A smart bedding system and its scheduling method

Abstract

This application discloses a smart bedding system and its scheduling method, applied in the field of smart bedding control technology. The method includes: acquiring various actions to be performed by the smart bedding system; for each action, determining a disturbance value reflecting the degree of disturbance to the user based on the action's execution information; determining a disturbance threshold for a single time window; prioritizing the actions to be performed; and selecting actions to be performed in the next time window according to a selection rule that prioritizes high-priority actions and ensures the total disturbance value of the selected actions does not exceed the disturbance threshold. Applying this solution allows for unified scheduling of actions while meeting the functional objectives of the smart bedding system, reducing the disturbance to the user's sleep and rest.

Description

Technical Field

[0001] This invention relates to the field of intelligent bedding management technology, and in particular to an intelligent bedding system and its scheduling method. Background Technology

[0002] Current smart bedding often needs to perform multiple active actions, such as adjusting airbag pressure based on the user's sleeping posture or set goals, adjusting the bed frame angle, providing gentle vibration prompts, turning on the night light, or issuing voice reminders. Each of these actions has a clear function and purpose, but the current control strategy involves different actuators operating according to their own local rules, lacking unified scheduling. That is, the control strategy only focuses on whether each function is achieved, such as whether the pressure is controlled properly or the angle is reached, without quantitative constraints on whether the actions themselves disturb the user. Therefore, it is easy for multiple actions to be executed simultaneously, resulting in users often experiencing disturbances due to noise, sudden changes, vibrations, or frequent shifts during actual use, thus affecting the user experience, especially the continuity and comfort of sleep.

[0003] In conclusion, how to reduce the disturbance of movements to users' sleep and rest while meeting the functional goals of smart bedding is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a smart bedding system and its scheduling method, so as to reduce the disturbance of actions to the user's sleep and rest while meeting the functional objectives of the smart bedding system.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] In a first aspect, the present invention provides a method for scheduling the actions of intelligent bedding, comprising:

[0007] Obtain the various actions to be performed by the smart bedding;

[0008] For each action, based on the execution information of the action, a disturbance value is determined to reflect the degree of disturbance the action causes to the user;

[0009] Determine the disturbance threshold for a single time window;

[0010] Prioritize the various actions to be performed;

[0011] According to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, and the selected actions are executed in the next time window.

[0012] In one implementation, for each action, based on the execution information of the action, a disturbance value reflecting the degree of disturbance to the user is determined, including:

[0013] For each action, based on the action type in the action's execution information, determine the executor that performs the action, and obtain the executor's base disturbance value;

[0014] Based on the execution information of the action, the superposition value of the action is determined;

[0015] The base disturbance value is added to the superimposed value to obtain the disturbance value determined to reflect the degree of disturbance to the user caused by the action.

[0016] The execution information includes one or more of the following: action type, action start value, action target value, action duration, upper limit of action slope change, action frequency, and action noise level.

[0017] In one implementation, determining the disturbance threshold for a single time window includes:

[0018] Get the configuration value of the disturbance threshold;

[0019] Determine whether the disturbance threshold is set to a fixed value;

[0020] If so, the configuration value will be used as the disturbance threshold for a single time window;

[0021] If not, the configuration value is adjusted based on the current time period and / or the current mode setting and / or the current user status, and the adjusted value is used as the disturbance threshold for a single time window.

[0022] In one implementation, the method further includes: setting a maximum number of executions of each action within the same window as a local action constraint;

[0023] Accordingly, following the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, including:

[0024] According to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, and the selected actions to be executed in the next time window conform to the local action constraints.

[0025] In one implementation, prioritizing the various actions to be performed includes:

[0026] For any action to be performed, the total priority score of the action is obtained based on the initial priority score, urgency score, and safety score of the action;

[0027] The actions to be executed are prioritized according to their total priority scores, from highest to lowest.

[0028] In one implementation, it further includes:

[0029] For the actions selected from the pending actions to be executed in the next time window, determine whether there are any concurrent conflicts between the actions;

[0030] If not, the selected actions will be executed in the next time window;

[0031] If so, for each group of actions that causes a concurrent conflict, if the group of actions supports off-peak execution in the next time window, the group of actions will be executed off-peak in the next time window. If the group of actions does not support off-peak execution in the next time window, only some of the actions in the group will be retained, so that the retained actions in the group do not have concurrent conflicts or that the retained actions in the group support off-peak execution in the next time window.

