Waste disposal service management method, management device, and management program

Abstract

To prevent the convenience of services associated with waste disposal from being impaired and ensure the appropriate operation of the services.SOLUTION: The discharge trend of wastes based on the history of waste discharges by a user of services associated with waste disposal and / or the discharge prediction of the wastes based on the history of commodity purchases by the user are calculated. A demand forecast for the services is calculated using a prediction model that adopts at least one of the discharge trend of the wastes and the discharge prediction of the wastes as a parameter. The level of the services is estimated by a simulation using the demand forecast and the resources inputted to the services as parameters. A notification for proposing a change of behavior of at least one of the waste discharges and the commodity purchases by the user on the basis of the result of comparison of the estimated level of the services with a regulated level, is transmitted to the terminal of the user.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present disclosure relates to a method, an apparatus, and a program for managing services relating to waste (garbage) disposal. [Background technology]

[0002] JP 2021-182456 A discloses a method for managing the collection, transportation, and disposal of waste. This conventional method accumulates information on the type and amount of waste generated by waste generators. Then, based on this accumulated information, the amount of waste generated on a specific day is predicted for each type of waste. The waste collection and transportation company and the waste disposal company each make plans for the collection, transportation, and disposal of waste based on the predicted information.

[0003] JP 2021-179825 A discloses a method for managing vehicles that collect and transport waste. This conventional method receives waste information (size, weight, quantity, etc.) from each terminal of a user who generates waste. Then, the total amount of waste desired to be collected within a specified area is calculated, and a dispatch plan for collection and transportation vehicles to be sent to the specified area is made based on this total amount. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2021-182456 A [Patent Document 2] Patent Publication No. 2021-179825 Summary of the Invention [Problem to be solved by the invention]

[0005] These conventional methods predict future waste discharge patterns based on information on the discharge behavior of waste disposal entities, such as waste generators and users, and make plans for waste collection and transportation based on these discharge patterns. Therefore, while it is expected that the convenience of the series of waste disposal services from collection and transportation to disposal will be improved, it is difficult for waste disposal entities to develop an awareness of reducing the amount of waste generated. Therefore, when it is predicted that the amount of waste generated will exceed the capacity of waste disposal companies, it becomes difficult to make appropriate plans, and there is a possibility that the convenience of the service will be impaired.

[0006] One object of the present disclosure is to provide a technology that can prevent the convenience of waste disposal services from being impaired and enable the services to be operated appropriately. [Means for solving the problem]

[0007] A first aspect of the present disclosure is a method for managing services relating to waste disposal, which has the following features. The method comprises: acquiring at least one of a waste discharge history of a user who uses the service and a product purchase history of the user; Calculating at least one of a waste generation tendency of the user based on the generation history and a waste generation forecast of the user based on the purchase history; calculating a demand forecast for the service using a prediction model having at least one of the waste discharge tendency and the waste discharge forecast as a parameter; estimating a level of the service by a simulation using the demand forecast and resources to be invested in the service as parameters; sending a notification to the user's terminal, the notification suggesting a change in at least one of the user's waste generation and product purchase behavior based on a comparison result between the estimated level of service and a specified level; Includes.

[0008] A second aspect of the present disclosure is an apparatus for managing services relating to waste disposal, and has the following characteristics. The device includes a memory and a processor. The memory stores at least one of a waste discharge history of a user who uses the service and a product purchase history of the user. The processor performs processing based on the data stored in the memory. The processor, Calculating at least one of a waste disposal tendency of the user based on the waste disposal history and a waste disposal forecast of the user based on the purchase history; calculating a demand forecast for the service using a prediction model having at least one of the waste discharge tendency and the waste discharge forecast as a parameter; estimating a level of the service through a simulation using the demand forecast and the resources to be invested in the service as parameters; Based on a comparison result between the estimated level of service and a specified level, a notification is sent to the user's terminal, the notification suggesting a change in at least one of the user's waste generation and product purchase behavior. It is structured as follows.

