Transaction reminding method and device, equipment and storage medium

Abstract

This application discloses a method, apparatus, device, and storage medium for reminding users of tasks, relating to the field of smart device technology. The method includes: determining to-do items in a wearable smart device database, wherein the to-do items are categorized and organized based on tasks input by a target user through different channels; performing personalized planning on the to-do items based on the target user; and providing reminders to the target user based on the personalized planning according to the intelligently sensed status of the target user. This personalized planning rationally arranges the reminder time for to-do items according to the actual needs and habits of the target user, and provides reminders based on the personalized planning according to the intelligently sensed status of the target user, thereby minimizing user disturbance while ensuring timely and reliable reminders, thus eliminating user reminder anxiety.

Description

Technical Field

[0001] This application relates to the field of smart device technology, and in particular to methods, apparatus, devices and storage media for reminding users of important information. Background Technology

[0002] In the current field of smart wearable products, reminder functions have become a core component of many applications.

[0003] The reminder function of existing smart wearable products reminds users at fixed times or before fixed times. This method of reminder is prone to reminding users too early or when they are busy. Reminding users too early may cause them to ignore the reminder, and reminding users when they are busy may cause them to perceive the reminder as urging, thus causing them to feel annoyed.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a method, apparatus, device, and storage medium for reminding users of tasks, aiming to solve the technical problem that reminders given when users are busy can easily be perceived as urgings, thus causing users to feel annoyed.

[0006] To achieve the above objectives, this application proposes a method for reminding people of matters, the method comprising:

[0007] The to-do list in the wearable smart device database is identified. The to-do list is categorized and organized based on the items that the target user inputs as reminders through different channels.

[0008] Personalized planning for the to-do items based on the target user;

[0009] Based on the intelligent perception of the target user's status, reminders are given to the target user based on the personalized plan.

[0010] In one embodiment, prior to the step of determining the to-do items in the wearable smart device database, the following steps are included:

[0011] The system obtains reminders input by target users through different channels, including voice command input, calendar application input, and photo input.

[0012] For items in the list of items requiring reminders that are not explicitly stated, a multimodal and context-based completion process is performed to obtain the completed items;

[0013] The completed items and other items in the reminder items are input into a preset large language model to obtain a database of to-do items for wearable smart devices. The preset large language model is used to classify the to-do items and evaluate the time required to complete them.

[0014] In one embodiment, the step of performing personalized planning for the to-do items based on the target user includes:

[0015] The system obtains the target user's personal information and the corresponding to-do items' attributes. The personal information includes schedule information and user profile, and the to-do items' attributes include reminder time, urgency, and importance.

[0016] Personalized planning is carried out based on the target user's personal circumstances and the attributes of the corresponding to-do items.

[0017] In one embodiment, the step of performing personalized planning based on the target user's personal circumstances and the attributes of the corresponding to-do items includes:

[0018] When the target user requests to change or add a to-do item, the latest personal information of the target user and the latest item attributes of the corresponding to-do item are obtained;

[0019] Based on the latest personal information and latest task attributes, the target user's to-do list is rearranged, and the rearranged to-do list is fed back to the target user.

[0020] Once the target user's information based on the feedback response is obtained, personalized planning is performed based on the target user.

[0021] In one embodiment, the step of performing personalized planning based on the target user's personal circumstances and the attributes of the corresponding to-do items further includes:

[0022] Based on the attributes of each to-do item, determine whether the corresponding to-do item is a fixed-time reminder item;

[0023] If the corresponding to-do item is a fixed-time reminder item, then the reminder time of the fixed-time reminder item is determined to be fixed and unchanged;

[0024] If the corresponding to-do item is not a fixed-time reminder item, then a personalized plan will be made based on the target user's personal situation and the to-do items that are not fixed-time reminder items.

[0025] In one embodiment, the step of providing reminders to the target user based on the personalized plan according to the intelligently sensed state of the target user includes:

[0026] The target user's environmental status, mental state, and other smart device data are input into a preset AI model to provide reminders to the target user based on the personalized plan. The AI ​​model is used to determine the plan for reminding the target user from a preset behavior pattern library based on the target user's status.

[0027] In one embodiment, the step of providing reminders to the target user based on the personalized plan includes:

[0028] Based on a preset AI model, the target user's idle or busy status is analyzed according to the environmental state, mental state, and smart device data to determine the target user's behavioral status.

[0029] Based on a preset AI model, a plan for reminding the target user corresponding to the behavioral state is determined from a preset behavioral pattern library.

