Vitality value evaluation system for elderly living at home

Abstract

The invention discloses a living elderly vigor value evaluation system, which comprises a hardware module, an AI calculation processing module and a user side, the hardware module comprises a data collection module, an activity fluctuation index acquisition module, a vigor value evaluation module, an AI intelligent analysis module and a personalized recommendation module, and the AI calculation processing module comprises an information processor. The user side comprises a PC side, an applet side and an APP side, and the data collection module and the activity fluctuation index acquisition module are both connected with the information processor. According to the system for evaluating the vitality value of the elderly living at home, the algorithm efficiency is high, the precision and the real-time performance are both considered, the activity condition of the elderly living at one day is analyzed, the activity condition of the elderly is analyzed within the corresponding time range, a corresponding adjustment scheme and personalized recommendation are given to the elderly according to the conclusion, and the elderly living at home is more vigorous. The old people are divided according to age groups and physical quality, the activity of the old people is analyzed more finely, and errors can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart elderly care technology, and in particular to a vitality value assessment system for elderly people at home. Background Art

[0002] The vitality value assessment system for the elderly at home is a method for dynamic prediction and assessment of the elderly at home. As people pay more and more attention to the problem of population aging and the rapid development of technologies such as the Internet and artificial intelligence, the concept of smart elderly care has begun to take root in people's hearts. With the continuous development of science and technology, people's requirements for the vitality value assessment system for the elderly at home are also getting higher and higher.

[0003] The existing vitality value assessment system for the elderly at home has certain drawbacks when used. Most technologies mainly use wearable devices to collect activity data of the elderly. The elderly have a weak sense of experience, poor comfort, and difficulty in proficient operation, which leads to a lack of enthusiasm. Once the elderly are out of the device, there is no data source, and the monitoring device becomes invalid immediately; the existing mobile devices cannot accurately determine the indoor location, and can only count the number of steps taken by the elderly in a day, but cannot count the activity data of the elderly in different spaces at home. Therefore, wearable devices cannot distinguish the actual activity data of users; wearable data mobile devices mainly transmit data through Bluetooth communication. The transmission distance of Bluetooth technology is limited, usually around 10 to 100 meters, and the transmission rate is not as fast as WiFi; in an environment where there are many Bluetooth devices, channel interference may occur, affecting the stability of the connection; although Bluetooth connections can be encrypted, there are still some potential security risks and may be attacked, especially in public environments; the existing evaluation of the activities of the elderly is mainly based on the stride, frequency and number of steps of the elderly. The main data collection equipment for this type of detection is a wearable bracelet, followed by fixed-point detection equipment, which needs to be deployed in places where the elderly often move around in their homes. At least two or more detection devices are needed to collect data for analysis. For this reason, we propose a vitality value assessment system for elderly people at home. Summary of the invention

[0004] Technical problem solved: In view of the shortcomings of the prior art, the present invention provides a vitality value assessment system for elderly people at home. The algorithm is efficient and takes into account both accuracy and real-time performance. It analyzes the activities of the elderly at home in one day and analyzes the activities of the elderly within a corresponding time range. Based on this conclusion, the elderly are given corresponding adjustment plans and personalized recommendations. The elderly are divided into age groups and physical fitness, and the activity of the elderly is analyzed more finely, which can effectively reduce errors and effectively solve the problems in the background technology.

[0005] Technical solution: To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a vitality value assessment system for elderly people at home, including a hardware module, an AI computing and processing module and a user end, the hardware module includes a data collection module, an activity fluctuation index acquisition module, a vitality value assessment module, an AI intelligent analysis module and a personality recommendation module, the AI ​​computing and processing module includes an information processor, the user end includes a PC end, a mini program end and an APP end, the data collection module, the activity fluctuation index acquisition module, the vitality value assessment module, the AI ​​intelligent analysis module and the personality recommendation module are all connected to the information processor, and the information processor is connected to the PC end, the mini program end and the APP end;

[0006] Data collection module, used to obtain the activity information and status information of the target elderly;

[0007] An activity fluctuation index acquisition module is used to obtain the fluctuation index of the target elderly person;

[0008] A vitality value evaluation module is used to obtain the vitality value of the target elderly person according to the above index;

[0009] The AI ​​intelligent analysis and personalized recommendation module is used to obtain the elderly’s recent activity data and change trends, and make personalized recommendations based on such changes.

