Smart wearable system based on AI recognition and LED content display social service

Abstract

The present invention relates to the technical fields of artificial intelligence, intelligent wearable systems, etc., and provides an intelligent wearable system based on AI recognition and an LED content display social clothing. By setting a user end and setting a flexible LED display screen, a body state sensor and a control host on the social clothing body, the body state sensor collects the current body state data of the user wearing the social clothing body, and the user end provides an interactive interface to display special user group options to the user for the user to select the user group. The control host outputs the current demand state of the wearing user according to the recognition of the current body state data and the special user group, queries a preset social content library according to the current demand state to obtain social speech adapted to the current demand state of the wearing user, and controls the flexible LED display screen to display the social speech, thereby realizing the provision of intuitive and accurate meaning display, and providing more effective social assistance for the special user group.

Description

Technical Field

[0001] The present invention relates to the technical fields of artificial intelligence, smart wearable systems, and in particular to a smart wearable system based on AI recognition and LED content display social clothing. Background Art

[0002] At present, some clothing with social attributes mainly assists social interaction by installing LED light strips on clothing and using LED light display. However, clothing based on LED light strips cannot meet the social assistance needs of some special groups, for example, assisting autistic patients in expressing their needs. Moreover, clothing based on LED light strips is not a real social clothing in the strict sense. Clothing based on LED light strips cannot be displayed to the outside world with intuitive words, and the meaning conveyed is not intuitive and accurate, which is not conducive to accurate assistance in social interaction.

[0003] In summary, existing clothing with LED light strips has technical problems such as failing to provide intuitive and accurate meaning display and failing to provide more effective social assistance. Summary of the invention

[0004] In view of the deficiencies in the above-mentioned prior art, the present invention provides an intelligent wearable system based on AI recognition and LED content display social clothing, so as to provide intuitive and accurate meaning display and provide more effective social assistance for special user groups.

[0005] In a first aspect, the present invention provides an intelligent wearable system based on AI recognition, comprising:

[0006] A social service body, wherein a flexible LED display screen is distributed on the social service body;

[0007] A body state sensor, which is distributed in the inner layer of the social service clothing body and is used to collect current body state data of a user wearing the social service clothing body;

[0008] The user terminal runs the smart wear system APP, and the smart wear system APP displays special user group options to the user through an interactive interface, so that the user can select the user group;

[0009] A control host is mounted on the social service body and is connected and communicated with the user terminal, the flexible LED display and the body state sensor; the control host includes an AI recognition module and a control module running on a main board; the AI ​​recognition module outputs the current demand state of the wearing user based on the recognition of the current body state data and special user groups; the control module queries a preset social content library based on the current demand state to obtain social language adapted to the current demand state of the wearing user, and controls the flexible LED display to display the social language.

[0010] In a second aspect, the present invention provides a LED content display social clothing, and the LED content display social clothing applies the above-mentioned AI recognition-based smart wearable system.

[0011] Compared with the prior art, the present invention has the following beneficial effects:

[0012] The present invention provides an intelligent wearable system based on AI recognition and an LED content display social clothing. Through the social clothing body, a user end is set and a flexible LED display screen, a body state sensor and a control host are set on the social clothing body. The body state sensor is distributed in the inner layer of the social clothing body and is used to collect the current body state data of a wearing user wearing the social clothing body. The user end runs an intelligent wearable system APP. The intelligent wearable system APP displays special user group options to the user through an interactive interface for the user to select the user group. The control host is connected and communicated with the user end, the flexible LED display screen and the body state sensor. The control host includes an AI recognition module and a control module running on a main board. The AI ​​recognition module outputs the current demand state of the wearing user according to the recognition of the current body state data and the special user group. The control module queries a preset social content library according to the current demand state to obtain a social speech adapted to the current demand state of the wearing user, and controls the flexible LED display screen to display the social speech, thereby realizing the provision of intuitive and accurate meaning display, and providing more effective social assistance for special user groups. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their description are used to explain the present invention and do not constitute an improper limitation of the present invention. Some specific embodiments of the present invention will be described in detail in an exemplary and non-restrictive manner with reference to the drawings. The same reference numerals in the drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the drawings:

[0014] Figure 1 This is a schematic diagram of the architecture of an intelligent wearable system based on AI recognition according to an embodiment of the present invention;

[0015] Figure 2 It is a schematic diagram of the architecture of the social service entity according to an embodiment of the present invention.