[0032] In one implementation, it further includes:

[0033] For any action selected from the various actions to be executed, determine whether the action meets the shaping conditions;

[0034] If so, the action is shaped to reduce the degree of disruption to the user during the execution of the action;

[0035] The shaping methods include: limiting the maximum slope of the movement, limiting the single change amplitude of the movement, breaking the complete movement into multiple step movements and setting the interval between the step movements, using a gradual curve to replace the abrupt curve, and reducing the intensity and duration of the movement, or one or more of these.

[0036] In one implementation, it further includes:

[0037] When a user disturbance is detected, pre-defined corrective measures are executed;

[0038] The corrective measures include: reducing the action slope of the remaining pending actions, reducing the action amplitude of the remaining pending actions, extending the waiting time for the next action, and suspending one or more of the low-priority actions.

[0039] In one implementation, it further includes:

[0040] When an abnormality is detected in the smart bedding and / or the user activates the night silent mode, the preset degradation measures are executed;

[0041] The degradation measures include: suspending comfort-enhancing actions, reducing the frequency of preset high-noise actions, setting a limit on the number of actuators performing simultaneous actions, and replacing voice prompts with one or more light prompts.

[0042] Secondly, the present invention provides a smart bedding device, comprising: a smart bedding device body, a memory, and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the steps of the smart bedding device scheduling method as described above.

[0043] By applying the technical solution provided in this invention, various actions to be performed by the smart bedding can be obtained. Instead of immediately executing these actions, a disturbance value is determined for each action based on its execution information, reflecting the degree of disturbance to the user. In other words, for each action, the disturbance value quantifies its impact on the user, allowing actions executed by different actuators to be included in the same scheduling framework. This enables unified scheduling of various actions, avoiding excessive disturbance to the user. Furthermore, considering the varying importance and urgency of different actions, this solution prioritizes the actions to be performed, ensuring that higher-priority actions are executed first. Then, based on the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed a disturbance threshold, actions are selected from the remaining actions to be performed for execution in the next time window. This means that when these selected actions are executed in the next time window, their total disturbance value does not exceed the disturbance threshold, thus improving the user experience and reducing disturbance to the user's sleep and rest.

[0044] In summary, the proposed solution not only meets the functional objectives of smart bedding but also achieves unified scheduling of actions, reducing the disturbance of actions to users' sleep and rest. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1A flowchart illustrating the implementation of a motion scheduling method for intelligent bedding according to a specific embodiment of the present invention;

[0047] Figure 2 A schematic diagram of the connection structure between the memory and processor of a smart bedding device provided in a specific embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the structure of a computer-readable storage medium according to the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0050] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating the implementation of a motion scheduling method for smart bedding according to a specific embodiment of the present invention. The motion scheduling method for smart bedding may include the following steps:

[0052] Step S101: Obtain the various actions to be performed by the smart bedding.

[0053] The smart bedding described in this application can be a smart mattress, smart bed, or nursing bed, etc., capable of realizing one or more functions such as airbag pressure regulation, bed frame adjustment, vibration alerts, light reminders, and voice prompts. Compared with traditional control and scheduling methods, this application does not only take the completion of an action as the sole objective, but also incorporates the actions performed by different actuators into a unified scheduling framework. It further considers how the action is completed, whether it will cause significant disturbance, whether it needs to give way to other actions, and whether it should be delayed or downgraded in the current time period, so that the solution of this application can effectively improve the user experience.

[0054] The actions to be executed can include user-preset actions or actions automatically generated by the system program. For example, the system program may be set to perform functions such as timed pressure adjustment, automatic sleep posture adjustment, nursing reminders, safety prompts, equipment protection actions, and receiving remote control commands. These functions can generate one or more actions to be executed when the corresponding trigger conditions are met.

[0055] The smart bedding can acquire one or more actions to be performed, usually multiple, and a list of actions to be performed can be generated according to each action.

[0056] Step S102: For each action, based on the action's execution information, determine a disturbance value that reflects the degree of disturbance the action causes to the user.

