Information processing system, information processing method, and program

Abstract

To make it possible to easily input data necessary for calculating greenhouse gas emission.SOLUTION: An information processing system includes: an emission coefficient storage unit that stores an emission coefficient for calculating greenhouse gas emissions in association with activity specification information that specifies an activity of emitting greenhouse gas; an activity amount input unit that accepts input of an activity amount related to the activity and an item related to the activity amount; an activity estimation unit that estimates the activity specification information by machine learning based on the item; and an emission calculation unit that calculates emissions by multiplying the activity amount by the emission coefficient corresponding to the estimated activity specification information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] Estimation of carbon dioxide emissions has been carried out (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-091900 Summary of the Invention [Problem to be solved by the invention]

[0004] It is time-consuming to register the data required to calculate emissions into the system.

[0005] The present invention has been made in view of the above background, and has an object to make it possible to easily input data required for calculating greenhouse gas emissions. [Means for solving the problem]

[0006] The main invention of the present invention for solving the above problem is an information processing system comprising: an emission coefficient memory unit that stores an emission coefficient for calculating an amount of greenhouse gas emissions in correspondence with activity specification information that specifies an activity that emits greenhouse gas; an activity amount input unit that accepts input of an activity amount related to the activity and items related to the activity amount; an activity estimation unit that estimates the activity specification information by machine learning based on the items; and an emission calculation unit that calculates the emission amount by multiplying the activity amount by the emission coefficient corresponding to the estimated activity specification information.

[0007] Other problems and solutions disclosed in this application will be made clear in the description of the preferred embodiments of the invention and the drawings. Effect of the Invention

[0008] According to the present invention, data required for calculating greenhouse gas emissions can be easily input. [Brief description of the drawings]

[0009] [Figure 1] 1 is a diagram showing an example of the overall configuration of an emission management system according to an embodiment of the present invention; [Diagram 2] 2 is a diagram illustrating an example of a hardware configuration of a management server 2. FIG. [Diagram 3] 2 illustrates an example of the software configuration of a management server 2. FIG. [Figure 4] FIG. 13 is a diagram illustrating the operation of the management server 2. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] <System Overview> An emission management system according to one embodiment of the present invention will be described below. The emission management system of this embodiment is intended to manage greenhouse gas emissions from emitters such as companies. The emission management system of this embodiment accepts input of the activity amount of the emitter or another emitter located upstream or downstream in the emitter's supply chain, and multiplies this by an emission coefficient to calculate the emission amount. The emission management system of this embodiment manages which emission coefficient should be used for which activity amount, making it possible to calculate the emission amount simply by inputting the activity amount.

[0011] 1 is a diagram showing an example of the overall configuration of an emission management system of this embodiment. The emission management system of this embodiment is configured to include a management server 2. The management server 2 is communicably connected to a user terminal 1 via a communication network 3. The communication network 3 is, for example, the Internet, and is constructed by a public telephone line network, a mobile phone line network, a wireless communication path, Ethernet (registered trademark), or the like.

[0012] The user terminal 1 is a computer operated by a user of a waste generating company or the like. The user terminal 1 can be, for example, a smartphone, a tablet computer, a personal computer, or the like. The user can use the user terminal 1 to access the management server 2 and calculate the amount of waste generated.

[0013] The management server 2 is a computer that calculates and manages emissions. The management server 2 may be a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing.

[0014] <Administration Server> FIG. 2 is a diagram showing an example of the hardware configuration of the management server 2. Note that the illustrated configuration is an example, and other configurations may be used. The management server 2 includes a CPU 201, a memory 202, a storage device 203, a communication interface 204, an input device 205, and an output device 206. The storage device 203 is, for example, a hard disk drive, a solid state drive, or a flash memory that stores various data and programs. The communication interface 204 is an interface for connecting to the communication network 3, and is, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line network, a wireless communication device for wireless communication, a USB (Universal Serial Bus) connector or an RS232C connector for serial communication, etc. The input device 205 is, for example, a keyboard, a mouse, a touch panel, a button, a microphone, etc. that input data. The output device 206 is, for example, a display, a printer, a speaker, etc. that output data. Each functional unit of the management server 2 described below is realized by the CPU 201 reading a program stored in the storage device 203 into the memory 202 and executing it, and each storage unit of the management server 2 is realized as part of the storage area provided by the memory 202 and the storage device 203.

[0015] 3 is a diagram showing an example of the software configuration of the management server 2. The management server 2 includes an emission coefficient storage unit 231, a vector information storage unit 232, an activity amount storage unit 233, an emission amount storage unit 234, an activity amount input unit 210, an activity estimation unit 211, an emission coefficient acquisition unit 212, an emission coefficient input unit 213, an emission amount calculation unit 214, and a compilation unit 215.

[0016] The emission coefficient storage unit 231 stores information including emission coefficients for calculating greenhouse gas emissions (hereinafter referred to as emission coefficient information). The emission coefficients may be primary data (data collected by the emitter itself, obtained from direct measurement, or data obtained from calculations based on direct measurement in the first information source) or secondary data (data other than primary data, for example, data standardized (statistically processed) from emissions of multiple companies that provide the same type of product).

