Intelligent heat dissipation shoe system based on user physiological data analysis

Abstract

The invention relates to the technical field of intelligent heat dissipation, in particular to an intelligent heat dissipation shoe system based on user physiological data analysis. The system comprises an amplitude position unit, a calculation and judgment unit, a change prediction unit and an intelligent heat dissipation unit. According to the invention, a pressure matrix is organized according to the pressure data of the attaching module, the bearing force value and the bearing force position point of the intelligent shoe are retrieved, the average bearing force value is calculated according to the bearing force value of the intelligent shoe, and then the bearing force threshold value is calculated; whether the foot in the bearing force position point is completely attached to the insole or not is judged according to the bearing force value and the bearing force threshold value of the intelligent shoe, the key area position of the foot is concentrated, the measurement range is reduced, the number of unnecessary temperature sensors is reduced, the resolution ratio and energy efficiency of temperature data are improved, and meanwhile when the key area position of the foot is concentrated, the temperature data can be accurately measured. And the foot temperature can be accurately read at the moment when the foot and the insole are completely attached, so that the error of foot temperature measurement caused by unstable contact is avoided, and the accuracy of temperature measurement is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent heat dissipation technology, and in particular to an intelligent heat dissipation shoe system based on user physiological data analysis. Background Art

[0002] Smart heat dissipation shoes are smart shoes that use advanced sensors and data analysis technology to monitor and adjust the temperature of the user's feet. By collecting the user's physiological body temperature data and foot temperature and making temperature changes, the temperature inside the shoe can be automatically adjusted to provide users with a more comfortable, healthy and intelligent life experience. In the future, with the continuous advancement of technology and the expansion of market demand, the smart heat dissipation shoe system is expected to become a leading product in the field of smart wearable devices. Since the user wears smart shoes during exercise, the smart shoes vibrate, which causes the smart shoes to move with a large amplitude. When the movement amplitude is large, the contact between the foot and the insole is unstable, so that the foot and the insole are not completely fitted. It is necessary to measure the position of all the feet and the internal area of ​​the smart shoe, which increases the measurement range and the number of unnecessary temperature sensors, resulting in reduced resolution and energy efficiency of the temperature data. When the foot temperature is measured when the foot and the insole are not completely fitted, the error of the foot temperature measurement is increased, resulting in reduced temperature measurement accuracy. Therefore, we provide a smart heat dissipation shoe system based on user physiological data analysis. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent heat dissipation shoe system based on user physiological data analysis to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned object, the present invention provides an intelligent heat dissipation shoe system based on the analysis of user physiological data, comprising an amplitude position unit, a calculation and judgment unit, a change prediction unit and an intelligent heat dissipation unit;

[0005] The amplitude position unit obtains the pressure and acceleration data of the cycle time through the sensor to calculate the acceleration peak value of the smart shoe and the change slope of the pressure data, and then comprehensively analyzes the vibration amplitude index of the smart shoe to determine the vibration amplitude of the smart shoe. When the smart shoe has a high movement amplitude, the pressure matrix is ​​organized according to the pressure data using the matrix and the bearing force values ​​and bearing force position points of the first three smart shoes are retrieved. The bearing force values ​​of the first three smart shoes are used to determine whether the foot and the insole in the bearing force position point are completely fitted. When the foot and the insole in the bearing force position point are completely fitted, the bearing force position point is marked as 1;

[0006] The calculation and judgment unit is used to receive a command that the foot and the insole are completely in contact with each other in the force position point in the amplitude position unit. The calculation and judgment unit obtains the force position point marked as 1 and the number of marks from the amplitude position unit. When the foot and the insole are completely in contact with each other, the sensor in the smart shoe and the smart bracelet worn by the user are triggered. The foot temperature is detected according to the force position point marked as 1 and the average foot temperature is calculated. At the same time, the smart bracelet worn by the user obtains physiological temperature data and calculates the average physiological temperature. The average physiological temperature and the average foot temperature are used to determine whether the physiological temperature and the foot temperature are increased by using the set standard physiological temperature parameters and the set standard foot temperature parameters. When the physiological temperature and the foot temperature are increased, the heat, heat dissipation power, and heat dissipation status in the smart shoe are recorded.

[0007] The change prediction unit is used to receive the command of the calculation and judgment unit that the physiological body temperature and the foot temperature increase, the change prediction unit obtains the heat, heat dissipation power, and heat dissipation state in the smart shoe from the calculation and judgment unit, calculates the temperature change inside the smart shoe, and then predicts the temperature inside the smart shoe;

[0008] The intelligent heat dissipation unit is used to receive the internal temperature, heat dissipation state, heat dissipation power of the smart shoe predicted in the change prediction unit and the standard foot temperature parameters set in the calculation and judgment unit, calculate the heat dissipation control parameters of the smart shoe, and then dissipate the heat of the smart shoe according to the calculated heat dissipation control parameters.