[0057] In this application, to enable different types of actions to be scheduled within the same framework, an disturbance value is used to quantify the degree of disturbance an action causes to the user. Specifically, based on the action's execution information, a disturbance value is determined to reflect the degree of disturbance the action causes to the user. Of course, the specific parameters included in the execution information can be set and adjusted according to actual needs, as long as they can effectively measure the disturbance value of the action.

[0058] For example, in one specific embodiment of the present invention, step S102 may specifically include:

[0059] For each action, based on the action type in the action's execution information, determine the executor that performs the action and obtain the executor's basic disturbance value;

[0060] Based on the execution information of the actions, the cumulative value of the actions is determined;

[0061] The base disturbance value and the superimposed value are added together to form the disturbance value determined to reflect the degree of disturbance to the user by the action;

[0062] The execution information includes one or more of the following: action type, action start value, action target value, action duration, upper limit of action slope change, action frequency, and action noise level.

[0063] This implementation takes into account that there are various executors that perform actions, and different executors may have different levels of disturbance to the user. Therefore, in this implementation, for each action, the executor that performs the action is first determined based on the action type, and then the basic disturbance value of the executor is obtained. That is, the basic disturbance value of the executor is used as the basic part of the disturbance value of the action. Then, based on this, the superimposed value of the action is obtained according to the execution information of the action. The basic disturbance value and the superimposed value are added together, and finally used as the determined disturbance value to reflect the degree of disturbance of the action to the user.

[0064] As can be seen, in this implementation method, the basic difference in the degree of disturbance caused by different actuators is distinguished by the basic disturbance value. The difference in the degree of disturbance caused by the same actuator's action due to the different execution information of the specific action can be effectively reflected in the superimposed value, making the disturbance value determined by this implementation method more accurate and reliable.

[0065] For a specific actuator, its basic disturbance value can be preset. For example, based on the specific model of the actuator and the typical noise, mechanical vibration and other factors detected during the experiment, its basic disturbance value can be preset.

[0066] The execution information of an action, also known as the action's attributes, reflects how the action should be performed. For example, if an action is specifically an airbag pressure adjustment action, its execution information is "change from pressure P1 to pressure P2 within a limited time." If an action is a bed frame adjustment, its execution information is "adjust the angle from A1 to A2 within a limited time and at a limited incline." If an action is a light reminder, its execution information is "gradually change the brightness from L1 to L2 within a few seconds." If an action is a voice prompt, its execution information is "trigger a voice output of a fixed duration at a certain moment."

[0067] There are various ways to determine the superposition value of an action based on its execution information. In this implementation, the execution information includes one or more of the following: action type, action start value, action target value, action duration, upper limit of action slope change, action frequency, and action noise level. Based on this execution information, there are multiple ways to determine the superposition value. For example, a calculation model for the superposition value can be established to obtain a relatively accurate and reliable superposition value based on the execution information. Alternatively, the superposition value can be obtained through simple weighted calculations based on this execution information. For instance, the action amplitude can be determined according to the action start value and action target value; the larger the action amplitude, the higher the superposition value, meaning the action amplitude and the superposition value are positively correlated. Correspondingly, the longer the action duration, the larger the upper limit of action slope change, the higher the action frequency, and the higher the action noise level, the larger the resulting superposition value will be.

[0068] In other embodiments, other execution information items can be set for the action according to actual needs. The execution information items for different actions can also be different, which does not affect the implementation of the present invention. For example, in one embodiment, the current time period parameter is also introduced into the execution information. This means that for the same action, the cumulative value of the action will be greater during the user's sleep period at night compared to non-sleep periods such as before bedtime or during the day, which will result in a greater disturbance value for the action.

[0069] Step S103: Determine the disturbance threshold for a single time window.

[0070] The disturbance threshold for a single time window is used to constrain the selection of actions in subsequent steps. This disturbance threshold can be set to a fixed value or a dynamically changing value.

[0071] For example, in one specific embodiment of the present invention, step S104 may specifically include:

[0072] Get the configuration value of the disturbance threshold;

[0073] Determine whether the disturbance threshold is set to a fixed value;

[0074] If so, the configuration value will be used as the disturbance threshold for a single time window;

[0075] If not, adjust the configuration value based on the current time period and / or the current mode setting and / or the current user status, and use the adjusted value as the disturbance threshold for a single time window.

