Information processing device, information processing method, and program

Abstract

To individually predict battery deterioration in accordance with the actual usage conditions of a user without relying on empirical rules. [Solution] An investigation result acquisition unit 102 acquires investigation result information regarding the usage of each of n mobile terminals 2, including at least the battery capacity of each of the n mobile terminals 2, reported by each of n terminal users C who use each of the n mobile terminals 2. An SOH analysis unit 103 generates a multiple regression analysis curve graph showing the correlation between the usage period t of each of the n mobile terminals 2 and the SOH, based on the acquired investigation result information, to be used for estimating the battery status of other target devices.

Description

[Technical Field]

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

[0002] The deterioration of batteries in mobile devices such as smartphones is said to be correlated with the performance of the battery itself and the usage patterns of the device. In particular, the environment in which the mobile device is placed is said to have an impact on battery deterioration. In contrast, in the mobile device market, battery condition has not been given much importance, and it has been recommended to replace mobile devices after a certain period of time (for example, two years). However, deterioration of batteries over time in devices that are powered by batteries, including mobile terminals, is becoming a major issue. There have been existing technologies for diagnosing battery degradation. For example, Patent Document 1 describes a technology that calculates the open circuit voltage and internal resistance of a lead-acid battery in a fully charged state, and calculates the discharge capacity of the lead-acid battery from the open circuit voltage and internal resistance in the fully charged state. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-201464 Summary of the Invention [Problem to be solved by the invention]

[0004] However, there is a need for the development of technology that can individually predict the state of battery deterioration in accordance with the actual usage situation of the user, rather than relying on empirical rules like conventional technologies including the technology described in Patent Document 1.

[0005] The present invention has been made in consideration of such circumstances, and aims to provide a method that can individually predict battery deterioration in accordance with the actual usage situation of the user, without relying on empirical rules. [Means for solving the problem]

[0006] an acquisition means for acquiring first information regarding usage of each of the one or more target devices, the first information including at least information regarding the battery of each of the one or more target devices, reported by each of one or more users who use each of the one or more target devices powered by power from a battery; a generating means for generating second information indicating a correlation between a usage period of each of the one or more target devices and a battery state, the second information being used to estimate a battery state of the one or more target devices or another target device, based on the first information acquired by the acquiring means; An information processing device comprising: [Effects of the Invention]

[0007] According to the present invention, it is possible to individually predict battery deterioration in accordance with the actual usage conditions of each user without relying on empirical rules. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram showing an overview of a service that can be realized by an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied; [Figure 2] FIG. 10 is a diagram showing an image of the results of a fact-finding survey questionnaire. [Figure 3] FIG. 10 is a diagram showing an image of a multiple regression analysis curve graph. [Figure 4] 1 is a diagram illustrating an example of a configuration of an information processing system including a server according to an embodiment of the information processing device of the present invention. [Figure 5] 5 is a block diagram showing an example of a hardware configuration of a server in the information processing system shown in FIG. 4. FIG. [Figure 6]6 is a functional block diagram showing a functional configuration for executing a battery deterioration prediction process and a purchase price calculation process, among the functional configurations of the server in FIG. 5. FIG. [Figure 7] 10 shows an example of a dedicated app screen displayed on a mobile device, which displays an evaluation of each item that may be a cause of deterioration as a result of a battery deterioration diagnosis of the mobile device. [Figure 8] 10 shows an example of a dedicated app screen displayed on a mobile device, which suggests how to use the mobile device based on the results (Report) of a battery deterioration diagnosis of the mobile device. [Figure 9] This is a screen of a dedicated app displayed on a mobile terminal, which indicates that the alert settings on the screen of FIG. 8 have been completed. [Figure 10] 10 shows an example of a dedicated app screen displayed on a mobile device, which suggests future handling of the mobile device based on the results of a battery deterioration diagnosis of the mobile device. [Figure 11] This is an example of a dedicated app screen displayed on a mobile device, which suggests future handling of the mobile device when no problems are found in the mobile device's defect check. [Figure 12] This shows an example of a dedicated app screen that is displayed when a malfunction occurs on a mobile device, and includes a software button that activates a malfunction check function. [Figure 13] This is an example of a screen from a dedicated app that is displayed on a mobile device, suggesting future handling of the mobile device when an abnormality is found during a problem check on the mobile device. [Figure 14] This is an example of a dedicated app screen displayed on a mobile device, which is displayed when a service provider makes a purchase appraisal of the mobile device and suggests future handling of the mobile device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0010] First, referring to Figures 1 to 3, we will explain an overview of a service (hereinafter referred to as "this service") that can be realized by an information processing system (see Figure 4 described later) to which a server 1 according to one embodiment of the information processing device of the present invention is applied.

[0011] FIG. 1 is a diagram showing an outline of this service that can be realized by an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied. FIG. 2 shows an image of the results of the survey questionnaire. FIG. 3 is a diagram showing an image of a multiple regression analysis curve graph.

