Sofa semi-adaptive control method based on multi-sensor fusion and related products

Abstract

The application discloses a sofa semi-adaptive control method based on multi-sensor fusion and related products. The sofa is provided with a pressure sensor array, an angle sensor and an air bag. The method comprises the following steps: acquiring pressure distribution parameters and seat angle parameters through the pressure sensor array and the angle sensor respectively; judging the seating state of the sofa according to the pressure distribution parameters and a preset pressure threshold; if the seating state of the sofa is a seating state, determining a target air bag inflation threshold corresponding to the seat angle parameter according to the seat angle parameter and a preset air bag inflation threshold mapping table; and inflating or deflating the air bag according to the target air bag inflation threshold. The application realizes accurate matching of the seat angle and the inflation amount through the preset air bag inflation threshold mapping table, does not need a complex AI algorithm, can realize accurate and automatic support force adjustment under the premise of controllable cost, and greatly improves the use experience and comfort of the intelligent sofa.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to a semi-adaptive control method for sofas based on multi-sensor fusion and related products. Background Technology

[0002] In existing technologies, intelligent seat airbag control technology is mainly divided into three categories: fully adaptive control, simple adaptive control, and manual control. Fully adaptive control systems use numerous sensors combined with real-time algorithms to achieve pressure distribution identification and dynamic adjustment. While offering superior performance, this technology is highly complex and expensive, making it difficult to popularize in the mid-range market and furniture sector. Simple adaptive control schemes adjust based solely on the principle of pressure complementarity, lacking precise control and logical judgment capabilities. They cannot flexibly adjust according to user usage, have a limited adjustment range, and offer little improvement in user experience. Manual control schemes rely on users manually adjusting the inflation volume of airbags in different areas via a control panel, which is cumbersome, cannot automatically respond to changes in seating status, and has a low level of intelligence. In conclusion, existing intelligent seat airbag control technologies struggle to achieve precise and automated support force adjustment while maintaining controllable costs. Summary of the Invention

[0003] This invention provides a semi-adaptive control method for sofas based on multi-sensor fusion and related products, aiming to solve the problem that existing intelligent seat airbag control technology is unable to achieve precise and automated support force adjustment under the premise of controllable cost.

[0004] In a first aspect, embodiments of the present invention provide a semi-adaptive control method for a sofa based on multi-sensor fusion, wherein the sofa is equipped with a pressure sensor array, an angle sensor, and an airbag, and the method includes: Pressure distribution parameters and seat angle parameters are obtained through the pressure sensor array and the angle sensor, respectively. The seating status of the sofa is determined based on the pressure distribution parameters and the preset pressure threshold. If the sofa is in a seated state, the target airbag inflation threshold corresponding to the seat angle parameter is determined according to the seat angle parameter and the preset airbag inflation threshold mapping table. The preset airbag inflation threshold mapping table stores airbag inflation thresholds that correspond one-to-one with different seat angle parameters. The airbag is inflated or deflated according to the target airbag inflation threshold.

[0005] Secondly, the present invention also provides a sofa semi-adaptive control device based on multi-sensor fusion, including a unit for performing the above-described method.

[0006] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the above-described method.

[0007] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0008] This invention provides a semi-adaptive control method for sofas based on multi-sensor fusion and related products. The invention acquires pressure distribution parameters and seat angle parameters using a pressure sensor array and an angle sensor, respectively. Based on the pressure distribution parameters and a preset pressure threshold, it automatically determines the sofa's seating state. When a seated state is determined, it queries a preset airbag inflation threshold mapping table based on the seat angle parameters to determine the corresponding target airbag inflation threshold. Then, it inflates and deflates the airbags according to the target airbag inflation threshold. This solution uses a preset airbag inflation threshold mapping table to associate and store the seat angle parameters with the airbag inflation thresholds. It eliminates the need for complex real-time AI algorithms and numerous sensors, requiring only a limited number of sensors and table lookup operations to achieve support force adjustment, significantly reducing hardware costs and computational requirements. Simultaneously, it automatically determines the seating state through pressure distribution parameters, achieving automated adjustment of inflation upon seating. The mapping relationship between seat angle parameters and airbag inflation thresholds enables precise support force adjustment at different angles. Therefore, this invention can achieve precise and automated support force adjustment at a controllable cost, significantly improving the user experience and comfort of smart sofas. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating the steps of the sofa semi-adaptive control method based on multi-sensor fusion in an embodiment of the present invention. Figure 2 for Figure 1 A schematic diagram of the sub-steps of S120; Figure 3 for Figure 1 A schematic diagram of another sub-step of S120; Figure 4 for Figure 1 A schematic diagram of the sub-steps of S130; Figure 5for Figure 4 A schematic diagram of the sub-steps of S132; Figure 6 for Figure 5 A schematic diagram of the sub-step of S1322; Figure 7 This is a flowchart illustrating the steps of another embodiment of the present invention: a sofa semi-adaptive control method based on multi-sensor fusion. Figure 8 This is a schematic block diagram of a sofa semi-adaptive control device based on multi-sensor fusion according to an embodiment of the present invention; Figure 9 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. 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.

[0012] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0013] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0014] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0016] As people's demands for quality of life continue to rise, smart seats, as an important product for improving sitting comfort, have been widely used in the furniture and automotive industries. Smart seats use airbag inflation and deflation to adjust the support force for different parts of the user's body, effectively alleviating fatigue caused by prolonged sitting and improving the user's riding experience. Airbag control technology, as the core technology of smart seats, directly affects the comfort and user experience due to its control precision, response speed, and level of intelligence. However, existing smart seat airbag control technologies struggle to achieve precise and automated support force adjustment while maintaining cost control.

