipment (fire extinguishers, fire alarms, emergency lights, etc.). From the images captured by the 360-degree camera, the system estimates whether each piece of equipment is properly installed and whether it is nearing the end of its lifespan due to deterioration or replacement. Next, the administrator inputs information such as "conduct disaster prevention drills twice a year," "plan to update emergency broadcasting equipment," and "plan to replace all evacuation guidance lights with LEDs" via voice or text input. The system then reflects this information in the plan and evaluates its compliance against the requirements of each subsidy. The deficiency management mechanism issues instructions such as "please add an estimated value of the energy-saving effect from switching to LED guidance lights," and when the user adds data on utility costs or differences in electricity usage, the calculation section of the plan is automatically updated. Based on this plan, grant applications and equipment upgrade plans are created all at once. Since the system internally maintains information such as the total area of ​​the facility, the number of tenants, and the number of evacuation routes, inconsistencies are less likely to occur during submission. Furthermore, if the fire department or local government requests a re-examination of the seismic resistance of a particular area, the system can re-analyze LiDAR data and generate a structural safety assessment report. As a result, administrators can enjoy the convenience of completing procedures on a single platform, even for large-scale facilities. At the stage of creating the performance report, the location and model number of the already installed emergency exit signs are scanned again and recorded in the document. Even when replacing more than 50 signs at once, the system automatically generates sequential numbers and matches the photos with the model numbers, significantly reducing errors in manual list creation.

[0068] <Example 8> This example assumes a scenario where an overseas company applies for subsidies (such as support for global expansion) and various permits when starting a business in Japan, and demonstrates how to utilize voice translation and document multilingualization to overcome language barriers. Foreign companies wishing to establish a base in Japan often face complex procedures involving visas, company registration, various notifications, and subsidies for office setup. This system provides a multilingual user interface, including English and Chinese, and features a function that automatically translates explanations given in English (or other languages) while the user takes 360-degree photos of the office interior on-site, and incorporates them into the Japanese application form. For example, if a user says in English, "We plan to set up an office space with 20 desks and a small conference room," the system will generate the Japanese text "We plan to set up an office space with 20 desks and a small conference room" through real-time translation. LiDAR sensors measure the office space, and the layout, including the dimensions of walls and partitions, and the location of electrical outlets, is analyzed. Based on this information, the AI ​​analysis unit determines that "the floor area is Xm 2 "The conference room area is Xm 2 These values ​​will be reflected in the Japanese document. The deficiency management system creates a list of documents required for corporate registration in Japan, requirements for permits and licenses for establishing an office, and requirements for subsidies. This list includes additional documents specific to overseas companies, such as "proof of residence status for foreign managers," "certified copy of corporate registration (planned)," "copy of lease agreement," and "information on opening a Japanese bank account." If such documents are held in English, they can be uploaded and an automatic translation attempt will be made. If there are any deficiencies, an error message such as "official translation certificate required" will be displayed. Furthermore, subsidy applications require details such as budget plans, planned number of employees, and business details. This system uses multilingual natural language processing to create a draft that conforms to the Japanese writing style and format required by government offices, while referencing the original English text. Users simply review the final Japanese application, and if there are no problems, they add an electronic signature and press the submit button. In this way, even overseas companies can significantly reduce the burden of creating Japanese documents in-house. After actually opening the office, a performance report is required to receive the subsidy. At that time, the office can be photographed again with a 360-degree camera and compared with the LiDAR measurement results to reflect in the report that "the layout has been completed as planned," thus reducing the risk of misuse.

