An intelligent body temperature central monitoring and warning system

Abstract

The application discloses an intelligent body temperature central monitoring and warning system and relates to the technical field of medical instruments.The system comprises the following steps: extracting a first body temperature sensor from distributed body temperature sensors and obtaining a first real-time body temperature of a target user through the first body temperature sensor; calling a predetermined transmission strategy and transmitting the first real-time body temperature to a data processing center according to the predetermined transmission strategy; activating a predetermined data calibration mechanism of the memory in the data processing center and calibrating 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 application solves the technical problems that the prior art cannot realize real-time, continuous and remote monitoring in body temperature monitoring and lacks effective body temperature calibration and warning mechanisms, realizes continuous monitoring, remote transmission and real-time visualization of body temperature, and improves the technical effects of the efficiency and accuracy of body temperature monitoring.

Description

TECHNICAL FIELD

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

[0002] Currently, body temperature monitoring technology is facing challenges in real-time, continuity and remote monitoring. Traditional body temperature monitoring methods such as mercury thermometer and electronic thermometer can only perform intermittent measurement and cannot realize real-time and continuous tracking of the body temperature of a target user. This method often has the problem of long measurement interval and cannot timely discover abnormal changes in body temperature. The body temperature monitoring means in the prior art usually lack effective body temperature data calibration and automatic warning mechanism, which makes it impossible to timely issue a warning when an abnormal body temperature occurs, thereby affecting the health care of the target user. SUMMARY

[0003] The present application provides an intelligent body temperature central monitoring and warning system, which is used to solve the technical problems that the prior art cannot realize 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, which comprises:

[0006] The intelligent wearable body temperature monitoring device is used to extract a first body temperature sensor in a distributed body temperature sensor and acquire 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 human body part of the target user; 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; the central management platform is used to activate a predetermined data calibration mechanism of the memory in 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; and the information display device is used to visually display the first effective real-time body temperature.

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

[0008] The application extracts a first body temperature sensor in a distributed body temperature sensor, and obtains a first real-time body temperature of a target user through the first body temperature sensor; a predetermined transmission strategy is called, and the first real-time body temperature is transmitted to a data processing center according to the predetermined transmission strategy; a predetermined data calibration mechanism of the memory in the data processing center is activated, and the first real-time body temperature is calibrated according to the predetermined data calibration mechanism to obtain a first effective real-time body temperature; and the first effective real-time body temperature is visually displayed. The application solves the technical problems that the prior art cannot realize real-time, continuous and remote monitoring in body temperature monitoring, and lacks effective body temperature calibration and warning mechanisms. The real-time body temperature of the target user is obtained through the distributed body temperature sensor, and the data is transmitted to the data processing center through the data transmission module. The central management platform activates the predetermined data calibration mechanism to calibrate the body temperature data, obtains the effective real-time body temperature, and the information display device visually displays the calibrated body temperature data, realizes continuous monitoring, remote transmission and real-time visualization of the body temperature, and improves the efficiency and accuracy of the body temperature monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0010] Figure 1 A structure schematic diagram of an intelligent body temperature central monitoring and warning system is provided for the embodiment of the application.

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

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

[0013] The application provides an intelligent body temperature central monitoring and warning system, which solves the technical problems that the prior art cannot realize real-time, continuous and remote monitoring in body temperature monitoring, and lacks effective body temperature calibration and warning mechanisms. The real-time body temperature of the target user is obtained through the distributed body temperature sensor, and the data is transmitted to the data processing center through the data transmission module. The central management platform activates the predetermined data calibration mechanism to calibrate the body temperature data, obtains the effective real-time body temperature, and the information display device visually displays the calibrated body temperature data, realizes continuous monitoring, remote transmission and real-time visualization of the body temperature, and improves the efficiency and accuracy of the body temperature monitoring.

[0014] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0015] It should be noted that any variants of the terms "comprising" and "having" are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to the process, method, product or device.

[0016] Embodiments, such as Figure 1 As shown in the embodiments of the present application, an intelligent body temperature central monitoring and warning system is provided, which comprises:

[0017] The intelligent wearable body temperature monitoring device 11 is configured to extract a first body temperature sensor from the distributed body temperature sensors and acquire 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.

[0018] In the embodiments of the present application, the intelligent wearable body temperature monitoring device monitors the body temperature of the target user in real time through a plurality of distributed body temperature sensors. The plurality of distributed body temperature sensors are distributed at different parts of the monitoring target, such as under the armpit, in front of the chest, etc. The target user is monitored for body temperature through a first body temperature sensor in the distributed body temperature sensors to obtain a 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 configured to monitor the body temperature of different parts of the target user.