[0030] Furthermore, to achieve the above objectives, this application also proposes a reminder device, which includes:

[0031] The determination module is used to determine the to-do items in the wearable smart device database. The to-do items are sorted and organized based on the items that the target user inputs as reminders through different channels.

[0032] The planning module is used to perform personalized planning for the to-do items based on the target user;

[0033] The reminder module is used to remind the target user based on the personalized plan according to the intelligently sensed status of the target user.

[0034] In addition, to achieve the above objectives, this application also proposes a reminder device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the reminder method as described above.

[0035] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the reminder method described above.

[0036] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the reminder method described above.

[0037] One or more technical solutions proposed in this application have at least the following technical effects:

[0038] After identifying the to-do items in the wearable smart device's database, personalized planning is performed on these items based on the target user. These to-do items are categorized and organized from user input via different channels, allowing for personalized planning that rationally schedules reminder times based on the target user's actual needs and habits. Furthermore, since users may be in different states when reminders are needed, and different states are better able to handle different types of to-do items, personalized planning is implemented based on the target user's perceived state to ensure timely and reliable reminders while minimizing user disruption and reducing reminder anxiety. Attached Figure Description

[0039] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating the first embodiment of the method for reminding users of matters in this application.

[0042] Figure 2 This is a flowchart illustrating Embodiment 2 of the method for reminding users of matters in this application.

[0043] Figure 3 This is a flowchart illustrating the third embodiment of the method for reminding users of matters in this application.

[0044] Figure 4 A simplified flowchart illustrating the intelligent sensing reminder method provided for the matters mentioned in this application;

[0045] Figure 5 This is a schematic diagram of the module structure of the reminder device according to an embodiment of this application;

[0046] Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the notification method in this application embodiment.

[0047] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0048] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0049] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0050] The main solution of this application embodiment is: the server of the wearable smart device determines the to-do items in the wearable smart device database, wherein the to-do items are obtained by classifying and organizing the items that need to be reminded based on the target user's input through different channels; personalized planning is performed on the to-do items based on the target user; and reminders are given to the target user based on the personalized planning according to the intelligently sensed status of the target user.

[0051] In this embodiment, for ease of description, the following description uses the server of the wearable smart device as the execution entity.

[0052] Because the reminder function of existing smart wearable products reminds users at fixed times or before fixed times, this method is prone to reminding users too early or when they are busy. Reminding users too early can easily lead to them ignoring the reminder, and reminding users when they are busy can easily lead them to perceive the reminder as urging, thus causing them to feel annoyed.

[0053] This application provides a solution that, after identifying to-do items in the database of a wearable smart device, performs personalized planning for these items based on the target user. The to-do items are categorized and organized from user input via different channels, allowing for personalized planning that rationally schedules reminder times based on the target user's actual needs and habits. Furthermore, since users may be in different states when reminders are needed, and different states are better able to handle different types of to-do items, this application aims to selectively remind users of relevant to-do items based on their state. Therefore, based on the intelligently sensed state of the target user, personalized planning-based reminders are provided, thereby minimizing user disruption while ensuring timely and reliable reminders and alleviating reminder anxiety.

[0054] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or server capable of performing the above functions. The following description uses a server for a wearable smart device as an example to illustrate this embodiment and the subsequent embodiments.

[0055] Based on this, the embodiments of this application provide a method for reminding people of matters, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for reminding users of matters in this application.

[0056] In this embodiment, the reminder method includes steps S10 to S30:

[0057] Step S10: Determine the to-do items in the wearable smart device database. The to-do items are sorted and organized based on the items that the target user inputs through different channels and needs to be reminded.

[0058] It's important to note that to-do items are tasks, events, or reminders that users need to complete at a future point in time or within a specified period. These items are entered by users through various means, categorized, and then stored in the wearable smart device's database. The target users are those who use wearable smart devices and require personalized reminders. The different means refer to various methods users use to input reminders, including but not limited to voice commands, calendar applications, and photo input.

[0059] Understandably, by using multiple input methods, target users can more conveniently add to-do items without being limited by time and space. Furthermore, categorizing and organizing data improves its structure, providing a basis for subsequent planning of to-do items, thereby improving reminder efficiency and accuracy.

[0060] In practice, target users can input reminders through various means (e.g., voice commands, mobile apps, photos, etc.). All reminders are then input into a large language model, which categorizes them based on importance (high, medium, low), urgency (urgent, moderate, low), life domain (work, personal, family), and implementation attributes (travel - location, mobile operation - app, PC operation - application). Finally, all processed items are organized into a single database to determine the to-do list in the database.

