Information processing system and method

Abstract

The purpose of the present invention is to assist a user in smoothly performing a task. An information processing system (1) comprises: a storage unit (110) that stores a personal information database (111), a task information database (112), and a reminder management database (113); and a control unit (120) that includes a registration unit (121), an inference unit (122) which infers an emotion of a user who has been assigned to uncompleted task information, an adjustment unit (123) which adjusts a setting related to a reminder to the user in the task information on the basis of an emotion inference result, and a reminder execution unit (124).

Description

Information Processing System and Method

[0001] The present disclosure relates to an information processing system and method.

[0002] Generally, a user who is a person in charge of a business is assigned a time-limited business as a "task". And an information processing system for managing tasks as information in a database sends a reminder notification to the user assigned to the task information before the deadline when the task information registered in the database has not been completed by the deadline.

[0003] Patent Document 1 discloses a technology related to a schedule management system for sending a reminder notification to a corresponding user about a registered schedule. The schedule management system according to Patent Document 1 senses the situation of the user and calculates an evaluation value from the sensed result. Then, when the evaluation value is greater than or equal to a threshold value, the schedule management system sends a reminder notification to the user.

[0004] Japanese Patent Application Laid-Open No. 2010-117860

[0005] Here, reminder notifications from the information processing system are effective in helping users complete tasks by the deadline. However, the frequency and content of reminder notifications for task information may have different effects on task progress and completion depending on the user's psychological state. In other words, depending on the user's psychological state, even if the task content is the same, a higher frequency of reminders may promote task completion, or conversely, hinder it. Similarly, depending on the user's psychological state, even if the task content is the same, the content of the reminder may affect the user's performance in completing the task. Therefore, reminder settings that take the user's psychological state into consideration are required. Furthermore, reminder notifications from the information processing system are effective in helping the person in charge of the task complete the task by the deadline. In addition, the progress of a task may affect other tasks handled by various stakeholders, such as the person in charge's supervisor or members of the project to which the task belongs. However, the technology described in Patent Document 1 provides reminder notifications based only on the situation of the person in charge who is the target of the reminder. Therefore, there is a challenge in that the timing at which the person in charge takes action on a task in response to a reminder may differ from the timing desired by the stakeholders involved in the task.

[0006] The first objective of this disclosure is to provide an information processing system and method for supporting the smooth execution of tasks by users, in view of the above-mentioned issues. The second objective of this disclosure is to provide an information processing system and method for supporting the smooth execution of tasks by personnel at an effective time for those involved in the task.

[0007] The information processing system described herein comprises an estimation unit that estimates the emotions of a user assigned to incomplete task information, and an adjustment unit that adjusts the settings for reminders to the user in the task information based on the results of the emotion estimation.

[0008] The information processing method according to this disclosure involves a computer estimating the emotions of a user assigned to incomplete task information and adjusting the reminder settings for the user in the task information based on the estimation result of the emotions. Another information processing system according to this disclosure includes a calculation unit that calculates an attention level indicating the degree of attention to the task information by persons other than the person assigned to the incomplete task information, and an adjustment unit that adjusts the reminder settings for the person in charge in the task information based on the attention level. The information processing method according to this disclosure involves a computer calculating an attention level indicating the degree of attention to the task information by persons other than the person assigned to the incomplete task information, and adjusting the reminder settings for the person in charge in the task information based on the attention level.

[0009] This disclosure will help users to smoothly complete tasks. Furthermore, this disclosure will help those involved in the task to smoothly complete tasks at an effective time for all parties involved.

[0010] This is a block diagram showing the overall configuration of the reminder system, including the information processing system related to this disclosure. This is a block diagram showing the configuration of a reminder server, which is an example of the information processing system related to this disclosure. This is a block diagram showing the configuration of an information processing terminal related to this disclosure. This is a flowchart showing the flow of the reminder setting adjustment process related to this disclosure. This is a flowchart showing the flow of the reminder setting adjustment process related to this disclosure. This is a flowchart showing the flow of the reminder notification process related to this disclosure. This is a block diagram showing the overall configuration of the reminder system, including the information processing system related to this disclosure. This is a block diagram showing the configuration of the reminder server, which is an example of the information processing system related to this disclosure. This is a block diagram showing the overall configuration of the reminder system, including configuration of an information processing terminal, which is an example of the information processing system related to this disclosure. This is a block diagram showing the flow of the reminder initial setting process related to this disclosure. This is a flowchart showing the flow of the reminder setting adjustment process related to this disclosure. This is a flowchart showing the flow of the reminder notification process related to this disclosure. This is a flowchart showing the flow of another example of the reminder setting adjustment process related to this disclosure. This is a block diagram showing the overall configuration of the reminder system, including the information processing system related to this disclosure. This is a block diagram showing the configuration of a reminder server, which is an example of the information processing system related to this disclosure. This is a block diagram showing the configuration of an information processing terminal, which is an example of the information processing system related to this disclosure. This is a block diagram showing the overall configuration of the reminder system, including the information processing system, related to this disclosure. This is a block diagram showing the overall configuration of the reminder system, including the information processing system, related to this disclosure.

[0011] In the following, specific embodiments of this disclosure will be described in detail with reference to the drawings. In each drawing, the same elements are denoted by the same reference numerals, and redundant explanations will be omitted where necessary for clarity.

[0012] (Embodiment 1) The information system according to this embodiment 1 estimates the emotions of users assigned to incomplete task information on the server side, and adjusts the reminder settings for the user in the task information based on the emotion estimation result. This supports the smooth execution of tasks by the user.

[0013] Figure 1 is a block diagram showing the overall configuration of a reminder system 1000 including the information processing system 1 according to this disclosure. The reminder system 1000 comprises a reminder server 100, information processing terminals 200-1 to 200-n, and biometric information measuring devices 300-1 to 300-n. Hereinafter, n is a natural number. Each of the reminder server 100, information processing terminals 200-1 to 200-n, and biometric information measuring devices 300-1 to 300-n is connected to communicate via a communication network N. Hereinafter, the communication network N is a wired, wireless, or both type of communication network. The communication network N may include, for example, the Internet. Each of the information processing terminals 200-1 to 200-n shall have equivalent functions. Therefore, in the following description, information processing terminals 200-1 to 200-n may be simply referred to as "information processing terminal 200". Furthermore, each of the biological information measuring devices 300-1 to 300-n shall have equivalent functions. For this reason, in the following description, the biological information measuring devices 300-1 to 300-n may be simply referred to as "biological information measuring device 300". In addition, each of the users U1 to Un shall be assigned a task with at least a deadline as task information. Each of the users U1 to Un shall process and complete the task information assigned to them using the information processing terminal 200 or the like. At least some of the users U1 to Un may be persons belonging to an organization such as a company. For this reason, in the following description, users U1 to Un may be simply referred to as "user U".

[0014] The reminder system 1000 is an information processing system that assigns tasks to each of the users U1 to Un and sends reminder notifications to the information processing terminal 200, etc., of the assigned user U for tasks that are not yet completed and are registered in the database described later. Here, "not completed" refers to a state in which the status of the task information is not marked as "completed," meaning that the deadline for completion of the task information has passed, or that the deadline for completion of the task information has not passed and it is in progress, i.e., it is being processed. The number of users to be reminded only needs to be at least one. Therefore, the reminder system 1000 only needs to include at least one set of information processing terminals 200 and a biometric information measuring device 300, and a reminder server 100. Furthermore, the reminder server 100 is an example of the information processing system 1 according to this embodiment. Therefore, the reminder system 1000 can be said to include the information processing system 1.

[0015] The biological information measuring device 300 is a device that measures the biological information of user U, who is the target of measurement. The biological information measuring device 300 should continuously measure biological information at regular intervals. In other words, the biological information measuring device 300 may constantly monitor the biological information of user U. Here, biological information includes, but is not limited to, biomarkers such as heart rate, skin conduction response, and movement. For example, the biological information measuring device 300 may measure multiple channels of measurement data and biological information using sensors for measuring electroencephalography (EEG) or electrocardiogram (ECG). For example, the biological information measuring device 300 may be an electroencephalograph or an electrocardiogram measuring device.

[0016] Alternatively, the biometric information measuring device 300 may be installed in close proximity to each user U, or it may be a wearable terminal attached to each user U. In the example in Figure 1, the biometric information measuring device 300-1 measures the biometric information of user U1. Similarly, the biometric information measuring device 300-n measures the biometric information of user Un. For example, the biometric information measuring device 300-1 includes the biometric information measured from user U1, along with user U1's identification information and measurement date and time, etc., in a registration request and sends the registration request to the reminder server 100 via the communication network N. The reminder system 1000 may also include a dedicated biometric information analysis server that collects and analyzes the biometric information measured from each user U by each biometric information measuring device 300-1 to 300-n via the communication network N. In that case, the biometric information analysis server sends the analysis results and measurement results for each user U, as well as a registration request including user U's identification information and measurement date and time, etc., to the reminder server 100 via the communication network N.

[0017] Alternatively, for example, the biometric information measuring device 300-1 may be connected to the information processing terminal 200-1 used by user U1 via short-range wireless or wired communication. In this case, the biometric information measuring device 300-1 may transmit the measured biometric information, etc., to the information processing terminal 200-1. The information processing terminal 200-1 may then transmit a registration request, including the biometric information received from the biometric information measuring device 300-1, the identification information of user U1, and the measurement date and time, etc., to the reminder server 100 via the communication network N.

[0018] The information processing terminal 200 is an information processing device used by user U to process tasks corresponding to task information. In the example in Figure 1, information processing terminal 200-1 is used by user U1, and similarly thereafter, information processing terminal 200-n is used by user Un. However, it is not necessary for each user U to have one information processing terminal 200; one information processing terminal 200 may be shared by multiple users U. Also, one user U may use multiple information processing terminals 200. In these cases, the information processing terminal 200 shall identify the user U using it by login information. The detailed configuration of the information processing terminal 200 will be described later.

[0019] The information processing terminal 200 is assumed to be connected to various peripheral devices, such as a camera, microphone, input device for operation information, display device, and speaker (configurations not shown), via wired or wireless communication. Some or all of the above peripheral devices may be built into the information processing terminal 200. The camera captures the user U's face and actions, and outputs the captured image data to the information processing terminal 200. The image data is, for example, a general-purpose image format such as JPEG (Joint Photographic Experts Group) or PNG (Portable Network Graphics) of a predetermined image size, but is not limited to these. The microphone acquires the user U's speech and voice tone as sound data and outputs the acquired sound data to the information processing terminal 200. Here, the audio data is either uncompressed or compressed audio data in audio file formats such as WAV (Waveform Audio Format) or AIFF (Audio Interchange File Format). However, the audio file format is not limited to these. The input device is a keyboard or mouse. The input device acquires keyboard and mouse operation information from user U and outputs the acquired operation information to the information processing terminal 200. The display device displays the display information input from the information processing terminal 200 on the screen. The speaker outputs the audio data input from the information processing terminal 200.

[0020] Figure 2 is a functional block diagram showing the configuration of a reminder server 100, which is an example of the information processing system 1 according to this disclosure. The reminder server 100 is an information processing device that manages personal information, task information, and reminder setting information for users U assigned to incomplete task information. The "reminder setting information" is an example of "settings related to reminders." The reminder server 100 also performs reminder notification processing for users U assigned to incomplete task information based on the reminder setting information. The reminder server 100 may be implemented as a computer system with distributed or redundant functions using multiple computer devices. The reminder server 100 comprises a storage unit 110, a control unit 120, and an IF (Interface) unit 130.

[0021] The storage unit 110 includes, for example, a non-volatile storage device such as a hard disk or flash memory, and a memory such as RAM (Random Access Memory), i.e., a volatile storage device. The storage unit 110 stores a personal information DB (DataBase) 111, a task information DB 112, and a reminder management DB 113. The personal information DB 111, task information DB 112, and reminder management DB 113 can be said to correspond to storage areas managed by database management software. Furthermore, the task information DB 112 may include the reminder management DB 113.

[0022] The personal information database 111 is a database that manages user information, biometric data, operation history, personality information, etc., for each user U. User information, biometric data, operation history, personality information, etc. may also be called personal information. User information may include identification information that identifies each user U, personal information such as name, and organizational attribute information such as department, position, and job title. User information also includes the recipient of reminder notifications, i.e., destination information. Destination information may include, but is not limited to, the user U's email address, identification information and address information of the information processing terminal 200 used by the user U, the user U's login ID, and account information for information systems such as SNS (Social Networking Service).

[0023] The biometric information group is a collection of biometric information and measurement date and time, etc., measured by the biometric information measuring device 300 described above. The biometric information group is associated with personal information corresponding to the identification information of user U included in the registration request for biometric information, etc., received from the biometric information measuring device 300. The biometric information group may also include at least one or both of the following: image data of user U's facial expression captured during operation of the information processing terminal 200, or voice data of user U recorded during operation of the information processing terminal 200. The image data and voice data are associated with the date and time when they were captured or recorded.

[0024] The operation history may include input information from input devices such as the keyboard and mouse, recorded when each user U operates the information processing terminal 200. The input information from input devices may also include finger pressure information during keyboard input. Furthermore, the operation history associates the above-mentioned input information with the date and time it was recorded.

[0025] Personality information should include information that each user U has self-analyzed by answering questionnaires, etc., as well as information that indicates user U's personality as evaluated and analyzed by related parties such as user U's superiors, colleagues, and subordinates.

[0026] Task Information DB112 is a database that manages the content, progress, and processing history of task information assigned to each user U. For example, task information may include task ID, task name, task content, assignee, completion deadline, completion date or completion flag, category, affiliated project, stakeholders, importance or priority, remarks, etc. The assignee is user information such as the user ID to which the task information is assigned. The completion deadline may also be called the scheduled completion date and time of the task information. Stakeholders are the user information of the assignee's superiors, colleagues, subordinates, etc., or users belonging to the affiliated project. Furthermore, task information may include multiple subtasks. Subtask information may include subtask ID, subtask name, subtask content, completion deadline, completion date or completion flag, etc. A subtask is a milestone that specifically subdivides a task. For example, if the task is a presentation, subtasks may include information gathering, graph creation, document creation, proofreading of materials, presentation, etc. Task information may also include the user U's level of interest in the task content, the assignee's usual work content, etc.

[0027] The progress status is information indicating the degree of progress and status of task information for each task ID. The progress status may also be able to identify whether the corresponding task information is incomplete. The processing history includes task information for which the completion date has been entered or the completion flag is turned on, and at least the task ID. Note that the task information managed in the task information DB112 is not limited to what is described above.

[0028] The reminder management DB 113 is a database that manages reminder settings for user U, who is the person in charge of the task information managed in the task information DB 112, that is, reminder setting information. The reminder management DB 113 may, for example, manage the reminder setting information and reminder history in association with the task ID or subtask ID. The task ID or subtask ID uniquely corresponds to the information contained in the task information DB 112 mentioned above. In addition, the reminder management DB 113 may further associate the destination information of the reminder notification with the task ID or subtask ID. The destination information is the destination information of user U contained in the personal information DB 111 for the person in charge whose user information is associated with the task ID or subtask ID in the task information DB 112. The reminder setting information includes the frequency, number of reminders, and intervals of reminders, as well as the content of the reminders. The reminder setting information may also include the scheduled date and time of the reminder. The content of the reminders may include text information included in the reminder notification, operation instruction information to operate the information processing terminal 200 that receives the reminder notification, etc. Text information is part of the display information shown on the screen by the information processing terminal 200 that received the reminder notification. Action instruction information is information that instructs the information processing terminal 200 on what action to take upon receiving the reminder notification. The action may be, for example, a pop-up display, an alarm sound, or a voice message. If the information processing terminal 200 is a portable information terminal, the action may be vibration of the information processing terminal 200. The reminder history may include the date and time of the reminder notification, the content of the notified reminder, etc.

[0029] The control unit 120 is a control device that controls each component of the reminder server 100. The control unit 120 is a processor such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), or quantum processor (quantum computer control chip). For example, the control unit 120 loads a program from the storage unit 110 into memory and executes the program. The program is a computer program that implements the processing of the information processing method according to this disclosure, although its configuration is not shown. As a result, the control unit 120 realizes the functions of the registration unit 121, estimation unit 122, adjustment unit 123, and reminder execution unit 124. Furthermore, some or all of the registration unit 121, estimation unit 122, adjustment unit 123, and reminder execution unit 124 may be implemented in hardware separate from the control unit 120, for example, in a general-purpose or dedicated circuit implemented in a semiconductor device.