[0017] The emission coefficient storage unit 231 can store emissions in association with activities. The emission coefficient storage unit 231 can store information that identifies an activity (activity specification information), the scope of the activity, and an emission coefficient in association with each other. The emission coefficient storage unit 231 can store activity specification information, the scope of the activity, the category of the activity, and an emission coefficient in association with each other. Note that the scope and category of the activity are assumed to be the scope and category of the GHG Protocol. Also, the category may be omitted.

[0018] The activity identification information may be in any format as long as it is information for identifying an activity. For example, if an ID (activity ID) that uniquely identifies an activity is set in data input to the management server 2 (hereinafter, referred to as import data), the activity ID can be used as type identification information.

[0019] The vector information storage unit 232 stores information for identifying an activity. In this embodiment, the information for identifying an activity is vector information obtained by vectorizing words. The vector information storage unit 232 stores the vector information and the activity identification information in association with each other.

[0020] The activity amount storage unit 233 stores the amount of activity. The activity amount storage unit 233 can store a company ID, information specifying the time when the activity was performed (time information), activity specification information, attribute information, and the amount of activity in association with each other. The time information can be set to any period such as a fiscal year, a year, a month, a date, or a date and time range. The attribute information can be various items related to the activity (for example, any items such as a supplier of a product or the like, a related department, or a person in charge).

[0021] The emission amount storage unit 234 stores the calculated greenhouse gas emission amount. The emission amount storage unit 234 can store a company ID, time information, scope, category, and emission amount in association with each other. The scope and category can be the scope and category registered in the classification storage unit 232 described above.

[0022] The activity amount input unit 210 accepts the input of the activity amount. The activity amount is, for example, the number of products produced (pieces), the number of products purchased (pieces), the weight x distance transported by logistics (ton-kilometers), the amount of fuel consumed (liters), and the amount of money (yen). The activity amount input unit 210 accepts the input of time information and the activity amount together with various attribute information related to the activity from the user. The activity amount input unit 210 may receive import data from the user terminal 1. The import data may be, for example, data exported from an ERP system or the like (export data) or data obtained by converting the export data. The import data may be, for example, CSV data, JSON data, or XML data. For example, in CSV data, it is known which item is which type of data, and the type of activity can be identified by what value is entered in which item of the CSV data in the type identification information. In addition, in JSON data, XML data, and the like, the type of item of the set data may be tagged or set in the attribute.

[0023] The activity estimation unit 211 identifies an activity based on an item related to the amount of activity. The activity estimation unit 211 estimates activity identification information by machine learning based on the item. In this embodiment, the activity estimation unit 211 creates vector information by vectorizing the received item, and can select vector information (first vector information) stored in the vector information storage unit 232 according to the distance from the created vector information (second vector information) by referring to the vector information storage unit 232, and can read out activity identification information corresponding to the selected first vector information from the vector information storage unit 232. The activity estimation unit 211 can identify a predetermined number (which may be one) in ascending order of the distance between the first and second vector information, for example.

[0024] The emission coefficient acquisition unit 212 acquires an emission coefficient related to an activity. The emission coefficient acquisition unit 212 can read out an emission coefficient corresponding to a company ID and activity specification information from the emission coefficient storage unit 231. When the emission coefficient is managed by an external system, the emission coefficient acquisition unit 212 may access the external system to acquire the emission coefficient.

[0025] The emission coefficient input unit 213 accepts the input of an emission coefficient. The emission coefficient input unit 213 identifies a company ID indicating an emission entity to which the user belongs (for example, the emission coefficient input unit 213 can accept the input of a company ID. In addition, the management server 2 includes a user information storage unit that stores user information related to the user, and the company ID is set in the user information and the company ID can be acquired from the user information storage unit), accepts input of type identification information and an emission coefficient from the user, and registers the company ID, type identification information, and emission coefficient in the emission coefficient storage unit 231. When an emission coefficient corresponding to the type of activity amount related to the import data is not stored in the emission coefficient storage unit 231, the emission coefficient input unit 213 can, for example, notify the user terminal 1 of that effect and accept the emission coefficient from the user terminal 1.

[0026] The emission calculation unit 214 calculates the emission amount based on the emission coefficient and the amount of activity. The emission calculation unit 214 can calculate the emission amount for each piece of information received from the user (for example, each record included in the import data). The emission calculation unit 214 can calculate the emission amount by multiplying the amount of activity by the emission coefficient corresponding to the activity specification information specified based on the item related to the amount of activity.

[0027] If the unit in which the amount of activity is expressed matches the unit (tCO2 / unit) assumed by the emission coefficient, the emission calculation unit 214 can calculate the amount of emission by multiplying the amount of activity by the emission coefficient. If the units do not match, the emission calculation unit 214 can also calculate the amount of emission after performing unit conversion.

[0028] The emission calculation unit 214 can register the calculated emission amount in the emission amount storage unit 234. The emission calculation unit 214 can register in the emission amount storage unit 234 the company ID, time information such as the current date or time, the scope and category of the calculated emission amount, and the calculated emission amount in association with each other.