[0061] Optionally, before step S10, the reminder method further includes:

[0062] The system obtains reminders input by target users through different channels, including voice command input, calendar application input, and photo input.

[0063] For items in the list of items requiring reminders that are not explicitly stated, a multimodal and context-based completion process is performed to obtain the completed items;

[0064] The completed items and other items in the reminder items are input into a preset large language model to obtain a database of to-do items for wearable smart devices. The preset large language model is used to classify the to-do items and evaluate the time required to complete them.

[0065] It's important to clarify that voice command input involves the user inputting reminders to the wearable smart device via voice commands, such as "Remind me of a meeting at 9 AM tomorrow." Calendar app input involves the user inputting reminders through a calendar management app on their phone or wearable device, such as adding "Workout at 3 PM" to their calendar app. Photo input involves the user inputting reminders by taking a picture with the wearable smart device; for example, the device takes a picture of a meeting notice, and uses image recognition technology to extract the text information to obtain the desired information. Multimodal input combines multiple input methods (such as voice, text, and images) to understand and process information. Context refers to the environment and background information when the user inputs information, including time, location, and user habits, used to help understand and complete the input. Completion processing supplements and refines the input of unclear information using multimodal and contextual information, making the content more complete and explicit.

[0066] Understandably, by providing multiple input methods, target users can more easily add to-do items without being limited by time and space, thereby improving user convenience and system flexibility, allowing target users to choose the most suitable input method according to their own habits and current environment.

[0067] Understandably, obtaining the reminders needed by the target user through multiple input methods can provide a more comprehensive understanding of these reminders, thus avoiding omissions and enabling more accurate reminders to the target user.

[0068] Understandably, by using multimodal and contextual information completion processing, the completeness and accuracy of user input can be improved, reducing the user's input burden and enhancing the intelligence level of wearable smart devices. This allows wearable smart devices to better understand and process user input, thereby providing more accurate reminder services.

[0069] Understandably, categorizing and time-based assessments of tasks using a pre-defined large language model can improve data structuring and processing efficiency, enabling wearable smart devices to better understand and manage users' to-do lists, thereby providing more accurate and personalized reminders. Simultaneously, categorization and time-based assessments can also help users better plan their time and tasks, improving work efficiency.

[0070] In the specific implementation, the system first acquires reminders input by the target user through various means, including voice commands, calendar applications, and photos. For example, a user can say "Remind me of a meeting at 9 AM tomorrow" via voice command, add "Workout at 3 PM" to their calendar, or input a picture of a meeting notice. For reminders that lack specific details, the system completes the information. For instance, a user might only say "Remind me of a meeting" without specifying the time and location. This missing information can be supplemented using multimodal data (such as voice, text, and images) and contextual information (such as current time, user location, and user behavior). For example, the specific time and location of the meeting can be inferred based on the user's current schedule and historical behavior. Finally, after completion, the completed reminders, along with other clearly defined reminders, are input into a pre-defined large language model. This model then categorizes the reminders and estimates the time required to complete them. For example, a large language model can categorize "meeting" as "work" and estimate that it will take 1 hour to complete the task. The categorized and time-assessed tasks are then stored in the to-do list database of a wearable smart device for subsequent personalized planning and reminders.

[0071] Step S20: Perform personalized planning for the to-do items based on the target user;

[0072] It should be noted that personalized planning is a customized to-do list arrangement and reminder strategy for target users based on their personal circumstances (such as schedule information, target user profile, etc.) and the attributes of to-do items (such as reminder time, urgency, importance, etc.).

[0073] Understandably, personalized planning can reasonably arrange reminder times for to-do items based on the actual needs and habits of the target users, avoiding reminding them at busy or inappropriate times, thereby improving the effectiveness of reminders and the user experience. At the same time, personalized planning can also prevent the target users from being disturbed when they are focused on working or handling things, thus helping them to better manage their time and tasks and improve work efficiency.

[0074] In practice, after identifying the tasks, personalized planning is then carried out, including obtaining the target user's personal information, such as schedule information and target user profile, as well as obtaining task attributes, such as reminder time, urgency, and importance. For example, if the target user profile shows that the target user is a busy business person, the wearable smart device's server may schedule urgent and important meeting reminders during the target user's relatively free time, such as after lunch or before leaving get off work.