[0012] This service can be realized by an information processing system to which a server 1 managed by a service provider G is applied. The service provided by the service provider G is provided to a terminal user C and a store staff S of a predetermined store. Terminal user C is a person who uses a battery-powered mobile terminal 2. The store staff S is a counter staff member at a predetermined store that handles the mobile terminal 2 as a business. The "prescribed store" includes a sales agent, repair shop, purchaser, etc. of smartphones and the like.

[0013] When using the Service, Terminal User C operates dedicated application software (hereinafter referred to as the "Dedicated App") that enables the use of the Service and is installed on Mobile Terminal 2. Terminal User C can also use the Service by accessing a dedicated website (hereinafter referred to as the "Dedicated Site") that enables the use of the Service and is displayed by the browser function of Mobile Terminal 2. Hereinafter, "terminal user C operates mobile terminal 2" means that terminal user C uses the service from a dedicated app or dedicated website. When using this service, the store staff S operates a dedicated app installed on a terminal 3 (hereinafter referred to as "store terminal 3") installed in the store. The store staff S can also use this service by accessing a dedicated website displayed by the browser function of the store terminal 3. Hereinafter, "store staff S operates the store terminal 3" means that store staff S uses the service from a dedicated app or dedicated website.

[0014] In this service, a questionnaire survey (hereinafter referred to as "actual situation survey questionnaire") regarding the use of n mobile terminals 2 is conducted for each of n terminal users C (n is any integer value equal to or greater than 1). Note that one terminal user C may use multiple mobile terminals 2, in which case the terminal user C will be counted as one person for one mobile terminal 2. Also, one mobile terminal 2 may be shared by multiple terminal users C, but in this case too, one representative person will be designated, and the terminal user C for one mobile terminal 2 will be counted as one person.

[0015] The fact-finding survey questionnaire is conducted by displaying a UI (User Interface) consisting of one or more questions and corresponding input fields on the mobile terminal 2. The terminal user C answers the fact-finding survey questionnaire by operating the mobile terminal 2. However, the method of conducting the fact-finding survey questionnaire is not limited to this. For example, the fact-finding survey questionnaire may be attached to an email addressed to the terminal user C, and the terminal user C may answer it.

[0016] The survey questionnaire includes general questions about the actual usage of the mobile terminal 2 as well as questions about the battery. Figure 2 shows a specific example of a survey questionnaire. That is, as shown in Fig. 2, the fact-finding questionnaire administered to n terminal users C includes questions No. 1 to No. 19. Specifically, the questions include, for example, "What is your age?", "What is your gender?", "Please enter your postal code?", "What is your occupation?", "What is your family composition?", "When did you purchase it?", "Where did you purchase it?", "What is the model name?", "Do you use a cover?", "What type is it?", "Did you repair the battery after purchase?", "Where did you have it repaired?", "What is the average usage time?", "Where do you usually use it?", "Do you turn on Wi-Fi?", "What purpose do you use it for other than making calls?", "Is the charger a genuine product?", "When do you charge it?", and "What is the current battery capacity?"

[0017] Terminal user C inputs answers to such questions, for example, as shown in Fig. 2. That is, as shown in Fig. 2, the age is "35 years old", the sex is "male", the postal code is "XXX-XXXX", the occupation is "company employee", the family structure is "married, two children", the purchase date of mobile terminal 2 is "YYYY / MM / DD", the purchase location of mobile terminal 2 is "authorized store (new)", the model name of mobile terminal 2 is "XXX", whether a cover is used is "Yes", the type of cover is "notebook type", the repair history of mobile terminal 2 after purchase is "Yes", the place to request repairs is "authorized store", and the mobile terminal 2 The answers entered are: daily usage time is "1 hour", main place of use of mobile device 2 is "home", whether or not Wi-Fi is used is "yes", purposes of use of mobile device 2 other than calling are "news, SNS (real name registration), video sites, music, payment", whether the charger is genuine is "yes", when to charge it is "I charge it when the battery is about to run out (top-up charging)", and current battery capacity is "85% of maximum capacity".

[0018] The fact-finding questionnaire as described above is conducted on n terminal users C. The input results by each of the n terminal users C are associated with the questions and acquired as survey result information by the server 1. In addition to the fact-finding questionnaire, the server 1 also acquires the results of independently conducted internet surveys as survey result information. As a specific example of a survey system, for example, a fact-finding survey questionnaire is conducted on terminal user C every time a mobile terminal 2 is bought back at a specified store. By conducting this for a specified period (for example, three months), a large amount of survey result information is accumulated on server 1. Also, an internet survey based on diverse viewpoints is conducted by multiple staff members (for example, 30 people) for a specified period (for example, three months), and the survey result information is accumulated on server 1 (for example, 5,000 plots).

[0019] In this service, a regression analysis is performed based on multiple pieces of survey result information accumulated in the server 1. Specifically, the server 1 generates a multiple regression analysis curve graph. The multiple regression analysis curve graph is a graph showing the correlation between the usage period t of each of n mobile terminals 2 and the SOH (State of Health), which is an index showing the battery's deterioration state or health. The SOH is calculated using the formula "fully charged capacity at deterioration (Ah) / initial fully charged capacity (Ah) × 100".

