CN110897645A - Low-power-consumption human body state detection system realized based on NB-IoT - Google Patents
Low-power-consumption human body state detection system realized based on NB-IoT Download PDFInfo
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Abstract
The invention discloses a low-power-consumption human body state detection system based on NB-IoT (NB-IoT), which comprises a shoe part detection device and a cloud server, wherein the shoe part detection device is arranged on a shoe and comprises an MCU (microprogrammed control Unit) main control module, a sensor and an NB-IoT module, and the sensor and the NB-IoT module are respectively connected with the MCU main control module; the sensor is used for monitoring a human body and generating human body monitoring data; the MCU main control module is used for reading human body monitoring data generated by the sensor and outputting the human body monitoring data to the NB-IoT module; the NB-IoT module is used for forwarding the human body monitoring data to a cloud server through an NB-IoT network; the cloud server is used for obtaining human body state information according to the human body monitoring data operation. The low-power-consumption human body state detection system based on the NB-IoT can reduce the power consumption of the system, reduce the hardware configuration cost and improve the accuracy of the detection result.
Description
Technical Field
The invention relates to the technical field of human body detection, in particular to a low-power-consumption human body state detection system based on NB-IoT.
Background
With the improvement of living standard, people pay more and more attention to healthy life, and running is the cheapest, common and accepted exercise mode by the public. But few have comprehensive knowledge of the running posture.
The products for detecting running postures on the market at present often have the problems of large calculation power consumption, insufficient precision caused by the fact that a calculation method is limited due to the influence of hardware conditions, high MCU and storage configuration, high cost and the like. In addition, the transmission of the human body state information data to the user is limited by the close range and speed.
Disclosure of Invention
The invention aims to provide a low-power-consumption human body state detection system which is low in power consumption, low in hardware configuration cost and accurate in detection result and is realized based on NB-IoT.
In order to solve the technical problems, the invention adopts the following technical scheme:
a low-power consumption human body state detection system based on NB-IoT comprises a shoe part detection device and a cloud server, wherein the shoe part detection device is arranged on a shoe and comprises an MCU main control module, a sensor and an NB-IoT module, and the sensor and the NB-IoT module are respectively connected with the MCU main control module; the sensor is used for monitoring a human body and generating human body monitoring data; the MCU main control module is used for reading human body monitoring data generated by the sensor and outputting the human body monitoring data to the NB-IoT module; the NB-IoT module is used for forwarding the human body monitoring data to a cloud server through an NB-IoT network; the cloud server is used for obtaining human body state information according to the human body monitoring data operation.
Preferably, the low-power-consumption human body state detection system based on the NB-IoT comprises a terminal device, wherein the terminal device is in communication connection with a cloud server through an NB-IoT network, and is used for acquiring human body state information from the cloud server and displaying the human body state information.
Preferably, the MCU main control module reads the human body monitoring data generated by the sensor through the SPI or IIC interface.
Preferably, the shoe part detection device further comprises a SIM card module connected with the NB-IoT module, and is used for identifying a SIM card of a telecom operator to perform telephone or short message communication.
Preferably, the cloud server is further configured to send data information to the shoe part detection device; the NB-IoT module is also used for receiving the data information and forwarding the data information to the MCU main control module; the SIM card module is also used for receiving a telephone dialed by a telecom operator and a short message sent by the telecom operator; and the MCU master control module is also used for controlling the sensor to be dormant and restarted according to the data information, the telephone dialed by a telecom operator and the sent short message.
Preferably, the shoe part detection device further comprises a storage module connected with the MCU master control module, and the storage module is used for storing human body monitoring data generated by the sensor;
the MCU main control module is used for transmitting the human body monitoring data generated by the sensor to the cloud server through the NB-IoT module in real time;
or the MCU master control module is used for pre-storing the human body monitoring data generated by the sensor into the storage module and transmitting the stored human body monitoring data to the cloud server through the NB-IoT module according to a preset transmission cycle or a preset transmission condition.
Preferably, the MCU main control module is configured to store the human body monitoring data in the storage module when detecting that the NB-IoT module data transmission is abnormal, and continue to transmit the human body monitoring data to the cloud server through the NB-IoT module after the data transmission abnormality is eliminated.
