Intelligent body temperature central monitoring and warning system

Abstract

The invention discloses an intelligent body temperature central monitoring and warning system, which relates to the technical field of medical appliances, and comprises the following steps: extracting a first body temperature sensor in distributed body temperature sensors, and obtaining a first real-time body temperature of a target user through the first body temperature sensor; calling a preset transmission strategy, and transmitting the first real-time body temperature to a data processing center according to the preset transmission strategy; activating a predetermined data calibration mechanism of a memory in the data processing center, and performing calibration processing on the first real-time body temperature according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature; and visually displaying the first effective real-time body temperature. The technical problems that in the prior art, real-time, continuous and remote monitoring cannot be achieved in the body temperature monitoring process, and an effective body temperature calibration and warning mechanism is lacked are solved, and the technical effects that continuous monitoring, remote transmission and real-time visualization of the body temperature are achieved, and the efficiency and accuracy of body temperature monitoring are improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to an intelligent body temperature central monitoring and warning system. Background Art

[0002] Currently, body temperature monitoring technology faces challenges in terms of real-time, continuity, and remote monitoring. Traditional body temperature monitoring methods such as mercury thermometers and electronic thermometers can usually only perform intermittent measurements and cannot achieve real-time and continuous tracking of the target user's body temperature. This method often has the problem of long measurement intervals and inability to detect abnormal changes in body temperature in a timely manner. The body temperature monitoring methods in the existing technology usually lack effective body temperature data calibration and automatic warning mechanisms, which makes it impossible to issue warnings in time when abnormal body temperature occurs, thereby affecting the health monitoring of the target user. Summary of the invention

[0003] The present application provides an intelligent body temperature central monitoring and warning system, which is used to solve the technical problems that the existing technology cannot achieve real-time, continuous and remote monitoring in body temperature monitoring and lacks effective body temperature calibration and warning mechanism.

[0004] In view of the above problems, the present application provides an intelligent body temperature central monitoring and warning system.

[0005] The present application provides an intelligent body temperature central monitoring and warning system, the system comprising:

[0006] An intelligent wearable body temperature monitoring device, the intelligent wearable body temperature monitoring device is used to extract the first body temperature sensor in the distributed body temperature sensor, and obtain the first real-time body temperature of the target user through the first body temperature sensor, wherein the first real-time body temperature corresponds to the first body part of the target user; a data transmission module, the data transmission module is used to call a predetermined transmission strategy, and transmit the first real-time body temperature to a data processing center according to the predetermined transmission strategy; a central management platform, the central management platform is used to activate a predetermined data calibration mechanism in the memory of the data processing center, and calibrate the first real-time body temperature according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature; an information display device, the information display device is used to visually display the first effective real-time body temperature.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The present application extracts the first temperature sensor in the distributed temperature sensor, and obtains the first real-time temperature of the target user through the first temperature sensor; calls a predetermined transmission strategy, and transmits the first real-time temperature to the data processing center according to the predetermined transmission strategy; activates the predetermined data calibration mechanism in the memory of the data processing center, and calibrates the first real-time temperature according to the predetermined data calibration mechanism to obtain the first effective real-time temperature; and visualizes the first effective real-time temperature. The present invention solves the technical problems that the prior art cannot realize real-time, continuous, and remote monitoring in temperature monitoring, and lacks an effective temperature calibration and warning mechanism. The real-time temperature of the target user is obtained through a distributed temperature sensor, and the data is transmitted to the data processing center through a data transmission module. The central management platform activates the predetermined data calibration mechanism to calibrate the temperature data to obtain the effective real-time temperature. The information display device visualizes the calibrated temperature data, realizing continuous monitoring, remote transmission and real-time visualization of temperature, and improving the efficiency and accuracy of temperature monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0010] Figure 1 A schematic diagram of the structure of an intelligent body temperature central monitoring and warning system provided in an embodiment of the present application;

[0011] Figure 2 A schematic diagram of the structure of a central management platform of an intelligent body temperature central monitoring and warning system provided in an embodiment of the present application.