[0076] In this implementation, the configuration value of the disturbance threshold is first obtained, and then it is determined whether the disturbance threshold is set to a fixed value. If it is set to a fixed value, the configuration value can be directly used as the disturbance threshold for a single time window.

[0077] Conversely, if not set to a fixed value, the configuration value needs to be adjusted based on the current time period and / or the current mode setting and / or the current user status. The specific adjustment rules can be set according to actual needs. For example, in one specific implementation, if the current time period matches the set user sleep period, the configuration value can be reduced; if the current mode is set to Do Not Disturb mode / Silent mode, the configuration value can be reduced; if the current user status is stable, the configuration value can be reduced, thereby reducing the disturbance threshold.

[0078] It should also be noted that the user state described here refers to the intensity of the user's physical activity on the smart bedding. For example, turning over, raising legs, sitting up, slight shaking, and local pressure changes will all affect the user state. In practical applications, the user state can be measured by parameters such as the amplitude of mattress pressure changes, the distance the pressure center moves, the number of body movements, and micro-motion signals. For example, the user's body movement level and postural stability can be calculated based on these parameters as the determined user state.

[0079] Step S104: Prioritize the various actions to be performed.

[0080] Since different actions have different functions, varying degrees of time urgency, and different safety relevance, the proposed solution prioritizes each action to be executed, ensuring that higher-priority actions are selected subsequently.

[0081] Of course, the specific priority sorting rules can be set and adjusted according to actual needs. For example, in a specific embodiment of the present invention, step S104 may specifically include:

[0082] For any action to be performed, the total priority score of the action is obtained based on the initial priority score, urgency score, and safety score of the action.

[0083] The actions to be executed are prioritized according to their total priority scores, from highest to lowest.

[0084] In this implementation, the total priority score of an action is obtained based on its initial priority score, urgency score, and safety score; that is, a comprehensive score is used to measure the priority of an action. The initial priority score reflects the inherent priority of the action, which is usually included when the action is generated. Alternatively, different initial priority scores can be pre-configured according to action type. The urgency score reflects the urgency of the action. For example, some actions are set to be non-delayable by the system program or the user, such as a voice broadcast action set by the user to be triggered at a certain time; such actions will have a high urgency score. Conversely, if an action is delayable, its urgency score will be lower, allowing it to yield to higher-priority actions. The safety score reflects the safety relevance of the action; that is, if the action is related to user safety, such as necessary support and adjustment actions or safety prompt actions, it will have a high safety score.

[0085] Based on the initial priority score, urgency score, and safety score of an action, these scores can be directly added together or weighted together to obtain the total priority score of the action. Then, the actions to be executed can be prioritized according to the total priority score from high to low.

[0086] Step S105: According to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, select the actions to be executed in the next time window from the actions to be executed, and execute the selected actions in the next time window.

[0087] After prioritizing the actions to be executed, the proposed solution selects the actions in descending order of priority, and the total disturbance value of the selected actions does not exceed the disturbance threshold selection rule. In other words, the disturbance threshold is equivalent to the total disturbance budget for the next time window, ensuring that the total disturbance value of the actions executed in the next time window does not exceed the disturbance budget.

[0088] For example, in a scenario where the disturbance threshold is 100, the actions to be executed are ordered by priority, referred to as actions 1 to 5. For instance, if the disturbance value of action 1 is 20, action 1 is selected first, and it can be seen that the disturbance value of action 1 does not exceed the disturbance threshold. If the disturbance value of action 2 is 50, it can be seen that the total disturbance value of actions 1 and 2 is 70, still within the disturbance threshold, so action 2 can be selected. If the disturbance value of action 3 is 35, it can be seen that if action 3 is selected, the total disturbance value will reach 105, exceeding the disturbance threshold, so action 3 needs to be skipped. If the disturbance value of action 4 is 40, it can be seen that if action 4 is selected, the total disturbance value will exceed the disturbance threshold, so action 4 needs to be skipped. If the disturbance value of action 5 is 10, it can be seen that the total disturbance value of actions 1, 2, and 5 is 80, within the disturbance threshold, so action 5 can be selected.