Preferably, the sensor comprises an acceleration sensor, and the acceleration sensor is used for acquiring acceleration information in the process of human body movement; the MCU master control module is used for reading the acceleration information and outputting the acceleration information to the NB-IoT module; the NB-IoT module is used for forwarding the acceleration information to a cloud server through an NB-IoT network; the cloud server is used for calculating and acquiring human motion state information according to the acceleration information, wherein the human motion state information comprises slow walking, fast walking, running, sedentary, step frequency and speed.
Preferably, the sensor comprises a GPS sensor for acquiring geographical position coordinate data; the MCU master control module is used for reading the geographic position coordinate data and outputting the geographic position coordinate data to the NB-IoT module; the NB-IoT module is used for forwarding the geographic position coordinate data cloud server through an NB-IoT network; and the cloud server acquires the position information, the direction information, the altitude information and the weather information of the person according to the geographic position coordinate data through data query, and calculates the track information of the movement of the person.
Preferably, the sensor comprises a pressure sensor, and the pressure sensor is used for collecting pressure value data of the human body to the shoe; the MCU main control module is used for reading the pressure value data and outputting the pressure value data to the NB-IoT module; the NB-IoT module is used for forwarding the pressure value data cloud server through an NB-IoT network; and the cloud server calculates the weight and the body fat rate of the person according to the data.
Preferably, the sensors comprise heart rate sensors for acquiring heart rate, respiration rate, blood pressure and blood oxygen level data of the human body; the MCU main control module is used for reading the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data and outputting the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data to the NB-IoT module; the NB-IoT module is used for forwarding the heart rate, respiration rate, blood pressure and blood oxygen level data to a cloud server through an NB-IoT network; and the cloud server judges whether the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data are in a normal range or not through data query and comparison.
The invention has the beneficial technical effects that: the low-power-consumption human body state detection system based on the NB-IoT realizes the application of the NB-IoT technology in the aspect of human body state detection, and effectively reduces the energy consumption of the human body state detection system based on the low-power-consumption design of the NB-IOT technology; the shoe part detection device is in communication connection with the cloud server through an NB-IOT network, and the processing and operation of sensor data are transferred to the server for processing, so that the calculation power consumption of the MCU master control module is reduced, the hardware configuration of the MCU master control module can be reduced, and the hardware cost is further reduced; in addition, the processing and the operation of the sensor data are carried out on the server, and the calculation method is not limited by the MCU master control module of the shoe part detection device, so that the accuracy of the detection result can be improved.
Drawings
Fig. 1 is a schematic structural diagram of a low-power human body state detection system implemented based on NB-IoT of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly understood by those skilled in the art, the present invention is further described with reference to the accompanying drawings and examples.
As shown in fig. 1, in an embodiment of the present invention, a low-power human body status detection system implemented based on NB-IoT includes a shoe portion detection device 10 and a cloud server 20, the shoe portion detection device 10 is disposed on a shoe, and the shoe portion detection device 10 can be combined with a vamp, a shoe sole, a heel, a sole, a shoe buckle, and an insole by means of pasting, sewing, and embedding.
The shoe part detecting device 10 comprises an MCU main control module 11, and a sensor 12 and an NB-IoT module 13 which are respectively connected with the MCU main control module 11. The sensor 12 is used for monitoring a human body and generating human body monitoring data; the MCU main control module 11 is used for reading human body monitoring data generated by the sensor 12 and outputting the human body monitoring data to the NB-IoT module 13; the NB-IoT module 13 is used for forwarding the human body monitoring data to the cloud server 20 through the NB-IoT network; the cloud server 20 is configured to calculate and acquire human body state information according to the human body monitoring data.
The shoe part detection device 10 further comprises a power supply 16 for supplying power, and the power supply 16 is connected with the MCU main control module 11 through a power management module 17. The power supply 16 may be a common battery, or a rechargeable battery of nickel-cadmium, nickel-hydrogen, or lithium ion.