[0017] To address this, this invention proposes a semi-adaptive control method for sofas based on multi-sensor fusion and related products. By acquiring pressure distribution parameters and seat angle parameters, the method determines the sofa's seating state based on the pressure distribution parameters and a preset pressure threshold. In the seated state, the method determines the target airbag inflation threshold based on the seat angle parameters and a preset airbag inflation threshold mapping table, and finally performs inflation / deflation operations on the airbags according to this threshold. This method employs lightweight hardware and logic control based on a preset mapping table, eliminating complex sensors and AI algorithms. While controlling costs, it achieves automated and precise adjustment of airbag support force, improving the user experience and facilitating the technology's widespread adoption in the mid-range market and furniture industry. Details are as follows: First, the structure of the sofa according to this embodiment of the invention is described. The sofa includes a multi-sensor module, a control module, an air pump module, and an airbag module, which are connected sequentially. The multi-sensor module is used to collect the sofa's state data, including pressure distribution, seat angle, and seating status. The multi-sensor module includes a pressure sensor array, an angle sensor, and a weight sensor. The pressure sensor array uses flexible fabric pressure sensors, distributed in key areas of the sofa cushion and backrest, such as the buttocks, waist, and back, to collect pressure distribution data in real time and identify user sitting, getting up, and changes in posture. The angle sensor is installed on the sofa's backrest adjustment mechanism to detect the sofa backrest angle in real time, with a detection range of 0°-90° and an accuracy of ±1°. The weight sensor is used to assist in judging the seating status and distinguish the weight difference between the human body and objects. The control module receives data from the multi-sensor module, performs data fusion processing, and outputs control commands according to a preset mapping table. The air pump module includes an air pump, an air tank, multiple solenoid valves, and a pressure sensor. The air pump generates compressed air, and the air tank stores compressed air to ensure inflation speed and pressure stability. The solenoid valves are divided into inlet and outlet valves, with each airbag corresponding to a set of inlet and outlet valves for independent control. The pressure sensor monitors the internal pressure of each airbag in real time and feeds the data back to the control module for closed-loop control. The airbag module includes multiple independently controllable airbag units distributed in areas such as the sofa cushion, lumbar region, backrest, and sides. The airbag material uses polyurethane film or TPU elastic material, which has good airtightness and durability. The shape and size of the airbags are ergonomically designed; for example, the lumbar airbags have a U-shaped structure, and the side airbags have a strip-shaped structure. The airbags are connected to the solenoid valves through air tubes, and their volume and firmness are changed by inflation and deflation to adjust the support force for different parts of the body.

[0018] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a sofa semi-adaptive control method based on multi-sensor fusion provided in an embodiment of the present invention. The method includes steps S110-S150.

[0019] S110. Obtain pressure distribution parameters and seat angle parameters through the pressure sensor array and the angle sensor, respectively; In this embodiment, the pressure distribution parameter refers to the comprehensive pressure-related data collected by the pressure sensor array from key support areas such as the sofa cushion and backrest. The seat angle parameter refers to the angle between the sofa backrest and the base detected by the angle sensor. The pressure sensor array refers to a combination of multiple flexible fabric pressure sensors ergonomically arranged in the key support areas of the sofa. The angle sensor refers to the angle detection sensor installed at the sofa backrest adjustment mechanism, with a detection range of 0° to 90° and a detection accuracy of ±1°. Specifically, after the sofa's semi-adaptive control system is powered on, the pressure sensor array continuously collects real-time pressure data from its arrangement area. After integration and processing by the control module, it forms a pressure distribution parameter containing multi-dimensional pressure information. The angle sensor detects the angle change of the sofa backrest in real time and uses the detected angle value as the seat angle parameter. Both types of parameters are transmitted to the control module of the control system in real time. The control module stores the received parameters in real time and performs basic data preprocessing, eliminating invalid interference data to ensure the integrity and validity of the parameters. Specifically, this step addresses the technical problems of existing technologies, such as the lack of accurate and real-time acquisition methods for sofa occupancy-related status data, or the excessively high hardware costs required for acquisition. Existing simple adaptive solutions do not systematically collect pressure and angle data, failing to provide data support for subsequent control. While fully adaptive solutions can achieve multi-dimensional data acquisition, they require numerous sensors, resulting in high hardware costs. This step achieves accurate multi-dimensional acquisition of pressure and angle data through a lightweight sensor combination, eliminating the need for overly complex and densely packed sensor arrays. This approach controls hardware costs while ensuring comprehensive and real-time data acquisition, laying a reliable data foundation for subsequent occupancy status judgment and airbag inflation adjustment. By achieving real-time, accurate, and low-cost acquisition of sofa pressure and angle status data, effective data support is provided for subsequent occupancy status judgment and airbag inflation threshold matching, ensuring the smooth and orderly execution of subsequent control steps.

[0020] S120. Determine the seating status of the sofa based on the pressure distribution parameters and the preset pressure threshold; In this embodiment, the preset pressure threshold refers to the pressure threshold pre-stored in the control module for determining whether the sofa is occupied. It includes two categories: seating pressure threshold and leaving pressure threshold. The seating state refers to the sofa's state of being occupied or unoccupied, specifically divided into seating and leaving states. Specifically, the control module first retrieves the internally stored preset pressure threshold, then performs a multi-dimensional comparative analysis of the real-time received pressure distribution parameters with the preset pressure threshold. Simultaneously, it combines the overall characteristics of the pressure distribution to determine the sofa's current actual seating state. During the comparative analysis, the control module verifies the validity of the pressure distribution parameters, eliminating invalid data caused by sensor drift, minor external touches, etc., ensuring the accuracy of the seating state judgment. If the judgment determines the seating state to be occupied, subsequent steps related to matching the airbag inflation threshold are triggered; if the judgment determines the leaving state, subsequent steps related to deflating the airbag are triggered. Specifically, this step addresses the technical problem of existing technologies failing to automatically and accurately determine the seat's occupancy status. Existing manual operation schemes rely entirely on user intervention, lacking an automatic occupancy status assessment step. Simple adaptive schemes rely on a simplistic approach to status assessment, prone to misjudgments. This step uses pressure distribution parameters as the core basis for judgment, combined with preset pressure thresholds for systematic analysis and assessment. It achieves automatic occupancy status determination without any user intervention. Furthermore, data validity verification further improves the accuracy of the judgment, preventing unnecessary airbag malfunctions due to misjudgments. By achieving automatic and accurate judgment of the sofa's occupancy status without user intervention, it effectively avoids judgment errors caused by invalid data, providing precise status data for subsequent automated airbag adjustment and significantly enhancing the intelligence level of the control system.

