Control method and device of intelligent temperature control mattress, electronic equipment and product

Abstract

The invention discloses a control method and device of an intelligent temperature control mattress, electronic equipment and a product, and relates to the technical field of intelligent mattresses. Acquiring real-time pressure data detected by a plurality of pressure sensors arranged in the intelligent temperature control mattress and real-time temperature data detected by a plurality of temperature sensors arranged on the surface of the intelligent temperature control mattress; determining the current sleeping posture of the user on the intelligent temperature control mattress and the confidence coefficient of the human body part corresponding to each area based on the real-time pressure data detected by the plurality of pressure sensors; determining a target temperature of each region based on a preset baseline temperature, the confidence coefficient of the human body part corresponding to each region and the posture compensation vector of each region; and based on the current real-time temperature data of each area and the target temperature of each area, the temperature of each area is adjusted through a closed-loop control algorithm so that the temperature of each area can be maintained in the interval where the corresponding target temperature is located. The method can adapt to posture changes of the user in sleep in real time, and the sleep quality of the user is effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of smart mattress technology, specifically relating to a control method, device, electronic equipment, and product for a smart temperature-controlled mattress. Background Technology

[0002] A smart temperature-controlled mattress is an innovative product that uses built-in sensors and an intelligent control system to monitor and adjust the mattress temperature in real time, creating a constant-temperature sleep environment for users throughout the year. The mattress incorporates a high-precision temperature sensor that monitors both the body surface temperature and the mattress surface temperature in real time. The temperature control system automatically adjusts the heating or cooling modules according to preset temperatures or user needs, ensuring the mattress temperature remains within a comfortable range of 15-60℃. For example, it can quickly heat up to above 30℃ in winter and cool down to below 25℃ in summer using semiconductor cooling or water circulation technology, breaking the temperature limitations of traditional mattresses.

[0003] Currently, most existing smart temperature-controlled mattresses control the temperature of the entire mattress, making it difficult to individually adjust the temperature of local areas such as the shoulders, waist, and feet (for example, the shoulders need more heat dissipation when sleeping on the side, while the feet may need heating when sleeping on the back). They are not responsive enough to changes in local heat load caused by changes in sleeping posture, which affects the user's sleep quality.

[0004] Therefore, how to provide an effective solution to adapt to changes in a user's posture during sleep in real time has become a pressing problem to be solved in existing technologies. Summary of the Invention

[0005] The purpose of this invention is to provide a control method, device, electronic device, and product for an intelligent temperature-controlled mattress, in order to solve the aforementioned problems existing in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a control method for an intelligent temperature-controlled mattress, comprising: The system acquires real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, wherein the smart temperature-controlled mattress is divided into left and right sides. The current sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area are determined based on real-time pressure data detected by multiple pressure sensors. Both sides of the smart temperature-controlled mattress are divided into multiple areas. Based on the pre-set baseline temperature, the confidence level of the corresponding human body parts in each region, and the posture compensation vector of each region, the target temperature of each region is determined. Based on the current real-time temperature data of each region and the target temperature of each region, the temperature of each region is adjusted through a closed-loop control algorithm to keep the temperature of each region within the corresponding target temperature range. The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

[0007] In one possible design, the method further includes: Predict the user's sleeping posture in the next time period and the confidence level of the corresponding body parts in each area in the next time period; Based on the confidence level of the human body parts corresponding to each region at the current time and the confidence level of the human body parts corresponding to each region in the next time period, a pre-adjustment region is determined. The pre-adjustment region is a region that is not currently a human body part region but will be a human body part region in the next time period, as determined based on the confidence level of the human body parts. The temperature of the pre-adjusted area is pre-adjusted.

[0008] In one possible design, the confidence level for predicting the user's sleeping position in the next time period and the corresponding body parts in each area during the next time period includes: Based on the user's sleeping postures over several recent consecutive periods, predict the user's sleeping posture in the next period and the confidence level of the corresponding body parts in each area of ​​the next period.