[0009] A third aspect of the present disclosure is a program for managing services relating to waste disposal, which has the following characteristics. The program is A process of acquiring at least one of a waste discharge history of a user who uses the service and a product purchase history of the user; A process of calculating at least one of a waste discharge tendency of the user based on the discharge history and a waste discharge prediction of the user based on the purchase history; A process of calculating a demand forecast for the service using a prediction model having at least one of the waste discharge tendency and the waste discharge forecast as a parameter; a process of estimating a level of the service by a simulation using the demand forecast and resources to be invested in the service as parameters; A process of transmitting a notification to a terminal of the user, the notification suggesting a change in at least one of the user's behavior regarding waste generation and product purchases, based on a comparison result between the estimated level of service and a specified level; to be executed by the computer. Effect of the Invention

[0010] According to the present disclosure, the level of a waste disposal service is estimated by a simulation using a demand forecast for the service and resources invested in the service as parameters. In addition, a notification is sent to suggest a change in at least one of the user's behavior regarding waste generation and product purchases based on a comparison result between the estimated level and a specified level. This makes it possible to prevent the convenience of the waste disposal service from being impaired and to operate the service appropriately. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram for explaining an overview of services relating to waste disposal. [Diagram 2] FIG. 2 is a diagram for explaining an example of the configuration of the processing facility and the base illustrated in FIG. 1. [Diagram 3] FIG. 13 is a diagram showing an example of a transition in the level of waste disposal services. [Figure 4] FIG. 2 is a diagram illustrating an example of the overall configuration of a waste treatment system including the management server shown in FIG. [Diagram 5] FIG. 2 illustrates an example of a functional configuration of a management server. [Figure 6] 6 is a flowchart showing a flow of processing that is particularly related to the embodiment and is performed by the data processing device shown in FIG. 5. [Figure 7] 7 is a flowchart showing the process flow performed in step S15 of FIG. 6. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals, and the description thereof will be simplified or omitted.

[0013] 1. Overview 1-1. Waste disposal services FIG. 1 is a diagram for explaining an overview of services related to waste disposal (hereinafter also referred to as "waste disposal services" or "disposal services"). FIG. 1 depicts an urban CT, and disposal services are provided in this urban CT. Here, urban CT refers to a physical space in which multiple individuals live their lives by providing multiple services including disposal services. There is no limitation on the size of the urban CT in this disclosure. A so-called smart city is an example of a large-scale urban CT, an underground mall is an example of a medium-scale urban CT, and a large building is an example of a small-scale urban CT.

[0014] FIG. 1 illustrates a management server 1 that manages a processing service, a processing facility 2 of a vendor that provides the processing service, and a base 3 of a user UX that uses the processing service. The management server 1 corresponds to a management device according to an embodiment. In order to manage the processing service, the management server 1 actively or passively collects data (hereinafter also referred to as "vendor data") VND related to the vendor that manages the processing facility 2. The management server 1 also actively or passively collects data (hereinafter also referred to as "user data") USR related to a user UX residing at the base 3. The management server 1 also performs data processing (described below) for managing the waste processing service based on the vendor data VND and the user data USR.

[0015] The treatment facility 2 disposes of the waste WS discharged from the base 3 (including intermediate disposal and final disposal; the same applies below). The total number of treatment facilities 2 is at least one. Examples of vendors that manage the treatment facility 2 include corporations and local governments. As with the total number of treatment facilities 2, there is at least one base 3. Examples of the user UX residing at the base 3 include corporations and natural persons. If the user UX is a corporation, the base 3 is expected to be a business establishment such as a store or facility of this corporation.

[0016] FIG. 2 is a diagram for explaining an example of the configuration of the treatment facility 2 and the base 3. In the example shown in FIG. 2, the treatment facility 2 includes a treatment space 21 and a waiting space 22. In the disposal space 21, containers TB containing waste WS are loaded and unloaded from mobile objects 23. In the treatment space 21, waste WS is removed from the containers TB and disposed of. In the treatment space 21, empty containers TB are also loaded onto the mobile objects 23. A plurality of mobile objects 23 are waiting in the waiting space 22. A vendor terminal (hereinafter also referred to as a "vendor terminal") 24 that manages the treatment facility 2 communicates with each of these mobile objects 23 via a network.

[0017] Each of the mobile bodies 23 collects and transports the container TB. Specifically, the mobile body 23 collects the container TB containing the waste WS from the base 3 according to a command (collection command) from the vendor terminal 24. The mobile body 23 also replenishes an empty container TB at the base 3 according to a command (replenishment command) from the vendor terminal 24. Each of the mobile bodies 23 may or may not have an occupant (e.g., a driver, a worker, etc.) on board. Each of the mobile bodies 23 may have an automatic driving function and may have a function of automatically collecting and automatically replenishing the container TB.

[0018] The vendor terminal 24 manages the collection and replenishment of the container TB by the mobile body 23. The collection and replenishment of the container TB are performed periodically and in response to a request (on-demand) from the base 3. Therefore, the vendor terminal 24 manages the container TB and the mobile body 23 to handle the periodic collection and replenishment of the container TB and the on-demand collection and replenishment of the container TB. To perform this management, data related to the operating status of the container TB and the mobile body 23 is grasped by the vendor terminal 24. Examples of the data related to the operating status include the positions of the container TB and the mobile body 23, the state of the mobile body 23 (for example, moving, waiting, charging, undergoing inspection, collecting the container TB, refilling the container TB, etc.), the cruising distance of the mobile body 23, etc.