[0020] Figure 3 shows an image of a multiple regression analysis curve graph. That is, the multiple regression analysis curve graph is a graph in which the horizontal axis represents the usage period t of the mobile terminal 2 by terminal user C and the vertical axis represents SOH. The multiple plotted circles show the relationship between the usage period t and SOH for each mobile terminal 2. Note that one circle may represent one mobile terminal 2, or may represent a group of multiple mobile terminals 2. Curve L represents the regression curve. As shown in Figure 3, the shorter the period of use (left side of the graph), the higher the SOH value, and the longer the period of use (right side of the graph), the higher the SOH value. Note that, as indicated by the arrow, values ​​that deviate significantly from the regression curve (curve L) can be assumed to be degradation caused by the usage style of terminal user C.

[0021] Once the multiple regression analysis curve graph is generated, machine learning using AI (artificial intelligence) is carried out for a predetermined period (e.g., three months) based on the generated multiple regression analysis curve graph, using the accumulated multiple survey result information as input data. By performing this type of machine learning, it becomes possible to output information showing the correlation between the multiple regression analysis curve graph of Figure 3 and the responses to the fact-finding questionnaire of Figure 2. Specifically, for example, it is possible to output information showing the correlation between the age of terminal user C and SOH, or the correlation between the environment in which terminal user C is located (for example, the temperature derived from the postal code) and SOH. Also, for example, it is possible to output information showing the correlation between the place of purchase of mobile terminal 2 (for example, a new product purchased officially, a second-hand product purchased overseas, etc.) and SOH.

[0022] Furthermore, for example, using a multiple regression analysis curve graph, even if the current battery capacity is unknown, the value of the SOH can be estimated from the usage period t. Furthermore, a multiple regression analysis curve graph can be generated for each OS (Operating System) of the mobile terminal 2 (for example, OS1 and OS2 in FIG. 1). Although not shown, a multiple regression analysis curve graph can also be generated for each manufacturer and model. For example, a multiple regression analysis curve graph can be generated for each of manufacturers A to C. Furthermore, a multiple regression analysis curve graph can be generated for each of models a1 to c3 of manufacturer A. A multiple regression analysis curve graph can also be generated regardless of OS, manufacturer, or model. In this case, a common multiple regression analysis curve graph (for example, the multiple regression analysis curve graph represented by the curve L in FIG. 1) can be generated by normalizing the multiple regression analysis curve graphs generated for each OS (for example, the multiple regression analysis curve graph represented by the curve L1 and L2 in FIG. 1).

[0023] As a result of machine learning, if it becomes possible to output information showing the correlation between the multiple regression analysis curve graph and the responses to the fact-finding questionnaire in Figure 2, it will be possible to diagnose the battery deterioration of each mobile device 2 and calculate a purchase price that takes into account the state of battery deterioration. For example, the battery deterioration diagnosis may be performed by store staff S at the request of terminal user C, or it may be performed automatically at predetermined intervals as a function of a dedicated app. Furthermore, if a battery deterioration diagnosis is performed as a function of the dedicated app, information indicating the degree of deterioration may be notified to the terminal user C as a "notice." This allows the terminal user C to recognize the deterioration of the battery of the mobile terminal 2, and at the same time provides an indicator for deciding when to replace the mobile terminal 2. As a result, the terminal user C can replace the mobile terminal 2 at the best possible time. Furthermore, based on the battery deterioration diagnosis result, correction data for slowing down the speed of battery deterioration may be transmitted to the mobile terminal 2. This makes it possible to extend the life of the battery of the mobile terminal 2.

[0024] To summarise, this service can be expected to have the following effects: In other words, this service encourages battery deterioration diagnosis across the entire industry in the secondhand market, thereby encouraging device user C to repair their battery or offering advice on replacing it. In this case, the purchase price can be adjusted depending on the condition of the battery at the time of replacement. This also helps to optimize the appraised value of mobile devices 2 in the secondhand market. As a result, the normal distribution of mobile devices 2 in the secondhand market is ensured, and those who wish to purchase a mobile device 2 in the secondhand market can make a purchase after understanding the condition of the mobile device 2 (for example, its estimated remaining life, etc.). Furthermore, since many device users C change their models when they sense battery deterioration, applying this service will help promote model changes not only in the second-hand market but also in the new market. In addition, machine learning using AI (artificial intelligence) can optimize the battery condition, which varies from person to person, making it possible to create buying and selling opportunities at the best possible time for device user C. In addition, the store staff S can guide the terminal user C to repair or replace the device based on legitimate grounds. As a result, it can also create new advertising demand for the dedicated app. Furthermore, because this service can be applied to major consumer goods such as smartphones, it is expected that its value and benefits will be enormous.

[0025] Next, with reference to FIG. 4, a description will be given of the configuration of an information processing system that realizes the provision of the above-described service, that is, an information processing system that includes a server 1 according to an embodiment of an information processing device of the present invention. FIG. 4 is a diagram showing an example of the configuration of an information processing system including a server according to an embodiment of the information processing device of the present invention.