[0012] Explanation of the accompanying drawings: intelligent wearable body temperature monitoring device 11, data transmission module 12, central management platform 13, information display device 14. DETAILED DESCRIPTION

[0013] The present application provides an intelligent body temperature central monitoring and warning system to solve the technical problems that the prior art cannot achieve real-time, continuous and remote monitoring in body temperature monitoring and lacks an effective body temperature calibration and warning mechanism. The real-time body temperature of the target user is obtained through a distributed body temperature sensor, and the data is transmitted to the data processing center through a data transmission module. The central management platform activates a predetermined data calibration mechanism to calibrate the body temperature data to obtain an effective real-time body temperature. The information display device visualizes the calibrated body temperature data, thereby realizing continuous monitoring, remote transmission and real-time visualization of body temperature, and improving the efficiency and accuracy of body temperature monitoring.

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0016] Examples, such as Figure 1 As shown, the embodiment of the present application provides an intelligent body temperature central monitoring and warning system, the system comprising:

[0017] The smart wearable body temperature monitoring device 11 is used to extract the first body temperature sensor in the distributed body temperature sensor, and obtain the first real-time body temperature of the target user through the first body temperature sensor, wherein the first real-time body temperature corresponds to the first body part of the target user.

[0018] In an embodiment of the present application, the intelligent wearable body temperature monitoring device monitors the body temperature of the target user in real time through multiple distributed body temperature sensors. Multiple distributed body temperature sensors are distributed in different parts of the monitoring target, such as armpits, chest, etc. The body temperature of the target user is monitored by the first body temperature sensor in the distributed body temperature sensors to obtain the first real-time body temperature of the target user. The first body temperature sensor refers to any one of the distributed body temperature sensors, and each body temperature sensor is used to monitor the body temperature of different parts of the target user.

[0019] The first real-time body temperature obtained through monitoring corresponds to a first body part of the target user. For example, the real-time body temperature detected by a body temperature sensor distributed at the armpit is the temperature at the armpit of the target user.

[0020] Furthermore, in the system provided in the embodiment of the application, the smart wearable body temperature monitoring device 11 also includes:

[0021] A real-time body temperature time series acquisition module, the real-time body temperature time series acquisition module is used to obtain the first real-time body temperature time series of the first human body part through the first body temperature sensor; a regression fitting processing module, the regression fitting processing module is used to perform polynomial regression fitting processing on the first body temperature scatter plot drawn according to the first real-time body temperature time series to obtain a first fitting formula; a real-time body temperature verification module, the real-time body temperature verification module is used to analyze the first fitting formula to obtain a first real-time predicted body temperature, and verify the first real-time body temperature through the first real-time predicted body temperature.

[0022] In the embodiment of the present application, first, the real-time body temperature time series acquisition module continuously monitors the temperature changes of the target user through the first body temperature sensor. The real-time body temperature time series acquisition module is responsible for acquiring the first real-time body temperature time series of the target user within a period of time. The first real-time body temperature time series refers to a continuous body temperature data sequence that records the changes in the body temperature of the first body part (such as the armpit, chest, etc.) of the target user within a certain period of time.

[0023] Next, the regression fitting processing module is responsible for a deeper analysis of the first real-time body temperature time series data. The regression fitting processing module first draws a first body temperature scatter plot based on the first real-time body temperature time series, and each point in the scatter plot represents the body temperature data at a certain moment. Through these scatter plots, the trend of body temperature changes over time can be intuitively seen. Then, the regression fitting processing module uses a polynomial regression algorithm to fit the data in the first body temperature scatter plot to generate a first fitting formula.

[0024] Finally, the real-time body temperature verification module further verifies the collected body temperature data to ensure its accuracy and reliability. The working principle of this module is to predict the first real-time predicted body temperature of the target user at a certain moment by analyzing the first fitting formula generated by regression fitting. Then, the predicted body temperature is compared with the first real-time body temperature actually collected. Specifically, after the body temperature data is collected, the fitting curve generated by regression fitting, that is, the first fitting formula, is used to predict the expected body temperature of the target user at the same time, and the first real-time predicted body temperature is obtained. If there is a significant difference between the actual measured body temperature and the predicted body temperature, the verification mechanism is triggered and re-collected. At this time, if the difference between the measured body temperature and the predicted body temperature exceeds 0.5 degrees Celsius, it is considered that there is an abnormality in the measurement, and the body temperature data is automatically re-collected, and the measured data is re-checked to ensure the accuracy of the data.

[0025] Furthermore, in the system provided in the embodiment of the application, the smart wearable body temperature monitoring device 11 also includes:

[0026] A circuit wake-up module, the circuit wake-up module is used to activate a timed wake-up circuit, wherein the timed wake-up circuit has an identifier of a predetermined time interval; a body temperature monitoring module, the body temperature monitoring module is used to wake up the first body temperature sensor based on the predetermined time interval to perform dynamic body temperature monitoring on the first human body part to obtain the first real-time body temperature timing.

