Micro-space traditional chinese medicine adaptive planning and ai self-learning regulation method based on global health care of family environment

Abstract

This invention discloses a micro-space TCM-adaptive planning and AI self-learning control method based on holistic health care in the home environment, involving the fields of family health care and intelligent environmental control technology. The method includes the following steps: S1, Initialization and Record Building: The user inputs and stores the physical condition test reports of all family members and the distribution map of the family's micro-spaces into the system. This micro-space TCM-adaptive planning and AI self-learning control method based on holistic health care in the home environment deeply integrates TCM constitution theory with family micro-space planning. Through TCM constitution record building, it clarifies the basic constitution, chronic diseases, and allergens of family members, and marks and divides each micro-space in the home according to its location, function, lighting, and ventilation. This achieves TCM-adaptive planning of the micro-spaces. Simultaneously, it matches specific environmental parameters for each space according to different constitutions, upgrading family environmental control from physical parameter adjustment to personalized adaptation to meet the needs of human health care.

Description

Technical Field

[0001] This invention relates to the field of family health care and intelligent environment control technology, specifically to a micro-space TCM adaptive planning and AI self-learning control method based on the whole-domain health care of the family environment. Background Technology

[0002] With the popularization of the concept of healthy living, smart home devices have gradually achieved basic control over the indoor environment. However, the existing home environment control and health care system still has many shortcomings and is difficult to meet the personalized and comprehensive health care needs based on traditional Chinese medicine constitution.

[0003] First, existing home environment control mainly involves adjusting physical parameters such as temperature, humidity, and lighting. It is impossible to develop personalized environmental control strategies based on the different physical conditions and chronic diseases of family members. The environment is poorly adapted to human health and wellness, which in turn interferes with the user's comfort experience. Second, the existing control methods have poor self-learning and iteration capabilities, and can only operate according to fixed parameters. They cannot dynamically adjust the control strategies according to the behavioral habits, physical changes of family members and the changing seasons. At the same time, they ignore the functional differences of different micro-spaces in the family and cannot achieve precise control across the entire area. Third, existing home environment monitoring and control equipment lacks systematic integration, and the data interoperability between various sensors and smart home devices is poor. It is impossible to achieve full-domain perception and linkage analysis of environmental data, physiological data, and behavioral data. Furthermore, micro-space health and wellness planning is not carried out in conjunction with spatial characteristics such as orientation, lighting, and ventilation, and the health and wellness value of space utilization is not fully realized. Summary of the Invention

[0004] The purpose of this invention is to provide a micro-space TCM adaptive planning and AI self-learning regulation method based on the whole-domain health care of the home environment, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a micro-space TCM adaptability planning and AI self-learning regulation method based on holistic health care in the home environment, comprising the following steps: S1. Initial file creation: Users enter the physical fitness test reports of all family members and the distribution map of family micro-spaces into the system for recording and storage, and install corresponding sensors in each micro-space area for full-area perception and monitoring. S2. Baseline Learning and Adaptation Process: When the user enables AI, the AI ​​automatically learns the user's habits based on the environmental baseline data and the behavioral baselines of the user's family members, and automatically generates initial adaptation rules based on the loaded content of the TCM rules. S3. Daily Real-time Operation: Real-time collection of environmental data (temperature, humidity, light, sound, air), physiological data (heart rate, respiration, sleep, posture), and behavioral data (activity, location) through sensors. Based on the collected data, TCM reasoning and judgment are performed, and then the optimal control command is output to control smart home devices in a coordinated manner. At the same time, the changes in the environment and the user's physiology and comfort after the control are monitored and the monitoring data is sent back to the AI ​​for real-time monitoring and control processing. S4, AI self-learning iterative update: Fine-tuning thresholds (such as temperature ±0.5℃, brightness ±5%) based on daily, weekly, and last day of the month; updating scene strategies (morning, daytime, sleep, and weekend) for the purpose of comfort, physical improvement, and energy saving; and judging biased improvement values ​​through physical fitness retest data. At the same time, the AI ​​model performs adaptation strategy reset processing based on solar terms and seasons. S5, Traditional Chinese Medicine Assisted Intervention Process: When AI identifies an imbalance in a user's constitution or the risk of invasion of the six pathogenic factors, it will be automatically triggered. At this time, tiered intervention will be used to assist in regulation, and the constitution indicators will be re-monitored 24 hours after the intervention to track the effect. Then, the corresponding plan will be adjusted according to the monitored effect. S6. Abnormal Warning and Safety Assurance: If the system detects abnormal physiological conditions of the user (such as abnormal heart rate or breathing, indicating that the user is at risk of sleep apnea), abnormal indoor environment (such as excessive humidity, excessive VOC, gas leak, etc.), or abnormal user safety (such as falling or being unable to get up for a long time), the system will issue an alarm or notify other family members (or community staff) to carry out rescue according to the degree of danger.