[0026] The information processing system shown in Fig. 4 is configured to include a server 1, mobile terminals 2-1 to 2-m (m is any integer value equal to or greater than n), and a store terminal 3. In this specification, when there is no need to distinguish between the mobile terminals 2-1 to 2-m, they will be collectively referred to as "mobile terminal 2." In this case, the person operating the mobile terminal 2 will be referred to as "terminal user C." Furthermore, if the mobile terminal 2 is simply held for sale, it does not constitute an information processing system. However, the following explanation will be given on the assumption that the mobile terminal 2 is not simply held for sale, but is operated by terminal user C. The server 1, the mobile terminal 2, and the store terminal 3 are connected to each other via a predetermined network N such as the Internet.

[0027] The server 1 is an information processing device managed by the service provider G. The server 1 communicates with the mobile terminal 2 and the store terminal 3 as needed, and executes various processes for realizing this service.

[0028] The mobile terminal 2 is an information processing device operated by a terminal user C. The mobile terminal 2 is configured as, for example, a smartphone, a tablet, or the like.

[0029] The store terminal 3 is an information processing device operated by a store staff member S of the store. The store terminal 3 is configured as, for example, a personal computer, a smartphone, a tablet, or the like.

[0030] FIG. 5 is a block diagram showing an example of a hardware configuration of a server in the information processing system shown in FIG.

[0031] The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a memory unit 18, a communication unit 19, and a drive 20.

[0032] The CPU 11 executes various processes according to a program recorded in the ROM 12 or a program loaded from the storage unit 18 into the RAM 13 . The RAM 13 also stores data and the like necessary for the CPU 11 to execute various processes.

[0033] The CPU 11, ROM 12, and RAM 13 are connected to one another via a bus 14. An input / output interface 15 is also connected to this bus 14. An input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20 are connected to the input / output interface 15.

[0034] The input unit 16 is configured by, for example, a keyboard, and outputs various information. The output unit 17 is configured with a display such as a liquid crystal display, a speaker, etc., and outputs various information as images and sounds. The storage unit 18 is configured with a DRAM (Dynamic Random Access Memory) or the like, and stores various data. The communication unit 19 communicates with other devices (for example, the mobile terminal 2 and the store terminal 3 in FIG. 2) via a network N including the Internet.

[0035] Removable media 40, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately attached to the drive 20. A program read from the removable media 40 by the drive 20 is installed in the storage unit 18 as needed. Furthermore, the removable medium 40 can also store various data stored in the storage unit 18 in the same manner as the storage unit 18.

[0036] Although not shown, the mobile terminal 2 and the store terminal 3 in Fig. 4 can also have basically the same hardware configuration as that shown in Fig. 5. Therefore, a description of the hardware configuration of the mobile terminal 2 and the store terminal 3 will be omitted.

[0037] 5, various processes including the battery deterioration prediction process and the purchase price calculation process can be executed in the server 1. As a result, the service provider G can provide the above-mentioned service to the terminal user C and the store staff S. The "battery deterioration prediction process" refers to a process of predicting the deterioration of the battery of terminal user C's mobile terminal 2 by machine learning based on the results of the regression analysis described above. The "purchase price calculation process" refers to a process of calculating the purchase price of the mobile terminal 2 of terminal user C based on the result of the battery deterioration prediction process. The functional configuration for executing the battery deterioration prediction process and the purchase price calculation process executed in the server 1 will be described below.

[0038] FIG. 6 is a functional block diagram showing the functional configuration of the server in FIG. 5 for executing the battery deterioration prediction process and the purchase price calculation process.

[0039] 6, when the execution of the battery deterioration prediction process is controlled in the CPU 11 of the server 1, a notification control unit 101, a survey result acquisition unit 102, a SOH analysis unit 103, and a deterioration diagnosis unit 104 function. When the execution of the purchase price calculation process is controlled, a purchase price calculation unit 105 also functions. In addition, an area of ​​the storage unit 18 of the server 1 is provided with a survey result DB 181 and an analysis result DB 182.

[0040] The notification control unit 101 executes control to notify each of the n terminal users C of a fact-finding survey questionnaire consisting of one or more input items. Specifically, the notification control unit 101 executes control to display the input items of the fact-finding survey questionnaire on each of the n mobile terminals 2. However, the method of notifying the fact-finding survey questionnaire is not limited to this. For example, the fact-finding survey questionnaire may be notified by attaching it to an email addressed to the terminal user C.

[0041] The notification control unit 101 also controls to notify at least one of the mobile terminal 2 and the store terminal 3 of the battery degradation diagnosis result generated by the degradation diagnosis unit 104 .

[0042] The notification control unit 101 also controls to notify at least one of the mobile terminal 2 and the store terminal 3 of the purchase price calculated by the purchase price calculation unit 105 .

[0043] The investigation result acquisition unit 102 acquires, as investigation result information, information regarding the use of each of the n mobile terminals 2, including at least information regarding the batteries of each of the n mobile terminals 2, reported by each of the n terminal users C who use each of the n mobile terminals 2. The investigation result information acquired by the investigation result acquisition unit 102 is stored and managed in the investigation result DB 181.

[0044] The SOH analysis unit 103 performs regression analysis based on the survey result information to generate a multiple regression analysis curve graph showing the correlation between the usage period t and SOH of each of the n mobile terminals 2. The multiple regression analysis curve graph generated by the SOH analysis unit 103 is stored and managed in the analysis result DB 182.