[0019] The vendor terminal 24 also manages the disposal of the waste WS in the processing space 21. As with the data on the operating status, data on the disposal status of the waste WS in the processing space 21 is also grasped by the vendor terminal 24. The data on the disposal status is recorded, for example, for each combination of the type of waste WS and the operating status of the equipment for disposing of this type of waste WS. Examples of the types of waste WS include burnable waste, non-burnable waste, and special waste (e.g., recyclable waste, bottles, and cans). Examples of the equipment for disposing of the waste WS include equipment for temporarily storing and sorting the waste WS, equipment for incinerating and dismantling the waste WS, and equipment for treating the ash, exhaust, and wastewater generated in the disposal of the waste WS.

[0020] The data on the operating status of the container TB and the mobile body 23, and the data on the processing status of the waste WS in the processing space 21 are included in the vendor data VND shown in Fig. 1. The data on the operating status and the data on the processing status are examples of resource data input into the waste processing service, and are used for a service simulation (described later).

[0021] Activity spaces 31, 32, and 33 are examples of multiple bases 3. Activity space 31 is the residence of user U1, activity space 32 is the residence of user U2, and activity space 33 is the residence of user U3. Users U1 to U3 are examples of users UX who use the processing service. The activity spaces 31, 32, and 33 are provided with waste spaces 31a, 32a, and 33a, respectively, in which containers TB are placed. These waste spaces are provided, for example, facing the road of the mobile object 23 at each base. At least one container TB is installed in each of the waste spaces 31a to 33a.

[0022] Two or more containers TB corresponding to the types of waste WS may be installed in the waste spaces 31a, 32a, and 33a. The containers TB are configured to be identifiable according to the types of waste WS. For example, the containers TB are colored with an identification color corresponding to the types of waste WS. In another example, an identification mark corresponding to the type of waste WS is attached to the outer surface of the container TB. Examples of the identification mark include a two-dimensional code such as a barcode or a QR code (registered trademark), and an RFID (Radio Frequency Identification) tag.

[0023] The waste spaces 31a, 32a, and 33a are provided with sensors 31b, 32b, and 33b, respectively. Each sensor acquires data on the collection status of waste WS by the container TB installed in each waste space. Examples of data on the collection status include the type of waste WS contained in the container TB, the weight of the waste WS contained in the container TB, the storage rate of the waste WS in the container TB, the residence time of the waste WS contained in the container TB, and the concentration (or odor level) of a specific gas around the container TB. The data acquired by the sensor 31b is transmitted to the terminal 31c of the user U1. The data acquired by the sensor 32b is transmitted to the terminal 32c of the user U2, and the data acquired by the sensor 33b is transmitted to the terminal 33c of the user U3.

[0024] The terminals 31c, 32c, and 33c are, for example, computers (for example, smartphones, tablets, etc.) carried by the users U1, U2, and U3, respectively. The terminals 31c, 32c, and 33c may also be computers provided in the activity spaces 31, 32, and 33, respectively.

[0025] An example of waste WS generated at the site 3 is container packaging for product PD. Representative examples of product PD are consumables such as daily necessities and office supplies, and food, and there are various types of container packaging for product PD. For example, when container packaging is classified based on material and shape, examples include glass bottles, aluminum cans, steel cans, PET bottles, paper container packaging, and plastic container packaging. Liquid consumables and food are mainly enclosed in glass bottles, aluminum cans, steel cans, and PET bottles. Solid consumables and food are mainly enclosed in paper and plastic container packaging.

[0026] Data related to the purchase of a product PD by the user UX is recorded in the user terminal 3Xc (referring to a terminal of the user UX; the same applies below). For example, data on a product PD purchased using a communication function of the user terminal 3Xc is recorded in this user terminal 3Xc. In another example, an image is acquired from a camera installed in a storage space (not shown) such as a refrigerator or warehouse provided at the base 3, and the product PD purchased by the user is identified by recognizing an object contained in this image. As a result, data related to the purchase of the product PD by the user UX is recorded in the user terminal 3Xc.

[0027] Data on the collection status of the waste WS by the sensors 31b, 32b, and 33b, and data on the purchase of the product PD by the users U1, U2, and U3 are included in the user data USR shown in Fig. 1. At least one of the data on the collection status of the waste WS and the data on the purchase of the product PD is used to calculate the discharge trend of the waste WS (described later).