[0075] Step S30: Based on the intelligently sensed status of the target user, provide reminders to the target user based on the personalized plan.

[0076] It should be noted that intelligent sensing uses sensors, data acquisition, and analysis technologies to perceive the target user's status in real time, including environmental conditions, mental state, and data from the smart devices being used. The status refers to the target user's overall condition at a specific moment or within a certain time period, including environmental conditions, mental state (such as the target user's emotions and level of concentration), and data from other smart devices (such as the status of the target user's mobile phone, tablet, etc.).

[0077] Understandably, intelligent sensing allows wearable smart devices to obtain the target user's status in real time, enabling them to adjust reminder plans accordingly. In other words, personalized reminders are planned for the target user. This allows wearable smart devices to adjust the reminder time of to-do items based on contextual intelligent sensing and dynamic decision-making, minimizing disturbance to the target user and thus eliminating reminder anxiety.

[0078] In practical implementation, based on personalized planning, the target user's status is monitored in real time using intelligent sensing technology. For example, sensors detect that the target user's environment is an office, wearable devices detect the target user's emotions and level of concentration, and other smart devices detect the status of the devices the target user is using. Based on these statuses, the most appropriate reminder method and adjustment plan are selected from a preset behavior pattern library, and then reminders are given to the target user according to the adjusted plan.

[0079] This embodiment provides a method for reminding users of tasks. After identifying to-do items in the database of a wearable smart device, the method performs personalized planning based on the target user. The to-do items are categorized and organized from user inputs requiring reminders through different channels. This personalized planning allows for the reasonable scheduling of reminder times based on the target user's actual needs and habits. Furthermore, since users may be in different states when reminders are needed, and different states are better able to handle different types of to-do items, this method selectively reminds users of relevant tasks based on their state. Therefore, based on the intelligently sensed state of the target user, personalized planning-based reminders are provided. This ensures timely and reliable reminders while minimizing user disruption and alleviating reminder anxiety.

[0080] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S20 also includes steps S01~S02:

[0081] Step S01: Obtain the personal information of the target user and the item attributes of the corresponding to-do items. The personal information includes schedule information and user profile. The item attributes include reminder time, urgency, and importance.

[0082] Step S02: Based on the target user's personal circumstances and the attributes of the corresponding to-do items, perform personalized planning based on the target user.

[0083] It should be noted that "personal information" refers to personal information related to the target user, including but not limited to schedule information and user profiles, used to assist in personalized planning. Schedule information refers to the timetable and planning information recorded by the target user on wearable smart devices or other related applications, such as meeting arrangements and appointment times. User profiles are user characteristic models built based on multi-dimensional data such as the target user's behavior, preferences, and habits, used to describe the user's personalized needs and behavioral patterns. Task attributes are characteristics related to the to-do item, including reminder time, urgency, and importance, used to describe the characteristics and priority of the to-do item. Reminder time is the specific time at which the to-do item requires a reminder. Urgency: The urgency level of the to-do item, usually divided into high, medium, and low levels, used to indicate the urgency of the task. Importance: The importance level of the to-do item, usually divided into urgent, moderate, and low levels, used to indicate the priority of the task.

[0084] Understandably, obtaining information about a user's personal circumstances and the attributes of their to-do items can provide a rich data foundation for subsequent personalized planning, enabling wearable smart devices to more comprehensively understand the user's needs and behavioral patterns, thereby providing more accurate and personalized reminder services.

[0085] Understandably, personalized planning can rationally schedule reminders for to-do items based on users' actual needs and habits, avoiding reminders at busy or inconvenient times, thereby improving the effectiveness of reminders and user experience. At the same time, it can also help users better manage their time and tasks, improving work efficiency.

[0086] In practical implementation, the first step is to acquire the target user's personal information, including schedule information and user profile. Schedule information can be obtained from the user's calendar app or wearable device, such as multiple meetings scheduled for a particular day. User profiles can be built by analyzing the user's historical behavioral data and preferences; for example, the user might be a frequent business traveler or a fitness enthusiast. Simultaneously, the attributes of the corresponding to-do items need to be acquired, including reminder time, urgency, and importance. These attributes help wearable smart devices better understand the characteristics and priority of each to-do item. Then, personalized planning is performed based on the individual's situation and item attributes. For example, if the user profile indicates a frequent business traveler, the wearable smart device might schedule urgent and important meeting reminders during the user's relatively free time, such as after lunch or before leaving get off work. Furthermore, the wearable smart device will rationally prioritize reminders based on the urgency and importance of the to-do items. For example, for urgent and important items, the wearable smart device might remind the user multiple times in advance, while for non-urgent and unimportant items, it might remind the user once when the user is relatively free.

