Intelligent sofa lifting method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an intelligent sofa lifting method and device, electronic equipment and a storage medium, the method and the device are applied to an intelligent sofa, the intelligent sofa comprises camera equipment, the camera equipment is in communication connection with the intelligent sofa, and the method comprises the following steps: acquiring an image of the intelligent sofa in a preset range through the camera equipment; identifying a target object from the image, wherein the target object is a user whose distance from the intelligent sofa is smaller than a preset first distance value in the image; obtaining human body feature information of the target object; acquiring intelligent sofa base height information matched with the human body characteristic information of the target object according to a preset corresponding relationship between the human body characteristic information and the intelligent sofa base height; and adjusting the height from the base of the intelligent sofa to the ground according to the height information of the base of the intelligent sofa.

Description

Technical Field

[0001] The present application relates to the field of smart home technology, and in particular to a smart sofa lifting method, device, electronic device and storage medium. Background Art

[0002] As a common soft furnishing, smart sofas provide a comfortable resting environment for homes and office spaces. Especially after long hours of sitting or working or being tired, smart sofas provide people with a place to relax and restore their energy. However, people of different heights and needs have different requirements for the height of smart sofas, which makes the height adjustment of smart sofas particularly important. In addition to the basic manual switch, the height-adjustable smart sofa designs currently on the market also introduce advanced methods such as remote control control, smartphone application control, and voice control, which greatly facilitates user operation. However, the existing height-adjustable smart sofas all require manual control of the height of the smart sofa, which is not very convenient. Designing a smart sofa that can automatically realize the height-adjustable function according to the different situations of the target users will bring great convenience, improve the user's comfort, and improve the quality of life. Summary of the invention

[0003] The embodiments of the present application provide a smart sofa lifting method, device, electronic device and storage medium, which can make the smart sofa lift intelligently according to human body feature information, improve convenience and further improve the quality of life of users.

[0004] The first aspect of the present application provides a smart sofa lifting method, which is applied to a smart sofa. The smart sofa includes: a camera device, and the camera device establishes a communication connection with the smart sofa, including:

[0005] Acquire an image within a preset range of the smart sofa by using the camera device;

[0006] Identify a target object from the image, where the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value;

[0007] Obtaining human feature information of the target object;

[0008] According to the preset correspondence between the human body feature information and the height of the smart sofa base, the height information of the smart sofa base matching the human body feature information of the target object is obtained;

[0009] The height of the base of the smart sofa from the ground is adjusted according to the height information of the base of the smart sofa.

[0010] In some possible embodiments, the human feature information of the target object includes the detected height information and age information of the target object, and the correspondence between the human feature information and the height of the smart sofa base includes: the correspondence between the height range value and the height of the smart sofa base, and according to the preset correspondence between the human feature information and the height of the smart sofa base, obtaining the height information of the smart sofa base that matches the human feature information of the target object includes:

[0011] According to the detected height information and age information of the target object, the height interval value of the target object is obtained, and the height range value where the height interval value of the target object is located is matched in the corresponding relationship. According to the height range value where the height interval value is located, the corresponding smart sofa base height value is matched.

[0012] In some possible embodiments, obtaining the target object's height interval value according to the obtained detected height information and age information of the target object includes:

[0013] Extracting the detected height information value and appearance information feature value of the target object identified in the image;

[0014] The detected height information value and the appearance information feature value are input into a preset detection model to obtain the target object height interval value, wherein the detection model is obtained by training an image recognition model by inputting sample height information and sample appearance feature information.

[0015] In some possible embodiments, when there are two or more target users whose height is less than the preset first distance value, inputting the detected height information value and the appearance information feature value into a preset detection model to obtain the target object height interval value includes:

[0016] Inputting the detected height information value and the appearance information feature value of each target object into the preset detection model respectively, and obtaining the height interval value of each target object respectively;

[0017] The method further comprises: inputting the detected height information value and the appearance information feature value of each target object into the preset detection model, and obtaining the detection range value of the age of each target object;

[0018] According to the height range value of the height interval value, the corresponding height value of the smart sofa base is matched, including:

[0019] In the obtained height interval values ​​of each target object, the corresponding height value of the smart sofa base is matched according to the height range value of the target object with the largest age detection range value.

[0020] In some possible embodiments, the smart sofa is provided with a control panel, and the method further includes:

[0021] When receiving a smart sofa base height adjustment instruction input by a user through a control panel, the height of the smart sofa base is adjusted according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa adjustment height information.

[0022] In some possible embodiments, the method further includes: inputting the detected height information value and the appearance information feature value of the target object into the preset detection model, and also obtaining the target object age detection range value;

[0023] The smart sofa is provided with a control panel and a child lock device, and the method further comprises:

[0024] When the age detection range value of the target object that matches the height of the smart sofa base is outside the preset age range value, upon receiving a smart sofa base height adjustment instruction input by the user through the control panel, the height of the smart sofa base is adjusted according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa height adjustment information;

[0025] When the age detection range value of the target object matching the height of the smart sofa base is within the preset age range, the child lock device is activated, and no response is given to the user's adjustment instruction for the height of the smart sofa base received after the child lock device is activated.

[0026] In some possible embodiments, the smart sofa is further provided with an extension plate, the extension plate is rotatably connected to one side of the smart sofa base, the extension plate can be formed around the smart sofa base to form an expanded state connected to the outer side of the smart sofa base and a folded state after being folded toward the bottom of the smart sofa, the outer side of the smart sofa is a side of the smart sofa base opposite to the backrest of the smart sofa, the smart sofa base is also provided with a pressure sensor, and after the child lock is activated, the method further includes:

[0027] Detecting posture information of a user on the smart sofa by using the camera;

[0028] When the posture of the user on the smart sofa is in a preset posture, and the pressure sensor detects that the distance between the user on the smart sofa and the outside of the smart sofa is less than a preset second distance, the extension plate is controlled to be unfolded to an unfolded state.