[0030] When the registration unit 121 receives a registration request from an information processing terminal 200 or a biometric information measuring device 300, it registers the received information and setting information generated in response to the registration request in the personal information DB 111, task information DB 112, or reminder management DB 113, according to the information contained in the registration request.

[0031] The estimation unit 122 estimates the emotions of user U assigned to incomplete task information. Specifically, the estimation unit 122 searches the task information DB 112 for task information where the completion date is not entered or the completion flag is off, and identifies the user information assigned as the person in charge to the task information that matches the search. The estimation unit 122 may also search the task information DB 112 for incomplete task information by referring to the progress status. Alternatively, the estimation unit 122 may search the reminder management DB 113 for incomplete task information. Then, the estimation unit 122 estimates the emotions of user U corresponding to the user information based on at least one of the biometric information group or operation history included in the identified user information from the personal information DB 111.

[0032] For example, the estimation unit 122 may estimate user U's emotions based on a set of biological information, using physiological biometrics as an evaluation scale. Specifically, the estimation unit 122 may analyze biological information such as heart rate, skin conduction response, electroencephalogram, and electrocardiogram measurement data measured from user U to generate models of user U's concentration level, mental fatigue level, stress level, etc., and estimate the mental state, i.e., user U's emotions, from the models. If the set of biological information is image data or audio data, the estimation unit 122 may estimate user U's emotions based on the set of biological information by processing described later.

[0033] Furthermore, the estimation unit 122 may estimate user U's emotions based on user U's operation history. Specifically, the estimation unit 122 may identify input information from an input device during the time period when user U was processing the retrieved task information, or during the time period immediately before or after that time period, in user U's operation history. For example, if the operation history contains a string related to the relevant task information in the file name, the estimation unit 122 may identify the time period when that file was being edited as the time period when user U was processing the retrieved task information. Alternatively, if the operation history includes a specific application used to process the relevant task information, the estimation unit 122 may identify the time period when that application was used as the time period when user U was processing the retrieved task information. Alternatively, the estimation unit 122 may identify image data and voice data of user U during the time period identified from user U's operation history as user U's biometric information from the biometric information group in the personal information DB 111. Therefore, it can be said that the input information etc. identified by the estimation unit 122 includes at least one or both of user U's operation history and / or biometric information.

[0034] The estimation unit 122 then analyzes user U's behavior, key input content, finger pressure during key input, typing speed, facial expressions, voice tone, etc., from the identified input information, using an AI (Artificial Intelligence) based motion prediction algorithm. Specifically, the estimation unit 122 may use methods such as neural networks, support vector machines, decision trees, and k-nearest neighbors as the AI-based motion prediction algorithm. Here, the estimation unit 122 may estimate user U's emotions from the identified input information. For example, the estimation unit 122 may use an identification method based on a learning model generated by machine learning the combinations of each input information item and the corresponding emotions in advance, for emotion estimation based on key input content, finger pressure during key input, typing speed, facial expressions, voice tone, and voice.

[0035] Furthermore, the estimation unit 112 may perform emotion estimation of user U based on user U's voice. In this case, known voice-based emotion recognition techniques may be used for voice-based emotion estimation. For example, for voice-based emotion estimation, statistical quantities (mean, variance, slope, etc.) of features such as pitch (frequency) and volume extracted multiple times in a time series may be calculated, and the emotion contained in the voice may be estimated by estimating the emotion category to which the feature vector belongs and its coordinate value in the emotion space from a multidimensional feature vector converted from the voice signal. Here, the machine learning methods described above may be used for emotion estimation based on the feature vector. Then, the estimation unit 122 may estimate user U's emotion based on the above analysis results.

[0036] Furthermore, the estimation unit 122 may analyze the user's emotional state by analyzing the user's typing speed and key input content during the processing of specific task information from the operation history. For example, the estimation unit 122 may estimate the emotional state based on typing speed and rhythm. For instance, fast typing speeds often indicate concentration and positive emotions, while slow typing may indicate negative emotions such as high stress or difficulty in processing the task information being processed. Also, if the typing rhythm changes at regular intervals, it may indicate stable emotions, while irregular rhythms may indicate anxiety or impatience. The estimation unit 122 may also use keystroke dynamics technology to measure the time each key is held down and estimate the emotional state. For example, long key press times may indicate fatigue or stress. Additionally, a high error rate may indicate that the user is experiencing stress. Therefore, the estimation unit 122 should take these factors into account when estimating the emotional state of the user U based on typing speed and key input content. In this context, typing speed refers to an indicator that measures how many characters can be entered within a certain amount of time. For example, it measures the number of characters that can be entered per minute (WPM: Words Per Minute). For instance, if user U can enter 50 words per minute, their typing speed is 50 WPM.

[0037] Furthermore, the estimation unit 122 may estimate user U's emotions based on a combination of user U's biometric information and operation history. In addition, the estimation unit 122 may estimate user U's emotions by adding user U's personality information to at least one of the biometric information and operation history.

[0038] Furthermore, the estimation unit 122 may estimate user U's emotion as one of several levels in a predetermined index indicating user U's psychological state in response to task information. Specifically, the estimation unit 122 may estimate user U's emotion level using the aforementioned biometric information group or operation history. For example, the estimation unit 122 may determine positive emotion on a three-level scale, or negative emotion on a three-level scale. In this case, for example, the estimation unit 122 estimates a larger value for the number representing the level of positive emotion as user U's positive emotion towards task information increases. Alternatively, the estimation unit 122 estimates a larger value for the number representing the level of negative emotion as user U's negative emotion towards task information increases. Alternatively, the emotion levels may be set to three levels: "negative" as level 1, "positive and non-negative" as level 2, and "positive" as level 3. Alternatively, the degree from positive to negative may be used as an index of user U's psychological state. For example, if the emotional level is set on a scale of 1 to 10, levels 1 to 5 may represent positive emotions, and levels 6 to 10 may represent negative emotions. In this case, positive emotions would be higher at level 1 than at level 5, and negative emotions would be higher at level 10 than at level 6. Note that the emotional level is not limited to this example, as long as there are two or more levels. Alternatively, the estimation unit 112 only needs to be able to estimate the user U's emotion as a level that indicates at least one of either positive or negative emotions in relation to the task information. Alternatively, the estimation unit 122 may estimate the levels of positive and negative emotions of the user U in relation to the task information as numerical values.

[0039] User U's emotions towards task information may include, for example, the following: If User U repeatedly writes and deletes while editing a file related to specific task information, it is possible that User U is having difficulty processing that task. In that case, the estimation unit 122 may simply estimate User U's emotions towards the specific task information as "negative" without classifying them into levels. Conversely, if User U does not repeatedly write and delete while editing a file related to specific task information, it may simply be estimated as "positive." Alternatively, the level of emotion may be classified according to the editing time and the number of characters repeatedly edited when writing and deleting are repeatedly performed on the file related to the specific task information. For example, if the editing time and number of characters are below a predetermined value, the estimation unit 122 may estimate a higher level of positive emotion, and if they are above the predetermined value, it may estimate a higher level of negative emotion compared to when they are below the predetermined value. This allows the settings related to reminders to be adjusted to appropriate information according to the level. Furthermore, when estimating the level of emotion based on User U's voice, for example, a trained model that has been machine-learned may be used. For example, an emotion level estimation AI model can be used that takes a multidimensional feature vector converted from an audio signal as input and outputs a level of positive or negative emotion. The input data of the multidimensional feature vector converted from the audio signal and the output data of the emotion level are used as training data. Machine learning is then performed on the emotion level estimation AI model using this training data. As a result, the estimation unit 122 may use the trained model of the emotion level estimation AI model that has undergone machine learning to estimate the emotion level based on the user U's voice. In this way, the settings related to reminders can be adjusted to appropriate information according to the level.

[0040] Furthermore, the estimation unit 122 may estimate user U's emotions at the time new task information is assigned to user U. In other words, the estimation unit 122 may estimate user U's emotions from biometric information measured at the time new task information is assigned to user U or from acquired operation history in the most recent time period. This allows for a more accurate estimation of user U's emotions regarding the assigned task information.

[0041] Furthermore, the estimation unit 122 may estimate the user U's emotions multiple times while the task information is incomplete. For example, the estimation unit 122 may estimate the user U's emotions multiple times using measured biometric information and acquired operation history while the user U is processing specific task information. This makes it possible to understand the changes and trends in the user U's emotional level during processing specific task information. Therefore, the reminder settings described later can be adjusted more appropriately.

[0042] Furthermore, the estimation unit 122 may estimate the user's emotions by taking into account the completion status of task information previously handled by the user U. The completion status here refers to actual processing information related to task information, such as the processing content of completed task information, the relationship between reminder notifications and processing dates, and the relationship between the deadline and the actual completion date. Specifically, the estimation unit 122 may refer to the processing history of the task information DB 112, identify past task information related to the task information that the user U is currently processing, i.e., incomplete, and estimate the user U's emotions regarding the task information currently being processed by taking into account the completion status of the identified past task information. For example, the estimation unit 122 may identify past task information that is similar to the task information currently being processed in terms of task content, category, affiliated project, stakeholders, or importance. Then, the estimation unit 122 may estimate the user U's emotions regarding the task information currently being processed by taking into account the difference between the deadline and the actual completion date of the identified past task information, the progress in response to reminder notifications, etc. For example, if the actual completion date of a identified past task was earlier than the deadline, it can be inferred that the user felt good about that task. Therefore, in such cases, the estimation unit 122 may estimate that user U's emotions regarding the task currently being processed are positive, or estimate a higher level of positivity. Conversely, if the actual completion date of a identified past task was close to or after the deadline, the estimation unit 122 may estimate that user U's emotions are negative, or estimate a higher level of positivity. The estimation unit 122 may also estimate user U's emotions based on user U's emotions or emotional changes when user U checked the reminder notification for the identified past task, or on the emotional changes of user U in the past regarding the task currently being processed. Alternatively, the estimation unit 122 may refer to the personal information DB 111 and estimate user U's emotions at the time based on user U's biometric information or operation history during the processing period of the identified past task. The estimation unit 122 then takes into account the estimation results of user U during the processing period of the identified past task information to estimate user U's emotions in the currently processing task information.This can improve the accuracy of estimating the user U's emotion with respect to the assigned task information. Note that the emotion estimation process is not limited to these, and known emotion estimation techniques may be used.

[0043] The adjustment unit 123 adjusts the settings regarding the reminder for the user U in the task information based on the emotion estimation result by the estimation unit 122. Specifically, the adjustment unit 123 updates the reminder setting information in the reminder management DB 113 in the corresponding task information based on the emotion estimation result by the estimation unit 122. For example, the adjustment unit 123 may determine the initial setting of the reminder setting information based on the emotion estimation result at the timing when new task information is assigned to the user U, and register the determined initial setting as the reminder setting information in the reminder management DB 113. Also, the adjustment unit 123 may update the reminder management DB 113 so as to change the reminder setting information based on the emotion estimation result of the user U in the incomplete task information. Also, the adjustment unit 123 may update the reminder management DB 113 so as to change the reminder setting information in the incomplete task information based on the transition of the continuously estimated emotion of the user U. Also, the adjustment unit 123 may adjust the reminder setting information so as to include all the information registered in the task information or the information focused on some important points in the reminder content based on the emotion estimation result.

[0044] In particular, the adjustment unit 123 may determine whether the emotion level in the estimation result is equal to or higher than a predetermined threshold, and adjust the settings regarding the reminder so as to change at least either the number of reminders or the content according to the determination result. Thus, by adjusting the number of reminders and the content in view of the user's emotion, it is possible to support the execution of tasks in line with the user's psychological state.

[0045] For example, if the threshold is negative emotion level 3, the adjustment unit 123 determines whether user U's emotional level to the newly assigned task information is negative emotion level 3 or higher. If the estimated emotional level of user U is negative emotion level 3, the adjustment unit 123 determines that user U's emotional level is negative emotion level 3 or higher. Also, if the estimated emotional level of user U is "positive" or "other than positive and negative," the adjustment unit 123 may determine that user U's emotional level is less than negative emotion level 3. Similarly, if the estimated emotional level of user U is negative emotion level 1 or 2, the adjustment unit 123 also determines that user U's emotional level is less than negative emotion level 3.

[0046] For example, if the estimated emotion of user U to newly assigned task information is "positive," the adjustment unit 123 may determine the initial settings for the reminder settings information to be less frequent or longer in frequency and interval compared to when the estimated emotion is "negative," and register this in the reminder management DB 113. In this case, since user U's psychological state is positive towards the task information, setting the timing of the reminder notification earlier than the default can encourage user U to complete the task. In this case, the adjustment unit 123 may also adjust the reminder settings information by adding wording that urges user U to submit or report quickly. In these cases, since user U's psychological state to the assigned task information is positive, slightly increasing the burden on user U can encourage user U to complete the task.

[0047] On the other hand, when the estimation result of the user U's emotion regarding the newly assigned task information is "negative", the adjustment unit 123 may determine an initial setting in which the text of the reminder notification is expressed more politely compared to the case where the estimation result is "positive", and register it in the reminder management DB 113. For example, when the task information is document creation, the adjustment unit 123 may elaborate on the content of the reminder notification, such as including the information of the user to whom the document is to be reviewed in the text of the reminder notification. Alternatively, when the estimation result of the emotion is "negative", the adjustment unit 123 may determine an initial setting for the content that extracts some important points and register it in the reminder management DB 113. Alternatively, when the estimation result of the emotion is "negative", the adjustment unit 123 may determine, as an initial setting, the content that reveals information such as the person related to the corresponding task information, for example, the person waiting for the completion of the corresponding task information, and register it in the reminder management DB 113.

[0048] Alternatively, when the estimation result of the emotion is "negative", the adjustment unit 123 may determine an initial setting for the refined reminder setting information to send reminder notifications for each completion deadline of the subtasks of the task information, compared to the case where the estimation result is "positive", and register it in the reminder management DB 113. For example, when the task information is document creation, the deadline for creating the first draft of the document, that is, the deadline for requesting review from the supervisor, is set as subtask 1, and the deadline for revising the document is set as subtask 2. In this way, the adjustment unit 123 may set the tasks for sending multiple reminder notifications from the task information as subtasks and determine the subtasks as the initial setting of the reminder setting information. In these cases, since the psychological state of the user U to whom the corresponding task information is assigned is negative, by setting the hurdle for task achievement low, the execution of the task by the user U can be supported. Also, the adjustment unit 123 may adjust not only the initial setting but also change the reminder setting information at any timing based on the estimation result of the emotion of the user U at that time during the period from the start to the completion of the processing of the corresponding task information by the user U.

[0049] Furthermore, the set of emotional levels estimated multiple times within a certain period shall be called the emotional psychological state or simply the emotional state. In this case, if negative emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "negative." Similarly, if positive emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "positive." Here, if the adjustment unit 123 indicates that the emotional psychological state in the multiple estimation results has transitioned from a first state to a second state, and that the second state has been maintained for a certain period of time, it may adjust the settings related to the reminder. For example, let's say the first state is "positive" and the second state is "negative." In this case, suppose the adjustment unit 123 determines from the multiple estimation results that user U's emotional psychological state has transitioned from "positive" to "negative," and that the "negative" psychological state has been maintained for several hours. In such a case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information to lower the hurdle for task completion as described above.

[0050] On the other hand, the first state is defined as "negative," and the second state as "positive." In this case, the adjustment unit 123 determines, based on multiple estimation results, that user U's emotional psychological state shifted from "negative" to "positive," and that this "positive" psychological state was maintained for several hours. In such cases, the adjustment unit 123 may adjust the reminder settings by changing the timing of the reminder notification for the relevant task information earlier, reducing the number of reminder notifications, or adding wording to the reminder content that urges submission or reporting to be expedited. In these cases, it is considered that user U has overcome the peak of processing the relevant task information, and as described above, by slightly increasing the burden on user U, it is possible to promote user U's task completion. Therefore, the adjustment unit 123 can flexibly adjust reminders based on the transition of user U's emotions, based on multiple estimation results. It should also be noted that the above-mentioned emotional psychological state can be applied to emotional levels.

