WO2019202724A1

WO2019202724A1 - Energy data providing system, energy data providing method, and energy data providing program

Info

Publication number: WO2019202724A1
Application number: PCT/JP2018/016250
Authority: WO
Inventors: 知礼八子; 将仁谷口
Original assignee: 株式会社ウフル
Priority date: 2018-04-20
Filing date: 2018-04-20
Publication date: 2019-10-24

Abstract

[Problem] To promote use of operation data of an IoT device by providing the operation data after changing the operation data into data required for a third party with use of a machine-learned model. [Solution] An energy data providing system 10 is constituted by devices 12A to 12C such as air-conditioner, a server 30, and application-providing computers 50A to 50C. The devices 12A to 12C have operation data 18A to 18C, respectively. The operation data 18A to 18C are transmitted to the server 30 in association with users of the devices 12A to 12C. The application-providing computers 50A to 50C have corresponding machine-learned models 58A, 58B, respectively, and the server 30 converts the obtained operation data 12A to 12C into energy data 60A, 60B by the machine-learned models 58A, 58B. The energy data 60A, 60B are provided to different terminals 80, 90 of a third party than those of a manufacturer of the devices 12A to 12C.

Description

Energy data providing system, energy data providing method, and energy data providing program

The present invention relates to a technique for converting machine operation data using a machine-learned model, and is used in the field of IoT (Internet of Things), for example.

In the IoT era, big data is being acquired from various IoT devices. For example, Patent Document 1 discloses a technique for estimating the amount of electric power used by an outdoor unit in a multi-air conditioner system from actual data including the outdoor unit frequency and the indoor unit operation rate when the multi-air conditioner is in operation.

JP 2016-217645 A

However, for example, data indicating the operating status of an air conditioner or the like as disclosed in Patent Document 1 can be acquired by a real estate company that manages a facility such as a building in which an air conditioner is installed, or a user of the facility. , Utilization in a form that can be provided to third parties is not progressing.

The present invention aims to promote utilization by converting IoT device operation data into data necessary for a third party using a machine-learned model.

The present invention provides an acquisition means for acquiring operation data from a device, a conversion means for converting the operation data into energy data, a providing means for providing the energy data to a third party different from the manufacturer of the device, An energy data providing system is provided.

Further, the present invention includes a step of obtaining operation data from a device, a step of converting the operation data into energy data, and a step of providing the energy data to a third party different from the manufacturer of the device. Provide a method for providing energy data.

Furthermore, the present invention provides a computer for obtaining operation data from a device, converting the operation data into energy data, and providing the energy data to a third party different from the device manufacturer. And provide an energy data provision program for executing

According to the present invention, big data such as operational data acquired from an IoT device is provided by converting operational data of the IoT device into energy data necessary for a third party using a machine-learned model. Can be promoted.

It is a schematic diagram which shows an example of the whole structure of the energy data provision system which concerns on embodiment. It is a figure which shows an example of the hardware constitutions of an apparatus. It is a figure which shows an example of operation data. It is a figure which shows an example of the hardware constitutions of a server. It is a figure which shows an example of the hardware constitutions of an application provision computer. It is a figure which shows an example of a function structure of the whole energy data provision system. It is a figure which shows an example of energy data. It is a flowchart which shows an example of the process sequence in the energy data provision system side. It is a flowchart of an example of the process sequence in the third party side. It is a figure which shows an example of the display screen displayed on a third party's terminal.

<Overall Configuration> FIG. 1 is an example of an energy data providing system according to this embodiment. The energy data providing system 100 converts operation data of a device such as an air conditioner into energy data consumed by the device using a machine-learned model, and provides it to a third party different from the device manufacturer.

The energy data providing system 100 includes devices 12A to 12C installed in facilities 10A to 10C such as buildings, a server 30, application providing computers 50A to 50C, and

third party terminals

80 and 90. These are connected via a network 70 including the Internet, for example. Note that the number of devices, the number of application providing computers, and the number of third party terminals illustrated here are merely examples, and the present invention is not limited thereto.

FIG. 2 is an example of the hardware configuration of the device 12A. Although the device 12A will be described here, the other devices 12B and 12C have the same configuration. The device 12A includes a processor 12, a memory 16, a storage 18, and a communication unit 20, which are connected by a bus (not shown). The processor 14 is configured by, for example, a CPU (Central Processing Unit), and performs various processes by reading and executing various programs stored in the memory 16.