[0029] The second aspect of the present application provides a smart sofa lifting device, which is applied to a smart sofa. The smart sofa includes: a camera device, and the camera device establishes a communication connection with the smart sofa, including:

[0030] An acquisition module is used to acquire an image within a preset range of the smart sofa through the camera device; identify a target object from the image, wherein the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value; obtain human feature information of the target object; and acquire height information of the smart sofa base that matches the human feature information of the target object according to a preset correspondence between the human feature information and the height of the smart sofa base;

[0031] The processing module is used to adjust the height of the base of the smart sofa from the ground according to the height information of the base of the smart sofa.

[0032] A third aspect of the present application provides an electronic device, including:

[0033] processor;

[0034] a memory for storing instructions executable by the processor;

[0035] Among them, the processor is configured to execute the instructions to implement an intelligent sofa lifting method as described in any one of the embodiments of the first aspect of the present application.

[0036] The fourth aspect embodiment of the present application provides a storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute an intelligent sofa lifting method as described in any one of the embodiments of the first aspect of the present application.

[0037] The technical solution provided by the embodiment of the present application includes at least the following beneficial effects:

[0038] The height of the smart sofa base is automatically adjusted according to the specific human characteristics of the target object (such as height and age) to provide a personalized comfortable experience. By automatically adjusting the height of the smart sofa, users of different heights and needs can get the best sitting posture, improving user comfort and satisfaction. In addition, the height of the sofa is automatically adjusted by using the camera equipment and the preset correspondence, without the need for manual operation by the user, which greatly improves the convenience of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of an application scenario of an intelligent sofa lifting method proposed in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of a process of a smart sofa lifting method proposed in an embodiment of the present application;

[0041] Figure 3A schematic diagram of a flow chart of another intelligent sofa lifting method proposed in an embodiment of the present application;

[0042] Figure 4 A schematic diagram of a flow chart of another intelligent sofa lifting method proposed in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of a flow chart of another intelligent sofa lifting method proposed in an embodiment of the present application;

[0044] Figure 6 A schematic diagram of the structure of an intelligent sofa lifting device proposed in an embodiment of the present application;

[0045] Figure 7 This is a schematic diagram of the structure of another intelligent sofa lifting device proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0047] In order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. For example, the first instruction and the second instruction are to distinguish different user instructions, and their order is not limited. Those skilled in the art can understand that the words "first" and "second" do not limit the quantity and execution order, and the words "first" and "second" do not necessarily limit them to be different.

[0048] It should be noted that, in the embodiments of the present application, words such as "exemplarily" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present related concepts in a specific way.

[0049] In addition, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c, where a, b, c can be single or multiple.

[0050] It should be noted that in the embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0051] As a common soft furnishing furniture, smart sofas are usually composed of cushions, backrests and armrests, providing a comfortable resting environment for home and office spaces. Especially after long hours of sitting or working or being tired, smart sofas provide a place for people to relax and restore their energy, but the height of smart sofas is particularly important for people of different heights and different needs.

[0052] The height-adjustable smart sofa designs currently on the market have adopted electric lifting mechanisms (for example, using electric motors, gears, screws or hydraulic systems to achieve height adjustment) and manual adjustment mechanisms (for example, spiral lifting rods, gas springs, etc.) in mechanical structure design through technological innovation and development, providing flexible adjustment options. In terms of control systems, in addition to basic manual switches, advanced methods such as remote control, smartphone application control and voice control have also been introduced, greatly facilitating user operation. In actual cases, there are designs that achieve sliding and lifting through hidden grooves at the armrests of smart sofas and iron frame fixed cross frames, and there are also smart sofas that automatically unfold storage boards in combination with built-in motors and connecting mechanisms. These designs not only enhance the functionality of smart sofas, but also improve their practicality.

[0053] However, current liftable smart sofas require manual control of the height of the smart sofa. Therefore, designing a smart sofa that automatically realizes the lift function according to different conditions of the target users, such as age, height and other human characteristics will bring great convenience, enhance user comfort and improve the quality of life.

[0054] In view of this, an embodiment of the present application proposes a smart sofa lifting method, which is applied to a smart sofa, wherein the smart sofa includes: a camera device, wherein the camera device establishes a communication connection with the smart sofa, including: acquiring an image within a preset range of the smart sofa through the camera device; identifying a target object from the image, wherein the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value; obtaining human feature information of the target object; acquiring smart sofa base height information matching the human feature information of the target object according to a preset correspondence between the human feature information and the height of the smart sofa base; and adjusting the height of the base of the smart sofa from the ground according to the smart sofa base height information.

[0055] The smart sofa lifting method proposed in the embodiment of the present application obtains the user's image information in real time through the camera device in the smart sofa, and intelligently adjusts the height of the smart sofa base according to the body characteristics in the image, providing a more personalized and comfortable use experience. First, the system can automatically provide a smart sofa adjustment plan that meets the needs according to the user's body characteristics by identifying the user who is close to the smart sofa in real time; secondly, the system accurately adjusts the height of the smart sofa according to the corresponding relationship between the human body characteristics and the height of the smart sofa base, optimizes the user's sitting and lying posture, and avoids the discomfort caused by the improper height of the smart sofa. The user does not need to manually adjust the smart sofa, and the system can automatically adjust according to the body shape and needs, which greatly improves the comfort and convenience, and is particularly suitable for occasions where the smart sofa is used for a long time. In addition, the system can also be personalized according to the needs of each user, meet the use needs of family members of different body shapes, and avoid the discomfort caused by a single height setting. Finally, this method combines intelligent technology with traditional furniture, promotes the development of smart homes, improves the added value of smart sofa products, and conforms to the trend of modern home intelligence. In general, this application provides users with a more intelligent and personalized smart sofa experience through the combination of camera equipment and human body recognition technology, improving the comfort, practicality and intelligence level.

