CN111044680A - Atmospheric environment exercise health monitoring method and monitoring system - Google Patents
Atmospheric environment exercise health monitoring method and monitoring system Download PDFInfo
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Abstract
The invention provides an atmospheric environment health monitoring method, which relates to the field of environmental health monitoring and comprises the following steps: s1: the server side continuously acquires the acquired positioning information; if the acquisition is not completed, the acquisition is continued until the completion, and then the step S2 is performed; s2: analyzing the track information and time according to the positioning information acquired in the step S1; if the analysis is not completed, continuing the analysis until the analysis is completed, and then performing step S3; s3: performing monitoring site and concentration matching calculation according to the track information and time in the step S2 until the calculation is completed, and performing exposure time attribution calculation; s4: configuring exposure parameters; s5: calculating an exposure level; s6: and generating an exposure level report, and completing the exposure level analysis. According to the exposure time, the exposure concentration and the relevant parameters, the relevant exposure level intake is calculated, and the relevant exposure level is comprehensively analyzed, so that the comprehensive analysis of sites and human bodies is ensured, and the exposure level intake is fully demonstrated and researched.
Description
Technical Field
The invention relates to the field of environmental health monitoring, in particular to an atmospheric environmental health monitoring method and system.
Background
In the early 80 s of the 20 th century, duan and ott proposed the concept of exposure assessment, defining "exposure" as the instantaneous exposure of a person or group of persons to a certain pollutant at a given time. If the duration is considered together, an "integrated exposure value" over a period of time is obtained, which we generally speak of more average exposure, i.e. the cumulative exposure divided by the integration time. At present, two methods are mainly used at home and abroad for exposure evaluation: firstly, a method of wearing an individual wearing device for a large number of people, such as an individual sampling pump, a passive sampler and the like, is utilized, and the method needs to recruit a large number of people and needs to distribute and recycle a large number of sampling devices, so that the labor and material costs are high. Meanwhile, as each individual is specifically identified, differences among different individuals can bring a large number of confounding factors to later analysis. On the contrary, the other method adopts the air quality data of the environment published by the country or the air quality data on the international website, the data are widely applied to all target groups, and huge uncertainty caused by mismatching of exposure data and group activities is often brought to research results.
Chinese patent document CN 109493973A relates to a household residential air environment health risk early warning method, belongs to the technical field of environmental monitoring, and solves the problems that in the prior art, environmental monitoring and early warning cannot be carried out according to actual stay time and behavior difference of a user in a room, and environmental exposure cannot be analyzed and evaluated according to actual conditions of rooms with different functions. A household residence air environment health risk early warning method specifically comprises the following steps: acquiring environmental monitoring parameters of rooms with different functions and exposure behavior data of users in the rooms with different functions; drawing exposure concentration curves of different types of air pollutants, and calculating the exposure concentrations of the different types of air pollutants; and evaluating and early warning the exposure risk, and pushing the environmental monitoring parameters, the exposure behavior data, the exposure concentration curve and the evaluation early warning result to a user.
Chinese patent document CN105021230A provides an indoor environment monitoring and health early warning system suitable for households, offices and the like. The invention consists of two parts, namely an indoor environment monitoring system and a health early warning system. The indoor environment monitoring system is provided with sensors for temperature, humidity, light sensation, air dust concentration, formaldehyde and the like, each sensor detects each parameter of the indoor environment, and the parameters are uploaded to the control unit through the ZigBee network after being processed. Indoor environment monitoring and health early warning system based on mobius curve when detecting each item index of indoor environment, can be according to everyone individual's difference, the influence of indoor environment to it is analyzed, gives the suggestion to its health state to reduce the emergence of the life health harm incident that indoor environment quality is too bad to lead to.
The above patent documents can only monitor a small area or a fixed area, but cannot monitor all living areas of a crowd and perform risk early warning.