[0009] In one possible design, after acquiring real-time pressure data detected by multiple pressure sensors deployed on either side of the smart thermostatic mattress and real-time temperature data detected by multiple temperature sensors deployed on said either side of the surface of the smart thermostatic mattress, the method further includes: The real-time pressure data detected by the multiple pressure sensors and the real-time temperature data detected by the multiple temperature sensors are preprocessed.

[0010] In a possible design, the target temperature of any region is S_zone = S_base + confidence × ΔS_posture, where S_base represents the pre-set baseline temperature, confidence represents the confidence level of the region corresponding to the human body part, and ΔS_posture represents the posture compensation vector of the region.

[0011] In a possible design, the posture compensation vector for any region is ΔS_posture=f(C(z),pose,user_pref), where C(z) represents the degree of contact between the user's body and the region, pose represents the user's sleeping posture, user_pref represents the user's temperature preference for the sleeping posture, and f() represents the function used to calculate the posture compensation vector.

[0012] In one possible design, the human body parts include hands, shoulders, chest, waist, hips, legs, and / or feet.

[0013] In a second aspect, the present invention provides a control device for an intelligent temperature-controlled mattress, comprising: The acquisition unit is used to acquire real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, wherein the smart temperature-controlled mattress is divided into left and right sides. The first determining unit is used to determine the current sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area based on the real-time pressure data detected by multiple pressure sensors, wherein both sides of the smart temperature-controlled mattress are divided into multiple areas. The second determining unit is used to determine the target temperature of each region based on the preset baseline temperature, the confidence level of the human body part corresponding to each region, and the posture compensation vector of each region. The adjustment unit is used to adjust the temperature of each area based on the current real-time temperature data of each area and the target temperature of each area, and through a closed-loop control algorithm, so that the temperature of each area is maintained within the corresponding target temperature range. The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

[0014] Thirdly, the present invention provides an electronic device comprising a memory, a processor, and a transceiver connected in sequence and communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the control method for the intelligent temperature-controlled mattress as described in the first aspect or any possible design of the first aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the control method for the intelligent temperature-controlled mattress described in the first aspect or any possible design of the first aspect.

[0016] Fifthly, the present invention provides a computer program product containing instructions that, when the instructions are executed on a computer, cause the computer to perform the control method for the intelligent temperature-controlled mattress as described in the first aspect or any possible design of the first aspect.

[0017] Beneficial effects: This invention acquires real-time pressure data detected by multiple pressure sensors deployed on one side of a smart temperature-controlled mattress, and real-time temperature data detected by multiple temperature sensors deployed on the surface of the mattress on the same side. Based on the real-time pressure data detected by the multiple pressure sensors, it determines the user's current sleeping posture and the confidence level of the corresponding body parts in each area of ​​the smart temperature-controlled mattress. Then, based on a pre-set baseline temperature, the confidence level of the corresponding body parts in each area, and the posture compensation vector of each area, it determines the target temperature for each area. Finally, based on the current real-time temperature data and the target temperature of each area, a closed-loop control algorithm is used to adjust the temperature of each area to maintain the temperature of each area within the corresponding target temperature range. In this way, independent temperature adjustment of the left and right sides of the mattress can be achieved, allowing the same bed to meet the different physical needs of two users, improving comfort and adaptability. At the same time, the pressure detected by the pressure sensors can identify the user's sleeping posture. When the user changes from supine to side-lying or rolls over, the system automatically identifies and adjusts the temperature of the corresponding area to avoid local overheating or undercooling, improving the user experience and sleep quality. Secondly, real-time temperature monitoring and closed-loop control are introduced to maintain the temperature in each zone within its corresponding target temperature range, achieving dynamic temperature closed-loop control. Furthermore, multi-zone refined management and control allows for on-demand temperature adjustment in different zones, achieving more precise ergonomic adaptation and effectively improving user sleep quality. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the control method for an intelligent temperature-controlled mattress provided in this application embodiment; Figure 2 A block diagram of the control device for the intelligent temperature-controlled mattress provided in this application embodiment; Figure 3 This is a block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is 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. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0020] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0021] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0022] To adapt to changes in a user's posture during sleep, this application provides a control method, device, electronic device, and product for an intelligent temperature-controlled mattress. This control method, device, electronic device, and product can adapt to changes in a user's posture during sleep in real time, effectively improving the user's sleep quality.