[0089] At this point, all actions to be executed have been traversed, and the selection process can end. It can be seen that in this example, following the selection rule of prioritizing high-priority actions and ensuring the total disturbance value of the selected actions does not exceed the disturbance threshold, actions 1, 2, and 5 are specifically selected from the pending actions. Therefore, actions 1, 2, and 5 can be executed in the next time window. Actions 3 and 4 in this example will be executed in the following time window, thus enabling the scheduling strategy for smart bedding in this application to effectively reduce disturbance to the user.

[0090] In one specific embodiment of the present invention, it may further include: setting a maximum number of executions of each action within the same window as a local action constraint;

[0091] Accordingly, following the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the remaining actions, including:

[0092] Based on the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, and the selected actions to be executed in the next time window conform to the local action constraints.

[0093] This implementation takes into account that the disturbance threshold set above is a constraint on the total disturbance of actions within a time window. On this basis, some local action constraints can be further set. This is because if the same type of action is executed many times within a time window, even if it does not exceed the disturbance threshold, the continuous disturbance of the same action may affect the user experience.

[0094] Therefore, in this implementation, a maximum number of executions of each action within the same window is set as a local action constraint. For example, within the same window, there needs to be a constraint on the maximum number of voice prompts, the maximum number of bed frame movements, and the maximum number of rapid airbag pressure adjustments, thereby preventing a single type of action from causing continuous disruption. It is also understood that the maximum number of executions within the same window can differ for different actions. Of course, if an action, even if executed multiple times consecutively within a time window, does not significantly impact the user experience, then the maximum number of executions set for it within the same window can be larger, which is equivalent to relaxing the local action constraint for that action based on the actual situation.

[0095] Because this implementation adds local action constraints, when executing step S105, it is necessary to select actions to be executed in the next time window from the actions to be executed according to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold. Furthermore, the selected actions to be executed in the next time window must meet the local action constraints. That is, this implementation requires satisfying both the disturbance threshold requirement and the local action constraints. For example, in the example above, actions 2 and 5 are of the same type, and the maximum number of times this type of action can be executed within the same window is 1. Therefore, after selecting action 2, action 5 cannot be selected.

[0096] In one specific embodiment of the present invention, it may further include:

[0097] For the actions selected from the pending actions to be executed in the next time window, determine whether there are any concurrent conflicts between the actions;

[0098] If not, the selected actions will be executed in the next time window;

[0099] If so, for each group of actions that causes a concurrent conflict, if the group of actions supports off-peak execution in the next time window, the group of actions will be executed off-peak in the next time window. If the group of actions does not support off-peak execution in the next time window, only some of the actions in the group will be retained, so that the retained actions in the group do not have concurrent conflicts or that the retained actions in the group support off-peak execution in the next time window.

[0100] This implementation further considers that if some actions are performed simultaneously, they may increase the user's sense of being disturbed, thereby reducing the user experience. For example, when the actions of rapidly raising the bed frame and significantly inflating and deflating the airbag are performed at the same time, it is easy to amplify the user's perception. Similarly, when voice prompts and buzzer prompts are output at the same time, it may also constitute repeated disturbance.

[0101] In this implementation, for each action selected from the pending actions to be executed in the next time window, it is determined whether there are any concurrent conflicts between the actions. It is understood that if there are no concurrent conflicts, there is no need to implement a staggered execution strategy. If there are concurrent conflicts, for example, actions 01 and 03 are a set of concurrent conflicting actions, and both support staggered execution within the next time window, then these two actions can continue to be executed in the next time window, but they need to be staggered in time.

[0102] For example, if the time window is 30 seconds long, and actions 04 and 05 are a set of concurrent conflicting actions, and each of them has a duration of, for example, 20 seconds, then it can be seen that in this example, actions 04 and 05 cannot be executed at different times within the same time window. Therefore, only some actions in this set of actions can be retained, such as only action 04, to avoid the concurrent conflict. In this example, action 05 will not be executed in the next time window.

[0103] For example, if the time window is 30 seconds long, and actions 04, 05, and 06 are a group of concurrent conflicting actions, and each of them has a duration of, for example, 12 seconds, then it can be seen that in this example, actions 04, 05, and 06 cannot be executed in staggered phases within the same time window. Therefore, only some actions in this group can be retained, such as only actions 04 and 05, so that actions 04 and 05 can be executed in staggered phases within the next time window. In this example, action 06 will not be executed in the next time window.