[0010] As a preferred technical solution of the present application, the data collection module is used to collect the activity data of the target elderly, and obtain the activity information and status information of the target elderly based on the activity data; the activity fluctuation index acquisition module is used to determine the frequency of the target elderly's switching in space according to the status information of the target elderly, and obtain the activity fluctuation index of the target elderly according to the activity time of the target elderly; the vitality value evaluation module is used to calculate the vitality value of the elderly based on the activity time, duration, location and frequency of sensor triggering of the target elderly as features, combined with the interactive fluctuation index, etc.; the AI ​​intelligent analysis module and the personalized recommendation module construct a user portrait based on the basic information and activity data of the elderly, and use the user's age, activity duration, vitality value and other attributes to calculate the similarity between users, and recommend relevant conditioning information to the elderly based on the similarity.

[0011] As a preferred technical solution of the present application, the hardware module, the AI ​​computing and processing module and the user end are interconnected for communication; the hardware module is used to collect activity information of the elderly; the AI ​​computing and processing device is used to receive the activity information of the elderly collected by the hardware module, and use the AI ​​algorithm to analyze the activity information of the user, output the vitality value result of the elderly activity, and send the result to the user end, and the activity information includes at least one of the time, duration, location information and number of times the sensor is triggered.

[0012] As a preferred technical solution of the present application, the data collection module collects the activity information of the elderly at home through sensors, collects the basic information of the elderly through the client, and establishes a basic mathematical model of the elderly. The sensors for collecting data mainly include human infrared sensors and gateway sensors, and the data is transmitted through wireless transmission.

[0013] As a preferred technical solution of the present application, the fluctuation of the activity fluctuation index acquisition module mainly refers to the frequency of switching between different spaces when the user exercises. This index can reflect some living habits of the elderly at home and the degree of daily exercise.

[0014] As a preferred technical solution of the present application, the vitality value evaluation module aggregates the data collected by the data collection module and the activity fluctuation index acquisition module, combines the basic information of the user's age, constructs digital features, and inputs the features into the model. Based on the average activity duration of the age group as a reference, the corresponding vitality value of the user is calculated through the model.

[0015] As a preferred technical solution of the present application, the AI ​​intelligent analysis module and the personalized recommendation module make an analysis based on the recent vitality value of the elderly after obtaining the daily vitality value of the elderly, and analyze the recent activity trend of the elderly. The long-term data will outline the activity trend of the elderly, and can further reflect the trend of the elderly's physical health, so as to respond in time when the elderly's body shows a declining state.

[0016] As a preferred technical solution of this application, it specifically includes the following process:

[0017] S1: synchronously collect activity data and physiological parameter data of the target object, perform AI analysis on the activity data to obtain activity characteristic information of the target object, and perform AI analysis on the physiological parameter data to obtain physiological state characteristic information of the target object;

[0018] S2: Based on the basic characteristic information of the activity of the elderly in this age group, obtain the distribution information of the average activity duration of the elderly in this age group in different spaces, and combine this data with the data collected in step S1 as the assigned feature to obtain the input data of the vitality value evaluation system;

[0019] S3: Input the obtained input data into the model for calculation. At this time, it is necessary to determine whether the activity data of the elderly person for the day are all empty. If they are all empty, it is necessary to combine other devices to determine whether the elderly person is at home and whether there is danger. Other devices are also needed to be referenced. When the system determines that the elderly person is out that day, no calculation is required. If there is data in different spaces, the data can be input into the vitality value evaluation system to calculate the vitality value of the elderly person.

[0020] S4: The obtained vitality value needs to be processed again to limit the vitality value range to between 60 and 100;

[0021] S5: The final vitality value is transmitted to the PC, mini program and APP.

