Patent Application
20240036906
The present application claims priority to and incorporates by reference the entire contents of Japanese Patent Application No. 2022-121939 filed in Japan on Jul. 29, 2022.
The present invention relates to an information management apparatus, a calculation apparatus, a computer-readable recording medium, an information processing system, and an information processing method.
Conventionally, a technology using a cloud environment for collecting data from apparatuses (devices), such as a gateway apparatus, a sensor apparatus, and a control apparatus, that are installed in a plant or the like is known.
However, in the conventional technology, it is difficult to efficiently enhance functions of the cloud environment. For example, in the conventional technology, there is a need to set a port dedicated for software when a web application server on the cloud environment transmits data to an external Artificial Intelligence (AI) application server.
The present invention has been conceived in view of the foregoing situations, and an object of the present invention is to efficiently manage a calculated value that is obtained from a measurement value that is collected by a device.
According to an aspect of the embodiments, an information management apparatus includes, a reception unit that receives measurement data that is collected by a device, a first setting unit that sets a first virtual device corresponding to the measurement data, and a second setting unit that, when a calculation apparatus that performs a predetermined calculation receives the measurement data and when acquiring first calculated data that is generated from the measurement data, sets a second virtual device corresponding to the first calculated data.
According to an aspect of the embodiments, a calculation apparatus includes, a reception unit that receives, from an information management apparatus, measurement data that is associated with a first virtual device set by the information management apparatus and that is collected by a device, a calculation unit that generates first calculated data by performing a predetermined calculation on the measurement data, and a transmission unit that transmits the first calculated data as data that is associated with a second virtual device set by the information management apparatus to the information management apparatus.
According to an aspect of the embodiments, a non-transitory computer-readable recording medium having stored therein an information management program that causes a computer to execute a process, the process includes, receiving measurement data that is collected by a device, setting a first virtual device corresponding to the measurement data, and setting, when a calculation apparatus that performs a predetermined calculation receives the measurement data and when acquiring first calculated data that is generated from the measurement data, a second virtual device corresponding to the first calculated data.
According to an aspect of the embodiments, a non-transitory computer-readable recording medium having stored therein a calculation program that causes a computer to execute a process, the process includes, receiving, from an information management apparatus, measurement data that is associated with a first virtual device set by the information management apparatus and that is collected by a device, generating first calculated data by performing a predetermined calculation on the measurement data, and transmitting the first calculated data as data that is associated with a second virtual device set by the information management apparatus to the information management apparatus.
According to an aspect of the embodiments, an information processing system includes, an information management apparatus, and a calculation apparatus, wherein the information management apparatus includes a reception unit that receives measurement data that is collected by a device, a first setting unit that sets a first virtual device corresponding to the measurement data, and a second setting unit that sets a second virtual device corresponding to first calculated data that is generated from the measurement data by the calculation apparatus, and the calculation apparatus includes a reception unit that receives, from the information management apparatus, the measurement data that is associated with the first virtual device, a calculation unit that generates the first calculated data by performing a predetermined calculation on the measurement data, and a transmission unit that transmits the first calculated data as data that is associated with the second virtual device to the information management apparatus.
According to an aspect of the embodiments, an information processing method implemented by an information management apparatus and a calculation apparatus, the information processing method includes, receiving, by the information management apparatus, measurement data that is collected by a device, setting, by the information management apparatus, a first virtual device corresponding to the measurement data, setting, by the information management apparatus, a second virtual device corresponding to first calculated data that is generated from the measurement data by the calculation apparatus, receiving, by the calculation apparatus, the measurement data that is associated with the first virtual device from the information management apparatus, generating, by the calculation apparatus, the first calculated data by performing a predetermined calculation on the measurement data; and transmitting, by the calculation apparatus, the first calculated data as data that is associated with the second virtual device to the information management apparatus.
Embodiments of information management apparatus, a calculation apparatus, a computer-readable recording medium, an information processing system, and an information processing method according to the present invention will be described in detail below with reference to the drawings. The present invention is not limited by the embodiments described below.