[0104] It should also be noted that when a group of actions with concurrent conflicts does not support staggered execution in the next time window, and only some actions in the group are retained, the higher priority actions in the group are usually retained.

[0105] In some implementations, after acquiring the various actions to be performed by the smart bedding, a pre-merging operation can be added as needed before calculating the disturbance value. For example, if multiple small airbag pressurization requests occur consecutively within a short period of time, these actions can be merged into a smooth pressurization action, which is more conducive to increasing smoothness compared to multiple jump executions.

[0106] In one specific embodiment of the present invention, it may further include:

[0107] For any action selected from the various actions to be executed, determine whether the action meets the shaping conditions;

[0108] If so, the action is shaped to reduce the degree of disruption to the user during the execution of the action;

[0109] The shaping methods include: limiting the maximum slope of the movement, limiting the single change amplitude of the movement, breaking the complete movement into multiple step movements and setting the interval between the step movements, using a gradual curve to replace the abrupt curve, and reducing the intensity and duration of the movement, or one or more of these.

[0110] This implementation takes into account that before the action is actually sent to the executor, the parameters of the action can be reshaped as needed, thereby further reducing interference. Specifically, for any action selected from the various actions to be executed, it is determined whether the action meets the shaping conditions. The specific content of the shaping conditions can be set according to actual needs. For example, some high-priority tasks or tasks with high security relevance are usually required to be completed in a timely manner without specific agreement. Such tasks can be determined to not meet the shaping conditions. Similarly, due to user's personal needs, for some types of tasks, users expect them to be completed quickly with a large rate of change. These tasks can also be determined to not meet the shaping conditions.

[0111] For actions that meet the shaping criteria, shaping can be performed to reduce the degree of disturbance to the user during the execution of the action. Specifically, limiting the maximum change slope of the action, limiting the single change amplitude of the action, breaking the complete action into multiple step actions and setting the interval between step actions, using a gradual curve instead of an abrupt curve, and reducing the intensity and duration of the action can all help to further reduce the disturbance to the user. Of course, the specific shaping method can be set according to the actual situation, and one or more shaping contents can be set for different actions.

[0112] For example, in practical applications, adjusting the bed frame angle will not be done quickly, but rather smoothly at a low speed. Similarly, adjusting the airbag pressure can be done in small steps, gradually approaching the target pressure, with short pauses between each step to allow the user time to adjust. And for lighting alerts, a gradual brightening / dimming curve can be used to avoid sudden glare.

[0113] In one specific embodiment of the present invention, it may further include:

[0114] When a user disturbance is detected, pre-defined corrective measures are executed;

[0115] The corrective measures include: reducing the slope of the remaining pending actions, reducing the amplitude of the remaining pending actions, extending the waiting time for the next action, and suspending one or more of the low-priority actions.

[0116] This implementation takes into account that when a user disturbance response is detected, it indicates that the current action scheduling of the smart bedding is still affecting the user experience. Therefore, one or more corrective measures will be implemented, such as reducing the action slope of the remaining pending actions, reducing the action amplitude of the remaining pending actions, extending the waiting time for the next action, pausing low-priority actions, etc. Furthermore, in some implementations, when a user disturbance response is detected, in addition to the above corrective measures, the disturbance value can be recalculated and the action queue reordered and selected according to the corrected action situation. Additionally, the disturbance threshold can be temporarily lowered so that subsequent actions can reduce disturbance to the user. Once the user has returned to a stable state for a certain period of time, the corrective measures can be canceled, and the original normal scheduling mode can be restored.

[0117] Furthermore, there are various ways to detect user startle responses. For example, user feedback can be continuously collected during the execution of an action to determine whether a startle response has occurred. Feedback could come from mattress pressure / micro-motion signals, allowing the system to determine if the user exhibits significant rolling over, increased shaking, or exacerbated local pressure redistribution due to the current action. Alternatively, in the above implementation where the user's body movement level and postural stability are used as the determined user state, the determination of whether a startle response has occurred can be made directly based on the determined user state.

[0118] In one specific embodiment of the present invention, it may further include:

[0119] When an abnormality is detected in the smart bedding and / or the user activates the night silent mode, the preset degradation measures are executed;

[0120] The downgrade measures include: suspending comfort-enhancing actions, reducing the frequency of preset high-noise actions, setting a limit on the number of actuators that can perform simultaneous actions, and replacing voice prompts with one or more light prompts.

