WO2018108175A1 - Task plan adjustment method for wearable device, and device - Google Patents

Abstract

A task plan adjustment method for a wearable device, and a related device. The method comprises: receiving user activity data corresponding to task units that is obtained and uploaded by a wearable device according to an original task plan table (S110); performing mathematic processing on related user activity data by using the task units as units, so as to determine executive result data of the task units (S120); evaluating the executive result data corresponding to the task units according to evaluation reference data corresponding to the corresponding task units, and determining evaluation result data corresponding to the evaluation reference data (S130); adjusting settings of the task units corresponding to the evaluation result data in the original task plan table according to preset conditions corresponding to the task units, and generating a new task plan table (S140); and pushing the new task plan table to the wearable device (S150). By means of the method, a task plan selected by a user is properly changed according to an actual condition, and accordingly, the objective for healthily and effectively developing a habit is achieved.

Description

Wearable device task plan adjustment method and device Technical field

The present invention relates to the technical field of smart devices, and in particular, to a wearable device task plan adjustment method and device.

Background technique

With the development of wearable devices, the variety of wearable devices is becoming more and more abundant, and the application population is more and more extensive, from adult mobile phones, smart bracelets, smart glasses, etc. to wearable devices that are gradually popularized among children. Children's smart watches, etc. The function development of today's children's smart watches has made great progress. It has the ability to analyze children's behaviors through the heart rate sensors, accelerometers and other components set in the watch, so parents or teachers can learn about children through such children's smart watches. Acting and then guiding the child's behavior makes it a powerful tool for children to develop good behavioral habits.

In order to realize the purpose of let children's smart watches urge children to develop good living and learning habits, in the prior art, alarms are often used to remind a certain task, and further, by setting a pre-established schedule, one day, one week or other time is planned. The task of the cycle. However, the mission plan obtained through these technical means is either single-function or static, unable to adapt to changes in the actual situation, and it is impossible to combine the actual data with the big data that children are used to cultivate to develop more scientific and individualized habits. plan.

Summary of the invention

Based on this, the primary object of the present invention is to solve at least one of the above problems, and to provide a wearable device task plan adjustment method and a corresponding device thereof, wherein the device includes a wearable device task plan adjustment device, a server, and a Wearable device to run the method described in the previous goal.

In order to achieve the above object of the present invention, the following technical solutions are adopted:

In a first aspect, a method for adjusting a wearable device task plan of the present invention includes the following steps: receiving user activity data uploaded by a wearable device, where the user activity data is acquired according to each corresponding task unit in an original task schedule; Performing mathematical processing on the related user activity data in units of the task unit to determine execution result data of each task unit; and executing result data corresponding to each task unit according to the evaluation reference data corresponding to each corresponding task unit Performing an evaluation, determining evaluation result data corresponding to the evaluation reference data; adjusting a setting of a task unit corresponding to the evaluation result data in the original task schedule according to a preset condition corresponding to the task unit, generating a new A task schedule; push the new task schedule to the wearable device.

In a second aspect, another wearable device task plan adjustment method of the present invention includes the steps of: setting a local task plan according to each task unit in an original task schedule received from a cloud server; specified in each task unit Timely executing the planning instruction specified by the task unit, acquiring corresponding user activity data; uploading the user activity data to the cloud server; acquiring the evaluation result information and/or the new task schedule table of the cloud server according to the user activity data, The result information is displayed accordingly and/or the original task schedule is replaced.

In a third aspect, the present invention provides a wearable device task plan adjustment apparatus comprising: at least one processor; and at least one memory communicatively coupled to the at least one processor; the at least one memory comprising The processor-executable instructions, when executed by the at least one processor, cause the apparatus to perform at least the following: receiving each of the wearable devices acquired and uploaded according to an original task schedule User activity data corresponding to the task unit; performing mathematical processing on the related user activity data in units of the task unit to determine execution result data of each task unit; according to the evaluation reference data corresponding to each corresponding task unit, Performing evaluation result data corresponding to each task unit, determining evaluation result data corresponding to the evaluation reference data; adjusting the original task schedule to correspond to the evaluation result data according to a preset condition corresponding to the task unit The setting of the task unit to generate a new task schedule; The wearable device to push the new task schedule.

In a fourth aspect, the present invention provides another wearable device task plan adjusting apparatus, comprising: at least one processor; and at least one memory communicably connected to the at least one processor; the at least one memory Included by the processor executable instructions, when executed by the at least one processor, causing the apparatus to perform at least the following: according to tasks in an original task schedule received from a cloud server The unit sets the local task plan; executes the plan instruction specified by the task unit at the time specified by each task unit, acquires corresponding user activity data; uploads the user activity data to the cloud server; and obtains the cloud server according to the user activity The evaluation result information of the data and/or the new task schedule table respectively displays the result information and/or replaces the original task schedule.

In a fifth aspect, the present invention also provides a wearable device task plan adjustment server, including a first processor, wherein the first processor is configured to perform a wearable device task plan adjustment method of the first aspect.

In a sixth aspect, the present invention further provides a wearable device, comprising a second processor, wherein the second processor is configured to perform another wearable device task plan adjustment method of the second aspect.

In a seventh aspect, a computer program is provided in an embodiment of the present invention, comprising computer readable code, when the server runs the computer readable code, causing the method described in the first aspect to be performed.

In an eighth aspect, a computer program is provided in an embodiment of the present invention, comprising computer readable code, when the wearable device runs the computer readable code, causing the method described in the second aspect to be performed.

A ninth aspect, the embodiment of the present invention provides a computer readable medium, wherein the computer program according to the seventh aspect or the eighth aspect is stored.

The method and the device can realize the adaptive modification of the established task plan according to the actual result obtained by correspondingly analyzing the data collected by the plan execution after the terminal device downloads and executes the scheduled task plan, and proposes a more reasonable and more reasonable. Personalize new mission plans and push them to users. This method changes the drawbacks of the original static execution of the original task plan, and rationally utilizes the user's actual execution data and combines the big data formed by relevant data from many other users, so that the task plan selected by the user is continuously changed according to the actual situation, and the combination is By controlling the control of the baseline data, it is possible to adjust the difficulty level of the task plan as needed, to achieve the effect of step-by-step habit cultivation, and finally to achieve the purpose of allowing the user to develop good habits in a healthy and effective manner.

DRAWINGS

1 is a flowchart of a method for adjusting a task plan of a wearable device according to an embodiment of the present invention;

2 is a specific flowchart of step S130 of a method for adjusting a task plan of a wearable device according to an embodiment of the present invention;

FIG. 3 is a specific flowchart of step S160 of a method for adjusting a task plan of a wearable device according to another embodiment of the present invention;

4 is a schematic structural diagram of a device for adjusting a task plan of a wearable device according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of a sending module 150 in a device planning adjustment apparatus for a wearable device according to an embodiment of the present invention;

6 is a flowchart of a method for adjusting a task plan of a wearable device according to still another embodiment of the present invention;

FIG. 7 is a specific flowchart of step S210 of a method for adjusting a task plan of a wearable device according to still another embodiment of the present invention;

FIG. 8 is a schematic structural diagram of a device for adjusting a task plan of a wearable device according to still another embodiment of the present invention; FIG.