[0021] S130. If the sofa is in a seated state, determine the target airbag inflation threshold corresponding to the seat angle parameter according to the seat angle parameter and the preset airbag inflation threshold mapping table. The preset airbag inflation threshold mapping table stores airbag inflation thresholds that correspond one-to-one with different seat angle parameters. In this embodiment, the preset airbag inflation threshold mapping table refers to a parameter table pre-stored in the control module that establishes a correspondence between sofa seat angle parameters and airbag inflation thresholds. The airbag inflation threshold refers to the critical inflation pressure value required for the airbag to achieve different support forces. The target airbag inflation threshold refers to the inflation pressure value required for an airbag matching the current seat angle parameters; it is the core target value for airbag inflation / deflation operations. Specifically, after determining that the sofa is in a seated state, the control module immediately retrieves the real-time received seat angle parameters and simultaneously calls the internally pre-stored preset airbag inflation threshold mapping table. It matches and retrieves the seat angle parameters against the angle-related parameters in the mapping table. Based on the accurate matching result, it determines the airbag inflation threshold corresponding to the current seat angle parameters and uses this threshold as the target airbag inflation threshold. The control module performs a secondary verification of the matching result to ensure that the target airbag inflation threshold matches the actual usage angle of the current seat. After successful verification, the threshold is transmitted in real-time to the air pump control unit, providing a clear target parameter for subsequent airbag inflation / deflation operations. Specifically, this step addresses the technical problem of existing technologies failing to accurately match airbag inflation volume based on seat angle. Existing simple adaptive solutions adjust airbags solely through pressure complementarity, failing to consider seat angle for targeted inflation volume adjustments. While fully adaptive solutions can achieve dynamic adjustment, they require complex AI algorithms and powerful computing platforms, resulting in excessive costs. This step establishes a fixed correspondence between seat angle and airbag inflation volume using a pre-defined mapping table. This achieves accurate matching between seat angle and airbag inflation volume without requiring complex AI algorithms or numerous sensors, ensuring precise airbag inflation volume adjustment while strictly controlling costs. By achieving precise and rapid matching of seat angle parameters and airbag inflation volume thresholds without complex calculations or high-end hardware support, it ensures a high degree of adaptability between airbag support force and seat usage angle while maintaining controllable costs, effectively improving the accuracy of airbag support for the human body.

[0022] S140. Inflate and deflate the airbag according to the target airbag inflation threshold.

[0023] In this embodiment, an airbag refers to an elastic airbag unit that can be independently inflated and deflated and distributed in areas such as sofa cushions, waist, and back. It mainly includes back airbags and waist airbags. Specifically, the control module transmits the determined target airbag inflation threshold to the air pump module in real time. The air pressure sensor in the air pump module continuously and in real time collects the current actual inflation pressure value of the airbag and compares this value with the target airbag inflation threshold in real time. If the actual pressure value is less than the target airbag inflation threshold, the control module will instruct the air pump to start working and open the corresponding airbag's air intake valve to inflate the airbag until the actual pressure of the airbag reaches the target airbag inflation threshold, and then immediately shut off the air pump and the corresponding air intake valve. If the actual pressure value is greater than the target airbag inflation threshold, the control module will instruct the corresponding airbag's air exhaust valve to deflate the airbag until the actual pressure of the airbag reaches the target airbag inflation threshold, and then immediately shut off the corresponding air exhaust valve. The entire inflation and deflation process achieves closed-loop control through real-time data feedback from the air pressure sensor, ensuring that the airbag pressure can accurately reach the target value. Specifically, this step addresses the technical problem of insufficient precise closed-loop control in existing airbag support adjustment technologies. Because existing simple adaptive solutions lack a clear target inflation value, their adjustment accuracy is extremely low. Manual operation solutions rely entirely on user experience, failing to guarantee precision. This step uses a target airbag inflation threshold as the core adjustment standard, achieving closed-loop control of inflation and deflation through real-time feedback from air pressure sensors. This allows for precise airbag pressure adjustment without any user intervention, ensuring the stability of airbag support. By achieving precise closed-loop control of airbag inflation and deflation, the airbag pressure is ensured to accurately reach the target value, guaranteeing stable and appropriate support from the sofa airbags for the user, effectively improving riding comfort.

[0024] In one embodiment, such as Figure 2 As shown, step S120 includes: S121-S123.

[0025] S121. Determine whether the pressure distribution parameter is greater than a preset pressure threshold and whether the pressure distribution is continuous. S122. If the pressure distribution parameter is greater than or equal to the preset pressure threshold and the pressure distribution is continuous, then the sitting state of the sofa is determined to be the seated state. S123. If the pressure distribution parameter is less than the preset pressure threshold and the duration exceeds the preset duration threshold, then the sitting state of the sofa is determined to be the unseat state.