[0051] Furthermore, the estimation unit 122 may estimate the user U's level of tension. The estimation unit 122 estimates that user U is in a state of tension when the heart rate velocity among user U's biometric information is above a predetermined speed. The adjustment unit 123 may adjust the reminder setting information for the relevant task information based on the estimation result of user U's level of tension, by including operational instruction information other than screen display, such as voice notifications and keyboard operation changes, which are displayed as pop-up screens on the screen of the information processing terminal 200. For example, if user U is in a state of tension, the adjustment unit 123 may assume that user U's concentration is scattered. In this case, it is advisable to adjust the reminder setting information for the relevant task information by adding operational instruction information for voice notifications. Alternatively, in this case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information by adding operational instruction information that is displayed as a pop-up screen on the screen of the information processing terminal 200 at a position where user U's gaze is focused, along with a warning sound, and that does not accept other terminal operations until the pop-up screen is confirmed. Furthermore, if user U is in a state of tension, the adjustment unit 123 may assume that user U is rushing to process the task. In this case, it is advisable to adjust by adding an action instruction to reduce the depth of key input to the reminder setting information of the relevant task. Also, if user U is in a state of tension, the adjustment unit 123 may assume that user U is panicking and not calm. In this case, it is advisable to adjust by adding an action instruction to display a pop-up for final confirmation to the reminder setting information of the relevant task.

[0052] The reminder execution unit 124 refers to the reminder management DB 113 to identify the task information to be reminded and sends a reminder notification based on the reminder setting information to the destination information of user U to which the identified task information is assigned. Specifically, the reminder execution unit 124 identifies a task ID or subtask ID for which the timing of the reminder notification is set to be a predetermined period before the completion deadline of the task information, based on the reminder setting information in the reminder management DB 113. Then, the reminder execution unit 124 identifies the user information set as the person in charge for the identified task ID or subtask ID from the task information DB 112. Then, the reminder execution unit 124 identifies the destination information included in the identified user information from the personal information DB 111. Then, the reminder execution unit 124 generates a reminder notification message that includes the reminder content included in the reminder setting information for the identified task ID or subtask ID and sends the reminder notification message to the destination information via the communication network N. Furthermore, when user U completes the assigned task information, the reminder execution unit 124 registers the completion date and time in the task information DB 112's completion date field, or updates the completion flag to ON. In this case, the reminder execution unit 124 also registers the completion of the corresponding task information in the task information DB 112 in the progress status and processing history. In addition, the reminder execution unit 124 may also delete the information related to the corresponding task information from the reminder management DB 113 and move it to the processing history or other locations in the task information DB 112.

[0053] The IF unit 130 is an interface circuit that communicates between the reminder server 100 and the outside world. Specifically, the IF unit 130 communicates with information processing terminals 200-1 to 200-n and biological information measuring devices 300-1 to 300-n via the communication network N. The IF unit 130 may be implemented, for example, as a general-purpose or dedicated circuit implemented in a semiconductor device. Alternatively, the IF unit 130 may be implemented as a combination of the above-mentioned communication circuit and software that controls the communication processing.

[0054] Figure 3 is a block diagram showing the configuration of an information processing terminal 200 according to this disclosure. The information processing terminal 200 comprises a storage unit 210, a control unit 220, and an IF unit 230. The storage unit 210 includes, for example, a non-volatile storage device such as a hard disk or flash memory, and a memory such as RAM, i.e., a volatile storage device. The storage unit 210 stores behavioral information 211 and biological information 212.

[0055] The behavioral information 211 includes user U's image data, sound data, and operation information, etc. The behavioral information 211 may also include information indicating user U's actions, analyzed from the image data, sound data, and operation information, etc. Each piece of data and information in the behavioral information 211 is associated with the date and time of acquisition.

[0056] The biological information 212 is biological information measured by the biological information measuring device 300 from user U. The biological information 212 includes the date and time of measurement.

[0057] The control unit 220 is a control device that controls each component of the information processing terminal 200. The control unit 220 is a processor such as a CPU, GPU, FPGA, or quantum processor. For example, the control unit 220 loads a program from the storage unit 210 into memory and executes the program. The program, although not shown in the diagram, is a computer program that implements various processes in the information processing terminal 200 according to this disclosure. As a result, the control unit 220 realizes the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223. Some or all of the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223 may be realized by hardware other than the control unit 220, such as a general-purpose or dedicated circuit implemented in a semiconductor device.

[0058] The acquisition unit 221 acquires image data from the camera, capturing the user U's face, movements, etc. The acquisition unit 221 also acquires sound data, including the user U's voice, from the microphone. The acquisition unit 221 also acquires user U's operation information from the input device. The acquisition unit 221 registers the acquired image data, sound data, and operation information as activity information 211 in the storage unit 210, associating them with the acquisition date and time. The acquisition unit 221 also acquires user U's biological information from the biological information measuring device 300, and registers the acquired biological information as biological information 212 in the storage unit 210, associating the measurement date and time with the acquired biological information.

[0059] The transmitting / receiving unit 222 transmits the behavioral information 211 and biometric information 212 registered in the storage unit 210 to the reminder server 100 via the communication network N. The transmitting / receiving unit 222 may transmit data or information each time the acquisition unit 221 acquires data or information, or each time data or information is registered in the storage unit 210. Alternatively, the transmitting / receiving unit 222 may periodically transmit untransmitted data or information from the storage unit 210.

[0060] Furthermore, the transmitting / receiving unit 222 receives reminder notifications from the reminder server 100 via the communication network N. The transmitting / receiving unit 222 then outputs display information, such as messages, included in the received reminder notification to the display control unit 223. If the received reminder notification includes operation instruction information, the transmitting / receiving unit 222 outputs the operation instruction information to the appropriate output destination. For example, if the operation instruction information includes a pop-up display, the transmitting / receiving unit 222 outputs the pop-up display instruction information to the display control unit 223. If the operation instruction information includes an alarm sound or voice message, the transmitting / receiving unit 222 outputs the alarm sound or voice message to the speaker via the IF unit 230. If the operation instruction information includes vibration, the transmitting / receiving unit 222 outputs a vibration instruction to the IF unit 130.

[0061] The display control unit 223 controls the display device to display the display information received from the transmitting / receiving unit 222. When the display control unit 223 receives instruction information for a pop-up display from the transmitting / receiving unit 222, it controls the display device to display a pop-up.

[0062] The IF unit 230 is an interface circuit that performs communication between the information processing terminal 200 and the outside. Specifically, the IF unit 130 communicates with the reminder server 100 via the communication network N. Furthermore, the IF unit 230 may also communicate with the biological information measuring device 300 via short-range wireless communication or wired communication. The IF unit 130 also outputs captured images, etc., received from the connected camera to the storage unit 110 via the control unit 120. The IF unit 130 also outputs sound data received from the connected microphone to the storage unit 110 via the control unit 120. The IF unit 130 also outputs input information received from the connected input device to the control unit 120. The IF unit 130 also outputs display information received from the control unit 120 to the display device. The IF unit 130 also outputs sound data received from the control unit 120 to the speaker. Furthermore, the IF unit 130 outputs the operation instruction information received from the control unit 120 to the vibration circuit. The IF unit 130 may be implemented, for example, by a general-purpose or dedicated circuit implemented in a semiconductor device. Alternatively, the IF unit 130 may be implemented by a combination of the above-mentioned communication circuit and software that controls the communication process.

[0063] Figure 4 is a flowchart showing the flow of the reminder setting adjustment process when new task information is assigned to user U as per this disclosure.

[0064] For example, User U's supervisor registers new task information, including its contents, completion deadline, and assigned person, as User U, on the information processing terminal. In response, the information processing terminal sends a registration request, including the task information and assigned person, to the reminder server 100 via the communication network N. In response, the registration unit 121 of the reminder server 100 acquires the task information to which User U has been assigned (S101). The registration unit 121 then registers the acquired task information in the task information DB 112. The registration unit 121 then registers the initial reminder settings for the acquired task information in the reminder management DB 113 (S102).

[0065] Furthermore, user U, who has been assigned the above task information, confirms via the information processing terminal 200 that new task information has been assigned to them, in response to contact from their supervisor or notification from the reminder server 100 regarding the person in charge of the task information. Around this time, the biometric information measuring device 300 measures user U's biometric information and transmits the measured biometric information, measurement date and time, and user U's identification information to the information processing terminal 200. In response, the acquisition unit 221 of the information processing terminal 200 acquires user U's biometric information from the biometric information measuring device 300. Also, when user U confirms the assigned task information, the acquisition unit 221 acquires user U's image data, sound data, and behavioral information 211 such as operation information. Then, the transmitting / receiving unit 222 of the information processing terminal 200 transmits a registration request including the behavioral information 211 and biometric information 212 to the reminder server 100 via the communication network N. Furthermore, the biometric information measuring device 300 may send a registration request, including the measured biometric information, to the reminder server 100 via the communication network N without going through the information processing terminal 200. In this case, the transmitting / receiving unit 222 of the information processing terminal 200 shall send a registration request, including the behavioral information 211, to the reminder server 100 via the communication network N.

[0066] Accordingly, the registration unit 121 of the reminder server 100 obtains a registration request including user U's biometric information and behavioral information from the information processing terminal 200 via the communication network N (S103). Alternatively, the registration unit 121 may obtain a registration request including user U's biometric information from the biometric information measuring device 300 via the communication network N, and a registration request including user U's behavioral information from the information processing terminal 200 via the communication network N. Then, the registration unit 121 registers the biometric information and behavioral information obtained in step S103 into user U's personal information DB 111 (S104).

[0067] Next, after steps S102 and S104, the estimation unit 122 estimates user U's emotions from the personal information database 111 (S105). At this point, user U has just been assigned new task information and has become aware of it, so the estimation unit 122 estimates user U's emotions assigned to the incomplete task information. Then, the adjustment unit 123 adjusts the reminder settings corresponding to the retrieved task information based on the emotion estimation result (S106). For example, the adjustment unit 123 adjusts by determining the changes to the reminder setting information according to whether the emotion estimation result is "positive," "negative," or "other than positive and negative." After that, the adjustment unit 123 updates the reminder management database 113 with the adjusted reminder setting information (S107). Then, the reminder server 100 finishes the reminder setting adjustment process.

[0068] Figure 5 is a flowchart showing the flow of the reminder setting adjustment process when task information assigned to user U under this disclosure is being processed.

[0069] For example, suppose user U is performing operations related to task information assigned to them using the information processing terminal 200. Around this time, as described above, the biometric information measuring device 300 measures user U's biometric information, and the acquisition unit 221 of the information processing terminal 200 acquires user U's image data, sound data, and behavioral information 211 such as operation information. Then, as described above, the transmitting / receiving unit 222 of the information processing terminal 200 sends a registration request including the behavioral information 211 and biometric information 212 to the reminder server 100 via the communication network N. Alternatively, as described above, the biometric information measuring device 300 may send a registration request including the measured biometric information, etc., to the reminder server 100 via the communication network N without going through the information processing terminal 200. In this case, the transmitting / receiving unit 222 of the information processing terminal 200 will send a registration request including the behavioral information 211 to the reminder server 100 via the communication network N.

[0070] In response to these, the registration unit 121 of the reminder server 100 acquires a registration request including the biometric information and behavioral information of user U, similar to step S103 described above (S201). Then, the registration unit 121 registers the biometric information and behavioral information acquired in step S201 into the user U's personal information DB 111 (S202).

[0071] Subsequently, the estimation unit 122 determines whether user U is processing task information based on the behavior information (S203). For example, the estimation unit 122 identifies user U's behavior information registered in the personal information DB 111 in step S202 from the personal information DB 111. Then, the estimation unit 122 refers to the task information DB 112 and, for example, determines whether user U is processing specific task information based on the operation history among the behavior information, such as the file name being edited or the application being used.

[0072] In step S203, if it is determined that user U is processing task information (YES in S203), the estimation unit 122 estimates the changes in user U's emotions from the personal information database 111 (S204). For example, the estimation unit 122 searches the personal information database 111 for a certain period of time from the present to a predetermined time ago for user U's biometric information and operation history. At this time, the estimation unit 122 may also search the personal information database 111 for the biometric information and operation history at the time when user U was processing task information within that period. Then, the estimation unit 122 estimates the changes in user U's emotions by performing various analyses on the retrieved biometric information and operation history for that period, as described above. Note that the estimation unit 122 may estimate emotions at a single point in time, not just the changes in emotions over a certain period.

[0073] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the retrieved task information based on the estimation results of the emotional transition (S205). For example, if the adjustment unit 123 indicates that the emotional level transition in multiple estimation results has moved from a first level to a second level and that the second level has been maintained for a certain period of time, it may adjust the settings by determining the changes to the reminder setting information as described above, according to the trend of the transition. After that, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information (S206). Then, the reminder server 100 terminates the reminder setting adjustment process.

[0074] Furthermore, if in step S203 it is determined that user U is not currently processing task information (NO in S203), the reminder server 100 terminates the reminder setting adjustment process.

[0075] Figure 6 is a flowchart illustrating the flow of the reminder notification process according to this disclosure. First, the reminder execution unit 124 of the reminder server 100 determines, at a predetermined timing, whether or not there is task information to be reminded in the task information DB 112 (S301). The predetermined timing may be, for example, a fixed interval. If it is determined in step S301 that there is no task information to be reminded, the reminder execution unit 124 executes step S301 again after a certain period of time.

[0076] In step S301, if it is determined that there is task information to be reminded, the reminder execution unit 124 identifies user U, who is responsible for the relevant task information (S302). Specifically, the reminder execution unit 124 may identify user U by referring to the reminder management DB 113 and the task information DB 112.

[0077] Then, the estimation unit 122 estimates the emotions of user U from the personal information database 111 (S303). For example, the estimation unit 122 estimates the emotions of user U from the personal information database 111 based on the latest biometric data set or operation history, or biometric data set and operation history, etc., of the identified user U. Alternatively, the estimation unit 122 may estimate the emotions of user U from the personal information database 111 based on multiple biometric data sets or operation history, or biometric data set and operation history, etc., of the identified user U over a certain period. Specifically, the estimation unit 122 estimates the emotions of user U in the same manner as in step S107 or S204 described above.

[0078] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the relevant task information based on the emotion estimation result (S304). For example, the adjustment unit 123 may make the adjustment by determining the changes to the reminder setting information, similar to steps S108 or S205 described above. Then, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information. After that, the reminder execution unit 124 determines whether the relevant task information is a target for a reminder in the adjusted settings (S305).

[0079] If the task information in step S305 is determined not to be subject to a reminder, the reminder execution unit 124 suspends the reminder notification (S307). At this time, the registration unit 121 may register the date and time of the suspension of the reminder notification in the reminder history of the reminder setting information corresponding to the task information in the reminder management DB 113. Alternatively, the adjustment unit 123 may readjust the reminder setting information in response to the suspension of the reminder notification and update the reminder management DB 113 with the readjusted reminder setting information.

[0080] On the other hand, if the relevant task information is determined to be a reminder target in step S305, the reminder execution unit 124 sends a reminder notification to the user U's information processing terminal 200 based on the adjusted reminder setting information (S306). The registration unit 121 may register the date and time of sending the reminder notification in step S306, its content, etc., in the reminder history of the reminder management DB 113. By utilizing the reminder history, it is possible to improve the accuracy of estimating the user U's emotions regarding future task information and adjusting the settings related to reminders.

[0081] In response to step S306, for example, the information processing terminal 200 receives a reminder notification from the reminder server 100 via the communication network N and performs processing according to the received reminder notification. For example, the information processing terminal 200 displays display information such as a message included in the reminder notification on the display device. Alternatively, if the reminder notification includes operation instruction information, the information processing terminal 200 displays a pop-up on the display device, outputs an alarm sound or voice message from the speaker, and performs vibrations, etc., as described above.

[0082] This allows user U, who has been reminded, to receive appropriate reminders about incomplete tasks that are tailored to their emotional state. Therefore, for user U who is working on tasks, the content and frequency of reminders can be appropriately changed according to user U's psychological state, thereby enhancing the effectiveness of the reminders. This enables efficient task management and supports user U in smoothly completing tasks.

[0083] In other words, since reminder settings can be customized according to the estimated emotions of user U, effective and personalized task management tailored to individual needs can be achieved. Furthermore, it is possible to identify a series of mental states that significantly affect user U's behavioral performance, such as concentration, mental fatigue, and stress levels, analyze these mental states, and provide reminders for planned schedules necessary for task completion.

[0084] Furthermore, the reminder execution unit 124 or registration unit 121 should update the task information DB 112 with the progress of the task information each time user U makes progress in processing the task information, and after completion. This allows for analysis of the time required from immediately after the reminder notification until user U starts processing the task information, the processing time, and whether or not the completion deadline was met. The progress status can then be used as the completion status of task information that user U has handled in the past.