[0027] In an embodiment of the present application, the circuit wake-up module and the body temperature monitoring module work together to ensure that the body temperature data can be dynamically monitored within a predetermined time interval, thereby obtaining an accurate real-time body temperature timing.

[0028] Specifically, the function of the circuit wake-up module is to activate the timed wake-up circuit, which has a predetermined time interval flag, and is used to automatically wake up the body temperature sensor within a specific time interval. This time interval is preset according to demand, for example, the body temperature sensor is automatically activated at a certain interval (such as 30 seconds, 1 minute or 2 minutes). In this way, the device can measure body temperature at regular intervals without manual intervention by the user. The design of the timed wake-up circuit not only ensures the continuous collection of body temperature data, but also effectively manages battery consumption, because it only activates the sensor when necessary, avoiding energy waste caused by continuous operation.

[0029] When the timed wake-up circuit is triggered, the body temperature monitoring module immediately performs a wake-up operation and activates the first body temperature sensor. At this time, the body temperature sensor is awakened and starts to measure the body temperature of the first body part of the target user. The body temperature monitoring module periodically wakes up the body temperature sensor according to the set predetermined time interval and collects the user's body temperature data in real time. Each collected body temperature data will form a continuous body temperature data sequence, that is, the first real-time body temperature time series.

[0030] The data transmission module 12 is used to retrieve a predetermined transmission strategy and transmit the first real-time body temperature to a data processing center according to the predetermined transmission strategy.

[0031] Furthermore, in the system provided by the application embodiment, the data transmission module performs data transmission via Bluetooth, WiFi or wireless radio frequency technology in a specific frequency band.

[0032] In an embodiment of the present application, the data transmission module calls a predetermined transmission strategy, which is a preset rule that determines how to process and transmit body temperature data, including the mode, frequency, and security measures of data transmission. Specifically, the predetermined transmission strategy stipulates that the body temperature data is encrypted for transmission to ensure that the data will not be stolen or tampered with by unauthorized third parties during the transmission process. Encrypted transmission is usually implemented using a symmetric encryption algorithm, such as AES (Advanced Encryption Standard). This encryption method ensures the security of the data and has efficient and fast processing capabilities, which is suitable for real-time transmission requirements.

[0033] Once the data is encrypted, the data transmission module will transmit the first real-time body temperature data to the data processing center through a set communication method according to a set predetermined transmission strategy. In this application, the data transmission module can transmit data through a variety of wireless communication methods, including Bluetooth, WiFi or other wireless radio frequency technologies in a specific frequency band.

[0034] The central management platform 13 is used to activate a predetermined data calibration mechanism stored in the memory of the data processing center, and calibrate the first real-time body temperature according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature.

[0035] Further, such as Figure 2 As shown, in the system provided by the application embodiment, the central management platform 13 also includes:

[0036] An individual characteristic information acquisition module, the individual characteristic information acquisition module is used to acquire the target multi-dimensional individual characteristic information of the target user; an environmental characteristic information acquisition module, the environmental characteristic information acquisition module is used to acquire the target multi-dimensional environmental characteristic information of the target user; a real-time body temperature calibration module, the real-time body temperature calibration module is used to calibrate the first real-time body temperature based on the predetermined data calibration mechanism and in combination with the target multi-dimensional individual characteristic information and the target multi-dimensional environmental characteristic information to obtain the first effective real-time body temperature; wherein the target multi-dimensional individual characteristic information includes characteristic information of a target individual basic dimension, a target individual physiological state dimension and a target individual psychological state dimension, wherein the target individual basic dimension includes at least individual age and individual gender, the target individual physiological state dimension includes at least physical activity, disease status, endocrine status, diet and drug status and sleep status, and the target individual psychological state dimension includes at least emotional fluctuations and biological rhythms; wherein the target multi-dimensional environmental characteristic information includes external temperature, external humidity and external air pressure.

[0037] In the embodiment of the present application, the central management platform activates a predetermined data calibration mechanism in the memory of the data processing center, and performs calibration processing on the first real-time body temperature according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature.