[0056] For example, Figure 1 The following is a schematic diagram of the application scenario of the smart sofa lifting system proposed in the embodiment of the present application. In this scenario, the lifting system of the smart sofa is equipped with a camera to provide a user experience of intelligent lifting smart sofa. The following is a brief introduction to the components in the figure:

[0057] Smart sofa 101: This is the core component of the system, integrating the base, seat, lifting mechanism and other functional components of the smart sofa. Smart sofa 101 can automatically adjust the height of the smart sofa base according to the needs of the user to optimize the user's sitting and lying posture, and improve comfort and convenience.

[0058] Camera device 102: The camera device 102 installed on the smart sofa is used to capture images of the surrounding environment in real time, especially the user's body features. Through image processing technology, the system can identify the user approaching the smart sofa and adjust the height of the smart sofa according to his or her body features to meet the user's personalized needs.

[0059] Among them, the dotted line indicates that the smart sofa can establish a communication connection with the camera device.

[0060] In summary, through the collaborative work of the smart sofa 101 and the camera device 102, the system can realize intelligent control of the lifting of the smart sofa, providing a more humane, comfortable and convenient user experience.

[0061] The following is a detailed explanation of how the smart sofa proposed in the embodiment of the present application is raised and lowered.

[0062] For example, Figure 2 The detailed steps of realizing the lifting of the smart sofa by the smart sofa 101 and the camera device 102 in the embodiment of the present application are as follows:

[0063] Step 201: Acquire an image within a preset range of the smart sofa through the camera device;

[0064] For example, the camera device is usually installed directly above or above the side of the smart sofa to ensure that it can cover the entire smart sofa area and a certain range around it. Such a position design can maximize the field of view while reducing blind spots. The camera device can be an ordinary camera or a 3D camera with depth perception. The 3D camera can not only capture two-dimensional images, but also obtain three-dimensional information of objects, which is very useful for subsequent extraction of human feature information.

[0065] The preset range refers to the area where the camera can effectively capture images, usually a circular or rectangular area centered on the smart sofa. The size of the range can be adjusted according to the actual application scenario. For example, in a home environment, it may be set to a radius of about 3 meters, while in a commercial environment it may be larger.

[0066] Exemplarily, when a user enters a preset range, the camera device is activated and starts capturing images. This trigger condition can be achieved in a variety of ways, for example, using an infrared sensor or passive infrared (PIR). This technology is mainly used to detect infrared radiation from humans or animals, and is often used in security systems, automatic lighting control, smart home devices and other fields. PIR sensors identify moving heat sources, such as human bodies, by detecting changes in infrared radiation in the environment, thereby triggering corresponding actions. The sensor detects that someone has entered the preset range, or the camera device continuously monitors the preset range and detects new objects through image processing technology.

[0067] When the user enters the preset range, the camera device automatically starts capturing images. These images include the user's full body or part of the body, depending on the viewing angle and position of the camera device. In order to ensure the accuracy of subsequent human feature information extraction, the camera device needs to provide high-quality images, which usually means high resolution, good lighting conditions and stable frame rate. Privacy protection must be considered during design and use. For example, the camera device can be set to be enabled only with the user's explicit consent, or anonymization can be performed during image processing to ensure the user's privacy.

[0068] Exemplarily, the image captured by the camera device contains every object that enters the preset range. These objects can be people, pets, or other objects. For human objects, the image will contain the following feature information: height, which estimates the user's height through image analysis; body shape, which identifies the user's body shape, such as fatness, muscle development, etc.; posture, which captures the user's standing or walking posture, which helps with subsequent comfort adjustments. If further identity verification is required, the user's facial features can also be captured, but privacy protection must be taken into account.

[0069] Step 202: identifying a target object from the image, wherein the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value;

[0070] The detailed process is as follows: The smart sofa first receives images acquired from the camera device, which contain all objects within a preset range. Then, the images are preprocessed, including denoising and contrast enhancement, to improve the accuracy of subsequent recognition. Then all objects in the image are recognized.

[0071] Exemplarily, target detection algorithms in computer vision technology, such as real-time target detection algorithms (You Only Look Once, YOLO), single-stage target detection algorithms (Single Shot Multi Box Detector, SSD), etc., are used to identify all objects in the image. These algorithms can detect the bounding boxes of objects in the image and classify them into different categories, such as people, pets, furniture, etc. Pay special attention to human objects in the image. These algorithms can usually identify the outline and key points of the human body. Among them, YOLO is a real-time target detection algorithm that regards the target detection task as a single regression problem and directly predicts the bounding box and category probability from the image pixels. The main feature of YOLO is fast speed and is suitable for real-time application scenarios. SSD is a single-stage target detection algorithm that realizes multi-scale target detection by adding multiple prediction layers to multiple feature maps of convolutional neural networks. SSD achieves a good balance between speed and accuracy and is suitable for application scenarios that require fast detection. It should be noted that the type of the target detection algorithm is not limited in the embodiments of the present application.

[0072] In the embodiment of the present application, if a 3D camera is used, the depth information of each object, that is, the distance between the object and the camera, can be directly obtained.