Figure 9 shows a block diagram of a server or wearable device for performing the method according to the invention;

Figure 10 shows a schematic diagram of a memory unit for holding or carrying program code implementing a method in accordance with the present invention.

detailed description

The embodiments of the present invention are described in detail below, and the examples of the embodiments are illustrated in the drawings, wherein the same or similar reference numerals are used to refer to the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the drawings are intended to be illustrative of the invention and are not to be construed as limiting.

The singular forms "a", "an", "the" It is to be understood that the phrase "comprise" or "an" Integers, steps, operations, components, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element. Further, "connected" or "coupled" as used herein may include either a wireless connection or a wireless coupling. The phrase "and/or" used herein includes all or any one and all combinations of one or more of the associated listed.

Those skilled in the art will appreciate that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs, unless otherwise defined. It should also be understood that terms such as those defined in a general dictionary should be understood to have meaning consistent with the meaning in the context of the prior art, and will not be idealized or excessive unless specifically defined as here. The formal meaning is explained.

It will be understood by those skilled in the art that "terminal" and "terminal device" as used herein include both a wireless signal receiver device, a device having only a wireless signal receiver without a transmitting capability, and receiving and transmitting hardware. A device having a receiving and transmitting hardware capable of two-way communication over a two-way communication link. Such devices may include cellular or other communication devices having a single line display or a multi-line display or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service), which may combine voice, data Processing, fax, and/or data communication capabilities; PDA (Personal Digital Assistant), which can include radio frequency receivers, pagers, Internet/Intranet access, web browsers, notepads, calendars, and/or GPS (Global Positioning System (Global Positioning System) receiver; conventional laptop and/or palmtop computer or other device having a conventional laptop and/or palmtop computer or other device that includes and/or includes a radio frequency receiver. As used herein, "terminal", "terminal device" may be portable, transportable, installed in a vehicle (aviation, sea and/or land), or adapted and/or configured to operate locally, and/or Run in any other location on the Earth and/or space in a distributed form. The "terminal" and "terminal device" used herein may also be a communication terminal, an internet terminal, a music/video playing terminal, and may be, for example, a PDA, a MID (Mobile Internet Device), and/or have a music/video playback. Functional mobile phones can also be smart TVs, set-top boxes and other devices.

The wearable device here can be a portable device that is directly worn on the body or integrated into the user's clothes or accessories, not only a single function hardware device, but also through software support and data interaction, cloud interaction. Hardware devices that implement communication and information processing functions can be watches, bracelets, mobile phones, necklaces, and the like.

The wearable device task plan adjustment method in an embodiment of the present invention is as shown in FIG. 1. The task plan adjustment method includes the following steps:

S110: Receive user activity data uploaded by the wearable device, where the user activity data is acquired according to each corresponding task unit in the original task schedule.

In order to provide better and more convenient services to users of wearable devices, pre-defined custom training task plans are usually provided on the wearable device provider's cloud server. These task plans are based on different angles. And the focus of the content design, the user can directly select a habit training task plan from the cloud server according to the initial situation, which is the original task schedule on the wearable device, each task schedule can include A task unit, such as "getting up plan", can also contain multiple task units, such as "getting up plan", "breakfast plan", "morning reading plan" and so on. The user activates the task schedule execution unit on the wearable device, and then the wearable device collects user activity data corresponding to each task unit according to the data instruction on the task schedule, and uploads to the cloud server through setting manner. On the top, the cloud server obtains and performs subsequent data processing. Preferably, the task unit includes a task destination content, a task execution detection start time, and a task execution detection end time, wherein the task execution detection start time is a time at which the execution of the task destination content is started, and the task execution detection end time is a stop detection. The time at which the task purpose content is executed, when the time reaches the task execution detection start time, the sensor related to the task purpose content is started and the data is recorded, and when the time reaches the task execution detection end time, the sensor is turned off and the data is stopped, and the recorded data is recorded. The data is the user activity data. The task unit is the basis on which the user wearable device performs, the user can understand the purpose effect of the task, and the time of the start and end of the specified detection task, or the number of times the task needs to be repeatedly executed and the total time required. Wait. Preferably, the user activity data includes execution time of the user activity, execution location and/or sensor data corresponding to the user activity, mathematically processing the execution time of the user activity to obtain a time data portion of the execution result data, and/or placing the user The execution location of the activity is mathematically processed to obtain a geographic location data portion of the execution result data, and/or the sensor data corresponding to the user activity is mathematically processed to obtain an active content data portion of the execution result data. The execution time and execution location are used to calibrate the basic element data obtained by the user when executing the task unit, and the sensor data is used to identify the execution time and execution location specified by the task unit therein. The execution time of the user activity is used to determine the time when the user actually performs a specific action of a task unit on the task schedule, and may also be used to determine the execution time period of a task unit (specifically according to the type of the task unit), the execution location It can then be used to determine whether the user is in the set position when performing the task unit, such as sleeping on the bed in the bedroom, and if it is detected that the execution place is on the classroom desk, it is not conducive to the development of healthy sleep behavior, then The later revision plan provides a data reference. In addition, the sensor data corresponding to the user activity is used to implement monitoring of the supervised data collection and more complex functions related to the above parameters, such as heart rate sensor data, acceleration sensor data, etc., and these sensors can conveniently detect what the user is in. Physical state to reflect the user's performance of a task unit. It can be known that the execution time of the user activity data is included between the task execution detection start time of the task unit and the task execution detection end time, and the user does not necessarily start to execute the task unit according to the task execution detection start time of the task unit, and often It is later than the detection start time, and in order to ensure sufficient detection of the actual execution of the task by the user, the task unit will arrange sufficient detection time, and even if the task specified detection end time is later than the time when the user actually ends the execution task, it is too early. Or it will be meaningless to perform the task too late. If the sensor data that the task has been executed is not detected within the detection start time and the detection end time, it indicates that the user did not perform the task this time, and will eventually get a corresponding Task sensor data is not executed.

Preferably, the uploading manner of the user activity data is real-time uploading or uploading at a predetermined time after the user activity data is formed. The real-time upload is uploaded to the server immediately after collecting a user activity data. The memory of the user equipment required by this method is small, and the task of data storage is performed by the server, but this method needs to be in a region with better network coverage, otherwise it may be Causes data loss. Another way to upload is to collect the user activity data and upload it in a certain set time. For example, upload it 4 hours after collecting the data. This method has high requirements on the user's equipment, but has low network requirements. After the user's activity data is collected, it is stored in the device, and is uploaded in a centralized time, for example, through a home WIFI.