[0028] 1-2. Level of waste disposal services In the embodiment, the level of the waste treatment service (hereinafter also referred to as the "service level") SL is considered. The service level SL can be estimated based on, for example, time elements related to the treatment service, resource elements consumed in the operation of the treatment service, and the like. Examples of time elements include punctuality (for example, the delay time from the scheduled time to the actual time of periodic collection and refilling of the container TB) and immediacy (for example, the waiting time from the requested time to the actual time of collection and refilling of the container TB). The shorter the delay time or waiting time, the higher the service level SL. Examples of resource elements include fuel and electricity for operating the mobile body 23 and the waste treatment facility WS. The lower the fuel consumption rate or electricity consumption rate, the higher the service level SL.

[0029] The elements used to estimate the service level SL are time-related elements. Therefore, the service level SL varies depending on the time (time period). FIG. 3 is a diagram showing an example of the transition of the service level SL. In the example shown in FIG. 3, the service level SL is calculated taking into account the above-mentioned elements, and it can be understood that the service level SL varies depending on the time (time period). This makes it possible to grasp a tendency that, for example, the service level SL is particularly low in the time period from time t1 to t2 and the service level SL is particularly high in the time period from time t3 to t4.

[0030] The management server 1 performs a simulation of the waste disposal service (hereinafter also referred to as "service simulation") in order to estimate the service level SL. In the service simulation, the state of the waste disposal service is simulated based on the resources (service resources) input to the disposal service and the demand forecast for the disposal service. Examples of the service resources include a container TB, a mobile body 23, and disposal facilities for the waste WS. The demand forecast for the waste disposal service is performed based on the waste disposal tendency calculated for each user of the disposal service. The demand forecast and the disposal tendency will be described in detail later.

[0031] 1-3. Suggestions for behavioral change The management server 1 also compares the estimated service level SL (hereinafter also referred to as the "service level SLE") with a specified level Lth in order to maintain the estimated service level SL within a desired range. As the specified level Lth, two types of levels that specify the lower and upper limits of the desired range of the service level SL are exemplified. These two types of levels are, for example, a first level Lth1 and a second level Lth2 (Lth2>Lth1) shown in FIG. 3.

[0032] If the comparison of the service level SLE with the specified level Lth reveals that the service level SLE falls below the specified level Lth (first level Lth1), the management server 1 transmits to the user terminal 3Xc a notification (hereinafter also referred to as a "proposal notification SGG") proposing a change in at least one of the user UX's behaviors of discharging waste WS and purchasing products PD. The user terminal 3Xc to which the proposal notification SGG is transmitted is, for example, a terminal of the user UX that requests the collection and refilling of the container TB containing the waste WS on the date and time (referring to a date and time period; the same applies below) when the service level SLE falls below the specified level Lth.

[0033] When the service level SLE falls below the specified level Lth, it means that the service resources are insufficient for the demand forecast for the processing service. Therefore, the following are examples of the proposal notification SGG. (i) Prompt for a change in the date and time of on-demand collection and replenishment of the container TB (to a date and time other than the date and time at which the service level SLE falls below the specified level Lth). (ii) The user UX is encouraged to purchase alternative products that generate less waste WS than the products PD (consumables, food) that he or she normally purchases. (iii) Encourage people to go out and eat out. When the proposal notification SGG is sent, an incentive (for example, a discount coupon for a processing service fee, a discount coupon for an alternative product, or a discount coupon for a dining out service) that encourages behavior in accordance with the proposal notification SGG may be sent to the user terminal 3Xc.

[0034] Even if it is found that the service level SLE exceeds the specified level Lth (second level Lth2), the management server 1 transmits a proposal notification SGG to the user terminal 3Xc. The user terminal 3Xc to which the proposal notification SGG is transmitted is, for example, a terminal of a user UX that requests collection and refilling of the container TB containing the waste WS on a date and time different from the date and time when the service level SLE exceeds the specified level Lth. The following are examples of the proposal notification SGG. (iv) Prompt for a change in the date and time of on-demand collection and replenishment of the TB (to a date and time when the service level SLE exceeds the specified level Lth). (v) The user UX encourages the purchase of alternative products that generate more waste WS than the products PD (consumables, food) that they normally purchase. When the proposal notification SGG is sent, an incentive (for example, a discount coupon for a processing service fee, a discount coupon for an alternative product) for encouraging an action in accordance with the proposal notification SGG may be sent to the user terminal 3Xc.