[0006] Furthermore, in step S1, when the user conducts a physical constitution test, a traditional Chinese medicine physical constitution record is established. Information is collected through intelligent tongue diagnosis and pulse diagnosis instruments, and the basic physical constitution of each family member is automatically determined by filling out a traditional Chinese medicine physical constitution questionnaire. The corresponding chronic diseases, allergens, work and rest schedules and ages of each family member are also recorded.

[0007] Furthermore, in step S1, the mapping and division of the family micro-space is mainly divided into master and secondary bedrooms, living room, study, balcony and kitchen and bathroom. The corresponding locations, functions, orientations and lighting and ventilation conditions are marked. The installed sensors include temperature and humidity monitoring, light intensity sensing, odor monitoring and millimeter-wave radar sensors. At the same time, it is necessary to connect to smart home devices such as air conditioners, fresh air systems, lights, aromatherapy and health care devices.

[0008] Furthermore, the environmental baseline collection in step S2 includes 24-hour non-intrusive collection of temperature, humidity, light, noise and air quality in each micro-space, while the behavioral baseline includes the wake-up, sleep and work times, exercise, sedentary time periods and living trajectories of each family member.

[0009] Furthermore, the loading content of the TCM rules in step S2 includes the optimal temperature and humidity, light, aromatherapy and sound level of each space automatically matched according to the constitution determined by each family member. After the AI ​​automatically generates the settings, the user can also manually adjust them (mark their own preferences so that the AI ​​can automatically correct the corresponding adaptation parameters) for manual feedback calibration.

[0010] Furthermore, the TCM-based judgment principle in step S3 is to output optimal control commands based on the user's current physical condition, the function of the space, the usage time scenario, the current solar term, and the risk status to control smart home devices for linkage control, thereby controlling the automatic adjustment of air conditioning, fresh air, lighting, curtains, aromatherapy, five-tone music, moxibustion, or foot bath.

[0011] Furthermore, the risk identification in step S5 includes excessive humidity (which can easily aggravate phlegm and dampness in users), insufficient light (which can easily lead to qi stagnation), low temperature (which can easily lead to yang deficiency and cause symptoms such as colds and fevers), and low oxygen content (which can easily lead to nausea, headaches, reduced sleep quality, and decreased immunity).

[0012] Furthermore, the graded intervention in step S5 includes Level 1 intervention (environment): automatic heating, dehumidification, supplemental lighting, ventilation, etc.; Level 2 intervention (equipment): starting moxibustion, fumigation, foot bath, etc.; Level 3 intervention (recommendation): pushing medicinal diet (and its preparation steps), daily life, exercise programs (including movement guidance, exercise duration for each movement, corresponding recipes, etc.).

[0013] Furthermore, in step S6, if an abnormality is detected in the indoor environment, the smart home devices will be automatically controlled to ventilate and an alarm will be issued to alert the user.

[0014] This invention provides a micro-space TCM-adaptive planning and AI self-learning regulation method based on holistic health and wellness in the home environment, which has the following beneficial effects: 1. This invention deeply integrates traditional Chinese medicine (TCM) constitution theory with family micro-space planning. By establishing TCM constitution records, it clarifies the basic constitution, chronic diseases, and allergens of family members, and marks and divides each micro-space of the family according to its location, function, lighting, and ventilation. This achieves TCM-adaptive planning of micro-spaces. At the same time, it matches exclusive environmental parameters for each space according to different constitutions, upgrading the family environment control from physical parameter adjustment to personalized adaptation to meet the health and wellness needs of the human body, greatly improving the compatibility between the environment and the human body for health and wellness.