[0073] When using an ordinary camera, triangulation is a commonly used method. Triangulation estimates the distance between an object and the camera by using geometric principles. The specific steps include: first, use an ordinary camera to capture an image containing the object, and preprocess the image, including denoising and contrast enhancement, to improve the accuracy of subsequent recognition. Then, use an object detection algorithm (such as YOLO, SSD) to identify the object in the image and obtain the bounding box and center point coordinates (u, v) of the object. Next, convert the image coordinates (u, v) to physical coordinates (x, y), which usually requires the intrinsic parameter matrix of the camera (including focal length, image center, etc.). The distance between the object and the camera is calculated using triangulation. Assuming that the optical axis of the camera is perpendicular to the ground, the height of the object is H, the installation height of the camera is h, the focal length of the camera is f, and the height of the object in the image is h_img. The calculation formula is:

[0074] d = H*f / h_img,

[0075] If the installation height of the camera is h, then the actual distance from the object to the ground is (D) = dh. For example, illustratively, the focal length of the camera is 500 pixels, the installation height is 1.5 meters, the actual height of the object is 1.8 meters, the height h_img of the object in the image is 100, the calculated distance is 9 meters, and the actual distance is 7.5 meters. Through these steps, ordinary cameras and image processing technology can be used to effectively estimate the distance between the object and the camera, providing necessary information for the automatic adjustment of the smart sofa. It should be noted that in order to ensure the accuracy of the calculation, the camera needs to be calibrated to obtain the accurate focal length and internal parameter matrix, while considering the influence of environmental factors such as light and background complexity, as well as the errors in the triangulation method.

[0076] The smart sofa presets a first distance value to filter out users whose distance to the smart sofa is less than the first distance value. The distance of each detected human object is compared with the preset first distance value to filter out qualified users. Finally, the system outputs a list of users whose distance to the smart sofa is less than the preset first distance value, and these users are considered to be target objects.

[0077] Through this process, the system can accurately identify users who are closer to the smart sofa, providing a basis for subsequent extraction of human feature information and adjustment of the height of the smart sofa.

[0078] After the target object is identified, the human feature information of the target object is obtained and processed. The details are as follows.

[0079] Step 203: Obtaining human body feature information of the target object;

[0080] The human feature information of the target object includes the detected height information and age information of the target object.

[0081] Step 204: acquiring the height information of the smart sofa base that matches the human body feature information of the target object according to the preset correspondence between the human body feature information and the height of the smart sofa base;

[0082] The correspondence between the human body feature information and the height of the smart sofa base includes: the correspondence between the height range value and the height of the smart sofa base. According to the preset correspondence between the human body feature information and the height of the smart sofa base, the height information of the smart sofa base matching the human body feature information of the target object is obtained, including:

[0083] According to the detected height information and age information of the target object, the height interval value of the target object is obtained, and the height range value where the height interval value of the target object is located is matched in the corresponding relationship. According to the height range value where the height range value is located, the corresponding smart sofa base height value is matched.

[0084] In some possible embodiments, the height interval value can be obtained by a preset detection model, and the steps are as follows: Figure 3 As shown, the method for obtaining the target object's height interval value according to the obtained detected height information and age information of the target object includes:

[0085] Step 301: extracting the detected height information value and appearance information feature value of the target object identified in the image;

[0086] The detected height information value and the appearance information feature value are input into a preset detection model to obtain the target object height interval value, wherein the detection model is obtained by training an image recognition model by inputting sample height information and sample appearance feature information.

[0087] First, extract the appearance information feature value: For example, use image processing technology (such as convolutional neural network) to extract the appearance features of the target object from the image. These features may include facial features, clothing color, hairstyle, etc.

[0088] The extracted appearance feature value is used as input. For example, the appearance feature value can be a multi-dimensional vector representing information such as facial features, clothing color, etc.

[0089] Then, the appearance features are input into a preset detection model: wherein the preset detection model is obtained by training the image recognition model by inputting the sample height information and the sample appearance feature information. The model can predict the height interval value of the target object based on the input height information value and appearance information feature value.

[0090] In the process of model training, a large amount of sample data is used, each sample includes an image, sample height information and sample appearance feature information. Through supervised learning methods, the training model learns the mapping relationship between height information and appearance features and height interval values.

[0091] Step 302: Obtain the target object's height interval value.

[0092] The acquired data feature data is input into the trained detection model to obtain the height range value of the target object.

[0093] An example of the correspondence between human feature information and the height of the smart sofa base is shown below, where the human feature information at least includes: height and age.

[0094] For example, the corresponding relationship between the height range value and the height of the smart sofa base is as follows: a table or database is pre-set to record different height range values ​​and corresponding smart sofa base height values. For example:

[0095] The height range of 150-160cm corresponds to a smart sofa base height of 30cm;

[0096] The height range of 160-170cm corresponds to a smart sofa base height of 35cm;

[0097] The height range of 170-180cm corresponds to a smart sofa base height of 40cm;

[0098] The height range of 180-190cm corresponds to a smart sofa base height of 45cm;

[0099] Obtain the target object's body feature information: obtain the target object's height information through image processing technology.

[0100] For example, the age information of the target object can also be obtained. The age information can help adjust the height of the smart sofa base to meet the needs of users of different age groups.

[0101] Obtaining the target object's height interval value: Determine the target object's height interval value based on the obtained detected height information. For example, if the target object's height is 175cm, then its height interval value is 170-180cm.

[0102] In the correspondence between the preset height range value and the height of the smart sofa base, find the height range value of the target object's height interval value.

[0103] According to the preset correspondence between the human body feature information and the height of the smart sofa base, the smart sofa automatically adjusts its height after the smart sofa base height information matching the human body feature information of the target object is acquired, as shown in step 205 .