[0045] The degradation diagnosis unit 104 predicts the degradation of the battery of the mobile terminal 2k (k is an arbitrary integer value between 1 and m) based on the multiple regression analysis curve graph generated by the SOH analysis unit 103, and generates a battery degradation diagnosis result as a result. Specifically, the degradation diagnosis unit 104 diagnoses the state of battery degradation by applying the mobile terminal 2k to the multiple regression analysis curve graph, and generates a battery degradation diagnosis result as a result.

[0046] The purchase price calculation unit 105 calculates the purchase price of the mobile terminal 2k based on the battery deterioration diagnosis result of the mobile terminal 2k generated by the deterioration diagnosis unit 104.

[0047] Although one embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment, and modifications, improvements, etc. within the scope of achieving the object of the present invention are considered to be included in the present invention.

[0048] For example, in the above-described embodiment, the AI-based machine learning output information indicating the correlation between the multiple regression analysis curve graph of Fig. 3 and the responses to the fact-finding questionnaire of Fig. 2. However, the information for which the correlation with the multiple regression analysis curve graph of Fig. 3 is determined is not particularly limited to the responses to the questionnaire, and may be any information. For example, battery degradation is caused by multiple factors related to the use of the device, such as charging while the device is not in use, charging over time, the number of times the device has heated up, the frequency of communication, etc. Therefore, information indicating the correspondence between one or more factors that contribute to the degradation of the mobile terminal 2 and the multiple regression analysis curve graph of FIG. 3 may be output. Here, these items can be obtained as responses to a fact-finding questionnaire, but can also be obtained from the state of the mobile terminal 2 (including the usage and goals of terminal user C). That is, in such a case, machine learning using AI may output information indicating the correlation between the multiple regression analysis curve graph of Figure 3 and one or more items that cause deterioration (hereinafter referred to as "item-related information"). As a result of the battery deterioration diagnosis of a specified mobile terminal 2, an evaluation of the specified mobile terminal 2 (e.g., an evaluation such as "excellent" or "good") for each of one or more items is obtained based on the actual state of the specified mobile terminal 2 and the item-related information.

[0049] FIG. 7 shows an example of a dedicated app screen displayed on a mobile terminal, which displays an evaluation of each item that may be a cause of deterioration as a result of a battery deterioration diagnosis of the mobile terminal. "○○○○-kun" at the top of the screen in FIG. 7 is the name of the character corresponding to the mobile terminal 2, and was set by the terminal user C when the dedicated app was installed, etc. The "Going Well" message below "XXXXXX" on the screen in Figure 7 is the overall result of the battery deterioration diagnosis for the mobile terminal 2. The "Get 2 Points" message to the right of this message indicates that a certain number of points have been earned. These points can be earned, for example, depending on the overall result of the battery deterioration diagnosis, and can be used by the terminal user C when purchasing a new battery, etc. At the bottom of the screen in Fig. 7, a "Report" is displayed showing an evaluation (e.g., evaluations such as "excellent" or "good") of a predetermined mobile terminal 2 for each of one or more items that may cause deterioration. In the example in Fig. 7, such items include "charging while doing other things," "top-up charging," "charging time," "charging time zone," "number of times heat occurs," and "frequency of communication."

[0050] The display format of the battery deterioration diagnosis result (evaluation) on the screen is not limited to the example shown in FIG. 7, and various other formats can be adopted. For example, if an image of a character named "○○○○-kun" is rated as poor for an item that causes deterioration, an image showing the character in a state of poor deterioration, such as swelling, cracking, melting red, or burning, may be displayed on the mobile terminal 2. Conversely, if the item that is a cause of deterioration is evaluated as good, the character may be displayed on the mobile terminal 2 as an image showing that the deterioration evaluation is good and progressing smoothly, such as by making the character appear shiny, sharp, elite, or have a resort-like atmosphere.

[0051] FIG. 8 shows an example of a dedicated app screen displayed on a mobile terminal, which suggests how to use the mobile terminal based on the results (report) of a battery deterioration diagnosis of the mobile terminal. In the example of Figure 8, as a centralized control to prevent further deterioration, a suggestion is displayed that an alert (push notification) will be issued if the usage exceeds the set limit for one or more items that are factors in deterioration. This alert initially displays recommended values, but can be freely set by terminal user C. This is because recommended values ​​may not necessarily be perceived as appropriate by terminal user C. In addition, below such alert suggestions, content (e.g., reading material or articles) that provides device user C with tips and techniques for reducing battery degradation is displayed.

[0052] When the above-mentioned alert settings are completed, the screen shown in FIG. FIG. 9 is a screen of the dedicated app displayed on the mobile terminal, showing that the alert settings on the screen of FIG. 8 have been completed. 9, the terminal user C can select whether or not to perform another battery deterioration diagnosis (One Week Check) after using the mobile terminal 2 for one week based on the alert set in this way. To maintain the user's intention to suppress battery deterioration, the above-mentioned points may be earned if a good result is obtained in this One Week Check.