[0038] Specifically, first, the target multi-dimensional individual characteristic information of the target user is obtained through the individual characteristic information acquisition module. The target multi-dimensional individual characteristic information includes characteristic information of the target individual basic dimension, the target individual physiological state dimension and the target individual psychological state dimension. The target individual basic dimension includes at least the individual age and individual gender, the target individual physiological state dimension includes at least physical activity, disease state, endocrine condition, diet and drug condition and sleep state, and the target individual psychological state dimension includes at least emotional fluctuations and biological rhythms. In order to obtain the target individual basic dimension information, the target user's age and gender are obtained by extracting the health record of the target user. The target individual physiological state dimensions, such as physical activity, disease state, endocrine condition, etc., are continuously tracked by the health monitoring equipment worn by the user, such as a smart watch, to obtain the activity level and health status of the target user in real time. The target individual psychological state dimensions, such as emotional fluctuations and biological rhythms, are detected by the target user's self-report or smart devices, such as pressure sensing devices.

[0039] Next, the target multi-dimensional environmental characteristic information of the target user is obtained through the environmental characteristic information acquisition module. The target multi-dimensional environmental characteristic information includes external temperature, external humidity and external air pressure. This information is collected and obtained in real time through a thermometer, an environmental humidity sensor and a meteorological sensor (such as a barometer).

[0040] Once the target multi-dimensional individual characteristic information and the target multi-dimensional environmental characteristic information are obtained, the real-time body temperature calibration module calibrates the first real-time body temperature based on a predetermined data calibration mechanism and in combination with the target multi-dimensional individual characteristic information and the target multi-dimensional environmental characteristic information to obtain a first effective real-time body temperature.

[0041] Furthermore, in the system provided in the application embodiment, the central management platform 13 also includes:

[0042] A benchmark extraction module, the benchmark extraction module is used to sequentially extract the predetermined individual benchmark and the predetermined environmental benchmark in the predetermined data calibration mechanism; a plan reading module, the plan reading module is used to read the feature vectorization plan; a first vectorization processing module, the first vectorization processing module is used to sequentially vectorize the predetermined individual benchmark and the target multi-dimensional individual feature information according to the feature vectorization plan, and obtain an individual benchmark vector and a target individual vector respectively; a second vectorization processing module, the second vectorization processing module is used to sequentially vectorize the predetermined environmental benchmark and the target multi-dimensional environmental feature information according to the feature vectorization plan, and obtain an environmental benchmark vector and a target environmental vector respectively; a real-time body temperature weighted calibration module, the real-time body temperature weighted calibration module is used to perform weighted calibration on the first real-time body temperature using the individual similarity coefficient between the individual benchmark vector and the target individual vector and the environmental similarity coefficient between the environmental benchmark vector and the target environmental vector as weights to obtain the first effective real-time body temperature.

[0043] In an embodiment of the present application, first, the benchmark extraction module extracts individual benchmarks and environmental benchmarks from a predetermined data calibration mechanism. Individual benchmarks usually include physiological characteristics such as age, gender, and health status, while environmental benchmarks include external environmental conditions such as temperature, humidity, and air pressure. The predetermined individual benchmark is usually based on the standard body temperature data of healthy people, taking into account factors such as the average age, gender, and health status of the group, to derive a benchmark value suitable for most individuals. The predetermined environmental benchmark extracts applicable environmental data such as temperature, humidity, and air pressure based on local climate, seasonal changes, and other factors.

[0044] Next, the plan reading module reads the feature vectorization plan and provides processing rules for subsequent vectorization processing. The plan file usually uses a standard format (such as JSON or XML), which contains rules on how to vectorize individual features and environmental features. The file specifies which features need to be vectorized, how to quantify these features (for example, dividing age into different intervals, representing gender in binary, and representing physical activity intensity in categorical values, etc.), and clarifies the corresponding values ​​for each feature. By reading these rules, different individual and environmental data are processed according to predetermined standards.

[0045] Next, the first vectorization processing module vectorizes the target multi-dimensional individual feature information of the predetermined individual benchmark and the target user according to the feature vectorization plan. First, the basic information such as the age and gender of the individual is converted into a numerical vector. The age can be directly input as a numerical value, and the gender is expressed in binary form (such as male = 1, female = 0). Secondly, for physiological status information such as physical activity, disease status, and endocrine conditions, a similar method is used to convert these data into numerical values. For example, physical activity may be represented by "low / medium / high" as 0, 1, and 2, respectively, and information such as physiological status is also digitized in this way. In this way, through the standardization process, the system generates individual benchmark vectors and individual feature vectors of target users, forming numerical data that can be used for subsequent calculations.