[0023] The control method for the smart temperature-controlled mattress provided in this application can be applied to a server communicating with the smart temperature-controlled mattress or to the control unit of the smart temperature-controlled mattress. It is understood that the described execution entity does not constitute a limitation on the embodiments of this application.

[0024] The control method of the intelligent temperature-controlled mattress provided in the embodiments of this application will be described in detail below.

[0025] like Figure 1 The diagram shown is a flowchart of a control method for an intelligent temperature-controlled mattress provided in the first aspect of an embodiment of this application. The control method for the intelligent temperature-controlled mattress may include, but is not limited to, the following steps S101-S104.

[0026] Step S101. Obtain real-time pressure data detected by multiple pressure sensors deployed on any side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on any side of the surface of the smart temperature-controlled mattress.

[0027] The smart temperature-controlled mattress is divided into left and right sides.

[0028] In one or more embodiments, multiple pressure sensors may be arrayed, for example, 32×32 pressure sensors or more may be set in a smart temperature-controlled mattress (or on the left and right sides of a smart temperature-controlled mattress).

[0029] When using real-time pressure data detected by multiple pressure sensors and real-time temperature data detected by multiple temperature sensors, the sampling frequency of the pressure sensors can be 5-20Hz (default 10Hz), and the sampling frequency of the temperature sensors can be 0.2-1Hz (default 0.5Hz). The real-time pressure data detected by the pressure sensors and the real-time temperature data detected by the temperature sensors are timestamped together.

[0030] In one or more embodiments, after acquiring real-time pressure data detected by multiple pressure sensors deployed on any side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, the real-time pressure data detected by the multiple pressure sensors and the real-time temperature data detected by the multiple temperature sensors may be preprocessed.

[0031] Specifically, the system can perform baseline correction and calibration on the real-time pressure data detected by the pressure sensor, and periodically perform baseline drift correction by sampling the static zero point (when no one is present). It can also perform jitter reduction and filtering on the real-time pressure data, such as short-time median filtering (3-5 frames window) + exponential moving average (EMA). Longer-term low-pass filtering can be applied to the real-time temperature data. For individual sensor anomalies (abrupt changes), the median of surrounding neighboring points can be used as a substitute. Furthermore, the detected real-time pressure data can be standardized to normalize it to 0-1 for model input, and the real-time pressure data space can be rearranged, dividing the smart temperature-controlled mattress into a 32×32 grid and mapping it to physical coordinates (x, y) according to the bed's geometry.

[0032] Step S102. Based on the real-time pressure data detected by multiple pressure sensors, determine the user's current sleeping posture on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area.

[0033] The smart temperature-controlled mattress described herein is divided into multiple zones on both sides. It should be noted that when installing temperature sensors, it is essential to ensure that each zone has at least one temperature sensor.

[0034] In one or more embodiments, the current sleeping posture of a user on a smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area can be determined by a pre-trained posture detection model. The posture detection model can be trained by using historical pressure data detected by multiple pressure sensors as sample input and the historical sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area as sample output.

[0035] The body parts mentioned may include, but are not limited to, hands, shoulders, chest, waist, hips, legs and / or feet. The same body part may be divided into left and right parts, such as left hand and right hand, left shoulder and right shoulder, etc.

[0036] The pose detection model may be, but is not limited to, a Convolutional Neural Network (CNN) model or a Recurrent Neural Network (RNN) model, etc., and no specific limitation is made in the embodiments of this application.

[0037] Step S103. Based on the preset baseline temperature, the confidence level of the human body parts corresponding to each region, and the attitude compensation vector of each region, determine the target temperature of each region.