The memory 16 stores a program executed by the CPU 14, and is constituted by, for example, a ROM (Read Only Memory) or a RAM (Random Access Memory). The storage 18 stores various data including the operation data 18A of the device 12A, a control program (not shown), and the like. The communication unit 20 performs data communication with the server 30 or the like via the network 70.

FIG. 3 is a diagram showing an example of operation data. FIG. 3A shows operation data 18A of the device 12A (◯ × 1F east side air conditioner of the building). The operation data 18A includes “[Equipment Category] Air Conditioner”, “[Model] DAI-05”, “[Product Serial Number 33333333]”, “[Manufacturer] Company A”, “[Installation Location] 1F East”, “[ Log] ... "is included.

FIG. 3 (B) shows the operation data 18B of the device 12B (Ox building 1F west air conditioner). The operation data 18B also includes [device category], [model], [product serial number], [manufacturer], [installation location], and [log]. FIG. 3 (C) shows the operation data 18C of the device 12C (Ox Building 2F East Air Conditioner), [Device Category], [Model], [Product Serial Number], [Manufacturer], [Installation Location] ] And [Log] are included. Here, the [log] includes information such as [date / time] 2018/3/7 8: 32-21: 10, [setting] heating, [setting temperature] 22 degrees, and the like.

FIG. 4 is a diagram illustrating an example of a hardware configuration of the server 30. The server 30 acquires the operation data 18A to 18C from the devices 12A to 12C and provides them to the application providing computers 50A to 50C, and manages the users and the operation data of the devices 12A to 12B.

The server 30 includes a processor 32, a memory 34, a storage 38, and a communication unit 46, which are connected by a bus (not shown). The processor 32 is configured by, for example, a CPU (Central Processing Unit), and performs various processes by reading and executing various programs stored in the memory 34. The memory 34 stores a program executed by the CPU 14, and is configured by, for example, a ROM (Read Only Memory) or a RAM (Random Access Memory).

The storage 36 stores various data and programs. In this example, the storage 36 stores a management program 38, user information 40 of the devices 12A to 12B, operation data 42 acquired from the devices 12A to 12C, and machine-learned model provider information 44. The management program 38 acquires the operation data 18A to 18C from the devices 12A to 12C and provides them to the application providing computers 50A to 50C. It also manages the users and operating data of the devices 12A-12B.

The stored and learned model providing source information 44 includes an address “http: //www.*******” indicating the location where the machine learned models 58A and 58B of the application providing computers 50A to 50C are stored. The communication unit 46 performs data communication with the server 30,

third party terminals

80, 90, and the like via the network 70.

FIG. 5 is a diagram illustrating an example of a hardware configuration of the application providing computer 50A. The hardware configuration of the application providing computer 50B is the same. In response to a request from the

third party terminals

80 and 90, the application providing computer 50A converts the operation data into energy data based on the operation data 18A to 18B acquired from the server 30, and the

third party terminals

80 and 90 To send to. The application providing computer 50A is owned by an application vendor or the manufacturer of the devices 12A to 12C.

The application providing computer 50A includes a processor 52, a memory 54, a storage 56, and a communication unit 62, which are connected by a bus (not shown). Since the functions of the processor 52, the memory 54, and the communication unit 62 are the same as those of the server 30, description thereof will be omitted.

The storage 56 stores various data and programs. In this example, the storage 56 stores a machine learned model 58A and energy data 60A converted by the machine learned model 58A. In this example, the machine learned model 58A is a power consumption calculation application, and converts the acquired operation data 18A to 18C into energy data. The machine-learned model 58A is realized by, for example, an application program provided by an application vendor or a device manufacturer. In addition, a management program for constructing the energy data providing system 100 in cooperation with the server 30 may be stored.

FIG. 7A shows an example of energy data 60A converted by the machine-learned model 58A. In the illustrated example, energy data A of [2F east side power consumption], [date / time] 2018/3/7, and [power consumption / day] 3 kwh is shown. The energy data 60 is transmitted to the third party terminal 80 (or 90), and the third party terminal 80 confirms the energy data 60A. The third party has an impression that “the yesterday was 3 kwh, and the power consumption of the air conditioner was large”, and for example, it can promote awareness of power saving after the next day. Here, the third party may be a person other than the manufacturer of the devices 12A to 12C, and may be a user of the device 12A, for example.