[0046] The second vectorization processing module then performs similar vectorization processing on the environmental baseline and target environmental feature information. The collected environmental data, such as temperature, humidity, and air pressure, are converted into numerical form according to the rules of the feature vectorization plan. For example, the environmental temperature and humidity can be directly taken as their actual values, while the air pressure can be converted into standard air pressure units for representation, generating the environmental baseline vector and the target environmental feature vector.

[0047] The real-time body temperature weighted calibration module uses the similarity coefficients between the individual baseline vector and the target individual vector, and between the environmental baseline vector and the target environmental vector as weights to perform weighted calibration on the first real-time body temperature. The similarity coefficient between the individual baseline vector and the target individual vector is the individual similarity coefficient. To obtain the individual similarity coefficient, the cosine similarity method is first used to calculate the similarity between the individual baseline vector and the target individual vector. Then, the vector consistency number is calculated, that is, the number of identical items between the individual baseline vector and the target individual vector in each feature dimension is compared, and the ratio of the consistency number to the total number of dimensions is calculated to obtain the second similarity. Finally, the mean of the first similarity and the second similarity is used as the individual similarity coefficient. The environmental similarity coefficient between the environmental baseline vector and the target environmental vector is calculated using the cosine similarity principle.

[0048] Finally, the real-time body temperature weighted calibration module uses the individual similarity coefficient and the environmental similarity coefficient to perform weighted calibration on the first real-time body temperature to obtain the first effective real-time body temperature. Specifically, the individual similarity coefficient and the environmental similarity coefficient are respectively multiplied by the first effective real-time body temperature to obtain a weighted value. Then, these weighted values ​​are added and finally the average is taken to obtain the final first effective real-time body temperature.

[0049] Furthermore, in the system provided in the application embodiment, the central management platform 13 also includes:

[0050] A first similarity calculation module, the first similarity calculation module is used to calculate the similarity between the individual baseline vector and the target individual vector using the cosine similarity principle to obtain a first similarity; a second similarity calculation module, the second similarity calculation module is used to count the vector consistency number between the individual baseline vector and the target individual vector, and obtain the ratio of the vector consistency number to the total number of vectors, which is recorded as a second similarity; an individual similarity coefficient acquisition module, the individual similarity coefficient acquisition module is used to take the average of the first similarity and the second similarity, which is recorded as the individual similarity coefficient.

[0051] In an embodiment of the present application, the first similarity calculation module uses the cosine similarity principle to calculate the similarity between the individual reference vector and the target individual vector. Specifically, the individual reference vector represents the characteristics of the standard individual in multiple dimensions, and the target individual vector represents the characteristics of the target user in the same dimensions. By calculating the cosine similarity between the two vectors using the cosine similarity principle, a first similarity is obtained, which reflects the overall similarity between the target individual and the standard individual in the feature dimension.

[0052] Next, the second similarity calculation module counts the vector consistency number between the individual baseline vector and the target individual vector. The vector consistency number refers to whether the values ​​of the two vectors in each dimension are consistent, that is, whether they take the same value in the same dimension. If the values ​​in a certain dimension are the same, it is counted as a consistent item. After counting the consistent items in all dimensions, the consistency number is obtained, and then the ratio of the consistency number to the total number of dimensions of the vector is calculated to obtain the second similarity.

[0053] Finally, the individual similarity coefficient acquisition module takes the average of the first similarity and the second similarity, which is recorded as the individual similarity coefficient. Specifically, the individual similarity coefficient is obtained by summing the first similarity and the second similarity and then dividing by two.

[0054] The information display device 14 is used to visually display the first effective real-time body temperature.

[0055] In the embodiment of the present application, the information display device presents the first effective real-time body temperature through the display interface so that the staff can quickly and intuitively understand the temperature change trend and current status of the target user. The temperature fluctuation of the target user is displayed in the form of intuitive charts, temperature change curves, lists, etc., and the temperature is monitored in real time to see if it exceeds the normal range. In addition, the interface will also display other relevant information, such as the name, age and other basic information of the target user.