[0009] As a further improvement of the technical solution, the amplitude position unit includes a motion amplitude module and a position fitting module;

[0010] The motion amplitude module obtains the pressure and acceleration data of the smart shoe through the pressure sensor and acceleration sensor in the smart shoe, records the number of acceleration data within the cycle time, calculates the peak value of the acceleration of the smart shoe from the maximum acceleration and the minimum acceleration within the cycle time, calculates the slope of the pressure data according to the pressure data, comprehensively analyzes the vibration amplitude index of the smart shoe using the calculated peak value of the acceleration of the smart shoe and the slope of the pressure data, and then uses the comprehensively analyzed vibration amplitude index of the smart shoe to judge the vibration amplitude of the smart shoe;

[0011] The position fitting module is used to receive the high movement amplitude command in the movement amplitude module, the position fitting module obtains pressure data from the movement amplitude module, organizes the pressure matrix according to the pressure data using a matrix and retrieves the bearing force values ​​and bearing force position points of the first three smart shoes, and then calculates the average bearing force value and the bearing force threshold value according to the bearing force values ​​of the first three smart shoes, and uses the bearing force values ​​of the first three smart shoes and the bearing force threshold value to determine whether the foot and the insole at the bearing force position point are completely fitted;

[0012] When the bearing force value of the smart shoe is greater than the bearing force threshold, it means that the foot and the insole at the bearing force position point are completely in contact with each other, and the bearing force position point is marked as 1, and the number of marks is recorded;

[0013] When the bearing force value of the smart shoe is less than the bearing force threshold, it means that the foot and the insole at the bearing force position point are not completely fitted together, and the bearing force position point is marked as 0.

[0014] As a further improvement of the technical solution, the implementation principle of the matrix organization pressure matrix in the position fitting module is as follows:

[0015] Collect pressure data p(t) to organize the pressure matrix, and obtain the pressure matrix p of the organization. The specific algorithm formula is:

[0016]

[0017] Where the array is m×n, then the size of the tissue pressure matrix p is m×n, where P i,j (t) represents the bearing capacity value of the i-th row and j-th column at time t.

[0018] As a further improvement of the technical solution, the calculation and judgment unit includes a trigger calculation module and a temperature judgment module;

[0019] The trigger calculation module is used to receive a command that the foot and the insole are completely fitted in the force position point in the position fitting module, and the trigger calculation module obtains the force position point marked as 1 and the number of marks from the position fitting module. When the foot and the insole are completely fitted, the temperature sensor in the smart shoe and the smart bracelet worn by the user are triggered. The temperature sensor in the smart shoe detects the foot temperature corresponding to the force position point according to the force position point marked as 1, and the smart bracelet worn by the user obtains physiological body temperature data and calculates the average physiological body temperature.

[0020] When the number of marks is greater than 1, the average foot temperature is calculated based on the foot temperature;

[0021] When the number of marks is less than 1, there is no need to calculate the average foot temperature, and the foot temperature corresponding to the bearing position point marked as 1 is transmitted to the temperature judgment module;

[0022] The temperature judgment module is used to receive the average value of the physiological body temperature in the trigger calculation module, and receive the average value of the foot temperature in the trigger calculation module or the foot temperature corresponding to the bearing position point marked as 1, and use the average value of the physiological body temperature and the average value of the foot temperature to judge whether the physiological body temperature and the foot temperature are increased, or use the average value of the physiological body temperature and the foot temperature corresponding to the bearing position point marked as 1 to judge whether the physiological body temperature and the foot temperature are increased.

[0023] As a further improvement of the technical solution, the specific judgment situation in the temperature judgment module includes:

[0024] Case 1: When the average physiological body temperature is greater than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is greater than the set standard foot temperature parameter, it indicates that the physiological body temperature and foot temperature have increased, and the heat, environmental factors, heat dissipation power, heat dissipation state, and thermal conductivity state in the smart shoe are recorded;

[0025] Case 2: When the average physiological body temperature is greater than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased;

[0026] Case 3: When the average physiological body temperature is less than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased;

[0027] Case 4: When the average physiological body temperature is less than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is greater than the set standard foot temperature parameter, it indicates that the physiological body temperature and the foot temperature are increased.