A configuration of an information processing system 100 according to one embodiment, a configuration of each of apparatuses, and the flow of processing will be described in sequence, and thereafter, effects of the embodiment will be described.
The configuration of the information processing system 100 according to one embodiment will be described in detail below with reference to
The information processing system 100 includes a web application server 10 that is an information management apparatus, AI application servers 20 (20-1, 20-2, . . . ) that are calculation apparatuses, and plant apparatuses 30 (30A, 30C, . . . ). Here, the web application server 10 is constructed in a cloud environment. Further, the plant apparatuses 30 are installed in a plant. Meanwhile, the information processing system 100 illustrated in
Processing of the entire information processing system 100 as described above will be described. Meanwhile, Steps S1 to S6 may be performed in a different order. Further, a part of processes at Step S1 to S6 may be omitted.
The web application server 10 receives measurement data from the plant apparatuses 30 (Step S1). For example, the web application server 10 receives, as JavaScript (registered trademark) Object Notation (JSON) data that is text data, a sensor value or the like that is collected by the plant apparatus 30A that is a sensor apparatus.
The web application server 10 sets virtual devices 30-V corresponding to the plant apparatuses 30 (Step S2). For example, the web application server 10 sets a virtual device 30A-V1 corresponding to measurement data that is transmitted by the plant apparatus 30A. Further, when the web application server 10 performs a calculation using an AI function or the like on the measurement data, the web application server 10 sets a virtual device 30A-V corresponding to the calculated data. For example, the web application server 10 sets the virtual devices 30-V corresponding to different kinds of calculated data, such as a virtual device 30A-V2 corresponding to an AI function 1 that is calculated by the AI application server 20-1 and a virtual device 30A-V3 corresponding to an AI function 2 that is calculated by the AI application server 20-2.
The web application server 10 transmits the measurement data to the AI application servers 20 by using an external linkage common Application Programming Interface (API) (Step S3). For example, the web application server 10 transmits measurement data A collected by the plant apparatus 30A, as Comma-Separated Values (CSV) data that is text data, to the AI application server 20-1 that performs a calculation by using the AI function 1, via the virtual device 30A-V1. In this case, the web application server 10 is able to further transmit the measurement data A collected by the plant apparatus 30A to the AI application server 20-2 that performs a calculation by using the AI function 2.
The AI application server 20 generates calculated data from the measurement data (Step S4). For example, the AI application server 20-1 generates calculated data A-1 by inputting the measurement data A collected by the plant apparatus 30A to the AI function 1. At this time, the AI application server 20-2 is also able to generate calculated data A-2 by inputting the measurement data A collected by the plant apparatus 30A to the AI function 2.
The AI application servers 20 transmits the calculated data, as the measurement data of the virtual devices 30-V, to the web application server 10 via the external linkage common API (Step S5). For example, by transmitting the calculated data A-1 as JSON data via a virtual device 30-V2, the AI application server 20-1 is able to transmit the calculated data A-1 as the measurement data of the virtual device 30-V2 to the web application server 10. At this time, by transmitting the calculated data A-2 as JSON data via a virtual device 30-V3, the AI application server 20-2 is able to transmit the calculated data A-2 as the measurement data of the virtual device 30-V3 to the web application server 10.
The web application server 10 displays the measurement data that is device data and the calculated data that is virtual device data (Step S6). For example, the web application server 10 displays the virtual device 30A-V1 that corresponds to the measurement data A received from the plant apparatus 30A and the virtual device 30A-V2 that corresponds to the calculated data A-1 received from the AI application server 20-1 on a terminal device (not illustrated) of an administrator of the information processing system 100. At this time, the web application server 10 is also able to display the virtual device 30A-V3 that corresponds to the calculated data A-2 received from the AI application server 20-2 on the terminal device (not illustrated) of the administrator of the information processing system 100. Furthermore, the administrator of the information processing system 100 is able to view various kinds of data from the virtual device 30-V as described above. For example, the administrator of the information processing system 100 is able to view a graph that represents a temporal change of the calculated data A-1 by performing click operation about display of the virtual device 30A-V2.