[0035] In this manner, in the embodiment, a service simulation is performed to calculate the service level SLE. In the embodiment, a proposal notification SGG is also sent to the user terminal 3Xc according to the result of the comparison between the service level SLE and the specified level Lth. Therefore, it is possible to prevent the convenience of the processing service from being impaired and to maintain the service level SLE within a desirable range. Therefore, it is possible to operate the waste processing service appropriately. Furthermore, as a result of the user UX selecting an action in accordance with the proposal notification SGG, it is also possible to reduce the amount of waste WS discharged from this user UX. Therefore, it is also possible to contribute to maintaining a sustainable society.

[0036] 2. System configuration example 2-1. Overall configuration example Fig. 4 is a diagram illustrating an example of the overall configuration of a waste disposal system including a management server 1. In the example shown in Fig. 4, the waste disposal system includes a vendor terminal 24 and a user terminal 3Xc in addition to the management server 1. The vendor terminal 24 and the user terminal 3Xc communicate with the management server 10 via a communication line network 4. The communication line network 4 is not particularly limited, and a wired or wireless network may be used.

[0037] The management server 1 comprises a data processing device 11 and databases (DB) 12 and 13. The data processing device 11 comprises at least one processor 14 and at least one memory 15. The processor 14 includes a CPU (Central Processing Unit). The memory 15 is a volatile memory such as a DDR memory, and expands various programs used by the processor 14 and temporarily stores various data. The various programs used by the processor 14 include a waste treatment program according to the embodiment. The various data used by the processor 14 includes data stored in the databases 12 and 13.

[0038] The database 12 is formed in a predetermined storage device (e.g., a hard disk, a flash memory). The database 12 stores vendor data VND. The vendor data VND is transmitted from the vendor terminal 24 to the management server 1 via the communication network 4. Examples of the vendor data VND include identification data of the treatment facility 2 and the vendor managing it, data on the operating status of the container TB and the mobile body 23, and data on the treatment status of the waste WS in the treatment space 21.

[0039] Like the database 12, the database 13 is formed in a predetermined storage device. The database 13 stores user data USR. The user data USR is transmitted from the user terminal 3Xc to the management server 1 via the communication network 4. Examples of the user data USR include identification data of the site 3 and the user UX residing therein, data on the collection status of the waste WS acquired from a sensor installed in the waste disposal space of the site 3, and data on the purchase of the product PD by the user UX residing at the site 3.

[0040] 2-2. Example of management server function configuration Fig. 5 is a diagram showing an example of the functional configuration of the management server 1. In the example shown in Fig. 5, the management server 1 includes a WS discharge tendency calculation unit 11a, a PD purchase tendency calculation unit 11b, a PD demand prediction unit 11c, a WS discharge prediction unit 11d, an SV demand prediction unit 11e, an SV simulator 11f, an SL evaluation unit 11g, and an SGG generation unit 11h. These functional blocks shown in Fig. 5 are realized by the processor 14 shown in Fig. 4 executing the waste treatment program in the memory 15 shown in Fig. 4.

[0041] The WS discharge tendency calculation unit 11a calculates the discharge tendency of waste WS for each user and transmits it to the SV demand prediction unit 11e. Examples of the discharge tendency of waste WS include the period when the user UX disposes of consumables (or food), the time from when the consumables (or food) are brought into the activity space 3X (referring to the activity space of the user UX; the same applies below) to when they are disposed of, and the ratio of the weight (or volume) of the consumables (or food) when they are not used to the weight (or volume) of the consumables (or food) when they are disposed of. Another example of the discharge tendency of waste WS is the manner in which the user UX disposes of consumables (or food). Examples of the manner of disposal include, for example, disposing of a container package of a certain consumable (or food) as is, or disposing of several container packages of the same type of consumables (or food) together.

[0042] The waste WS discharge tendency of the user UX is calculated, for example, by machine learning based on the waste WS discharge history data (discharge history D). This discharge history data is generated from data on the collection status of the waste WS acquired from the sensor 3Xb provided in the waste space 3Xa. According to the waste WS discharge history data, the period in which the user UX disposes of consumables (or food) can be calculated.

[0043] In another example, the waste WS discharge tendency of the user UX is calculated based on the waste WS discharge history data and data on the time when the product PD was brought into the activity space 3X. This bring-in time can be estimated, for example, based on an image from a camera separately installed in the activity space 3X. By estimating the bring-in time, the time from when the consumables (or food) were brought into the activity space 3X to when they were discarded can be calculated.