[0015] 2. This invention constructs an AI-powered full-process self-learning and iterative update system. Through baseline learning, it learns the behavioral habits of family members and basic environmental data, generates initial adaptation rules, and then dynamically adjusts them by combining daily real-time monitoring data. At the same time, it fine-tunes the control threshold and updates the scene strategy on a daily, weekly, and monthly basis, and resets the adaptation strategy according to the solar terms and seasons. It also judges the improvement effect by combining physical fitness retest data, so that the control strategy can continuously adapt to the behavioral changes, physical fitness improvements, and natural rhythm changes of family members. This achieves dynamic, precise, and long-term environmental control, taking into account multiple goals such as comfort, physical fitness improvement, and energy saving.

[0016] 3. This invention realizes the comprehensive perception and monitoring of the home environment, human physiology and behavior. It integrates environmental sensors such as temperature, humidity, light, and odor with millimeter-wave radar sensors, and simultaneously collects physiological and behavioral data. Combined with traditional Chinese medicine reasoning and judgment, it realizes multi-data linkage analysis, and then performs integrated linkage control of smart home devices such as air conditioners, fresh air systems, aromatherapy, and moxibustion. It breaks through the problems of poor data interoperability and isolated control of existing devices, and realizes the comprehensive and intelligent health and wellness control of the home micro-space. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall operation process of the micro-space TCM adaptive planning and AI self-learning regulation method based on the whole-domain health care of the family environment of the present invention. Detailed Implementation

[0018] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0019] like Figure 1 As shown, the micro-space TCM adaptive planning and AI self-learning regulation method based on holistic health care in the home environment includes the following steps: S1. Initial File Setup: Users input all family members' physical fitness test reports and family micro-space distribution maps into the system for recording and storage. Corresponding sensors are installed in each micro-space area for full-area perception and monitoring. When conducting physical fitness tests, users need to use traditional Chinese medicine (TCM) physical fitness file setup. Information is collected through intelligent tongue and pulse diagnosis instruments, and the basic physical fitness of each family member is automatically determined by filling out a TCM physical fitness questionnaire. The system also records the chronic diseases, allergens, daily routines, and ages of each family member. The mapping and division of family micro-spaces are mainly divided into master and secondary bedrooms, living room, study, balcony, and kitchen and bathroom. The corresponding locations, functions, orientations, lighting, and ventilation conditions are marked. The installed sensors include temperature and humidity monitoring, light intensity sensing, odor monitoring, and millimeter-wave radar sensors. At the same time, it is necessary to connect to smart home devices such as air conditioners, fresh air systems, lights, aromatherapy, and health care devices. After installation, users need to perform system debugging to ensure that the sensors and devices can operate normally and upload data. S2. Baseline Learning and Adaptation Process: After the user activates AI, AI automatically learns the user's habits based on environmental baseline data and the behavioral baselines of each family member. It also automatically generates initial adaptation rules based on the loaded content of Traditional Chinese Medicine (TCM) rules. Environmental baseline data collection includes 24-hour non-intrusive collection of temperature, humidity, light, noise, and air quality in each micro-space. Behavioral baseline data includes the wake-up, sleep, and work times, exercise, sedentary periods, and daily routines of each family member. The loaded content of TCM rules includes the optimal temperature, humidity, light, aromatherapy, and