[0016] Figure 3 It is a schematic diagram of the architecture of a user terminal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only an embodiment of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0018] Embodiment 1

[0019] See also Figure 1-Figure 3 This embodiment provides an AI-based smart wearable system, including:

[0020] A social service body, wherein a flexible LED display screen is distributed on the social service body;

[0021] A body state sensor, which is distributed in the inner layer of the social service clothing body and is used to collect current body state data of a user wearing the social service clothing body;

[0022] The user terminal runs the smart wear system APP, and the smart wear system APP displays special user group options to the user through an interactive interface, so that the user can select the user group;

[0023] A control host is mounted on the social service body and is connected and communicated with the user terminal, the flexible LED display and the body state sensor; the control host includes an AI recognition module and a control module running on a main board; the AI ​​recognition module outputs the current demand state of the wearing user based on the recognition of the current body state data and special user groups; the control module queries a preset social content library based on the current demand state to obtain social language adapted to the current demand state of the wearing user, and controls the flexible LED display to display the social language.

[0024] It should be noted that the social service body, as the core carrier of the intelligent wearable system, integrates other modules (such as body status sensors and control hosts) to facilitate users to wear and interact socially. The flexible LED display is used to present specific social words and convey the user's needs or status to the outside world in an intuitive and dynamic way. Compared with traditional LED light strips, flexible LED displays can clearly express complex content in the form of text and images, making up for the shortcomings of traditional LED light strips in conveying a single meaning. In addition, flexible LED displays can ensure the comfort of clothing and adapt to a variety of wearing scenarios.

[0025] It should also be noted that the body state sensors are distributed in the inner layer of the social service and are used to collect the real-time body state data of the wearer (such as heart rate, blood pressure, blood oxygen, skin temperature, etc.). The body state sensors provide real-time monitoring of the user's body state, which can reflect the user's real state (such as anxiety, fatigue, hunger), and provide accurate data support for the analysis of the AI ​​recognition module.

[0026] It should also be noted that the smart wear system APP running on the user side provides an interactive interface, allowing users to actively select their own special user group type (such as the deaf-mute, autistic patients, depression patients, etc.). The smart wear system APP sets the special user group type option to clarify the user's personalized needs and transmits the selection information to the control host. The control host can provide more precise social assistance based on the needs of specific users through the special user group type selected by the user side.

[0027] It should also be noted that the control host integrates the AI ​​recognition module and the control module, which is the core operation and decision-making part of the entire system. The AI ​​recognition module generates the user's current demand state by analyzing the user's current physical state data and the type of special user groups. The control module queries the social content library according to the user's current demand state, outputs the adapted social speech, and controls the flexible LED display screen for display, thereby integrating the physical state data and user selection information, intelligently judging the user's actual needs, and improving the accuracy of the judgment. In addition, the control module can preset the social content library, dynamically match user needs, and output appropriate social speech in real time, thereby improving the social assistance effect of the system. Among them, the preset social content library can support the personalized expression needs of different user groups. For example, for the deaf and mute, the content library can provide more direct personalized expression; for patients with autism, the content library can focus on emotional prompts.

[0028] In some preferred embodiments, when the AI ​​recognition module identifies that the special user group selected by the user is an autistic patient, the current physical state data of the identified autistic patient is analyzed, and the current demand state of the autistic patient is output. The control module queries the preset social content library according to the current demand state of the autistic patient to obtain the social speech adapted to the current demand state of the autistic patient, and controls the flexible LED display screen to display the social speech adapted to the current demand state of the autistic patient. It should be noted that autistic patients usually encounter difficulties in social interaction, and they may not be able to effectively express their emotions, needs or discomfort. The behavioral expression of autistic patients sometimes does not conform to conventional social patterns, and they may be very sensitive to environmental stimuli (such as sound, vision, touch). Therefore, by identifying their demand state through physical state data (such as heart rate, skin electrical activity, etc.), effective social assistance can be provided for them without relying on traditional language expression. For the emotions and needs of autistic patients, a more objective reflection can be obtained through physical state data, such as heart rate, skin electrical activity, muscle tension, etc., which can more accurately reflect their physical state. For example, when autistic patients feel anxious or stressed, changes in their physical state, such as increased heart rate and increased skin electrical activity, will occur. By analyzing these physical state data, the AI ​​recognition module can determine the patient's emotional and demand status, thereby providing personalized help. In addition, autistic patients often feel uneasy or stressed when facing complex social situations, such as crowded crowds, environmental noise, etc., which may cause them to be unable to express their needs or emotions in time. In this case, the AI ​​recognition module can actively identify their emotional state (such as anxiety, irritability, etc.), and give clear and appropriate social words through the flexible LED display to help patients overcome social barriers. In addition, the needs of autistic patients in social activities may vary from person to person, and their demand status is usually not obvious. Recognizing specific physical state data through the AI ​​recognition module can not only provide patients with real-time emotional feedback, but also provide others with a way to understand the patient's current state through quantitative data (such as heart rate, skin electrical activity, etc.). For example, in public places, seeing the text prompts on the flexible LED display, others can understand the patient's needs, such as "I feel anxious, please give me space." In one example, suppose an autistic patient encounters anxiety in a social situation, and the physical state data is as follows: Heart rate: 115 beats per minute (high, indicating anxiety). Electrodermal activity (EDA): significantly increased (indicating tension). Temperature: skin temperature slightly decreased (indicating discomfort or increased stress). Based on these physical state data, the AI ​​recognition module analyzes that the patient is in an anxious state, which may be caused by stress caused by the external environment (such as a noisy crowd), and then outputs the corresponding social language on the flexible LED display, for example, "I feel anxious, please give me some space, thank you!".

