Intelligent mattress adjustment method and apparatus, electronic device, and storage medium

Abstract

An intelligent mattress adjustment method and apparatus, an electronic device, and a storage medium. The method comprises: creating an actual use state model on the basis of a user use state parameter sent by a sensing unit, and a user manual input parameter, wherein the user use state parameter is measured by the sensing unit when a user uses an intelligent mattress (S110); on the basis of the actual use state model and a preset use state model, performing calculation to obtain an optimized use state model, wherein the preset use state model is derived by applying experimental data to the intelligent mattress (S120); and on the basis of the optimized use state model, controlling air bag groups to complete state adjustment (S130). The intelligent mattress adjustment method can control different states of the intelligent mattress for different users.

Description

Intelligent mattress adjustment method, device, electronic device and storage medium Technical Field

[0001] The present invention relates to the field of smart homes, and in particular to an intelligent mattress adjustment method, device, electronic equipment and storage medium. Background Art

[0002] A mattress is an item that is placed between the human body and the bed to ensure that users get a healthy and comfortable sleep. Mattresses are made of a variety of materials, and mattresses made of different materials can bring different feelings to users.

[0003] In the field of pursuing comfort and relaxation, such as massage beds and massage chairs, a smart mattress or back cushion with multiple airbag groups inside is usually used. When in use, the multiple airbag groups in the mattress or back cushion are adjusted to different degrees according to the human body structure, so that the multiple airbag groups output different air volumes and pressures, which are more in line with the human body structure and provide a better user experience.

[0004] However, the current smart mattress can only control the airbag group according to the set program, the control mode is single and the applicability is poor, and it is unable to achieve different control methods for different users. Summary of the Invention

[0005] Based on this, it is necessary to provide a smart mattress adjustment method, device, computer equipment and readable storage medium to address the above technical problems. The method can control different states of the smart mattress for different users and has good applicability.

[0006] The present invention provides a smart mattress adjustment method, which is applied to a control unit, wherein the smart mattress is provided with multiple airbag groups inside, and each airbag group is provided with a sensor unit on the surface, and the airbag groups and the sensor units are electrically connected to the control unit. The method includes:

[0007] Creating an actual application state model based on the user usage state parameters sent by the sensing unit and the user manually input parameters, wherein the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress;

[0008] Calculating an optimized usage state model based on the actual application state model and the preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress;

[0009] The state model is used to control the airbag group to complete state adjustment according to the optimization.

[0010] In one embodiment, the creating the actual application state model based on the user usage state parameters sent by the sensing unit and the user manually input parameters includes:

[0011] Classify and calculate the user usage state parameters and the user manual input parameters according to the position distribution of the multiple airbag groups to obtain a local user usage state model and a local user manual input model;

[0012] A local actual application state model is created based on the local user usage state model and the local user manual input model;

[0013] The edges of multiple local actual application state models are smoothed to obtain an actual application state model.

[0014] In one embodiment, the calculating of the optimized usage state model based on the actual application state model and the preset usage state model includes:

[0015] Calculating the actual application state model and the preset usage state model respectively according to a preset allocation function to obtain optimized usage state parameters;

[0016] An optimized usage state model is created according to the optimized usage state parameters.

[0017] In one embodiment, the preset allocation function includes the ratio between the actual application state model and the preset usage state model under different conditions, and the sum of the parameter proportions of the actual application state model and the preset usage state model in the optimized usage state model is 1.

[0018] In one embodiment, the method further comprises:

[0019] The optimized usage state model is sent to the cloud or the terminal, and the optimized usage state model replaces the preset usage state model stored in the cloud or the terminal.

[0020] In one embodiment, the method further comprises:

[0021] Obtain a preset usage state model stored in the cloud or terminal, and control the airbag group to complete state adjustment according to the preset usage state model.

[0022] The present invention also provides an intelligent mattress adjustment device, which is applied to a control unit and includes:

[0023] a creation module, configured to create an actual application state model based on user usage state parameters sent by the sensing unit and user manually input parameters, wherein the user usage state parameters are parameters detected by the sensing unit when the user uses the smart mattress;

[0024] an optimization module, configured to calculate an optimized usage state model based on the actual application state model and a preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress;

[0025] The regulating module is used to control the airbag group to complete state regulation according to the optimized usage state model.

[0026] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any of the above-described intelligent mattress adjustment methods when executing the computer program.

[0027] The present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements any of the above-described intelligent mattress adjustment methods.

[0028] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-described intelligent mattress adjustment methods.