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

[0020] Further, the system provided by the embodiments of the present application further comprises:

[0021] a real-time body temperature time sequence acquisition module for acquiring a first real-time body temperature time sequence of the first human body part through the first body temperature sensor;

[0022] In the embodiments of the present application, the real-time body temperature time sequence acquisition module continuously monitors the body temperature changes of the target user through the first body temperature sensor. The real-time body temperature time sequence acquisition module is responsible for acquiring the first real-time body temperature time sequence of the target user within a period of time. The first real-time body temperature time sequence refers to a continuous body temperature data sequence, which records the changes of the body temperature of the first human 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 deeper analysis of the first real-time body temperature time sequence data. The regression fitting processing module first draws a first body temperature scatter plot based on the first real-time body temperature time sequence, and each point in the scatter plot represents the body temperature data at a certain time. Through these scatter plots, the trend of body temperature change over time can be directly observed. Then, the regression fitting processing module uses a polynomial regression algorithm to fit the data in the first body temperature scatter plot, generating 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 time by analyzing the first fitting formula generated by regression fitting. Then, the predicted body temperature is compared with the actually collected first real-time body temperature. Specifically, after collecting the body temperature data, the expected body temperature of the target user at the same time is predicted using the fitting curve generated by regression fitting, i.e., the first fitting formula, to obtain the first real-time predicted body temperature. If there is a significant difference between the actually measured body temperature and the predicted body temperature, the verification mechanism is triggered, and re-collection is performed. 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 the measurement is abnormal, and the body temperature data is automatically re-collected and re-verified to ensure the accuracy of the data.

[0025] Further, the system provided by the embodiments of the present application further comprises:

[0026] The circuit wake-up module is configured to activate a timing wake-up circuit, wherein the timing wake-up circuit is provided with an identification of a predetermined time interval; and the body temperature monitoring module is configured 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 sequence.

[0027] In the embodiments 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 the predetermined time interval, thereby obtaining an accurate real-time body temperature sequence.

[0028] Specifically, the function of the circuit wake-up module is to activate the timing wake-up circuit, which is provided with an identification of a predetermined time interval for automatically waking up the body temperature sensor within a specific time interval. This time interval is pre-set according to the requirements, for example, the body temperature sensor is automatically activated every certain time (such as 30 seconds, 1 minute or 2 minutes). In this way, the device can perform body temperature measurement at regular intervals without manual intervention. The design of the timing wake-up circuit not only ensures the continuous collection of body temperature data, but also effectively manages the consumption of the battery, because it only activates the sensor when necessary, avoiding energy waste caused by continuous operation.

[0029] When the timing wake-up circuit is triggered, the body temperature monitoring module immediately performs a wake-up operation to activate the first body temperature sensor. At this time, the body temperature sensor is woken up and starts to measure the body temperature of the first human 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 to collect user body temperature data in real time. Each collection of body temperature data forms a continuous body temperature data sequence, i.e. the first real-time body temperature sequence.

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

[0031] Further, in the system provided by the embodiments of the present application, the data transmission module transmits data through Bluetooth, WiFi or specific frequency band wireless radio frequency technology.

[0032] In the embodiments of the present application, the data transmission module calls a predetermined transmission strategy, which is a pre-set rule to determine how to process and transmit body temperature data, including the mode, frequency and security measures of data transmission. Specifically, the predetermined transmission strategy provides that the body temperature data is transmitted in an encrypted manner to ensure that the data cannot be stolen or tampered with by unauthorized third parties during transmission. The implementation of encrypted transmission usually adopts a symmetric encryption algorithm such as AES (Advanced Encryption Standard), which ensures the security of the data and has efficient and fast processing capacity, 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 according to the set predetermined transmission strategy through the set communication mode. In the present application, the data transmission module can transmit data through various wireless communication modes, including Bluetooth, WiFi or other specific frequency band wireless radio frequency technology.

[0034] The central management platform 13 is used to activate the 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 the first effective real-time body temperature.

[0035] Further, as shown in Figure 2 The central management platform 13 further comprises:

[0036] An 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 is used to acquire target multi-dimensional environment characteristic information of the target user; a 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 environment characteristic information to obtain the first effective real-time body temperature; wherein the target multi-dimensional individual characteristic information includes characteristic information of target individual basic dimension, target individual physiological state dimension and 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 state, endocrine condition, diet and drug condition and sleep state, and the target individual psychological state dimension at least includes emotional fluctuation and biological rhythm; wherein the target multi-dimensional environment characteristic information includes external temperature, external humidity and external air pressure.