An overview of information processing as the reference technology will be described first, and thereafter, a problem with the reference technology will be described.
An information processing system of the reference technology performs information processing as described below. Firstly, the web application server receives measurement data that is transmitted from a connected plant apparatus. Secondly, the web application server performs a data selection process and a transmission process for each of functions in response to a request from an external linkage calculation function, that is, an AI application server. Thirdly, the AI application server that is the external linkage function performs a software calculation process. Fourthly, the AI application server transmits calculated data to the web application server. Fifthly, the web application server associates the calculated data received from the AI application server, and displays the calculated data as data of the plant apparatus.
The information processing of the reference technology as described above has a problem as described below. Firstly, when functions of the cloud environment are to be enhanced by external linkage, there is a need to generate a port dedicated for software, so that a cost for generating a dedicated function increases. Secondly, with an increase in functions, there is a need to add dedicated functions, such as a function 1 and a function 2. Thirdly, there is a need to perform association operation for selecting a device to which data is transmitted when the data is to be transmitted to a linked function, in close cooperation with the web application server and the external linkage function.
An overview of the information processing system 100 according to one embodiment will be firstly described below and thereafter effects of the information processing system 100 will be described.
In the information processing system 100, the web application server 10 receives the measurement data that is collected by the plant apparatus 30, sets a virtual device corresponding to the plant apparatus 30, transmits the measurement data to the AI application server 20 that performs a predetermined calculation, and acquires calculated data that the AI application server 20 has generated from the measurement data via the virtual device 30-V2.
Further, when acquiring each piece of calculated data generated by different kinds of calculations from the measurement data, the web application server 10 sets the plurality of virtual devices 30-V corresponding to the respective pieces of calculated data, transmits the measurement data to the AI application server 20 by using a common API that performs transmission and reception of data to and from external apparatuses, and acquires a plurality of pieces of calculated data via the corresponding virtual devices by using the common API. Furthermore, the web application server 10 stores the measurement data and the calculated data, and displays at least one of the stored measurement data and the stored calculated data as a predetermined graph.
In other words, the information processing system 100 is able to manage, as a measurement value of a different device, the calculated value that is obtained by software processing, such as external linkage, from a physical quantity that is measured by a device. At this time, in the information processing system 100, function enhancement by external linkage need not be performed for each of functions, so that it is possible to reduce a development cost of the web application server 10.
In the information processing system 100, effects as described below are achieved. Firstly, there is no need to set a dedicated port for external linkage at the time of function enhancement, so that it is possible to reduce the number of ports of the cloud environment and reduce the development cost. Secondly, by fixedly using the common API as a port, it is possible to use the port for Internet of Things (IoT) hardware. Thirdly, the web application server 10 does not need information on a linked function. In other words, the web application server 10 needs only device information (hardware information or the like) when receiving data as a virtual device, so that it is possible to reduce time and effort for linkage. Fourthly, it is possible to generate a virtual device corresponding to a plurality of kinds of software processing from a single device. Fifthly, if storage and display are performed while associating the measurement value and the calculated value of the device, in some cases, re-calculations may be needed when a calculation means or a display means is changed; however, by separately handling the measurement value and the calculated value while adopting the calculated value as the measurement value of the virtual device, it becomes possible to easily perform re-calculations and re-construction. As described above, the information processing system 100 is able to efficiently enhance functions of the cloud environment.
A functional configuration of each of the apparatuses included in the information processing system 100 illustrated in
As illustrated in
Meanwhile, the web application server 10 is not limited to a server apparatus that is constructed in the cloud environment, but may be a physical server, a virtual machine, a container, or the like.