[0053] FIG. 10 shows an example of a dedicated app screen displayed on a mobile terminal, which suggests future handling of the mobile terminal based on the results of a battery deterioration diagnosis of the mobile terminal. If the results of the battery deterioration diagnosis of the mobile terminal 2 are significantly poor, for example, if the battery is significantly deteriorated and the results of the deterioration diagnosis do not improve even after following the suggestions presented on the screen of Figure 8 described above, a screen such as that shown in Figure 10 will be displayed on the mobile terminal 2. That is, software buttons indicating how to handle the mobile terminal 2 in the future, specifically, a software button for "Get an appraisal now," a software button for "Still using," and a software button for "Donate to the Smartphone Frog Project," are displayed on the screen of Figure 10. When the software button "Get a trade-in appraisal now" is pressed, the screen transitions to one where the service provider will make a trade-in appraisal of the mobile terminal 2. When the software button "continue to use" is pressed, it is determined that the mobile terminal 2 will continue to be used, and the screen transitions to a predetermined screen (not shown). When the software button "Donate to the Smartphone Frog Project" is pressed, the screen changes to one where procedures for making a donation on the mobile terminal 2 can be carried out.

[0054] Here, the functions of the dedicated app include the battery deterioration diagnosis function mentioned above, as well as a function to check the status of each part of the mobile terminal 1 (whether there is a malfunction or not) (hereinafter referred to as the "malfunction check function"). The fault check function is activated by a predetermined trigger. This predetermined trigger may be when a set predetermined period of time has elapsed, or when the terminal user C gives an explicit instruction operation. Items for which such a defect check is performed include, for example, a cracked screen, battery, charging failure, speaker, microphone, home button, and camera failure. Here, a predetermined method using the multiple regression analysis curve graph shown in Figure 3 is used to check for battery defects. If there are no problems as a result of such an operation confirmation check, the screen shown in FIG. Figure 11 shows an example of a dedicated app screen displayed on a mobile device, which suggests future handling of the mobile device when no problems are found in the trouble check of the mobile device.

[0055] The predetermined trigger for starting the malfunction check function is not limited to the above-mentioned example. For example, when various sensors (not shown) built into the mobile terminal 2 detect problematic behavior toward the mobile terminal 2, a screen such as that shown in Fig. 12 may be displayed on the mobile terminal 2, and a malfunction check may be triggered by pressing a software button on the screen that reads "Check operation now." That is, FIG. 12 shows an example of a dedicated application screen that is displayed when a malfunction occurs on a mobile terminal, and that includes a software button that activates a malfunction check function. The problem behavior is not particularly limited as long as it can be detected by various sensors built into the mobile terminal 2, and examples that can be used include dropping, collision, water / submersion in water, pressure, and the like.

[0056] If a problem check is performed due to such problematic behavior on the mobile terminal 2 and no abnormality is found in the mobile terminal 2, the screen shown in Figure 11 will be displayed, but if an abnormality such as a malfunction is found, the screen shown in Figure 13 will be displayed. Figure 13 shows an example of a dedicated app screen displayed on a mobile device, which suggests how to handle the mobile device in the future if an abnormality is found during a trouble check on the mobile device. That is, software buttons indicating how to handle the mobile terminal 2 in the future, specifically, a software button for "repair and return now," a software button for "continue to use," and a software button for "donate to the Smartphone Frog Project," are displayed on the screen of Figure 13. When the software button "Repair and send it in now" is pressed, the screen transitions to one where procedures for repairing the mobile terminal 2 by the service provider can be carried out. When the software button "continue to use" is pressed, it is determined that the mobile terminal 2 will continue to be used, and the screen transitions to a predetermined screen (not shown). When the software button "Donate to the Smartphone Frog Project" is pressed, the screen changes to one where procedures for making a donation on the mobile terminal 2 can be carried out. Figure 13 shows an example of a dedicated app screen displayed on a mobile device, which suggests how to handle the mobile device in the future if an abnormality is found during a trouble check on the mobile device.

[0057] Figure 14 shows an example of a dedicated app screen displayed on a mobile device, which is displayed when a service provider makes a purchase appraisal of the mobile device and suggests future handling of the mobile device. When the photo on the mobile terminal 2 is uploaded, the service provider performs a purchase appraisal, and the purchase price (23,800 yen in the example of FIG. 14) is displayed as the appraisal result. That is, software buttons indicating how to handle the mobile terminal 2 in the future, specifically, for example, a software button that says "Sell on the mobile phone market and get double QUOH points" and a software button that says "," are displayed on the screen of Figure 14. When the software button "Sell at Mobile Market and get double QUOH points" is pressed, the screen changes to one where procedures for the service provider to buy back the mobile device 2 are carried out. When the purchase of the mobile device 2 is completed on the screen after the change, the predetermined points (double the usual points) mentioned in Fig. 7 are awarded. When the software button "Rough prediction price one year from now" is pressed, it is determined that the mobile terminal 2 will continue to be used, and the screen transitions to one showing the purchase price etc. in the event that the mobile terminal is used for 12 months without being repurchased.