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

[0038] Specifically, first, the target multi-dimensional individual feature information of the target user is acquired by the individual feature information acquisition module. The target multi-dimensional individual feature information includes feature information of a target individual basic dimension, a target individual physiological state dimension and a target individual psychological state dimension. 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 state, endocrine condition, diet and drug condition and sleep state. The target individual psychological state dimension at least includes emotional fluctuation and biological rhythm. To obtain the target individual basic dimension information, the health record of the target user is extracted to obtain the age and gender of the target user. The target individual physiological state dimension, such as physical activity, disease state, endocrine condition, etc., is continuously tracked by the health monitoring device 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 dimension, such as emotional fluctuation and biological rhythm, is detected by the target user's self-report or a smart device, such as a pressure sensing device.

[0039] Next, the target multi-dimensional environmental feature information of the target user is acquired by the environmental feature information acquisition module. The target multi-dimensional environmental feature information includes external temperature, external humidity and external air pressure. These information is collected in real time by a temperature and humidity meter, an environmental humidity sensor and a meteorological sensor (such as a barometer).

[0040] Once the target multi-dimensional individual feature information and the target multi-dimensional environmental feature information are acquired, 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 feature information and the target multi-dimensional environmental feature information to obtain the first effective real-time body temperature.

[0041] Further, the system provided by the application embodiment further comprises:

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

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

[0044] Next, the plan reading module reads a feature vectorization plan to provide processing rules for subsequent vectorization processing. The plan file usually adopts 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 quantize these features (for example, dividing age into different intervals, representing gender in binary, representing physical activity intensity in classified numerical values, etc.), and clearly specifies the corresponding numerical values of 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 characteristic information of the predetermined individual reference and the target user according to the characteristic vectorization plan. First, the basic information of the individual such as age and gender is converted into a numerical vector. The age can be directly input as a numerical value, and the gender is represented in binary form (e.g., male = 1, female = 0). Second, for physiological state information such as physical activity, disease state, and endocrine condition, similar methods are used to convert these data into numerical values. For example, physical activity can be represented as 0, 1, and 2 for "low / medium / high", and the physiological state information is also numerically processed in this way. In this way, through the standardization process, the individual reference vector and the individual characteristic vector of the target user are generated, forming numerical data that can be used for subsequent calculations.

[0046] Subsequently, the second vectorization processing module performs similar vectorization processing on the environment reference and the target environment characteristic information. Through the collected environmental data such as temperature, humidity, and air pressure, these information is converted into numerical form according to the rules of the characteristic vectorization plan. For example, the actual values of the environmental temperature and humidity can be directly taken, while the air pressure can be converted into standard atmospheric pressure units for representation, generating the environment reference vector and the target environment characteristic vector.

[0047] The real-time body temperature weighted calibration module uses the similarity coefficients of the individual reference vector and the target individual vector, and the environment reference vector and the target environment vector as weights to perform weighted calibration on the first real-time body temperature. The similarity coefficient of the individual reference vector and the target individual vector is the individual similarity coefficient. To obtain the individual similarity coefficient, first, the cosine similarity method is used to calculate the similarity between the individual reference vector and the target individual vector. Then, the number of consistent vectors is calculated, i.e., the number of identical items in each characteristic dimension between the individual reference vector and the target individual vector is compared, and the ratio of the consistent number to the total dimension number is calculated to obtain the second similarity. Finally, the average of the first similarity and the second similarity is taken as the individual similarity coefficient. The environmental similarity coefficient of the environment reference vector and the target environment vector is calculated by 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 used to multiply the first effective real-time body temperature respectively to obtain weighted values. Then, these weighted values are added together, and finally the average is taken to obtain the final first effective real-time body temperature.

[0049] Further, the system provided by the application embodiment further comprises:

[0050] The first similarity calculation module is configured to calculate the similarity between the individual reference vector and the target individual vector by using the cosine similarity principle, and obtain a first similarity.

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

[0052] Next, the second similarity calculation module counts the number of consistent vectors between the individual reference vector and the target individual vector. The number of consistent vectors refers to whether the values of the two vectors in each dimension are consistent, that is, whether the same values are taken 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 number of consistent items is obtained, and then the ratio of the number of consistent items to the total number of dimensions 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 as the individual similarity coefficient. Specifically, by summing the first similarity and the second similarity, and then dividing by two, the individual similarity coefficient is obtained.