[0087] In practice, all reminder content can be input into the AI ​​model, allowing the AI ​​model to generate a daily reminder schedule based on the following rules;

[0088] Rules: 1. Send reminders according to the user-specified time; 2. Highly urgent, highly important reminders that are due today must be included in today's reminder schedule; 3. Avoid multiple reminders that "need to be completed in more than 1 hour" being sent together. Distribute these tasks reasonably and evenly throughout the day. For example, if two reports need to be written and there are no other reminders that day, schedule them for the morning and afternoon respectively to balance user stress and restore energy for a reasonable workload distribution; 4. Arrange reminder times reasonably based on the attributes of each reminder. For example, a reminder to pick up a package from the home delivery station should be sent after get off work; a reminder to send work emails should be sent during work hours while the user is in front of the computer; 5. Balance work and rest, and integrate different types of reminders; for example, "Remind me to exercise three times a week" should be combined with other reminders. 6. Integrate the three reminders into the three-day intervals, or if the user is already very tired from a business trip, schedule them on a day when they don't need to travel; 7. Balance the reminders for personal, family, and work activities each day, ensuring these three types of activities are included every day, rather than accumulating them into each day; 8. Based on historical data or user feedback, understand user preferences and build a user profile: daily activities (outdoor sports / crafts / games / fitness), personality (laissez-faire / persistent / detail-oriented / hedonistic). Under the premise of a healthy lifestyle (without affecting sleep, diet, etc.), adjust the plan according to the user profile. For example, if the user has a fitness plan in the evening, if the user is a fitness enthusiast, remind them not to eat too much when dining with friends to avoid affecting their workout; if the user is a laid-back user, do not send a reminder.

[0089] Furthermore, step S02 also includes:

[0090] When the target user requests to change or add a to-do item, the latest personal information of the target user and the latest item attributes of the corresponding to-do item are obtained;

[0091] Based on the latest personal information and latest task attributes, the target user's to-do list is rearranged, and the rearranged to-do list is fed back to the target user.

[0092] Once the target user's information based on the feedback response is obtained, personalized planning is performed based on the target user.

[0093] It should be noted that "Changing a to-do item" refers to users modifying existing to-do items, including but not limited to changing reminder times and item content. "Adding a to-do item" refers to users adding new items that require reminders. "Latest Personal Information" refers to the user's latest schedule information and user profile obtained by the wearable smart device when a user changes or adds a to-do item. "Latest Item Attributes" refers to the latest reminder time, urgency, and importance attributes of the to-do item obtained by the wearable smart device when a user changes or adds a to-do item. "Confirmation Information" is information from the user confirming the rescheduled to-do item provided by the wearable smart device, indicating that the user accepts the arrangement proposed by the wearable smart device.

[0094] Understandably, when a target user needs to change existing to-do items or add new ones, wearable smart devices will obtain the user's latest personal information, including the latest schedule information and user profile, as well as the latest attributes of the corresponding to-do items, to ensure that subsequent personalized planning is based on the latest data, thereby improving the accuracy and practicality of reminders.

[0095] Understandably, by rearranging to-do lists and providing timely feedback to users, wearable smart devices ensure that users are always aware of the latest to-do list arrangements. This not only improves user satisfaction but also helps users better manage their time and tasks, avoiding confusion caused by inconsistent information. Personalized planning based on user confirmation information ensures that the final reminder schedule meets the user's actual needs and preferences.

[0096] Furthermore, step S02 also includes:

[0097] Based on the attributes of each to-do item, determine whether the corresponding to-do item is a fixed-time reminder item;

[0098] If the corresponding to-do item is a fixed-time reminder item, then the reminder time of the fixed-time reminder item is determined to be fixed and unchanged;

[0099] If the corresponding to-do item is not a fixed-time reminder item, then a personalized plan will be made based on the target user's personal situation and the to-do items that are not fixed-time reminder items.

[0100] It should be noted that fixed-time reminders are to-do items with a clear and fixed reminder time.

[0101] Understandably, by determining whether a task is a fixed-time reminder, it is possible to distinguish between tasks that must be reminded at a specific time and those that can be flexibly scheduled. This ensures that the reminder time for fixed-time reminders remains unchanged, preventing users from missing important fixed-time events due to scheduling conflicts or other factors, thereby improving the accuracy and reliability of reminders.