[0104] Step 205: adjusting the height of the base of the smart sofa from the ground according to the height information of the base of the smart sofa.

[0105] Exemplarily, according to the found height range value, the corresponding smart sofa base height value is matched. For example, if the height interval value of the target object is 170-180cm, the corresponding smart sofa base height value is 40cm.

[0106] For example, when the smart sofa automatically adjusts its height, its armrests and backrests are also automatically adjusted to a preset height according to the preset height of the smart sofa.

[0107] In some possible embodiments, as mentioned in step 202, the smart sofa outputs a list of users whose distance from the smart sofa is less than a preset first distance value, and these users are considered to be target objects.

[0108] Illustratively, the target object may be one or more than one target object.

[0109] Then, if there are more than two target objects within the preset range, the height is adjusted based on the ages of the users in the user list. When there are two or more target users whose height is smaller than the preset first distance value, the height interval value of the target object is obtained by inputting the detected height information value and the appearance information feature value into the preset detection model, and the height interval value of each target object is obtained. Figure 4 As shown, the method also includes:

[0110] Step 401: inputting the detected height information value and the appearance information feature value of each target object into the preset detection model, and obtaining the detection range value of the age of each target object;

[0111] Step 402: According to the height range value of the height interval value, the corresponding height value of the smart sofa base is matched. In this step, it includes:

[0112] In the obtained height interval values ​​of each target object, the corresponding height value of the smart sofa base is matched according to the height range value of the target object with the largest age detection range value.

[0113] For example, in step 401, the system inputs the detected height information value and appearance information feature value of each target object into a preset detection model, and not only predicts the height interval value of the target object, but also predicts the age detection range value of each target object. The detailed process is as follows:

[0114] like Figure 3 As shown, the height interval value of the target object is obtained, and the age detection range value of each target object is obtained through model detection in a similar way; that is, the extracted detection height information value and appearance information feature value are input into the preset detection model. The model predicts the height interval value and age detection range value of each target object based on the input data.

[0115] For example, the model predicts that the height range of target object A is 170-180cm, and the age detection range is 25-35 years old.

[0116] Step 402: According to the height range value within which the height interval value lies, a corresponding smart sofa base height value is matched.

[0117] In step 402, the system selects the height interval value of the target object with the largest age detection range value according to the height interval value and age detection range value of each target object, and matches and obtains the corresponding height value of the smart sofa base. The detailed process is as follows:

[0118] Select the target object with the largest age detection range value: Among all target objects, compare their respective age detection range values ​​and select the target object with the largest age detection range value.

[0119] Example: Assume that the camera device detects two target objects, the age detection range of target object A is 25-35 years old, and the age detection range of target object B is 60-70 years old. Then target object B is selected.

[0120] First, match and obtain the corresponding height value of the smart sofa base: First, obtain the height interval value: According to the height interval value of the selected target object, obtain its corresponding height range value. For example, the height interval value of target object B is 175-185cm. Then, in the correspondence between the preset height range value and the height of the smart sofa base, find the height value of the smart sofa base corresponding to the height range value of target object B of 175-185cm. For example, the height value of the smart sofa base corresponding to 175-185cm is 40cm.

[0121] For example, after further identifying the height interval value through the age range identified by the system, if the age of the target object is greater than the preset range, for example, the target object is an elderly person over 60 years old, the corresponding smart sofa base height obtained by matching the height interval value should be set one level higher than the height of younger young people.

[0122] Exemplarily, when the age of the target object is classified into the age range of the elderly, if the height of the target object is greater than the preset height range, the smart sofa is raised to a second preset height. After the target object sits on the smart sofa, the smart sofa is raised to a first preset height within the height range of the target object. The first preset height is less than the second preset height, wherein the second preset height is a height that is one level higher than the height of the smart sofa that matches the height. A higher height is set to make it easier for the elderly to sit on the smart sofa.

[0123] In some possible embodiments, the smart sofa is further provided with a control panel, and the method further comprises:

[0124] When receiving a smart sofa base height adjustment instruction input by a user through a control panel, the height of the smart sofa base is adjusted according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa adjustment height information.

[0125] For example, before sitting down, the smart sofa is pre-set to a higher height for easy sitting, and then gradually lowered to a smart sofa height that matches the height range after sitting down. However, for different target objects, there will be different suitable smart sofa heights. Then, the height can be adjusted through the adjustment button on the control panel of the smart sofa to address the differences of different groups, meet the needs of target users, and improve comfort.

[0126] For example, anyone over the age of 10 can use this adjustment button to self-adjust the height of the smart sofa.

[0127] However, in some possible embodiments, for the safety of younger children, such as children under 10 years old or even younger, to prevent the child from hurting himself when pressing the adjustment button, the smart sofa can also automatically activate the child lock when the age information of the target object received from the camera is less than the preset age range, so as to prevent the child from adjusting the height of the smart sofa by himself through the adjustment button. Therefore, in addition to the method proposed in the embodiment of the present application, the method also includes: the detected height information value and the appearance information feature value of the target object are input into the preset detection model, and the target object age detection range value is obtained; the smart sofa is provided with a control panel and a child lock device, and the method also includes:

[0128] When the age detection range value of the target object that matches the height of the smart sofa base is outside the preset age range value, upon receiving a smart sofa base height adjustment instruction input by the user through the control panel, adjusting the height of the smart sofa base according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa adjustment height information;

[0129] When the age detection range value of the target object matching the height of the smart sofa base is within the preset age range, the child lock device is activated, and no response is given to the user's adjustment instruction for the height of the smart sofa base received after the child lock device is activated.

