JP7519927B2 - Common infrastructure system for achieving DX - Google Patents

Description

This application relates to a common infrastructure system for realizing digital transformation (abbreviated as DX in this application) aimed at realizing DX.

In recent years, computer systems have come to be used for a wide variety of purposes all over the world, and the scope of their use is expanding. Furthermore, with the fusion of communication technology and Internet technology, the popularity of IoT (Internet of Things) is increasing day by day.

Against this background, the Cabinet Office is advocating the idea of realizing a human-centered society that balances economic development with the resolution of social issues through a system known as Society 5.0 that highly integrates cyberspace (virtual space) and physical space (real space).

A society that realizes Society 5.0 will overcome these issues and difficulties by connecting everyone and everything through the IoT, sharing a wide range of knowledge and information, and creating new value that has never been seen before. Furthermore, artificial intelligence (AI) will provide the necessary information when it is needed, and through social innovation, a society will be realized in which each individual can play an active role comfortably.

In light of this background, various techniques have been proposed relating to tools, methods, and devices using programs that support the development of IoT application programs.
For example, in order to enable developers to easily search for the development deliverables they need, the development deliverables of an application program are grouped by function, and developers can search for development assets by referring to a function dictionary.

However, while this conventional technology allows for efficient development by managing development assets, it requires input from the user to refer to a function dictionary, and does not provide a perspective for extracting application programs (hereafter referred to as common functions) that are likely to be used in common across fields from among the software components for each function prepared for reuse, which means that users must decide each time whether or not they can reuse development assets.

In addition, a technology has been proposed that uses the concept of "mashups," which combine two or more Web services (Web APIs: Web Application Programming Interfaces) to create a new service, to provide a core set of service provision functions that can be used by a variety of applications, making it possible to provide services without much effort.

However, this conventional technology has problems in that it classifies functions from the perspective of common functions and application programs that are specific to each software component and used individually (hereinafter referred to as individual functions), and does not process whether they are applicable to the web service that is currently being developed.

In light of this, another prior art technique proposed is to classify software components for each function prepared for the purpose of reuse into parts with common functions and parts with individual functions at the smallest possible unit, and to allow system users to develop applications by combining the common functions and individual functions via a GUI (Graphical User Interface) (see, for example, Patent Document 1 below).

JP 2001-43079 A

However, the conventional technology described in Patent Document 1 allows users to develop applications by combining any components via a GUI, but this method has the problem that the system cannot automatically determine past common functions and individual functions when users develop their own applications. This is because applications need to be developed by combining common functions and individual functions that have been registered in advance via a GUI.

This application discloses technology to solve the problems described above, and aims to provide a common infrastructure system for DX realization that can efficiently develop applications for DX realization.

The common infrastructure system for realizing DX disclosed in this application comprises an external input reading unit that imports metadata consisting of the detailed function analyzed this time and the additional information associated with the detailed function from the outside,
a similarity analysis unit that analyzes a similarity between the metadata imported by the external input reading unit and a combination of a detailing function and associated information associated with the detailing function, the combination being registered in an application database in advance;
a similarity determination processing unit that determines whether the similarity analyzed by the similarity analysis unit is equal to or greater than a preset threshold, and if the similarity is equal to or greater than the threshold, extracts the detailed function as a common function for realizing DX;
and a screen display unit that displays the common functions extracted by the similarity determination processing unit.

The common infrastructure system for DX realization disclosed in this application makes it possible to efficiently develop applications for DX realization.

FIG. 1 is a block diagram showing a schematic configuration of a common infrastructure system for realizing DX in accordance with embodiment 1. 1 is a flowchart illustrating the operation of a common infrastructure system for realizing DX according to embodiment 1. A block diagram showing the general configuration of a common infrastructure system for realizing DX in accordance with embodiment 2. 11 is a flowchart illustrating the operation of a common infrastructure system for realizing DX according to the second embodiment.

In the following embodiment, a nuclear power plant will be described as an example of various businesses, but the present application is not limited to this.
Embodiment 1.
FIG. 1 is a block diagram showing a schematic configuration of a common infrastructure system for realizing DX according to the first embodiment.

The common infrastructure system 1 for realizing DX according to this embodiment 1 is a system that automatically extracts common functions (application programs that are likely to be used in common in various fields) to be used in the development of IoT applications aimed at realizing DX in nuclear power plants.

This common infrastructure system 1 for realizing DX has a system configuration including a memory 30, a hard disk drive 40, and a CPU (Central Processing Unit) 10 inside the client terminal 3, and also has a display device 8 such as an LCD display, and a data input device 9 such as a mouse and a keyboard as devices externally connected to the client terminal 3.