[0102] Understandably, personalized planning allows for flexible adjustment of reminder times for non-fixed-time items based on users' actual needs and schedules. This aims to minimize disruption to users while ensuring timely and reliable reminders and reducing reminder anxiety.

[0103] Furthermore, step S02 also includes:

[0104] When the target user requests to add an item to the schedule information that shares free time, obtain reference information on the schedules of other users related to the target user;

[0105] From the reference information and the schedule information, identify the shared time when the target user and the other users are both free;

[0106] Based on the target user's newly added shared free time items and the shared time, a personalized plan is made based on the target user.

[0107] It should be noted that sharing free time refers to sharing free time with other people's schedules. The reference information refers to the schedule information of other users related to the target user.

[0108] Understandably, when a target user wants to add a new item to their schedule that requires sharing a free time slot with other users, it is necessary to obtain the schedule information of the other users related to the target user after obtaining their consent, and then refer to that schedule information to find a free time slot for both users. This ensures that the newly added shared item can be arranged smoothly and improves the efficiency and accuracy of schedule management.

[0109] Based on the first and second embodiments of this application, the same or similar content as the above embodiments in the third embodiment of this application can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Before step S30, the reminder method further includes step S1:

[0110] Step S1: The environmental state, mental state, and other smart device data of the target user are intelligently sensed and input into a preset AI model to provide reminders to the target user based on the personalized plan. The AI ​​model is used to determine the plan for reminding the target user from a preset behavior pattern library based on the target user's state.

[0111] It's important to note that environmental conditions refer to the external environment in which the target user is located, including surrounding objects, noise levels, and lighting. Mental state refers to the target user's current psychological and emotional state, such as fatigue, excitement, anxiety, or focus. Smart device data refers to the status data of other smart devices (such as mobile phones and tablets) being used by other users. The preset behavior pattern library is a database containing various user behavior patterns, from which the AI ​​model can select the most suitable reminder behavior pattern for the target user's current state.

[0112] Understandably, intelligent sensing technology can be used to monitor the target user's environmental status, mental state, and data from other smart devices the user is using in real time, in order to gain a more comprehensive understanding of the user's current environment and psychological state. Based on the user's real-time status, the system can adjust the to-do items that need to be reminded to the target user in real time, providing the most appropriate reminders and avoiding disturbing the user or missing important reminders.

[0113] Furthermore, step S30 also includes:

[0114] Based on a preset AI model, the target user's idle or busy status is analyzed according to the environmental state, mental state, and smart device data to determine the target user's behavioral status.

[0115] Based on a preset AI model, a plan for reminding the target user corresponding to the behavioral state is determined from a preset behavioral pattern library.

[0116] It's important to note that behavioral state refers to the target user's current behavioral pattern, including idle and busy states, used to determine the most suitable reminder method. Reminder planning involves determining a reminder strategy from a pre-defined behavioral pattern library based on the target user's behavioral state, including the reminder's timing, method, and content.

[0117] Understandably, by comprehensively analyzing various state data, it is possible to accurately determine whether a user is currently fatigued or focused on a task. After determining the target user's behavioral state, the system selects the most suitable reminder strategy from a pre-set behavioral pattern library using a pre-set AI model. The reminder strategy is then communicated to the target user, and with the user's consent, the reminder plan is modified to avoid disturbing the user or missing important reminders.

[0118] In the specific implementation, refer to Figure 4 By using environmental sensors (cameras, IMUs, microphones, etc.) and biosensors (PPG, etc.) on the smart devices worn by the user, as well as other smart devices that the user is using (computers, mobile phones, etc.), the system can perceive the current user and environmental status and determine the corresponding reminder plan based on the following rules through an AI model.

[0119] Rules: 1. If user fatigue is detected, adjust subsequent reminder plans and inform the user. For example, suggest the user take a break after completing their current task; or complete some tasks that allow for rest (such as taking a break while traveling); or postpone non-urgent reminders to the next day. 2. Avoid interrupting the user's current focused activity. For example, if the user is composing an email, remind them after the email is sent; if the user is playing a game, remind them after the game ends; if the user is running, remind them when they are resting or stretching after training; remind them when they are daydreaming or doing nothing. 3. When the user's current task takes a long time to complete, and there are no urgent or important remaining reminders, automatically adjust the reminder schedule and inform the user, "A fitness plan was detected at 9 PM, but you are watching a movie, so the reminder will not be given; it will be postponed to 7 AM tomorrow (the time will be determined based on the user's habits)." Real-time communication with the user is necessary to adjust the plan according to their needs. For example, if the user takes too long to complete a task, affecting the timely reminders, directly ask the user how to arrange the subsequent plan and adjust the subsequent reminder plan in real time based on user feedback.