[0022] Beneficial effects: Compared with the prior art, the present invention provides a vitality value assessment system for elderly people at home, which has the following beneficial effects: the vitality value assessment system for elderly people at home has an efficient algorithm, taking into account both accuracy and real-time performance, analyzes the activities of the elderly at home for one day and analyzes the activities of the elderly within the corresponding time range, and uses this conclusion to give the elderly corresponding adjustment plans and personalized recommendations, divides the elderly according to age groups and physical fitness, and analyzes the activity of the elderly more finely, which can effectively reduce errors. The present invention obtains the original data of the elderly's activities through intelligent non-contact sensors, constructs a vitality value model, accurately detects the activities of the elderly, and predicts the trend and development trend of the elderly's activities. AI analysis can be used to make personalized recommendations, which is conducive to delaying the decline of the elderly's activity ability and keeping the elderly in a healthy state. The entire vitality value assessment system for elderly people at home has a simple structure and is easy to operate, and the effect of use is better than that of traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The present invention is a schematic diagram of the overall structure of a vitality value assessment system for elderly people at home.

[0024] Figure 2 The present invention is a schematic flow chart of a vitality value assessment system for elderly people at home. DETAILED DESCRIPTION

[0025] The technical scheme of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments, but it will be understood by those skilled in the art that the following described embodiments are part of embodiments of the present invention, rather than all embodiments, and are only used to illustrate the present invention, and should not be considered as limiting the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of the present invention. If specific conditions are not specified in the embodiments, they are carried out according to normal conditions or conditions recommended by the manufacturer. If the manufacturer is not specified in the reagents or instruments used, they are all conventional products that can be purchased commercially.

[0026] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0027] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0028] like Figure 1 , 2 As shown, a vitality value assessment system for elderly people at home includes a hardware module, an AI computing and processing module and a user end. The hardware module includes a data collection module, an activity fluctuation index acquisition module, a vitality value assessment module, an AI intelligent analysis module and a personality recommendation module. The AI ​​computing and processing module includes an information processor. The user end includes a PC end, a mini program end and an APP end. The data collection module, the activity fluctuation index acquisition module, the vitality value assessment module, the AI ​​intelligent analysis module and the personality recommendation module are all connected to the information processor, and the information processor is connected to the PC end, the mini program end and the APP end.

[0029] Data collection module, used to obtain the activity information and status information of the target elderly;

[0030] An activity fluctuation index acquisition module is used to obtain the fluctuation index of the target elderly person;

[0031] A vitality value evaluation module is used to obtain the vitality value of the target elderly person according to the above index;

[0032] The AI ​​intelligent analysis and personalized recommendation module is used to obtain the elderly’s recent activity data and change trends, and make personalized recommendations based on such changes.

[0033] The algorithm is efficient and takes into account both accuracy and real-time performance. It analyzes the activities of the elderly at home in a day and analyzes their activities within the corresponding time range. Based on this conclusion, it gives the elderly corresponding adjustment plans and personalized recommendations. It divides the elderly according to age groups and physical fitness, and analyzes their activity more carefully, which can effectively reduce errors.

[0034] Furthermore, the data collection module is used to collect the activity data of the target elderly, and obtain the activity information and status information of the target elderly based on the activity data; the activity fluctuation index acquisition module is used to determine the frequency of the target elderly's switching in space according to the status information of the target elderly, and obtain the activity fluctuation index of the target elderly according to the activity time of the target elderly; the vitality value evaluation module is used to calculate the vitality value of the elderly based on the activity time, duration, location and frequency of sensor triggering of the target elderly as features, combined with the interactive fluctuation index, etc.; the AI ​​intelligent analysis module and the personalized recommendation module construct user portraits based on the basic information and activity data of the elderly, and use the user's age, activity duration, vitality value and other attributes to calculate the similarity between users, and recommend relevant conditioning information to the elderly based on the similarity.