The hard disk drive 40 stores the following data: an application function DB (Data Base) 11, cluster analysis logic 12, analysis results 13, and a threshold value 14 for determining similarity. In addition, although not shown, a program for operating the CPU 10 is also stored in advance.

In the above-mentioned application function DB11, each application program developed in the past is modularized in advance into the smallest unit, and these are stored as detailed functions. In other words, a detailed function is an application program that has the function of being used repeatedly without duplication, so that application programs with the same function do not have to be remade over and over again. Furthermore, associated additional information is added to each detailed function in advance. Therefore, in this application DB11, detailed functions and additional information are stored as metadata 2 in a state categorized by JSON format (JavaScript Object Notation) or the like.

Cluster analysis logic 12 refers to the logic used in similarity analysis unit 5, which will be described later. Analysis result 13 is data resulting from an analysis of the similarity between the newly analyzed detailing function and past detailing functions, calculated by similarity analysis unit 5. Threshold value 14 is a preset standard threshold value for determining the similarity between the newly analyzed detailing function and past detailing functions.

Meanwhile, the memory 30 is made up of, for example, random access memory and flash memory, and has an external input reading unit 4, a similarity analysis unit 5, a similarity determination processing unit 6, and a screen display unit 7 built in it. Then, the functional units of the external input reading unit 4, the similarity analysis unit 5, the similarity determination processing unit 6, and the screen display unit 7 operate based on operation commands issued by the CPU 10 executing a program.

The external input reading unit 4 reads a configuration file such as a JSON format of metadata 2 consisting of the detailed function of the application program to be newly analyzed and the additional information previously associated with this detailed function, and expands it on the memory 30.

The similarity analysis unit 5 compares the metadata 2 consisting of the detailed functions and associated additional information input to the external input reading unit 4 via the data input device 9 with the metadata consisting of the detailed functions and associated additional information preregistered in the application function DB 11, and analyzes the similarity between the two using cluster analysis logic 12. The analysis result is then stored in the analysis result 13 on the hard disk drive 40.

The similarity determination processing unit 6 executes a process for determining whether the similarity is equal to or greater than the threshold value 14 using the threshold value 14 on the hard disk drive 40 for the similarity analysis result 13 from the similarity analysis unit 5.

The screen display unit 7 executes a process of displaying the highly similar detailed functions determined by the similarity determination processing unit 6 and extracted as new analysis targets as common functions to the user via the display device 8.

Next, the concept of data selection will be explained.
Conventionally, a user had to extract or select components for each function, such as common functions related to input, output, and processing, and unique functions, and register them in advance in a database (e.g., a knowledge database), making it difficult to automatically extract common functions.

In order to solve this problem, in this application, the detailed function of each application program and the associated additional information are stored as metadata 2 in the hard disk drive 40. The additional information includes the field (e.g., plant operation), each solution classification (e.g., work efficiency), support target (e.g., on-site work), and function category (input, output, processing). By associating this additional information with the detailed function and analyzing it, the system can automatically extract or select common functions. Note that the associated additional information may be in a pattern other than the above.

Next, the operation of the common infrastructure system 1 for realizing DX in this embodiment 1 will be explained with reference to the flowchart in Figure 2.

The external input reading unit 4 determines whether the metadata 2 (the detailing function of the application program and the additional information previously associated with this detailing function) to be newly analyzed this time has been input via the data input device 9 of the client terminal 3 and exists (step S100).

If the result of this determination is that metadata 2 exists, the detailed function and accompanying information for the metadata 2 input to memory 30 are expanded (step S101). Note that if the result of the determination in step S100 is that no metadata exists, the process ends and terminates.

Next, the similarity analysis unit 5 reads out the detailed functions and associated information that have been previously stored in the application function DB 11 of the hard disk device 40, and expands them on the memory 30 (step S102).

Next, the similarity analysis unit 5 analyzes the similarity by combining the detailed functions and their associated information contained in the metadata 2 to be newly analyzed that was expanded on the memory 30 in step S101 with the detailed functions and their associated information that were previously stored in the application function DB 11 in step S102.

To analyze this similarity, the cluster analysis logic 12 is used as a multivariate analysis method registered in the hard disk drive 40 to calculate the similarity (step S103). The calculated result is then stored in the hard disk drive 40 as the analysis result 13.

The similarity determination processing unit 6 uses the threshold value 14 registered in the hard disk device 40 to determine whether the similarity calculated in step S103 is equal to or greater than the threshold value 14 (step S104). If the result of this determination indicates that the detailed function has a high similarity of equal to or greater than the threshold value 14, the record is added to the application function DB 11 as a common function.