A configuration example of the web application server that is an information management apparatus will be described below with reference to
The communication unit 11 controls data communication with a different apparatus. For example, the communication unit 11 performs data communication with each of communication apparatuses via a router or the like. Further, the communication unit 11 is able to perform data communication with a terminal of an operator (not illustrated).
The storage unit 12 stores therein various kinds of information that are referred to when the control unit 13 operates and various kinds of information that are acquired when the control unit 13 operates. The storage unit 12 includes a measurement data storage unit 12a and a calculated data storage unit 12b. Here, the storage unit 12 may be implemented by, for example, a semiconductor memory device, such as a random access memory (RAM) or a flash memory, or a storage device, such as a hard disk or an optical disk. Meanwhile, in the example illustrated in
The measurement data storage unit 12a stores therein the measurement data that is transmitted from the plant apparatuses 30. One example of information that is stored in the measurement data storage unit 12a will be described below with reference to
The “apparatus identification information” indicates identification information for identifying the plant apparatus 30, and is, for example, an identification number of the plant apparatus 30. The “time” indicates a time at which the plant apparatus 30 acquires data, and is represented by, for example, date-month-year and second-minute-hour. The “measurement data” indicates intensity of the data that is acquired by the plant apparatus 30, and is, for example, fluid pressure, flow velocity, temperature, or the like.
Specifically,
Meanwhile, the measurement data storage unit 12a may be set in a storage area dedicated for a virtual device that is constructed by a first setting unit 13b of the control unit 13 to be described later.
The calculated data storage unit 12b stores therein the calculated data that is transmitted from the AI application server 20. One example of information that is stored in the calculated data storage unit 12b will be described below with reference to
The “apparatus identification information” indicates identification information for identifying the plant apparatus 30, and is, for example, the identification number of the plant apparatus 30. The “time” indicates a time at which the plant apparatus 30 acquires data, and is represented by, for example, date-month-year and second-minute-hour. The “calculated data” indicates intensity of a score that is calculated from the data that is acquired by the plant apparatus 30, and is, for example, a score value that indicates a degree of risk of a process of a plant, or the like.
Specifically,
Here, the pieces of calculated data 12b-A1, 12b-A2, 12b-A3, etc. are pieces of data that are subjected to different calculation processes from the measurement data 12a-A that is collected by the plant apparatus 30A. For example, the calculated data 12b-A1 is data that is subjected to a calculation process by the AI function 1, the calculated data 12b-A2 is data that is subjected to a calculation process by the AI function 2, and the calculated data 12b-A3 is data that is subjected to a calculation process by the AI function. Further, similarly, the pieces of calculated data 12b-B1, 12b-B2, 12b-B3, etc. are pieces of data that are subjected to different calculation processes from the measurement data 12a-B that is collected by the plant apparatus 30B, and the pieces of calculated data 12b-C1, 12b-C2, 12b-C3, etc. are pieces of data that are subjected to different calculation processes from the measurement data 12a-C that is collected by the plant apparatuses 30C.
Meanwhile, the calculated data storage unit 12b may be set in a storage area dedicated for a virtual device that is constructed by a second setting unit 13c of the control unit 13 to be described later.
The control unit 13 controls the entire web application server 10. The control unit 13 includes a reception unit 13a, the first setting unit 13b, the second setting unit 13c, a transmission unit 13d, an acquisition unit 13e, and a display unit 13f. Here, the control unit 13 may be implemented by, for example, an electronic circuit, such as a central processing unit (CPU) or a micro processing unit (MPU), or an integrated circuit, such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).
The reception unit 13a receives measurement data that is collected by a device. For example, the reception unit 13a receives measurement data in the JSON format from the plant apparatuses 30, such as a sensor apparatus, a gateway apparatus, and a control apparatus, that are installed in a plant. Meanwhile, the reception unit 13a stores the received measurement data in the measurement data storage unit 12a.