[0029] In some preferred embodiments, when the AI ​​recognition module recognizes that the special user group selected by the user is a deaf-mute, the current physical state data of the identified deaf-mute is analyzed, and the current demand state of the deaf-mute is output. The control module queries the preset social content library according to the current demand state of the deaf-mute to obtain the social speech adapted to the current demand state of the deaf-mute, and controls the flexible LED display screen to display the social speech adapted to the current demand state of the deaf-mute. It should be noted that deaf-mute people usually encounter more difficulties in social occasions due to limited hearing and inability to communicate verbally. Since they cannot express their needs through traditional voice communication, deaf-mute people often rely on body language or sign language to communicate, but this may not be efficient or understood in some occasions. Therefore, analyzing the emotions and needs of deaf-mute people based on physical state data (such as heart rate, skin electrodermal activity, respiratory rate, etc.) can provide necessary social assistance without verbal communication. In this embodiment, through the AI ​​recognition module, the judgment module and the flexible LED display screen, the system can automatically identify the current demand state of the deaf-mute and generate social speech when the deaf-mute cannot express, thereby effectively overcoming the communication barriers faced by the deaf-mute. For example, when the deaf-mute feels nervous or anxious, the heart rate and skin electrical activity may rise, which can provide important information for the AI ​​recognition module. The AI ​​recognition module can accurately analyze and output the current demand state of the deaf-mute, and provide corresponding social speech through the control module, thereby reducing misunderstandings and increasing the effectiveness of communication. In addition, the deaf-mute has long faced a sense of isolation in social interactions because they cannot use language to express themselves like ordinary people. With the assistance of the smart wearable system in this embodiment, the deaf-mute can get timely help when encountering specific needs. For example, when feeling tired, anxious or needing help, the system can automatically generate social speech, which can not only reduce communication barriers, but also enhance the social participation of the deaf-mute. In some examples, suppose a deaf-mute is attending a social gathering. Due to the noisy environment, he feels a little anxious, and the physical state data is as follows: heart rate: 110 beats per minute (slightly higher than the baseline value, indicating anxiety). Electrodermal activity (EDA): significantly increased (indicating tension). Accelerometer data: The data shows that the user is stationary and shows signs of not adapting to the environment. The AI ​​recognition module infers that the user is in a state of anxiety and tension based on the increase in heart rate and electrodermal activity. Combined with the static data of the accelerometer, it is judged that the user may feel that the environment is oppressive or too noisy and needs to seek quiet. The control module queries the social content library according to the needs of the deaf-mute person, selects appropriate social language, and controls the display of the flexible LED display. For example, the flexible LED display is controlled to display: "I am a little anxious. Please help me find a quiet place. Thank you!"