The screen display unit 7 also executes a process of displaying to the user via the display device 8 the analysis results by the similarity analysis unit 5 and the common functions for which the similarity determination processing unit 6 has determined that the similarity is equal to or greater than the threshold value 14 (step S105). If the similarity is low, that is, less than the threshold value 14, the process is terminated. As a result, the display device 8 displays the common functions that have been determined to be highly similar to the user.

As described above, according to the common infrastructure system for realizing DX in this embodiment 1, the system can automatically extract and select the common functions of each solution after determining whether the similarity is high or low by utilizing data, so that the extraction and selection of common functions can always be performed appropriately with little effort, making it possible to efficiently develop applications for realizing DX.

Embodiment 2.
FIG. 3 is a block diagram showing the schematic configuration of a common infrastructure system for realizing DX according to the second embodiment, and components corresponding to or equivalent to those in the first embodiment shown in FIG. 1 are given the same reference numerals.

The common infrastructure system for realizing DX in this second embodiment is a system that, like the first embodiment, automatically extracts common functions (application programs that are likely to be used in common) to be used in the development of IoT applications aimed at realizing DX in nuclear power plants while communicating between the client terminal 3 and the server 15.

In this second embodiment, a server 15 is added to the configuration of the first embodiment, and this server 15 includes a memory 30, a hard disk drive 40, a CPU 10, a display device 8, and a data input device 9.

The hard disk device 40 has preregistered therein the application function DB 11, the cluster analysis logic 12, the analysis result 13, and the threshold value 14. The memory 30 also has built therein an external input reading unit 4, a similarity analysis unit 5, a similarity determination processing unit 6, and a screen display unit 7.
Although not shown, the client terminal 3 also has a memory, a hard disk drive, a CPU, a display device, and a data input device.

Next, the operation of the common infrastructure system 1 for realizing DX in this second embodiment will be explained with reference to the flowchart in FIG.

In the common infrastructure system 1 for realizing DX in this second embodiment, metadata 2 consisting of the detailing function of the application program to be newly analyzed and the additional information previously associated with this detailing function is input from a data input device (not shown) equipped in the client terminal 3 and communicated to the server 15, so that the server 15 acquires the metadata 2 (step S106).

Then, in the server 15, common functions to be used in the development of IoT applications aimed at realizing DX of nuclear power plants are extracted. Steps S101 to S105 from step S106 onwards for this purpose are the same as the processing contents shown in Fig. 2, and therefore the description thereof will be omitted here.
The screen display unit 7 not only displays the common functions on the display device 8, but also transmits them to the client terminal 3 via a communication line, so that they can also be displayed on a display device (not shown).

As described above, according to the common infrastructure system for realizing DX in this second embodiment, the server 15 can be equipped with the function of automatically extracting common functions, which makes it easier to share and store data and reduces the load on the client terminal 3, making it even easier to realize DX.

Although various exemplary embodiments are described in this application, the various features, aspects, and functions described in one or more of the embodiments are not limited to application in a particular embodiment, but may be applied to the embodiments alone or in various combinations.

Therefore, countless variations not illustrated are contemplated within the scope of the technology disclosed in this application. For example, this includes cases in which at least one component is modified, added, or omitted, and even cases in which at least one component is extracted and combined with a component of another embodiment.

1. DX realization common infrastructure system, 2. Metadata, 3. Client terminal,
4 External input reading unit, 5 Similarity analysis unit, 6 Similarity judgment processing unit, 7 Screen display unit,
8 Display device, 9 Data input device, 10 CPU, 11 Application function DB, 12 Cluster analysis logic, 13 Analysis result, 14 Threshold, 15 Server,
30 memory, 40 hard disk drive.

Claims (3)

an external input reading unit that externally imports metadata consisting of the detailed function that is the subject of the analysis and additional information associated with the detailed function;
a similarity analysis unit that analyzes a similarity between the metadata imported by the external input reading unit and a combination of a detailing function and associated information associated with the detailing function, the combination being registered in an application database in advance;
a similarity determination processing unit that determines whether the similarity analyzed by the similarity analysis unit is equal to or greater than a preset threshold, and if the similarity is equal to or greater than the threshold, extracts the detailed function as a common function for realizing DX;
a screen display unit that displays the common functions extracted by the similarity determination processing unit;
A common infrastructure system for realizing DX. The common infrastructure system for realizing DX described in claim 1, wherein the similarity analysis unit analyzes the similarity using cluster analysis logic, and the similarity determination processing unit extracts detailed functions whose similarity is equal to or greater than a threshold based on the results of the analysis by the similarity analysis unit. A common infrastructure system for realizing DX according to claim 1 or claim 2, in which a client terminal and a server are connected by a communication line, the server includes the external input reading unit, the similarity analysis unit, and the similarity determination processing unit, and the server acquires the metadata input from the client terminal.