S120: Perform mathematical processing on the related user activity data in units of task units to determine execution result data of each task unit.

The user activity data obtained by the cloud server is the original activity data collected by the sensor related to the task unit on the wearable device, such as the pulsation frequency, the pulse power degree, the change start time, the duration and the like time data acquired by the heart rate sensor, and the acceleration. The direction, rate, rate change and corresponding time and time acquired by the sensor, as well as the longitude and latitude of the positioning sensor and the time data corresponding to the latitude and longitude, etc., it can be seen that these data often contain the type of task that can be judged. The feature data and the time data corresponding to the feature data, etc., the specific data collection can be judged by a person skilled in the art according to actual needs. The wearable device collects and uploads the raw data in the easiest way, and the data processing work is done by the cloud server, which makes the wearable device hardware lower and easier to implement. The mathematical processing is to apply different preset rules or preset algorithms to the original data from different sensors in the user activity data for data processing, thereby obtaining the execution result data. Since the processing of the above raw data is carried out in a targeted manner, the data collected by different sensors needs to be subjected to different mathematical processing, that is, the data is processed using different data processing rules or algorithms, such as data obtained from the heart rate sensor. The collected pulsation frequency, pulse kinetics and other data are compared with the data sheets under different physical conditions obtained in advance, and it is found that the data shows the state of the user at a certain time, and is sleeping. The state of the walk, or the state of the walk, or the state of the run, etc., and the data obtained by the position sensor is calculated according to the set function to calculate the user's stop position, dwell time, etc., for the mathematical processing of the sensor data. The specific functions or algorithms that arrive can be flexibly selected or programmed by those skilled in the art. Different raw preset data or preset algorithms are applied to the original data of the user activity data for data processing, so as to obtain data processing results corresponding to each sensor, and then according to the needs of each task unit, from a sensor or The data processing results of the plurality of sensors are comprehensively determined, thereby obtaining different execution result data corresponding to each task unit, where the execution result data includes the task unit completion status, the completion time, the completed location, and the like, such as The execution result data of the "get up plan" may be "get up 7:20 bedroom" or fail to detect that the user gets up in the sensor detection interval, that is, "not getting up the bedroom". The execution result data content of each task unit is different, the size is different, and the data format may be different. For example, only the heart rate sensor can be used to get up to judge whether the completion or not, and the feeding and walking may require the cooperation of the heart rate sensor and the acceleration sensor to confirm and distinguish. The execution result data obtained, but ultimately processed, must have a data format corresponding to the task unit on the standard data table, and is suitable for comparison with a standard data table, which can also be pre-programmed by those skilled in the art.

S130: The execution result data corresponding to each task unit is evaluated according to the evaluation reference data corresponding to each corresponding task unit, and the evaluation result data corresponding to the evaluation reference data is determined.

Each task schedule stored in the server contains various corresponding task units. In order to facilitate the evaluation of the execution level of these task units, such as whether execution, degree of completion, quality of completion, etc., it is necessary to pre-define each task unit. By setting one evaluation reference data, comparing the execution result data corresponding to each task unit of the user with the corresponding evaluation reference data, it is possible to determine the evaluation result data corresponding to the selected evaluation reference data. For example, a certain task unit is "getting up plan", the wake-up time as one of the execution result data is "7:20", and the evaluation reference data corresponding to "getting up plan" in the selected task schedule is "7" :00", the information corresponding to the evaluation result data obtained by the comparison is "20 minutes late", of course, those skilled in the art can understand that the digital display form of the information can be "-20min" or other prescribed formats. The form of the data.

S140: Adjust a setting of the task unit corresponding to the evaluation result data in the original task schedule according to a preset condition corresponding to the task unit, and generate a new task schedule.

The evaluation result data obtained through the previous steps will be a data table corresponding to the original task schedule, which can only display the user's execution of the original mission plan, including the degree of completion of the task, The quality of the completion, etc., but it is not yet possible to determine how the user should select a new mission plan after performing the original mission plan. At this point, the server will further analyze the evaluation result data and compare it with the preset conditions corresponding to each task unit. Since there may be only one task unit in the original task schedule selected by the user, for example, an original task schedule is used to specifically train children to get up in the morning, the original schedule includes only the early task unit; there may be multiple A task unit, such as an original task schedule, is used to develop a child's work habits, including an early task unit, a nap task unit, and a night sleep task unit. In either case, at least one evaluation result data is obtained for the execution of the original task schedule. The preset condition corresponding to the task unit is stored in the cloud server, and the preset condition has different hypothetical situations, and the evaluation result data falls within one of the hypothetical situations, and each hypothetical situation Corresponding to a processing result, that is, adjusting the task unit corresponding to the evaluation result data in the original task schedule, adjusting to a more appropriate content specified in advance, and adjusting at least one task unit in the original task schedule. A new task schedule is obtained, so that a more appropriate new task schedule can be determined based on the actual execution of the original task schedule by the user. Preferably, the specific manner of adjusting the setting of the task unit corresponding to the evaluation result data in the original task schedule according to the preset condition corresponding to the task unit is such that the preset condition includes one or more expressions, each The expression includes a set value range and a mapping of the adjustment task unit corresponding to the set value range, when the evaluation result data obtained by executing a task unit in the original task schedule falls within the numerical range of one of the expressions And adjusting the task unit corresponding to the evaluation result data according to the mapping, that is, the hypothetical situation and the related processing manner are included in an expression, wherein the hypothetical situation is specifically set to include the set value range, and the processing manner And a mapping of the adjustment task unit corresponding to the set value range, the mapping points to a specific scheme for modifying the corresponding task unit, when the evaluation result data is within one of the set value ranges , adjusting the task unit corresponding to the evaluation result data according to the mapping corresponding to the set value rangeThe form of the numerical range includes a time range, a time period range, a number of times, and the like. For example, but not limited to, for the task unit "getting up plan", the content of the expression A in the preset condition means "an execution time period of 10 days from the night 20 More than 7 minutes or more, the evaluation reference data for changing the wake-up plan is 7:30", or the content means "more than 7 times in 20 days or more from 10 days in an execution time period, and the evaluation reference data for changing the wake-up plan is 7: 30. At the same time, the reminder time for changing the wake-up plan is 6:50”; the meaning of the expression B in the preset condition means “the execution time period of the wake-up plan is changed from no more than 20 minutes in the 10 days after the execution time period of 10 days. It is 20 days"; the meaning of the expression C in the preset condition is "one execution time period is 10 minutes or more from the night within 10 days, 3 to 7 times, and the evaluation reference data for changing the wake-up plan is 7:15"; the preset condition is also More similar hypothetical situations can be included. If the data content of the evaluation result data obtained within 10 days of an execution time period means "8 times more than 20 minutes later", it can be judged that the evaluation result data falls within the numerical range of the expression A, and should be expressed according to the expression. The mapping in Equation A adjusts the corresponding part of the task unit "Get Up Plan", that is, the evaluation reference data of the wake-up plan is changed to "7:30" or the adjustment reminder time is "6:50"; and if it is obtained in one cycle The data content of the evaluation result data shows that the meaning of the data content is "2 times longer than 20 minutes later", and the task schedule is adjusted according to the expression B; if the evaluation result data obtained in one execution period shows the data content, the meaning is "late" If it is 4 times more than 20 minutes", the value range in C is satisfied, so the task schedule is re-established according to the scheme mapped in Expression C. Some task units do not need to have an execution time period, and the preset conditions corresponding to the task unit do not include data of the execution time period; some task units only need to detect execution without the need for execution time, then The content of the execution time is not included in the preset condition corresponding to the task unit.