The NarrowBand Internet of things (NB-IoT) is constructed in a cellular network, consumes only a bandwidth of about 180kHz, and can be directly deployed in a GSM network, a UMTS network, or an LTE network to reduce deployment cost, achieve smooth upgrade, and support cellular data connection of low-power devices in a wide area network, which is also called a low-power wide area network (LPWAN). The invention realizes the application of the NB-IoT technology in the aspect of human body state detection, and effectively reduces the energy consumption of a human body state detection system based on the low-power-consumption design of the NB-IOT technology; the shoe part detection device 10 is in communication connection with the cloud server 20 through an NB-IOT network, and the processing and operation of sensor data are transferred to the server 20 for processing, so that the calculation power consumption of the MCU main control module 11 is reduced, the hardware configuration of the MCU main control module 11 can be reduced, and the hardware cost is further reduced; in addition, the processing and operation of the sensor data are performed on the server 20, and the calculation method is not limited by the MCU main control module 11 of the shoe portion detecting device 10, so that the accuracy of the detection result can be improved.
Preferably, the low-power human body state detection system implemented based on NB-IoT includes a terminal device 30, and the terminal device 30 is in communication connection with the cloud server 20 through an NB-IoT network, and is configured to obtain the human body state information from the cloud server 20 and display the human body state information. The terminal device 30 may be a mobile device, a home appliance, or other device having an NB-IoT module. The terminal device 30 of the invention is provided with an NB-IoT module, can be in communication connection with the cloud server 20 through an NB-IoT network, acquires the human body state information from the cloud server 20 and displays the human body state information to a user, and the transmission of the human body state information data between the terminal device 30 and the cloud server 20 is not limited by distance and speed.
Preferably, the terminal device 30 may also be internally disposed in the shoe portion detecting device 10, and includes one or more display devices connected to the NB-IoT module, where the display devices include a display, a lamp, and a vibrator, and the display devices preset a corresponding relationship between a human body state and a display state.
Preferably, the MCU main control module 11 is connected to the sensor 12 through the SPI or IIC interface, and reads the human monitoring data generated by the sensor 12. The shoe part detecting device 10 further includes a SIM card module 14 connected to the NB-IoT module 13, where the SIM card module 14 is used to identify a SIM card of a telecommunications carrier, so that the shoe part detecting device 10 can use a service of the telecommunications carrier, such as telephone or short message communication, to support 5G, 4G, 3G, or 2G communication of the carrier.
Preferably, the shoe portion detecting device 10 further comprises a storage module 15 connected to the MCU main control module 11, wherein the storage module 15 is used for storing the human body monitoring data generated by the sensor 12. The shoe portion detecting device 10 performs data transmission with the cloud server 20 by any one of the following control methods:
the MCU main control module 11 transmits the human body monitoring data generated by the sensor 12 to the cloud server 20 through the NB-IoT module 13 in real time.
Second, the MCU main control module 11 sets a transmission period or transmission condition in advance, or sets a transmission period or transmission condition according to an instruction sent to the NB-IoT module 13 by the cloud server 20, for example, data is transmitted once every 30s or data is stored more than 10M. The MCU main control module 11 stores the data of the sensor 12 in the storage module 15, and transmits the stored data to the cloud server 20 through the NB-IoT module 13 when a transmission cycle or a transmission condition is reached.
Preferably, in the process of data transmission by the NB-IoT module 13, the MCU main control module 11 is further configured to detect whether data transmission by the NB-IoT module 13 is abnormal, where the data transmission abnormality of the NB-IoT module 13 includes NB-IoT module abnormality, communication disconnection between the NB-IoT module and a base station, data transmission failure or error of the NB-IoT module, when the MCU main control module 11 detects the NB-IoT module data transmission abnormality, retrieve whether data with abnormal transmission is stored in the storage module 15, if not, store the data, and after the abnormality is removed, continue to transmit the human body monitoring data to the cloud server 20 through the NB-IoT module 13.
Preferably, the sensor 12 includes an acceleration sensor, and the acceleration sensor is used for acquiring acceleration information in the human motion process and acquiring acceleration data in a three-dimensional direction. The MCU main control module 11 is configured to read the acceleration data, upload the acceleration data to the cloud server 20 through the NB-IoT module 13, generate an acceleration/time waveform in the cloud server 20, smooth the waveform by using smoothing filtering and kalman filtering to reduce errors, and analyze the data after smoothing filtering to calculate the step number; and cutting out a waveform of each period of the data after the Kalman filtering, and analyzing the characteristic value of the waveform and the condition of a threshold value.