[0028] As a further improvement of the technical solution, the change prediction unit includes a temperature change module and a predicted temperature module;

[0029] The temperature change module is used to receive commands from the temperature judgment module to increase the physiological body temperature and the foot temperature. The temperature change module obtains the heat, environmental factors, heat dissipation power, heat dissipation state, and heat conduction state inside the smart shoe from the temperature judgment module, and calculates the temperature change inside the smart shoe;

[0030] The predicted temperature module is used to receive the temperature change amount inside the smart shoe in the temperature change module and the foot temperature and the number of marks corresponding to the bearing force position point marked as 1 in the trigger calculation module;

[0031] When the number of marks is greater than 1, the maximum foot temperature is selected from the foot temperatures corresponding to the force-bearing position points marked as 1, and the temperature inside the smart shoe is predicted using the maximum foot temperature and the temperature change inside the smart shoe;

[0032] When the number of marks is less than 1, the temperature inside the smart shoe is predicted using the foot temperature corresponding to the force bearing position point marked as 1 and the temperature change inside the smart shoe.

[0033] As a further improvement of the present technical solution, the intelligent heat dissipation unit is used to receive the temperature predicted inside the smart shoes in the predicted temperature module, the heat dissipation state, the thermal conductivity state, the heat dissipation power and the standard foot temperature parameters set in the temperature judgment module, and calculate the heat dissipation control parameters of the smart shoes, and then dissipate the heat of the smart shoes according to the calculated heat dissipation control parameters. When the smart shoes are in the heat dissipation process, the temperature of the foot position corresponding to the bearing position point marked as 1 is monitored in real time. When the real-time monitored foot temperature is lower than the set standard foot temperature parameter, the heat dissipation function of the smart shoes is stopped.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. In the intelligent heat dissipation shoe system based on user physiological data analysis, the position fitting module is used to receive the high movement amplitude command in the movement amplitude module, the position fitting module obtains pressure data from the movement amplitude module, organizes the pressure matrix according to the pressure data by using the matrix and retrieves the bearing value and bearing position point of the first three intelligent shoes, and then calculates the average bearing value according to the bearing value of the first three intelligent shoes and then calculates the bearing threshold, and uses the bearing value and the bearing threshold of the first three intelligent shoes to judge whether the foot and the insole in the bearing position point are completely fitted, by focusing on the key area position of the foot, reducing the measurement range and the number of unnecessary temperature sensors, improving the resolution and energy efficiency of the temperature data, and at the same time, when the key area position of the foot is concentrated and the foot and the insole are completely fitted, the foot temperature can be accurately read at the moment, avoiding the error of reducing the foot temperature measurement due to unstable contact, and improving the accuracy of temperature measurement.

[0036] 2. In the intelligent heat dissipation shoe system based on user physiological data analysis, the intelligent heat dissipation unit is used to receive the temperature predicted inside the intelligent shoe in the predicted temperature module, the heat dissipation state, the thermal conductivity state, the heat dissipation power and the standard foot temperature parameters set in the temperature judgment module, and calculate the heat dissipation control parameters of the intelligent shoe, and then dissipate the heat of the intelligent shoe according to the calculated heat dissipation control parameters. When the intelligent shoe is in the heat dissipation process, the temperature of the foot position corresponding to the bearing position point marked as 1 is monitored in real time. When the real-time monitored foot temperature is lower than the set standard foot temperature parameter, the heat dissipation function of the intelligent shoe is stopped. By calculating the heat dissipation control parameters of the intelligent shoe, the discomfort caused by uncomfortable foot temperature can be reduced and the overall comfort of the user can be improved. At the same time, the intelligent shoe can avoid unnecessary energy waste and improve energy efficiency by accurately controlling the heat dissipation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A unit block diagram of the present invention;

[0038] Figure 2 It is a block diagram of the module unit of the present invention.

[0039] The meaning of each number in the figure is:

[0040] 1. Amplitude position unit; 11. Movement amplitude module; 12. Position fitting module;

[0041] 2. Calculation and judgment unit; 21. Trigger calculation module; 22. Temperature judgment module;

[0042] 3. Change prediction unit; 31. Temperature change module; 32. Prediction temperature module; 4. Intelligent heat dissipation unit. DETAILED DESCRIPTION

[0043] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The present invention provides an intelligent heat dissipation shoe system based on user physiological data analysis, please refer to Figure 1 , including an amplitude position unit 1, a calculation and judgment unit 2, a change prediction unit 3 and an intelligent heat dissipation unit 4;