[0030] In some preferred embodiments, when the AI ​​recognition module recognizes that the special user group selected by the user is the elderly, the current physical state data of the elderly identified is analyzed, and the current demand state of the elderly is output. The control module queries the preset social content library according to the current demand state of the elderly to obtain social speech adapted to the current demand state of the elderly, and controls the flexible LED display screen to display the social speech adapted to the current demand state of the elderly. It should be noted that the elderly often face multiple challenges due to changes in physical state, psychology, social and cognitive aspects, including physical health problems (such as hypertension, heart disease), cognitive impairment (such as Alzheimer's disease) and social isolation. The elderly may not be good at expressing their needs, especially when they have sudden health problems or emotional fluctuations, they may not be able to express them accurately through words, and even find it difficult to actively seek help. In this embodiment, the AI ​​recognition module analyzes the physical state data of the elderly (such as heart rate, blood pressure, skin temperature, etc.), can evaluate their physical condition in real time, and infer the current demand state of the elderly based on this data, so as to provide customized social assistance, help the elderly to express their needs accurately and timely, and avoid emotional distress or health risks caused by the inability to express themselves. In addition, the emotions and physical health of the elderly are often manifested as fluctuations in physical state data. For example, an increase in heart rate and blood pressure may mean emotional agitation or health problems, and changes in skin electrical activity may reflect tension or anxiety. When the elderly experience physical discomfort, emotional fluctuations, or cognitive impairment, they may not be able to effectively express their needs through language or behavior. Through the real-time data collected by the body state sensor, the AI ​​recognition module can capture these changes more objectively and accurately. For many elderly people, especially those with cognitive impairments (such as Alzheimer's disease), they may not be able to express themselves effectively in complex social situations, or find it difficult to find the right language to deal with social interactions when they are anxious or stressed. By querying the social content library through the control module and generating social words that are suitable for the current physical state of the elderly, the system can actively help them express their needs, whether it is seeking help, requesting rest, or expressing discomfort, thereby reducing the difficulties that the elderly may encounter in social situations. Especially in the case of sudden health problems or emotional distress, the system can assist the elderly to speak up, making it easier for them to gain understanding and help from others. In some examples, suppose an elderly person is in poor health and has the following physical status data: Blood pressure: 170 / 100 mmHg (high blood pressure, indicating physical tension). Heart rate: 110 beats per minute (high, indicating increased physical load). Skin temperature: low (possibly due to poor blood circulation or long periods of inactivity). Accelerometer data: shows that the user has been inactive for a long time and is in a sitting position.The AI ​​recognition module analyzes the elderly's current physical condition data (such as high blood pressure, high heart rate, and long periods of inactivity) and determines that the user may be in a state of physical discomfort or anxiety. At this time, the control module can query the social content library, select social words suitable for the elderly, and control the display of the flexible LED display. For example, "I feel a little uncomfortable, please help me."

[0031] In some preferred embodiments, when the AI ​​recognition module recognizes that the special user group selected by the user is an anxiety patient, the current physical state data of the anxiety patient identified is analyzed, and the current demand state of the anxiety patient is output. The control module queries the preset social content library according to the current demand state of the anxiety patient to obtain the social speech adapted to the current demand state of the anxiety patient, and controls the flexible LED display screen to display the social speech adapted to the current demand state of the anxiety patient. It should be noted that anxiety is a common mental health problem. Patients usually experience excessive tension, worry, and anxiety, accompanied by physical symptoms such as increased heart rate, rapid breathing, muscle tension, etc. These symptoms sometimes cause patients to be unable to clearly express their needs, or have difficulty making rational judgments in high anxiety situations. Many anxiety patients cannot find appropriate language or behavior to express themselves when they are emotionally excited, and may not even be able to actively seek help. By real-time monitoring of the physical state data of anxiety patients (such as heart rate, skin electrode activity, breathing rate, etc.), the AI ​​recognition module can timely capture the signs of emotional fluctuations of anxiety patients, and automatically analyze the patient's demand state. The flexible LED display screen is controlled by the judgment module to display social speech adapted to the current demand state of the anxiety patient, thereby effectively assisting the anxiety patient in social interaction and reducing the communication barriers caused by anxiety. In some examples, it is assumed that an anxiety patient is participating in a social event, the surrounding environment is noisy and unfamiliar, and the patient's physical state data is as follows: Heart rate: 115 beats per minute (significantly higher than the normal range, indicating anxiety). Skin electrode activity (EDA): significantly increased (indicating tension). Acceleration sensor data: The data shows that the patient is pacing in place, showing signs of restlessness. The AI ​​recognition module determines that the patient is in a state of anxiety and tension based on the heart rate, skin electrode activity and acceleration sensor data, and outputs the current demand state that the anxiety patient feels very nervous and may need to seek help or request a rest. The control module queries the social content library according to the current demand state, selects social speech suitable for the current anxiety patient, and controls the flexible LED display screen to display. For example, the flexible LED display screen can be controlled to display "I feel a little nervous now and need to be alone."

