CN111863277A - Crowd body temperature monitoring system based on big data - Google Patents
Crowd body temperature monitoring system based on big data Download PDFInfo
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Abstract
The invention discloses a crowd body temperature monitoring system based on big data, which comprises a data primary inspection module, a positioning module, a health analysis module, a generation printing module and a timing module, wherein the timing module is used for recording the wearing time of a plurality of mobile terminals; the positioning module is used for positioning the moving tracks of the plurality of mobile terminals; the data primary inspection module is used for initially inspecting the data acquired by the data acquisition module, and the data passing the primary inspection is sent to the server; the health analysis module is used for analyzing the health condition of the health bracelet user and sending the health analysis result to the sending module; the body temperature of the old and the infant can be recorded in real time by wearing the articles similar to the bracelet and the like, the body temperature of the old and the infant does not need to be detected and the health table does not need to be manually filled in when the old and the infant approach to detection points, and the body temperature can be conveniently known through the articles similar to the bracelet.
Description
Technical Field
The invention belongs to the field of epidemic situation prevention and control, relates to a body temperature monitoring and management technology, and particularly relates to a crowd body temperature monitoring system based on big data.
Background
Epidemic situation, the Chinese words, refers to the occurrence and development of epidemic diseases, and the major epidemic situations appearing in a large range include Severe Acute Respiratory Syndrome (SARS), influenza A H1N1 and novel coronavirus pneumonia. Wherein, the novel coronavirus pneumonia is pneumonia caused by 2019 novel coronavirus infection. In order to effectively control epidemic situations and make anti-epidemic work, body temperature monitoring points are established at community entrances, village entrances, office building entrances, subway entrances and the like in various regions at home, the body temperature of people entering the region is monitored, health codes are displayed, and basic work of epidemic situation prevention and control is made.
In the prior art, in order to effectively control epidemic situations and avoid spreading of epidemic situations, body temperature monitoring points are established at a community entrance, an office area entrance, a railway station exit and the like, health codes and artificial body temperature detection must be shown when the body temperature monitoring points are passed through, but aiming at the old, the weak, the sick, the disabled and the young, the crowds cannot use intelligent equipment, the initial health codes of the mobile terminal cannot be passed through, filling of a health table can only be carried out through a writing pen, the writing pen is used by a plurality of people in the using process, the hidden danger of virus infection exists, and the epidemic situations are not favorably prevented and controlled.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a crowd body temperature monitoring system based on big data.
The technical problem to be solved by the invention is as follows:
when the population such as the old, the weak, the sick, the disabled and the children passes through the body temperature monitoring point, the intelligent device cannot be used skillfully, so that the effective health code cannot be presented, and the health form can be filled in only through a writing pen; the writing pen is used by a plurality of people in the filling process, has the hidden trouble of virus infection and is not beneficial to the prevention and control of epidemic situations.