[0044] In another example, the waste WS discharge tendency of the user UX is calculated by combining the discharge history data of the waste WS and the purchase history data (purchase history D) of the product PD. The purchase history data of the product PD is generated from data related to the purchase of the product PD by the user UX. According to the purchase history data of the product PD, it is possible to obtain information on what kind of consumables (or foods) the waste WS is derived from and information on the weight (or volume) of the consumables (or foods) when unused. Therefore, it is possible to calculate the ratio of the weight (or volume) of the consumables (or foods) when discarded to the weight (or volume) of the consumables (or foods) when unused.

[0045] The PD purchasing tendency calculation unit 11b calculates the purchasing tendency of the product PD for each user and transmits it to the PD demand prediction unit 11c. Examples of the purchasing tendency of the product PD include the day of the week and time period when the user UX purchases a certain consumable (or food), the purchase cycle of this consumable (or food), and the weight (or volume) of this consumable (or food) per purchase. Another example of the purchasing tendency of the product PD is the purchasing manner of the consumable (or food) by the user UX. Examples of the purchasing manner include, for example, purchase using the communication function of the user terminal, purchase of the consumable (or food) at a store, and the like.

[0046] The purchasing tendency of the product PD of the user UX is calculated, for example, by machine learning based on the purchase history data of the product PD. This purchase history data is generated, for example, from data of the product PD purchased using the communication function of the user terminal 3Xc. In another example, the purchase history data of the product PD is generated by a recognition process using an image captured by a camera of a storage space such as a refrigerator or a warehouse installed at the base 3 of the user UX.

[0047] The PD demand prediction unit 11c predicts the demand for the product PD for each user based on the purchasing tendency of the product PD received from the PD purchasing tendency calculation unit 11b, and transmits the prediction result to the WS discharge prediction unit 11d. The demand prediction for the product PD is, for example, based on a human model (prediction model) using data indicating the purchasing tendency of the product PD as a parameter. HM This is done by applying the HM 1 is a model of the user UX purchasing a product PD. Human model HM 1 is prepared for each user. Human model HM 1 may be prepared for each user group having the same attributes as the user UX attributes (e.g., age, gender).

[0048] The WS discharge prediction unit 11d predicts the discharge of waste WS for each user based on the demand prediction for the product PD received from the PD demand prediction unit 11c, and transmits the prediction to the SV demand prediction unit 11e. The waste WS discharge prediction is, for example, based on a human model (prediction model) using data indicating the demand prediction for the product PD as a parameter. HM This is done by applying the human model to HM 2 is a model of the user UX's action of discharging waste WS from the product PD. HM 2 is prepared for each user. Human model HM As with 1, human model HM 2 may be prepared for each user group having the same attributes as the user UX attributes.

[0049] The SV demand prediction unit 11e predicts the demand for the processing service (SV) for each user based on at least one of the waste WS discharge tendency received from the WS discharge tendency calculation unit 11a and the waste WS discharge prediction received from the WS discharge prediction unit 11d. Demand for the processing service (SV) is exemplified by demand for periodic collection and replenishment of the container TB, and demand for on-demand collection and replenishment of the container TB. The SV demand prediction unit 11e may predict the demand for periodic collection and replenishment and the demand for on-demand collection and replenishment separately.

[0050] The demand forecast for the processing service is based on a human model (prediction model) using at least one of data showing the waste WS discharge trend and data showing the waste WS discharge forecast as a parameter. HM This is done by applying the human model to the HM 3 is a model of the user UX behavior when using a processing service. Human Model HM 3 is prepared for each user. Human model HM 3 may be prepared for each user group having the same attributes as the user UX attributes.

[0051] The SV simulator 11f performs a service simulation. In the service simulation, for example, service resource data (service resource D) and data indicating the demand forecast for the processing service by the SV demand forecast unit 11e are applied to a service model (prediction model) SM having as parameters, thereby simulating the state of the processing service. Examples of this service resource data include data on the operating status of the container TB and the mobile body 23, and data on the processing status of the waste WS in the processing space 21. The SV simulator 11f also estimates a service level SL by this service simulation, and transmits the service level SLE to the SL evaluation unit 11g.

[0052] The SL evaluation unit 11g compares the service level SLE received from the SV simulator 11f with the specified level Lth. Examples of the specified level Lth include the first level Lth1 and the second level Lth2 shown in FIG. 3. For example, if there is a date and time when the service level SLE is below the first level Lth1, the SL evaluation unit 11g transmits information on this date and time to the SGG generation unit 11h. In another example, if there is a date and time when the service level SLE is above the second level Lth2, the SL evaluation unit 11g transmits information on this date and time to the SGG generation unit 11h.