[0056] Furthermore, the system provided in the embodiment of the application further includes an intelligent warning module, and the intelligent warning module specifically includes:

[0057] A body temperature threshold judgment module, the body temperature threshold judgment module is used to judge whether the first effective real-time body temperature meets the preset body temperature threshold; a warning signal issuing module, the warning signal issuing module is used to issue a warning signal if it does not meet the threshold; an abnormal warning module, the abnormal warning module is used to call a predetermined warning mechanism based on the warning signal to warn the target user of abnormal body temperature; wherein the predetermined warning mechanism reminds the staff at least by sound, flashing and pop-up window.

[0058] In an embodiment of the present application, the body temperature threshold judgment module is used to judge whether the first effective real-time body temperature meets the predetermined body temperature threshold. The predetermined body temperature threshold includes a high temperature threshold and a low temperature threshold, which are used to judge whether the body temperature is too high or too low. If the first effective real-time body temperature exceeds the normal range, the body temperature is considered abnormal. The threshold judgment is set based on clinical medical standards. For example, the normal body temperature range for adults is 36.3°C to 37.2°C. If the body temperature is lower than 36.3°C or higher than 37.2°C, it may indicate abnormal body temperature.

[0059] If the first effective real-time body temperature exceeds the preset body temperature threshold, the warning signal issuing module immediately issues a warning signal and sends it to the abnormal warning module. After receiving the warning signal, the abnormal warning module further calls the preset warning mechanism and issues a specific abnormal body temperature warning. The preset warning mechanism includes sound alarms, flashing red lights, pop-up window reminders, etc., to ensure that staff can promptly notice the abnormal body temperature of the target user during busy work.

[0060] Furthermore, in the system provided in the application embodiment, the intelligent warning module is also used to obtain the real-time positioning information of the target user through a positioning sensor, and add the real-time positioning information to the abnormal body temperature warning.

[0061] In an embodiment of the present application, the intelligent warning module obtains the real-time positioning information of the target user through a positioning sensor, and adds the real-time positioning information to the abnormal temperature warning. Specifically, the position of the target user is tracked in real time by a positioning sensor, usually through GPS, Wi-Fi or Bluetooth positioning technology. These positioning information include the specific location of the user's current location. When the system detects that the target user's temperature is abnormal, the real-time positioning information of the target user is displayed or sent to the staff together with the abnormal temperature warning, so as to help them quickly locate the target user's position and take appropriate measures.

[0062] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0063] The present application extracts the first temperature sensor in the distributed temperature sensor, and obtains the first real-time temperature of the target user through the first temperature sensor; calls a predetermined transmission strategy, and transmits the first real-time temperature to the data processing center according to the predetermined transmission strategy; activates the predetermined data calibration mechanism in the memory of the data processing center, and calibrates the first real-time temperature according to the predetermined data calibration mechanism to obtain the first effective real-time temperature; and visualizes the first effective real-time temperature. The present invention solves the technical problems that the prior art cannot realize real-time, continuous, and remote monitoring in temperature monitoring, and lacks an effective temperature calibration and warning mechanism. The real-time temperature of the target user is obtained through a distributed temperature sensor, and the data is transmitted to the data processing center through a data transmission module. The central management platform activates the predetermined data calibration mechanism to calibrate the temperature data to obtain the effective real-time temperature. The information display device visualizes the calibrated temperature data, realizing continuous monitoring, remote transmission and real-time visualization of temperature, and improving the efficiency and accuracy of temperature monitoring.

[0064] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0066] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An intelligent body temperature central monitoring and warning system, characterized in that: include: An intelligent wearable body temperature monitoring device, the intelligent wearable body temperature monitoring device is used to extract a first body temperature sensor from the distributed body temperature sensors, and obtain a first real-time body temperature of a target user through the first body temperature sensor, wherein the first real-time body temperature corresponds to a first body part of the target user; A data transmission module, the data transmission module is used to call a predetermined transmission strategy and transmit the first real-time body temperature to a data processing center according to the predetermined transmission strategy; A central management platform, the central management platform is used to activate a predetermined data calibration mechanism stored in the memory of the data processing center, and perform calibration processing on the first real-time body temperature according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature; An information display device, wherein the information display device is used to visually display the first effective real-time body temperature.

2. The system according to claim 1, characterized in that The intelligent wearable body temperature monitoring device also includes: A real-time body temperature time series acquisition module, the real-time body temperature time series acquisition module is used to acquire a first real-time body temperature time series of the first human body part through the first body temperature sensor; A regression fitting processing module, the regression fitting processing module is used to perform polynomial regression fitting processing on a first body temperature scatter plot drawn according to the first real-time body temperature time series to obtain a first fitting formula; A real-time body temperature verification module is used to analyze the first fitting formula to obtain a first real-time predicted body temperature, and verify the first real-time body temperature through the first real-time predicted body temperature.