[0045] The amplitude position unit 1 obtains the pressure and acceleration data of the cycle time through the sensor to calculate the acceleration peak value of the smart shoe and the change slope of the pressure data, and then comprehensively analyzes the vibration amplitude index of the smart shoe to determine the vibration amplitude of the smart shoe. When the smart shoe produces a high movement amplitude, the pressure matrix is ​​organized according to the pressure data using the matrix and the bearing value and bearing position point of the first three smart shoes are retrieved. The bearing value of the first three smart shoes is used to determine whether the foot and the insole in the bearing position point are completely fitted. When the foot and the insole in the bearing position point are completely fitted, the bearing position point is marked as 1; the calculation and judgment unit 2 is used to receive the command that the foot and the insole in the bearing position point in the amplitude position unit 1 are completely fitted. The calculation and judgment unit 2 obtains the bearing position point marked as 1 and the number of marks from the amplitude position unit 1. When the foot and the insole are completely fitted, the sensor in the smart shoe and the smart bracelet worn by the user are triggered to detect the foot according to the bearing position point marked as 1. The temperature of the foot is measured and the average temperature of the foot is calculated. At the same time, the smart bracelet worn by the user obtains physiological body temperature data and calculates the average physiological body temperature. The average physiological body temperature and the average foot temperature are used to determine whether the physiological body temperature and the foot temperature are increased by using the set standard physiological body temperature parameters and the set standard foot temperature parameters. When the physiological body temperature and the foot temperature are increased, the heat, heat dissipation power and heat dissipation state in the smart shoe are recorded; the change prediction unit 3 is used to receive the command of the calculation and judgment unit 2 that the physiological body temperature and the foot temperature are increased. The change prediction unit 3 obtains the heat, heat dissipation power and heat dissipation state in the smart shoe from the calculation and judgment unit 2 and calculates the temperature change inside the smart shoe, and then predicts the internal temperature of the smart shoe; the smart heat dissipation unit 4 is used to receive the internal temperature, heat dissipation state and heat dissipation power of the smart shoe predicted in the change prediction unit 3 and the standard foot temperature parameters set in the calculation and judgment unit 2, calculate the heat dissipation control parameters of the smart shoe, and then dissipate the heat of the smart shoe according to the calculated heat dissipation control parameters.

[0046] The following is a refinement of the above units, see Figure 2 ;

[0047] The amplitude position unit 1 includes a motion amplitude module 11 and a position fitting module 12;

[0048] The movement amplitude module 11 obtains the pressure data p(t) and acceleration data a(t) of the smart shoe during the cycle time t (the cycle time is 5 minutes) through the pressure sensor and acceleration sensor in the smart shoe, records the number of acceleration data during the cycle time, and selects the maximum acceleration a(t) from the maximum acceleration a(t) during the cycle time. max and the minimum acceleration a(t) min , according to the maximum acceleration a(t)max and the minimum acceleration a(t) min Calculate the peak value of the smart shoe acceleration to obtain the calculated peak value of the smart shoe acceleration A(t)=a(t)max -a(t) min , calculate the slope of pressure data change based on pressure data p(t) Among them, dp(t) represents a small change in the pressure data p(t), gt represents a small change in the cycle time t. By monitoring the pressure change slope, the smart shoe can respond to the user's activity state changes more quickly, improve the dynamics of pressure monitoring, and input the calculated smart shoe acceleration peak value A and the pressure data change slope S into the machine learning model. The machine learning model outputs weight coefficients α and β corresponding to the calculated smart shoe acceleration peak value A and the pressure data change slope S. The calculated smart shoe acceleration peak value A, the pressure data change slope S and the weight coefficients α and β are used to perform a comprehensive analysis of the smart shoe vibration amplitude index. By integrating the data of multiple indicators, the influence of measurement errors and local anomalies can be reduced, and the accuracy of prediction can be improved. The smart shoe vibration amplitude index Cx obtained by comprehensive analysis and the set vibration amplitude index are then used to judge the vibration amplitude of the smart shoe. When the smart shoe vibration amplitude index Cx obtained by comprehensive analysis is greater than the set vibration amplitude index, it means that the user is wearing the smart shoe for exercise, causing the smart shoe to produce a high movement amplitude.

[0049] Comprehensive analysis of the realization principle of the vibration amplitude index of smart shoes:

[0050] Collect and calculate the peak value A of the smart shoe acceleration, the slope S of the pressure data change, and the weight coefficients α and β to comprehensively analyze the smart shoe vibration amplitude index, and obtain the comprehensive analysis of the smart shoe vibration amplitude index Cx. The specific algorithm formula is:

[0051] Cx=αA+βB;

[0052] Among them, this formula is used to comprehensively analyze the vibration amplitude index of smart shoes. By integrating the data of multiple indicators, it can reduce the impact of measurement errors and local anomalies and improve the accuracy of prediction;