[0026] In this embodiment, the preset duration threshold refers to the time threshold for determining the seat-off state pre-stored in the control module. It is a time judgment standard set to exclude situations such as brief seat-offs and minor external interference. Continuous pressure distribution means that the pressure data collected by the pressure sensor array forms a continuous pressure coverage in the key area of ​​the sofa where the human body sits, which conforms to the pressure distribution characteristics of human seating. Specifically, the control module first retrieves the real-time pressure distribution parameters from the storage unit, and first determines whether the actual pressure value corresponding to the parameter is greater than or equal to the preset pressure threshold. At the same time, it simultaneously analyzes the overall characteristics of the pressure distribution to determine whether the pressure data forms a continuous pressure distribution state that conforms to the characteristics of human seating in the key area where the human body sits. If both judgment results are yes, the sofa is directly determined to be in a seated state. If the actual pressure value corresponding to the pressure distribution parameter is less than the preset pressure threshold, the control module will immediately start a timing program to monitor the changes in the pressure distribution parameters in real time. If the duration of the low-pressure state reaches and exceeds the preset duration threshold, the sofa is determined to be in a seat-off state. If the pressure distribution parameter recovers to above the preset pressure threshold during the timing process, the timing program is immediately terminated, maintaining the judgment result of the original state of the sofa. Specifically, this step addresses the technical problem of existing technologies that rely solely on pressure values ​​for determining seating status, making them prone to misjudgment due to external interference. Existing simple methods, which judge seating status based solely on pressure readings, are susceptible to misinterpreting situations like placing objects or briefly touching the sofa as sitting, or briefly leaving the seat as leaving, leading to incorrect airbag adjustments. This step combines pressure values ​​and pressure distribution characteristics for seating determination, and pressure values ​​and duration for leaving determination. This multi-dimensional approach effectively eliminates various external interference factors, improving the accuracy of status assessment. By achieving multi-dimensional and accurate judgment of sofa seating status, misjudgments caused by factors such as object placement and brief disturbances are effectively eliminated, improving the accuracy of seating and leaving determination and ensuring the effectiveness and rationality of subsequent airbag adjustment operations.

[0027] In one embodiment, such as Figure 3 As shown, step S120 includes: S124-S127.

[0028] S124. Obtain weight parameters through the weight sensor; S125. Determine the seating status of the sofa based on the weight parameters and the preset weight threshold; S126. If the weight parameter is greater than or equal to the preset weight threshold, the pressure distribution parameter is greater than or equal to the preset pressure threshold, and the pressure distribution is continuous, then the sitting state of the sofa is determined to be the seated state. S127. If the weight parameter is less than the preset weight threshold or the pressure distribution parameter is less than the preset pressure threshold and the duration exceeds the preset duration threshold, then the sitting state of the sofa is determined to be the unseat state.

[0029] In this embodiment, the weight sensor refers to a sensor installed on the support frame under the sofa cushion to detect the weight the sofa bears. The weight parameter refers to the actual weight the sofa currently bears, collected by the weight sensor. The preset weight threshold refers to a weight threshold pre-stored in the control module to distinguish between human and non-human weight objects. Specifically, the weight sensor collects the sofa's load-bearing weight data in real time and converts it into standardized weight parameters, which are then transmitted to the control module in real time. The control module retrieves the internally pre-stored preset weight threshold and combines it with the real-time received weight parameters and pressure distribution parameters for comprehensive judgment. First, it determines whether the weight parameter is greater than or equal to the preset weight threshold. Simultaneously, it determines whether the pressure distribution parameter is greater than or equal to the preset pressure threshold and whether the pressure distribution is continuous. If all three judgments are true, the sofa is determined to be in a seated state. If the weight parameter is less than the preset weight threshold, or the pressure distribution parameter is less than the preset pressure threshold and the duration of this low-pressure state exceeds a preset duration threshold, the sofa is determined to be in an unseated state, provided either condition is met. Throughout the judgment process, the control module synchronously verifies the weight parameter and pressure distribution parameter to ensure consistency in the judgment results of the two types of data. Specifically, this step addresses the technical problem of misjudgment in existing technologies that rely solely on a single pressure parameter to determine seating status. This is because pressure parameters alone cannot effectively distinguish between a person sitting on the sofa and a heavy object placed on it, potentially leading to unnecessary misadjustments of the airbags. This step integrates weight and pressure distribution parameters for comprehensive judgment. It effectively distinguishes between human and non-human weights using weight thresholds and further verifies seating status by combining pressure distribution characteristics, forming a multi-sensor fusion judgment method that significantly improves the accuracy and robustness of the judgment. By implementing multi-sensor fusion for sofa seating status judgment, it can effectively distinguish between human seating and object placement, avoiding misjudgments caused by single-parameter judgments, raising the accuracy of seating and departure detection to a higher level, and significantly enhancing the robustness of the control system.

[0030] In one embodiment, such as Figure 4 As shown, step S130 includes: S131-S132.

[0031] S131. Query the preset airbag inflation threshold mapping table according to the seat angle parameter, and determine the target preset angle range into which the seat angle parameter falls. Each preset angle range is stored in the preset airbag inflation threshold mapping table in one-to-one correspondence with each group of airbag inflation thresholds. Each group of airbag inflation thresholds includes the back airbag inflation threshold and the waist airbag inflation threshold. S132. Obtain the corresponding target back airbag inflation threshold and target waist airbag inflation threshold according to the target preset angle range.