[0069] <Example 9> This embodiment demonstrates how this system can be applied when a medical institution (clinic, etc.) applies for necessary notifications to the public health center, permits for the installation of medical equipment, and subsidies for the enhancement of regional medical care, etc., when opening a new facility. When establishing a medical facility, stricter hygiene and equipment standards are imposed than those for a typical restaurant. These standards cover details such as the number of washrooms, the size of the patient waiting room, accessibility features, and the medical waste disposal system. Traditionally, this involved the time-consuming process of architectural design firms and doctors collaborating to create blueprints and submitting them to the public health center. This system uses LiDAR to acquire the clinic's internal structure and registers planned medical equipment using camera footage and audio recording. The user (doctor or medical coordinator) stated, "We need to install one X-ray machine and have a soundproofed room," and "The treatment room needs to have a floor area of ​​15m²." 2 The AI ​​films the hospital while saying things like, "That's all," and "Ensure wheelchair access is available in the patient waiting area." The AI ​​then compares the footage with layout information, checking in real time how much radiation shielding is needed, whether accessibility standards are met, and points out any deficiencies. Furthermore, this system retrieves subsidy requirements for regional healthcare enhancement and local government-specific grant programs from its database. For example, it checks requirements such as "up to 1 million yen in subsidies for introducing ultrasound diagnostic equipment" and reflects them in the medical equipment list. When the model number and planned purchase price of the equipment are entered, the subsidy amount is automatically calculated. The system is designed so that users can upload any missing documents (such as facility compliance certificates, copies of medical licenses, and business plans) as they become available. The application forms created in this way generate a total of documents, including notifications for the establishment of a medical institution (addressed to the public health center), applications for permission to use radiation (addressed to the prefectural government), and applications for subsidies (addressed to the relevant municipal or national government office). The system manages deficiencies by assigning format requirements (paper submission or electronic submission), and users can choose the final submission method. After the medical institution is established, the system takes photographs of the actual X-ray room and examination rooms again, and compiles a performance report confirming that the installation was completed without any discrepancies from the plan. Medical facilities may undergo renovations or install additional equipment in the future, and because the initial information is registered in this system's database, the same mechanism can be easily reused when applying for additional construction work. As a result, administrative procedures will be simplified, and more medical institutions will be able to open more quickly.

[0070] <Example 10> This example demonstrates the system operation for sole proprietors and freelancers applying for subsidies such as the "Small Business Sustainability Subsidy." Even in cases where there is no physical store or office, the system generates application forms using on-site surveys and online data. The Small Business Sustainability Subsidy can be used for a wide range of purposes, including capital investment and public relations activities, but it requires detailed documentation of business plans, expense breakdowns, and sales forecasts. Freelancers and small business owners often struggle with creating such documents. Therefore, this system focuses on online interviews, extracting the user's current business situation through voice recordings and automatically generating a business plan. Specifically, users explain things like "current sales figures" and "equipment they want to introduce using subsidies" via web conferencing tools or smartphone apps. The system then transcribes the audio into text in real time, and an AI module in the cloud categorizes it into items such as "business overview," "challenges and solutions," and "effectiveness of introduced equipment." If the user has a home or small office, they can upload spatial data captured with a 360-degree camera or LiDAR to check for the presence of a retail space and the current equipment setup. The generated draft plan summarizes the business's strengths, the benefits of the equipment to be introduced, and the expected increase in sales using natural language processing. The system also includes a mechanism to check for deficiencies, such as whether it includes ineligible expenses and whether the business plan's timeframe meets the requirements. Furthermore, it checks what kind of business registration the user has submitted as a sole proprietor and prompts them to attach an opinion letter from the Chamber of Commerce if necessary. After submitting the plan and undergoing a review process, if it is approved, the next step is to create an implementation report. This requires uploading photos of the installed equipment and receipts, but the system automatically tags the photos and links them to information such as "receipt for a new laptop (model number XX)" to create a document. If there are any deficiencies, the system will display errors such as "receipt is missing date" or "purchase information is insufficient," so users only need to take additional photos or obtain the necessary documents. In this way, even sole proprietors who are not familiar with administrative tasks can reliably receive subsidies. Once the implementation report is completed, the system stores all the data in a single folder in the cloud, allowing it to be reused when applying for other subsidies in subsequent years. In this way, the system significantly reduces the procedural burden on small businesses, and is also expected to improve the efficiency of the review process by standardizing the submission format for administrative review.