Let the acceleration data of the x, y, z axes be ax, ay, az, and the touch point be the highest point amx of ax.
According to the number of steps of one foot of a person normally moving within 1 second, the number of the three steps cannot exceed the number of the three steps, and at least A sampling points are inferred to exist in one step according to the sampling rate of the sensor. The acceleration Ax of the human body is certainly larger than a threshold Ax when the human body moves in one step and accelerates, the acceleration of the human body is certainly smaller than a threshold Bx when the human body moves in one step and decelerates, when the acceleration is changed from being smaller than Ax to being larger than Ax, then the acceleration is changed from being larger than Ax to being smaller than Bx, the acceleration is just corresponding to the foot lifting and falling actions of the human body, the lowest point which is smaller than Ax before and smaller than Bx after is identified, and the sampling points in the period of time are larger than A sampling points, namely the human body is identified to move in one step.
When the waveform of the data in the period does not satisfy the condition of one step and the data in the three axes is not the initial value, the period C is identified as no longer step motion, and the second period C appears in a certain time from the first period C, the time between the two periods is identified as sedentary.
After one step of human motion is identified, the step frequency D of one step can be calculated according to time. The threshold for the slow and fast walking is defined as D1, the threshold for the walking and running is D2, and the threshold for the z-axis acceleration az of the fast walking and running in one step is Ez. When the step frequency D is less than D1, this step is identified as a slow walk; when the step frequency D is greater than D2, this step is identified as running; when the step frequency is equal to or higher than D1 and equal to or lower than D2, the step is recognized as fast walking when the highest value of az is lower than Ez, and running when the highest value of az is equal to or higher than Ez.
When one step is walking, the value of ay is Fay when ax is the highest value, i.e. the touchdown point, in the period; the y-axis integrated value of all sampling points in the period is Fty, and the maximum value of the y value in the period is Fmy. When (ay < intra-octave motion start y-axis threshold 1) | ((Fty ═ intra-octave axis accumulation value threshold 2) & (Fmy < intra-octave axis maximum value threshold 3)), identifying as intra-octave; identify outer eight when (ay > outer eight motion start y-axis threshold 1) | ((Fty > -outer eight y-axis accumulated value threshold 2) | (Fmy > outer eight y-axis maximum value threshold 3)); other cases are identified as being out of inner and outer eight steps.
When one step is running, when ax is the highest value, namely the bottom touch point, in the period, the bottom touch point and n points adjacent to 0 are taken as sampling points, n ax values are obtained as Gax1, Gax2 and … GaxN, n az values are obtained as Gaz1, Gaz2, … and GazN, and n is determined according to the sampling frequency and az discrete coefficients, and the smaller the discrete coefficient is, the smaller n is; identifying a heel landing when (Gaz1+ Gaz2+ … + GazN)/(Gax1+ Gax2+ … + GaxzN) > is the heel landing threshold; identifying a volar as (Gaz1+ Gaz2+ … + GazN)/(Gax1+ Gax2+ … + GaxzN) < ═ volar threshold; other conditions are identified as midfoot landing.
When one step is running, the minimum value Hay1 of ay and the maximum value Hay2 of ay are obtained in the period, and when Hay1 is equal to the inversion threshold value 1, inversion is identified; eversion is identified when Hay2> -eversion threshold 1 and Hay1> -eversion threshold 2, and other cases identify non-valgus running.
When one step is running, the time difference of the first minimum value laz, laz and amx of az is obtained in the period and is identified as the touchdown time; subtracting the touchdown time from the cycle time to obtain a ground clearance time; the minimum value laz in the touchdown time multiplied by the mass of the user is the touchdown impact force.
When one step is running, the first highest point of az in the period is a ground clearance point Jaz, the ground clearance time is t, the ground clearance S ═ jj ═ d (t/2)) d (t/2) is calculated according to the double integral, and then the value of the ground clearance is determined according to the threshold range.
Preferably, the cloud server 13 further performs data calibration through a learning algorithm, and corrects a threshold, an algorithm condition or an algorithm according to different running posture data of professional runners in different modes, sampling frequency of the sensor, calibrated original data and different positions of the shoe part detection device, namely, the shoe where the sensor is located, so as to achieve more accurate calculation of accurate data.