sound level for each space, automatically matched according to the constitution of each family member. After the AI ​​automatically generates the rules, the user can also manually adjust them (mark their own preferences so that the AI ​​can automatically correct the corresponding adaptation parameters) for manual feedback calibration. The manually calibrated rules will serve as the basis for AI's subsequent learning. S3. Real-time Daily Operation: Real-time collection of environmental data (temperature, humidity, light, sound, air), physiological data (heart rate, respiration, sleep, posture), and behavioral data (activity, location) via sensors. Based on the collected data, traditional Chinese medicine (TCM) reasoning is used to make judgments, then optimal control commands are output to control smart home devices in a coordinated manner. Simultaneously, changes in the environment and the user's physiological and comfort levels after control are monitored, and the monitoring data is transmitted back to the AI ​​for real-time monitoring and control processing. The TCM reasoning principle is based on monitoring the user's current constitution, the function of the space, the usage time scenario, the current solar term, and risk status to output optimal control commands to control smart home devices in a coordinated manner. This includes automatically adjusting air conditioning, fresh air systems, lighting, curtains, aromatherapy, five-tone music, moxibustion, or foot baths. All control operations can be viewed in real-time and manually paused. S4. AI self-learning iterative update: Fine-tuning thresholds (such as temperature ±0.5℃, brightness ±5%) are performed based on daily, weekly, and last day of the month. Scene strategies (morning, daytime, sleep, and weekend) are updated with the aim of improving comfort, physical fitness, and energy saving. Biased improvement values ​​are judged through physical fitness retest data. At the same time, the AI ​​model is adapted and reset according to the solar terms and seasons. The rules and data of each AI iteration are backed up in the cloud to ensure that the data is not lost. S5. Traditional Chinese Medicine (TCM) Assisted Intervention Process: This process is automatically triggered when AI identifies a user's constitution as imbalanced or at risk of invasion by the six pathogenic factors. At this point, tiered intervention is implemented for auxiliary regulation, and the body's constitution indicators are re-monitored 24 hours after intervention to track the effect. The corresponding plan is then adjusted based on the monitored results. Risk identification includes excessive humidity (which can worsen phlegm and dampness), insufficient light (which can lead to qi stagnation), low temperature (which can cause yang deficiency leading to colds, fevers, and other symptoms), and low oxygen levels (which can cause nausea, headaches, reduced sleep quality, and decreased immunity). Tiered intervention includes: Level 1 intervention (environment): automatic heating, dehumidification, supplemental lighting, and ventilation; Level 2 intervention (equipment): activation of moxibustion, fumigation, and foot baths; and Level 3 intervention (recommendations): recommendation of medicinal diets (and their preparation steps), daily routines, and exercise plans (including movement guidance, exercise duration, and corresponding recipes). The Level 3 intervention can be triggered sequentially or in combination based on the degree of imbalance in the user's constitution. S6. Abnormal Warning and Safety Assurance: If abnormal physiological conditions are detected in the user (e.g., abnormal heart rate or breathing, indicating a risk of sleep apnea), abnormal indoor environment (e.g., excessive humidity, excessive VOCs, gas leaks, etc.), or abnormal user safety (e.g., falls or prolonged bed rest), an alarm will be issued or other family members (or community workers) will be notified for rescue according to the degree of danger. If an abnormality is detected in the indoor environment, the smart home devices will be automatically controlled to ventilate and an alarm will be issued to remind the user. The degree of danger is divided into three levels: general, moderate, and emergency, with different warning and rescue measures corresponding to different levels.