[0032] In this embodiment, the target preset angle range refers to the angle range that matches the current seat angle parameters in the preset airbag inflation threshold mapping table. It is a continuous angle range pre-divided in the mapping table. The back airbag inflation threshold refers to the critical inflation pressure value required for the back airbag to achieve different support forces. The lumbar airbag inflation threshold refers to the critical inflation pressure value required for the lumbar airbag to achieve different support forces. The target back airbag inflation threshold refers to the target inflation pressure value of the back airbag that matches the target preset angle range. The target lumbar airbag inflation threshold refers to the target inflation pressure value of the lumbar airbag that matches the target preset angle range. Specifically, after receiving the seat angle parameters, the control module immediately calls the internally stored preset airbag inflation threshold mapping table. This mapping table divides the angle range of the sofa back from 0° to 90° into multiple consecutive preset angle intervals. Each angle interval uniquely corresponds to a set of parameters including the back airbag inflation threshold and the lumbar airbag inflation threshold. The control module compares the seat angle parameters with each preset angle interval in the mapping table one by one, accurately determines the specific angle interval in which the parameter falls, and takes it as the target preset angle interval. Then, based on the target preset angle interval, it retrieves the corresponding back airbag inflation threshold and lumbar airbag inflation threshold from the mapping table and determines them as the target back airbag inflation threshold and the target lumbar airbag inflation threshold, respectively. After retrieval, the control module performs an adaptability verification on the two sets of thresholds to ensure that they match the actual usage angle of the current seat. Specifically, this step addresses the technical problem in existing technologies that cannot precisely adjust airbags in different areas based on seat angle. Existing simple adaptive solutions interconnect airbags in different areas for adjustment, failing to achieve independent and precise adjustment of each airbag. This step divides the seat angle into multiple continuous intervals and configures independent inflation thresholds for the back and lumbar airbags in each interval. This enables targeted adjustment of airbags in different areas at different seat angles, improving the ergonomic fit of airbag support. By achieving precise matching between seat angle intervals and inflation thresholds for different airbag areas, independent and targeted adjustment of the back and lumbar airbags is achieved, enhancing the ergonomic fit of airbag support and making airbag support at different seat angles more closely match the actual support needs of the human body.

[0033] For example, in this embodiment, the preset airbag inflation threshold mapping table divides the 0°-90° angle range of the sofa back into nine consecutive preset angle intervals. The intervals and their corresponding stored back and lumbar airbag inflation thresholds are as follows: 0°-10° corresponds to 15kPa for the back airbag and 20kPa for the lumbar airbag; 10°-20° corresponds to 20kPa for the back airbag and 25kPa for the lumbar airbag; 20°-30° corresponds to 25kPa for the back airbag and 30kPa for the lumbar airbag; 30°-40° corresponds to 30kPa for the back airbag and 32kPa for the lumbar airbag; 40°-50° corresponds to 32kPa for the back airbag and 35kPa for the lumbar airbag; 50°-60° corresponds to 35kPa for the back airbag and 35kPa for the lumbar airbag. The air pressure is 38 kPa for the back airbag and 40 kPa for the lumbar airbag at 60°-70°. At 70°-80°, the air pressure is 45 kPa for the back airbag and 40 kPa for the lumbar airbag. At 80°-90°, the air pressure is 50 kPa for the back airbag and 40 kPa for the lumbar airbag. If the seat angle parameter detected by the control module in real time is 65°, S131 is executed first to substitute 65° into the preset airbag inflation threshold mapping table for querying. It is determined that the seat angle parameter falls within the target preset angle range of 60°-70°. Then, S132 is executed to directly obtain the corresponding target back airbag inflation threshold of 38 kPa and target lumbar airbag inflation threshold of 40 kPa from the mapping table based on the target preset angle range.

[0034] In one embodiment, such as Figure 5 As shown, step S132 includes: S1321-S1323.

[0035] S1321. Determine height characteristic parameters based on the pressure peak location and the pressure distribution range, determine weight characteristic parameters based on the pressure peak size, and determine body shape characteristic parameters based on the pressure distribution concentration. S1322. Calculate the body shape adjustment coefficient based on the height characteristic parameter, the weight characteristic parameter, and the body shape characteristic parameter; S1323. Adjust the target back airbag inflation threshold and the target waist airbag inflation threshold according to the body shape adjustment coefficient to obtain the adjusted target back airbag inflation threshold and target waist airbag inflation threshold.

[0036] In this embodiment, the pressure peak location refers to the coordinate position of the maximum pressure detected by the pressure sensor array, used to characterize the main support area where the user's body contacts the sofa. The pressure distribution range refers to the longitudinal span of the effective pressure area detected by the pressure sensor array, used to characterize the longitudinal range of the user's body contact with the sofa. The pressure peak magnitude refers to the maximum pressure detected by the pressure sensor array, used to characterize the maximum pressure exerted by the user on the sofa. The pressure distribution concentration refers to the degree of concentration of the pressure distribution, which can be characterized by calculating the standard deviation or variance of the pressure distribution, used to distinguish between thin and overweight body types. The height characteristic parameter is a parameter determined based on the pressure peak location and pressure distribution range, used to characterize the user's height characteristics. The weight characteristic parameter is a parameter determined based on the pressure peak magnitude, used to characterize the user's weight characteristics. The body shape characteristic parameter is a parameter determined based on the pressure distribution concentration, used to characterize the user's body shape characteristics. The body shape adjustment coefficient is a coefficient calculated based on the user's height characteristic parameter, weight characteristic parameter, and body shape characteristic parameter, used to adjust the airbag inflation threshold.