[0032] In some preferred embodiments, the flexible LED display screens are distributed in key areas of the social clothing body, including the chest and shoulders, and the flexible LED display screens in each key area operate independently under the control of the control module. Furthermore, the social speech displayed by the flexible LED display screens in different areas of the chest and shoulders is the same or different. It should be noted that the chest and shoulders, as key parts of the human body, have high visual conspicuity, especially in social occasions that require others to understand and respond quickly. By setting flexible LED display screens in these areas, different social speech can be displayed in real time more flexibly according to user needs.

[0033] In some preferred embodiments, when the flexible LED display screen displays the social talk, it supports the display of the social talk in different colors, different fonts, and different font sizes. It should be noted that changes in color, font, and font size can effectively convey different emotions and emotional intensities. For example, the use of red may indicate urgency or strong emotions, such as anger and anxiety; while blue is usually associated with calmness and relaxation. Changes in font thickness, shape (such as italics, bold, etc.) and font size can also further express changes in emotions or the priority of information.

[0034] In some preferred embodiments, the preset social content library includes different specialized social speech, and the different specialized social speech is used to provide different user groups. It should be noted that each user group (such as autistic patients, deaf-mute people, anxiety patients, etc.) has unique needs, expressions and ways of understanding in social interaction. By providing specially customized social speech for different user groups, it can be ensured that the system can effectively and accurately support the social interaction of the group in each social occasion. For example, autistic patients may encounter difficulties in face-to-face communication, and traditional social speech may not be suitable for them. For the autistic group, the content in the social speech library can include concise and direct expressions, avoiding complex or ambiguous language, so as to help them express their needs more clearly and reduce social pressure. In addition, different groups usually show different emotional and behavioral characteristics in social situations. For example, anxiety patients may tend to avoid social interaction or need more space, while deaf-mute people may need to express or receive information in a visual way. By customizing specialized social speech, personalized social support can be provided according to their characteristics and needs, reducing misunderstandings, conflicts or social barriers. For example, when someone with anxiety is feeling uneasy, the social arsenal might include specialized lines such as “I need some space, please talk later” or “I’m feeling a little anxious, please give me some time.”

[0035] In some preferred embodiments, the body state sensor includes a plurality of special body state sensors for collecting different types of body state data, and the plurality of special body state sensors are distributed in the inner layer of the social service body, close to different parts of the human body. It should be noted that different types of body state sensors can monitor and collect physiological data of different dimensions. For example, heart rate, body temperature, skin electrical activity, electromyographic signals, etc. can all reflect different body states. By deploying a variety of sensors in different parts, the system can capture the user's physical state more comprehensively and accurately.

[0036] In some preferred embodiments, the multiple special body state sensors include a heart rate sensor, a galvanic skin response sensor, a temperature sensor, an electromyographic sensor, and an acceleration sensor; the heart rate sensor is located in the chest area of ​​the inner layer of the social service body, close to the chest of the human body; the galvanic skin response sensor is located in the wrist area of ​​the inner layer of the social service body, close to the wrist of the human body; the temperature sensor is located in the armpit area of ​​the inner layer of the social service body, close to the armpit of the human body; the electromyographic sensor is located in the shoulder area of ​​the inner layer of the social service body, close to the shoulder of the human body; the acceleration sensor is located in the waist area of ​​the inner layer of the social service body, close to the waist of the human body. It should be noted that the chest area, especially above the sternum, close to the heart, is the most suitable part for monitoring heart rate. Changes in heart rate directly reflect the user's emotional state, health status and physical exertion, especially in emotional states such as anxiety, tension, and excitement, the heart rate usually changes significantly. By arranging the heart rate sensor in the chest area, the changes in heartbeat can be accurately captured in real time. Galvanic skin response (EDA) sensors monitor changes in the conductivity of the skin surface, which is closely related to emotional responses (such as anxiety, stress, excitement, etc.). The wrist is a convenient location for arranging and collecting galvanic skin response data. At the same time, because the skin on the wrist is thinner, the sensor can more sensitively capture changes in conductivity. Human body temperature is an important indicator of health and physiological status. The armpit is an area with sensitive temperature changes. The fluctuation of body temperature will change significantly, especially when there are emotional changes, physical movements or health abnormalities. The armpit position can detect small changes in body temperature more accurately. Electromyographic sensors are used to monitor the electrical activity of muscles, especially changes in muscle tension. The shoulder area is a part of the human body that is prone to accumulating muscle tension in daily life. Especially in cases of anxiety, stress, physical fatigue, etc., the muscle activity and tension of the shoulder will increase significantly. By arranging electromyographic sensors in the shoulder area, the relaxation or tension of the muscles can be accurately monitored. Accelerometers are used to monitor the body's movement state, including posture changes, gait, activity intensity, etc. The waist is the core part of human activity and can well reflect the body's movement state and posture changes. The acceleration sensor placed at the waist can accurately capture the user's activities, such as walking, running, standing, etc.