[0054] The information display device 14 is configured 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 body temperature change trend and current state of the target user. Through intuitive charts, body temperature change curves, lists and other forms, the body temperature fluctuation of the target user is displayed, and whether the body temperature exceeds the normal range is monitored in real time. In addition, the interface also displays other related information, such as the name, age and other basic information of the target user.

[0056] Further, the system provided by the embodiment of the present application further comprises an intelligent warning module, and the intelligent warning module specifically comprises:

[0057] a body temperature threshold judgment module, configured to judge whether the first effective real-time body temperature meets a predetermined body temperature threshold; an alarm signal sending module, configured to send an alarm signal if the first effective real-time body temperature does not meet the predetermined body temperature threshold; and an abnormality alarm module, configured to call a predetermined alarm mechanism based on the alarm signal to perform body temperature abnormality alarm for the target user, wherein the predetermined alarm mechanism at least reminds a staff member in a sound, flashing light, and pop-up window manner.

[0058] In the embodiments of the present application, the body temperature threshold judgment module is configured to judge whether the first effective real-time body temperature meets a predetermined body temperature threshold. The predetermined body temperature threshold includes a high temperature threshold and a low temperature threshold, which are respectively used to judge whether the body temperature is too high or too low. If the first effective real-time body temperature is out of the normal range, the body temperature is considered to be abnormal. The threshold judgment is based on the clinical medical standard setting, for example, the normal body temperature range of an adult is 36.3℃ to 37.2℃, and if the body temperature is lower than 36.3℃ or higher than 37.2℃, it may indicate that the body temperature is abnormal.

[0059] If the first effective real-time body temperature is out of the predetermined body temperature threshold, the alarm signal sending module immediately sends an alarm signal to the abnormality alarm module. After receiving the alarm signal, the abnormality alarm module further calls a predetermined alarm mechanism to send a specific body temperature abnormality alarm. The predetermined alarm mechanism includes a sound alarm, red light flashing, pop-up window reminding, and the like, to ensure that the staff member can timely notice the body temperature abnormality of the target user in a busy work.

[0060] Further, the system provided by the embodiments of the present application further includes that the intelligent alarm module is further configured to acquire real-time positioning information of the target user through a positioning sensor and add the real-time positioning information to the body temperature abnormality alarm.

[0061] In the embodiments of the present application, the intelligent alarm module acquires real-time positioning information of the target user through a positioning sensor and adds the real-time positioning information to the body temperature abnormality alarm. Specifically, the positioning sensor is used to track the position of the target user in real time, which is usually achieved through GPS, Wi-Fi, or Bluetooth positioning technology. The positioning information includes the specific position where the user is currently located. When the system detects the body temperature abnormality of the target user, the real-time positioning information of the target user is displayed or sent to the staff member together with the body temperature abnormality alarm, thereby helping them quickly locate the position of the target user and take corresponding measures.

[0062] In the embodiments of the present application, the above-mentioned embodiments of the present application at least have the following technical effects:

[0063] The application extracts the first body temperature sensor in the distributed body temperature sensor, and obtains the first real-time body temperature of the target user through the first body temperature sensor; the predetermined transmission strategy is called, and the first real-time body temperature is transmitted to the data processing center according to the predetermined transmission strategy; the predetermined data calibration mechanism of the memory in the data processing center is activated, and the first real-time body temperature is calibrated according to the predetermined data calibration mechanism to obtain the first effective real-time body temperature; the first effective real-time body temperature is visually displayed. The application solves the technical problems that the existing technology cannot realize real-time, continuous and remote monitoring in body temperature monitoring, and lacks effective body temperature calibration and warning mechanism. The real-time body temperature of the target user is obtained through the distributed body temperature sensor, and the data is transmitted to the data processing center through the data transmission module. The central management platform activates the predetermined data calibration mechanism to calibrate the body temperature data, obtains the effective real-time body temperature, and the information display device visually displays the calibrated body temperature data, realizes continuous monitoring, remote transmission and real-time visualization of the body temperature, and improves the efficiency and accuracy of the body temperature monitoring.

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

[0065] The above only describes the preferred embodiments of the application, and does not limit the application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

[0066] The present application and the drawings are only exemplary description of the application, and are considered to cover any and all modifications, changes, combinations or equivalents within the scope of the application. Obviously, those skilled in the art can make various modifications and changes to the application without departing from the scope of the application. Thus, if these modifications and changes of the application belong to the scope of the application and its equivalents, the application intends to include these modifications and changes.