[0130] The child lock is a safety feature that aims to prevent children or other unauthorized users from misoperating the device, thereby avoiding potential safety risks or damage. In the context of the smart sofa proposed in the embodiment of the present application, the child lock function can ensure that children cannot adjust the height of the smart sofa base at will, thereby ensuring their safety and the normal operation of the device.

[0131] The child lock can reduce safety risks caused by misoperation by limiting the use of the adjustable function of the smart sofa by younger children. For example, it can prevent children from adjusting the height of the smart sofa base without adult supervision, which may cause falls or other accidental injuries.

[0132] In addition, it can ensure that the device settings are not accidentally changed, keeping the device running in a preset and safe state.

[0133] When the child lock function is activated, the related control buttons or certain functions on the touch screen will be locked and cannot respond to user operations. Usually a specific operation or password is required to unlock the child lock. For example, the user may need to press and hold a button for a few seconds or enter a preset password to unlock.

[0134] In an embodiment of the present application, the smart sofa will display an indicator light or screen prompt when the child lock is activated to inform the user that the device is in a locked state.

[0135] Through these functions and mechanisms, the child lock ensures the safety and stability of the smart sofa during use. Especially in a family environment with children, the child lock function is particularly important and can effectively prevent accidental injuries caused by misoperation of children.

[0136] In some possible embodiments, for younger children, in order to prevent safety problems caused by falling from the smart sofa, the smart sofa is further provided with an extension plate, and the extension plate is rotatably connected to one side of the smart sofa base. The extension plate can be formed around the smart sofa base to form an unfolded state connected to the outer side of the smart sofa base and a folded state after being folded toward the bottom of the smart sofa. The outer side of the smart sofa is the side of the smart sofa base opposite to the backrest of the smart sofa. A pressure sensor is also provided on the smart sofa base. After the child lock is activated, Figure 5 As shown, in addition to the smart sofa lifting method proposed in the embodiment of the present application, the method also includes:

[0137] Step 501: Detecting the posture information of the user on the smart sofa through the camera;

[0138] The smart sofa detects the posture information of the user on the smart sofa through the camera, which may include the user's sitting posture, standing posture, etc. In the embodiment of the present application, some specific postures are preset, such as standing, sitting on the edge of the smart sofa, etc., which are considered to be possible safety risks.

[0139] Step 502: When the user posture on the smart sofa is in a preset posture, and the pressure sensor detects that the distance between the user on the smart sofa and the outside of the smart sofa is less than a preset second distance, the extension plate is controlled to unfold to an unfolded state.

[0140] The extension plate of the smart sofa is rotatably connected to one side of the smart sofa base, and can form two states around the smart sofa base: an unfolded state and a folded state. The outside of the smart sofa refers to the side of the smart sofa base relative to the backrest of the smart sofa. A pressure sensor is also provided on the base of the smart sofa. It is used to detect the position of the user on the smart sofa. The smart sofa presets a distance value (for example, 20 cm) to determine whether the user is close to the outside of the smart sofa. When the distance between the user and the outside of the smart sofa is less than this preset second distance, the system considers that the user is at risk of falling.

[0141] When the system detects that the user is in a preset posture and detects through the pressure sensor that the user is less than a preset second distance from the outside of the smart sofa, the system will control the extension plate to unfold to the unfolded state. After the extension plate is unfolded, the support area of ​​the smart sofa can be increased to prevent the user from falling from the smart sofa, especially for younger children, providing additional safety protection.

[0142] Exemplarily, the system detects through a camera device that a child is standing on the edge of a smart sofa.

[0143] The pressure sensor detects that the child is 19 cm away from the outside of the smart sofa, which is less than the preset second distance of 20 cm. The child is detected to be standing and less than 20 cm away from the outside of the smart sofa, which meets the conditions for deploying the extension board. The smart sofa controls the extension board to deploy, increasing the support area of ​​the smart sofa to prevent the child from falling off the smart sofa.

[0144] Exemplarily, the length and width of the extension plate can be designed according to the size of the smart sofa. Generally, the length of the extension plate can be 30-50 cm, and the width can be 1 / 3 to 1 / 2 of the width of the smart sofa base.

[0145] For example, the extension plate can be connected to one side of the smart sofa base through a hinge, and can be easily unfolded and folded. When not in use, the extension plate can be folded back to the bottom of the smart sofa without affecting normal use.

[0146] Exemplarily, when the user leaves the smart sofa or is no longer in a preset posture, the system controls the extension plate to automatically fold back to the bottom of the smart sofa and restore it to its original state.

[0147] Through these functions and mechanisms, the smart sofa can not only automatically adjust the height of the smart sofa base according to the height and age information of the target object, but also activate the child lock and extension board under certain circumstances to ensure the safety of children and the normal operation of the equipment.

[0148] In some possible embodiments, the method further includes:

[0149] When the detected height information value and the appearance information feature value are input into a preset detection model and it is detected that the detected height information value and the appearance information feature value are abnormal values, an abnormal prompt is output.

[0150] Exemplarily, the smart sofa determines whether the input detected height information value and appearance information feature value are abnormal values. Abnormal values ​​may include data that does not conform to human characteristics, such as pets or objects.

[0151] When the input height information value and appearance information feature value are detected as abnormal values, the system will output an abnormal prompt. The abnormal prompt can be output in many ways, such as: Voice prompt: The smart sofa sends a voice prompt through the built-in speaker to inform the user that an abnormal value has been detected.

[0152] For example: Control panel prompt: The system displays a prompt message on the control panel of the smart sofa to inform the user that an abnormal value has been detected.

[0153] The smart sofa can also use voice prompts and control panel prompts at the same time to ensure that users can notice abnormal situations in time.