Preferably, the sensor 12 further includes a GPS sensor, the GPS sensor is configured to acquire geographic position coordinate data and time data, after the geographic position coordinate data and the time data are uploaded to the cloud server 12, the cloud server 12 queries and acquires position information, direction information, altitude information, and weather information of a person according to the geographic position coordinate data and the time data, and may accurately calculate trajectory information of a person's movement by comparing the geographic position coordinate data, the time data, and big data with fault tolerance, and the trajectory length is divided by time to acquire a speed, thereby acquiring a stride frequency.
Preferably, the sensor 12 further includes a pressure sensor, the pressure sensor is used for collecting pressure value data and time data of the human body to the shoes in the vertical direction, a pressure value/time data waveform is generated on the cloud server 20, the weight of the human body can be calculated through the static waveform characteristics, and the body fat percentage can be calculated through the waist circumference and the weight of the user.
Preferably, the sensors 12 further comprise heart rate sensors for acquiring heart rate, respiration rate, blood pressure, and blood oxygen level data of the human body. The MCU main control module 11 reads the heart rate, respiration rate, blood pressure, and blood oxygen level data, and outputs the heart rate, respiration rate, blood pressure, and blood oxygen level data to the NB-IoT module 13. The NB-IoT module 13 is configured to forward the cardiac efficiency, respiration rate, blood pressure, blood oxygen level data to the cloud server 20 through the NB-IoT network. The cloud server 20 judges whether the heart rate, respiration rate, blood pressure and blood oxygen level data are within a normal range through data query and comparison, and outputs a comparison result.
Preferably, the cloud server 20 is further configured to send data information to the shoe part detection device 10, the NB-IoT module 13 is further configured to receive the data information and forward the data information to the MCU main control module 11, and the MCU main control module 11 is further configured to control the sensor 12 to sleep and restart according to the data information. For example, the cloud server 20 sends "01, 01" to the shoe portion detecting device 10, and the MCU main control module 11 controls the acceleration sensor to sleep; the cloud server 20 sends 01, 02 to the shoe part detection device 10, and the MCU master control module 11 controls the acceleration sensor to restart; the cloud server 20 sends '02, 01' to the shoe part detection device 10, and the MCU master control module 11 controls the GPS sensor to sleep; the cloud server 20 sends 02, 02 to the shoe part detection device 10, and the MCU master control module 11 controls the restart of the GPS sensor.
The MCU main control module 11 is also used for controlling the sensor to be dormant and restarted according to the telephone dialed by a telecom operator and the sent short message. The MCU master module 11 may control the sensor to sleep and restart according to a phone with a specific number or a short message with a specific number. For example, if the SIM card module 14 of the shoe part detecting device 10 receives a short message with the content of "1001" of the preset phone number 13000000000, the MCU main control module 11 controls the acceleration sensor to sleep; if the SIM card module 14 of the shoe part detecting device 10 receives the short message with the preset telephone number 13000000000 content of "1002", the MCU main control module 11 controls the acceleration sensor to restart; if the SIM card module 14 of the shoe part detecting device 10 receives the short message with the preset telephone number 13000000000 content of "1003", the MCU main control module 11 controls the GPS sensor to sleep; if the SIM card module 14 of the shoe part detecting device 10 receives a short message with "1004" content of the preset phone number 13000000000 or a phone with a phone number 13000000000, the MCU main control module 11 controls the GPS sensor to restart.
The MCU main control module 11 controls the sensor 12 to sleep and restart according to the data information sent by the cloud server 20, the telephone dialed by a telecom operator and the sent short message, so that the sensor 12 is in sleep when data detection is not needed, and the energy consumption of the shoe part detection device 10 is effectively reduced.
The foregoing is considered as illustrative of the preferred embodiments of the invention and is not to be construed as limiting the invention in any way. Various equivalent changes and modifications can be made by those skilled in the art based on the above embodiments, and all equivalent changes and modifications within the scope of the claims should fall within the protection scope of the present invention.