[0020] In summary, combining Figure 1 As shown, the working principle of the micro-space TCM adaptability planning and AI self-learning regulation method based on the whole-domain health care of the family environment is as follows: First, the user conducts a TCM physical examination and enters the test report and micro-space distribution map information into the system to initialize the system file. Then, the monitor and equipment are installed and deployed, thus laying the data and hardware foundation for subsequent regulation. Secondly, personalized initial adaptation rules are generated through AI baseline learning, and the accuracy of the rules is improved by manual calibration. Then, it enters the daily real-time operation stage to realize the closed-loop operation of multi-data collection, TCM reasoning and judgment and equipment linkage control. Then, the AI ​​performs self-learning iteration and updates on a daily, weekly and monthly basis, and combines the seasonal reset strategy to continuously optimize the control strategy. When the AI ​​identifies the user's physical imbalance or environmental risk, it automatically triggers graded TCM auxiliary intervention and tracks the effect to dynamically adjust. Finally, by monitoring anomalies across all dimensions, safety warnings and emergency response are coordinated to achieve the goal of comprehensively protecting the health and safety of family members in their residences.

[0021] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A micro-space TCM-adaptive planning and AI self-learning regulation method based on holistic health and wellness in the home environment, characterized by: Includes the following steps: S1. Initial file creation: Users enter the physical fitness test reports of all family members and the distribution map of family micro-spaces into the system for recording and storage, and install corresponding sensors in each micro-space area for full-area perception and monitoring. S2. Baseline Learning and Adaptation Process: When the user enables AI, the AI ​​automatically learns the user's habits based on the environmental baseline data and the behavioral baselines of the user's family members, and automatically generates initial adaptation rules based on the loaded content of the TCM rules. S3. Daily Real-time Operation: Real-time collection of environmental, physiological, and behavioral data through sensors, and TCM reasoning and judgment based on the collected data. Then, the optimal control command is output to control smart home devices in a coordinated manner. At the same time, the changes in the environment and the user's physiology and comfort after the control are monitored and the monitoring data is sent back to the AI ​​for real-time monitoring and control processing. S4, AI self-learning iterative update: fine-tuning the threshold based on daily, weekly, and last day of each month; updating the scenario strategy with the aim of improving comfort, physical fitness, and energy saving; and judging the biased improvement value through physical fitness retest data. At the same time, the AI ​​model performs adaptation strategy reset processing based on solar terms and seasons. S5, Traditional Chinese Medicine Assisted Intervention Process: When AI identifies an imbalance in a user's constitution or the risk of invasion of the six pathogenic factors, it will be automatically triggered. At this time, tiered intervention will be used to assist in regulation, and the constitution indicators will be re-monitored 24 hours after the intervention to track the effect. Then, the corresponding plan will be adjusted according to the monitored effect. S6. Abnormal Warning and Safety Assurance: If a user's physiological abnormality, indoor environmental abnormality, or user safety abnormality is detected, an alarm will be issued or other family members will be notified to carry out rescue according to the degree of danger.

2. The micro-space TCM adaptability planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 1, characterized in that, In step S1, when a user undergoes a physical constitution test, a traditional Chinese medicine (TCM) physical constitution record is created. Information is collected through an intelligent tongue and pulse diagnosis instrument, and a TCM physical constitution questionnaire is filled out to automatically determine the basic physical constitution of each family member. The corresponding chronic diseases, allergens, daily routines, and ages of each family member are also recorded.

3. The method according to claim 2, wherein, In step S1, the mapping and division of the family micro-space is mainly divided into master and secondary bedrooms, living room, study, balcony and kitchen and bathroom, and the location, function, orientation and lighting and ventilation are marked accordingly. The installed sensors include temperature and humidity monitoring, light intensity sensing, odor monitoring and millimeter-wave radar sensors. At the same time, it is necessary to connect air conditioner, fresh air, lighting, aromatherapy and health and wellness smart home devices.

4. The family environment-based global health and wellness micro-space Chinese medicine adaptability planning and AI self-learning regulation method according to claim 1, characterized in that, The environmental baseline collection in step S2 includes 24-hour non-intrusive collection of temperature, humidity, light, noise and air quality in each micro-space, while the behavioral baseline includes the wake-up, sleep and work times, exercise, sedentary time periods and daily routines of each family member.

5. The micro-space TCM adaptability planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 4, characterized in that, The loading of TCM rules in step S2 includes automatically matching the optimal temperature and humidity, light, aromatherapy, and sound level for each space based on the constitution determined by each family member. After the AI ​​automatically generates the settings, users can also manually adjust them for human feedback and calibration.

6. The micro-space TCM adaptive planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 1, characterized in that, The TCM-based judgment principle in step S3 is to output optimal control commands based on the user's current physical condition, the function of the space, the usage time scenario, the current solar term, and the risk status to control smart home devices for linkage control, thereby controlling the automatic adjustment of air conditioning, fresh air, lighting, curtains, aromatherapy, five-tone music, moxibustion, or foot bath.

7. The micro-space TCM adaptive planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 1, characterized in that, The risk identification in step S5 includes excessive humidity, insufficient light, low temperature, and low oxygen content.

8. The micro-space TCM adaptability planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 7, characterized in that, The graded intervention in step S5 includes: Level 1 intervention: automatic heating, dehumidification, supplemental lighting, and ventilation; Level 2 intervention: initiating moxibustion, fumigation, and foot bath; and Level 3 intervention: pushing medicinal diet, daily life, and exercise plans.

9. The micro-space TCM adaptability planning and AI self-learning regulation method based on holistic health care in the home environment according to claim 1, characterized in that, If an abnormality is detected in the indoor environment during step S6, the smart home devices will be automatically controlled to ventilate and an alarm will be issued to alert the user.

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