FIG. 7B shows an example of energy data 60B converted by the machine-learned model 58B of another application providing computer 50B. In this example, the machine-learned model 58B is a proposal application for the layout and number of installed air conditioners, and converts the acquired operation data 18A to 18C into energy data.

In the example of Fig. 7 (B), energy data B is shown as "2F cooling efficiency is not good. Power consumption will be reduced by 0.8kwh, so air conditioning should be installed on the west side of 2F." Yes. This energy data is transmitted to the third party terminal 90 (or 80), and the third party terminal 90 confirms the energy data 60B. On the third party side, it is possible to promote awareness such as “Is it possible to install an air conditioner on the 2F west side?”. Here, the third party may be an administrator of the facility 10A, for example.

<Functional Configuration> FIG. 6 is a diagram illustrating an example of a mechanism configuration of the entire energy data providing system 100 according to the present embodiment. The energy data providing system 100 includes an operation data acquiring unit 102, a conversion unit 104, an energy data providing unit 106, a selection receiving unit 108, an evaluation input receiving unit 110, and a payment process receiving unit 112. These functions are realized by executing various programs of the devices 12A to 12C, the server 30, and the application providing computers 50A to 50C and data communication between them.

The operation data acquisition unit 102 acquires operation data 18A to 18C from the devices 12A to 12C. The conversion means 104 converts the acquired operation data 18A to 18C into energy data, and is realized by an application program provided by an application vendor or a device manufacturer.

The energy data providing means 106 provides the energy data to a third party different from the manufacturer of the devices 12A to 12C. The selection accepting unit 108 accepts selection of an application (conversion unit) from a third party or selection of operation data (device) to be converted.

The evaluation input receiving unit 110 receives an input of evaluation of the conversion unit (app) from a third party. When the third party selects the operation data, the payment processing reception unit 112 collects the operation data usage fee from the third party and receives, for example, a payment process for paying the operation data provider. Further, when a third party tries to convert the operation data, the payment process accepting unit 112 collects a conversion usage fee from the third party and accepts, for example, a payment process for paying to the conversion means provider. Note that the payee is an example and is not limited thereto.

<Operation>... FIG. 8 is a flowchart showing a processing procedure on the energy data providing system 100 side. Control units in the devices 12A to 12C, such as air conditioners, acquire device operation data 18A to 18C (step S10). Since there may be a plurality of devices, data may be collected for each user in a device group. The control unit of the devices 12A to 12C transmits the operation data 18A to 18C to the server 30 via the communication unit 20, so that the server 10 acquires the operation data 18A to 18C associated with each user ( Step S12).

The server 30 transmits the acquired operation data 18A to 18C to the application providing computers 50A to 50C, and the application providing computers 50A to 50C use the machine-learned models 58A to 58C to convert the operation data 18A to 18C into the energy data 60A. Conversion to ~ 60C (step S14). As the machine-learned models 58A and 58B, those corresponding to the manufacturers and model numbers of the devices 12A to 12C are selected. Further, a third party may freely select the machine-learned models 58A and 58B used for conversion by selecting an application.

The converted energy data 60A to 60C are provided to a third party (step S16). The third party is other than the manufacturer of the devices 12A to 12C. For example, the third party is a user of the devices 12A to 12A, a real estate company or a management company of the facilities 10A to 10C where the devices 12A to 12C are installed. is there. The energy data 60A to 60C may be transmitted directly from the application providing computers 50A to 50C to the third party terminal 80 or may be transmitted via the server 30. The provision of the energy data 60A to 60C may be confirmed in the cloud or may be downloaded.

FIG. 9 shows a flowchart of the third party process. The third party uses, for example, the

terminals

80 and 90 to access the energy data providing service provided by the server 30, and selects the devices 12A to 12C (operation data 18A to 18C) (step S20). For this selection, for example, one device may be selected or a plurality of devices may be selected simultaneously. Alternatively, it is possible to select for each floor or for each facility. Such selection acceptance is realized by the selection acceptance means 108.

FIG. 10 (A) is a diagram showing a display screen 81 of the third party terminal 80, and the display screen 81 displays a button 82 for selecting an air conditioner to be converted into energy data.