[0121] This implementation takes into account that smart bedding may experience abnormal situations such as malfunctions of some actuators, limited power supply, communication delays, excessive pump noise, and abnormal valve operation. Users may also activate the silent mode at night. In such cases, the solution proposed in this application does not simply stop the operation of the smart bedding, but automatically switches to a degraded operation mode, that is, executes preset degraded measures, so as to minimize disturbances, maintain functionality, and ensure safety under limited conditions.

[0122] In the degraded operation mode, safety-related functions or preset necessary functions are retained in priority. Therefore, in this implementation, the degraded measures may include pausing comfort enhancement actions, reducing the frequency of preset high-noise actions, setting a limit on the number of actuators that can act simultaneously to prevent too many actuators from acting at the same time, replacing voice prompts with light prompts, such as replacing voice prompts with light prompts, and breaking down large bed frame actions into slower, fewer actions.

[0123] For example, when the air pump is noisy and in silent night mode, non-critical pressure adjustment actions can be delayed, with only necessary minor corrections retained; when the bed frame motor temperature rises too high, the maximum speed and single amplitude of the bed frame movement can be reduced; when the voice module is unavailable, it can automatically switch to light or light vibration as alternative prompts.

[0124] In practical applications, the action scheduling process can be logged. Log content can include the source of the action request, action execution information, disturbance value, whether it was staggered / merged / delayed, user feedback results, and the final execution result. These logs can be used for subsequent analysis and strategy optimization. For example, when users frequently report that nighttime actions are too noticeable, the logs can identify which type of action has been consistently consuming a large amount of disturbance budget, thereby optimizing parameters or adjusting the scheduling strategy. For instance, if the logs identify that the total disturbance value of a certain action has exceeded a preset alarm threshold within a recent period (e.g., a week, a month), the action can be adjusted, such as limiting its frequency or reducing the upper limit of the action's slope change. In some implementations, to improve user experience and enhance the interpretability of system behavior, the system can also output simplified explanatory information, such as: the bed frame action was not executed immediately because of insufficient disturbance budget; the voice prompt was replaced by a light prompt because the nighttime silent mode was activated.

[0125] By applying the technical solution provided in this invention, various actions to be performed by the smart bedding can be obtained. Instead of immediately executing these actions, a disturbance value is determined for each action based on its execution information, reflecting the degree of disturbance to the user. In other words, for each action, the disturbance value quantifies its impact on the user, allowing actions executed by different actuators to be included in the same scheduling framework. This enables unified scheduling of various actions, avoiding excessive disturbance to the user. Furthermore, considering the varying importance and urgency of different actions, this solution prioritizes the actions to be performed, ensuring that higher-priority actions are executed first. Then, based on the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed a disturbance threshold, actions are selected from the remaining actions to be performed for execution in the next time window. This means that when these selected actions are executed in the next time window, their total disturbance value does not exceed the disturbance threshold, thus improving the user experience and reducing disturbance to the user's sleep and rest.

[0126] In summary, the proposed solution not only meets the functional objectives of smart bedding but also achieves unified scheduling of actions, reducing the disturbance of actions to users' sleep and rest.

[0127] Corresponding to the above embodiments of the smart bedding scheduling method, this invention also provides a smart bedding system, see [link to relevant documentation]. Figure 2 As shown, it includes: the smart bedding body, the memory, and the processor. Figure 2 The smart bedding body is not shown in the diagram. Memory 201 is used to store computer programs; processor 202 is used to execute the computer programs to implement the steps of the smart bedding scheduling method as described in any of the above embodiments.

[0128] This invention also provides a computer-readable storage medium and a computer program product, which can be referred to in correspondence with the above description.

[0129] The computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the smart bedding scheduling method as described in any of the above embodiments.

[0130] See also Figure 3The computer-readable storage medium 30 stores a computer program 31, which, when executed by a processor, implements the steps of the smart bedding scheduling method as described in any of the above embodiments. The computer-readable storage medium 30 referred to herein includes RAM (Random Access Memory), main memory, ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), registers, hard disks, removable disks, or any other form of storage medium known in the art.