[0029] The above-mentioned intelligent mattress adjustment method, device, electronic device and storage medium create a preset usage state model as the basic model for user usage optimization by deducing a large amount of data. Combined with the actual application state model generated by the user's current use and the user manual input model manually input by the user according to their own needs, a revised optimized usage state model can be calculated. Compared with the preset usage state model, the actual usage state model and the user manual input model, the optimized usage state model is more suitable for the user. The intelligent mattress adjustment method can realize the control of different states of the intelligent mattress for different users, thereby better meeting the user's usage habits and needs and having good applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] FIG1 is a flow chart of a smart mattress adjustment method according to the present invention;

[0032] FIG2 is a second flow chart of the intelligent mattress adjustment method of the present invention;

[0033] FIG3 is a third flow chart of the intelligent mattress adjustment method of the present invention;

[0034] FIG4 is a fourth flow chart of the intelligent mattress adjustment method of the present invention;

[0035] FIG5 is a module diagram of the intelligent mattress adjustment device of the present invention;

[0036] FIG6 is a schematic structural diagram of the smart mattress of the present invention;

[0037] FIG. 7 is a diagram showing the internal structure of a computer device according to an embodiment. DETAILED DESCRIPTION

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0039] The following describes the intelligent mattress adjustment method, device, electronic device and storage medium of the present invention with reference to FIG1 to FIG7.

[0040] As shown in FIG1 , in one embodiment, a smart mattress adjustment method is applied to a control unit, wherein the smart mattress is provided with multiple airbag groups inside, and each airbag group is provided with a sensor unit on the surface, and the airbag groups and the sensor units are electrically connected to the control unit, comprising the following steps:

[0041] Step S110 , creating an actual application state model according to the user usage state parameters sent by the sensing unit and the user manually input parameters, where the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress.

[0042] Specifically, when a user lies on the smart mattress, the sensor unit can capture the pressure data generated by the user's use of the smart mattress. This pressure data is the user's usage status parameter. Since the smart mattress has multiple airbag groups inside, and each airbag group is equipped with a sensor unit on the surface, the user's usage status parameter can be determined based on the sensor unit serial number and the pressure data detected by the sensor unit. At the same time, the user can also manually input the required parameters into the control unit. Manually input parameters include one or more of the user ID, user body shape, height, pressure preference for lying flat / sideways, user sleeping habits, softness and hardness preference, etc. Because there are inevitably differences between manually input parameters and user usage status parameters, it is necessary to effectively combine the two parameters to generate a more practical actual application status model of the smart mattress for the current user.

[0043] Step S120 , calculating an optimized usage state model according to the actual application state model and the preset usage state model. The preset usage state model is derived by applying experimental data to the smart mattress.

[0044] Specifically, a smart mattress will initially have a preset usage model. This model is derived from extensive user data collected during the R&D phase, and therefore differs from the user's desired usage model. As the user uses the smart mattress, the preset usage model is modified based on the user's daily usage data (i.e., the actual usage model). This modified, optimized usage model better fits the user's body shape and meets their needs.

[0045] Step S130 , controlling the airbag group to complete state adjustment according to the optimized usage state model.

[0046] Specifically, the optimized usage state model includes the modified state of each airbag group in the smart mattress, and the output air volume and pressure of the airbag group of the smart mattress can be adjusted according to the model.

[0047] The above-mentioned smart mattress adjustment method creates a preset usage state model as the basic model for user usage optimization through deduction of a large amount of data, and combines the actual application state model generated by the user's current use and the user manual input model manually input by the user according to their own needs to calculate a revised optimized usage state model. This optimized usage state model is more suitable for the user than the preset usage state model, the actual usage state model and the user manual input model. This smart mattress adjustment method can realize the control of different states of the smart mattress for different users, thereby better meeting the user's usage habits and needs and having good applicability.

[0048] The airbag group in the smart mattress is composed of an airbag, an air valve and an air pump, and the sensing unit is one or more of a piezoresistive sensor, a weight sensor or a capacitive pressure sensor.

[0049] As shown in FIG2 , in one embodiment, creating an actual application state model based on the user usage state parameters sent by the sensing unit and the user manually input parameters includes the following steps:

[0050] Step S111 , classifying and calculating the user usage state parameters and the user manual input parameters according to the position distribution of the plurality of airbag groups, and obtaining a local user usage state model and a local user manual input model.

[0051] Specifically, as shown in Figure 6, a user is positioned in the middle of the smart mattress. Assuming the human body is divided into four parts: head and neck, upper body, lower body, and arms, the mattress is divided into multiple regions based on the user's usage habits. It should be noted that this region is composed of the airbag group 630 within the smart mattress. The resulting results are shown on the left. The darker area 610 in the center is directly in contact with the user's body and has a higher detected pressure. The lighter areas 620 at the edges are adjacent to the user's body and have a relatively lower detected pressure. The regions contacted by the four user body parts are then distinguished based on the different gravitational forces, and parameters are calculated for each region, ultimately resulting in four localized user usage state models.