Preferably, when the task unit does not express the degree of completion by the time when the task is completed, there is a characteristic that the target is completed once executed, so the preset condition is set as the preset evaluation cumulative number interval, and the mapping of the corresponding task unit is performed. When the cumulative evaluation number for evaluating the execution result data corresponding to each task unit is within the preset evaluation cumulative number interval, the setting of the task unit corresponding to the evaluation result data is adjusted in the original task schedule table, Generate a new task schedule.

Preferably, as shown in FIG. 2, the step of evaluating the execution result data corresponding to each task unit in step S130 includes:

S131: Compare the execution result data and the evaluation reference data according to data block correspondences of each other to obtain comparison amplitude data. There are different task units in the task schedule, and the user obtains different execution result data after execution, and presents different data blocks in the data information, and compares the corresponding data blocks in the evaluation reference data to obtain corresponding The comparison amplitude data, such as the length of time, morning and evening, or the number of executions of the task unit.

S132: Convert the comparison amplitude data into evaluation result data according to the evaluation rule in the evaluation reference data. In the evaluation rules, a certain comparison amplitude data is specified corresponding to a certain evaluation result. For example, when the comparison amplitude data is “late 20 minutes”, the evaluation result data “deduct 1 data unit” is given, and the data unit can take different forms. Such as scores, virtual items, cumulative time, cumulative times, etc.

Preferably, the specific method is to set the evaluation result data into a form of a score, and the evaluation rule is: when the comparison amplitude data satisfies the preset data range, that is, an evaluation score corresponding to the specific preset data range is given, for example, evaluation The default data range in the corresponding data block in the reference data is “15 to 30 minutes late, deduct 1 point; 30 minutes later, deduct 2 points”, then for the comparison amplitude data is “20 minutes late”, you will get "Deduction of 1 point" evaluation score. After obtaining the corresponding evaluation score, setting the preset condition to the evaluation score for measuring the evaluation result data satisfies the preset score, that is, when the evaluation score corresponding to the at least one task unit satisfies the preset corresponding to the task unit When a specific score is set in the condition, the setting of the task unit corresponding to the evaluation score is adjusted to generate a new task schedule. Specifically, the degree of the user completing the task unit is measured by the score. When the evaluation result data meets the corresponding item in the preset condition, the corresponding score is added or subtracted from the task result, and the preset condition is obtained. The cumulative result of the request—the total score obtained by a task unit within a certain period of time. When the total score obtained reaches the preset score, the new task schedule is modified accordingly. The introduction of scores as a medium makes the data processing logic clearer. The number of scores can also be displayed by the virtual appearance of the image, such as safflower, fruit or red flag, which can be selectively displayed on the user wearable device to increase the interest.

The cumulative number of preset conditions and the score system preset conditions can be used alone or in combination.

S150: Push the new task schedule to the wearable device.

When the execution result data is judged according to the preset condition to obtain a new task schedule that satisfies the preset condition, the server immediately pushes the new task schedule to the wearable device.

Preferably, another embodiment of the present invention, as shown in FIG. 3, after the server pushes the new task schedule to the wearable device, further includes a modify authority verification step S160, which specifically includes:

S161: Send the new task schedule to the client.

First, the new task schedule should be sent to the user, so that the user can know the content of the task schedule sent. The user chooses to execute directly, modify the execution or select other task schedules according to his or her own situation.

S162: Acquire a modified task schedule obtained by modifying the new task schedule submitted by the client, and parsing the permission information in the modified task schedule.

When the user decides to partially adopt the content in the task schedule according to his own situation and needs to modify other content, the server obtains the modified result obtained by modifying the obtained new task schedule submitted by the client. The task schedule, and parsing the modified permission information included in the modified task schedule, the permission information is a password or a real-time verification code (a dedicated link is provided by the server, and after the user clicks the selection, the server sends the corresponding digital code to the user, the user After being acquired, it is input into the modification request, and then the server performs the matching degree verification. It can also be verified by using specific biometrics, such as fingerprint information, iris features, and the like.

S163: If the rights information matches the pre-stored rights information, update the stored new task plan table corresponding to the modified task plan table.

The client generates a modified task schedule. At this time, the task schedule is uploaded to the server on the user side, so that the server further updates the new task schedule before the modification, so that the client adopts the task. The schedule matches the server-side task schedule. When the modified permission information meets the permission information pre-existing on the user account on the server, the server receives the modified task schedule table and correspondingly updates the stored new task schedule.

Preferably, in order to meet the user requirements of different age groups and different living backgrounds, the task schedule execution interface is more interesting, and the task schedule may include the content of the user interface skin theme information, and the user interface is specifically used to perform the corresponding task. The user interface associated with the scheduled tasks in the schedule. For example, in the evening time, choose the appearance of the starry sky, and choose the appearance of the city landscape or the sports field with sunlight during the day.

In accordance with the foregoing method, based on the modular thinking of the computer system, an embodiment of the present invention provides a device for adjusting a task plan of a wearable device, as shown in FIG. 4, including:

The receiving module 110 is configured to receive user activity data uploaded by the wearable device, where the user activity data is acquired according to each corresponding task unit in the original task schedule.

The user activates the task schedule execution unit on the wearable device, and then the wearable device collects user activity data corresponding to each task unit according to the data instruction on the task schedule, and uploads to the cloud server through setting manner. The receiving module 110 of the cloud server acquires and provides the other module for corresponding subsequent data processing. The user activity data includes the execution time of the user activity, the execution location, and/or the sensor data corresponding to the user activity. Those skilled in the art can understand that the user data may further include basic information such as user ID information and device hardware version information.

The conversion module 120 is configured to perform mathematical processing on the related user activity data in units of the task unit to determine execution result data of each task unit.