[0154] For example, the smart sofa extracts a height information value of 30cm of a target object through image processing technology, and extracts the appearance feature values ​​of the object, including four legs, hair, etc.

[0155] This information is input into the preset detection model. Based on the input height information value and appearance information feature value, the model determines that the object is a pet, not a human. The smart sofa detects that the input height information value and appearance information feature value are abnormal values.

[0156] The smart sofa issues a voice prompt through the built-in speaker: "Non-human object detected, please confirm." And a prompt message is displayed on the control panel of the smart sofa: "Non-human object detected, please confirm." After this, the smart sofa does not automatically adjust the height of the smart sofa according to the characteristic information of the pet.

[0157] Through these functions, the smart sofa can effectively detect and prompt abnormal values ​​to ensure the normal operation of the system and the safety of users. This function is very important in practical applications, especially in a home environment, to prevent misoperation and unnecessary safety hazards.

[0158] In some possible embodiments, the smart sofa is further provided with a human physiological characteristic detection device, and the method further includes:

[0159] When it is detected that there is a user on the smart sofa, the physiological characteristic parameters of the user on the smart sofa are detected by the human physiological characteristic detection device, and the physiological characteristic parameters include at least one of heart rate and blood pressure. When it is detected that the heart rate or blood pressure of the user on the smart sofa is abnormal, the height value of the smart sofa is adjusted to help the physiological characteristic parameters of the user on the smart sofa return to normal.

[0160] Exemplarily, adjusting the height value of the smart sofa also includes adjusting the inclination angle of the backrest of the smart sofa.

[0161] Exemplarily, when it is detected that a user is on the smart sofa, the system detects the user's physiological characteristic parameters, including heart rate and blood pressure, through a human physiological characteristic detection device.

[0162] The smart sofa presets the normal range values ​​of heart rate and blood pressure for different groups. For example, the normal heart rate range is 60-100 beats / minute, and the normal blood pressure range is 90-120mmHg (systolic pressure) and 60-80mmHg (diastolic pressure).

[0163] The smart sofa compares the detected physiological characteristic parameters with the preset normal range values ​​to determine whether there is an abnormality. If the heart rate or blood pressure exceeds the normal range, the physiological characteristic parameters are considered abnormal.

[0164] For example, when a user sits on a smart sofa, if it is detected that the user's heart rate is higher than a normal range, the smart sofa will adjust and increase the inclination angle of the smart sofa backrest to help the user lie down, relax and lower the heart rate.

[0165] If the user's heart rate is detected to be lower than the normal range, the smart sofa will adjust and reduce the inclination angle of the smart sofa backrest to help the user restore his heart rate.

[0166] If the user's blood pressure is detected to be higher than the normal range, the smart sofa will adjust and reduce the inclination angle of the smart sofa backrest to help the user relax and lower blood pressure.

[0167] If the user's blood pressure is detected to be lower than the normal range, the smart sofa will adjust and increase the inclination angle of the smart sofa backrest to help the user restore blood pressure.

[0168] Exemplarily, the above measures only play a mitigating role. When the user's blood pressure reaches a dangerous critical value, the smart sofa will give voice reminders and alarms and take emergency measures, such as automatically contacting emergency contacts and calling emergency numbers.

[0169] It should be understood that although Figure 2-5The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-5 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0170] In some embodiments, Figure 6 As shown, a smart sofa lifting device 600 is provided, including: an acquisition module 601, a processing module 602, wherein:

[0171] The acquisition module 601 is used to acquire an image within a preset range of the smart sofa through the camera device; identify a target object from the image, wherein the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value; obtain human feature information of the target object; and acquire height information of the smart sofa base that matches the human feature information of the target object according to a preset correspondence between the human feature information and the height of the smart sofa base;

[0172] The processing module 602 is used to adjust the height of the base of the smart sofa from the ground according to the height information of the base of the smart sofa.

[0173] For further definition of the intelligent sofa lifting device, please refer to the definition of an intelligent sofa lifting method above, which will not be repeated here. Each module in the above device 600 can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the terminal device in hardware form, or can be stored in the memory in the terminal device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0174] Another embodiment provides a storage medium for storing a computer program. The computer program includes instructions for implementing the method described in the embodiment of the present application. By installing the computer program on a computer, the computer can execute the corresponding method.

[0175] Another embodiment provides a computer program product, which includes computer program codes. When these computer program codes are run on a computer, they enable the computer to implement the method proposed in the embodiment of the present application. In this way, the user can implement the intelligent sofa lifting method of the embodiment of the present application by using this computer program product.

[0176] For example, Figure 7 It is a schematic block diagram of another intelligent sofa lifting device provided in an embodiment of the present application.

[0177] Figure 7 The smart sofa lifting device 700 shown is composed of four main parts: a processor 701, a memory 702, a communication interface 703 and a bus 704. Each part has its specific function and role, and these components and their functions in the embodiment of the present application will be explained in detail below.

[0178] Processor 701 is the core control unit of the smart sofa lifting device, responsible for performing various calculation and control tasks. It processes data from various sensors and user input, runs preset algorithms and models, and controls the lifting and other functions of the smart sofa. It runs image processing algorithms, posture detection algorithms, physiological feature detection algorithms, etc. According to the detection results and preset rules, it controls the lifting and lowering of the smart sofa, the start and stop of the child lock, the unfolding and folding of the extension board, etc.

[0179] The memory 702 is used to store various data and programs required for the operation of the system. It includes but is not limited to the operating system, application programs, configuration files, user data, detection models, etc. It stores the operating system and application programs to ensure that the system can start and run normally. It also stores user data, sensor data, detection results, etc.