[0058] The following are not limited to the above-described embodiment. For example, in the above-described embodiment, battery deterioration of a mobile terminal 2 such as a smartphone or tablet is predicted, but the "target device" in the present invention is not limited to the above-described embodiment. In other words, any device that runs on power from a battery is included in the "target device" in the present invention. Therefore, any device, such as a battery-powered automobile, drone, or various hardware, can be included in the "target device."

[0059] Also, for example, the question items in the fact-finding questionnaire in Fig. 3 are merely examples. In addition to the question items shown in Fig. 3, other question items may be included to obtain various information required to understand the usage status of the mobile terminal 2.

[0060] Furthermore, the system configuration shown in FIG. 4 and the hardware configuration of the server 1 shown in FIG. 5 are merely examples for achieving the object of the present invention, and are not particularly limited.

[0061] Furthermore, the functional block diagram shown in Fig. 6 is merely an example and is not particularly limited. That is, it is sufficient if the information processing system in Fig. 4 is provided with a function that can execute the above-described series of processes as a whole, and the type of functional block used to realize this function is not particularly limited to the example in Fig. 6.

[0062] Furthermore, the locations of the functional blocks are not limited to those shown in FIG. 6 and may be arbitrary. For example, in the example of Figure 6, the above-mentioned battery deterioration prediction process and purchase price calculation process are configured to be performed on the server 1 side, but this is not limited to this, and at least part of these processes may be performed on the mobile terminal 2 side or the store terminal 3 side. That is, the functional blocks required to execute the battery deterioration prediction process and the purchase price calculation process are configured to be provided on the server 1 side, but this is merely an example. At least some of the functional blocks arranged on the server 1 side may be configured to be provided on the mobile terminal 2 side or the store terminal 3 side.

[0063] The above-described series of processes can be executed by hardware or software. Furthermore, one functional block may be configured as a single piece of hardware, a single piece of software, or a combination thereof.

[0064] When a series of processes is executed by software, the programs that make up the software are installed into a computer or the like from a network or a recording medium. The computer may be a computer built on dedicated hardware. The computer may also be a computer capable of executing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0065] The recording medium containing such a program may be composed not only of a removable medium (not shown) that is distributed separately from the device main body in order to provide the program to the user, but also of a recording medium that is provided to the user in a state that is pre-installed in the device main body.

[0066] In this specification, the steps describing the program to be recorded on the recording medium include not only processes that are performed chronologically in accordance with the order, but also processes that are not necessarily performed chronologically but are performed in parallel or individually. In addition, in this specification, the term "system" refers to an overall device that is made up of a plurality of devices, a plurality of means, etc.

[0067] In summary, the information processing apparatus to which the present invention is applied is sufficient if it has the following configuration, and can take on a variety of different embodiments. That is, an information processing device to which the present invention is applied (for example, the server 1 in FIG. 4) an acquisition means (for example, the survey result acquisition unit 102 of FIG. 6) for acquiring first information (for example, the survey result information described above) regarding the use of each of the one or more target devices (for example, the n mobile terminals 2 described above) powered by a battery, the first information including at least information about the battery of each of the one or more target devices (for example, the capacity of the battery displayed on the mobile terminal 2) reported by each of one or more users (for example, the n terminal users C described above) who use each of the one or more target devices; a generating means (e.g., the SOH analysis unit 103 in FIG. 6) for generating second information (e.g., the multiple regression analysis curve graph in FIG. 2) that indicates a correlation between the usage period (e.g., the usage period t in FIG. 2) of each of the one or more target devices and the battery state (e.g., the SOH in FIG. 2), based on the first information acquired by the acquiring means, and that is used to estimate the battery state of the one or more target devices or another target device; Equipped with.

[0068] As a result, second information indicating a correlation between the usage period and the battery state of each of the one or more target devices is generated based on first information regarding battery usage reported from each of the one or more target devices powered by power from the battery. As a result, it becomes possible to predict battery deterioration using the second information. That is, it becomes possible to predict battery deterioration individually in accordance with the actual usage situation of each user without relying on empirical rules.

[0069] The system further includes a notification control unit (for example, the notification control unit 101 in FIG. 6) that controls notification of a questionnaire (for example, the fact-finding questionnaire in FIG. 1) consisting of one or more input items to each of the one or more users, The acquisition means can acquire, as the first information, the results of the survey by the questionnaire notified under the control of the notification control means. Alternatively, for example, the acquisition means acquires information indicating a state of the target device as the first information.

[0070] As a result, a questionnaire consisting of one or more input items is notified to each of the one or more users. Then, the results of the survey based on the notified questionnaire are acquired as first information related to battery usage. Alternatively, information indicating the status of the target devices is acquired as the first information. Then, based on the first information related to the batteries notified from each of the one or more target devices, second information indicating a correlation between the usage period and the battery status of each of the one or more target devices is generated. As a result, it becomes possible to predict battery deterioration using the results of a survey of one or more users or the second information that takes into account the state of the target device. In other words, it becomes possible to predict battery deterioration individually in accordance with the actual usage situation of each user without relying on empirical rules.

[0071] The device may further include a second generation means (e.g., degradation diagnosis unit 104 in Figure 6) that generates third information (battery degradation diagnosis result) indicating the degradation state of the battery of the target device based on the first information and the second information.