The purpose of the invention can be realized by the following technical scheme:
a crowd body temperature monitoring system based on big data comprises an information input module, a plurality of mobile terminals, a data acquisition module, a data primary inspection module, a positioning module, a sending module, a display module, a health analysis module, a generation and printing module, a database, a timing module and a server;
the information input module is used for inputting personal information of a user of the mobile terminal and sending the personal information and the body information to the database for storage, wherein the personal information comprises a real name, a personal sex, a real age and an existing medical history; the timing module is used for recording the wearing time of the plurality of mobile terminals; the positioning module is used for positioning the moving tracks of the plurality of mobile terminals; the mobile terminals are specifically health bracelets worn by wrists of users, the health bracelets are used for recording physical conditions of the users and sending the physical conditions to the server, and the physical conditions comprise body temperature data, activity areas, heart rate data and wearing time of the users;
the data acquisition module is used for acquiring data of the plurality of mobile terminals and the positioning module and sending the data to the data primary inspection module; the data preliminary examination module is used for the data that the preliminary examination data acquisition module gathered, and the data transmission that the preliminary examination passes through to the server, and specific preliminary examination process is as follows:
s1: acquiring body temperature data Wi, i of a health bracelet user for the previous 15 days is 1, … … and 15, and four body temperature safety levels are set: the corresponding values of the four body temperature safety levels are Mo, o is 1, 2, 3 and 4, and M1 is more than M2 is more than M3 is more than M4;
s2: traversing the maximum temperature value Wmax and the minimum temperature value Wmin in the body temperature data of the health bracelet user in the previous 15 days, and setting a body temperature safety threshold Wy;
s3: if Wmin is larger than Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a high risk level, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s4: if Wmax is less than or equal to Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a no-danger level, the initial examination is passed, and the step S5 is entered;
s5: acquiring the activity area of the health bracelet user in the previous 15 days, marking the activity area of the health bracelet user in each day as Qi, i is 1, … … and 15, and setting four area risk levels: the high risk area, the middle risk area and the low risk area correspond to values Xe, e is 1, 2 and 3, and X1 is more than X2 is more than X3;
s6: if any high-risk area exists in the activity area 15 days before the health bracelet user, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s7: if any high-risk area does not exist in the activity area of the health bracelet user in the previous 15 days, the initial examination is passed, and the step S8 is entered;
s8: acquiring the wearing time of the health bracelet user in the previous 15 days, marking the wearing time of the health bracelet user as Pti, i is 1, … … and 15, and setting three wearing times and: the corresponding values of the three wearing time sums are Nf, f is 1, 2 and 3, and N1 is greater than N2 is greater than N3;
s9: calculating the wearing time sum Pzt of the health bracelet user in the previous 15 days by using a summation formula, wherein if the wearing time sum Pzt is smaller than the third wearing time sum, the initial examination does not pass;
s10: the initial inspection data is sent to a server;
the database is used for storing the acquired data; the health analysis module is used for analyzing the health condition of the health bracelet user and sending the health analysis result to the sending module; the transmitting module is used for receiving the health analysis result and transmitting the health analysis result to the display module; the display module is used for displaying the health data of the health bracelet user at the body temperature monitoring point.
Further, the specific analysis process of the health analysis module is as follows:
SS 1: acquiring middle danger level, low danger level and days without danger level in the body temperature safety level of a health bracelet user 15 days before, wherein the days with the middle danger level are h, and the days with the low danger level are l;
SS 2: acquiring the number of risk areas and low risk areas in an activity area 15 days before a health bracelet user, wherein the number of the medium risk areas is j;
SS 3: calculating a safety value Aq of body temperature data and a risk value Fx of an activity area in 15 days before using a formula to obtain a health bracelet user, wherein the specific formula is as follows:
Aq＝M2*h+M3*l+M4*(15-h-l)；
Fx＝X2*j+X3*(15-j)；
SS 4: acquiring a heart rate value xin of a health bracelet user, combining a safety value Aq, taking a numerical value after dequantization, and calculating a physical condition value Sz of the health bracelet user by using a formula:
SS 5: acquiring the wearing time sum Pzt of the health bracelet user in the previous 15 days, and calculating to obtain the average wearing time Pavt of the previous 15 days;
SS 6: combining the physical condition value Sz of the health bracelet user, the risk value Fx of the activity area and the average wearing time Pavt, carrying out dequantization processing, then taking a numerical value, and calculating the health value Jk of the health bracelet user by using a formula;
SS 7: the health value is fed back to the server and the sending module, the health value is compared with a preset health threshold value in the database, if the health value exceeds the preset health threshold value, the server generates a monitoring qualified signal and loads the monitoring qualified signal to the sending module, and if the health value does not exceed the preset health threshold value, the server generates a monitoring unqualified signal and loads the monitoring unqualified signal to the sending module;
SS 8: and the sending module receives the qualified monitoring signal and the unqualified monitoring signal and sends the two signals to the display module.