A specific example will be described below. The reception unit 13a receives the measurement data 12a-A {time T001: the measurement data A001, time T002: the measurement data A002, time T003: the measurement data A003, etc.} collected by the plant apparatus 30A, the measurement data 12a-B {time T001: the measurement data B001, time T002: the measurement data B002, time T003: the measurement data B003, etc.} collected by the plant apparatus 30B, the measurement data 12a-C {time T001: the measurement data C001, time T002: the measurement data C002, time T003: the measurement data C003, etc.} collected by the plant apparatus 30C, and the like.
The first setting unit 13b sets a first virtual device corresponding to the measurement data. At this time, the first setting unit 13b generates the first virtual device on a cloud system by using a resource that is included in the cloud system.
A specific example will be described below. The first setting unit 13b constructs, on the cloud environment, the virtual device 30A-V1 that corresponds to the measurement data 12a-A collected by the plant apparatus a virtual device 30B-V1 that corresponds to the measurement data 12a-B collected by the plant apparatuses a virtual device 30C-V1 that corresponds to the measurement data 12a-C collected by the plant apparatus and the like.
The second setting unit 13c, when a calculation apparatus that performs a predetermined calculation receives the measurement data and when acquiring first calculated data that is generated from the measurement data, sets a second virtual device corresponding to the first calculated data. At this time, the second setting unit 13c generates the second virtual device on the cloud system by using a resource that is included in the cloud system.
A specific example will be described below. The second setting unit 13c, when transmitting the measurement data 12a-A collected by the plant apparatus 30A to the AI application server 20-1 and acquiring the calculated data 12b-A1 that is generated by using the AI function 1 included in the AI application server 20-1, constructs the virtual device 30A-V2 that corresponds to the calculated data 12b-A1. At this time, the second setting unit 13c may construct the virtual device 30A-V2 before receiving the measurement data 12a-A from the plant apparatus 30A, or may construct the virtual device 30A-V2 before transmitting the measurement data 12a-A to the AI application server 20-1.
Further, when acquiring second calculated data that is generated from the measurement data by the calculation apparatus, the second setting unit 13c sets a third virtual device that corresponds to the second calculated data. Furthermore, when acquiring third calculated data that is generated from the measurement data by the calculation apparatus, the second setting unit 13c sets a fourth virtual device that corresponds to the third calculated data.
A specific example will be described below. The second setting unit 13c, when acquiring the calculated data 12b-A2 that is generated by using the AI function 2 included in the AI application server 20-2 from the measurement data 12a-A collected by the plant apparatus 30A, constructs the virtual device 30A-V3 that corresponds to the calculated data 12b-A2. Similarly, when acquiring the calculated data 12b-A3 that is generated by using an AI function 3 included in an AI application server 20-3 from the measurement data 12a-A collected by the plant apparatus 30A, the second setting unit 13c constructs a virtual device 30A-V4 that corresponds to the calculated data 12b-A3. Specifically, the second setting unit 13c generates the corresponding virtual device 30-V for each of the plant apparatuses 30 every time the calculation process is performed. Meanwhile, the second setting unit 13c is also able to generate a virtual device corresponding to calculated data that is generated by further performing a calculation process on the calculated data, instead of the calculated data generated from the measurement data.
The transmission unit 13d transmits the measurement data that is associated with the first virtual device to the calculation apparatus by using a common API that is shared between the information management apparatus and the calculation apparatus. For example, the transmission unit 13d transmits the measurement data in the CSV format to the AI application server 20 by using a common API that enables data transmission and reception between the web application server 10 and the AI application server 20. At this time, the transmission unit 13d transmits the measurement data to the AI application server 20 via the virtual device 30-V corresponding to the measurement data.
A specific example will be described below. The transmission unit 13d transmits the measurement data 12a-A collected by the plant apparatus 30A to each of the AI application server 20-1, the AI application server 20-2, the AI application server 20-3, etc. via the virtual device by using the common API.