Claims

1. An intelligent body temperature central monitoring and alerting system, characterized in that, The application relates to a smart wearable body temperature monitoring device, a data transmission module, a central management platform, an information display device and the like. The smart wearable body temperature monitoring device is used for extracting a first body temperature sensor in a distributed body temperature sensor and acquiring 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 human body part of the target user. The data transmission module is used for calling a predetermined transmission strategy and transmitting the first real-time body temperature to a data processing center according to the predetermined transmission strategy. The central management platform is used for activating a predetermined data calibration mechanism of an internal 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. The information display device is used for visually displaying the first effective real-time body temperature. The central management platform further comprises an individual characteristic information acquisition module, an environment characteristic information acquisition module and a real-time body temperature calibration module. The individual characteristic information acquisition module is used for acquiring target multi-dimensional individual characteristic information of the target user. The environment characteristic information acquisition module is used for acquiring target multi-dimensional environment characteristic information of the target user. The real-time body temperature calibration module is used for calibrating 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 environment characteristic information to obtain the first effective real-time body temperature. The target multi-dimensional individual characteristic information comprises 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 at least comprises individual age and individual gender, the target individual physiological state dimension at least comprises physical activity, disease state, endocrine condition, diet and drug condition and sleep state, and the target individual psychological state dimension at least comprises emotional fluctuation and biological rhythm. The target multi-dimensional environment characteristic information comprises external temperature, external humidity and external air pressure. The central management platform further comprises a benchmark extraction module and a preplan reading module. The benchmark extraction module is used for sequentially extracting a predetermined individual benchmark and a predetermined environment benchmark in the predetermined data calibration mechanism. The preplan reading module is used for reading a characteristic vectorization preplan. A first vectorization processing module is used for sequentially performing vectorization processing on the predetermined individual benchmark and the target multi-dimensional individual characteristic information according to the characteristic vectorization preplan to respectively obtain an individual benchmark vector and a target individual vector. A second vectorization processing module is used for sequentially performing vectorization processing on the predetermined environment benchmark and the target multi-dimensional environment characteristic information according to the characteristic vectorization preplan to respectively obtain an environment benchmark vector and a target environment vector. A real-time body temperature weighted calibration module is configured to perform weighted calibration on the first real-time body temperature with the individual similarity coefficient of the individual reference vector and the target individual vector and the environment similarity coefficient of the environment reference vector and the target environment vector, to obtain the first effective real-time body temperature. The central management platform further comprises: A first similarity calculation module is configured to perform similarity calculation on 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 is configured to count the number of consistent vectors of the individual reference vector and the target individual vector, and obtain the ratio of the number of consistent vectors to the total number of vectors, denoted as a second similarity. An individual similarity coefficient acquisition module is configured to take the mean of the first similarity and the second similarity, denoted as the individual similarity coefficient.

2. The system of claim 1, wherein, The intelligent wearable body temperature monitoring device further comprises: A real-time body temperature time sequence acquisition module is configured to acquire a first real-time body temperature time sequence of the first human body part through the first body temperature sensor. A regression fitting processing module is configured to perform polynomial regression fitting processing on a first body temperature scatter plot drawn according to the first real-time body temperature time sequence, to obtain a first fitting formula. A real-time body temperature verification module is configured to analyze the first real-time predicted body temperature obtained from the first fitting formula, and verify the first real-time body temperature through the first real-time predicted body temperature.

3. The system of claim 2, wherein, The intelligent wearable body temperature monitoring device further comprises: A circuit wake-up module is configured to activate a timing wake-up circuit, wherein the timing wake-up circuit has an identification of a predetermined time interval. A body temperature monitoring module is configured 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 sequence.

4. The system of claim 1, wherein, The data transmission module transmits data through Bluetooth, WiFi, or wireless radio frequency technology of a specific frequency band.

5. The system of claim 1, wherein, The intelligent warning module specifically comprises: A body temperature threshold judgment module is configured to judge whether the first effective real-time body temperature meets a predetermined body temperature threshold. A warning signal sending module is configured to send a warning signal if the condition is not met. An abnormality warning module is configured to call a predetermined warning mechanism based on the warning signal to perform body temperature abnormality warning for the target user. The predetermined warning mechanism at least reminds the staff in the form of sound, flashing, and pop-up window.

6. The system of claim 5, wherein, The intelligent warning module is further configured to acquire real-time positioning information of the target user through a positioning sensor, and add the real-time positioning information to the body temperature abnormality warning.

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