[0071] The inventions described above, which conceptualize the multiple embodiments, are described below in ≪1≫ (First Invention) to ≪31≫ (Third Invention). ≪1≫ A system that automatically generates application documents based on sensor information, and checks and manages for any deficiencies in said application documents, A database containing information on the requirements for the subsidies or permit programs to which applications are being made, A sensor unit for acquiring on-site information from a facility or store, A generation means that analyzes the data acquired from the sensor unit and compares it with the requirements information to generate a draft application form, A defect management system that automatically detects defects in the draft to conform it to a predetermined format and notifies the user of any defects, Document creation means that reflects the corrected content by the aforementioned deficiency management means and enables the output of the final application form. Equipped with, The aforementioned document creation means also supports the generation of performance reports that should be prepared after permission or subsidy grant decisions are made, and can automatically generate such performance reports using the same sensor information or additionally acquired sensor information. Application document automated generation and management system. ≪2≫ In the system described in ≪1≫, The aforementioned sensor unit includes a 360-degree camera and grasps the layout or equipment status within the facility based on the wide-area video information captured. system. ≪3≫ In the system described in ≪1≫, The aforementioned sensor unit includes a LiDAR sensor and analyzes the positional relationship of walls and equipment in space in three dimensions to automatically generate drawings or layout information necessary for application documents. system. ≪4≫ In the system described in ≪1≫, The sensor unit is equipped with a voice input means and converts the content of the interview with the on-site staff or applicant into text data and provides it to the generation means. system. ≪5≫ In the system described in ≪1≫, The database storing the aforementioned requirements information includes requirements from multiple application destinations such as the national government, local governments, and private grant organizations, and the generation means compares these requirements and automatically proposes the optimal application plan. system. ≪6≫ In the system described in ≪1≫, The aforementioned deficiency management means includes a function to quantify or rank and display items that do not meet the requirements, and presents the user with a priority level corresponding to the degree of deficiency. system. ≪7≫ In the system described in ≪1≫, The aforementioned document creation means generates application documents by automatically inserting text extracted from sensor information according to a pre-registered template. system. ≪8≫ In the system described in ≪1≫, The generation means combines sensor information and a generative AI to perform natural language processing and outputs a draft with formatted text. system. ≪9≫ In the system described in ≪1≫, The generation means updates the draft through multiple iterative analyses, and the deficiency management means re-checks it each time it is updated, thereby creating a final document with progressively improved accuracy. system. ≪10≫ In the system described in ≪1≫, When the aforementioned deficiency management means detects a deficiency, it prompts the user to enter the missing information via voice guidance or a pop-up message. system. ≪11≫ In the system described in ≪1≫, The aforementioned document creation method is linked to an electronic application portal, enabling the final document to be automatically sent in a specified format. ≪12≫ In the system described in ≪1≫, Based on the results of matching the requirements information, the system automatically generates a checklist of the minimum necessary documents and attachments, and includes a lock function that prevents the submission of the application until the entire checklist is completed. system. ≪13≫ In the system described in ≪1≫, The system includes a history management function to prevent fraud by adding timestamps and geotags to the recorded data captured or acquired by the aforementioned sensor unit. system. ≪14≫ In the system described in ≪1≫, The aforementioned generation means automatically detects the difference between the period before and after the application and reflects it in the content of the performance report. system. ≪15≫ In the system described in ≪1≫, The aforementioned document creation method includes a scheduling function for managing the submission deadline and required items of the performance report, and notifies the user when the deadline approaches. system. ≪16≫ In the system described in ≪1≫, The sensor unit has a function to extract keywords from the content of the audio data it acquires and to automatically display the subsidy requirements corresponding to those keywords as links. system. ≪17≫ In the system described in ≪1≫, The aforementioned deficiency management means includes a function to analyze deficiency notifications (email, messages on the portal, etc.) received from administrative agencies and to suggest sensor information or documents necessary to resolve the deficiency to the user. system. ≪18≫ In the system described in ≪1≫, The aforementioned generation means includes a function to automatically calculate numerical indicators such as CO2 reduction and energy-saving effects, and reflects the calculation results in the fields to be entered in the application form. system. ≪19≫ In the system described in ≪1≫, The aforementioned document creation means manages drafts of multiple application documents simultaneously and includes a dashboard that visualizes the progress of each case. system. ≪20≫ In the system described in ≪1≫, The sensor unit automatically analyzes images or videos acquired by the sensor to identify the degree of deterioration and model number of the equipment, and automatically enters the identification result into the equipment description section of the application form. system. ≪21≫ In the system described in ≪1≫, The aforementioned document creation means includes an interface that accepts review from users or experts, and reconstructs the draft by analyzing the review results with AI. system. ≪22≫ In the system described in ≪1≫, The aforementioned deficiency management means presents missing or insufficiently answered items to the user using visual indicators such as color coding, and prompts them to make corrections. system. ≪23≫ In the system described in ≪1≫, The aforementioned system provides an estimation function before application submission, and reflects the simulation results of construction costs and subsidy amounts in the application documents. system. ≪24≫ In the system described in ≪1≫, The sensor unit synchronizes video data acquired by the sensor unit with drawing data or layout data generated by the generation means, and includes a function to mutually link images and explanatory text in the application documents. system. ≪25≫ In the system described in ≪1≫, The aforementioned document creation means includes a function that enables the application documents to be finalized without any deficiencies to be affixed with an electronic signature or electronic certificate. system. ≪26≫ In the system described in ≪1≫, The aforementioned system logs the entire application document generation process, allowing users and administrators to refer to the logs to check operation history and data history. system. ≪27≫ In the system described in ≪1≫, The aforementioned generation means is automatically updated in response to changes in the format of application documents or updates to requirements, and the draft is modified to conform to the latest rules. system. ≪28≫ In the system described in ≪1≫, Even if the aforementioned deficiency management measures do not meet the prescribed requirements, alternative candidates will be presented, such as similar other systems or higher or lower-level subsidy requirements. system. ≪29≫ In the system described in ≪1≫, The voice data acquired as sensor information is linked with a translation device capable of translating into multiple languages, enabling explanations and document creation for foreign owners, etc. system. ≪30≫ In the system described in ≪1≫, When preparing the aforementioned performance report, the plan created at the time of the grant decision and the sensor data after construction are compared to quantify the degree of deviation, and this value is output as a key indicator in the performance report. system. ≪31≫ In the system described in ≪1≫, The system has a function to store environmental information (temperature, humidity, CO2 concentration, etc.) acquired from the aforementioned sensor unit in a time series and to calculate the energy-saving effect and comfort evaluation required in application documents. system.