The acquisition unit 13e acquires the calculated data calculated by the calculation apparatus, by using a common API. For example, the acquisition unit 13e acquires the calculated data in the JSON format from the AI application server 20 by using a common API that enables data transmission and reception between the web application server 10 and the AI application server 20. At this time, the acquisition unit 13e acquires the calculated data from the AI application server 20 via the virtual device 30-V corresponding to the calculated data. Meanwhile, the acquisition unit 13e stores the acquired calculated data in the calculated data storage unit 12b.
A specific example will be described below. The acquisition unit 13e acquires the calculated data 12b-A1 from the AI application server 20-1 via the virtual device by using the common API. Further, the acquisition unit 13e acquires the calculated data 12b-A2 from the AI application server 20-2 via the virtual device 30A-V3 by using the common API. Furthermore, the acquisition unit 13e acquires the calculated data 12b-A3 from the AI application server 20-3 via the virtual device 30A-V4 by using the common API.
At this time, the acquisition unit 13e is able to acquire the calculated data via the virtual device 30-V based on device information (hardware information, tag information, or network map information).
The display unit 13f displays the first virtual device corresponding to the measurement data and the second virtual device corresponding to the first calculated data. Further, the display unit 13f displays data associated with the virtual device that is selected from the first virtual device and the second virtual device that are displayed.
A specific example of a display screen that is output by the display unit 13f will be described below with reference to
In the example illustrated in
A configuration example of the AI application server that is an information management apparatus will be described below with reference to
The communication unit 21 controls data communication with a different apparatus. For example, the communication unit 21 performs data communication with each of communication apparatuses via a router or the like. Further, the communication unit 21 performs data communication with a terminal of an operator (not illustrated).
The storage unit 22 stores therein various kinds of information that are referred to when the control unit 23 operates and various kinds of information that are acquired when the control unit 23 operates. The storage unit 22 includes an AI function data storage unit 22a. Here, the storage unit 22 may be implemented by, for example, a semiconductor memory device, such as a RAM or a flash memory, or a storage apparatus, such as a hard disk or an optical disk. Meanwhile, in the example illustrated in
The AI function data storage unit 22a stores therein data related to an AI application that is executed by the AI application server 20. One example of information that is stored in the AI function data storage unit 22a will be described below with reference to
The “AI identification information” indicates identification information for identifying the AI function, and is, for example, an identification number of the AI function. The “AI function” indicates a trained machine learning model, and is, for example, a machine learning model that outputs calculated data in response to input of measurement data. The “application information” indicates identification information for identifying an AI application that generates the calculated data from the measurement data, and is, for example, an identification number of the AI application.
Specifically,
The control unit 23 controls the entire AI application server 20. The control unit 23 includes a reception unit 23a, a calculation unit 23b, and a transmission unit 23c. Here, the control unit 23 may be implemented by, for example, an electronic circuit, such as a CPU or an MPU, or an integrated circuit, such as an ASIC or an FPGA.
The reception unit 23a receives the measurement data that is associated with the first virtual device set by the information management apparatus and that is collected by the device from the information management apparatus. For example, the reception unit 23a receives the measurement data from the web application server 10 by using a common API that enables data transmission and reception between the web application server 10 and the AI application server 20. At this time, the reception unit 23a receives the measurement data from the web application server 10 via the virtual device 30-V that is set by the web application server 10 and that corresponds to the measurement data.
A specific example will be described below. The reception unit 23a receives the measurement data 12a-A that is collected by the plant apparatus 30A, from the web application server 10 via the virtual device 30A-V1 by using the common API.
The calculation unit 23b generates the first calculated data by performing a predetermined calculation on the measurement data. For example, the calculation unit 23b inputs the measurement data to the AI function that is stored in the storage unit 22, and generates calculated data based on output data.
A specific example will be described below. The calculation unit 23b inputs the measurement data 12a-A collected by the plant apparatus 30A to the AI function 1, and adopts output data as the calculated data 12b-A1.
The transmission unit 23c transmits the first calculated data as data that is associated with the second virtual device set by the information management apparatus to the information management apparatus. For example, the transmission unit 23c transmits the calculated data to the web application server 10 by using a common API that enables data transmission and reception between the web application server 10 and the AI application server 20. At this time, the transmission unit 23c transmits the calculated data to the web application server 10 via the virtual device 30-V that corresponds to the calculated data.