[0085] Therefore, as described above, the estimation unit 122 may estimate the user's emotions by taking into account the achievement status of task information that the user U has previously handled. For example, the estimation unit 122 can estimate whether the currently assigned task information is in an area where the user U is good or bad, based on the past achievement status of task information similar to the category and content of the task information assigned to the user U. Therefore, the adjustment unit 123 can adjust the reminder settings for the task information currently assigned to the user U more appropriately based on the emotion estimation result that takes into account the achievement status of task information that the user U has previously handled. For example, the reminder execution unit 124 can send reminder notifications at a frequency that is more individually optimized for the user U.

[0086] Furthermore, if task information includes multiple subtasks, it is possible to implement detailed and highly accurate reminder settings, such as adjusting the granularity of reminder notifications to the subtask level according to the user's emotions or emotional changes. This enables effective reminder notifications for the user and effectively supports task completion.

[0087] (Embodiment 2) The information system according to this second embodiment estimates the emotions of the user assigned to the incomplete task information on the information processing terminal side, and adjusts the reminder settings for the user in the task information based on the emotion estimation result. This supports the smooth execution of tasks by the user, similar to the first embodiment described above.

[0088] Figure 7 is a block diagram showing the overall configuration of the reminder system 1000a, which includes the information processing systems 11 to 11n according to this disclosure. The reminder system 1000a is a modified version of the reminder system 1000 described above. Therefore, the following explanation will focus on the differences from Embodiment 1 described above, and similar content will be omitted from illustrations and explanations as appropriate.

[0089] The reminder system 1000a comprises a reminder server 100a, information processing terminals 200a-1 to 200a-n, and biological information measuring devices 300-1 to 300-n. Each of the reminder server 100a, information processing terminals 200a-1 to 200a-n, and biological information measuring devices 300-1 to 300-n is connected to communicate via a communication network N. Each of the information processing terminals 200a-1 to 200a-n is assumed to have equivalent functions. Therefore, in the following description, information processing terminals 200a-1 to 200a-n may be simply referred to as "information processing terminal 200a". Furthermore, information processing terminal 200a-1 is an example of the information processing system 11 according to this embodiment. Similarly, hereafter, information processing terminal 200a-n is an example of the information processing system 1n according to this embodiment. Therefore, in the following explanation, each of the information processing systems 11 to 1n may be simply referred to as "information processing system 11".

[0090] Figure 8 is a block diagram showing the configuration of the reminder server 100a according to this disclosure. Compared to the reminder server 100 shown in Figure 2 above, the reminder server 100a has the estimation unit 122 and adjustment unit 123 removed, and the provision unit 125 and update unit 126 added. The other configurations of the reminder server 100a are the same as those of the reminder server 100.

[0091] The control unit 120 loads a program containing various processes of the reminder server 100a according to this disclosure from the storage unit 110 into memory and executes the program. This enables the control unit 120 to implement the functions of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124. Note that some or all of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124 may be implemented by hardware separate from the control unit 120, such as a general-purpose or dedicated circuit implemented in a semiconductor device.

[0092] The provision unit 125 provides search results by performing searches and other operations in response to search requests from the information processing terminal 200a to the personal information DB 111, task information DB 112, or reminder management DB 113, and transmitting the search results to the requesting information processing terminal 200a. The update unit 126 updates the personal information DB 111, task information DB 112, or reminder management DB 113 in response to update requests from the information processing terminal 200a, and transmits the update results to the requesting information processing terminal 200a.

[0093] Figure 9 is a block diagram showing the configuration of an information processing terminal 200a-1, which is an example of the information processing system 11 according to this disclosure. Compared to the information processing terminal 200 in Figure 3 described above, the information processing terminal 200a-1 has the transmitting / receiving unit 222 replaced with a transmitting / receiving unit 222a, and an estimation unit 224 and an adjustment unit 225 have been added. The other configurations of the information processing terminal 200a-1 are assumed to be the same as those of the information processing terminal 200.

[0094] The control unit 220 loads a program implementing the information processing method according to this disclosure from the storage unit 210 into memory and executes the program. This enables the control unit 220 to realize the functions of the acquisition unit 221, the transmission / reception unit 222a, the display control unit 223, the estimation unit 224, and the adjustment unit 225. Note that some or all of the acquisition unit 221, the transmission / reception unit 222a, the display control unit 223, the estimation unit 224, and the adjustment unit 225 may be implemented in hardware separate from the control unit 220, for example, in a general-purpose or dedicated circuit implemented in a semiconductor device.

[0095] The transmitting / receiving unit 222a transmits search requests or update requests to the personal information DB 111, task information DB 112, or reminder management DB 113 to the reminder server 100a via the communication network N. The transmitting / receiving unit 222a also receives search results or update results from the personal information DB 111, task information DB 112, or reminder management DB 113 from the reminder server 100a via the communication network N. In addition, the transmitting / receiving unit 222a has the same functions as the transmitting / receiving unit 222 in Figure 3 described above.

[0096] The estimation unit 224 and the adjustment unit 225 have the same functions as the estimation unit 122 and the adjustment unit 123 in Figure 2 described above. However, the estimation unit 224 estimates the emotions of user U using the behavioral information 211 and biometric information 212 stored in the memory unit 210. In addition, the estimation unit 224 estimates the emotions of user U using the search results from the personal information DB 111 and task information DB 112 received by the transmitting / receiving unit 222a.

[0097] The adjustment unit 225 adjusts the reminder settings for user U in the task information using the search results from the task information DB 112 and reminder management DB 113 received by the transmission / reception unit 222a, and the emotion estimation results from the estimation unit 224. Then, the transmission / reception unit 222a sends an update request, including the adjusted reminder setting information, to the reminder server 100a via the communication network N.

[0098] Furthermore, since the reminder setting adjustment process according to this embodiment is generally equivalent to that in Figures 4 and 5 described above, the differences will be explained below. In this embodiment, the registration, search, update, and deletion processes in steps S101 to S109 of Figure 4 to the personal information DB 111, task information DB 112, or reminder management DB 113 shall be interpreted as the transmission of registration requests, search requests, update requests, and deletion requests from the information processing terminal 200a to the reminder server 100a, and the reception of the results of each request. The same applies to steps S201 to S206 of Figure 5.

[0099] Furthermore, the reminder notification process according to this embodiment is generally equivalent to that shown in Figure 6 above, so the differences will be explained in detail below. In step S303 of Figure 6, the emotion estimation process is performed by the estimation unit 224 of the information processing terminal 200a, which estimates the emotion in response to the estimation request from the reminder server 100a. In step S304 of Figure 6, the adjustment process is performed by the adjustment unit 225 of the information processing terminal 200a, and the transmission / reception unit 222a sends an update request including the adjusted reminder setting information to the reminder server 100a.

[0100] Thus, this second embodiment can achieve the same effects as the first embodiment described above.

[0101] (Embodiment 3) The information system according to this embodiment 3 distributes or makes redundant functions across the server and information processing terminal to achieve the same processing as in embodiment 1 or 2 described above. As a result, it supports the smooth execution of tasks by the user, similar to embodiment 1 or 2 described above.

[0102] Figure 10 is a block diagram showing the overall configuration of the reminder system 1000b, which includes the information processing system 1b according to this disclosure. The reminder system 1000b is a modified version of the reminder system 1000 or 1000a described above. Therefore, the following explanation will focus on the differences from the embodiments 1 or 2 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0103] The reminder system 1000b comprises a reminder server 100b, information processing terminals 200b-1 to 200b-n, and biological information measuring devices 300-1 to 300-n. Each of the reminder server 100b, information processing terminals 200b-1 to 200b-n, and biological information measuring devices 300-1 to 300-n is connected to communicate via a communication network N. Each of the information processing terminals 200b-1 to 200b-n is assumed to have equivalent functions. Therefore, in the following description, information processing terminals 200b-1 to 200b-n may be simply referred to as "information processing terminal 200b". The reminder server 100b and information processing terminals 200b-1 to 200b-n are examples of the information processing system 1b according to this embodiment.

[0104] The reminder server 100b shares at least some configurations with the reminder server 100 in Figure 2 and the reminder server 100a in Figure 8. Similarly, the information processing terminal 200b shares some configurations with the information processing terminal 200 in Figure 3 and the information processing terminal 200a-1 in Figure 9. For example, the reminder server 100b may be modified by adding the provision unit 125 and update unit 126 from Figure 8 to the reminder server 100 in Figure 2. The information processing terminal 200b may then have a configuration equivalent to the information processing terminal 200a in Figure 9. In these cases, for example, the reminder server 100b sends the estimation result to the information processing terminal 200b after processing the emotion. The information processing terminal 200b then adjusts the reminder setting information using the received estimation result and sends an update request, including the adjusted reminder setting information, to the reminder server 100b. Alternatively, the information processing terminal 200b may send the estimation result to the reminder server 100b after the emotion estimation process. The reminder server 100b may then adjust the reminder setting information using the received estimation result. Alternatively, the reminder setting adjustment process in Figures 4 and 5 may be performed by the information processing terminal 200b, as in Embodiment 2 described above, to perform both the estimation and adjustment processes. Furthermore, the reminder notification process in Figure 6 may be performed by the reminder server 100b, including the emotion estimation and adjustment processes, as in Embodiment 1 described above. Note that the combination of functional division between the reminder server 100b and the information processing terminal 200b is not limited to these.

[0105] Thus, this third embodiment can achieve the same effects as the first and second embodiments described above.

[0106] (Embodiment 4) The information system according to this embodiment 4 calculates an attention level on the server side, which indicates the degree of attention paid to the task information by stakeholders other than the person assigned to the incomplete task information, and adjusts the reminder settings for the person in charge of the task information based on the attention level. This supports the smooth execution of the task by the person in charge at an effective timing for the stakeholders of the task.

[0107] For example, an employee needs to submit deliverables and reports related to their assigned task information to the project manager or their supervisor. In this case, instead of simply sending a reminder to the employee at a predetermined time, such as one day before the deadline, the frequency and content of the reminders should reflect the level of attention given to the task information by other members of the project, managers, and supervisors. This promotes more effective task management and collaboration among project members. This approach allows for reminders that reflect the priority and urgency of the task information, taking into account the needs and preferred timing of the employee and the collaborating members, compared to simple time- or personal environment-based reminder systems.

[0108] Figure 11 is a block diagram showing the overall configuration of a reminder system 1000 including an information processing system 1 according to this disclosure. The reminder system 1000 comprises a reminder server 100, information processing terminals 200-1 to 200-n and 200-s, and biometric information measuring devices 300-1 to 300-n and 300-s. Hereinafter, n is a natural number. Each of the reminder server 100, information processing terminals 200-1 to 200-n and 200-s, and biometric information measuring devices 300-1 to 300-n and 300-s is connected to communicate via a communication network N. Hereinafter, the communication network N is a wired, wireless, or both type of communication network. The communication network N may include, for example, the Internet. Each of the information processing terminals 200-1 to 200-n and 200-s shall have equivalent functions. Therefore, in the following explanation, information processing terminals 200-1 to 200-n and 200-s may be simply referred to as "information processing terminal 200". Also, each of the biological information measuring devices 300-1 to 300-n and 300-s shall have equivalent functions. Therefore, in the following explanation, biological information measuring devices 300-1 to 300-n and 300-s may be simply referred to as "biological information measuring device 300". Furthermore, each of the personnel U1 to Un shall be assigned a task with at least a deadline as task information. Each of the personnel U1 to Un shall process and complete the task information assigned to them using the information processing terminal 200, etc. Furthermore, related parties Us shall be persons related to a specific task information assigned to any of the personnel U1 to Un. Stakeholders Us include, for example, those who participate in the project to which the specific task information assigned to Person U1 belongs, or those whose processing of their own task information is affected by the progress of the specific task information of Person U1's superiors, colleagues, subordinates, etc. Therefore, Stakeholders Us may also be "administrators" who manage the task information assigned to Person U1, etc. Furthermore, there may be two or more Stakeholders Us. At least some of Person U1 to Un and Stakeholders Us may be, for example, persons belonging to an organization such as a company. In the following explanation, Person U1 to Un and Stakeholders Us may be simply referred to as "User U".

[0109] The reminder system 1000 is an information processing system that assigns tasks to each of the assigned personnel U1 to Un and sends reminder notifications to the assigned personnel's information processing terminals 200, etc., for tasks that are incomplete and registered in the database described later. Here, "incomplete" refers to a state in which the status of the task information is not marked as "completed," meaning that the task information's completion deadline has passed, or that the task information's completion deadline has not passed and it is in progress, i.e., it is being processed. The number of users to be reminded only needs to be at least one. Therefore, the reminder system 1000 only needs to include at least one personnel's information processing terminal 200, the related personnel Us's information processing terminals 200-s and biometric information measuring devices 300-s, and the reminder server 100. Furthermore, the reminder server 100 is an example of the information processing system 1 according to this embodiment. Therefore, the reminder system 1000 can be said to include the information processing system 1.

[0110] The biological information measuring device 300 is a device that measures the biological information of user U, who is the target of measurement. The biological information measuring device 300 should continuously measure biological information at regular intervals. In other words, the biological information measuring device 300 may constantly monitor the biological information of user U. Here, biological information includes, but is not limited to, biomarkers such as heart rate, skin conduction response, and movement. For example, the biological information measuring device 300 may measure multiple channels of measurement data and biological information using sensors for measuring electroencephalography (EEG) or electrocardiogram (ECG). For example, the biological information measuring device 300 may be an electroencephalograph or an electrocardiogram measuring device.

[0111] Alternatively, the biometric information measuring device 300 may be installed in close proximity to each user U, or it may be a wearable terminal attached to each user U. In the example in Figure 11, the biometric information measuring device 300-1 measures the biometric information of person in charge U1. Similarly, the biometric information measuring device 300-n measures the biometric information of person in charge Un. Then, the biometric information measuring device 300-s measures the biometric information of person in charge Us. For example, the biometric information measuring device 300-s includes the biometric information measured from person in charge Us, along with the identification information of person in charge Us and the measurement date and time, etc., in the registration request and sends the registration request to the reminder server 100 via the communication network N. The reminder system 1000 may also include a dedicated biometric information analysis server that collects and analyzes the biometric information measured from each user U by each biometric information measuring device 300-1 to 300-n via the communication network N. In that case, the biometric information analysis server sends a registration request to the reminder server 100 via the communication network N, including the analysis results and measurement results for each user U, as well as the user U's identification information and measurement date and time.

[0112] Alternatively, for example, the biometric information measuring device 300-s may be connected to an information processing terminal 200-s used by the person concerned Us via short-range wireless or wired communication. In this case, the biometric information measuring device 300-s may transmit the measured biometric information, etc., to the information processing terminal 200-s. The information processing terminal 200-s may then transmit a registration request, including the biometric information received from the biometric information measuring device 300-s, the identification information of the person concerned Us, and the measurement date and time, etc., to the reminder server 100 via the communication network N.

[0113] The information processing terminal 200 is an information processing device used by user U to process tasks corresponding to task information. In the example in Figure 11, information processing terminal 200-1 is used by person in charge U1, and similarly thereafter, information processing terminal 200-n is used by person in charge Un. Also, information processing terminal 200-s is used by related parties Us. However, it is not necessary for each user U to have one information processing terminal 200; one information processing terminal 200 may be shared by multiple users U. Furthermore, one user U may use multiple information processing terminals 200. In these cases, the information processing terminal 200 shall identify the user U using it by login information. The detailed configuration of the information processing terminal 200 will be described later.

[0114] The information processing terminal 200 is assumed to be connected to various peripheral devices, such as a camera, microphone, input device for operation information, display device, and speaker (configurations not shown), via wired or wireless communication. Some or all of the above peripheral devices may be built into the information processing terminal 200. The camera captures the user U's face and actions, and outputs the captured image data to the information processing terminal 200. The image data is, for example, a general-purpose image format such as JPEG (Joint Photographic Experts Group) or PNG (Portable Network Graphics) of a predetermined image size, but is not limited to these. The microphone acquires the user U's speech and voice tone as sound data and outputs the acquired sound data to the information processing terminal 200. Here, the audio data is either uncompressed or compressed audio data in audio file formats such as WAV (Waveform Audio Format) or AIFF (Audio Interchange File Format). However, the audio file format is not limited to these. The input device is a keyboard or mouse. The input device acquires keyboard and mouse operation information from user U and outputs the acquired operation information to the information processing terminal 200. The display device displays the display information input from the information processing terminal 200 on the screen. The speaker outputs the audio data input from the information processing terminal 200.