When the third party selects the device, the payment processing accepting means 112 performs a payment process of the operating data usage fee (step S22). For example, a payment process to a provider of operating data is accepted. The payment fee at this time is a subscription model that increases or decreases depending on the amount of operating data (the number of selected devices). FIG. 10B is a diagram showing a display screen 83 of the third party terminal 80. The display screen 83 displays the current payment amount and the payee, and also displays an “OK” button 84. Has been. When the third party presses the button 84, the operation data usage fee payment processing is completed. Payment may be made by credit card settlement registered in advance.

Next, a machine learned model to be converted by a third party is selected (step S24). The machine-learned model can be easily selected by selecting an application. The selection of the machine-learned model is realized by the selection receiving unit 108.

When a third party selects a machine-learned model that the third party wants to convert, the payment processing accepting unit 112 performs a conversion fee payment process (step S26). For example, a payment process to a company of an application providing computer having the selected machine-learned model is accepted. The payment fee at this time is increased or decreased depending on the amount of operating data (the number of selected devices). FIG. 10C is a diagram showing a display screen 85 of the third party terminal 80. The display screen 85 displays the current payment amount and the payee, and also displays an “OK” button 86. Has been. When a third party presses the button 86, the conversion fee payment process is completed. The payment of the conversion usage fee may also be made by credit card settlement as described above.

When the payment process is completed, the energy data is displayed on the display unit of the third party terminals 80 and 90 (step S28). The example displayed on the third terminal 80 is illustrated in FIG. 7A described above, and the example displayed on the third party terminal 90 is illustrated in FIG. 7B described above. ing.

When the display of energy data is completed, the app evaluation screen is displayed on the third party terminal. FIG. 10D is a diagram showing a display screen 87 of the third-party terminal 80. The display screen 87 is used for inputting the used application (“application 1” in the illustrated example) and its evaluation. An asterisk 96 is displayed. When the third party increases or decreases the number of stars according to the degree of app satisfaction and inputs an evaluation (step S30), the operation on the

third party terminals

80 and 90 ends. Note that the display of the evaluation input screen is realized by the evaluation input receiving unit 110. It may be in the form of a cloud or a dedicated application.

<Effect> According to the embodiment described above, the energy data providing system 10 includes the operation data acquisition unit 102 that acquires the operation data 18A to 18C of the devices 12A to 12C such as the air conditioners, and the operation data 18A to 18C. Is converted to energy data 60A to 60C, and energy data providing means 106 for providing the energy data 60A to 60C to

terminals

80 and 90 of a third party different from the manufacturer of the devices 12A to 12C. As described above, the operation data of the IoT device is converted into the energy data consumed by the device, and the data is provided to a third party, whereby the utilization of the big data acquired from the IoT device can be promoted.

In addition, according to the present embodiment, since the conversion unit 104 is realized by an application program provided by an application vendor or a device manufacturer, the machine-learned model constituting the conversion unit 104 on the

third party terminals

80 and 90 side. There is no need to own.

Furthermore, according to the present embodiment, by providing the evaluation input receiving means 106 that receives an evaluation input for the application program, the application program can be improved based on the evaluation.

When a third party obtains the operation data of the device when the third party obtains the operation data of the device, the device includes a selection accepting unit 108 that accepts selection of the device to be converted into energy data from the

third party terminals

80 and 90. By providing the payment processing acceptance means 112 for receiving payment processing related to the usage fee according to the amount, the payment destination of the usage fee (for example, the provider of operation data) is encouraged to actively participate in the system, As a result, utilization of operation data can be promoted.

The payment processing accepting unit 112 accepts selection of a device to be converted into energy data from the

third party terminals

80 and 90, and converts the operation data of the device into energy data. In order to accept payment processing related to the conversion fee for the energy data according to the amount of data converted to, the payment fee (e.g., the provider of conversion means) is actively encouraged to participate in the system, and eventually Utilization of operational data can be promoted.

<Modification> The embodiment described above is merely an example, and can be appropriately changed within a range in which the same effect can be obtained. Moreover, the form with which the following modifications were combined may be sufficient.
(1) The number of facilities 10A to 10C, the number of devices 12A to 12C, the number of

application providing computers

50A and 50C, and the number of

third party terminals

80 and 90 shown in the above-described embodiments are examples, and may be increased or decreased appropriately. Is possible.
(2) In the above-described embodiment, the server 30 and the application providing computers 50A to 50C are provided independently. However, this is also an example, and the server 30 holds the machine-learned models 58A and 58B. 30 and the application providing computers 50A to 50C may be integrated. Alternatively, part of the functions of the server 30 may be included in the application providing computers 50A to 50C, or part of the functions of the application providing computers 50A to 50C may be included in the server 30.