A specific example will be described below. The transmission unit 23c transmits the calculated data 12b-A1 to the web application server 10 via the virtual device by using the common API.
At this time, the transmission unit 23c is able to transmit the calculated data via the virtual device 30-V based on device information (hardware information, tag information, or network map information).
A configuration example of the plant apparatus 30 will be described below with reference to
The collection unit 31 collects data. For example, the collection unit 31 collects measurement data that is data of a plant. Further, the collection unit 31 transmits the data. For example, the collection unit 31 transmits the collected measurement data to the web application server 10.
The flow of a process performed by the information processing system 100 according to one embodiment will be described below with reference to
The plant apparatus 30 transmits the measurement data to the web application server 10 (Step S101). For example, the plant apparatus 30 transmits measurement data, such as a sensor value, that is collected by the plant to the web application server 10.
The web application server 10 sets the virtual device 30-V1 corresponding to the measurement data (Step S102). For example, the virtual device 30-V1 corresponding to the measurement data of the plant apparatus 30 is generated on a resource of the cloud environment. At this time, the web application server 10 stores the measurement data in a storage area (Step S103).
Further, the web application server 10 sets the virtual device 30-V2 corresponding to the calculated data (Step S104). For example, the virtual device 30-V2 corresponding to the calculated data of the plant apparatuses 30 is generated on a resource of the cloud environment.
The web application server 10 transmits the measurement data to the AI application server 20 (Step S105). At this time, the virtual device 30-V1 transmits the measurement data to the AI application server 20 by using the external linkage common API.
The AI application server 20 generates the calculated data from the measurement data (Step S106). For example, the AI application server 20 generates the calculated data 1 that is output by inputting the measurement data to the AI function 1.
The AI application server 20 transmits the calculated data to the web application server 10 (Step S107). At this time, the AI application server 20 transmits the calculated data to the web application server 10 by using the external linkage common API. Further, the web application server 10 stores the calculated data in a storage area (Step S108).
The web application server 10 acquires the measurement data and the calculated data from the storage area (Step S109). Further, the web application server 10 displays the measurement data and the calculated data (Step S110). Furthermore, when the measurement data and the calculated data are not needed, the web application server 10 is able to delete the virtual device 30-V so as not to display the data (Step S111).
When different kinds of calculated data are to be generated from the same measurement data by using different AI functions, the processes from Steps S104 to S108 are repeated every time a different calculation is performed. Specifically, the virtual device 30-V2, the virtual device 30-V3, a virtual device 30-V4, etc. that respectively correspond to the calculated data 1, the calculated data 2, the calculated data 3, etc. are generated.
Effects of the embodiment will be described below. Effects 1 to 6 corresponding to processing according to one embodiment will be described below.
Firstly, in the processing according to one embodiment as described above, the web application server 10 receives the measurement data that is collected by the plant apparatus 30, sets the virtual device 30-V1 corresponding to the measurement data, and when the AI application server that performs a predetermined calculation receives the measurement data and when acquiring the calculated data 1 that is generated from the measurement data, sets the virtual device 30-V2 corresponding to the calculated data 1. Therefore, in this processing, it is possible to efficiently manage a calculated value that is obtained from a measurement value that is collected by a device.
Secondly, in the processing according to one embodiment as described above, the web application server when acquiring the calculated data 2 that is generated from the measurement data by the AI application server 20-2, sets the virtual device 30-V3 corresponding to the calculated data 2, and when acquiring the calculated data 3 that is generated from the measurement data by the AI application server 20-3, sets the virtual device 30-V4 corresponding to the calculated data 3. Therefore, in this processing, a virtual machine is constructed every time a calculated value is added, so that it is possible to efficiently manage the calculated value that is obtained from the measurement value collected by the device.