Further, after the sending module receives the monitoring qualified signal and the monitoring unqualified signal, the sending module sends the health analysis result to the display module.
Furthermore, a pulse sensor and a temperature sensor are arranged in the plurality of mobile terminals, the display module is specifically a display terminal of the body temperature monitoring point, the timing module is further used for timing the sending time of the health analysis result sent by the sending module, and when the sending time reaches a preset time threshold, the timing module generates a timing signal and sends the timing signal to the server.
The system further comprises a generating and printing module, wherein the generating and printing module is used for generating a health table from the health analysis result and printing the health table at a specified place of the system.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides a crowd body temperature monitoring system based on big data, which is characterized in that personal information of a user is recorded into a mobile terminal through an information recording module, the personal information and body information are sent to a database, a timing module records the wearing time of the mobile terminal, a movable track of a mobile terminal of a positioning module is positioned, the mobile terminal is a healthy bracelet in actual life, the healthy bracelet can record the body condition of the user and send the body condition to a server, meanwhile, data of the mobile terminal and the positioning module are collected through a data collecting module, the data collected by the data collecting module are subjected to preliminary examination through the data collecting module, firstly, body temperature data Wi of the user of the healthy bracelet 15 days before is obtained, and four body temperature safety levels are set: high risk level, medium risk level, low risk level and no risk level, the corresponding values of the four body temperature safety levels are Mo, o is 1, 2, 3 and 4, setting a body temperature safety threshold Wy when M1 is more than M2 is more than M3 is more than M4, traversing the maximum body temperature Wmax and the minimum body temperature Wmin in the body temperature data of the health bracelet user 15 days before, if Wmin is more than Wy, then the body temperature of the health bracelet user in the previous 15 days is judged to be in a high risk level, the preliminary examination is not passed, the physical condition of the health bracelet user after the preliminary examination is directly displayed through the display module, if Wmax is less than or equal to Wy, then the body temperature of the health bracelet user in the previous 15 days is judged to be in a no-danger level, the initial examination is passed, secondly, obtain the active area of healthy bracelet user's preceding 15 days to with healthy bracelet user's active area mark of every day Qi, set for four regional risk classes: high risk area, well risk area and low risk area, and correspond value Xe in proper order, e is 1, 2, 3, and X1 > X2 > X3, if there is any one high risk area in the active area of healthy bracelet user's preceding 15 days, the preliminary examination is not passed, health status after the healthy bracelet user's preliminary examination directly shows through display module, if there is not any one high risk area in the active area of healthy bracelet user's preceding 15 days, the preliminary examination passes, finally, acquire the daily live time of healthy bracelet user's preceding 15 days, and mark healthy bracelet user's daily live time as Pti, set for three live time and: the health bracelet body temperature monitoring system comprises a first wearing time sum, a second wearing time sum and a third wearing time sum, wherein corresponding values of the three wearing time sums are Nf, f is 1, 2 and 3, N1 is more than N2 is more than N3, the sum Pzt of the wearing time of the health bracelet user in the previous 15 days is calculated by using a summation formula, if the sum Pzt of the wearing time is less than the sum of the third wearing time sum, the initial examination is not passed, and after the data are summarized, the data which are passed by the initial examination are sent to a server;
2. the data passing the initial examination is subjected to health analysis through a health analysis module, firstly, the dangerous grade, the low dangerous grade and the days without dangerous grade in the body temperature safety grade of the healthy bracelet user for 15 days are obtained, the number of the dangerous areas and the low dangerous areas in the activity area of the healthy bracelet user for 15 days is obtained, the safety value Aq and the risk value Fx of the body temperature data of the healthy bracelet user for 15 days are calculated by using the formula Aq (M2 h + M3 l + M4 (15-h-l) and the formula Fx (X2 j + X3 (15-j), secondly, the heart rate xin of the healthy bracelet user is obtained, and the safety value Aq is combined to removeTaking numerical value after quantization processing, and using formula