[0035] Furthermore, the hardware module, the AI ​​computing and processing module and the user end are interconnected for communication. The hardware module is used to collect activity information of the elderly. The AI ​​computing and processing device is used to receive the activity information of the elderly collected by the hardware module, and use the AI ​​algorithm to analyze the activity information of the user, output the vitality value result of the elderly activity, and send the result to the user end. The activity information includes at least one of the time, duration, location information and number of times the sensor is triggered.

[0036] Furthermore, the data collection module collects the elderly's home activity information through sensors, collects the elderly's basic information through the client, and establishes a basic mathematical model of the elderly. The sensors for collecting data mainly include human infrared sensors and gateway sensors, and the data is transmitted through wireless communication.

[0037] Furthermore, the fluctuation of the activity fluctuation index acquisition module mainly refers to the frequency of switching between different spaces when the user exercises. This index can reflect some living habits of the elderly at home and the degree of daily exercise.

[0038] Furthermore, the vitality value evaluation module aggregates the data collected by the data collection module and the activity fluctuation index acquisition module, combines the basic age information of the user, constructs digital features, and inputs the features into the model. Based on the average activity duration of the age group as a reference, the corresponding vitality value of the user is calculated through the model.

[0039] Furthermore, after obtaining the elderly's daily vitality value, the AI ​​intelligent analysis module and the personalized recommendation module make an analysis based on the elderly's recent vitality value and analyze the elderly's recent activity trends. Long-term data will outline the elderly's activity trends and can further reflect the elderly's physical health trends, so that timely responses can be made when the elderly's body shows a decline.

[0040] Furthermore, the specific process includes the following:

[0041] S1: synchronously collect activity data and physiological parameter data of the target object, perform AI analysis on the activity data to obtain activity characteristic information of the target object, and perform AI analysis on the physiological parameter data to obtain physiological state characteristic information of the target object;

[0042] S2: Based on the basic characteristic information of the activity of the elderly in this age group, obtain the distribution information of the average activity duration of the elderly in this age group in different spaces, and combine this data with the data collected in step S1 as the assigned feature to obtain the input data of the vitality value evaluation system;

[0043] S3: Input the obtained input data into the model for calculation. At this time, it is necessary to determine whether the activity data of the elderly person for the day are all empty. If they are all empty, it is necessary to combine other devices to determine whether the elderly person is at home and whether there is danger. Other devices are also needed to be referenced. When the system determines that the elderly person is out that day, no calculation is required. If there is data in different spaces, the data can be input into the vitality value evaluation system to calculate the vitality value of the elderly person.

[0044] S4: The obtained vitality value needs to be processed again to limit the vitality value range to between 60 and 100;

[0045] S5: The final vitality value is transmitted to the PC, mini program and APP.

[0046] Working principle: The algorithm is efficient and takes into account both accuracy and real-time performance. It analyzes the activities of the elderly at home for one day and analyzes the activities of the elderly within the corresponding time range. Based on this conclusion, the elderly are given corresponding adjustment plans and personalized recommendations. The elderly are divided according to age groups and physical fitness, and their activity is analyzed more finely, which can effectively reduce errors. The present invention obtains the original data of the elderly's activities through intelligent non-contact sensors, constructs a vitality value model, accurately detects the activities of the elderly, and predicts the trend of the elderly's activities and development trends. AI analysis can be used to make personalized recommendations, which is conducive to delaying the decline of the elderly's activity ability and keeping the elderly in a healthy state.

[0047] The present invention can assess the vitality value of the elderly more scientifically, and give corresponding intelligent analysis and recommendations for the activity value of the elderly, and process and exchange data through an information processor, and finally display the obtained results through the PC, mini program and APP.

[0048] Vitality evaluation module: Taking the average activity duration of elderly people of the same age and the spatial fluctuation index as the basic values, the basic score corresponding to the average duration of the elderly is specified, and the full score duration of each space is calculated. The activity duration of each space of the elderly is compared with the average value to obtain the relationship between the elderly's activities and the average value, and the corresponding score is obtained using this relationship. Finally, the sum of the scores in different spaces is the vitality score of the elderly on that day.