The user activity data acquired by the cloud server receiving module 110 is often simple time data, task unit type data, and the like. However, only these simple raw data cannot be used as the cloud server for analysis and judgment, so mathematical processing is required, and the conversion module 120 is required. These processes are expanded according to different task units, and the conversion is determined as the execution result data of each task unit. The execution result data has a fixed data format and is suitable for comparison with the standard data table.

The evaluation module 130 is configured to evaluate execution result data corresponding to each task unit according to the evaluation reference data corresponding to each corresponding task unit, and determine evaluation result data corresponding to the evaluation reference data.

Each task schedule stored in the server contains various corresponding task units. In order to facilitate the evaluation of the execution level of these task units, such as: whether to execute, how complete, how to complete the quality, etc., each task unit must be An evaluation reference data is set in advance, and the evaluation module 130 compares the execution result data corresponding to each task unit of the user with the corresponding evaluation reference data, and determines that the corresponding evaluation reference data is corresponding. Evaluation result data.

The update module 140 is configured to adjust a setting of the task unit corresponding to the evaluation result data in the original task schedule according to a preset condition corresponding to the task unit, to generate a new task schedule.

The update module 140 of the server further analyzes the evaluation result data, compares with the preset conditions corresponding to each task unit, and corresponds to the evaluation result data in the original task schedule table when the assumptions in the corresponding preset conditions are met. The task unit is adjusted and adjusted to a more appropriate content specified in advance, and different hypothetical situations correspond to different adjustment contents, so that a more appropriate new task schedule can be determined according to the actual execution of the original task schedule by the user.

The sending module 150 is configured to push the new task schedule to the wearable device.

When the execution result data is judged according to the preset condition to obtain a new task schedule that satisfies the preset condition, the sending module 150 of the server immediately pushes the new task schedule to the wearable device.

Preferably, as shown in FIG. 5, the sending module 150 in an embodiment of the present invention includes:

The sending unit 151 is configured to send the new task schedule to the client. First, the sending unit 151 sends a new task schedule to the user, so that the user knows the content of the sent task schedule, and the user selects to execute directly, modify the execution, or select another task schedule to execute according to his or her own situation.

The parsing unit 152 is configured to obtain a task schedule modification request submitted by the client, and parse the modification authority information included in the modification request. When the user decides to partially adopt the content in the task schedule according to his own situation and needs to modify other content, the server obtains a task schedule modification request submitted by the client, and the modification request includes the modification authority information, The parsing unit 152 parses, for example, a verification password, a real-time verification code, or a specific biometric.

The determining unit 153 sends the permission modification confirmation information to the client if the modification authority information matches the pre-stored authority information. When the determining unit 153 determines that the modified authority information meets the authority information pre-existing on the user account on the server, the server develops a task schedule modification authority to the user, and sends the permission modification confirmation information to the client.

The updating unit 154 acquires the modified task schedule of the client, and updates the stored new task schedule correspondingly. The user enters the modification interface of the task schedule, and makes corresponding changes to the task schedule to obtain a modified task schedule. At this time, the task schedule is uploaded to the server for the update in the server. The unit 154 further updates the new task schedule table before the modification, so that the task schedule adopted by the client matches the task schedule of the server.

The present invention also provides a wearable device task plan adjustment server, including a first processor, which is used to execute the wearable device task plan adjustment method of the above embodiment. If the user activity data uploaded by the wearable device is received by the receiving module 110, the user activity data is acquired according to each corresponding task unit in the original task schedule. The user activity data obtained by the receiving module 110 is mathematically processed by the conversion module 120 in units of the task unit to determine execution result data of each task unit. Further, based on the evaluation reference data corresponding to each corresponding task unit, the evaluation result data obtained by the conversion module 120 is evaluated by the evaluation module 130, and the evaluation result data corresponding to the evaluation reference data is determined. The setting of the task unit corresponding to the evaluation result data is adjusted in the original task schedule by the update module 140 according to a preset condition corresponding to each task unit, and a new task schedule is generated. Finally, the new task schedule is pushed to the wearable device by the sending module 150.

The wearable device task plan adjustment method provided in still another embodiment of the present invention, as shown in FIG. 6, includes the following steps:

S210: Set a local task plan according to each task unit in the original task schedule received from the cloud server.

The user selects the task schedule provided on the cloud server at the user end, and after determining and downloading from the above, there is an original task schedule, and the user sets the unit to be executed according to the task units in the original task schedule. Mission planning, such as controlling alarm clocks, related sensors, etc.

S220: execute a planning instruction specified by the task unit at a time specified by each task unit, and acquire corresponding user activity data.

According to the time node assigned to each task unit by the local machine, the related component is controlled, the planning instruction specified by the task unit is executed at the specified time, and the corresponding user activity data is acquired. For example, the alarm starts to sound the alarm at the "7:00" specified by the "Get Up Program", and records the time when the alarm is turned off. The geographical location sensor obtains the position of the local machine, the heart rate sensor and the acceleration sensor determine the user's activity status (the state of getting up, or Is a sleep state). Preferably, the task unit includes a task purpose content, a task execution detection start instruction, and a task execution detection end instruction, the task execution detection start instruction is an instruction to start the detection task purpose content execution, and the task execution detection end instruction is to stop detecting the task purpose content. Executed instructions. Further preferably, the task execution prompt instruction is added to the task unit, so that the prompt function module of the device is turned on to remind the user to perform the task purpose content, for example, the time for the task execution detection start instruction is “7:00”, at “6: 55" sets a corresponding task execution prompt instruction to let the device reminder function work to remind the user to prepare to execute the content of the task unit, and more fully guarantee the completion of the task.

Preferably, the local task plan includes a task prompt time, a sensor open time, and a sensor close time, wherein the task prompt time is set according to the task purpose content in advance, and the sensor open time is set according to the task execution detection start instruction. The sensor off time is set according to the task execution detection end command. The instructions described above are provided for execution by the device, and the native task plan content described herein can be provided to the user for reading, for the purpose of performing the guidance and modifying the reference.

Preferably, the user activity data is obtained by a sensor specified by the planning instruction, including the execution time of the user activity, the execution location, and/or sensor data corresponding to the user activity, to determine that the corresponding task unit is executed and The resulting result data.

S230: Upload the user activity data to the cloud server for formulating corresponding evaluation result information and/or a new task schedule.

The machine uploads the collected user activity data to the cloud server, and the server analyzes and processes the user activity data and formulates the evaluation result information, or obtains a new task schedule. The contents of these user activity data have been mentioned above and will not be described here. There are two ways to upload user activity data. One method is to upload to a server immediately after collecting a user activity data. The user equipment required by this method has small memory, and the task of data storage is performed by the server, but this method needs to be Areas with good network coverage may cause data loss. Another way to upload user activity data is to upload the data in a centralized manner after a certain set time. This method has high requirements on the user's device, but has low network requirements, and stores the user's activity data after collecting it. In the device, the time to be set is to be uploaded in a centralized manner, for example, through a home WIFI.