Calculating to obtain a physical condition value Sz of a health bracelet user, finally, obtaining the wearing time sum Pzt of the health bracelet user in the previous 15 days, calculating to obtain the average wearing time Pavt of the previous 15 days, combining the physical condition value Sz of the health bracelet user, the risk value Fx of the activity area and the average wearing time Pavt, obtaining a numerical value after dequantization, and utilizing a formula
Calculating a health value Jk of a healthy bracelet user, feeding the health value back to a server and a sending module, comparing the health value with a preset health threshold value in a database, if the health value exceeds the preset health threshold value, loading a monitoring qualified signal generated by the server into the sending module, if the health value does not exceed the preset health threshold value, loading a monitoring unqualified signal generated by the server into the sending module, after the sending module receives the monitoring qualified signal and the monitoring unqualified signal, sending a health analysis result to a display module by the sending module, displaying the health data of the healthy bracelet user by the display screen at a body temperature monitoring point, carrying out further health analysis on the health data passing through initial examination, and systematically converting the health value through a series of parameters such as a safety value, a risk value of an activity area, a heart rate value, an average wearing time and a body condition value, the health condition of the user is judged according to the comparison of the health value and the preset data threshold, so that a qualified monitoring signal and an unqualified monitoring signal are generated and sent to the display terminal, the detection personnel can realize the rapid body temperature detection of the personnel according to the signals, the detection is convenient and efficient, and the accuracy is high;
3. when the sending time of the health analysis result sent by the sending module reaches a preset time threshold, the timing module generates a timing signal and sends the timing signal to the server; the health table is generated from the health analysis result through the generating and printing module and is printed at a designated place of the system, so that the health table is convenient for users to carry, and the users can display an effective paper health table when the body temperature monitoring system is down;
in conclusion, the body temperature of the old and the infant can be recorded in real time by wearing the articles similar to the bracelet and the like, the body temperature of the old and the infant can be conveniently known through the articles similar to the bracelet without carrying out body temperature detection on the old and the infant and manually filling in a health table when the old and the infant approach to detection points.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is an overall system block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a crowd body temperature monitoring system based on big data comprises an information input module, a plurality of mobile terminals, a data acquisition module, a data initial inspection module, a positioning module, a sending module, a display module, a health analysis module, a generating and printing module, a database, a timing module and a server;
the information input module is used for inputting personal information of a user of the mobile terminal and sending the personal information and the body information to the database for storage, wherein the personal information comprises a real name, a personal sex, a real age and an existing medical history; the timing module is used for recording the wearing time of the plurality of mobile terminals; the positioning module is used for positioning the moving tracks of the plurality of mobile terminals; the mobile terminals are specifically health bracelets worn by wrists of users, the health bracelets are used for recording physical conditions of the users and sending the physical conditions to the server, and the physical conditions comprise body temperature data, activity areas, heart rate data and wearing time of the users;
the data acquisition module is used for acquiring data of the plurality of mobile terminals and the positioning module and sending the data to the data primary inspection module; the data preliminary examination module is used for the data that the preliminary examination data acquisition module gathered, and the data transmission that the preliminary examination passes through to the server, and specific preliminary examination process is as follows:
s1: acquiring body temperature data Wi, i of a health bracelet user for the previous 15 days is 1, … … and 15, and four body temperature safety levels are set: the corresponding values of the four body temperature safety levels are Mo, o is 1, 2, 3 and 4, and M1 is more than M2 is more than M3 is more than M4;
s2: traversing the maximum temperature value Wmax and the minimum temperature value Wmin in the body temperature data of the health bracelet user in the previous 15 days, and setting a body temperature safety threshold Wy;