[0115] Figure 12 is a functional block diagram showing the configuration of a reminder server 100, which is an example of the information processing system 1 according to this disclosure. The reminder server 100 is an information processing device that manages personal information of each user U, task information, and reminder setting information for the person in charge assigned to the incomplete task information. The "reminder setting information" is an example of "settings related to reminders". The reminder server 100 also performs reminder notification processing to the person in charge assigned to the incomplete task information based on the reminder setting information. The reminder server 100 may be implemented as a computer system in which the functions are distributed or made redundant by multiple computer devices. The reminder server 100 comprises a storage unit 110, a control unit 120, and an IF (Interface) unit 130.

[0116] The storage unit 110 includes, for example, a non-volatile storage device such as a hard disk or flash memory, and a memory such as RAM (Random Access Memory), i.e., a volatile storage device. The storage unit 110 stores a personal information DB (DataBase) 111, a task information DB 112, and a reminder management DB 113. The personal information DB 111, task information DB 112, and reminder management DB 113 can be said to correspond to storage areas managed by database management software. Furthermore, the task information DB 112 may include the reminder management DB 113.

[0117] The personal information database 111 is a database that manages user information, biometric data, operation history, personality information, etc., for each user U. User information, biometric data, operation history, personality information, etc. may also be called personal information. User information may include identification information that identifies each user U, personal information such as name, and organizational attribute information such as department, position, and job title. User information also includes the recipient of reminder notifications, i.e., destination information. Destination information may include, but is not limited to, the user U's email address, identification information and address information of the information processing terminal 200 used by the user U, the user U's login ID, and account information for information systems such as SNS (Social Networking Service).

[0118] The biometric information group is a collection of biometric information and measurement date and time, etc., measured by the biometric information measuring device 300 described above. The biometric information group is associated with personal information corresponding to the identification information of user U included in the registration request for biometric information, etc., received from the biometric information measuring device 300. The biometric information group may also include at least one or both of the following: image data of user U's facial expression captured during operation of the information processing terminal 200, or voice data of user U recorded during operation of the information processing terminal 200. The image data and voice data are associated with the date and time when they were captured or recorded.

[0119] The operation history may include input information from input devices such as the keyboard and mouse, recorded when each user U operates the information processing terminal 200. The input information from input devices may also include finger pressure information during keyboard input. Furthermore, the operation history associates the above-mentioned input information with the date and time it was recorded.

[0120] Personality information should include information that each user U has self-analyzed by answering questionnaires, etc., as well as information that indicates user U's personality as evaluated and analyzed by related parties such as user U's superiors, colleagues, and subordinates.

[0121] Task Information DB112 is a database that manages the content, progress, and processing history of task information assigned to each person in charge. For example, task information may include task ID, task name, task content, person in charge, completion deadline, completion date or completion flag, category, affiliated project, stakeholders, importance or priority, remarks, etc. The person in charge is user information such as the user ID to which the task information is assigned. The completion deadline may also be called the scheduled completion date and time of the task information. Stakeholders are the user information of the person in charge's superiors, colleagues, subordinates, etc., or users belonging to the affiliated project. Furthermore, task information may include multiple subtask information. Subtask information may include subtask ID, subtask name, subtask content, completion deadline, completion date or completion flag, etc. A subtask is a milestone that specifically subdivides a task. For example, if the task is a presentation, subtasks may include information gathering, graph creation, document creation, proofreading of materials, presentation, etc. Task information may also include the person in charge's level of interest in the task content, the person in charge's usual work content, etc.

[0122] The progress status is information indicating the degree of progress and status of task information for each task ID. The progress status may also be able to identify whether the corresponding task information is incomplete. The processing history includes task information for which the completion date has been entered or the completion flag is turned on, and at least the task ID. Note that the task information managed in the task information DB112 is not limited to what is described above.

[0123] The reminder management DB 113 is a database that manages reminder settings for assigned personnel in the task information managed in the task information DB 112, i.e., reminder setting information. The reminder management DB 113 may, for example, manage the reminder setting information and reminder history in association with the task ID or subtask ID. The task ID or subtask ID uniquely corresponds to the information contained in the task information DB 112 mentioned above. In addition, the reminder management DB 113 may further associate the destination information for reminder notifications with the task ID or subtask ID. The destination information is the destination information of user U contained in the personal information DB 111 for the user information of the assigned person associated with the task ID or subtask ID in the task information DB 112. The reminder setting information includes the frequency, number of reminders, and intervals of reminders, as well as the content of the reminders. The reminder setting information may also include the scheduled date and time of the reminders. The content of the reminders may include text information included in the reminder notification, operation instruction information to operate the information processing terminal 200 that receives the reminder notification, etc. Text information is part of the display information shown on the screen by the information processing terminal 200 that received the reminder notification. Action instruction information is information that instructs the information processing terminal 200 on what action to take upon receiving the reminder notification. The action may be, for example, a pop-up display, an alarm sound, or a voice message. If the information processing terminal 200 is a portable information terminal, the action may be vibration of the information processing terminal 200. The reminder history may include the date and time of the reminder notification, the content of the notified reminder, etc.

[0124] The control unit 120 is a control device that controls each component of the reminder server 100. The control unit 120 is a processor such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), or quantum processor (quantum computer control chip). For example, the control unit 120 loads a program from the storage unit 110 into memory and executes the program. The program is a computer program that implements the processing of the information processing method according to this disclosure, although its configuration is not shown. As a result, the control unit 120 realizes the functions of the registration unit 121, estimation unit 122, adjustment unit 123, reminder execution unit 124, and calculation unit 127. Furthermore, some or all of the registration unit 121, estimation unit 122, adjustment unit 123, reminder execution unit 124, and calculation unit 127 may be implemented in hardware separate from the control unit 120, for example, in a general-purpose or dedicated circuit implemented in a semiconductor device.

[0125] When the registration unit 121 receives a registration request from an information processing terminal 200 or a biometric information measuring device 300, it registers the received information and setting information generated in response to the registration request in the personal information DB 111, task information DB 112, or reminder management DB 113, according to the information contained in the registration request.

[0126] The calculation unit 127 calculates the level of attention given to the task information by stakeholders other than the person assigned to the incomplete task information. Here, "level of attention" is information that indicates the degree to which stakeholders pay attention to the progress of the task information to which a person who is a stranger to them has been assigned. The level of attention may also be called the "level of attention," which indicates the degree to which stakeholders are paying attention to the progress of the task information to which a person has been assigned. Furthermore, stakeholders, as mentioned above, include those whose processing of their own task information is affected by the progress of a particular task information, and administrators who manage task information. Here, administrators refer to users who have specific privileges and roles within the system. Specifically, these are users who have special privileges to access task information and its progress. Special privileges for access include creating, editing, deleting tasks, and assigning personnel. The level of attention can also be said to be information that indicates, for example, the degree to which an administrator who manages the progress of task information is concerned about whether the person in charge is working on the task information, how far along the processing is, and when it is expected to be completed. In other words, the level of attention can be seen as an indicator of how concerned the administrator is about the progress of the assigned task information.

[0127] Specifically, the calculation unit 127 analyzes the operation history of the person concerned Us in the personal information DB 111, calculates the number of times, frequency, and interval of access by the person concerned to the relevant task information in the task information DB 112, and calculates the level of attention based on the calculated information according to a predetermined standard. For example, suppose that person concerned Us is the superior of person in charge U1. Also, suppose that the progress of one or more task information, including the task information of person in charge U1, is managed using a Gantt chart. In this case, the calculation unit 127 calculates the number of times person concerned Us has viewed the progress of person in charge U1's task information in the Gantt chart from the operation history of person concerned Us, and calculates the level of attention higher than the standard value if the number or frequency is high or the interval is short. In other words, the calculation unit 127 calculates the level of attention based on the operation history of the person concerned in the information system related to the task information. Note that the information system related to the task information includes, for example, the application used for accessing the task information or the information system that manages the Gantt chart.

[0128] Alternatively, the calculation unit 127 may calculate the level of attention based on access rights in the information system related to the task information. An information system related to task information may be, for example, a shared workspace where multiple users share electronic data via an information processing terminal 200, etc., for a certain project, and share editing content and operation content. Alternatively, an information system related to task information may be, for example, a shared whiteboard provided by a predetermined information system. When the task information of person in charge U1 is handled in these information systems, the calculation unit 127 may determine that users other than person in charge U1 included in the access rights of the above information system are related parties Us. The calculation unit 127 may then analyze the operation history of related parties Us included in the access rights in the personal information DB 111, including the operation content and number of views of person in charge U1's task information in the above information system, and calculate the level of attention of related parties Us according to a predetermined standard.

[0129] Furthermore, the calculation unit 127 may also take into account the personality information of the person concerned Us, in addition to the operation history and access rights, to calculate the degree of attention Us is paying to the task information of person in charge U1.

[0130] The estimation unit 122 estimates the emotions of stakeholders Us regarding incomplete task information. The estimation unit 122 may also estimate the emotions of the person assigned to the incomplete task information. Therefore, it is preferable for the estimation unit 122 to estimate the emotions of user U. Specifically, the estimation unit 122 searches the task information DB 112 for task information where the completion date is not entered or the completion flag is off, and identifies the user information assigned as the person in charge or stakeholder to the task information that hits the search. The estimation unit 122 may also search the task information DB 112 for incomplete task information by referring to the progress status. Alternatively, the estimation unit 122 may search the reminder management DB 113 for incomplete task information. Then, the estimation unit 122 estimates the emotions of user U, who is at least one of the person in charge or stakeholder corresponding to the user information, based on at least one of the biometric information group or operation history included in the identified user information from the personal information DB 111.

[0131] For example, the estimation unit 122 may estimate user U's emotions based on a set of biological information, using physiological biometrics as an evaluation scale. Specifically, the estimation unit 122 may analyze biological information such as heart rate, skin conduction response, electroencephalogram, and electrocardiogram measurement data measured from user U to generate models of user U's concentration level, mental fatigue level, stress level, etc., and estimate the mental state, i.e., user U's emotions, from the models. If the set of biological information is image data or audio data, the estimation unit 122 may estimate user U's emotions based on the set of biological information by processing described later.

[0132] Furthermore, the estimation unit 122 may estimate user U's emotions based on user U's operation history. Specifically, the estimation unit 122 may identify input information from an input device during the time period when user U was processing the retrieved task information, or during the time period immediately before or after that time period, in user U's operation history. For example, if the operation history contains a string related to the relevant task information in the file name, the estimation unit 122 may identify the time period when that file was being edited as the time period when user U was processing the retrieved task information. Alternatively, if the operation history includes a specific application used to process the relevant task information, the estimation unit 122 may identify the time period when that application was used as the time period when user U was processing the retrieved task information. Alternatively, the estimation unit 122 may identify image data and voice data of user U during the time period identified from user U's operation history as user U's biometric information from the biometric information group in the personal information DB 111. Therefore, it can be said that the input information etc. identified by the estimation unit 122 includes at least one or both of user U's operation history and / or biometric information.

[0133] The estimation unit 122 then analyzes user U's behavior, key input content, finger pressure during key input, typing speed, facial expressions, voice tone, etc., from the identified input information using an AI (Artificial Intelligence) based motion prediction algorithm. Specifically, the estimation unit 122 may use methods such as neural networks, support vector machines, decision trees, and k-nearest neighbors as the AI-based motion prediction algorithm. Here, the estimation unit 122 may estimate user U's emotions from the identified input information. For example, the estimation unit 122 may use an identification method based on a learning model that has been pre-generated by machine learning the combination of each input information item with the corresponding emotion, for emotion estimation based on key input content, finger pressure during key input, typing speed, facial expressions, voice tone, etc.

[0134] Furthermore, the estimation unit 122 may perform emotion estimation of user U based on user U's voice. In this case, known voice-based emotion recognition techniques may be used for voice-based emotion estimation. For example, for voice-based emotion estimation, statistical quantities (mean, variance, slope, etc.) of features such as pitch (frequency) and volume extracted multiple times in a time series may be calculated, and the emotion category to which the feature vector belongs and its coordinate value in the emotion space may be estimated from the multidimensional feature vector converted from the voice signal, thereby estimating the emotion contained in the voice. Here, the machine learning methods described above may be used for emotion estimation based on the feature vector. Then, the estimation unit 122 may estimate user U's emotion based on the above analysis results.

[0135] Furthermore, the estimation unit 122 may analyze the user's emotional state by analyzing the user's typing speed and key input content during the processing of specific task information from the operation history. For example, the estimation unit 122 may estimate the emotional state based on typing speed and rhythm. For instance, fast typing speeds often indicate concentration and positive emotions, while slow typing may indicate negative emotions such as high stress or difficulty in processing the task information being processed. Also, if the typing rhythm changes at regular intervals, it may indicate stable emotions, while irregular rhythms may indicate anxiety or impatience. The estimation unit 122 may also use keystroke dynamics technology to measure the time each key is held down and estimate the emotional state. For example, long key press times may indicate fatigue or stress. Additionally, a high error rate may indicate that the user is experiencing stress. Therefore, the estimation unit 122 should take these factors into account when estimating the emotional state of the user U based on typing speed and key input content. In this context, typing speed refers to an indicator that measures how many characters can be entered within a certain amount of time. For example, it measures the number of characters that can be entered per minute (WPM: Words Per Minute). For instance, if user U can enter 50 words per minute, their typing speed is 50 WPM.

[0136] Furthermore, the estimation unit 122 may estimate user U's emotions based on a combination of user U's biometric information and operation history. In addition, the estimation unit 122 may estimate user U's emotions by adding user U's personality information to at least one of the biometric information and operation history.

[0137] Furthermore, the estimation unit 122 may estimate user U's emotion as one of several levels in a predetermined index indicating user U's psychological state in response to task information. Specifically, the estimation unit 122 may estimate user U's emotion level using the aforementioned biometric information group or operation history, etc. For example, the estimation unit 122 may determine positive emotion on a three-level scale, or negative emotion on a three-level scale, as the emotion level of user U. In this case, for example, the estimation unit 122 estimates a larger value for the number representing the level of positive emotion as the user U's positive emotion in response to task information increases. Alternatively, the estimation unit 122 estimates a larger value for the number representing the level of negative emotion as the user U's negative emotion in response to task information increases. Alternatively, the emotion levels may be set as three levels: "negative" as level 1, "positive and non-negative" as level 2, and "positive" as level 3. Alternatively, the degree from positive to negative may be used as an index of user U's psychological state. For example, if the emotional level is set on a scale of 1 to 10, levels 1 to 5 may be considered positive emotions, and levels 6 to 10 may be considered negative emotions. In this case, level 1 indicates a higher level of positive emotion than level 5, and level 10 indicates a higher level of negative emotion than level 6. Note that the emotional level is not limited to this example, as long as there are two or more levels. Alternatively, the estimation unit 122 may simply estimate the level indicating that user U's emotion towards the task information is at least one level of either positive or negative emotion as user U's emotion. Alternatively, the estimation unit 122 may estimate the levels of user U's positive and negative emotions towards the task information as numerical values.

[0138] Examples of an employee's feelings towards task information include the following: If an employee repeatedly writes and deletes while editing a file related to a specific task, it is possible that the employee is having difficulty processing that task. In this case, the estimation unit 122 may simply estimate the employee's feelings towards the specific task information as "negative" without classifying them into levels. Conversely, if the employee does not repeatedly write and delete while editing a file related to a specific task, it may simply be estimated as "positive." Alternatively, the level of emotion may be classified according to the editing time and the number of characters repeatedly edited when writing and deleting are repeated on the file related to the specific task information. For example, the estimation unit 122 may estimate a higher level of positive emotion if the editing time and number of characters are below a predetermined value, and estimate a higher level of negative emotion compared to the case where they are above the predetermined value. This allows the settings related to reminders to be adjusted to appropriate information according to the employee's emotional level. Furthermore, when estimating the emotional level based on the user U's voice, for example, a trained model that has been machine-learned can be used as follows. For example, an emotion level estimation AI model can be used that takes a multidimensional feature vector converted from an audio signal as input and outputs a level of positive or negative emotion. The input data of the multidimensional feature vector converted from the audio signal and the output data of the emotion level are used as training data. Machine learning is then performed on the emotion level estimation AI model using this training data. As a result, the estimation unit 122 may use the trained model of the emotion level estimation AI model that has undergone machine learning to estimate the emotion level based on the user U's voice. In this way, the settings related to reminders can be adjusted to appropriate information according to the level.