[0038] The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

[0039] In one or more embodiments, the target temperature of any region can be expressed as S_zone = S_base + confidence × ΔS_posture, where S_base represents a pre-set baseline temperature (e.g., 30°C), confidence represents the confidence level of the human body part corresponding to the region, and ΔS_posture represents the posture compensation vector of the region.

[0040] The posture compensation vector for any region can be represented as ΔS_posture=f(C(z),pose,user_pref), where C(z) represents the degree of contact between the user's body and the region, pose represents the user's sleeping posture (the corresponding quantized value), user_pref represents the user's temperature preference for the sleeping posture, and f() represents the function used to calculate the posture compensation vector. This function can be established through multiple tests, and is not specifically limited in this embodiment.

[0041] The degree of contact between the user's body and the area can be determined based on the pressure value detected by the pressure sensor in each area and its pressure ratio. The range of the degree of contact between the user's body and the area can be [0,1].

[0042] In one or more embodiments, the user's sleeping posture in the next time period and the confidence level of the human body parts corresponding to each region in the next time period can also be predicted. Based on the confidence level of the human body parts corresponding to each region at present and the confidence level of the human body parts corresponding to each region in the next time period, a pre-adjustment region is determined, and then the temperature of the pre-adjustment region is pre-adjusted. The pre-adjustment region is a region that is not currently a human body part region but will be a human body part region in the next time period, as determined based on the confidence level of the human body parts.

[0043] For example, when it is predicted that a user will turn over, the temperature of the pre-adjusted area can be pre-adjusted (e.g., heated or cooled 10-30 seconds in advance) to shorten the response time.

[0044] When predicting a user's sleeping position and the confidence level of the corresponding body parts for each area in the next time period, the prediction can be based on the user's sleeping positions over several recent consecutive time periods. Alternatively, the prediction can be based on the user's historical sleep records combined with their sleeping positions over several recent consecutive time periods.

[0045] Step S104. Based on the current real-time temperature data of each region and the target temperature of each region, adjust the temperature of each region through a closed-loop control algorithm so that the temperature of each region is maintained within the corresponding target temperature range.

[0046] When adjusting the temperature of each zone using a closed-loop control algorithm, the left and right sides of the smart temperature-controlled mattress can be controlled independently and in parallel, allowing for different preferences from two people. When there is a significant difference in the target temperature between the left and right sides, an energy optimization strategy can be activated to avoid energy waste or device overload. For example, if the target temperature for the left zone is 28°C and the target temperature for the right zone is 30°C, a difference of 2°C exceeds the preset threshold ΔT_max. In this case, the system can activate the energy optimization strategy to limit the total power P_total to not exceed the maximum power supply. At this time, the system can prioritize the power allocation to the occupied area (the area currently in contact with the user's body) based on the priority of the occupied area (the area currently in contact with the user's body) and the unoccupied area (the area currently not in contact with the user's body).

[0047] Closed-loop control algorithms can employ PID (proportional-integral-derivative) control or fuzzy control.

[0048] In one or more embodiments, the amplitude of regional temperature regulation can be limited, and the amplitude of each temperature change does not exceed a preset amplitude (e.g., 2°C / minute), simulating sudden changes that may affect comfort or overload the equipment. Simultaneously, temperature safety thresholds can be set, for example, setting the absolute maximum temperature to 40°C and the absolute minimum temperature to 10°C, to avoid excessively high or low temperatures.

[0049] In one or more embodiments, the duration of unoccupied area being unoccupied can be detected. When the duration of unoccupied area being unoccupied exceeds a preset duration (e.g., 3 minutes), the unoccupied area can be gradually controlled to enter a low-power energy-saving mode.

[0050] When adjusting the temperature of each zone, for a water-heated smart thermostatic mattress, the pump speed can be controlled (PWM-controlled DC pump or frequency converter drive). Flow is distributed by adjusting the pump speed and zone valves (PWM or stepper valves). Valves can be stepper or proportional solenoid valves, with angle control for precise flow adjustment. Temperature control depends on the flow rate and the temperature difference between the main unit (heat source / cold source).