s3: if Wmin is larger than Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a high risk level, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s4: if Wmax is less than or equal to Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a no-danger level, the initial examination is passed, and the step S5 is entered;
s5: acquiring the activity area of the health bracelet user in the previous 15 days, marking the activity area of the health bracelet user in each day as Qi, i is 1, … … and 15, and setting four area risk levels: the high risk area, the middle risk area and the low risk area correspond to values Xe, e is 1, 2 and 3, and X1 is more than X2 is more than X3;
s6: if any high-risk area exists in the activity area 15 days before the health bracelet user, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s7: if any high-risk area does not exist in the activity area of the health bracelet user in the previous 15 days, the initial examination is passed, and the step S8 is entered;
s8: acquiring the wearing time of the health bracelet user in the previous 15 days, marking the wearing time of the health bracelet user as Pti, i is 1, … … and 15, and setting three wearing times and: the corresponding values of the three wearing time sums are Nf, f is 1, 2 and 3, and N1 is greater than N2 is greater than N3;
s9: calculating the wearing time sum Pzt of the health bracelet user in the previous 15 days by using a summation formula, wherein if the wearing time sum Pzt is smaller than the third wearing time sum, the initial examination does not pass;
s10: the initial inspection data is sent to a server;
the database is used for storing the acquired data; the health analysis module is used for analyzing the health condition of the health bracelet user and sending the health analysis result to the sending module; the transmitting module is used for receiving the health analysis result and transmitting the health analysis result to the display module; the display module is used for displaying the health data of the health bracelet user at the body temperature monitoring point.
The specific analysis process of the health analysis module is as follows:
SS 1: acquiring middle danger level, low danger level and days without danger level in the body temperature safety level of a health bracelet user 15 days before, wherein the days with the middle danger level are h, and the days with the low danger level are l;
SS 2: acquiring the number of risk areas and low risk areas in an activity area 15 days before a health bracelet user, wherein the number of the medium risk areas is j;
SS 3: calculating a safety value Aq of body temperature data and a risk value Fx of an activity area in 15 days before using a formula to obtain a health bracelet user, wherein the specific formula is as follows:
Aq＝M2*h+M3*l+M4*(15-h-l)；
Fx＝X2*j+X3*(15-j)；
SS 4: acquiring a heart rate value xin of a health bracelet user, combining a safety value Aq, taking a numerical value after dequantization, and calculating a physical condition value Sz of the health bracelet user by using a formula:
SS 5: acquiring the wearing time sum Pzt of the health bracelet user in the previous 15 days, and calculating to obtain the average wearing time Pavt of the previous 15 days;
SS 6: combining the physical condition value Sz of the health bracelet user, the risk value Fx of the activity area and the average wearing time Pavt, carrying out dequantization processing, then taking a numerical value, and calculating the health value Jk of the health bracelet user by using a formula;
SS 7: the health value is fed back to the server and the sending module, the health value is compared with a preset health threshold value in the database, if the health value exceeds the preset health threshold value, the server generates a monitoring qualified signal and loads the monitoring qualified signal to the sending module, and if the health value does not exceed the preset health threshold value, the server generates a monitoring unqualified signal and loads the monitoring unqualified signal to the sending module;
SS 8: and the sending module receives the qualified monitoring signal and the unqualified monitoring signal and sends the two signals to the display module.
After the sending module receives the monitoring qualified signals and the monitoring unqualified signals, the sending module sends the health analysis results to the display module, and the health data of health bracelet users can be conveniently checked by detection personnel through the display module.
Wherein, a plurality of mobile terminal embeds has pulse sensor and temperature sensor, conveniently gathers the rhythm of the heart pulse and the body temperature of acquireing the user of service personnel, display module specifically is the display terminal of body temperature monitoring point, conveniently looks over user of service personnel's body temperature and healthy data, timing module still is used for timing to the sending time that sending module sent healthy analysis result, and when sending time reachd the scheduled time threshold value, timing module generation timing signal and send to the server, convenient timely health analysis result with user of service personnel sends to display terminal.