3. The system according to claim 2, characterized in that The intelligent wearable body temperature monitoring device also includes: A circuit wake-up module, the circuit wake-up module is used to activate a timed wake-up circuit, wherein the timed wake-up circuit has an identifier of a predetermined time interval; The body temperature monitoring module is used to wake up the first body temperature sensor to perform dynamic body temperature monitoring on the first human body part based on the predetermined time interval to obtain the first real-time body temperature time series.

4. The system according to claim 1, characterized in that The data transmission module performs data transmission via Bluetooth, WiFi or wireless radio frequency technology in a specific frequency band.

5. The system according to claim 1, wherein: The central management platform also includes: An individual characteristic information acquisition module, the individual characteristic information acquisition module is used to acquire target multi-dimensional individual characteristic information of the target user; An environment characteristic information acquisition module, the environment characteristic information acquisition module is used to acquire target multi-dimensional environment characteristic information of the target user; A real-time body temperature calibration module, the real-time body temperature calibration module is used to calibrate the first real-time body temperature based on the predetermined data calibration mechanism and in combination with the target multi-dimensional individual characteristic information and the target multi-dimensional environmental characteristic information to obtain the first effective real-time body temperature; The target multidimensional individual characteristic information includes characteristic information of the target individual basic dimension, the target individual physiological state dimension and the target individual psychological state dimension, wherein the target individual basic dimension at least includes individual age and individual gender, the target individual physiological state dimension at least includes physical activity, disease status, endocrine status, diet and drug status and sleep status, and the target individual psychological state dimension at least includes emotional fluctuations and biological rhythms; The target multi-dimensional environmental characteristic information includes external temperature, external humidity and external air pressure.

6. The system according to claim 5, characterized in that The central management platform also includes: A benchmark extraction module, the benchmark extraction module is used to sequentially extract a predetermined individual benchmark and a predetermined environmental benchmark in the predetermined data calibration mechanism; A plan reading module, the plan reading module is used to read the feature vectorization plan; A first vectorization processing module, the first vectorization processing module is used to sequentially perform vectorization processing on the predetermined individual benchmark and the target multi-dimensional individual feature information according to the feature vectorization plan to obtain an individual benchmark vector and a target individual vector respectively; A second vectorization processing module, the second vectorization processing module is used to sequentially vectorize the predetermined environmental reference and the target multi-dimensional environmental feature information according to the feature vectorization plan to obtain an environmental reference vector and a target environmental vector respectively; A real-time body temperature weighted calibration module, wherein the real-time body temperature weighted calibration module is used to perform weighted calibration on the first real-time body temperature using the individual similarity coefficient between the individual reference vector and the target individual vector and the environmental similarity coefficient between the environmental reference vector and the target environmental vector as weights to obtain the first effective real-time body temperature.

7. The system according to claim 6, characterized in that The central management platform also includes: A first similarity calculation module, the first similarity calculation module is used to calculate the similarity between the individual reference vector and the target individual vector by using the cosine similarity principle to obtain a first similarity; A second similarity calculation module, the second similarity calculation module is used to count the number of vector consistency between the individual reference vector and the target individual vector, and obtain a ratio of the vector consistency number to the total number of vectors, which is recorded as a second similarity; The individual similarity coefficient acquisition module is used to obtain the average of the first similarity and the second similarity, which is recorded as the individual similarity coefficient.

8. The system of claim 1, wherein: It also includes an intelligent warning module, which specifically includes: A body temperature threshold determination module, the body temperature threshold determination module is used to determine whether the first effective real-time body temperature meets a predetermined body temperature threshold; A warning signal issuing module, wherein the warning signal issuing module is used to issue a warning signal if the condition is not satisfied; An abnormal warning module, the abnormal warning module is used to call a predetermined warning mechanism based on the warning signal to warn the target user of abnormal body temperature; The predetermined warning mechanism at least reminds the staff by sound, flashing and pop-up window.

9. The system according to claim 8, characterized in that The intelligent warning module is also used to obtain the real-time positioning information of the target user through a positioning sensor, and add the real-time positioning information to the abnormal body temperature warning.

Images