[0037] Specifically, the control module analyzes the main support areas and longitudinal range of the user's body contacting the sofa based on the longitudinal coordinate position of the pressure peak location in the pressure sensor array and the longitudinal span of the pressure distribution range, thereby determining height characteristic parameters. The control module analyzes the maximum pressure exerted by the user on the sofa based on the pressure peak size, thereby determining weight characteristic parameters. The control module analyzes the concentration of pressure distribution based on the pressure distribution concentration, thereby determining body shape characteristic parameters. The control module calculates a body shape adjustment coefficient based on the height, weight, and body shape characteristic parameters. This coefficient reflects the degree to which the user's individual characteristics affect the airbag inflation volume requirement. The control module adjusts the target back airbag inflation volume threshold and the target waist airbag inflation volume threshold based on the body shape adjustment coefficient, using the adjusted inflation volume threshold as the final target inflation volume threshold. In essence, by extracting the user's height, weight, and body shape characteristic parameters based on pressure distribution characteristics and calculating the body shape adjustment coefficient to adjust the airbag inflation volume threshold, the system can automatically adjust the airbag inflation volume according to the user's individual differences, ensuring that users of different body types receive appropriate support, thus solving the problem that preset mapping tables cannot adapt to individual user differences. By adjusting the airbag inflation threshold using a body shape adjustment coefficient, precise support force can be adapted to users of different body shapes, improving user comfort and effectively solving the problem of insufficient adaptability of general fixed thresholds. This significantly improves the riding comfort and airbag support fit of different users.

[0038] In one embodiment, such as Figure 6 As shown, step S1322 includes: S1322a-S1322f.

[0039] S1322a. Calculate the height index based on the weighted sum of the longitudinal coordinate position of the pressure peak position in the pressure sensor array and the longitudinal span of the pressure distribution range; S1322b. Based on the height segment interval where the height index is located, query a preset height offset mapping table to obtain the height offset coefficient. The preset height offset mapping table stores multiple correspondences between height segment intervals and height offset coefficients. The height offset coefficient increases as the height index increases. S1322c. Determine the weight deviation coefficient based on the ratio of the pressure peak value to the preset standard pressure peak value; S1322d. Determine the body shape offset coefficient based on the ratio of the pressure distribution concentration to the preset standard concentration. S1322e. Calculate the product of the height offset coefficient, the weight offset coefficient, and the body shape offset coefficient to obtain the initial body shape adjustment coefficient; S1322f: Limit the initial body shape adjustment coefficient. When the initial body shape adjustment coefficient is greater than the preset upper limit threshold, set the output body shape adjustment coefficient to the preset upper limit threshold. When the initial body shape adjustment coefficient is less than the preset lower limit threshold, set the output body shape adjustment coefficient to the preset lower limit threshold.

[0040] In this embodiment, the height index is a numerical value used to quantify the user's height characteristics, calculated based on the pressure peak location and pressure distribution range. Height segment intervals are pre-defined ranges for the height index, with each segment interval corresponding to a height offset coefficient. A preset height offset mapping table is a data table pre-stored in the control module, which associates multiple height segment intervals with height offset coefficients. The height offset coefficient is a coefficient determined based on the height index and used to adjust the airbag inflation threshold. The preset standard pressure peak is a pre-defined pressure peak value for a standard user, used as a benchmark for calculating the weight offset coefficient. The weight offset coefficient is a coefficient determined based on the ratio of the pressure peak value to the preset standard pressure peak value, used to adjust the airbag inflation threshold. The preset standard concentration is a pre-defined pressure distribution concentration for a standard user, used as a benchmark for calculating the body shape offset coefficient. The body shape offset coefficient is a coefficient determined based on the ratio of the pressure distribution concentration to the preset standard concentration, used to adjust the airbag inflation threshold. The initial body shape adjustment coefficient is the unrestricted body shape adjustment coefficient calculated based on the height offset coefficient, weight offset coefficient, and body shape offset coefficient. The preset upper threshold and preset lower threshold are pre-set boundaries of the value range of the body shape adjustment coefficient, used to limit the initial body shape adjustment coefficient.

[0041] Specifically, the control module calculates a weighted sum based on the longitudinal coordinate position of the pressure peak location within the pressure sensor array and the longitudinal span of the pressure distribution range, using this weighted sum as the height index. The weights of the longitudinal coordinate position and longitudinal span can be adjusted according to the actual application scenario. The control module then looks up the corresponding height offset coefficient in a preset height offset mapping table based on the height segment interval where the height index falls. This preset height offset mapping table stores multiple height segment intervals, each corresponding to a height offset coefficient. The height offset coefficient increases with the height index, meaning taller users have larger height offset coefficients. The control module calculates the ratio of the pressure peak size to a preset standard pressure peak value, using this ratio as the weight offset coefficient. The control module calculates the ratio of the pressure distribution concentration to a preset standard concentration, using this ratio as the body shape offset coefficient. Finally, the control module calculates the product of the height offset coefficient, weight offset coefficient, and body shape offset coefficient, using this product as the initial body shape adjustment coefficient. The control module performs amplitude limiting on the initial body shape adjustment coefficient. When the initial body shape adjustment coefficient is greater than a preset upper threshold, the output body shape adjustment coefficient is set to the preset upper threshold; when the initial body shape adjustment coefficient is less than a preset lower threshold, the output body shape adjustment coefficient is set to the preset lower threshold; and when the initial body shape adjustment coefficient is between the preset upper and lower thresholds, the output body shape adjustment coefficient is set to the initial body shape adjustment coefficient. Specifically, by using a weighted sum to calculate the height index, the accuracy of height judgment is improved by comprehensively considering both the pressure peak position and the pressure distribution range. A preset height offset mapping table is used to achieve a non-linear mapping from the height index to the height offset coefficient, avoiding complex real-time calculations. The weight offset coefficient and body shape offset coefficient are determined by a ratio calculation method, achieving normalization and eliminating the influence of dimensions. The initial body shape adjustment coefficient is calculated comprehensively by a product method, realizing the synergistic superposition of the influence of various factors on the airbag inflation volume. Through amplitude limiting, excessive or insufficient inflation volume caused by extreme body shapes is prevented, ensuring the safety and reliability of the system. By comprehensively calculating multi-dimensional feature parameters and limiting protection, the accurate calculation of body shape adjustment coefficient is achieved, enabling the system to accurately adapt to individual differences of users while ensuring the system's security and reliability.