The system further comprises a generating and printing module, wherein the generating and printing module is used for generating the health table according to the health analysis result and printing the health table at a designated place of the system, the health analysis result is generated and printed, the system is convenient for users to carry, and the users can show the paper health table when the body temperature monitoring system is down.
The above formulas are all quantitative calculation, the formula is a formula obtained by acquiring a large amount of data and performing software simulation to obtain the latest real situation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The utility model provides a crowd body temperature monitoring system based on big data, in operation, through the information input module with in the personnel's personal information input mobile terminal, and send personal information and health information to the database, the timing module is taken notes mobile terminal's the time of wearing, the activity track of orientation module mobile terminal is fixed a position, healthy bracelet in the concrete actual life of mobile terminal, healthy bracelet can take notes user's health status, and send health status to the server, data through data acquisition module collection mobile terminal and orientation module simultaneously, the data that data acquisition module gathered go on examining through data acquisition module, firstly, acquire the body temperature data Wi of healthy bracelet user 15 days before, and set for four body temperature safety classes: high risk level, medium risk level, low risk level and no risk level, the corresponding values of the four body temperature safety levels are Mo, o is 1, 2, 3 and 4, setting a body temperature safety threshold Wy when M1 is more than M2 is more than M3 is more than M4, traversing the maximum body temperature Wmax and the minimum body temperature Wmin in the body temperature data of the health bracelet user 15 days before, if Wmin is more than Wy, then the body temperature of the health bracelet user in the previous 15 days is judged to be in a high risk level, the preliminary examination is not passed, the physical condition of the health bracelet user after the preliminary examination is directly displayed through the display module, if Wmax is less than or equal to Wy, then the body temperature of the health bracelet user in the previous 15 days is judged to be in a no-danger level, the initial examination is passed, secondly, obtain the active area of healthy bracelet user's preceding 15 days to with healthy bracelet user's active area mark of every day Qi, set for four regional risk classes: high risk area, well risk area and low risk area, and correspond value Xe in proper order, e is 1, 2, 3, and X1 > X2 > X3, if there is any one high risk area in the active area of healthy bracelet user's preceding 15 days, the preliminary examination is not passed, health status after the healthy bracelet user's preliminary examination directly shows through display module, if there is not any one high risk area in the active area of healthy bracelet user's preceding 15 days, the preliminary examination passes, finally, acquire the daily live time of healthy bracelet user's preceding 15 days, and mark healthy bracelet user's daily live time as Pti, set for three live time and: the first wearing time sum, the second wearing time sum and the third wearing time sum are obtained, corresponding values of the three wearing time sums are Nf, f is 1, 2 and 3, N1 is larger than N2 is larger than N3, the sum Pzt of the wearing time of the health bracelet user in the previous 15 days is calculated by using a summation formula, and if the sum Pzt of the wearing time is smaller than the third wearing time sum, the initial examination does not pass, and after the data are summarized, the data which pass the initial examination are sent to a server;
the data passing the initial examination is subjected to health analysis through a health analysis module, firstly, the dangerous grade, the low dangerous grade and the days without dangerous grade in the body temperature safety grade of the healthy bracelet user for 15 days are obtained, the number of the dangerous areas and the low dangerous areas in the activity area of the healthy bracelet user for 15 days is obtained, the safety value Aq and the risk value Fx of the body temperature data of the healthy bracelet user for 15 days are calculated by using a formula Aq (M2 h + M3 l + M4 (15-h-l) and a formula Fx (X2 j + X3 (15-j), secondly, the heart rate value xin of the healthy bracelet user is obtained, the numerical value is obtained after quantitative processing is combined with the safety value Aq, and the numerical value is obtained by using the formula
Calculating to obtain the physical condition value Sz of the health bracelet user, finally, acquiring the wearing time sum Pzt of the health bracelet user for the previous 15 days, and calculating to obtain the previous 15 daysThe average wearing time Pavt is obtained by combining the physical condition value Sz of the healthy bracelet user, the risk value Fx of the activity area and the average wearing time Pavt, carrying out dequantization processing and then obtaining a numerical value by using a formula