[0053] The position fitting module 12 is used to receive the high movement amplitude command from the movement amplitude module 11. The position fitting module 12 obtains the pressure data p(t) from the movement amplitude module 11, organizes the pressure matrix according to the pressure data p(t) using a matrix, and retrieves the first three smart shoe bearing values ​​p according to the organized pressure matrix. csl and the bearing position point (i, j), and then according to the bearing value p of the first three smart shoes csl Calculate the average bearing capacity at time t The average bearing capacity at time t Calculating the tolerance threshold Among them, k is a constant with a value range of (0.5, 1.5), using the bearing capacity values ​​p of the first three smart shoes cslThe tolerance threshold χ is used to judge whether the foot and the insole are completely in contact at the tolerance position point (i, j) at time t. By concentrating the key area positions of the foot, the measurement range and the number of unnecessary temperature sensors are reduced, and the resolution and energy efficiency of the temperature data are improved. At the same time, when the key area positions of the foot are concentrated and the foot and the insole are completely in contact, the foot temperature can be accurately read, avoiding the error of reducing the foot temperature measurement due to unstable contact, and improving the accuracy of temperature measurement. When the tolerance value p of the smart shoe is csl When the force value p of the smart shoe is greater than the bearing capacity threshold χ, it means that the foot and the insole are completely in contact at the bearing capacity point (i, j) at time t, and the bearing capacity point (i, j) at time t is marked as 1, and the number of marks is recorded. csl When it is less than the bearing capacity threshold χ, it means that the foot and the insole at the bearing capacity position point (i, j) at time t are not completely in contact, and the bearing capacity position point (i, j) at time t is marked as 0;

[0054] The principle of implementing the pressure matrix by using the matrix organization in the position fitting module 12 is as follows:

[0055] Collect pressure data p(t) to organize the pressure matrix, and obtain the pressure matrix p of the organization. The specific algorithm formula is:

[0056]

[0057] Where the array is m×n, then the size of the tissue pressure matrix p is m×n, where P i,j (t) represents the bearing capacity value of the i-th row and j-th column at time t. This formula is used to organize the pressure matrix.

[0058] The calculation and judgment unit 2 includes a trigger calculation module 21 and a temperature judgment module 22;

[0059] The trigger calculation module 21 is used to receive the command of the position fitting module 12 that the foot and the insole are completely fitted in the force position point at time t, and the trigger calculation module 21 obtains the force position point (i, j) marked as 1 and the number of marks from the position fitting module 12. When the command of the foot and the insole are completely fitted in the force position point at time t is received, the temperature sensor in the smart shoe and the smart bracelet worn by the user are triggered. The temperature sensor in the smart shoe detects the foot temperature Tz corresponding to the force position point (i, j) according to the force position point (i, j) marked as 1, and the smart bracelet worn by the user obtains physiological data, and then obtains physiological body temperature data Tw from the physiological data, and calculates the physiological body temperature average value according to the physiological body temperature data Tw Among them, Tw(t) refers to the physiological body temperature data at time t, and N refers to the number of physiological body temperature data. According to the average value of physiological body temperature, the smart shoe can adjust the working state of the cooling system as a whole to ensure that the user's foot temperature is coordinated with the overall body temperature and improve comfort. When the number of marks is greater than 1, the average foot temperature is calculated based on the foot temperature Tz. Wherein, Tz(t) refers to the foot temperature at time t, and M refers to the number of physiological body temperature data. By calculating the average value of the foot temperature, the temperature condition of the entire foot can be comprehensively evaluated, rather than relying solely on the data of a single measurement point. When the number of marks is less than 1, it is not necessary to calculate the average value of the foot temperature, and the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 is transmitted to the temperature judgment module 22;

[0060] The temperature judgment module 22 is used to receive the average physiological temperature in the trigger calculation module 21 And receive the average foot temperature in the trigger calculation module 21 Or the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1, using the average physiological body temperature and average foot temperature Determine whether the physiological body temperature and foot temperature are elevated by comparing with the set standard physiological body temperature parameters and the set standard foot temperature parameters, or use the average physiological body temperature The foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 and the set standard physiological body temperature parameters and the set standard foot temperature parameters are used to determine whether the physiological body temperature and the foot temperature are increased;

[0061] The specific judgment situations in the temperature judgment module 22 include:

[0062] Case 1: When the average physiological temperature Greater than the set standard physiological temperature parameters, and the average foot temperature Or when the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 is greater than the set standard foot temperature parameter, it means that the user consumes energy during exercise, and the energy consumption generates heat in the smart shoe, which leads to an increase in physiological body temperature and foot temperature, and records the heat in the smart shoe Q(t), environmental factor E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), and thermal conductivity state Te(t);

[0063] Case 2: When the average physiological temperature Greater than the set standard physiological temperature parameters, and the average foot temperature Or when the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased;

[0064] Case 3: When the average physiological temperature Lower than the set standard physiological temperature parameter, and the average foot temperature Or when the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased;

[0065] Case 4: When the physiological temperature average Lower than the set standard physiological temperature parameter, and the average foot temperature Or when the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 is greater than the set standard foot temperature parameter, it means that the user consumes energy during exercise, and the energy consumption generates heat in the smart shoe, which leads to an increase in physiological body temperature and foot temperature, and records the heat in the smart shoe Q(t), environmental factor E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), and thermal conductivity state Te(t);

[0066] The change prediction unit 3 includes a temperature change module 31 and a predicted temperature module 32;