[0052] Step S112 : creating a local actual application state model based on the local user usage state model and the local user manual input model.

[0053] Specifically, a local user usage state model is combined with the local user manual input model corresponding to that part to create a local actual application state model. It should be noted that the local user manual input model is determined based on the specific part of the body where the user inputs parameters, such as the head, neck, hand, leg, etc.

[0054] Step S113 , smoothing the edges of multiple local actual application state models to obtain an actual application state model.

[0055] Specifically, due to the special structure of the connections and joints of various parts of the human body, when the smart mattress obtains the model parameters generated based on the user's body, the parameters of the positions of the connections and joints of various parts of the user's body are unclear. In order to ensure the user experience, the model parameters of the connections and joints of various parts of the user's body are processed according to the model parameters of adjacent areas so that the smart mattress can better fit the user.

[0056] As shown in FIG3 , in one embodiment, calculating an optimized usage state model based on the actual application state model and the preset usage state model includes the following steps:

[0057] Step S121 : calculating the actual application state model and the preset usage state model respectively according to the preset allocation function to obtain optimized usage state parameters.

[0058] Specifically, the preset allocation function includes the ratio between the actual application state model and the preset usage state model under different conditions. For example, when one or several physical parameters of the user are within the first threshold, the ratio between the actual application state model and the preset usage state model is 1:1; when one or several physical parameters of the user are greater than the first threshold, the ratio between the actual application state model and the preset usage state model is 4:1. The sum of the parameter proportions of the actual application state model and the preset usage state model in the optimized usage state model is 1. For example, 80% of the model parameters of the actual application state model are selected, and 20% of the model parameters of the preset usage state model are selected.

[0059] Step S122: creating an optimized usage state model according to the optimized usage state parameters.

[0060] Specifically, all the models in this embodiment are obtained by constructing parameters, such as arranging and combining different regional parameters according to regional distribution to obtain models corresponding to the parameters.

[0061] It should be noted that due to the differences in body shape, weight and sleeping habits of each person, the parameters detected by each sensor unit in the smart mattress are also different. Therefore, based on the changes and sizes of the parameters detected by each sensor unit, the user's body shape and sleeping posture can be judged, thereby further correcting the optimized usage status model.

[0062] As shown in FIG4 , in one embodiment, the intelligent mattress adjustment method further includes the following steps:

[0063] In step S410 , the optimized usage state model is sent to the cloud or the terminal, and the optimized usage state model replaces the preset usage state model stored in the cloud or the terminal.

[0064] Step S420: Obtain a preset usage state model stored in the cloud or the terminal, and control the airbag group to complete state adjustment according to the preset usage state model.

[0065] Specifically, when the smart mattress in the user's home can accurately meet the user's usage needs after multiple uses, the cloud or terminal will record the user's usage data, that is, the optimized usage status model. When the user stays in a non-home place such as a hotel, the user can obtain the optimized usage status model from the cloud or terminal, and input the optimized usage status model into the smart mattress in the non-home place, so that the airbag group in the smart mattress can adjust its status to ensure that it can meet the user's usage habits and usage needs like the smart mattress at home.

[0066] The intelligent mattress adjusting device provided by the present invention is described below. The intelligent mattress adjusting device described below and the intelligent mattress adjusting method described above can be referred to in correspondence with each other.

[0067] As shown in FIG. 5 , in one embodiment, an intelligent mattress adjustment device includes a creation module 510 , an optimization module 520 , and an adjustment module 530 .

[0068] The creation module 510 is used to create an actual application state model according to the user usage state parameters sent by the sensing unit and the user's manually input parameters. The user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress.

[0069] The optimization module 520 is used to calculate an optimized usage state model based on the actual application state model and the preset usage state model. The preset usage state model is derived by applying experimental data to the smart mattress.

[0070] The adjustment module 530 is used to control the airbag group to complete state adjustment according to the optimized usage state model.

[0071] In one embodiment, a creation module 510 is specifically used to classify and calculate user usage status parameters and user manual input parameters based on the position distribution of multiple airbag groups to obtain a local user usage status model and a local user manual input model; create a local actual application status model based on the local user usage status model and the local user manual input model; and smooth the edges of multiple local actual application status models to obtain an actual application status model.

[0072] In one embodiment, the optimization module 520 is specifically configured to calculate the actual application state model and the preset usage state model according to a preset allocation function to obtain optimized usage state parameters; and to create an optimized usage state model according to the optimized usage state parameters.