Calculating a health value Jk of a healthy bracelet user, feeding the health value back to the server and the sending module, comparing the health value with a preset health threshold value in a database, if the health value exceeds the preset health threshold value, loading a monitoring qualified signal generated by the server into the sending module, if the health value does not exceed the preset health threshold value, loading an unqualified monitoring signal generated by the server into the sending module, after the sending module receives the qualified monitoring signal and the unqualified monitoring signal, sending a health analysis result to the display module by the sending module, and displaying the health data of the healthy bracelet user by the display screen at a body temperature monitoring point by the display module;
when the sending time of the health analysis result sent by the sending module reaches a preset time threshold, the timing module generates a timing signal and sends the timing signal to the server; generating a health table from the health analysis result through a generating and printing module and printing the health table at a specified place of the system;
in conclusion, the body temperature of the old and the infant can be recorded in real time by wearing the articles similar to the bracelet and the like, the body temperature of the old and the infant can be conveniently known through the articles similar to the bracelet without carrying out body temperature detection on the old and the infant and manually filling in a health table when the old and the infant approach to detection points.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. A crowd body temperature monitoring system based on big data is characterized by comprising an information input module, a plurality of mobile terminals, a data acquisition module, a data primary inspection module, a positioning module, a sending module, a display module, a health analysis module, a generating and printing module, a database, a timing module and a server;
the information input module is used for inputting personal information of a user of the mobile terminal and sending the personal information and the body information to the database for storage, wherein the personal information comprises a real name, a personal sex, a real age and an existing medical history; the timing module is used for recording the wearing time of the plurality of mobile terminals; the positioning module is used for positioning the moving tracks of the plurality of mobile terminals; the mobile terminals are specifically health bracelets worn by wrists of users, the health bracelets are used for recording physical conditions of the users and sending the physical conditions to the server, and the physical conditions comprise body temperature data, activity areas, heart rate data and wearing time of the users;
the data acquisition module is used for acquiring data of the plurality of mobile terminals and the positioning module and sending the data to the data primary inspection module; the data preliminary examination module is used for the data that the preliminary examination data acquisition module gathered, and the data transmission that the preliminary examination passes through to the server, and specific preliminary examination process is as follows:
s1: acquiring body temperature data Wi, i of a health bracelet user for the previous 15 days is 1, … … and 15, and four body temperature safety levels are set: the corresponding values of the four body temperature safety levels are Mo, o is 1, 2, 3 and 4, and M1 is more than M2 is more than M3 is more than M4;
s2: traversing the maximum temperature value Wmax and the minimum temperature value Wmin in the body temperature data of the health bracelet user in the previous 15 days, and setting a body temperature safety threshold Wy;
s3: if Wmin is larger than Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a high risk level, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s4: if Wmax is less than or equal to Wy, the body temperature of the health bracelet user in the previous 15 days is judged to be in a no-danger level, the initial examination is passed, and the step S5 is entered;
s5: acquiring the activity area of the health bracelet user in the previous 15 days, marking the activity area of the health bracelet user in each day as Qi, i is 1, … … and 15, and setting four area risk levels: the high risk area, the middle risk area and the low risk area correspond to values Xe, e is 1, 2 and 3, and X1 is more than X2 is more than X3;
s6: if any high-risk area exists in the activity area 15 days before the health bracelet user, the initial examination does not pass, and the physical condition of the health bracelet user after the initial examination is directly displayed through the display module;
s7: if any high-risk area does not exist in the activity area of the health bracelet user in the previous 15 days, the initial examination is passed, and the step S8 is entered;
s8: acquiring the wearing time of the health bracelet user in the previous 15 days, marking the wearing time of the health bracelet user as Pti, i is 1, … … and 15, and setting three wearing times and: the corresponding values of the three wearing time sums are Nf, f is 1, 2 and 3, and N1 is greater than N2 is greater than N3;
s9: calculating the wearing time sum Pzt of the health bracelet user in the previous 15 days by using a summation formula, wherein if the wearing time sum Pzt is smaller than the third wearing time sum, the initial examination does not pass;
s10: the initial inspection data is sent to a server;
the database is used for storing the acquired data; the health analysis module is used for analyzing the health condition of the health bracelet user and sending the health analysis result to the sending module; the transmitting module is used for receiving the health analysis result and transmitting the health analysis result to the display module; the display module is used for displaying the health data of the health bracelet user at the body temperature monitoring point.