[0072] As a result, third information indicating the deterioration state of the battery of the target device is generated based on the first information regarding battery usage and the second information indicating the correlation between the usage period of the target device and the battery state. As a result, it is possible to predict battery deterioration individually in accordance with the actual usage of each user.

[0073] The information processing device may further include a second notification control means (for example, notification control section 101 in FIG. 6) that executes control to notify the user of the third information generated by the second generation means.

[0074] This allows the user to recognize the deterioration of the battery of the target device, and at the same time provides an indicator for determining the timing of replacing the target device. As a result, the user can purchase a replacement device at the best possible time. Here, the third information can be notified to the user by displaying an image showing the third information on at least a portion of the screen displayed when the application installed on the target device is being executed.

[0075] The device may further include a calculation means (for example, the purchase price calculation unit 105 in FIG. 6) that calculates the purchase price of the target device based on the third information generated by the second generation means.

[0076] As a result, the purchase price of the target device is calculated based on the third information indicating the deterioration state of the battery of the target device. As a result, the target devices will be traded in at a fair price that takes into account the state of battery deterioration and will be circulated in the second-hand market. [Explanation of symbols]

[0077] 1 Server, 2 Mobile terminal, 3 Store terminal, 11 CPU, 12 ROM, 13 RAM, 14 Bus, 15 Input / output interface, 16 Input section, 17 Output section, 18 Memory section, 19 Communication section, 20 Drive, 40 Removable media, 101 Notification control section, 102 Survey result acquisition section, 103 SOH analysis section, 104 Deterioration diagnosis section, 105 Purchase price calculation section, 181 Survey result DB, 182 Analysis result DB, G Service provider, C Terminal user, S Person in charge, N Network, L Regression curve

Claims

1. an acquisition means for acquiring first information regarding usage of each of the one or more target devices, the first information including at least information regarding the battery of each of the one or more target devices, reported by each of one or more users who use each of the one or more target devices powered by power from a battery; a first generation means for generating, based on the first information acquired by the acquisition means, second information that reflects the usage status of the one or more target devices of each of the one or more users, and indicates a correlation between the usage period of each of the one or more target devices and the state of the battery, the second information being used to estimate the state of a battery of the one or more target devices or another target device; a learning means for executing predetermined machine learning using the first information acquired by the acquisition means and the second information generated by the first generation means based on the first information, and outputting information indicating the correlation between the first information and the second information; a first notification control means for executing control to notify each of the one or more users of a questionnaire consisting of one or more input items; Equipped with the acquiring means acquires, as the first information, a result of the survey by the questionnaire notified under the control of the first notification control means. Information processing system.

2. the acquiring means acquires information indicating a state of the target device as the first information; The information processing system according to claim 1 .

3. and second generating means for generating third information indicating a deterioration state of the battery of the target device based on the first information and the second information.

3. The information processing system according to claim 1 or 2.

4. The system further includes a second notification control unit that controls notification of the third information generated by the second generation unit to the user. The information processing system according to claim 3 .

5. The second notification control means notifying the user of the third information by displaying an image showing the third information on at least a part of a screen that is displayed when the application installed on the target device is being executed; The information processing system according to claim 4 .

6. further comprising a calculation means for calculating a purchase price of the target device based on the third information generated by the second generation means; The information processing system according to claim 3 .

7. An information processing method executed by an information processing system, an acquisition step of acquiring first information regarding usage of each of the one or more target devices, the first information including at least information regarding the battery of each of the one or more target devices, reported by each of one or more users who use each of the one or more target devices powered by power from a battery; a first generation step of generating, based on the first information acquired by the processing of the acquisition step, second information that reflects the usage status of the one or more target devices of each of the one or more users, and indicates a correlation between the usage period of each of the one or more target devices and the state of the battery, and that is used to estimate the state of a battery of the one or more target devices or another target device; a learning step of outputting information indicating a correlation between the first information and the second information by performing predetermined machine learning using the first information acquired in the acquisition step and the second information generated based on the first information in the first generation step; a first notification control step of executing control to notify each of the one or more users of a questionnaire consisting of one or more input items; Including, the acquiring step includes a step of acquiring, as the first information, a result of the survey by the questionnaire notified by the control of the first notification control step. Information processing methods.

8. On the computer, an acquisition step of acquiring first information regarding usage of each of the one or more target devices, the first information including at least information regarding the battery of each of the one or more target devices, reported by each of one or more users who use each of the one or more target devices powered by power from a battery; a first generation step of generating, based on the first information acquired by the processing of the acquisition step, second information that reflects the usage status of the one or more target devices of each of the one or more users, and indicates a correlation between the usage period of each of the one or more target devices and the state of the battery, and that is used to estimate the state of a battery of the one or more target devices or another target device; a learning step of outputting information indicating a correlation between the first information and the second information by performing predetermined machine learning using the first information acquired in the acquisition step and the second information generated based on the first information in the first generation step; a first notification control step of executing control to notify each of the one or more users of a questionnaire consisting of one or more input items; Execute a control process including the acquiring step executes a control process including a step of acquiring, as the first information, the results of the survey by the questionnaire notified by the control of the first notification control step; program.

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