Preferably, the uploading is performed when the device detects that the network signal meets the preset signal strength. Whether it is a network signal provided by a mobile communication network provider or an indoor WIFI signal, there is a problem of signal strength. The mobile communication device is often in a mobile state, and the signal strength is different in different places. If the signal is weak, the upload data may fail, so Select the network signal detected by the system to meet a certain signal strength, so as to further ensure the smooth progress of the uploaded data.

S240: Acquire the evaluation result information and/or the new task schedule of the cloud server according to the user activity data, and display the result information and/or replace the original task schedule table accordingly.

After the cloud server completes the data processing and obtains the evaluation result, the user can know the user's completion status of the activity task. If some evaluation media such as a score is used, the user's score can be known, or a more vivid representation manner can be used. For example, get a virtual gift as a reward (small red flower, small red flag, etc.). Or get a new task schedule that is more in line with the actual implementation, and appropriately improve or reduce the difficulty of the mission plan according to the actual performance of the user, and try to carry out the customary training step by step. The display result information and the replacement original task schedule can be performed separately or in combination.

Preferably, the step of displaying the result information comprises: matching the evaluation result information with a specific virtual item; displaying the virtual item. The virtual items are small red flowers, small red flags, small goldfish, etc., and different levels of evaluation result information correspond to different numbers of virtual items, so that the device interface is more beautiful, and the task execution is more interesting.

Preferably, as shown in FIG. 7, for step S210, the step of setting the local task plan further includes:

S211: Confirm the task schedule to modify the authority verification information.

When you need to modify the acquired task schedule, enter the edit permission verification information before editing, so that the modification matches the corresponding account on the server.

S212: Modify a specific task unit in the original task schedule. Modifying the task schedule downloaded from the server according to the user's own needs, you can modify the parameters in some of the task units, or delete the task unit or add task details.

S213: Set a local task plan according to each task unit in the modified task schedule, and upload the modified task schedule to the server.

After modifying the task schedule, you need to confirm the execution. The device is equipped with the task plan that the machine needs to perform according to the settings of each task unit in the task schedule. At the same time, the modified task schedule needs to be uploaded to the server to make the server and the machine. The task schedules used by the user are consistent so as to correspondingly display the evaluation result information obtained by the user performing the task unit and/or the replacement of the updated version of the task schedule.

In accordance with the foregoing method, another embodiment of the present invention provides a device for adjusting a task plan of a wearable device, as shown in FIG.

The receiving module 210 is configured to set a local task plan according to each task unit in the original task schedule received from the cloud server. The user selects the task schedule provided on the cloud server at the user end, and after the receiving module 210 determines and downloads from the above, the original task schedule is obtained, and the user sets the local machine according to each task unit in the original task schedule. The mission plan to be executed, such as controlling the alarm clock, related sensors, etc.

The execution module 220 executes the planning instruction specified by the task unit at a time specified by each task unit, and acquires corresponding user activity data. The execution module 220 controls the related components according to the time node assigned to each task unit by the local machine, executes the planning instruction specified by the task unit at a specified time, and acquires corresponding user activity data.

The uploading module 230 uploads the user activity data to the cloud server. The user uploads the collected user activity data to the cloud server through the uploading module 230. There are two methods for uploading, and one is uploaded to the server immediately after collecting a user activity data, and the user equipment required by the method is small. The task of data storage is left to the server, but this method needs to be in a region with good network coverage, otherwise data loss may occur. Another way to upload user activity data is to upload the data in a centralized manner after a certain set time. This method has high requirements on the user's device, but has low network requirements, and stores the user's activity data after collecting it. In the device, the time to be set is to be uploaded in a centralized manner, for example, through a home WIFI.

The obtaining module 240 is configured to obtain the evaluation result information and/or the new task schedule of the cloud server according to the user activity data, and display the result information and/or replace the original task schedule table accordingly. After the cloud server completes the data processing, the evaluation result is obtained, and the user can know the completion status of the activity task by the user through the obtaining module 240. If some evaluation media such as a score is used, the user's score can be known, or the user can be used. The representation of the image, such as obtaining a virtual gift as a reward (small red flower, small red flag, etc.). Or, after obtaining a new task schedule that is more in line with the actual implementation, the acquisition module 240 replaces the original task schedule table, and appropriately raises or reduces the difficulty of the task plan according to the actual performance of the user, and tries to perform the step-by-step habit cultivation. The display result information and the replacement original task schedule can be performed separately or in combination.

The present invention provides a wearable device according to the method described in another embodiment, including a second processor, which is configured to perform a wearable device task plan adjustment method according to another embodiment. The receiving module 210 sets a local task plan according to each task unit in the original task schedule received from the cloud server. The execution module 220 executes the planning instruction specified by the task unit at the time specified by each task unit, acquires corresponding user activity data, and uploads the user activity data to the cloud server through the uploading module 230. After the server processes the data to obtain a result, the obtaining module 240 acquires the evaluation result information of the cloud server according to the user activity data and/or a new task schedule, and displays the result information and/or replaces the original task plan. table. The final implementation of the task schedule is a step-by-step update.

To facilitate an understanding of the implementation of the present invention by those skilled in the art, the following examples describe how to complete the adjustment of the wearable device mission plan in an actual scenario.

The wearable device task plan adjustment server provides a variety of habit development task plans based on various age groups, various family situations or psychological research results on a certain interface, such as "getting up plan", "napping" Plan, "Good Night Plan", "Reading Plan" and / or "Sport Plan" and so on. The server detects that a certain user determines to select a certain task plan, and then detects that the user wishes to modify the application of the task plan and submits the modified task schedule, and the server verifies that the user's modification permission is passed, and is received and updated as The revised mission schedule. The user modifies the task plan selected by the user on the wearable device or other client, and submits it to the server after completion. When the server confirms that the task plan performed by the user on the wearable device includes three task units such as "get up plan", "napping plan" and "night plan", the training plan has a time period of 10 days, and the execution place is at home, In the kindergarten and at home, the detection time of each task unit in the training plan is “7:30”, “13:00” and “21:00” respectively. Parents can inform their children in advance at this time or The task unit is executed at a certain time before this time point, and the reminder can also be set on the wearable device, for example, the reminder time option is added to the task schedule table, and the reminder time corresponding to the previous text is “7:20” respectively. , "12:50" and "20:50". According to the method agreed in advance, the server obtains the user activity data transmitted on the wearable device. For example, the execution time of the above three task units in a certain day is "8:00", "13:10", "21:30". The server converts it into execution result data according to certain rules. After the execution period of the task in the task schedule, the result data summary statistics are executed and compared with the predetermined preset conditions, and the task unit "gets up plan" For example, the user has 7 wake-up times exceeding the evaluation baseline data in the task schedule for 20 minutes, which is equivalent to modifying the evaluation reference data in the task unit to "7:40" or modifying the reminder time in the task unit to "7:10". The condition, so the server launches a new task schedule that is appropriate for the actual execution of the user and pushes the new task schedule to the appropriate user.