2. The big-data based human body temperature monitoring system according to claim 1, wherein the health analysis module performs the following analysis process:
SS 1: acquiring middle danger level, low danger level and days without danger level in the body temperature safety level of a health bracelet user 15 days before, wherein the days with the middle danger level are h, and the days with the low danger level are l;
SS 2: acquiring the number of risk areas and low risk areas in an activity area 15 days before a health bracelet user, wherein the number of the medium risk areas is j;
SS 3: calculating a safety value Aq of body temperature data and a risk value Fx of an activity area in 15 days before using a formula to obtain a health bracelet user, wherein the specific formula is as follows:
Aq＝M2*h+M3*l+M4*(15-h-l)；
Fx＝X2*j+X3*(15-j)；
SS 4: acquiring a heart rate value xin of a health bracelet user, combining a safety value Aq, taking a numerical value after dequantization, and calculating a physical condition value Sz of the health bracelet user by using a formula:
SS 5: acquiring the wearing time sum Pzt of the health bracelet user in the previous 15 days, and calculating to obtain the average wearing time Pavt of the previous 15 days;
SS 6: combining the physical condition value Sz of the health bracelet user, the risk value Fx of the activity area and the average wearing time Pavt, carrying out dequantization processing, then taking a numerical value, and calculating the health value Jk of the health bracelet user by using a formula;
SS 7: the health value is fed back to the server and the sending module, the health value is compared with a preset health threshold value in the database, if the health value exceeds the preset health threshold value, the server generates a monitoring qualified signal and loads the monitoring qualified signal to the sending module, and if the health value does not exceed the preset health threshold value, the server generates a monitoring unqualified signal and loads the monitoring unqualified signal to the sending module;
SS 8: and the sending module receives the qualified monitoring signal and the unqualified monitoring signal and sends the two signals to the display module.
3. The crowd body temperature monitoring system based on big data according to claim 1, wherein the sending module sends the health analysis result to the display module after receiving the monitoring qualified signal and the monitoring unqualified signal.
4. The crowd body temperature monitoring system based on big data according to claim 1, wherein a plurality of mobile terminals are provided with pulse sensors and temperature sensors inside, the display module is a display terminal of a body temperature monitoring point, the timing module is further configured to time the sending time of the sending module for sending the health analysis result, and when the sending time reaches a predetermined time threshold, the timing module generates a timing signal and sends the timing signal to the server.
5. The big data based crowd body temperature monitoring system according to claim 1, further comprising a generating and printing module for generating a health table from the health analysis results and printing the health table at a designated place of the system.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112687400A (en) * | 2020-12-29 | 2021-04-20 | 心麦(江苏)大数据科技有限公司 | Intelligent perception epidemic prevention early warning method |
| CN114708711A (en) * | 2022-03-31 | 2022-07-05 | 河北金锁安防工程股份有限公司 | Epidemic situation alarm method and system based on machine vision |
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2020
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112687400A (en) * | 2020-12-29 | 2021-04-20 | 心麦(江苏)大数据科技有限公司 | Intelligent perception epidemic prevention early warning method |
| CN114708711A (en) * | 2022-03-31 | 2022-07-05 | 河北金锁安防工程股份有限公司 | Epidemic situation alarm method and system based on machine vision |
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