[0051] For smart temperature-controlled mattresses with semiconductor cooling / heating, the cooling / heating intensity can be adjusted by controlling the effective current through pulse width modulation (PWM).

[0052] In summary, this invention acquires real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side. Based on the real-time pressure data detected by the multiple pressure sensors, it determines the user's current sleeping posture on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area. Then, based on a pre-set baseline temperature, the confidence level of the corresponding human body parts in each area, and the posture compensation vector of each area, it determines the target temperature of each area. Finally, based on the current real-time temperature data of each area and the target temperature of each area, a closed-loop control algorithm is used to adjust the temperature of each area to maintain the temperature of each area within the corresponding target temperature range. In this way, independent temperature adjustment of the left and right zones of the mattress can be achieved, allowing the same bed to meet the different physical needs of two users, improving comfort and adaptability. At the same time, the pressure detected by the pressure sensors can identify the user's sleeping posture. When the user changes from supine to side-lying or rolls over, the system automatically identifies and adjusts the temperature of the corresponding area to avoid local overheating or undercooling, improving the user experience and sleep quality. Secondly, real-time temperature monitoring and closed-loop control are introduced to maintain the temperature in each zone within its corresponding target temperature range, achieving dynamic temperature closed-loop control. Furthermore, multi-zone refined management and control allows for on-demand temperature adjustment in different zones, achieving more precise ergonomic adaptation, effectively improving user sleep quality, and facilitating practical application and promotion.

[0053] Please see Figure 2 The second aspect of this application provides a control device for an intelligent temperature-controlled mattress, the control device comprising: The acquisition unit is used to acquire real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, wherein the smart temperature-controlled mattress is divided into left and right sides. The first determining unit is used to determine the current sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area based on the real-time pressure data detected by multiple pressure sensors, wherein both sides of the smart temperature-controlled mattress are divided into multiple areas. The second determining unit is used to determine the target temperature of each region based on the preset baseline temperature, the confidence level of the human body part corresponding to each region, and the posture compensation vector of each region. The adjustment unit is used to adjust the temperature of each area based on the current real-time temperature data of each area and the target temperature of each area, and through a closed-loop control algorithm, so that the temperature of each area is maintained within the corresponding target temperature range. The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

[0054] The working process, working details and technical effects of the control device for the intelligent temperature-controlled mattress provided in the second aspect of this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0055] Please see Figure 3 The third aspect of this application provides an electronic device, including a memory, a processor, and a transceiver that are sequentially and communicatively connected, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the control method for the intelligent temperature-controlled mattress as described in the first aspect of the application.

[0056] Specifically, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or last-in-first-out (FILO) memory, etc.; the processor may not be limited to microprocessors of the STM32F105 series, ARM (Advanced RISC Machines), x86 architecture processors, or processors with integrated NPU (neural-network processing units); the transceiver may be, but is not limited to, WiFi (Wireless Fidelity) wireless transceivers, Bluetooth wireless transceivers, General Packet Radio Service (GPRS) wireless transceivers, ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard), 3G transceivers, 4G transceivers, and / or 5G transceivers, etc.

[0057] This fourth aspect of the embodiment provides a computer-readable storage medium storing instructions comprising the control method for the intelligent temperature-controlled mattress described in the first aspect of the embodiment. Specifically, the computer-readable storage medium stores instructions that, when executed on a computer, perform the control method for the intelligent temperature-controlled mattress as described in the first aspect. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or Memory Sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0058] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the control method for the intelligent temperature-controlled mattress as described in the first aspect of this embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0059] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A control method for an intelligent temperature-controlled mattress, characterized in that, include: The system acquires real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, wherein the smart temperature-controlled mattress is divided into left and right sides. The current sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area are determined based on real-time pressure data detected by multiple pressure sensors. Both sides of the smart temperature-controlled mattress are divided into multiple areas. Based on the pre-set baseline temperature, the confidence level of the corresponding human body parts in each region, and the posture compensation vector of each region, the target temperature of each region is determined. Based on the current real-time temperature data of each region and the target temperature of each region, the temperature of each region is adjusted through a closed-loop control algorithm to keep the temperature of each region within the corresponding target temperature range. The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