[0042] For example, in this embodiment, the longitudinal coordinate range of the pressure sensor array along the vertical direction of the sofa back is set to 0-100cm. The weighting coefficient of the longitudinal coordinate of the pressure peak is preset to be 0.6, and the weighting coefficient of the longitudinal span of the pressure distribution range is 0.4. The preset height offset mapping table is divided into five height segment intervals: [0,20), [20,40), [40,60), [60,80), and [80,100]. The height offset coefficients corresponding to each interval are 0.7, 0.8, 1.0, 1.2, and 1.4, respectively. At the same time, the preset standard pressure peak value is 500N, the preset standard concentration is 0.8, and the preset upper limit threshold of the body shape adjustment coefficient is 1.5 and the preset lower limit threshold is 0.6. If the detected pressure peak position for a passenger is 70cm in the longitudinal coordinate of the pressure sensor array, the longitudinal span of the pressure distribution range is 30cm, the pressure peak size is 600N, and the pressure distribution concentration is 0.9, then S1322a is executed first to calculate the height index by weighted summation: height index = 70 × 0.6 + 30 × 0.4 = 42 + 12 = 54; then S1322b is executed to determine that 54 falls within the height segment interval [40, 60), and the corresponding height offset coefficient is obtained from the preset height offset mapping table as 1.0; then S1322c is executed to calculate the pressure peak size and the preset height offset mapping table. Let the ratio of the standard pressure peak be 600 ÷ 500 = 1.2. Then execute S1322d to calculate the ratio of the pressure distribution concentration to the preset standard concentration, and the body shape offset coefficient is 0.9 ÷ 0.8 = 1.125. Continue executing S1322e to multiply the three offset coefficients to obtain the initial body shape adjustment coefficient, which is 1.0 × 1.2 × 1.125 = 1.35. Finally execute S1322f to limit the initial body shape adjustment coefficient. It is determined that 1.35 is within the reasonable threshold range of 0.6 to 1.5, so the final output body shape adjustment coefficient is determined to be 1.35.

[0043] In one embodiment, such as Figure 7 As shown, the method in this embodiment further includes step S150.

[0044] S150. If the sofa is in an unseat state, control the airbag to deflate.

[0045] In this embodiment, the "unoccupied state" refers to the state where no one is sitting on the sofa. Specifically, after the control module determines that the sofa is in the unoccupied state, it immediately sends a unified deflation control command to the air pump module. Upon receiving the command, the air pump module synchronously opens the exhaust valves corresponding to all airbags, controlling all airbags to deflate synchronously. During the entire deflation process, the pressure sensor monitors the pressure changes inside the airbags in real time. When the pressure inside the airbags drops to the initial pressure value preset by the control system, the control module commands all exhaust valves to close, stopping the deflation operation of all airbags and successfully completing the entire unoccupied deflation control process. Specifically, this step addresses the technical problems in existing technologies where airbags are kept under high pressure for extended periods, leading to material fatigue and high energy consumption during subsequent inflation. This is because most existing seat airbag control schemes do not actively deflate the airbags after the seat is removed. Prolonged high pressure accelerates material aging and fatigue, and the increased pressure also prolongs the pump's operating time during subsequent inflation, further increasing overall energy consumption. This step automatically deflates the airbag to its initial pressure value upon detecting the removal of the seat, preventing prolonged pressure on the airbag and reducing pump operating time during subsequent inflation. By automatically deflating the airbag when the seat is removed, long-term fatigue wear on the airbag material is effectively reduced, significantly extending the airbag's lifespan. Simultaneously, it lowers energy consumption during subsequent inflation, improving the energy efficiency of the control system and the overall durability of the equipment.

[0046] Figure 8 This is a schematic block diagram of a sofa semi-adaptive control device 200 based on multi-sensor fusion provided in an embodiment of the present invention. Figure 8 As shown, corresponding to the above-described sofa semi-adaptive control method based on multi-sensor fusion, the present invention also provides a sofa semi-adaptive control device 200 based on multi-sensor fusion. This sofa semi-adaptive control device 200 includes a unit for executing the above-described sofa semi-adaptive control method based on multi-sensor fusion, and the device can be configured in a computer device. Specifically, please refer to... Figure 8 The sofa semi-adaptive control device 200 based on multi-sensor fusion includes: an acquisition unit 201, a judgment unit 202, a query unit 203, and a control unit 204.

[0047] Acquisition unit 201 is used to acquire pressure distribution parameters and seat angle parameters through the pressure sensor array and the angle sensor, respectively; The judgment unit 202 is used to judge the sitting state of the sofa based on the pressure distribution parameters and the preset pressure threshold. The query unit 203 is used to determine the target airbag inflation threshold corresponding to the seat angle parameter according to the seat angle parameter and the preset airbag inflation threshold mapping table if the seating state of the sofa is the seated state. The preset airbag inflation threshold mapping table stores the airbag inflation threshold corresponding to different seat angle parameters in advance. Control unit 204 is used to inflate and deflate the airbag according to the target airbag inflation threshold.

[0048] It should be noted that the sofa semi-adaptive control device 200 based on multi-sensor fusion in this embodiment also includes units that correspond one-to-one with the sofa semi-adaptive control method based on multi-sensor fusion described above. For the sake of brevity, these will not be elaborated here.

[0049] The aforementioned sofa semi-adaptive control device 200 based on multi-sensor fusion can be implemented as a computer program, which can, for example... Figure 9 It runs on the computer device shown.