Claims (10)
1. A low-power human body state detection system realized based on NB-IoT is characterized in that: the low-power-consumption human body state detection system based on the NB-IoT comprises a shoe part detection device and a cloud server, wherein the shoe part detection device is arranged on a shoe and comprises an MCU (microprogrammed control unit) main control module, a sensor and an NB-IoT module, and the sensor and the NB-IoT module are respectively connected with the MCU main control module; the sensor is used for monitoring a human body and generating human body monitoring data; the MCU main control module is used for reading human body monitoring data generated by the sensor and outputting the human body monitoring data to the NB-IoT module; the NB-IoT module is used for forwarding the human body monitoring data to a cloud server through an NB-IoT network; the cloud server is used for obtaining human body state information according to the human body monitoring data operation.
2. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the low-power-consumption human body state detection system based on the NB-IoT comprises terminal equipment, wherein the terminal equipment is in communication connection with a cloud server through the NB-IoT network and is used for acquiring human body state information from the cloud server and displaying the human body state information.
3. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the shoe part detection device also comprises an SIM card module connected with the NB-IoT module and used for identifying the SIM card of a telecom operator to carry out data information, telephone or short message communication.
4. The NB-IoT implementation-based low-power human state detection system of claim 3, wherein: the cloud server is also used for sending data information to the shoe part detection device; the NB-IoT module is also used for receiving the data information and forwarding the data information to the MCU main control module; the SIM card module is also used for receiving a telephone dialed by a telecom operator and a short message sent by the telecom operator; and the MCU master control module is also used for controlling the sensor to be dormant and restarted according to the data information, the telephone dialed by a telecom operator and the sent short message.
5. The NB-IoT implementation-based low-power human state detection system of claim 4, wherein: the shoe part detection device also comprises a storage module connected with the MCU main control module, and the storage module is used for storing human body monitoring data generated by the sensor;
the MCU main control module is used for transmitting the human body monitoring data generated by the sensor to the cloud server through the NB-IoT module in real time;
or the MCU master control module is used for pre-storing the human body monitoring data generated by the sensor into the storage module and transmitting the stored human body monitoring data to the cloud server through the NB-IoT module according to a preset transmission cycle or a preset transmission condition.
6. The NB-IoT implementation-based low-power human state detection system of claim 5, wherein: the MCU main control module is used for storing the human body monitoring data into the storage module when the NB-IoT module data transmission abnormality is detected, and continuously transmitting the human body monitoring data to the cloud server through the NB-IoT module after the data transmission abnormality is eliminated.
7. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the sensor comprises an acceleration sensor, and the acceleration sensor is used for acquiring acceleration information in the human body movement process; the MCU master control module is used for reading the acceleration information and outputting the acceleration information to the NB-IoT module; the NB-IoT module is used for forwarding the acceleration information to a cloud server through an NB-IoT network; the cloud server is used for calculating and acquiring human motion state information according to the acceleration information, wherein the human motion state information comprises slow walking, fast walking, running, sedentary, step frequency and speed.
8. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the sensor comprises a GPS sensor, and the GPS sensor is used for acquiring geographic position coordinate data; the MCU master control module is used for reading the geographic position coordinate data and outputting the geographic position coordinate data to the NB-IoT module; the NB-IoT module is used for forwarding the geographic position coordinate data cloud server through an NB-IoT network; and the cloud server acquires the position information, the direction information, the altitude information and the weather information of the person according to the geographic position coordinate data through data query, and calculates the track information of the movement of the person.
9. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the sensor comprises a pressure sensor, and the pressure sensor is used for acquiring pressure value data of a human body to the shoe; the MCU main control module is used for reading the pressure value data and outputting the pressure value data to the NB-IoT module; the NB-IoT module is used for forwarding the pressure value data cloud server through an NB-IoT network; and the cloud server calculates the weight and the body fat rate of the person according to the data.
10. The NB-IoT implementation-based low-power human state detection system of claim 1, wherein: the sensor comprises a heart rate sensor, and the heart rate sensor is used for acquiring heart efficiency, respiration rate, blood pressure and blood oxygen level data of a human body; the MCU main control module is used for reading the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data and outputting the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data to the NB-IoT module; the NB-IoT module is used for forwarding the heart rate, respiration rate, blood pressure and blood oxygen level data to a cloud server through an NB-IoT network; and the cloud server judges whether the heart efficiency, the respiration rate, the blood pressure and the blood oxygen level data are in a normal range or not through data query and comparison.
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