[0131] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0132] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0133] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the technical solutions and core ideas of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the present invention.

Claims

1. A method for scheduling the actions of intelligent bedding, characterized in that, include: Obtain the various actions to be performed by the smart bedding; For each action, based on the execution information of the action, a disturbance value is determined to reflect the degree of disturbance the action causes to the user; Determine the disturbance threshold for a single time window; Prioritize the various actions to be performed; According to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, and the selected actions are executed in the next time window.

2. The scheduling method for intelligent bedding according to claim 1, characterized in that, For each action, based on the execution information of the action, a disturbance value reflecting the degree of disturbance to the user is determined, including: For each action, based on the action type in the action's execution information, determine the executor that performs the action, and obtain the executor's basic disturbance value; Based on the execution information of the action, the superposition value of the action is determined; The base disturbance value is added to the superimposed value to obtain the disturbance value determined to reflect the degree of disturbance to the user caused by the action. The execution information includes one or more of the following: action type, action start value, action target value, action duration, upper limit of action slope change, action frequency, and action noise level.

3. The scheduling method for intelligent bedding according to claim 1, characterized in that, Determine the disturbance threshold for a single time window, including: Get the configuration value of the disturbance threshold; Determine whether the disturbance threshold is set to a fixed value; If so, the configuration value will be used as the disturbance threshold for a single time window; If not, the configuration value is adjusted based on the current time period and / or the current mode setting and / or the current user status, and the adjusted value is used as the disturbance threshold for a single time window.

4. The scheduling method for intelligent bedding according to claim 1, characterized in that, Also includes: For each action, set the maximum number of times the action can be executed within the same window, as a local action constraint; Accordingly, following the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, including: According to the selection rule of prioritizing high-priority actions and ensuring that the total disturbance value of the selected actions does not exceed the disturbance threshold, actions to be executed in the next time window are selected from the actions to be executed, and the selected actions to be executed in the next time window conform to the local action constraints.

5. The scheduling method for intelligent bedding according to claim 1, characterized in that, Prioritize the various actions to be performed, including: For any action to be performed, the total priority score of the action is obtained based on the initial priority score, urgency score, and safety score of the action; The actions to be performed are prioritized according to their total priority scores, from highest to lowest.

6. The scheduling method for intelligent bedding according to claim 1, characterized in that, Also includes: For the actions selected from the pending actions to be executed in the next time window, determine whether there are any concurrent conflicts between the actions; If not, the selected actions will be executed in the next time window; If so, for each group of actions that causes a concurrent conflict, if the group of actions supports off-peak execution in the next time window, the group of actions will be executed off-peak in the next time window. If the group of actions does not support off-peak execution in the next time window, only some of the actions in the group will be retained, so that the retained actions in the group do not have concurrent conflicts or that the retained actions in the group support off-peak execution in the next time window.

7. The scheduling method for intelligent bedding according to claim 1, characterized in that, Also includes: For any action selected from the various actions to be executed, determine whether the action meets the shaping conditions; If so, the action is shaped to reduce the degree of disruption to the user during the execution of the action; The shaping methods include: limiting the maximum slope of the movement, limiting the single change amplitude of the movement, breaking the complete movement into multiple step movements and setting the interval between the step movements, using a gradual curve to replace the abrupt curve, and reducing the intensity and duration of the movement, or one or more of these.

8. The scheduling method for intelligent bedding according to claim 1, characterized in that, Also includes: When a user disturbance is detected, pre-defined corrective measures are executed; The corrective measures include: reducing the action slope of the remaining pending actions, reducing the action amplitude of the remaining pending actions, extending the waiting time for the next action, and suspending one or more of the low-priority actions.

9. The scheduling method for intelligent bedding according to any one of claims 1 to 8, characterized in that, Also includes: When an anomaly is detected in the smart bedding and / or the user activates the night silent mode, the preset degradation measures are executed; The degradation measures include: suspending comfort-enhancing actions, reducing the frequency of preset high-noise actions, setting a limit on the number of actuators performing simultaneous actions, and replacing voice prompts with one or more light prompts.

10. A smart bedding system, characterized in that, include: The smart bedding body, the memory, and the processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the steps of the scheduling method for the smart bedding as described in any one of claims 1 to 9.

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