[0120] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method of reminding matters in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0121] This application also provides a reminder device; please refer to... Figure 5 The reminder device includes:

[0122] The determination module 10 is used to determine the to-do items in the wearable smart device database. The to-do items are sorted and organized based on the items that the target user inputs as reminders through different channels.

[0123] Planning module 20 is used to perform personalized planning for the to-do items based on the target user;

[0124] The reminder module 30 is used to remind the target user based on the personalized plan according to the intelligently sensed status of the target user.

[0125] Optionally, the determining module 10 is further configured to acquire reminders input by the target user through different means, including voice command input, calendar application input, and photo input; perform multimodal and context-based completion processing on items in the reminders that do not have clearly stated content to obtain completed items; input the completed items and other items in the reminders into a preset large language model to obtain a database of wearable smart device to-do items, wherein the preset large language model is used to classify the to-do items and evaluate the time required to complete the items.

[0126] Optionally, the planning module 20 is further configured to obtain the target user's personal information and the corresponding task attributes, wherein the personal information includes schedule information and user profile, and the task attributes include reminder time, urgency, and importance; and to perform personalized planning based on the target user according to the target user's personal information and the corresponding task attributes.

[0127] Optionally, the planning module 20 is further configured to, when the target user requests to change or add to-do items, obtain the latest personal information of the target user and the latest item attributes of the corresponding to-do items; rearrange the target user's to-do items based on the latest personal information and the latest item attributes, and provide feedback on the rearranged to-do items to the target user; and, upon obtaining confirmation information from the target user based on the feedback response, perform personalized planning based on the target user.

[0128] Optionally, the planning module 20 is further configured to determine whether a corresponding to-do item is a fixed-time reminder item based on the item attributes of each to-do item; if the corresponding to-do item is a fixed-time reminder item, then the reminder time of the fixed-time reminder item is determined to be fixed; if the corresponding to-do item is not a fixed-time reminder item, then personalized planning based on the target user's personal situation and the to-do items that are not fixed-time reminder items is performed.

[0129] Optionally, the reminder module 30 is further configured to input the environmental state, mental state, and other smart device data of the target user that are being intelligently sensed into a preset AI model, so as to provide reminders to the target user based on the personalized plan. The AI ​​model is used to determine the plan for reminding the target user from a preset behavior pattern library based on the state of the target user.

[0130] Optionally, the reminder module 30 is further configured to, based on a preset AI model, analyze the idle or busy state of the target user according to the environmental state, the mental state, and the smart device data, and determine the behavioral state of the target user; and, based on the preset AI model, determine a plan to remind the target user corresponding to the behavioral state from a preset behavioral pattern library.

[0131] The reminder device provided in this application, employing the reminder method described in the above embodiments, can solve the technical problem that reminders given when users are busy can easily be perceived as urgings, thus causing annoyance to users. Compared with the prior art, the beneficial effects of the reminder device provided in this application are the same as those of the reminder method provided in the above embodiments, and other technical features of the reminder device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0132] This application provides a reminder device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the reminder method in Embodiment 1 above.

[0133] The following is for reference. Figure 6 The diagram illustrates a structural schematic suitable for implementing the reminder device of the embodiments of this application. The reminder device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The reminder device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0134] like Figure 6As shown, the reminder device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the reminder device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the reminder device to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show reminder devices with various systems, it should be understood that implementing or having all of the systems shown is not required. More or fewer systems may be implemented alternatively.

[0135] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0136] The reminder device provided in this application, employing the reminder method described in the above embodiments, can solve the technical problem that reminders given when users are busy can easily be perceived as urgings, thus causing annoyance to users. Compared with the prior art, the beneficial effects of the reminder device provided in this application are the same as those of the reminder method provided in the above embodiments, and other technical features of this reminder device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0137] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0138] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0139] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the reminder method in the above embodiments.

[0140] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0141] The aforementioned computer-readable storage medium may be included in the reminder device; or it may exist independently and not assembled into the reminder device.

[0142] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the task reminder device, cause the task reminder device to: determine to-do items in the wearable smart device database, wherein the to-do items are categorized and organized based on the items that the target user inputs for reminders through different channels; perform personalized planning for the to-do items based on the target user; and provide reminders to the target user based on the personalized planning according to the intelligently sensed status of the target user.