[0067] The temperature change module 31 is used to receive the command of the temperature judgment module 22 that the physiological body temperature and the foot temperature increase. The temperature change module 31 obtains the heat Q(t), environmental factor E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), and thermal conductivity state Te(t) in the smart shoe from the temperature judgment module 22, and inputs the heat Q(t), environmental factor E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), and thermal conductivity state Te(t) in the smart shoe into the machine learning model. The machine learning model outputs the influence coefficient δ of the heat source on the temperature change, the influence coefficient ε of the environmental factor on the temperature change, the influence coefficient φ of the heat dissipation power on the temperature change, and the influence coefficient of the heat dissipation state on the temperature change The influence coefficient of thermal conductivity on temperature change γ is calculated based on the heat Q(t) in the smart shoe, environmental factors E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), thermal conductivity state Te(t), the influence coefficient of heat source on temperature change δ, the influence coefficient of environmental factors on temperature change ε, the influence coefficient of heat dissipation power on temperature change φ, and the influence coefficient of heat dissipation state on temperature change. The influence coefficient γ of the thermal conductivity state on the temperature change calculates the temperature change ΔT(t) inside the smart shoe at time t. By comprehensively considering multiple factors, the smart shoe can specifically adjust the temperature of specific areas of the foot and reduce the discomfort caused by temperature discomfort, thereby improving the overall comfort of the user;

[0068] Principle of calculating the temperature change inside the smart shoe at time t:

[0069] Heat Q(t) in smart shoes, environmental factors E(t), heat dissipation power Pn(t), heat dissipation state Sn(t), thermal conductivity state Te(t), influence coefficient of heat source on temperature change δ, influence coefficient of environmental factors on temperature change ε, influence coefficient of heat dissipation power on temperature change φ, influence coefficient of heat dissipation state on temperature change The influence coefficient γ of the thermal conductivity state on the temperature change is used to calculate the temperature change inside the smart shoe at time t. The specific algorithm formula is:

[0070]

[0071] Among them, this formula is used to calculate the temperature change inside the smart shoe at time t. By comprehensively considering multiple factors, the smart shoe can specifically adjust the temperature of specific areas of the foot to provide a more personalized comfort experience;

[0072] The temperature prediction module 32 is used to receive the temperature change ΔT(t) inside the smart shoe in the temperature change module 31 and the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 in the trigger calculation module 21, and the number of marks. When the number of marks is greater than 1, the maximum foot temperature Tzmax(t) at time t is selected from the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1, and the maximum foot temperature Tz is used to calculate the foot temperature Tzmax(t). max (t) and the temperature change ΔT(t) inside the smart shoe predicts the temperature T inside the smart shoe at the future time t+Δt (Δt represents the time step) pred (t+Δt)=Tz max (t)+ΔT(t), when the number of marks is less than 1, the foot temperature Tz corresponding to the bearing position point (i, j) marked as 1 and the temperature change ΔT(t) inside the smart shoe are used to predict the temperature T inside the smart shoe at the future time t+Δt pred (t+Δt)=Tz(t)+ΔT(t), where Tz(t) refers to the foot temperature at time t. The foot temperature at the force-bearing position can be used to more accurately understand the heat distribution and changes in the smart shoes in specific areas of the foot during activities. Combined with the temperature changes inside the smart shoes, the dynamic changes of the foot temperature can be more comprehensively analyzed, thereby improving the accuracy of temperature prediction.

[0073] The intelligent heat dissipation unit 4 is used to receive the temperature T inside the intelligent shoe predicted at the future time t+Δt in the predicted temperature module 32. pred (t+Δt), heat dissipation state Sn(t), thermal conductivity state Te(t), heat dissipation power Pn(t) and standard foot temperature parameter T set in the temperature judgment module 22 tar , and use the control algorithm to predict the temperature T inside the smart shoe at the future time t+Δt pred(t+Δt), heat dissipation state Sn(t), thermal conductivity state Te(t), heat dissipation power Pn(t), set standard foot temperature parameter T tar Calculate the heat dissipation control parameters of the smart shoe, and then dissipate the heat of the smart shoe according to the calculated heat dissipation control parameters. During the heat dissipation process, the smart shoe monitors the temperature of the foot position corresponding to the bearing position point (i, j) marked as 1 in real time. When the real-time monitored foot temperature is lower than the set standard foot temperature parameter, the heat dissipation function of the smart shoe is stopped. By calculating the heat dissipation control parameters of the smart shoe, the discomfort caused by the uncomfortable foot temperature can be reduced, and the overall comfort of the user can be improved. At the same time, the smart shoe can avoid unnecessary energy waste and improve energy efficiency when accurately controlling the heat dissipation.