[0053] When the SGG generating unit 11h receives information on date and time from the SL evaluating unit 11g, the SGG generating unit 11h generates a proposal notification SGG. When generating the proposal notification SGG, a user UX to be the target of the proposal notification SGG is specified. This user UX is, for example, a user who requests collection and refilling of a container TB containing waste WS at a date and time when the service level SLE falls below a first level Lth1. In another example, this user UX is a user who requests collection and refilling of a container TB containing waste WS at a date and time different from the date and time when the service level SLE exceeds a second level Lth2.

[0054] When the user UX that is the target of the suggestion notification SGG is identified, the SGG generation unit 11h generates a suggestion notification SGG to be sent to the terminal of this user UX. For a user UX that requests collection and refilling of a container TB containing waste WS on a date and time when the service level SLE falls below the first level Lth1, the above information (i) to (iii) is generated by referring to data on the collection status of the waste WS by this user UX and data on the purchase of the product PD. By using a similar method, the above information (vi) to (v) is generated for a user UX that requests collection and refilling of a container TB containing waste WS on a date and time different from the date and time when the service level SLE exceeds the second level Lth2.

[0055] 2-3. Data processing example 6 is a flowchart showing the flow of processing particularly related to the embodiment, which is performed by the data processing device 11 (processor 14). The routine shown in FIG. 6 is repeatedly executed at a fixed cycle.

[0056] In the routine shown in FIG. 6, first, the waste WS discharge tendency is calculated (step S11). In the process of step S11, the waste WS discharge tendency is calculated for each user. The waste WS discharge tendency of the user UX is calculated, for example, by machine learning based on the waste WS discharge history data. This discharge history data is generated from data on the collection status of the waste WS acquired from the sensor 3Xb provided in the waste space 3Xa.

[0057] In another example, the waste WS discharge tendency of the user UX is calculated based on the waste WS discharge history data and the data on the time when the product PD was brought into the activity space 3X. In yet another example, the waste WS discharge tendency of the user UX is calculated by combining the waste WS discharge history data and the product PD purchase history data.

[0058] Following the process of step S11, the discharge of waste WS is predicted (step S12). In the process of step S12, the discharge of waste WS is predicted for each user. The discharge of waste WS is predicted, for example, by applying data indicating a demand forecast for the product PD by the user UX to the human model described in FIG. HM Demand forecasting for product PD based on user UX is performed by applying the data showing the purchasing tendency for product PD based on user UX to the human model explained in Figure 5. HM This is done by applying the method 1. The purchasing tendency of the user UX for the product PD is calculated based on the purchasing history data of the product PD.

[0059] Following the process of step S12, a demand for the processing service is predicted (step S13). In the process of step S13, for example, at least one of the data showing the waste WS discharge tendency and the data showing the waste WS discharge prediction is calculated based on the human model described in FIG. HM 3, which forecasts the demand for processing services.

[0060] Following the process of step S13, the service level SL is estimated by a service simulation (step S14). In the process of step S14, for example, the service resource data and the data indicating the demand forecast obtained by the process of step S13 are applied to the service model SM, thereby estimating the service level SL.

[0061] Following the process of step S14, the service level SL estimated in the process of step S14 (i.e., the service level SLE) is compared with the specified level Lth (step S15). Details of the process of step S15 will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the flow of the process performed in step S15.

[0062] 7, first, the service level SL (service level SLE) estimated in the process of step S14, the first level Lth1, and the second level Lth2 are obtained (step S151). Then, the service level SLE is compared with the first level Lth1 and the second level Lth2 (steps S152 and S153).

[0063] When the service level SLE falls below the first level Lth1, or when the service level SLE exceeds the second level Lth2, the process of step S154 is performed. In the process of step S154, the date and time when the service level SLE falls below the first level Lth1 is identified. Or, the date and time when the service level SLE exceeds the second level Lth2 is identified.

[0064] Returning to FIG. 6, the process flow will be described further. Following the process of step S15, a proposal notification SGG is generated and transmitted to the user terminal UXc. The user UX to which the proposal notification SGG is sent is, for example, a user who requests collection and refilling of a container TB containing waste WS at a date and time when the service level SLE falls below a first level Lth1. In another example, this user UX is a user who requests collection and refilling of a container TB containing waste WS at a date and time different from the date and time when the service level SLE exceeds a second level Lth2. The date and time when the service level SLE falls below the first level Lth1 and the date and time when the service level SLE exceeds the second level Lth2 are identified by the process of step S154.