[0029] The tallying unit 215 tallys up the emission amount. The tallying unit 215 can tally up the emission amount calculated by the emission amount calculation unit 214 for each scope. The tallying unit 215 can tally up the emission amount calculated by the emission amount calculation unit 214 for each category. The scope and category can be read out from the distribution memory 232, which correspond to the company ID and type-specific information.

[0030] <Operation> FIG. 4 is a diagram illustrating the operation of the management server 2. As shown in FIG.

[0031] The management server 2 receives the amount of activity and items related to the amount of activity from the outside (S301). For example, it can receive upload of CSV data from the user terminal 1 or input to a form. The management server 2 creates vector information by vectorizing the received items (S302), and identifies activity specification information corresponding to the vector information stored in the vector information storage unit 232 that is close in distance from the vectorized vector information (one or more). When identifying multiple pieces of activity specification information, the management server 2 may suggest the activity specification information to the user and have the user select one (or accept input of other activity specification information). The management server 2 reads out the emission coefficient corresponding to the selected activity specification information from the emission coefficient storage unit 231 (S304), and calculates the emission amount by multiplying the amount of activity by the emission coefficient (S305). The management server 2 registers the calculated emission amount in the emission storage unit 234 (S306). Furthermore, the management server 2 can tally up and output the emission amounts registered in the emission amount storage unit 234 (S307).

[0032] In this manner, activity can be estimated from data relating to the amount of activity, and input can be facilitated.

[0033] Although the present embodiment has been described above, the above embodiment is intended to facilitate understanding of the present invention, and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit of the present invention, and equivalents thereof are also included in the present invention.

[0034] For example, in this embodiment, an activity is specified according to the distance of vector information, but the activity may be estimated by setting the vector information as a prompt and providing it to a large-scale language model (LLM).

[0035] Also, a learning model can be created by machine learning using the items as input data and the activity specification information as teacher data. In this case, the activity estimation unit 211 can estimate the activity specification information by providing the received items to the learning model.

[0036] <Disclosures> The present disclosure also includes the following configurations. [Item 1] an emission coefficient storage unit that stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gas; an activity amount input unit that receives an input of an activity amount related to the activity and an item related to the activity amount; an activity estimation unit that estimates the activity specification information by machine learning based on the items; an emission calculation unit that calculates the emission by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; An information processing system comprising: [Item 2] The information processing system according to item 1, A vector information storage unit that stores first vector information obtained by vectorizing the items and the activity specification information in association with each other, the activity estimation unit vectorizes the received items to create second vector information, selects the first vector information according to a distance from the created second vector information, and reads out the activity specification information corresponding to the selected first vector information from the vector information storage unit; An information processing system comprising: [Item 3] Item 2. An information processing system according to the present invention, the activity estimation unit estimates the activity specification information by providing a prompt including the first and second vector information to a large-scale language model; An information processing system comprising: [Item 4] The information processing system according to item 1, a learning model storage unit that stores a learning model created by machine learning using the item and the activity specification information as training data; the activity estimation unit estimates the activity specification information by providing the received item to the learning model; An information processing system comprising: [Item 5] a computer that stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gases, Receiving an input of an activity amount related to the activity and an item related to the activity amount; estimating the activity specification information by machine learning based on the items; calculating the emission amount by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; 2. An information processing method comprising: [Item 6] A computer stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gases, Receiving an input of an activity amount related to the activity and an item related to the activity amount; estimating the activity specification information by machine learning based on the items; calculating the emission amount by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; A program for executing. [Explanation of symbols]

[0037] 1 User terminal 2 Management Server

Claims

1. an emission coefficient storage unit that stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gas; an activity amount input unit that receives an input of an activity amount related to the activity and an item related to the activity amount; an activity estimation unit that estimates the activity specification information by machine learning based on the items; an emission calculation unit that calculates the emission by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; An information processing system comprising:

2. 2. The information processing system according to claim 1, a vector information storage unit that stores first vector information obtained by vectorizing the items and the activity specification information in association with each other; the activity estimation unit vectorizes the received items to create second vector information, selects the first vector information according to a distance from the created second vector information, and reads out the activity specification information corresponding to the selected first vector information from the vector information storage unit; An information processing system comprising:

3. 3. The information processing system according to claim 2, the activity estimation unit estimates the activity specification information by providing a prompt including the first and second vector information to a large-scale language model; An information processing system comprising:

4. 2. The information processing system according to claim 1, a learning model storage unit that stores a learning model created by machine learning using the item and the activity specification information as training data; the activity estimation unit estimates the activity specification information by providing the received item to the learning model; An information processing system comprising:

5. a computer that stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gases, Receiving an input of an activity amount related to the activity and an item related to the activity amount; estimating the activity specification information by machine learning based on the items; calculating the emission amount by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; 2. An information processing method comprising:

6. A computer stores an emission coefficient for calculating an amount of greenhouse gas emissions in association with activity specification information that specifies an activity that emits greenhouse gases, Receiving an input of an activity amount related to the activity and an item related to the activity amount; estimating the activity specification information by machine learning based on the items; calculating the emission amount by multiplying the amount of activity by the emission coefficient corresponding to the estimated activity specification information; A program for executing.

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