2. The control method for the intelligent temperature-controlled mattress according to claim 1, characterized in that, The method further includes: Predict the user's sleeping posture in the next time period and the confidence level of the corresponding body parts in each area in the next time period; Based on the confidence level of the human body parts corresponding to each region at the current time and the confidence level of the human body parts corresponding to each region in the next time period, a pre-adjustment region is determined. The pre-adjustment region is a region that is not currently a human body part region but will be a human body part region in the next time period, as determined based on the confidence level of the human body parts. The temperature of the pre-adjusted area is pre-adjusted.

3. The control method for the intelligent temperature-controlled mattress according to claim 2, characterized in that, The confidence levels for predicting a user's sleeping position in the next time period and the corresponding body parts in each area during the next time period include: Based on the user's sleeping postures over several recent consecutive periods, predict the user's sleeping posture in the next period and the confidence level of the corresponding body parts in each area of ​​the next period.

4. The control method for the intelligent temperature-controlled mattress according to claim 1, characterized in that, After acquiring real-time pressure data detected by multiple pressure sensors deployed on either side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on either side of the surface of the smart temperature-controlled mattress, the method further includes: The real-time pressure data detected by the multiple pressure sensors and the real-time temperature data detected by the multiple temperature sensors are preprocessed.

5. The control method for the intelligent temperature-controlled mattress according to claim 1, characterized in that, The target temperature of any region is S_zone = S_base + confidence × ΔS_posture, where S_base represents the preset baseline temperature, confidence represents the confidence level of the corresponding human body part in the region, and ΔS_posture represents the posture compensation vector of the region.

6. The control method for the intelligent temperature-controlled mattress according to claim 5, characterized in that, The posture compensation vector for any region is ΔS_posture=f(C(z),pose,user_pref), where C(z) represents the degree of contact between the user's body and the region, pose represents the user's sleeping posture, user_pref represents the user's temperature preference for the sleeping posture, and f() represents the function used to calculate the posture compensation vector.

7. The control method for the intelligent temperature-controlled mattress according to claim 1, characterized in that, The body parts include hands, shoulders, chest, waist, hips, legs and / or feet.

8. A control device for an intelligent temperature-controlled mattress, characterized in that, include: The acquisition unit is used to acquire real-time pressure data detected by multiple pressure sensors deployed on one side of the smart temperature-controlled mattress and real-time temperature data detected by multiple temperature sensors deployed on the surface of the smart temperature-controlled mattress on the same side, wherein the smart temperature-controlled mattress is divided into left and right sides. The first determining unit is used to determine the current sleeping posture of the user on the smart temperature-controlled mattress and the confidence level of the corresponding human body parts in each area based on the real-time pressure data detected by multiple pressure sensors, wherein both sides of the smart temperature-controlled mattress are divided into multiple areas. The second determining unit is used to determine the target temperature of each region based on the preset baseline temperature, the confidence level of the human body part corresponding to each region, and the posture compensation vector of each region. The adjustment unit is used to adjust the temperature of each area based on the current real-time temperature data of each area and the target temperature of each area, and through a closed-loop control algorithm, so that the temperature of each area is maintained within the corresponding target temperature range. The posture compensation vector for each region is determined based on the degree of contact between the user's body and each region, the user's sleeping posture, and the user's temperature preference for different sleeping postures.

9. An electronic device, characterized in that, The device includes a memory, a processor, and a transceiver that are sequentially and communicatively connected. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the control method for the smart temperature-controlled mattress as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or the instructions are executed by the computer, they implement the control method for the intelligent temperature-controlled mattress as described in any one of claims 1 to 7.

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