[0037] In some preferred embodiments, the AI ​​recognition module includes: a data preprocessing unit for preprocessing the current body state data to generate clean and standardized body state data; a feature extraction unit for extracting features from the clean and standardized body state data to obtain body state data suitable for model processing; a multimodal fusion analysis model for analyzing and processing the body state data suitable for model processing, and outputting the current demand state of the wearer. It should be noted that the raw data collected by the sensor is often affected by noise, interference, sensor accuracy and data loss. The role of the data preprocessing unit is to ensure that the data input to the subsequent processing module is of good quality and reliable. By denoising, standardizing and filling missing values, the data preprocessing unit can remove interference factors, making subsequent analysis more accurate. The data preprocessing unit unifies different types of sensor data into a processable standard format to avoid the inability of the model to effectively process data due to inconsistent formats. In addition, raw physiological data is usually high-dimensional and complex, and directly inputting it into a machine learning model may result in large computational complexity, low processing efficiency and inaccurate results. Through the feature extraction unit, representative and highly recognizable features can be extracted from the original data, thereby reducing the dimension, increasing the processing speed and focusing on key information. The feature extraction algorithm can design specific extraction rules or methods based on the physiological characteristics of different user groups (such as autistic patients, the elderly, anxiety patients, etc.). The physiological responses of different people may be different, and the feature extraction process can be optimized for these differences. For example, for patients with anxiety, the fluctuation of heart rate (such as fluctuation frequency and amplitude) and the intensity change of skin electrical response are used as key features; the feature extraction unit extracts the maximum fluctuation amplitude and fluctuation frequency from the continuous heart rate and skin electrical data for subsequent analysis. It should be noted that the core of the multimodal fusion analysis model is to fuse the body state data from different sensors for comprehensive analysis. Since the data of a single sensor may not fully reflect the user's physiological and emotional state, the fusion of multiple sensor data can provide more comprehensive information. For example, different types of signals such as heart rate, skin electrical response, temperature, etc. can jointly reveal the user's emotional state (such as anxiety, anger, comfort, etc.). Multimodal fusion can improve recognition accuracy and avoid misjudgment due to the failure of a single signal. In addition, the multimodal analysis model can be personalized based on individual differences. By learning from different user groups, the model can identify the unique patterns of each user in a specific physiological state, thereby more accurately predicting the user's needs. For example, for patients with autism, sudden changes in heart rate may represent overstimulation, while increased skin electrical response may indicate anxiety. By fusing these two signals, the model can more accurately infer the patient's needs.In general, in this embodiment, the data preprocessing unit ensures data quality, unified format and removes noise, providing clean and standardized data for subsequent processing; the feature extraction unit extracts effective features from clean and standardized data, reduces dimensions and highlights key information, and provides more concise and meaningful data for analysis; the multimodal fusion analysis model conducts a comprehensive analysis of the features extracted from different sensors to increase the accuracy, robustness and personalization capabilities of the model, thereby better realizing the identification and feedback of user demand status. It can be understood that the specific algorithms and processing procedures of the data preprocessing unit, the feature extraction unit and the multimodal fusion analysis model are conventional technologies in the field and are not described in detail in this embodiment.