[0050] Please see Figure 9 , Figure 9 This is a computer device provided in the embodiments of this application. Figure 9 This is a schematic block diagram of a computer device. The computer device 500 can be a sofa or a device inside a sofa.

[0051] See Figure 9 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0052] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a sofa semi-adaptive control method based on multi-sensor fusion.

[0053] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0054] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a sofa semi-adaptive control method based on multi-sensor fusion.

[0055] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 9The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0056] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0057] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0058] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0059] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0060] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0061] Those skilled in the art will 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.

[0062] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0063] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0064] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0065] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0066] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Since these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0067] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A semi-adaptive control method for a sofa based on multi-sensor fusion, characterized in that, The sofa is equipped with a pressure sensor array, an angle sensor, and an airbag; the method includes: Pressure distribution parameters and seat angle parameters are obtained through the pressure sensor array and the angle sensor, respectively. The seating status of the sofa is determined based on the pressure distribution parameters and the preset pressure threshold. If the sofa is in a seated state, the target airbag inflation threshold corresponding to the seat angle parameter is determined according to the seat angle parameter and the preset airbag inflation threshold mapping table. The preset airbag inflation threshold mapping table stores airbag inflation thresholds that correspond one-to-one with different seat angle parameters. The airbag is inflated or deflated according to the target airbag inflation threshold.

2. The method according to claim 1, characterized in that, The airbags include a back airbag, a lumbar airbag, and the step of determining the target airbag inflation threshold corresponding to the seat angle parameters based on the seat angle parameters and a preset airbag inflation threshold mapping table includes: The preset airbag inflation threshold mapping table is queried according to the seat angle parameter to determine the target preset angle range into which the seat angle parameter falls. Each preset angle range is stored in the preset airbag inflation threshold mapping table in one-to-one correspondence with each set of airbag inflation thresholds. Each set of airbag inflation thresholds includes the back airbag inflation threshold and the waist airbag inflation threshold. The corresponding target back airbag inflation threshold and target waist airbag inflation threshold are obtained based on the target preset angle range.

3. The method according to claim 2, characterized in that, The pressure distribution parameters include pressure peak location, pressure distribution range, pressure peak magnitude, and pressure distribution concentration. Following the step of obtaining the corresponding target back airbag inflation volume threshold and target waist airbag inflation volume threshold based on the target preset angle range, the method further includes: Height characteristic parameters are determined based on the location of the pressure peak and the range of pressure distribution; weight characteristic parameters are determined based on the magnitude of the pressure peak; and body shape characteristic parameters are determined based on the concentration of pressure distribution. Calculate the body shape adjustment coefficient based on the height characteristic parameter, the weight characteristic parameter, and the body shape characteristic parameter; The target back airbag inflation threshold and the target waist airbag inflation threshold are adjusted according to the body shape adjustment coefficient to obtain the adjusted target back airbag inflation threshold and target waist airbag inflation threshold.

4. The method according to claim 3, characterized in that, The step of calculating the body shape adjustment coefficient based on the height characteristic parameter, the weight characteristic parameter, and the body shape characteristic parameter includes: The height index is calculated by weighting the pressure peak position in the longitudinal coordinate position of the pressure sensor array with the longitudinal span of the pressure distribution range. Based on the height segment interval in which the height index is located, a preset height offset mapping table is consulted to obtain the height offset coefficient. The preset height offset mapping table stores the correspondence between multiple height segment intervals and height offset coefficients. The height offset coefficient increases as the height index increases. The weight deviation coefficient is determined based on the ratio of the peak pressure value to the preset standard peak pressure value. The body shape offset coefficient is determined based on the ratio of the pressure distribution concentration to the preset standard concentration. Calculate the product of the height offset coefficient, the weight offset coefficient, and the body shape offset coefficient to obtain the initial body shape adjustment coefficient; The initial body shape adjustment coefficient is subjected to a limiting process. When the initial body shape adjustment coefficient is greater than a preset upper limit threshold, the output body shape adjustment coefficient is set to the preset upper limit threshold. When the initial body shape adjustment coefficient is less than a preset lower limit threshold, the output body shape adjustment coefficient is set to the preset lower limit threshold.

5. The method according to any one of claims 1-4, characterized in that, The step of determining the seating status of the sofa based on the pressure distribution parameters and the preset pressure threshold includes: Determine whether the pressure distribution parameter is greater than a preset pressure threshold and whether the pressure distribution is continuous; If the pressure distribution parameter is greater than or equal to the preset pressure threshold and the pressure distribution is continuous, then the sofa is determined to be in a seated state. If the pressure distribution parameter is less than the preset pressure threshold and the duration exceeds the preset duration threshold, then the sofa is determined to be in an unseat state.

6. The method according to claim 5, characterized in that, The sofa is also equipped with a weight sensor. The step of determining the seating status of the sofa based on the pressure distribution parameters and a preset pressure threshold further includes: Weight parameters are obtained through the weight sensor; The seating status of the sofa is determined based on the weight parameters and the preset weight threshold. If the weight parameter is greater than or equal to the preset weight threshold, the pressure distribution parameter is greater than or equal to the preset pressure threshold, and the pressure distribution is continuous, then the sofa is determined to be in a seated state. If the weight parameter is less than the preset weight threshold or the pressure distribution parameter is less than the preset pressure threshold and the duration exceeds the preset duration threshold, then the sofa is determined to be in an unseat state.

7. The method according to claim 1, characterized in that, After the step of determining the seating status of the sofa based on the pressure distribution parameters and the preset pressure threshold, the method further includes: If the sofa is in an unseat state, the airbag is deflated.

8. A semi-adaptive control device for a sofa based on multi-sensor fusion, characterized in that, The apparatus includes a unit for performing the method of any one of claims 1-7.

9. A computer device comprising a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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