[0139] Furthermore, the estimation unit 122 should estimate the emotions of the person in charge at the time new task information is assigned to them. In other words, the estimation unit 122 should estimate the emotions of the person in charge from biometric information measured at the time new task information is assigned to them or from the acquired operation history in the most recent time period. This allows for a more accurate estimation of the person in charge's emotions regarding the assigned task information.

[0140] Furthermore, the estimation unit 122 may estimate the employee's emotions multiple times while the task information is incomplete. For example, the estimation unit 122 may estimate the employee's emotions multiple times using measured biometric information and acquired operation history while the employee is processing specific task information. This makes it possible to understand changes and trends in the employee's emotional level during processing specific task information. Therefore, the reminder settings described later can be adjusted more appropriately.

[0141] Furthermore, the estimation unit 122 may estimate the emotions of the person in charge by taking into account the achievement status of task information that the person in charge has handled in the past. Here, achievement status refers to actual information regarding the processing of task information, such as the processing content of completed task information, the relationship between reminder notifications and processing dates, and the relationship between the deadline and the actual completion date. Specifically, the estimation unit 122 may refer to the processing history of the task information DB 112, identify past task information related to the task information that the person in charge is currently processing, i.e., incomplete, and estimate the emotions of the person in charge regarding the task information currently being processed by taking into account the achievement status of the identified past task information. For example, the estimation unit 122 may identify past task information that is similar to the task information currently being processed in terms of task content, category, affiliated project, stakeholders, or importance. Then, the estimation unit 122 may estimate the emotions of the person in charge regarding the task information currently being processed by taking into account the difference between the deadline and the actual completion date of the identified past task information, the progress in response to reminder notifications, etc. For example, if the actual completion date of a identified past task was earlier than the deadline, it can be inferred that the user felt good about that task. Therefore, in such cases, the estimation unit 122 may infer that user U's emotions regarding the task currently being processed are positive, or that the level of positive emotions is higher. Conversely, if the actual completion date of a identified past task was close to or after the deadline, the estimation unit 122 may infer that user U's emotions are negative, or that the level of negative emotions is higher. The estimation unit 122 may also infer user U's emotions from the user U's emotions or the progression of emotions when the user U checked the reminder notification for the identified past task, or from the progression of user U's emotions in the past regarding the task currently being processed. Alternatively, the estimation unit 122 may refer to the personal information DB 111 and infer the emotions of the person in charge at the time based on the biometric information or operation history of the person in charge during the processing period of the identified past task. The estimation unit 122 then takes into account the estimation results of the person in charge during the processing period of the identified past task information to estimate the emotions of the person in charge of the task currently being processed.This may improve the accuracy of estimating the emotions of the person in charge regarding the assigned task information. The estimation unit 122 may also estimate the emotions of the person in charge Us regarding a given task information in the same manner as described above, taking into account the timing, the person in charge's achievement status, and the person in charge Us's operation history. The emotion estimation process is not limited to these, and known emotion estimation techniques may be used.

[0142] The adjustment unit 123 adjusts the settings for reminders to the person in charge of an incomplete task based on the level of attention of the person in charge Us calculated by the calculation unit 127. Specifically, the adjustment unit 123 updates the reminder setting information in the reminder management DB 113 for the relevant task information based on the level of attention of the person in charge Us for the relevant task information. More specifically, the adjustment unit 123 may adjust the reminder settings to change at least one of the number of reminders or the content of the reminders for the relevant task information based on the level of attention of the person in charge Us. For example, if the number of times the person in charge U1 checks the progress of the task information using a Gantt chart or the like is greater than a predetermined number, the calculation unit 127 calculates the level of attention to be higher than the threshold. If the level of attention is above the threshold, the adjustment unit 123 may change the number of reminders to the person in charge U1 for the relevant task information to be greater than the standard value. Conversely, if the level of attention is less than the threshold, the adjustment unit 123 may change the number of reminders to the person in charge U1 for the relevant task information to be less than the standard value. Furthermore, if the number of times stakeholders Us check the progress exceeds a predetermined number, it can be said that stakeholders Us are concerned about the progress of the relevant task information. Therefore, increasing the number of reminders sent to person in charge U1 can promote the completion of the relevant task information by person in charge U1. Also, if the level of attention exceeds a certain value, the adjustment unit 123 should modify the content of the reminder sent to person in charge U1 for the relevant task information to include phrases such as "consult with project members" or "get advice from your supervisor." This means that if person in charge U1 is not good at reporting or tends to be slow to start on task information, the adjustment unit 123 can modify the reminder content to support behavioral improvement. Also, if the level of attention exceeds a certain value, the adjustment unit 123 should adjust the subdivided reminder settings so that reminder notifications are sent to person in charge U1 for each completion deadline of the subtask unit of the relevant task information. Therefore, when the matter is of high interest to stakeholders Us, reminder notifications can be sent in a way that facilitates the smooth processing of task information by the person in charge U1, by subdividing the granularity of the reminder notifications or increasing their frequency.

[0143] Furthermore, the adjustment unit 123 may adjust the reminder settings based on the level of attention calculated by the calculation unit 127 and the estimated emotions of the stakeholders Us by the estimation unit 122.

[0144] The adjustment unit 123 adjusts the reminder settings for the person in charge in the task information based on the emotion estimation results of the person in charge or related party Us by the estimation unit 122. Specifically, the adjustment unit 123 updates the reminder setting information in the reminder management DB 113 for the relevant task information based on the emotion estimation results of the estimation unit 122. For example, the adjustment unit 123 may determine the initial setting of the reminder setting information based on the emotion estimation results of the person in charge or related party Us at the time new task information is assigned to the person in charge, and register the determined initial setting as reminder setting information in the reminder management DB 113. The adjustment unit 123 may also update the reminder management DB 113 to change the reminder setting information based on the emotion estimation results of the person in charge or related party Us for incomplete task information. Furthermore, the adjustment unit 123 may update the reminder management DB 113 to change the reminder setting information for incomplete task information based on the continuously estimated changes in the emotion of user U. Furthermore, the adjustment unit 123 may adjust the reminder setting information to include all the information registered in the task information, or information focused on some important points, based on the emotion estimation result.

[0145] In particular, the adjustment unit 123 determines whether the emotional level in the estimation result is above a predetermined threshold, and adjusts the reminder settings to change at least one of the number of reminders or the content of the reminders according to the determination result. By adjusting the number of reminders and content in consideration of the emotions of the person in charge in this way, it is possible to support the performance of tasks in line with the psychological state of the person in charge.

[0146] For example, if the threshold is negative emotion level 3, the adjustment unit 123 determines whether the level of the person in charge's emotion towards the newly assigned task information is negative emotion level 3 or higher. If the estimated level of the person in charge's emotion is negative emotion level 3, the adjustment unit 123 determines that the person in charge's emotion level is negative emotion level 3 or higher. Also, if the estimated level of the person in charge's emotion is "positive" or "other than positive and negative," the adjustment unit 123 may determine that the person in charge's emotion level is less than negative emotion level 3. Similarly, if the estimated level of the person in charge's emotion is negative emotion level 1 or 2, the adjustment unit 123 also determines that the person in charge's emotion level is less than negative emotion level 3.

[0147] For example, if the estimated emotion of the person in charge regarding newly assigned task information is "positive," the adjustment unit 123 should determine the initial settings for the reminder settings information to either reduce the number of reminders or increase the frequency and interval compared to when the estimated result is "negative," and register this in the reminder management DB 113. In this case, since the person in charge's psychological state is positive regarding the task information, setting the timing of the reminder notification earlier than the default can promote the person in charge's task completion. In this case, the adjustment unit 123 should also adjust the reminder settings information by adding wording that urges the person to submit or report quickly. In these cases, since the person in charge of the task information is in a positive psychological state, slightly increasing the burden on the person in charge can promote the person in charge's task completion.

[0148] On the other hand, if the estimated emotion of the person in charge regarding newly assigned task information is "negative," the adjustment unit 123 may decide on an initial setting that uses more polite language for the reminder notification text compared to when the estimation result is "positive," and register it in the reminder management DB 113. For example, if the task information is document creation, the adjustment unit 123 may elaborate on the content of the reminder notification by including information about the people who will review the document in the text of the reminder notification. Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may decide on an initial setting that extracts some important points and register it in the reminder management DB 113. Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may decide on an initial setting that reveals information such as the people involved in the relevant task information, for example, that there are people waiting for the completion of the relevant task information, and register it in the reminder management DB 113.

[0149] Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may determine the initial settings for subdivided reminder setting information so that reminder notifications are sent for each completion deadline of the subtask unit of the task information, compared to when the estimated emotion is "positive," and register this information in the reminder management DB 113. For example, if the task information is document creation, the deadline for creating the first draft of the document, i.e., the deadline for requesting review from a supervisor, may be set as subtask 1, and the deadline for revising the document may be set as subtask 2. In this way, the adjustment unit 123 may set tasks for sending multiple reminder notifications from the task information as subtasks and determine the subtasks as the initial settings for the reminder setting information. In these cases, since the psychological state of the person assigned the task information is negative, the hurdle for task completion can be lowered to support the person in performing the task. Furthermore, the adjustment unit 123 may also adjust the system so that, not limited to the initial settings, the person in charge can change the reminder setting information at any time between the start and completion of processing the task information, based on the estimated emotion of the person in charge at that time.

[0150] Furthermore, the set of emotional levels estimated multiple times within a certain period shall be called the emotional psychological state or simply the emotional state. In this case, if negative emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "negative." Similarly, if positive emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "positive." Here, if the adjustment unit 123 indicates that the emotional psychological state in the multiple estimation results has transitioned from a first state to a second state, and that the second state has been maintained for a certain period of time, it may adjust the settings related to the reminder. For example, let's say the first state is "positive" and the second state is "negative." In this case, suppose the adjustment unit 123 determines from the multiple estimation results that the employee's emotional psychological state has transitioned from "positive" to "negative," and that this "negative" psychological state has been maintained for several hours. In such a case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information to lower the hurdle for task completion as described above.

[0151] On the other hand, the first state is defined as "negative," and the second state as "positive." In this case, the adjustment unit 123 determines, based on multiple estimation results, that the employee's emotional psychological state shifted from "negative" to "positive," and that this "positive" psychological state was maintained for several hours. In such cases, the adjustment unit 123 may adjust the reminder settings by changing the timing of the reminder notification for the relevant task information earlier, reducing the number of reminder notifications, or adding wording to the reminder to urge submission or reporting. In these cases, it is considered that the employee has overcome the peak of processing the relevant task information, and as described above, slightly increasing the workload on the employee can promote their task completion. Therefore, the adjustment unit 123 can adjust reminders flexibly based on the employee's emotional changes based on multiple estimation results. It should also be noted that the above-mentioned emotional psychological state can be applied to emotional levels.

[0152] Furthermore, the estimation unit 122 may estimate the operator's level of tension. The estimation unit 122 estimates the user U's level of tension based on the operator's heart rate and velocity from their biometric information. The adjustment unit 123 may adjust the reminder setting information for the relevant task information based on the estimated level of tension of the operator, including operational instruction information other than screen displays, such as voice notifications and changes in keyboard operation, which are displayed as pop-up screens on the screen of the information processing terminal 200. For example, if the adjustment unit 123 determines that the operator is in a tense state based on the estimated level of tension of the operator, it may assume that the operator's concentration is scattered. In this case, it is advisable to adjust the reminder setting information for the relevant task information by adding operational instruction information for voice notifications. Alternatively, in this case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information by adding operational instruction information that displays a pop-up screen on the screen of the information processing terminal 200 in a position where the operator's gaze is focused, along with a warning sound, and that other terminal operations will not be accepted until the pop-up screen is confirmed. Furthermore, if the operator is in a tense state, the adjustment unit 123 may assume that the operator is in a hurry to process the task. In this case, it is advisable to adjust the settings by adding an action instruction to reduce the key input depth to the reminder settings of the relevant task information. Furthermore, the adjustment unit 123 may also adjust the settings if the person in charge is under stress or is flustered and not calm. In this case, it is advisable to adjust the settings by adding an action instruction to display a pop-up for final confirmation to the reminder settings of the relevant task information.

[0153] The reminder execution unit 124 refers to the reminder management DB 113 to identify the task information to be reminded and sends a reminder notification based on the reminder setting information to the recipient information of the person to whom the identified task information is assigned. Specifically, the reminder execution unit 124 identifies a task ID or subtask ID for which the timing of the reminder notification is set to be a predetermined period before the completion deadline of the task information, based on the reminder setting information in the reminder management DB 113. Then, the reminder execution unit 124 identifies the user information set as the person in charge for the identified task ID or subtask ID from the task information DB 112. Then, the reminder execution unit 124 identifies the recipient information included in the identified user information from the personal information DB 111. Then, the reminder execution unit 124 generates a reminder notification message that includes the reminder content included in the reminder setting information for the identified task ID or subtask ID and sends the reminder notification message to the recipient information via the communication network N. Furthermore, when a person in charge completes the assigned task information, the reminder execution unit 124 registers the completion date and time in the completion date of the corresponding task information in the task information DB 112, or updates the completion flag to ON. In this case, the reminder execution unit 124 also registers in the progress status and processing history that the corresponding task information in the task information DB 112 has been completed. In addition, in this case, the reminder execution unit 124 may also delete the information related to the corresponding task information from the reminder management DB 113 and move it to the processing history, etc., in the task information DB 112.

[0154] The IF unit 130 is an interface circuit that communicates between the reminder server 100 and the outside world. Specifically, the IF unit 130 communicates with information processing terminals 200-1 to 200-n and biological information measuring devices 300-1 to 300-n via the communication network N. The IF unit 130 may be implemented, for example, as a general-purpose or dedicated circuit implemented in a semiconductor device. Alternatively, the IF unit 130 may be implemented as a combination of the above-mentioned communication circuit and software that controls the communication processing.

[0155] Figure 13 is a block diagram showing the configuration of an information processing terminal 200 according to this disclosure. The information processing terminal 200 comprises a storage unit 210, a control unit 220, and an IF unit 230. The storage unit 210 includes, for example, a non-volatile storage device such as a hard disk or flash memory and a memory such as RAM, i.e., a volatile storage device. The storage unit 210 stores behavioral information 211 and biological information 212.

[0156] The behavioral information 211 includes user U's image data, sound data, and operation information, etc. The behavioral information 211 may also include information indicating user U's actions, analyzed from the image data, sound data, and operation information, etc. Each piece of data and information in the behavioral information 211 is associated with the date and time of acquisition.

[0157] The biological information 212 is biological information measured by the biological information measuring device 300 from user U. The biological information 212 includes the date and time of measurement.

[0158] The control unit 220 is a control device that controls each component of the information processing terminal 200. The control unit 220 is a processor such as a CPU, GPU, FPGA, or quantum processor. For example, the control unit 220 loads a program from the storage unit 210 into memory and executes the program. The program, although not shown in the diagram, is a computer program that implements various processes in the information processing terminal 200 according to this disclosure. As a result, the control unit 220 realizes the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223. Some or all of the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223 may be realized by hardware other than the control unit 220, such as a general-purpose or dedicated circuit implemented in a semiconductor device.

[0159] The acquisition unit 221 acquires image data from the camera, capturing the user U's face, movements, etc. The acquisition unit 221 also acquires sound data, including the user U's voice, from the microphone. The acquisition unit 221 also acquires user U's operation information from the input device. The acquisition unit 221 registers the acquired image data, sound data, and operation information as activity information 211 in the storage unit 210, associating them with the acquisition date and time. The acquisition unit 221 also acquires user U's biological information from the biological information measuring device 300, and registers the acquired biological information as biological information 212 in the storage unit 210, associating the measurement date and time with the acquired biological information.

[0160] The transmitting / receiving unit 222 transmits the behavioral information 211 and biometric information 212 registered in the storage unit 210 to the reminder server 100 via the communication network N. The transmitting / receiving unit 222 may transmit data or information each time the acquisition unit 221 acquires data or information, or each time data or information is registered in the storage unit 210. Alternatively, the transmitting / receiving unit 222 may periodically transmit untransmitted data or information from the storage unit 210.