[0072] The above is an explanation of several variations. [Industrial applicability]

[0073] This embodiment, multiple modifications and embodiments, and similar forms can be applied to administrative procedures, subsidy applications, and permit applications in a wide range of fields, such as restaurants, agriculture, commercial facilities, medical institutions, overseas corporate branches, and event organizers. It is noteworthy that by automating the process of document creation and addressing deficiencies, which were previously done manually, the workload on applicants is significantly reduced, and it can also be used in administrative review and audits. Furthermore, in the event of a natural disaster, applications for disaster victim certificates and various forms of financial assistance tend to concentrate in a short period of time at local governments in the affected areas, leading to serious problems such as congestion at service counters, increased burden on administrative staff, and delays in processing. Moreover, disaster victims themselves often face difficulties in preparing complex application documents amidst the stress of evacuation and other psychological stresses. In particular, the elderly, people with disabilities, and foreign residents experience even greater difficulties in understanding and filling out the necessary documents. From this perspective, this embodiment, multiple modifications and embodiments, and forms similar thereto are effective in effectively solving the challenges in application procedures during disasters. [Explanation of Symbols]

[0074] 10 Computers 12 Processing Units 14 Storage section 20 Imaging device 30 Recording device 40 Application destination computer AD application form AP Application CS Application and Report Creation System CS1 Application Form Creation System CS2 Report Creation System DF data file LB various libraries NW (Network Communication Network) PG Application Reporting Program PG1 Application Program PG2 Reporting Program RD report

Claims

1. An application program for creating an application form having multiple application items, using at least one application detection signal detected from at least one detection device, On the computer, A recognition function that recognizes the aforementioned multiple application items, An application signal acquisition function that causes at least one application detection signal to be acquired from at least one of the aforementioned detection devices, An application signal languageization function that converts the aforementioned at least one application detection signal into at least one application detection language, An application language selection function that allows the user to select the appropriate wording for each of the aforementioned multiple application items from at least one of the aforementioned application detection languages, To execute Application program.

2. The aforementioned computer is connected via a communication network to the receiving computer of the application form. To the aforementioned computer, If, as a result of the application language selection function, there are no deficiencies in the application requirements for any of the multiple application items, the application form containing the multiple application items is sent to the receiving computer by the application form transmission function. To further execute The application program described in claim 1.

3. To the aforementioned computer, If, as a result of the application language selection function, at least one of the multiple application items has a deficiency in the application requirements, the application deficiency notification function notifies the creator of the application item with the deficiency. An application signal reacquisition function that acquires at least one or more other application detection signals newly detected using the at least one of the aforementioned detection devices, After running it further, The application signal reacquisition function acquires at least one other application detection signal, which is then included in the at least one application detection signal, and the application signal languageization function and the application language selection function are executed again. The application program according to claim 2.