[0180] The communication interface 703 is responsible for exchanging data with other devices and systems. It can include wired and wireless communication interfaces, such as Wi-Fi, Bluetooth, USB, etc. It can transmit data with external devices (such as smart phones, tablet computers, smart home systems, etc.) to achieve remote control and data synchronization. It can also connect various sensors (such as cameras, pressure sensors, human physiological characteristics detection devices, etc.) to receive and send data.

[0181] The bus 704 is a communication channel connecting various components, ensuring efficient transmission of data and signals between various components, and transmitting data and control signals between components such as the processor 701, the memory 702, and the communication interface 703.

[0182] Through the collaborative work of these components, the smart sofa can automatically detect the user's body information characteristics, and adjust the height of the smart sofa and unfold the extension board according to the detection results to ensure the user's comfort and safety.

[0183] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0184] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor executes the instructions in the memory, and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0185] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present application.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0187] In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0188] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0189] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0190] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0191] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the embodiment of the present application, which should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

Claims

1. A smart sofa lifting method, characterized in that: Applied to a smart sofa, the smart sofa comprises: a camera device, the camera device establishes a communication connection with the smart sofa, including: Acquire an image within a preset range of the smart sofa by using the camera device; Identify a target object from the image, where the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value; Obtaining human feature information of the target object; According to the preset correspondence between the human body feature information and the height of the smart sofa base, the height information of the smart sofa base matching the human body feature information of the target object is obtained; The height of the base of the smart sofa from the ground is adjusted according to the height information of the base of the smart sofa.

2. The method according to claim 1, characterized in that The human feature information of the target object includes the detected height information and age information of the target object. The corresponding relationship between the human feature information and the height of the smart sofa base includes: the corresponding relationship between the height range value and the height of the smart sofa base. According to the preset corresponding relationship between the human feature information and the height of the smart sofa base, the height information of the smart sofa base matching the human feature information of the target object is obtained, including: According to the detected height information and age information of the target object, the height interval value of the target object is obtained, and the height range value where the height interval value of the target object is located is matched in the corresponding relationship. According to the height range value where the height interval value is located, the corresponding smart sofa base height value is matched.

3. The method according to claim 2, characterized in that The step of obtaining the height interval value of the target object according to the detected height information and age information of the target object comprises: Extracting the detected height information value and appearance information feature value of the target object identified in the image; The detected height information value and the appearance information feature value are input into a preset detection model to obtain the target object height interval value, wherein the detection model is obtained by training an image recognition model by inputting sample height information and sample appearance feature information.

4. The method according to claim 3, characterized in that: When there are two or more target users whose height is less than the preset first distance value, inputting the detected height information value and the appearance information feature value into a preset detection model to obtain the target object height interval value includes: Inputting the detected height information value and the appearance information feature value of each target object into the preset detection model respectively, and obtaining the height interval value of each target object respectively; The method further comprises: inputting the detected height information value and the appearance information feature value of each target object into the preset detection model, and obtaining the detection range value of the age of each target object; According to the height range value of the height interval value, the corresponding height value of the smart sofa base is matched, including: In the obtained height interval values ​​of each target object, the corresponding height value of the smart sofa base is matched according to the height range value of the target object with the largest age detection range value.

5. The method according to claim 3, characterized in that: The smart sofa is provided with a control panel, and the method further comprises: When receiving a smart sofa base height adjustment instruction input by a user through a control panel, the height of the smart sofa base is adjusted according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa adjustment height information.

6. The method according to any one of claim 3, characterized in that: The method further comprises: inputting the detected height information value and the appearance information feature value of the target object into the preset detection model, and obtaining the target object age detection range value; The smart sofa is provided with a control panel and a child lock device, and the method further comprises: When the age detection range value of the target object that matches the height of the smart sofa base is outside the preset age range value, upon receiving a smart sofa base height adjustment instruction input by the user through the control panel, adjusting the height of the smart sofa base according to the adjustment instruction input by the user, wherein the height adjustment instruction includes smart sofa adjustment height information; When the age detection range value of the target object matching the height of the smart sofa base is within the preset age range, the child lock device is activated, and no response is given to the user's adjustment instruction for the height of the smart sofa base received after the child lock device is activated.

7. The method according to claim 6, characterized in that The smart sofa is further provided with an extension plate, the extension plate is rotatably connected to one side of the smart sofa base, the extension plate can be formed around the smart sofa base to form an unfolded state connected to the outer side of the smart sofa base and a folded state after being folded toward the bottom of the smart sofa, the outer side of the smart sofa is a side of the smart sofa base opposite to the backrest of the smart sofa, the smart sofa base is also provided with a pressure sensor, and after the child lock device is activated, the method further includes: Detecting posture information of a user on the smart sofa by using the camera device; When the posture of the user on the smart sofa is in a preset posture, and the pressure sensor detects that the distance between the user on the smart sofa and the outside of the smart sofa is less than a preset second distance, the extension plate is controlled to be unfolded to an unfolded state.

8. An intelligent sofa lifting device, characterized in that: Applied to a smart sofa, the smart sofa comprises: a camera device, the camera device establishes a communication connection with the smart sofa, including: An acquisition module is used to acquire an image within a preset range of the smart sofa through the camera device; identify a target object from the image, wherein the target object is a user in the image whose distance from the smart sofa is less than a preset first distance value; obtain human feature information of the target object; and acquire height information of the smart sofa base that matches the human feature information of the target object according to a preset correspondence between the human feature information and the height of the smart sofa base; The processing module is used to adjust the height of the base of the smart sofa from the ground according to the height information of the base of the smart sofa.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement a smart sofa lifting method as described in any one of claims 1-7.

10. A storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute an intelligent sofa lifting method as described in any one of claims 1 to 7.

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