[0161] Furthermore, the transmitting / receiving unit 222 receives reminder notifications from the reminder server 100 via the communication network N. The transmitting / receiving unit 222 then outputs display information, such as messages, included in the received reminder notification to the display control unit 223. If the received reminder notification includes operation instruction information, the transmitting / receiving unit 222 outputs the operation instruction information to the appropriate output destination. For example, if the operation instruction information includes a pop-up display, the transmitting / receiving unit 222 outputs the pop-up display instruction information to the display control unit 223. If the operation instruction information includes an alarm sound or voice message, the transmitting / receiving unit 222 outputs the alarm sound or voice message to the speaker via the IF unit 230. If the operation instruction information includes vibration, the transmitting / receiving unit 222 outputs a vibration instruction to the IF unit 130.

[0162] The display control unit 223 controls the display device to display the display information received from the transmitting / receiving unit 222. When the display control unit 223 receives instruction information for a pop-up display from the transmitting / receiving unit 222, it controls the display device to display a pop-up.

[0163] The IF unit 230 is an interface circuit that performs communication between the information processing terminal 200 and the outside. Specifically, the IF unit 130 communicates with the reminder server 100 via the communication network N. Furthermore, the IF unit 230 may also communicate with the biological information measuring device 300 via short-range wireless communication or wired communication. The IF unit 130 also outputs captured images, etc., received from the connected camera to the storage unit 110 via the control unit 120. The IF unit 130 also outputs sound data received from the connected microphone to the storage unit 110 via the control unit 120. The IF unit 130 also outputs input information received from the connected input device to the control unit 120. The IF unit 130 also outputs display information received from the control unit 120 to the display device. The IF unit 130 also outputs sound data received from the control unit 120 to the speaker. Furthermore, the IF unit 130 outputs the operation instruction information received from the control unit 120 to the vibration circuit. The IF unit 130 may be implemented, for example, by a general-purpose or dedicated circuit implemented in a semiconductor device. Alternatively, the IF unit 130 may be implemented by a combination of the above-mentioned communication circuit and software that controls the communication process.

[0164] Figure 14 is a flowchart showing the initial setup process for reminders when new task information is assigned to Person U1 in this disclosure. Here, Person Us is the supervisor of Person U1 and is a person involved in the task information assigned to Person U1.

[0165] For example, Us, the supervisor of U1, registers new task information, including its contents, completion deadline, and the person in charge, U1, on the information processing terminal 200-s. In response, the information processing terminal 200-s sends a registration request, including the task information and person in charge, to the reminder server 100 via the communication network N. In response, the registration unit 121 of the reminder server 100 acquires the task information assigned to U1 (S401). The registration unit 121 then registers the acquired task information in the task information DB 112. The registration unit 121 may also register Us, the user who made the registration request, as a related party to the acquired task information in the task information DB 112. The registration unit 121 then registers the initial reminder settings for the acquired task information in the reminder management DB 113 (S402).

[0166] Figure 15 is a flowchart showing the flow of the reminder setting adjustment process when task information assigned to person in charge U1 related to this disclosure is being processed. Here, person in charge Us is the supervisor of person in charge U1 and is a person in charge of the task information assigned to person in charge U1.

[0167] For example, suppose that person Us uses the information processing terminal 200-s to access task information assigned to person U1 and check the progress of the task information. The biometric information measuring device 300-s periodically measures the biometric information of person Us and transmits the measured biometric information, measurement date and time, and identification information of person Us to the information processing terminal 200-s. In response, the acquisition unit 221 of the information processing terminal 200-s acquires the biometric information of person Us from the biometric information measuring device 300-s. The acquisition unit 221 also acquires behavioral information 211 such as image data, sound data, and operation information of person Us. Then, the transmitting / receiving unit 222 of the information processing terminal 200-s transmits a registration request including the behavioral information 211 and biometric information 212 to the reminder server 100 via the communication network N. Furthermore, the biometric information measuring device 300-s may transmit a registration request, including the measured biometric information, to the reminder server 100 via the communication network N without going through the information processing terminal 200-s. In this case, the transmitting / receiving unit 222 of the information processing terminal 200-s shall transmit a registration request, including the behavioral information 211, to the reminder server 100 via the communication network N.

[0168] Accordingly, the registration unit 121 of the reminder server 100 acquires a registration request including the biometric information and behavioral information of the person concerned Us (S501). The registration unit 121 may also acquire a registration request including the biometric information of the person concerned Us from the biometric information measuring device 300-s via the communication network N, and acquire a registration request including the behavioral information of the person concerned Us from the information processing terminal 200-s via the communication network N. Then, the registration unit 121 registers the biometric information and behavioral information acquired in step S501 into the personal information DB 111 of the person concerned Us (S502).

[0169] Subsequently, the calculation unit 127 determines whether the information accessed by the person concerned Us is related to the task information of person in charge U1 (S503). Here, it is assumed that the task information of person in charge U1 accessed by the person concerned Us is incomplete. For example, the calculation unit 127 identifies the action information of the person concerned Us that was registered in the personal information DB 111 in step S502 from the personal information DB 111. Then, the calculation unit 127 refers to the task information DB 112 and, for example, determines whether it relates to a specific task information based on the operation history of the action information, such as the file name being edited or the application being used. Alternatively, the calculation unit 127 may determine whether the person concerned Us is related to the task information based on the access rights in the information system related to the task information accessed by the person concerned Us.

[0170] In step S503, if it is determined that the information accessed by the person concerned Us is related to the task information of person in charge U1 (YES in S503), the calculation unit 127 calculates the degree of attention Us has paid to person in charge U1's task information from the personal information DB 111 (S504). For example, the calculation unit 127 searches the personal information DB 111 for a certain period of time from the present to a predetermined time ago for person in charge U1's biometric information and operation history. Then, the calculation unit 127 calculates the degree of attention Us has paid to person in charge U1's task information by performing various analyses on the retrieved biometric information and operation history for that period as described above. Alternatively, the calculation unit 127 may calculate the degree of attention according to the position of the person concerned Us. For example, if the person concerned Us is a superior of person in charge U1's superior, the task information assigned to person in charge U1 can be said to have a higher degree of attention within the organization. Alternatively, the calculation unit 127 may calculate the level of attention based on the deadline or progress status of the entire project to which person U1 belongs, or the annual achievement goals of the entire department or person U1. Alternatively, the calculation unit 127 may refer to the personal information DB 111 and calculate the level of attention based on the analysis results of the image data, sound data, and behavioral information such as operation information of person Us. For example, the estimation unit 122 analyzes eye movements from the image data of person Us during the time when person Us accessed person U1's task information. If the calculation unit 127 determines, based on the analysis results, that person Us was intently looking at the progress status of person U1's task information, the calculation unit 127 should calculate a higher level of attention for person Us. Alternatively, the estimation unit 122 analyzes the content of speech from the sound data of person Us during the time when person Us accessed person U1's task information. Furthermore, if the calculation unit 127 determines, based on the analysis results, that the task information of person in charge U1 includes a monologue, the calculation unit 127 may calculate a higher level of attention from related party Us. Alternatively, if the amount of operation of related party Us's input device during the time period in which related party Us accessed person in charge U1's task information exceeds a certain value, the calculation unit 127 may calculate a higher level of attention from related party Us. In addition, in this case, the registration unit 121 may add related party Us to the task information DB 112 as a related party to the relevant task information.

[0171] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the task information based on the attention level calculated in step S504 (S505). Specifically, the adjustment unit 123 adjusts by determining the content of the changes to the reminder setting information according to the level of attention level. For example, the calculation unit 127 calculates the attention level to be higher than the standard value if the number of times stakeholders Us have checked the task information of person in charge U1 using a Gantt chart, etc., is higher than a predetermined value. Therefore, if the attention level is higher than the standard value, the adjustment unit 123 adjusts by determining the content of the changes to the reminder setting information to increase the number of reminder notifications to person in charge U1 for the relevant task information or to increase the frequency. After that, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information (S506). Then, the reminder server 100 finishes the reminder setting adjustment process.

[0172] Furthermore, if in step S503 it is determined that the information accessed by the person concerned Us is not related to the task information of the person in charge U1 (NO in S503), the reminder server 100 terminates the reminder setting adjustment process.

[0173] Figure 16 is a flowchart showing the flow of the reminder notification process according to this disclosure. First, the reminder execution unit 124 of the reminder server 100 determines at a predetermined timing whether or not there is task information to be reminded in the task information DB 112 (S601). The predetermined timing may be, for example, a fixed interval. If it is determined in step S601 that there is no task information to be reminded (NO in S601), the reminder execution unit 124 executes step S601 again after a certain period of time.

[0174] In step S601, if it is determined that there is task information to be reminded (YES in S601), the reminder execution unit 124 determines whether or not there are stakeholders Us for the corresponding task information (S602). Specifically, the reminder execution unit 124 may determine the existence or non-existence of stakeholders Us by referring to the reminder management DB 113 and the task information DB 112.

[0175] In step S602, if it is determined that there is a person Us involved with the task information in question (YES in S602), the calculation unit 127 calculates the level of attention that person Us has to the task information of person U1 from the personal information DB 111 (S603). For example, the calculation unit 127 calculates the level of attention that person Us has to the task information of person U1 from the personal information DB 111 based on the latest operation history of the identified person Us. Alternatively, the calculation unit 127 may calculate the level of attention that person Us has to the task information of person U1 from the personal information DB 111 based on the operation history of the identified person Us over a certain period. Specifically, the calculation unit 127 calculates the level of attention that person Us has to the task information of person U1 in the same manner as in step S407 or S504 described above.

[0176] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the relevant task information based on the level of attention (S604). For example, the adjustment unit 123 may make the adjustment by determining the changes to the reminder setting information, similar to steps S408 or S505 described above. Then, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information. After that, the reminder execution unit 124 determines whether the relevant task information is a target for a reminder in the adjusted settings (S605).

[0177] If the task information in step S605 is determined not to be subject to a reminder, the reminder execution unit 124 suspends the reminder notification (S607). At this time, the registration unit 121 may register the date and time of the suspension of the reminder notification in the reminder history of the reminder setting information corresponding to the task information in the reminder management DB 113. Alternatively, the adjustment unit 123 may readjust the reminder setting information in response to the suspension of the reminder notification and update the reminder management DB 113 with the readjusted reminder setting information.

[0178] On the other hand, if the task information in step S605 is determined to be a target for a reminder, the reminder execution unit 124 sends a reminder notification to the information processing terminal 200-1 of the person in charge U1 based on the adjusted reminder setting information (S606). The registration unit 121 may register the date and time of sending the reminder notification in step S606, its content, etc., in the reminder history of the reminder management DB 113. By utilizing the reminder history, it is possible to improve the accuracy of calculating the level of attention given to relevant parties Us to future task information and adjusting the settings related to reminders. In addition, if it is determined in step S602 that there are no relevant parties Us for the task information in question (NO in S602), the reminder server 100 may also execute the process in step S606, which will be described later, according to the initial reminder settings in Figure 14.

[0179] In response to step S606, for example, the information processing terminal 200-1 receives a reminder notification from the reminder server 100 via the communication network N and performs processing according to the received reminder notification. For example, the information processing terminal 200-1 displays display information such as a message included in the reminder notification on the display device. Alternatively, if the reminder notification includes operation instruction information, the information processing terminal 200-1 displays a pop-up on the display device, outputs an alarm sound or voice message from the speaker, and performs vibrations, etc., as described above.

[0180] This allows the assigned person U1 to receive appropriate reminders for incomplete task information, tailored to the level of attention the stakeholders Us are paying to it. For example, if stakeholders Us frequently check the task information assigned to assigned person U1, it is highly likely that stakeholders Us are concerned about the progress of the task. The adjustment process within the reminder setting adjustment process and reminder notification process described in this disclosure allows for increasing the number of reminder notifications sent to assigned person U1 for task information that stakeholders Us are paying more attention to, and for subdividing the content of the notifications. As a result, assigned person U1 can more easily report progress to stakeholders Us appropriately in response to reminder notifications. Thus, it is possible to support the smooth execution of tasks by assigned person U1 at an effective time for stakeholders Us.

[0181] Figure 17 is a flowchart illustrating another example of the reminder setting adjustment process when the person in charge U1 related to this disclosure is processing the assigned task information. The reminder setting adjustment process in Figure 17 uses the estimated emotions of the person in charge Us, in addition to the level of attention, to adjust the reminder settings. The following explanation will focus on the differences from Figure 15, and explanations of processes that overlap with Figure 15 will be omitted as appropriate.

[0182] First, if it is determined in step S503 that the information accessed by the person concerned Us is related to the task information of person in charge U1 (YES in S503), then, in parallel with step S504 described above, the estimation unit 122 estimates the feelings of the person concerned Us towards the task information of person in charge U1 from the personal information DB 111 (S504a). For example, the estimation unit 122 searches the personal information DB 111 for biometric information and operation history of the person concerned Us for a certain period from the present to a predetermined time ago. Then, the estimation unit 122 estimates the changes in the feelings of the person concerned Us by performing various analyses on the biometric information and operation history for the searched period as described above. Note that the estimation unit 122 may estimate the feelings at a single point in time, not just the changes in feelings over a certain period.

[0183] Then, after steps S504 and S504a, the adjustment unit 123 adjusts the reminder settings corresponding to the relevant task information based on the estimated level of attention and emotions of the stakeholders Us to the task information (S505a). Subsequently, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information (S506). Then, the reminder server 100 terminates the reminder setting adjustment process.

[0184] For example, similar to step 505 described above, the settings for reminders corresponding to the task information are adjusted based on the level of attention calculated in step S504. Next, if the estimated emotion of the person concerned Us is "negative", the adjustment unit 123 may adjust the reminder settings information to further increase the number of reminders to person in charge U1, in addition to the reminder settings information adjusted based on the level of attention. Alternatively, in this case, the adjustment unit 123 may include in the content of the reminder to person in charge U1 a request to report the progress to the person concerned Us. Alternatively, in this case, the adjustment unit 123 may adjust the reminder settings information to subdivide and send reminder notifications for each completion deadline of the subtask unit of the task information. This increases the opportunities for the person concerned Us to grasp the progress of person in charge U1 in detail, making it easier to alleviate the negative emotions of the person concerned Us. Specifically, if the level of attention is above a predetermined threshold and the emotions of the person concerned are negative, the frequency of reminders is maximized and detailed reports of progress are included. If the level of attention is above a predetermined threshold and stakeholders' emotions are positive, maintain the normal reminder frequency. If the level of attention is below a predetermined threshold and stakeholders' emotions are negative, increase the reminder frequency and keep progress reports concise. If the level of attention is below a predetermined threshold and stakeholders' emotions are positive, minimize the reminder frequency.

[0185] Furthermore, if the position of the person in charge Us is higher than that of the person in charge U1's superior, the adjustment unit 123 should be adjusted to increase the frequency of reminder notifications or to make the content of the reminder notifications more detailed, thereby encouraging attention from the person in charge U1. This will enable more appropriate reminders for high-priority task information within the organization and enhance the effectiveness of the reminders.

[0186] Furthermore, the estimation unit 122 estimates, based on an analysis of the operation history of the personal information database 111, that the person concerned Us spends a relatively long time using a specific communication tool among the communication tools used for work on the information processing terminal 200-s. For example, the estimation unit 122 estimates that the person concerned Us is likely to prefer receiving progress reports via video chat application from their subordinate, employee U1. In this case, the adjustment unit 123 may include a message in the reminder setting information for the task information assigned to employee U1 recommending that they report progress via video chat application and submit documents, etc., as included in the estimation results. This helps both the person concerned Us and employee U1 to smoothly carry out their tasks.

[0187] In other words, because reminder settings can be customized based on the estimated emotions of stakeholders, it is possible to achieve effective and personalized task management tailored to the needs of stakeholders.

[0188] Furthermore, the adjustment unit 123 may adjust the reminder settings by taking into account the estimated emotions of the person in charge U1. This makes it possible to identify a series of mental states that significantly affect the behavioral performance of person in charge U1, such as their concentration on the task information being processed, their level of mental fatigue, and their stress level, to analyze these mental states, and to provide reminders of planned schedules necessary for task completion.

[0189] Furthermore, the reminder execution unit 124 or registration unit 121 should update the task information DB 112 with the progress of the task information each time the person in charge U1 makes progress in processing the task information, and after completion. This allows for analysis of the time required from immediately after the reminder notification until person in charge U1 starts processing the task information, the processing time, and whether or not the completion deadline was met. The progress status can then be used as the completion status of task information that person in charge U1 has handled in the past.