(3) The operation data (FIG. 3) and energy data (FIG. 7) shown in the above-described embodiment are examples, and other information may be included. The display screen of the third-party terminal 80 shown in FIG. 10 is also an example, and can be changed as appropriate within a range that exhibits the same effect.
(4) The converted energy data 18A to 18C may be transmitted to the

third party terminals

80 and 90 from the application providing computers 50A to 50C or may be performed via the server 30. Good.
(5) In the above-described embodiment, the conversion means (machine learning completed model) is evaluated by the number of stars.

(6) Supervised learning can be used as the algorithm in the machine-learned models 58A and 58B, but various other known algorithms may be used as the algorithm for machine learning. For example, unsupervised learning, semi-supervised learning, expression learning, subject learning, and the like. Also, other learning algorithms such as data mining and deep learning may be included. These learning algorithms include those using various known techniques or techniques (for example, association rule learning, decision tree learning, genetic programming, support vector machine, functional logic programming, etc.). The storage locations of the machine-learned models 58A and 58B are not limited to the

application providing computers

50A and 50B, but may be stored in the server 30 or other storage that can be connected to the network 70. You may remember.

(7) In the above-described embodiment, the procedure of the process performed on the energy data providing system 100 side (FIG. 8) is an example, and can be changed as appropriate within a range where the same effect is obtained. Moreover, the procedure (FIG. 9) of the process performed on the

third party terminals

80 and 90 side is also an example, and the steps may be interchanged within a range where the same effect is obtained.
(8) The present invention may be provided as a program executed by the server 30 or the application providing computers 50A to 50C. This program may be provided in a state of being recorded on a computer-readable recording medium, or may be downloaded via the network 70.

According to the present invention, operation data is acquired from a device, the operation data is converted into energy data by a conversion means, and the energy data is provided to a third party different from the manufacturer of the device. Therefore, it is useful for promoting the utilization of big data acquired from IoT devices.

10A to 10C: Facility 12A to 12C: Equipment 14: Processor 16: Memory 18: Storage 18A to 18C: Operation data 20: Communication unit 30: Server 32: Processor 34: Memory 36: Storage 38: Management program 40: User information 42: Operation data 44: Machine learning completed model provider information 46: Communication unit 50A to 50C: Application providing computer 52: Processor 54: Memory 56: Storage 58A, 58B: Machine learned

model

60A, 60B: Energy data 62: Communication Unit 70: Network 80, 90:

User terminal

81, 83, 85, 87:

Display screen

82, 84, 86, 88: Button 100: Energy data providing system 102: Operating data acquisition means 104: Conversion means 106: Energy data Provision means 08: selection receiving means 110: evaluation input receiving means 112: payment processing receiving means

Claims

An acquisition means for acquiring operational data from the device;
Conversion means for converting the operation data into energy data;
Providing means for providing the energy data to a third party different from the manufacturer of the device;
An energy data providing system.
The energy data providing system according to claim 1, wherein the conversion means is realized by an application program provided by an application vendor or a manufacturer of the device.
The energy data providing system according to claim 2, further comprising an evaluation input receiving means for receiving an input of evaluation for the application program.
Selection accepting means for accepting selection of the device to be converted into energy data from the third-party terminal,
When a third party obtains the operation data of the device,
From the third party, a payment process accepting unit that accepts a payment process related to a usage fee according to the amount of operating data acquired by the third party,
The energy data providing system according to claim 1, further comprising:
Selection accepting means for accepting selection of the device to be converted into energy data from the third-party terminal,
When operating data of the device is converted into energy data,
From the third party, according to the data amount of the operation data converted into the energy data, payment processing reception means for receiving payment processing related to the conversion fee of the energy data,
The energy data providing system according to claim 1.
Obtaining operational data from the device;
Converting the operational data into energy data;
Providing the energy data to a third party different from the manufacturer of the device;
A method for providing energy data.
On the computer,
Obtaining operational data from the device;
Converting the operational data into energy data;
Providing the energy data to a third party different from the manufacturer of the device;
An energy data provision program to execute