Thirdly, in the processing according to one embodiment as described above, the web application server 10 generates the virtual device 30-V1 on a cloud system by using a resource included in the cloud system, and generates the virtual device 30-V2 on the cloud system by using a resource included in the cloud system. Therefore, in this processing, by simplifying function enhancement in the cloud environment, it is possible to efficiently manage the calculated value that is obtained from the measurement value collected by the device.
Fourthly, in the processing according to one embodiment as described above, the web application server transmits the measurement data that is associated with the virtual device 30-V1 to the AI application server 20 by using a common API that is shared between the web application server 10 and the AI application server 20, and acquires calculated data that is generated by the AI application server 20 by using the common API. Therefore, in this processing, there is no need to associate a device to be selected at the time of function enhancement, so that it is possible to efficiently manage the calculated value that is obtained from the measurement value collected by the device.
Fifthly, in the processing according to one embodiment as described above, the web application server 10 displays the virtual device 30-V1 corresponding to the measurement data and the virtual device 30-V2 corresponding to the calculated data 1, and displays data that is associated with the virtual device 30-V that is selected from the virtual device 30-V1 and the virtual device 30-V2 that are displayed. Therefore, in this processing, the administrator of the plant is able to monitor the needed data, so that it is possible to efficiently manage the calculated value that is obtained from the measurement value collected by the device.
Sixthly, in the processing according to one embodiment as described above, the AI application server 20 receives, from the web application server 10, the measurement data that is associated with the virtual device 30-V1 set by the web application server 10 and that is collected by the device, generates the calculated data 1 by performing a predetermined calculation on the measurement data, and transmits the calculated data 1 as data that is associated with the virtual device 30-V2 set by the web application server 10 to the web application server 10. Therefore, in this processing, there is no need to develop an interface dedicated for plant software processing, so that it is possible to efficiently manage the calculated value that is obtained from the measurement value collected by the device.
Processing procedures, control procedures, specific names, and information including various kinds of data and parameters described in the specifications and the drawings as described above may be arbitrarily changed unless otherwise specified.
Further, the components of each of the apparatuses illustrated in the drawings are functionally conceptual and do not necessarily have to be physically configured in the manner illustrated in the drawings. In other words, specific forms of distribution and integration of the apparatuses are not limited to those illustrated in the drawings. That is, all or part of the apparatuses may be functionally or physically distributed or integrated in arbitrary units depending on various loads or use conditions.
Furthermore, for each processing function performed by each of the apparatuses, all or any part of the processing function may be implemented by a CPU and a program analyzed and executed by the CPU or may be implemented as hardware by wired logic.
A hardware configuration example of the web application server 10 that is an information processing apparatus will be described below. Meanwhile, other apparatuses, such as the AI application server 20, may have the same hardware configuration.
The communication apparatus 10a is a network interface card or the like and performs communication with a different server. The HDD 10b stores therein a program that causes the functions illustrated in
The processor 10d reads a program that performs the same process as each of the processing units illustrated in
In this manner, the web application server 10 operates as an apparatus that performs various kinds of processing methods by reading and executing a program. Further, the web application server 10 is able to implement the same functions as the embodiment as described above by causing a medium reading apparatus to read the above-described program from a recording medium and execute the read program. Meanwhile, the program described in the other embodiments need not always be executed by the web application server 10. For example, the present invention is similarly applicable to a case in which a different computer or a server performs a program and a case in which the different computer and the server execute the program in a cooperative manner.
The program may be distributed via a network, such as the Internet. Further, the program may be recorded in a computer readable recording medium, such as a hard disk, a flexible disk (FD), a compact disc-read only memory (CD-ROM), a magneto-optical disk (MO), or a digital versatile disc (DVD), and may be executed by being read from the recording medium by a computer.
Examples of combinations of the features of the disclosed technology are described below.
According to the present invention, it is possible to efficiently manage a calculated value that is obtained from a measurement value collected by a device.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-121939 | Jul 2022 | JP | national |