4. At least one detection device includes an imaging device that detects either still images or moving images, or both, and a recording device that records sound. The application program according to claim 2.

5. To the aforementioned computer, In the application signal language conversion function, if there is a discrepancy between the application imaging detection language converted from the application detection signal detected by the imaging device and the application recording detection language converted from the application detection signal detected by the recording device, the application imaging detection language is prioritized and the application language selection function is executed. The application program described in claim 4.

6. At least one detection device, A computer on which the application program described in any one of claims 1 to 5 is stored, Equipped with, The application program causes the computer to perform at least the recognition function, the application signal acquisition function, the application signal language conversion function, and the application language selection function. Application form creation system.

7. An application form creation method for creating an application form having multiple application items, using at least one application detection signal detected from at least one detection device, A recognition process that causes the computer to recognize the aforementioned multiple application items, The process of obtaining an application signal involves causing the computer to obtain at least one detection signal from at least one detection device, An application signal languageization step in which the computer languageizes the at least one application detection signal as at least one application detection language, An application language selection step in which the computer selects the wording corresponding to each of the multiple application items from the at least one application detection language, including, How to prepare the application form.

8. An application reporting program for creating an application form having multiple application items and a report for said application form, using at least one application detection signal and a reporting detection signal detected from at least one detection device, (1) The application program described in claim 4 or 5, (2) A reporting program for preparing reports, On the computer, An extraction function that extracts multiple reporting items from an application form containing the aforementioned multiple application items in order to create a report for that application form, A reporting signal acquisition function that causes at least one or more reporting detection signals to be acquired from at least one of the aforementioned detection devices, A reporting signal languageization function that converts the aforementioned at least one reporting detection signal into at least one reporting detection language, A reporting language selection function that allows the user to select the appropriate wording for each of the aforementioned multiple reporting items from at least one of the aforementioned reporting detection languages, To execute Reporting program and, including, Application and reporting program.

9. To the aforementioned computer, If, as a result of the reporting language selection function, there are no deficiencies in the reporting requirements for any of the multiple reporting items, the report containing the multiple reporting items is sent to the receiving computer. To further execute The application reporting program according to claim 8.

10. To the aforementioned computer, If, as a result of the reporting language selection function, at least one of the multiple reporting items has a deficiency in its reporting requirements, the reporting deficiency notification function notifies the creator of the deficiency in the reporting item. A report signal reacquisition function that acquires at least one other newly detected report detection signal using the aforementioned at least one detection device, After running it further, The report signal reacquisition function retrieves at least one other report detection signal, which is then included in the report detection signal, and the report signal languageization function and the report language selection function are executed again. The application reporting program according to claim 8.

11. To the aforementioned computer, In the aforementioned reporting signal language conversion function, if there is a discrepancy between the reporting imaging detection language converted from the reporting detection signal detected by the imaging device and the reporting recording detection language converted from the reporting detection signal detected by the recording device, the reporting imaging detection language is given priority and the reporting language selection function is executed accordingly. The application reporting program according to claim 10.

12. At least one detection device, A computer storing the application reporting program described in any one of claims 8 to 11, Equipped with, The application reporting program causes the computer to perform at least (1) the recognition function, the application signal acquisition function, the application signal language conversion function and the application language selection function, and (2) the extraction function, the report signal acquisition function, the report signal language conversion function and the report language selection function. Application form and report creation system.

13. An application form and report preparation method that prepares an application form having multiple application items and a report for said application form using at least one application detection signal and a reporting detection signal detected from at least one detection device, A recognition process that causes the computer to recognize the aforementioned multiple application items, The process of obtaining an application signal involves causing the computer to obtain at least one detection signal from at least one detection device, An application signal languageization step in which the computer languageizes the at least one application detection signal as at least one application detection language, An application language selection step in which the computer selects the wording corresponding to each of the multiple application items from the at least one application detection language, The extraction process involves causing the computer to extract multiple reporting items from an application form containing the multiple application items in order to create a report for that application form. A reporting signal acquisition step involves causing the computer to acquire at least one reporting detection signal from at least one of the detection devices, A reporting signal languageization step in which the computer languageizes the at least one reporting detection signal as at least one reporting detection language, A reporting language selection step in which the computer selects a word corresponding to each of the plurality of reporting items from the at least one reporting detection language, including, How to prepare application forms and reports.

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