[0143] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0144] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0145] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0146] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described reminder method. This solves the technical problem that reminders given when users are busy can easily be perceived as urgings, leading to user annoyance. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the reminder method provided in the above embodiments, and will not be repeated here.

[0147] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described reminder method.

[0148] The computer program product provided in this application solves the technical problem that reminders given when users are busy can easily be perceived as nagging, thus causing annoyance to users. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the reminder methods provided in the above embodiments, and will not be repeated here.

[0149] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.

Claims

1. A method for reminding people of tasks, characterized in that, The method includes: The to-do list in the wearable smart device database is identified. The to-do list is categorized and organized based on the items that the target user inputs as reminders through different channels. The to-do list is then personalized based on the target user. The step of performing personalized planning for the to-do items based on the target user includes: Obtain the target user's personal information and the item attributes of the corresponding to-do items, wherein the personal information includes schedule information and user profile; Based on the target user's personal circumstances and the attributes of the corresponding to-do items, a personalized plan is made for the target user; Based on the intelligently sensed status of the target user, reminders are given to the target user based on the personalized plan. The step of providing reminders to the target user based on the personalized plan according to the intelligently sensed state of the target user includes: The target user's environmental status, mental state, and other smart device data are input into a preset AI model to provide reminders to the target user based on the personalized plan. The AI ​​model is used to determine the plan for reminding the target user from a preset behavior pattern library based on the target user's status.

2. The method as described in claim 1, characterized in that, Before the step of determining the to-do items in the wearable smart device database, the method further includes: The system obtains reminders input by target users through different channels, including voice command input, calendar application input, and photo input. For items in the list of items requiring reminders that are not explicitly stated, a multimodal and context-based completion process is performed to obtain the completed items; The completed items and other items in the reminder items are input into a preset large language model to obtain a database of to-do items for wearable smart devices. The preset large language model is used to classify the to-do items and evaluate the time required to complete them.

3. The method as described in claim 1, characterized in that, The attributes of the matter include reminder time, urgency level, and importance level.

4. The method as described in claim 3, characterized in that, The step of performing personalized planning based on the target user's personal circumstances and the attributes of the corresponding to-do items includes: When the target user requests to change or add a to-do item, the latest personal information of the target user and the latest item attributes of the corresponding to-do item are obtained; Based on the latest personal information and latest task attributes, the target user's to-do list is rearranged, and the rearranged to-do list is fed back to the target user. Once the target user's information based on the feedback response is obtained, personalized planning is performed based on the target user.

5. The method as described in claim 3, characterized in that, The step of performing personalized planning based on the target user's personal circumstances and the attributes of the corresponding to-do items further includes: Based on the attributes of each to-do item, determine whether the corresponding to-do item is a fixed-time reminder item; If the corresponding to-do item is a fixed-time reminder item, then the reminder time of the fixed-time reminder item is determined to be fixed and unchanged; If the corresponding to-do item is not a fixed-time reminder item, then a personalized plan will be made based on the target user's personal situation and the to-do items that are not fixed-time reminder items.

6. The method as described in claim 1, characterized in that, The step of providing reminders to the target user based on the personalized plan includes: Based on a preset AI model, the target user's idle or busy status is analyzed according to the environmental state, mental state, and data from other users' smart devices, to determine the target user's behavioral state. Based on a preset AI model, a plan for reminding the target user corresponding to the behavioral state is determined from a preset behavioral pattern library.

7. A reminder device, characterized in that, The device includes: The determination module is used to determine the to-do items in the wearable smart device database. The to-do items are sorted and organized based on the items that the target user inputs as reminders through different channels. The planning module is used to perform personalized planning for the to-do items based on the target user. Specifically, the planning module is used to obtain the target user's personal information and the item attributes of the corresponding to-do items. The personal information includes schedule information and user profile. Based on the target user's personal information and the item attributes of the corresponding to-do items, the module performs personalized planning for the target user. The reminder module is used to provide reminders to the target user based on the personalized plan according to the intelligently sensed state of the target user. Specifically, the reminder module is used to input the intelligently sensed environmental state, mental state, and other smart device data of the target user into a preset AI model to provide reminders to the target user based on the personalized plan. The AI ​​model is used to determine the plan for reminding the target user from a preset behavior pattern library based on the state of the target user.

8. A reminder device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the reminder method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the reminder method as described in any one of claims 1 to 6.

Images