[0038] In some further preferred embodiments, the flexible LED display screens are distributed on the front chest, shoulder and back areas of the social service body, and different flexible LED display screens work independently under the control of the control host; a PPG sensor is set in the front chest area of ​​the social service body near the left chest position, and a fall detection sensor is set in the shoulder area or back area of ​​the social service body, and the control host is connected and communicated with the PPG sensor and the fall detection sensor; the PPG sensor monitors the user's heart rate data in real time, and the control host obtains the heart rate data and compares it with the user's baseline heart rate range to obtain a sharp change in the user's heart rate, and the sharp change in heart rate represents a sudden change in the user's heart rate. The fall detection sensor monitors the user's motion state in real time, and the control host obtains the motion state and compares it with the preset speed change and posture change range to obtain the user's fall event, which is manifested as the user's speed change and posture change exceeding the preset speed change and posture change range; when the fall event is obtained and there is no sudden heart rate change, the control host controls the flexible LED display screen in the shoulder area to enter the high-brightness flashing mode; when the fall event is obtained and there is a sudden heart rate change, the control host controls the flexible LED display screens in the back area, shoulder area and chest area to enter the high-brightness, fast-flashing SOS mode. It should be noted that the left side of the chest is close to the heart area and has rich blood flow signals. The PPG sensor can detect pulse waves and heart rate changes more accurately at this position. The blood flow in this area is strong, which can provide stable and clear pulse data, which is conducive to real-time monitoring of heart rate status. Moreover, the chest position is relatively stable when worn, and is not easily disturbed by the arm or other movements, and is suitable for long-term and accurate heart rate monitoring. This position design helps to improve the accuracy and continuity of heart rate data. In addition, the shoulder and back areas are key areas for user posture changes and movement direction changes. The shoulder sensor can keenly capture the user's tilt angle, while the back area is close to the center of gravity of the human body, which is suitable for detecting significant changes in acceleration and gravity direction. Fall events are usually accompanied by drastic changes in acceleration and posture. Sensors in the shoulder or back area can accurately detect these characteristic signals, such as rapid pitch, rotation or rollover, thereby improving the accuracy of fall detection. Moreover, the shoulder and back areas are relatively stable during normal movement (such as walking and running), so they can effectively reduce false alarms, increase the reliability of fall detection, and improve user experience. In addition, the control host can comprehensively analyze the changes of the PPG sensor's heart rate data and the fall sensor's motion state data by obtaining the heart rate data of the PPG sensor and the motion state data of the fall sensor. When a fall event is detected without a sharp change in heart rate, only a slight reminder is required, and when a sharp change in heart rate and a fall event occur at the same time, it is judged as an emergency. When a user falls but the heart rate does not change sharply, it is judged as a general fall event.At this time, the flexible LED display screen in the shoulder area is controlled to enter the high-brightness flashing mode, which can attract the attention of nearby people so as to get the necessary attention and help. At the same time, turning on the high-brightness flashing mode only in the shoulder area can not only serve as a warning, but also reduce unnecessary energy consumption. Moreover, the flashing at the shoulder position is easy to be discovered by others, which is conducive to getting quick help. When the user falls and is accompanied by a sharp change in heart rate, it is identified as a serious emergency state, and the user may have cardiovascular problems or loss of consciousness. At this time, the full-body high-brightness, fast-flashing SOS mode is activated to send out an obvious distress signal. The synchronous high-brightness fast flashing of the chest, back and shoulders can attract the attention of people around from all directions. In particular, the fast-flashing SOS mode can transmit a signal for help, which is convenient for others to identify and help.

[0039] Embodiment 2

[0040] See also Figure 1-Figure 3 The present embodiment provides a social wear with LED content display, and the social wear with LED content display applies the smart wear system based on AI recognition described in any of the above embodiments, by setting a user end and setting a flexible LED display screen, a body state sensor and a control host on the social wear body, the body state sensor is distributed in the inner layer of the social wear body, and is used to collect the current body state data of the user wearing the social wear body, the user end runs the smart wear system APP, and the smart wear system APP displays special user group options to the user through an interactive interface for the user to select the user group, the control host is connected and communicated with the user end, the flexible LED display screen and the body state sensor, the control host includes an AI recognition module and a control module running on the main board, the AI ​​recognition module outputs the current demand state of the wearing user according to the recognition of the current body state data and the special user group, the control module queries the preset social content library according to the current demand state to obtain the social speech adapted to the current demand state of the wearing user, and controls the flexible LED display screen to display the social speech, thereby realizing the provision of intuitive and accurate meaning display, and providing more effective social assistance for special user groups.