[0065] 3.Effects According to the embodiment described above, the proposal notification SGG is transmitted to the user terminal 3Xc according to the result of the comparison between the service level SLE and the specified level Lth. Therefore, it is possible to prevent the convenience of the processing service from being impaired and to maintain the service level SLE within a desirable range. Therefore, it is possible to operate the waste processing service appropriately. In addition, as a result of the user UX selecting an action in accordance with the proposal notification SGG, it is also possible to reduce the amount of waste WS discharged from this user UX. Therefore, it is also possible to contribute to the maintenance of a sustainable society. [Explanation of symbols]

[0066] 1 Management Server 2. Treatment facilities 3 Locations 11 Data processing device 12,13 Database 14 processors 15 Memory 21 Processing Space 22 Waiting Space 23 Mobile 24 Vendor terminal 31, 32, 33 Activity Space 31a, 32a, 33a Disposal space 31b, 32b, 33b Sensor 31c, 32c, 33c terminals 3Xc User Terminal SL Service Level TB container UX, U1, U2, U3 users WS Waste Lth1 1st level Lth2 Second level

Claims

1. A method for having a server manage a service relating to waste disposal, comprising: acquiring at least one of a waste discharge history of a user who uses the service and a product purchase history of the user; Calculating at least one of a waste generation tendency of the user based on the generation history and a waste generation forecast of the user based on the purchase history; A step of calculating a demand forecast for the service by the user by applying at least one of the calculated waste discharge tendency and the waste discharge forecast to a prediction model having at least one of the waste discharge tendency and the waste discharge forecast as a parameter, the prediction model being a model of the behavior of the user using the service; a step of estimating a level of the service by a simulation in which the calculated demand forecast and the resources to be inputted to the service are applied to a simulation model having parameters of the demand forecast for the service by the user and the resources to be inputted to the service; sending a notification to the user's terminal, the notification suggesting a change in at least one of the user's behavior of generating waste and purchasing goods, based on a comparison result between the estimated level of service and a prescribed level for maintaining the service within a desired range, the prescribed level being prescribed by a desired lower limit and upper limit of the service; A method for managing waste disposal services, comprising:

2. 2. The method of claim 1 , If the comparison result indicates that the estimated level is below the lower limit of the specified level, the notification proposing the change includes information on the service fee depending on the time and date of waste collection and information to encourage the reduction of waste generation or emission. A method for managing waste disposal services, comprising:

3. 2. The method of claim 1 , If the comparison result indicates that the estimated level is above the upper limit of the specified level, the notification proposing the change includes information on the service fee depending on the time and date of waste collection and information to encourage increased waste generation or discharge. A method for managing waste disposal services, comprising:

4. A device for managing services relating to waste disposal, comprising: A memory that stores at least one of a waste discharge history of a user who uses the service and a product purchase history of the user; A processor that performs processing based on the data stored in the memory; Equipped with The processor, Calculating at least one of a waste disposal tendency of the user based on the waste disposal history and a waste disposal forecast of the user based on the purchase history; calculating a demand forecast for the service by the user by applying at least one of the calculated waste discharge tendency and the waste discharge forecast to a prediction model that uses at least one of the waste discharge tendency and the waste discharge forecast as a parameter and models the behavior of the user in using the service; estimating a level of the service by a simulation in which the calculated demand forecast and the resources to be inputted to the service are applied to a simulation model having the demand forecast for the service by the user and the resources to be inputted to the service as parameters; Based on a comparison result between the estimated level of the service and a prescribed level for maintaining the service within a desired range, the prescribed level being prescribed by a desired lower limit and an upper limit of the service, a notification is sent to the user's terminal, suggesting a change in at least one of the user's behavior regarding waste generation and product purchases. A waste disposal service management device configured as described above.

5. A program for managing services relating to waste disposal, comprising: A process of acquiring at least one of a waste discharge history of a user who uses the service and a product purchase history of the user; A process of calculating at least one of a waste generation tendency of the user based on the waste generation history and a waste generation prediction of the user based on the purchase history; a process of calculating a demand forecast for the service by the user by applying at least one of the calculated waste discharge tendency and the waste discharge forecast to a prediction model that uses at least one of the waste discharge tendency and the waste discharge forecast as a parameter and models the behavior of the user in using the service; a process of estimating a level of the service by a simulation in which the calculated demand forecast and the resources to be inputted to the service are applied to a simulation model having parameters of the demand forecast for the service by the user and the resources to be inputted to the service; A process of sending a notification to a terminal of the user, the notification suggesting a change in at least one of the user's behavior of generating waste and purchasing goods, based on a comparison result between the estimated level of the service and a prescribed level for maintaining the service within a desired range, the prescribed level being prescribed by a desired lower limit and an upper limit of the service; A waste disposal service management program that causes a computer to execute the above.

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