[0190] Therefore, as described above, the estimation unit 122 may estimate the emotions by taking into account the achievement status of task information that the person in charge U1 has handled in the past. For example, the estimation unit 122 can estimate whether the currently assigned task information is in an area that person in charge U1 is good at or not good at, based on the past achievement status of task information similar to the category and content of the task information assigned to person in charge U1. Therefore, the adjustment unit 123 can adjust the reminder settings for the task information currently assigned to person in charge U1 more appropriately based on the emotion estimation result that takes into account the achievement status of task information that the person in charge has handled in the past. For example, the reminder execution unit 124 can send reminder notifications at a frequency that is more individually optimized for person in charge U1.

[0191] Furthermore, if the task information includes multiple subtasks, it is possible to implement detailed and highly accurate reminder settings, such as adjusting the granularity of reminder notifications to the subtask level according to the emotions or emotional changes of the person in charge, U1. This enables effective reminder notifications for person in charge, effectively supporting the completion of the task.

[0192] (Embodiment 5) The information system according to Embodiment 5 calculates an attention level on the information processing terminal side, which indicates the degree of attention paid to the task information by stakeholders other than the person assigned to the incomplete task information, and adjusts the reminder settings for the person in charge of the task information based on the attention level. This supports the smooth execution of the task by the person in charge at an effective timing for the stakeholders of the task, similar to Embodiment 4 described above.

[0193] Figure 18 is a block diagram showing the overall configuration of the reminder system 1000d, which includes the information processing system 1d according to this disclosure. The reminder system 1000d is a modified version of the reminder system 1000 described above. Therefore, the following explanation will focus on the differences from the embodiment 4 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0194] The reminder system 1000d comprises a reminder server 100d, information processing terminals 200-1 to 200-n and 200d-s, and biological information measuring devices 300-1 to 300-n and 300-s. Each of the reminder server 100d, information processing terminals 200-1 to 200-n and 200d-s, and biological information measuring devices 300-1 to 300-n and 300-s is connected to communicate via a communication network N. Furthermore, the information processing terminal 200d-s is an example of the information processing system 1d according to this embodiment.

[0195] Figure 19 is a block diagram showing the configuration of the reminder server 100d according to this disclosure. Compared to the reminder server 100 shown in Figure 12 above, the reminder server 100d has the estimation unit 122 and adjustment unit 123 removed, and the provision unit 125 and update unit 126 added. The other configurations of the reminder server 100d are the same as those of the reminder server 100.

[0196] The control unit 120 loads a program containing various processes of the reminder server 100d according to this disclosure from the storage unit 110 into memory and executes the program. This enables the control unit 120 to implement the functions of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124. Note that some or all of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124 may be implemented in hardware separate from the control unit 120, such as a general-purpose or dedicated circuit implemented in a semiconductor device.

[0197] The provisioning unit 125 provides search results by performing searches and other operations in response to search requests from information processing terminals 200d-s to the personal information DB 111, task information DB 112, or reminder management DB 113, and transmitting the search results to the requesting information processing terminal 200d-s. The update unit 126 updates the personal information DB 111, task information DB 112, or reminder management DB 113 in response to update requests from information processing terminals 200d-s, and transmits the update results to the requesting information processing terminal 200d-s. The provisioning unit 125 and the update unit 126 may also perform the same processing with information processing terminals 200-1 to 200-n.

[0198] Figure 20 is a block diagram showing the configuration of an information processing terminal 200d-s, which is an example of the information processing system 1d according to this disclosure. Compared to the information processing terminal 200 in Figure 13 described above, the information processing terminal 200d-s has the transmitting / receiving unit 222 replaced with a transmitting / receiving unit 222d, and an estimation unit 224, adjustment unit 225, and calculation unit 227 have been added. The other configurations of the information processing terminal 200d-s are assumed to be the same as those of the information processing terminal 200.

[0199] The control unit 220 loads a program implementing the information processing method according to this disclosure from the storage unit 210 into memory and executes the program. As a result, the control unit 220 realizes the functions of the acquisition unit 221, the transmission / reception unit 222d, the display control unit 223, the estimation unit 224, the adjustment unit 225, and the calculation unit 227. Note that some or all of the acquisition unit 221, the transmission / reception unit 222d, the display control unit 223, the estimation unit 224, the adjustment unit 225, and the calculation unit 227 may be realized by hardware other than the control unit 220, for example, by a general-purpose or dedicated circuit implemented in a semiconductor device.

[0200] The transmitting / receiving unit 222d transmits search requests or update requests to the personal information DB 111, task information DB 112, or reminder management DB 113 to the reminder server 100d via the communication network N. The transmitting / receiving unit 222d also receives search results or update results from the personal information DB 111, task information DB 112, or reminder management DB 113 from the reminder server 100d via the communication network N. In addition, the transmitting / receiving unit 222d has the same functions as the transmitting / receiving unit 222 in Figure 13 described above.

[0201] The estimation unit 224, adjustment unit 225, and calculation unit 227 have the same functions as the estimation unit 122, adjustment unit 123, and calculation unit 127 shown in Figure 12 above. However, the estimation unit 224 estimates the emotions of the person concerned Us using the behavioral information 211 and biometric information 212 stored in the memory unit 210. In addition, the estimation unit 224 estimates the emotions of the person concerned Us using the search results from the personal information DB 111 and task information DB 112 received by the transmitting / receiving unit 222d.

[0202] The calculation unit 227 uses the behavioral information 211 stored in the storage unit 210 to calculate the level of attention the stakeholders Us have to the task information assigned to the person in charge U1. The calculation unit 227 also uses the search results from the personal information DB 111 and task information DB 112 received by the transmission / reception unit 222d to calculate the level of attention the stakeholders Us have. The calculation unit 227 may also calculate the level of attention based on access rights in the information system related to the task information. Furthermore, the calculation unit 227 may take into account the personality information of the stakeholders Us in addition to the operation history and access rights to calculate the level of attention the stakeholders Us have to the task information of the person in charge U1.

[0203] The adjustment unit 225 adjusts the reminder settings for assigned personnel in incomplete task information based on the attention level of the stakeholders Us calculated by the calculation unit 227. The adjustment unit 225 also adjusts the reminder settings for assigned personnel in task information using the search results of the task information DB 112 and reminder management DB 113 received by the transmission / reception unit 222d, along with the attention level. Furthermore, the adjustment unit 225 may adjust the reminder settings for assigned personnel in task information using the emotion estimation results from the estimation unit 224. The transmission / reception unit 222d then sends an update request, including the adjusted reminder settings, to the reminder server 100d via the communication network N.

[0204] Furthermore, since the reminder setting adjustment process according to this embodiment is generally equivalent to that in Figures 14, 15, and 17 described above, the differences will be explained below. In this embodiment, the registration, search, update, and deletion processes in steps S401 to S409 of Figure 14 to the personal information DB 111, task information DB 112, or reminder management DB 113 shall be interpreted as the transmission of registration requests, search requests, update requests, and deletion requests from the information processing terminal 200d-s to the reminder server 100d, and the reception of the results of each request. The same applies to steps S501 to S506 in Figure 15, and steps S501 to S504, S504a, S505a, and S506 in Figure 17.

[0205] Furthermore, the reminder notification process according to this embodiment is generally equivalent to that in Figure 16 described above, so the differences will be explained in detail below. In step S603 of Figure 16, the attention level calculation process for the person concerned Us is performed by the calculation unit 227 of the information processing terminal 200d-s, which calculates the attention level in response to a calculation request from the reminder server 100d. In step S604 of Figure 16, the adjustment process is performed by the adjustment unit 225 of the information processing terminal 200d-s, and the transmission / reception unit 222d sends an update request including the adjusted reminder setting information to the reminder server 100d.

[0206] Thus, this fifth embodiment can achieve the same effects as the fourth embodiment described above.

[0207] (Embodiment 6) The information system according to Embodiment 6 distributes or makes redundant functions across the server and information processing terminal to achieve the same processing as Embodiments 4 or 5 described above. As a result, similar to Embodiments 4 or 5 described above, it supports the smooth execution of tasks by the person in charge at an effective timing for the people involved in the task.

[0208] Figure 21 is a block diagram showing the overall configuration of the reminder system 1000e, which includes the information processing system 1e according to this disclosure. The reminder system 1000e is a modified version of the reminder system 1000 or 1000d described above. Therefore, the following explanation will focus on the differences from the embodiments 4 or 5 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0209] The reminder system 1000e comprises a reminder server 100e, information processing terminals 200-1 to 200-n and 200e-s, and biological information measuring devices 300-1 to 300-n and 300-s. Each of the reminder server 100e, information processing terminals 200-1 to 200-n and 200e-s, and biological information measuring devices 300-1 to 300-n and 300-s is connected to communicate via a communication network N. The reminder server 100e and information processing terminal 200e-s are examples of the information processing system 1e according to this embodiment.

[0210] The reminder server 100e shares at least some of its configuration with the reminder server 100 in Figure 12 and the reminder server 100d in Figure 19. Similarly, the information processing terminal 200e-s shares some of its configuration with the information processing terminal 200 in Figure 13 and the information processing terminal 200d-s in Figure 20. For example, the reminder server 100e may be modified by adding the provision unit 125 and update unit 126 from Figure 19 to the reminder server 100 in Figure 12. The information processing terminal 200e-s may have the same configuration as the information processing terminal 200d-s in Figure 20. In these cases, for example, the reminder server 100e sends the attention level to the information processing terminal 200e-s after calculating the attention level. The information processing terminal 200e-s then adjusts the reminder setting information using the received attention level and sends an update request including the adjusted reminder setting information to the reminder server 100e. Alternatively, the information processing terminal 200e-s may send the attention level to the reminder server 100e after calculating the attention level. The reminder server 100e may then adjust the reminder setting information using the received attention level. Alternatively, the reminder setting adjustment process in Figures 14, 15, and 17 may be performed by the information processing terminal 200e-s, as in Embodiment 5 described above, to perform the attention level calculation and adjustment processes. Furthermore, the reminder notification process in Figure 16 may be performed by the reminder server 100e, including the attention level calculation and adjustment processes, as in Embodiment 4 described above. In addition, the reminder server 100e may send the estimation results to the information processing terminal 200e after calculating the attention level and estimating the emotion. The information processing terminal 200e-s may then adjust the reminder setting information using the received attention level and estimation results, and send an update request including the adjusted reminder setting information to the reminder server 100e. Alternatively, the information processing terminal 200e-s transmits the attention level and estimation results to the reminder server 100e after the attention level calculation process and emotion estimation process. The reminder server 100e can then adjust the reminder setting information using the received attention level and estimation results. Alternatively, the reminder setting adjustment process in Figures 14 and 15 may be performed by the information processing terminal 200e-s performing the attention level calculation process, estimation process, and adjustment process, as in Embodiment 5 described above.Furthermore, the reminder notification process in Figure 16 may also be performed by the reminder server 100e, including the attention level calculation process, emotion estimation process, and adjustment process, similar to the embodiment 4 described above. Note that the combination of functional division between the reminder server 100e and the information processing terminal 200e-s is not limited to these.

[0211] Thus, this embodiment 6 can also achieve the same effects as embodiments 4 and 5 described above.

[0212] (Embodiment 7) The information system according to Embodiment 7 distributes or makes redundant functions across the server and information processing terminal to achieve the same processing as Embodiments 4, 5, or 6 described above. As a result, similar to Embodiments 4, 5, or 6 described above, it supports the smooth execution of tasks by the person in charge at an effective timing for the people involved in the task.

[0213] Figure 22 is a block diagram showing the overall configuration of the reminder system 1000f, which includes the information processing system 1e-2 according to this disclosure. The reminder system 1000f is a modified version of the reminder systems 1000, 1000d, or 1000e described above. Therefore, the following explanation will focus on the differences from embodiments 4, 5, or 6 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0214] The reminder system 1000f comprises a reminder server 100e, information processing terminals 200e-1 to 200e-n and 200e-s, and biological information measuring devices 300-1 to 300-n and 300-s. Each of the reminder server 100e, information processing terminals 200e-1 to 200e-n and 200e-s, and biological information measuring devices 300-1 to 300-n and 300-s is connected to communicate via a communication network N. Each of the information processing terminals 200e-1 to 200e-n and 200e-s is assumed to have equivalent functions. Therefore, in the following description, information processing terminals 200e-1 to 200e-n and 200e-s may be simply referred to as "information processing terminal 200e". The reminder server 100e, and information processing terminals 200e-1 to 200e-n and 200e-s are examples of the information processing system 1e-2 according to this embodiment. That is, the information processing system 1e-2 is the same as the information processing system 1e described above, but with the addition of information processing terminals 200e-1 to 200e-n, which have the same functionality as information processing terminal 200e-s. Therefore, the information processing system 1e-2 according to this embodiment has the same functionality as the embodiment 6 described above. Furthermore, the combination of functions of each component of the information processing system 1e-2 can be varied, just as with the information processing system 1e described above.

[0215] Thus, this embodiment 7 can also achieve the same effects as embodiments 4, 5, and 6 described above.

[0216] (Other Embodiments) Although the embodiments described above were described as hardware configurations, the invention is not limited thereto. The invention can also be implemented by having the CPU execute a computer program to perform any processing.

[0217] In the examples described above, the program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrical, optical, acoustic or other forms of propagating signals.

[0218] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0219] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments, rather than being associated with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps described in any of the drawings may be changed as appropriate.

[0220] This application claims priority based on Japanese Patent Application No. 2024-161316 and Japanese Patent Application No. 2024-161317, both filed on 18 September 2024, and incorporates all of their disclosures herein.

[0221] This invention provides an information processing system and method to support the smooth execution of tasks by users, as well as an information processing system and method to support the smooth execution of tasks by those responsible for the tasks at an effective time for the stakeholders involved.

[0222] 1000 Reminder system, N Communication network, 1 Information processing system, 100 Reminder server, 110 Storage unit, 111 Personal information DB, 112 Task information DB, 113 Reminder management DB, 120 Control unit, 121 Registration unit, 122, 224 Estimation unit, 123, 225 Adjustment unit, 124 Reminder execution unit, 127 Calculation unit, 130 IF unit, 200 Information processing terminal, 210 Storage unit, 211 Behavioral information, 212 Biological information, 220 Control unit, 221 Acquisition unit, 222 Transmit / receive unit, 223 Display control unit, 230 IF unit, 300 Biological information measuring device, U User, U1-Un Person in charge, Us Related parties

Claims

1. An information processing system comprising: an estimation unit that estimates the emotions of a user assigned to incomplete task information; and an adjustment unit that adjusts the reminder settings for the user in the task information based on the emotion estimation results.

2. The information processing system according to claim 1, wherein the estimation unit estimates one of a plurality of levels in a predetermined index indicating the user's psychological state in relation to the task information as the emotion, and the adjustment unit determines whether the level in the estimation result is above a predetermined threshold, and adjusts the settings to change at least one of the number of reminders or the content of the reminders according to the determination result.

3. The information processing system according to claim 1 or 2, wherein the estimation unit estimates the user's emotions multiple times while the task information is incomplete, and the adjustment unit adjusts the settings if the psychological state of the emotions in the multiple estimation results indicates that it has transitioned from a first state to a second state and that the second state has been maintained for a certain period of time.

4. The information processing system according to claim 1 or 2, wherein the estimation unit further takes into account the achievement status of task information previously handled by the user to estimate the emotion.

5. An information processing method comprising a computer that estimates the emotions of a user assigned to incomplete task information, and adjusts the reminder settings for the user in the task information based on the results of the emotion estimation.

6. An information processing system comprising: a calculation unit that calculates an attention level indicating the degree of attention paid to the task information by stakeholders other than the person assigned to the incomplete task information; and an adjustment unit that adjusts the settings for reminders to the person in charge of the task information based on the attention level.

7. The information processing system according to claim 6, wherein the person concerned is an administrator who manages the task information.

8. The information processing system according to claim 6 or 7, wherein the calculation unit calculates the attention level based on the operation history in the information system related to the task information.

9. The information processing system according to claim 6 or 7, further comprising an estimation unit for estimating the emotions of the persons concerned, wherein the adjustment unit adjusts the settings based on the level of attention and the estimation results by the estimation unit.

10. An information processing method comprising: a computer calculating an attention level indicating the degree of attention paid to the task information by a person other than the person assigned to the incomplete task information; and adjusting the reminder settings for the person in charge of the task information based on the attention level.

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