[0041] It should be pointed out that the above embodiments are only preferred specific implementation modes of the present invention, and the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An intelligent wearable system based on AI recognition, characterized in that: include: A social service clothing body, wherein a flexible LED display screen is distributed on the social service clothing body; the flexible LED display screen is distributed on the front chest, shoulder and back areas of the social service clothing body; A body state sensor, which is distributed in the inner layer of the social service clothing body and is used to collect current body state data of a user wearing the social service clothing body; The user terminal runs the smart wear system APP, and the smart wear system APP displays special user group options to the user through an interactive interface, so that the user can select the user group; A control host, mounted on the social service body, is connected and communicated with the user terminal, the flexible LED display screen and the body state sensor; the control host includes an AI recognition module and a control module running on a main board; the AI ​​recognition module outputs the current demand state of the wearing user according to the recognition of the current body state data and the special user group; The control module queries a preset social content library according to the current demand state to obtain social speech adapted to the current demand state of the wearing user, and controls the flexible LED display screen to display the social speech; The AI ​​recognition module includes: a data preprocessing unit, used to preprocess the current body state data to generate clean and standardized body state data; a feature extraction unit, used to extract features from the clean and standardized body state data to obtain body state data suitable for model processing; a multimodal fusion analysis model, used to analyze and process the body state data suitable for model processing, and output the current demand state of the wearing user; The preset social content library includes different specialized social speech, and the different specialized social speech is used to provide to different user groups; when the AI ​​recognition module recognizes that the special user group selected by the user is autistic patients, the current physical state data of the identified autistic patients is analyzed, and the current demand state of the autistic patients is output; the control module queries the preset social content library according to the current demand state of the autistic patients to obtain the social speech adapted to the current demand state of the autistic patients, and controls the flexible LED display to display the social speech adapted to the current demand state of the autistic patients; when the AI ​​recognition module recognizes that the special user group selected by the user is deaf-mute, the current physical state data of the identified deaf-mute is analyzed, and the output The current demand state of the deaf-mute, the control module queries the preset social content library according to the current demand state of the deaf-mute to obtain social language adapted to the current demand state of the deaf-mute, and controls the flexible LED display screen to display the social language adapted to the current demand state of the deaf-mute; when the AI ​​recognition module recognizes that the special user group selected by the user is an anxiety patient, the current physical state data of the anxiety patient identified is analyzed, and the current demand state of the anxiety patient is output. The control module queries the preset social content library according to the current demand state of the anxiety patient to obtain social language adapted to the current demand state of the anxiety patient, and controls the flexible LED display screen to display the social language adapted to the current demand state of the anxiety patient; The different flexible LED display screens work independently under the control of the control host; a PPG sensor is arranged in the front chest area of ​​the social service body near the left chest position, and a fall detection sensor is arranged in the shoulder area or the back area of ​​the social service body, and the control host is connected and communicated with the PPG sensor and the fall detection sensor; the PPG sensor monitors the user's heart rate data in real time, and the control host obtains the heart rate data and compares it with the user's baseline heart rate range to obtain the user's sudden heart rate change, and the sudden heart rate change indicates that the user's heart rate suddenly rises or falls, and there is a high risk problem; the fall detection sensor is real The control host monitors the user's motion state, and the control host obtains the motion state and compares it with the preset speed change and posture change range to obtain the user's fall event, and the fall event is manifested as the user's speed change and posture change exceeding the preset speed change and posture change range; when the fall event is obtained and the sudden heart rate change does not exist, the control host controls the flexible LED display screen in the shoulder area to enter the high-brightness flashing mode; when the fall event is obtained and the sudden heart rate change exists, the control host controls the flexible LED display screens in the back area, shoulder area and front chest area to enter the high-brightness, fast-flashing SOS mode.

2. The AI ​​recognition-based smart wearable system according to claim 1, characterized in that: The flexible LED display screens are distributed in key areas of the social service body, including the chest and shoulders. The flexible LED display screens in each key area work independently under the control of the control module.

3. The AI ​​recognition-based smart wearable system according to claim 2, characterized in that: The social talk displayed on the flexible LED display screens in different areas of the chest and the shoulders is the same or different.

4. The AI ​​recognition-based smart wearable system according to claim 1, characterized in that: When the flexible LED display screen displays the social talk, it supports displaying the social talk in different colors, different fonts and different font sizes.

5. The AI ​​recognition-based smart wearable system according to any one of claims 1 to 4, characterized in that: The body state sensors include a variety of special body state sensors that collect different types of body state data. The various special body state sensors are distributed in the inner layer of the social service body and are close to different body parts of the human body.

6. The AI ​​recognition-based smart wearable system according to claim 5, characterized in that: The multiple special body state sensors include a heart rate sensor, a skin galvanic response sensor and a temperature sensor; the heart rate sensor is located in the chest area of ​​the inner layer of the social service body, close to the chest of the human body; the skin galvanic response sensor is located in the wrist area of ​​the inner layer of the social service body, close to the wrist of the human body; the temperature sensor is located in the armpit area of ​​the inner layer of the social service body, close to the armpit of the human body.

7. The AI ​​recognition-based smart wearable system according to claim 6, characterized in that: The multiple special body state sensors also include electromyographic sensors and acceleration sensors; the electromyographic sensors are located in the shoulder area of ​​the inner layer of the social service body, close to the shoulders of the human body; the acceleration sensors are located in the waist area of ​​the inner layer of the social service body, close to the waist of the human body.

8. An LED content display social service, characterized in that: The LED content display social clothing application is an AI recognition-based smart wearable system as described in any one of claims 1-7.

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