[0073] In one embodiment, the intelligent mattress adjustment device further includes a transmission module for sending the optimized usage state model to the cloud or terminal, and replacing the preset usage state model stored in the cloud or terminal with the optimized usage state model; obtaining the preset usage state model stored in the cloud or terminal, and controlling the airbag group to complete state adjustment according to the preset usage state model.

[0074] FIG7 illustrates a schematic diagram of the physical structure of an electronic device, which may be a smart terminal, and its internal structure diagram may be shown in FIG7 . The electronic device includes a processor, a memory, and a network interface connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the intelligent mattress adjustment method is implemented, and the method includes:

[0075] Creating an actual application state model based on the user usage state parameters sent by the sensing unit and the user's manually input parameters, where the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress;

[0076] An optimized usage state model is calculated based on the actual application state model and the preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress;

[0077] The airbag group is controlled to complete state adjustment according to the optimized usage state model.

[0078] Those skilled in the art will understand that the structure shown in Figure 7 is merely a block diagram of a partial structure related to the solution of the present invention, and does not constitute a limitation on the electronic device to which the solution of the present invention is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0079] In another aspect, the present invention further provides a computer storage medium storing a computer program, which, when executed by a processor, implements an intelligent mattress adjustment method, the method comprising:

[0080] Creating an actual application state model based on the user usage state parameters sent by the sensing unit and the user's manually input parameters, where the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress;

[0081] An optimized usage state model is calculated based on the actual application state model and the preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress;

[0082] The airbag group is controlled to complete state adjustment according to the optimized usage state model.

[0083] In another aspect, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, implements an intelligent mattress adjustment method, the method comprising:

[0084] Creating an actual application state model based on the user usage state parameters sent by the sensing unit and the user's manually input parameters, where the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress;

[0085] An optimized usage state model is calculated based on the actual application state model and the preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress;

[0086] The airbag group is controlled to complete state adjustment according to the optimized usage state model.

[0087] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0088] By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0089] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A smart mattress adjustment method, applied to a control unit, wherein a plurality of airbag groups are arranged inside the smart mattress, and a sensor unit is arranged on the surface of each airbag group, and the airbag group and the sensor unit are electrically connected to the control unit, characterized in that: The method comprises: Creating an actual application state model according to the user usage state parameters sent by the sensing unit and the user manually input parameters, wherein the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress; An optimized usage state model is calculated according to the actual application state model and the preset usage state model, wherein the preset usage state model is derived by applying experimental data to the smart mattress; The state model is used to control the airbag group to complete state adjustment according to the optimization.

2. The intelligent mattress adjustment method according to claim 1, characterized in that: The creating an actual application state model according to the user usage state parameters sent by the sensing unit and the user manually input parameters includes: Classify and calculate the user usage state parameters and the user manual input parameters according to the position distribution of the multiple airbag groups to obtain a local user usage state model and a local user manual input model; A local actual application state model is created according to the local user usage state model and the local user manual input model; The edges of multiple local actual application state models are smoothed to obtain an actual application state model.

3. The intelligent mattress adjustment method according to claim 2, characterized in that: The step of calculating the optimized usage state model according to the actual application state model and the preset usage state model includes: The actual application state model and the preset use state model are calculated respectively according to a preset allocation function to obtain an optimized use state parameter; An optimized usage state model is created according to the optimized usage state parameters.

4. The intelligent mattress adjustment method according to claim 3, characterized in that: The preset allocation function includes the ratio between the actual application state model and the preset usage state model under different conditions, and the sum of the parameter proportions of the actual application state model and the preset usage state model in the optimized usage state model is 1.

5. The intelligent mattress adjustment method according to claim 4, characterized in that: The method further comprises: The optimized usage state model is sent to the cloud or the terminal, and the optimized usage state model replaces the preset usage state model stored in the cloud or the terminal.

6. The intelligent mattress adjustment method according to claim 5, characterized in that: The method further comprises: Obtain a preset usage state model stored in the cloud or terminal, and control the airbag group to complete state adjustment according to the preset usage state model.

7. An intelligent mattress adjustment device, applied to a control unit, characterized in that: include: A creation module, used to create an actual application state model according to the user usage state parameters sent by the sensing unit and the user manually input parameters, wherein the user usage state parameters are the parameters detected by the sensing unit when the user uses the smart mattress; An optimization module, used for calculating an optimized use state model according to the actual application state model and a preset use state model, wherein the preset use state model is derived by applying experimental data to a smart mattress; The regulating module is used to control the airbag group to complete state regulation according to the optimized usage state model.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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