[0074] The implementation principle of using control algorithm to calculate heat dissipation control parameters:

[0075] Collect and predict the temperature T at the future time t+Δt pred (t+Δt), heat dissipation state Sn(t), thermal conductivity state Te(t), heat dissipation power Pn(t), set standard foot temperature parameter T tar Calculate the heat dissipation control parameter Hs, the specific algorithm formula is:

[0076]

[0077] Among them, η refers to the heat dissipation control parameter, K p Proportional control coefficient, K i Integral control coefficient, T pr (μ) refers to the predicted temperature at time μ, μ is a variable representing any time point from the initial time 0 to the current time t+Δt, dμ represents a small increment of the integral variable, K d Derivative control coefficient, Represents the derivative with respect to time t. This formula is used to calculate the heat dissipation control parameters of smart shoes. By predicting the future temperature and heat dissipation status, smart shoes can adjust the working parameters of the cooling system in real time to ensure that the foot is always kept in a comfortable temperature range, thereby improving user comfort.

[0078] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. The intelligent cooling shoe system based on the analysis of user physiological data is characterized by: It comprises an amplitude position unit (1), a calculation and judgment unit (2), a change prediction unit (3) and an intelligent heat dissipation unit (4); The amplitude position unit (1) obtains pressure and acceleration data of a periodic time through a sensor to calculate the acceleration peak value of the smart shoe and the change slope of the pressure data, and then comprehensively analyzes the vibration amplitude index of the smart shoe to determine the vibration amplitude of the smart shoe. When the smart shoe generates a high movement amplitude, the pressure matrix is ​​organized according to the pressure data using a matrix and the first three smart shoe bearing values ​​and bearing position points are retrieved. The first three smart shoe bearing values ​​are used to determine whether the foot at the bearing position point is completely fitted with the insole. When the foot at the bearing position point is completely fitted with the insole, the bearing position point is marked as 1. The calculation and judgment unit (2) is used to receive a command that the foot and the insole are completely in contact with each other in the force bearing position point in the amplitude position unit (1), and the calculation and judgment unit (2) obtains the force bearing position point marked as 1 and the number of marks from the amplitude position unit (1). When the foot and the insole are completely in contact with each other, the sensor in the smart shoe and the smart bracelet worn by the user are triggered, and the foot temperature is detected according to the force bearing position point marked as 1 and the average foot temperature is calculated. At the same time, the smart bracelet worn by the user obtains physiological body temperature data and calculates the average physiological body temperature. The average physiological body temperature and the average foot temperature are used together with the set standard physiological body temperature parameters and the set standard foot temperature parameters to determine whether the physiological body temperature and the foot temperature are increased. When the physiological body temperature and the foot temperature are increased, the heat, heat dissipation power and heat dissipation status in the smart shoe are recorded. The change prediction unit (3) is used to receive a command from the calculation and judgment unit (2) indicating that the physiological body temperature and the foot temperature have increased. The change prediction unit (3) obtains the heat, heat dissipation power, and heat dissipation state inside the smart shoe from the calculation and judgment unit (2), calculates the temperature change inside the smart shoe, and then predicts the temperature inside the smart shoe. The intelligent heat dissipation unit (4) is used to receive the internal temperature, heat dissipation state, and heat dissipation power of the intelligent shoe predicted by the change prediction unit (3) and the standard foot temperature parameter set in the calculation and judgment unit (2), calculate the heat dissipation control parameter of the intelligent shoe, and then dissipate the heat of the intelligent shoe according to the calculated heat dissipation control parameter.

2. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 1 is characterized in that: The amplitude position unit (1) comprises a motion amplitude module (11) and a position fitting module (12); The motion amplitude module (11) obtains pressure and acceleration data of the smart shoe through a pressure sensor and an acceleration sensor in the smart shoe, records the amount of acceleration data within a cycle time, calculates the peak value of the acceleration of the smart shoe from the maximum acceleration and the minimum acceleration within the cycle time, calculates the slope of the pressure data change according to the pressure data, comprehensively analyzes the vibration amplitude index of the smart shoe using the calculated peak value of the acceleration of the smart shoe and the slope of the pressure data change, and then uses the comprehensively analyzed vibration amplitude index of the smart shoe to determine the vibration amplitude of the smart shoe; The position fitting module (12) is used to receive a high movement amplitude command from the movement amplitude module (11), the position fitting module (12) obtains pressure data from the movement amplitude module (11), organizes a pressure matrix according to the pressure data using a matrix, retrieves the bearing force values ​​and bearing force position points of the first three smart shoes, calculates an average bearing force value according to the bearing force values ​​of the first three smart shoes, and then calculates a bearing force threshold, and uses the bearing force values ​​of the first three smart shoes and the bearing force threshold to determine whether the foot and the insole at the bearing force position point are completely fitted; When the bearing force value of the smart shoe is greater than the bearing force threshold, it means that the foot and the insole at the bearing force position point are completely in contact with each other, and the bearing force position point is marked as 1, and the number of marks is recorded; When the bearing force value of the smart shoe is less than the bearing force threshold, it means that the foot and the insole at the bearing force position point are not completely fitted together, and the bearing force position point is marked as 0.

3. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 2 is characterized in that: The principle of implementing the matrix organization pressure matrix in the position fitting module (12) is as follows: Collecting Pressure Data p (t) Organizational stress matrix, derive the organization's stress matrix p , the specific algorithm formula is: The array is m×n , then the pressure matrix of the organization p The size is m×n ,in P i,j (t) Indicates at time t Moment i Line j The bearing capacity of the column.

4. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 2 is characterized in that: The calculation and judgment unit (2) comprises a trigger calculation module (21) and a temperature judgment module (22); The trigger calculation module (21) is used to receive a command for the foot and the insole to be completely fitted in the force bearing position point in the position fitting module (12), and the trigger calculation module (21) obtains the force bearing position point marked as 1 and the number of marks from the position fitting module (12). When the command for the foot and the insole to be completely fitted is received, the temperature sensor in the smart shoe and the smart bracelet worn by the user are triggered. The temperature sensor in the smart shoe detects the foot temperature corresponding to the force bearing position point based on the force bearing position point marked as 1, and the smart bracelet worn by the user obtains physiological body temperature data and calculates the average physiological body temperature. When the number of marks is greater than 1, the average foot temperature is calculated based on the foot temperature; When the number of marks is less than 1, it is not necessary to calculate the average foot temperature, and the foot temperature corresponding to the bearing position point marked as 1 is transmitted to the temperature judgment module (22); The temperature judgment module (22) is used to receive the average value of the physiological body temperature in the trigger calculation module (21), and receive the average value of the foot temperature in the trigger calculation module (21) or the foot temperature corresponding to the bearing position point marked as 1, and use the average value of the physiological body temperature and the average value of the foot temperature to judge whether the physiological body temperature and the foot temperature are increased, or use the average value of the physiological body temperature and the foot temperature corresponding to the bearing position point marked as 1 to judge whether the physiological body temperature and the foot temperature are increased.

5. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 4 is characterized in that: The specific judgment conditions in the temperature judgment module (22) include: Case 1: When the average physiological body temperature is greater than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is greater than the set standard foot temperature parameter, it indicates that the physiological body temperature and foot temperature have increased, and the heat, environmental factors, heat dissipation power, heat dissipation state, and thermal conductivity state in the smart shoe are recorded; Case 2: When the average physiological body temperature is greater than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased; Case 3: When the average physiological body temperature is less than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is less than the set standard foot temperature parameter, it means that the foot temperature has not increased; Case 4: When the average physiological body temperature is less than the set standard physiological body temperature parameter, and the average foot temperature or the foot temperature corresponding to the bearing position point marked as 1 is greater than the set standard foot temperature parameter, it indicates that the physiological body temperature and the foot temperature are increased.

6. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 4 is characterized in that: The change prediction unit (3) comprises a temperature change module (31) and a predicted temperature module (32); The temperature change module (31) is used to receive commands from the temperature judgment module (22) indicating an increase in physiological body temperature and foot temperature. The temperature change module (31) obtains heat, environmental factors, heat dissipation power, heat dissipation state, and heat conduction state inside the smart shoe from the temperature judgment module (22) and calculates the temperature change inside the smart shoe. The predicted temperature module (32) is used to receive the temperature change amount inside the smart shoe in the temperature change module (31) and the foot temperature corresponding to the bearing force position point marked as 1 in the trigger calculation module (21), and the number of marks; When the number of marks is greater than 1, the maximum foot temperature is selected from the foot temperatures corresponding to the force-bearing position points marked as 1, and the temperature inside the smart shoe is predicted using the maximum foot temperature and the temperature change inside the smart shoe; When the number of marks is less than 1, the temperature inside the smart shoe is predicted using the foot temperature corresponding to the force bearing position point marked as 1 and the temperature change inside the smart shoe.

7. The intelligent heat dissipation shoe system based on user physiological data analysis according to claim 6 is characterized in that: The intelligent heat dissipation unit (4) is used to receive the temperature predicted inside the intelligent shoe in the predicted temperature module (32), the heat dissipation state, the heat conduction state, the heat dissipation power and the standard foot temperature parameter set in the temperature judgment module (22), and calculate the heat dissipation control parameter of the intelligent shoe, and then dissipate the heat of the intelligent shoe according to the calculated heat dissipation control parameter. When the intelligent shoe is in the heat dissipation process, the temperature of the foot position corresponding to the bearing position point marked as 1 is monitored in real time. When the foot temperature monitored in real time is lower than the set standard foot temperature parameter, the heat dissipation function of the intelligent shoe is stopped.

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