[0049]

[0050] Among them, value represents the total score of the i-th space, time represents the duration of the i-th space activity of the elderly on that day, and mean_time represents the average duration of the i-th space activity of the elderly in this age group. Here, the score corresponding to the average duration of the elderly in this age group is stipulated to be 90 points (percentage system), so the coefficient calculated at this time is 0.9, which can be adjusted according to actual conditions. The vitality values ​​calculated in different spaces are summed up and the value is processed to obtain the vitality value of the elderly for one day. At this time, the vitality value obtained is not distributed between 0 and 100 points, so secondary processing is required. At the same time, in order to ensure that the value does not cause unnecessary anxiety to the elderly, the lowest threshold is set, and the score interval is divided into 60-100 points. When the calculated vitality value is greater than 100, 100 is directly assigned as the final vitality value of the day; when the calculated vitality value is less than 70, a value between 60-69 is randomly selected as the final vitality value of the day; the values ​​in other intervals are not processed and are directly used as the final vitality value of the day.

[0051] For example, according to statistical analysis, the average time that elderly people aged 70-75 spend in their living room, kitchen and bathroom is 5 hours, 3 hours and 2 hours a day, and the full score for the living room, kitchen and bathroom is 40 points, 30 points and 30 points respectively. On a certain day, the time that Elder A spends in the three spaces is 4.5 hours, 2 hours and 2 hours respectively; the time that Elder B spends in the three spaces is 6 hours, 3.5 hours and 3 hours respectively; the time that Elder C spends in the three spaces is 3 hours, 1 hour and 1 hour respectively.

[0052] A Elderly's vitality value calculation process:

[0053]

[0054] Since the value is between 65 and 99, the final vitality value of Elder A on that day is rounded to 77 points.

[0055] The calculation process of the vitality value of Elder B:

[0056]

[0057] Since the value is greater than 100, the final vitality value of Elder A on that day is 100 points.

[0058] C Elderly's vitality value calculation process:

[0059]

[0060] Since this value is less than 65, the final vitality value of Elder A on that day was 63 points.

[0061] AI intelligent analysis and personalized recommendation module: The database stores the vitality value of the elderly, pulls the elderly’s recent data as features, analyzes whether the trend of the elderly’s activities has increased or remained the same, and combines factors such as the elderly’s physical condition and age. Build a user portrait, and combine this recommendation method to calculate the similarity between users using attributes such as the user’s age, activity duration, and vitality value. Find other users with similar interests to the target user, and then recommend content that these similar users like. Calculate the similarity between users based on the user’s browsing time and number of views of the article, and then recommend other content similar to the user’s favorite articles. In cold start scenarios with new users or less data, it does not rely on user behavior. As long as it obtains the user’s basic information and vitality value, it can calculate the similarity at the semantic level and recommend the corresponding content.

[0062] Since the vitality value is processed data and is different from the original data, the original data needs to be used when performing AI analysis on the data. Here, the number of times the sensor uploads data every day, that is, the frequency of departure from each space every day, is used as the input of the AI ​​model. Based on the trend of data changes, the changes in the user's activities in the past 7 days, 30 days, 90 days, and 360 days are obtained, and corresponding intelligent recommendations are given based on the changes and combined with user information such as age and physical condition.

[0063] It should be noted that, in this article, relational terms such as first and second (number one, number two), etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, 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 other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0064] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A vitality value assessment system for elderly people at home, comprising a hardware module, an AI computing and processing module and a user terminal, characterized in that: The hardware module includes a data collection module, an activity fluctuation index acquisition module, a vitality value evaluation module, an AI intelligent analysis module and a personality recommendation module, the AI ​​calculation processing module includes an information processor, the user end includes a PC end, a mini program end and an APP end, the data collection module, the activity fluctuation index acquisition module, the vitality value evaluation module, the AI ​​intelligent analysis module and the personality recommendation module are all connected to the information processor, and the information processor is connected to the PC end, the mini program end and the APP end; Data collection module, used to obtain the activity information and status information of the target elderly; An activity fluctuation index acquisition module is used to obtain the fluctuation index of the target elderly person; A vitality value evaluation module is used to obtain the vitality value of the target elderly person according to the above index; The AI ​​intelligent analysis and personalized recommendation module is used to obtain the elderly’s recent activity data and change trends, and make personalized recommendations based on such changes.

2. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: The data collection module is used to collect the activity data of the target elderly, and obtain the activity information and status information of the target elderly based on the activity data; the activity fluctuation index acquisition module is used to determine the frequency of the target elderly switching in space according to the status information of the target elderly, and obtain the activity fluctuation index of the target elderly according to the activity time of the target elderly; the vitality value evaluation module is used to calculate the vitality value of the elderly based on the activity time, duration, location and frequency of sensor triggering of the target elderly as features, combined with the interactive fluctuation index, etc.; The AI ​​intelligent analysis module and personalized recommendation module construct user portraits based on the basic information and activity data of the elderly, and use the user's age, activity duration, vitality value and other attributes to calculate the similarity between users, and recommend relevant conditioning information to the elderly based on the similarity.

3. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: The hardware module, AI computing and processing module and the user end are interconnected for communication. The hardware module is used to collect activity information of the elderly. The AI ​​computing and processing device is used to receive the activity information of the elderly collected by the hardware module, analyze the activity information of the user using an AI algorithm, output the vitality value result of the elderly activity, and send the result to the user end. The activity information includes at least one of the time, duration, location information and number of times the sensor is triggered.

4. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: The data collection module collects the activity information of the elderly at home through sensors, collects the basic information of the elderly through the client, and establishes a basic mathematical model of the elderly. The sensors for collecting data mainly include human infrared sensors and gateway sensors, and the data is transmitted through wireless communication.

5. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: The fluctuation of the activity fluctuation index acquisition module mainly refers to the frequency of switching between different spaces when the user exercises. This index can reflect some living habits of the elderly at home and the degree of daily exercise.

6. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: The vitality value evaluation module aggregates the data collected by the data collection module and the activity fluctuation index acquisition module, combines the basic information of the user's age, constructs digital features, and inputs the features into the model. Based on the average activity duration of the age group as a reference, the corresponding vitality value of the user is calculated through the model.

7. A vitality value assessment system for elderly people at home according to claim 1, characterized in that: After obtaining the daily vitality value of the elderly, the AI ​​intelligent analysis module and the personalized recommendation module make an analysis based on the recent value of the vitality value of the elderly, and analyze the recent activity trend of the elderly. Long-term data will outline the activity trend of the elderly, and can also further reflect the trend of the elderly's physical health, so as to respond in time when the elderly's physical condition shows a decline.

8. The vitality evaluation system for elderly people at home according to claim 1, characterized in that: The specific process includes the following: S1: synchronously collect activity data and physiological parameter data of the target object, perform AI analysis on the activity data to obtain activity characteristic information of the target object, and perform AI analysis on the physiological parameter data to obtain physiological state characteristic information of the target object; S2: Based on the basic characteristic information of the activity of the elderly in this age group, obtain the distribution information of the average activity duration of the elderly in this age group in different spaces, and combine this data with the data collected in step S1 as the assigned feature to obtain the input data of the vitality value evaluation system; S3: Input the obtained input data into the model for calculation. At this time, it is necessary to determine whether the activity data of the elderly person for the day are all empty. If they are all empty, it is necessary to combine other devices to determine whether the elderly person is at home and whether there is danger. Other devices are also needed to be referenced. When the system determines that the elderly person is out that day, no calculation is required. If there is data in different spaces, the data can be input into the vitality value evaluation system to calculate the vitality value of the elderly person. S4: The obtained vitality value needs to be processed again to limit the vitality value range to between 60 and 100; S5: The final vitality value is transmitted to the PC, the mini program and the APP.

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