Of course, it can also be a process like this:

A user (a parent) first selects the task schedule that is closest to the user of the browsing (the parent's child) and downloads it to the wearable device that the user is using by browsing the task plan provided on the server. On the other hand, if there is a need, the user wants to make more adaptive changes to certain information in the task schedule. Click on the modify option. After opening, there will be a link to verify the permission. The parent enters the password and password. Linking and modifying a task schedule, and modifying to form a new task schedule, the user executes according to the new task schedule, and the server also displays the new task being executed under the user account. Schedules. There are three habits in the mission plan, namely “Getting Up Program”, “Healthy Napping” and “Good Night Plan”. The training period is 10 days, and the execution place is at home, kindergarten and home. The start detection time of each task unit execution is “7:30”, “13:00” and “21:00” (parents can inform their children in advance at this point in time or before this point in time) The task unit can be executed at a certain time, and the reminder can also be set on the wearable device. For example, the reminder time option is added to each task unit of the task schedule, and the reminder time corresponding to the previous text is “7:20”, respectively. 12:50" and "20:50"), the end detection time is "8:30", "14:00", "22:00". The wearable device starts to collect data according to the above-mentioned time points, and selects to automatically upload the collected data to the server at 22:00 every day. After a planned time period, that is, 10 days later, the wearable device receives the data. The evaluation information sent by the server shows the execution result of the user's selected task plan and provides the updated task schedule. If the user finishes very well, the extended training plan period can be used to continue the execution. You can modify the options and choose a more scientific and more scientific development plan to continue. If the user can not achieve the content specified in each task unit and reach the certain standard set by the original, such as more than 7 times of getting up in the morning and evening for 20 minutes, the detection time of each task unit execution is updated to "7:40". Or update the reminder time in the task schedule to "7:10", and update the relevant content to the wearable device and execute it in the new execution cycle.

FIG. 9 illustrates a server or a wearable device (hereinafter referred to as a server or a wearable device as a device) in a wearable device task plan adjustment method according to the present invention. The device conventionally includes a processor 1010 and a computer program product or computer readable medium in the form of a memory 1020. The memory 1020 may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), an EPROM, a hard disk, or a ROM. The memory 1020 has a memory space 1030 for executing program code 1031 of any of the above method steps. For example, storage space 1030 for program code may include various program code 1031 for implementing various steps in the above methods, respectively. The program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such a computer program product is typically a portable or fixed storage unit as described with reference to FIG. The storage unit may have a storage section or a storage space or the like arranged similarly to the storage 1020 in FIG. The program code can be compressed, for example, in an appropriate form. Typically, the storage unit comprises program code 1031' for performing the steps of the method according to the invention, ie code that can be read by, for example, a processor such as 1010, which when executed by the device causes the device to perform the above Each step in the described method.

Those skilled in the art will appreciate that each block of the block diagrams and/or block diagrams and/or flow diagrams and combinations of blocks in the block diagrams and/or block diagrams and/or flow diagrams can be implemented by computer program instructions. . Those skilled in the art will appreciate that these computer program instructions can be implemented by a general purpose computer, a professional computer, or a processor of other programmable data processing methods, such that the processor is executed by a computer or other programmable data processing method. The blocks of the disclosed structure and/or block diagrams and/or flow diagrams or blocks specified in the various blocks.

Those skilled in the art can understand that the steps, measures, and solutions in the various operations, methods, and processes that have been discussed in the present invention may be alternated, changed, combined, or deleted. Further, other steps, measures, and schemes of the various operations, methods, and processes that have been discussed in the present invention may be alternated, modified, rearranged, decomposed, combined, or deleted. Further, the steps, measures, and solutions in the prior art having various operations, methods, and processes disclosed in the present invention may also be alternated, changed, rearranged, decomposed, combined, or deleted.

The above is only a part of the embodiments of the present invention, and it should be noted that those skilled in the art can also make several improvements and retouchings without departing from the principles of the present invention. It should be considered as the scope of protection of the present invention.

Claims (30)

1. A method for adjusting a wearable device task plan, comprising the following steps:

   Receiving user activity data uploaded by the wearable device, where the user activity data is acquired according to each corresponding task unit in the original task schedule;

   Performing mathematical processing on the relevant user activity data in units of the task unit to determine execution result data of each task unit;

   Performing evaluation result data corresponding to each task unit according to the evaluation reference data corresponding to each corresponding task unit, and determining evaluation result data corresponding to the evaluation reference data;

   Adjusting a setting of a task unit corresponding to the evaluation result data in the original task schedule according to a preset condition corresponding to the task unit, and generating a new task schedule;

   Push the new task schedule to the wearable device.
2. The wearable device task plan adjustment method according to claim 1, wherein the setting of the task unit corresponding to the evaluation result data is adjusted in the original task schedule according to the preset condition corresponding to the task unit The steps specifically include:

   The preset condition includes one or more expressions, each expression including a set value range and a mapping of an adjustment task unit corresponding to the set value range, when the evaluation result data is in the preset condition Within the set value range of one of the expressions, the task unit corresponding to the evaluation result data is adjusted in accordance with the map.
3. The wearable device task plan adjustment method according to claim 2, wherein the set value range is a preset evaluation cumulative number interval, and the mapping of the corresponding task unit is corresponding to each task unit. The cumulative evaluation number of the execution result data evaluation is within the preset evaluation cumulative number interval, and the setting of the task unit corresponding to the evaluation result data is adjusted in the original task schedule to generate a new task schedule.
4. The method of claim 2, wherein the step of evaluating the execution result data corresponding to each task unit comprises:

   Comparing the execution result data and the evaluation reference data according to each other's data block correspondence to obtain comparison amplitude data;

   The comparison amplitude data is converted into evaluation result data according to an evaluation rule in the evaluation reference data.
5. The wearable device task plan adjustment method according to claim 4, wherein the evaluation rule is as follows: when the comparison amplitude data satisfies a specific preset data range, that is, the specific preset data range is given Corresponding evaluation score;

   When the evaluation score corresponding to the at least one of the task units satisfies the specific score set in the preset condition corresponding to the task unit, the setting of the task unit corresponding to the evaluation score is adjusted to generate a new task schedule.
6. The wearable device task plan adjustment method according to claim 1, wherein the task unit includes task purpose content, task execution detection start time, task execution detection end time, and the task execution detection start time is start detection. The time at which the content of the task object is executed, the task execution detection end time is a time at which the execution of the content of the task object is stopped; the steps of acquiring the user activity data are as follows:

   Reaching the task execution detection start time, starting the sensor related to the task purpose content and recording the data;

   When the task execution detection end time is reached, the sensor is turned off and the data is stopped, and the recorded data is the user activity data.
7. The wearable device task plan adjustment method according to claim 6, wherein the user activity data includes an execution time of a user activity, an execution location, and/or sensor data corresponding to the user activity, and the user activity is performed. The execution time is mathematically processed to obtain the time data portion of the execution result data, and/or

   Performing mathematical processing on the execution location of the user activity to obtain a geographic location data portion of the execution result data, and/or

   The sensor data corresponding to the user activity is mathematically processed to obtain an active content data portion of the execution result data.
8. The wearable device task plan adjustment method according to claim 7, wherein the execution time of the user activity data is included between a task execution detection start time of the task unit and a task execution detection end time.
9. The wearable device task plan adjustment method according to claim 1, wherein in the process of performing the mathematical process, different preset rules are applied to the original data derived from different sensors in the user activity data or The preset algorithm performs data processing processing to obtain the execution result data.
10. The wearable device task plan adjustment method according to claim 1, wherein the step of pushing the new task schedule to the wearable device further comprises:

    Sending the new task schedule to the client;

    Obtaining a modified task schedule obtained by modifying the new task schedule submitted by the client, and parsing the permission information in the modified task schedule;

    If the rights information matches the pre-stored rights information, the saved new task plan table is updated corresponding to the modified task plan table.
11. The wearable device task plan adjustment method according to claim 10, wherein the authority information is at least one of a password, a real-time verification code, or a specific biometric.
12. The method for adjusting a task plan of a wearable device according to claim 1, wherein the uploading method of the user activity data is real-time uploading, or

    Uploaded at a predetermined time after the user activity data is formed.
13. The wearable device task plan adjustment method according to claim 1, wherein the task schedule further includes user interface skin theme information, wherein the user interface is related to executing a scheduled task in the task schedule User Interface.
14. A method for adjusting a wearable device task plan, comprising the following steps:

    Setting a local task plan based on each task unit in the original task schedule received from the cloud server;

    Execute the planning instruction specified by the task unit at a time specified by each task unit, and obtain corresponding user activity data;

    Uploading the user activity data to the cloud server for formulating corresponding evaluation result information and/or a new task schedule;

    Obtaining the evaluation result information and/or the new task schedule of the cloud server according to the user activity data, respectively displaying the evaluation result information and/or replacing the original task schedule.
15. The wearable device task plan adjustment method according to claim 14, wherein the task unit includes a task purpose content, a task execution detection start instruction, and a task execution detection end instruction, and the task execution detection start instruction is to start detection. And the task execution detection end instruction is an instruction to stop detecting the execution of the task destination content.
16. The method of claim 15 , wherein the task unit further comprises a task execution prompt instruction, wherein the prompt function of the task execution prompting instruction turns on the prompt function module of the device to remind the user to perform the task purpose. content.
17. The wearable device task plan adjustment method according to claim 15, wherein the local task plan includes a task prompt time, a sensor open time, and a sensor close time, and the task prompt time is advanced according to the task purpose content. The predetermined time setting, the sensor on time is set according to a task execution detection start command, and the sensor off time is set according to the task execution detection end instruction.
18. The wearable device task plan adjustment method according to claim 14, wherein the user activity data is obtained by a sensor specified by the planning instruction, including an execution time of a user activity, an execution location, and/or a user activity Corresponding sensor data is used to determine corresponding execution result data that the task unit is executed and obtained accordingly.
19. The method for adjusting a task plan of a wearable device according to claim 14, wherein the uploading method of the user activity data is real-time uploading, or

    Uploaded at a predetermined time after the user activity data is formed.
20. The wearable device task plan adjustment method according to claim 19, wherein the uploading is performed when detecting that the network signal satisfies a preset signal strength.
21. The wearable device task plan adjustment method according to claim 14, wherein the displaying the result information comprises:

    Corresponding to the evaluation result information and the specific virtual item;

    The virtual item is displayed.
22. The wearable device task plan adjustment method according to claim 14, wherein

    The step of setting a local task plan according to each task unit in the original task schedule received from the cloud server further includes:

    Confirm the task schedule to modify the authority verification information;

    Modifying specific task units in the original task schedule;

    The local task plan is set according to each task unit in the modified task schedule, and the modified task schedule is uploaded to the server.
23. A wearable device mission planning adjustment device includes:

    At least one processor;

    And at least one memory communicatively coupled to the at least one processor; the at least one memory comprising processor-executable instructions when the processor-executable instructions are executed by the at least one processor Causing the device to perform at least the following operations:

    Receiving user activity data corresponding to each task unit acquired and uploaded by the wearable device according to the original task schedule;

    Performing mathematical processing on the relevant user activity data in units of the task unit to determine execution result data of each task unit;

    Performing evaluation result data corresponding to each task unit according to the evaluation reference data corresponding to each corresponding task unit, and determining evaluation result data corresponding to the evaluation reference data;

    Adjusting a setting of a task unit corresponding to the evaluation result data in the original task schedule according to a preset condition corresponding to the task unit, and generating a new task schedule;

    Push the new task schedule to the wearable device.
24. The device of claim 23, wherein the operation of pushing the new task schedule to the wearable device comprises:

    Sending the new task schedule to the client;

    Obtaining a modified task schedule obtained by modifying the new task schedule submitted by the client, and parsing the permission information in the modified task schedule;

    If the rights information matches the pre-stored rights information, the saved new task plan table is updated corresponding to the modified task plan table.
25. A wearable device mission planning adjustment device includes:

    At least one processor;

    And at least one memory communicatively coupled to the at least one processor; the at least one memory comprising processor-executable instructions when the processor-executable instructions are executed by the at least one processor Causing the device to perform at least the following operations:

    Setting a local task plan based on each task unit in the original task schedule received from the cloud server;

    Execute the planning instruction specified by the task unit at a time specified by each task unit, and obtain corresponding user activity data;

    Uploading the user activity data to the cloud server;

    Acquiring the cloud server to display the result information and/or replace the original task schedule table according to the evaluation result information of the user activity data and/or the new task schedule.
26. A server includes a first processor, and the first processor is configured to perform the wearable device task plan adjustment method according to any one of claims 1 to 13.
27. A wearable device comprising a second processor, the second processor for performing the wearable device task plan adjustment method according to claims 14-22.
28. A computer program comprising computer readable code, when the server runs the computer readable code, causing the method of any of claims 1-13 to be performed.
29. A computer program comprising computer readable code, when the wearable device runs the computer readable code, causing the method of any one of claims 14-22 to be performed.
30. A computer readable medium storing the computer program of claim 28 or 29.

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