The invention aims at how to fully utilize a monitoring station network and establish a method for finely evaluating the atmospheric pollutant exposure of people based on environmental air monitoring data, and is not reported at home and abroad at present.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides an atmospheric environment exercise health monitoring method and a monitoring system, and the specific technical scheme is as follows:
in one aspect, the invention provides an atmospheric environment health monitoring method, which is characterized by comprising the following steps:
s1: the server side continuously acquires the acquired positioning information; if the acquisition is not completed, the acquisition is continued until the completion, and then the step S2 is performed;
s2: analyzing the track information and time according to the positioning information acquired in the step S1; if the analysis is not completed, continuing the analysis until the analysis is completed, and then performing step S3;
s3: performing monitoring station and concentration matching calculation according to the track information and time in the step S2 until the calculation is completed, performing exposure time attribution calculation, and performing a step S4 when the exposure time attribution calculation is completed;
s4: configuring the exposure parameters until the exposure parameters are configured, and performing step S5;
s5: calculating the exposure level until the exposure level calculation is completed, proceeding to step S6;
s6: and generating an exposure level report and completing the exposure level analysis.
Preferably, step S1 specifically includes the following steps:
s11: starting a mobile phone APP, collecting positioning information, connecting a map interface, and collecting the longitude and latitude of the mobile phone;
s12: sending the longitude and latitude information to a server at the frequency of 30s once, and judging whether the sent longitude and latitude information is unchanged for more than 20 min; if the mobile phone is determined not to be moved, step S13 is performed:
s13: and segmenting the time and the position of the movement and the non-movement through the mobile phone, sending the recorded time and the recorded position to the server, and completing the segmented acquisition of the positioning information.
Preferably, step S2 specifically includes the following steps:
s21: according to the positioning information segment table obtained in the step S13; configuring a behavior corresponding to the positioning information segment;
s22: acquiring behaviors and segments according to the step S21, and performing path segmentation and time calculation by using a path planning function of a map;
s23: and matching the path segments to the corresponding monitoring stations according to the monitoring station segment models to finally obtain the exposure time of each monitoring station, and finishing the calculation of the exposure time.
Preferably, step S3 specifically includes the following steps:
s31: positioning longitude and latitude by adopting a mobile phone map, detecting whether a monitoring station exists within 5km of the periphery, and if so, directly adopting the exposure concentration of the station of the monitoring station; if not, go to step S32;
s32: reading longitude and latitude, reversely inquiring the regional information of the mobile phone, inquiring 3 monitoring stations nearest to the mobile phone, calculating the center matching concentration according to a concentration diffusion algorithm, and finishing the acquisition of the exposure concentration by taking the center matching concentration as the existing exposure concentration;
P＝(1-u-v)*P1+u*P2+v*P3 (1)
wherein P is the central matching concentration, P1, P2 and P3 are the exposure concentrations of three monitoring stations respectively, and u and v are the weight contributions of the monitoring stations to the acquisition points respectively, wherein u is more than or equal to 0, v is more than or equal to 0, and u + v is less than or equal to 1.
Preferably, step S4 specifically includes the following steps:
s41: sequentially configuring behavior types, respiratory volumes and crowd characteristics;
s42: and (4) performing path planning analysis matching, monitoring station matching and exposure time segmentation calculation and matching in sequence according to the behavior type, the respiration volume and the crowd characteristics in the step S41 until the exposure parameter configuration is completed.
Preferably, step S5 specifically includes the following steps:
s51: confirming the exposure time according to step S2;
s52: confirming the exposure concentration according to step S3;
s53: confirming the exposure parameters according to step S4;
s54: multiplying the exposure time in the step S51, the exposure concentration in the step S52, and the exposure parameter in the step S53, and then accumulating to calculate the exposure level;
s55: and checking whether the monitoring station or the concentration information is missing or not, if so, continuing checking the monitoring station or the concentration information, and if so, generating an exposure level calculation result.
Preferably, the exposure level E in step S54ijDetermined according to equation (2);
Eij＝CAi×tAj×IR×10-6+pi×CAi×tIj×IR×10-6(2)
in the formula: i-certain atmospheric pollutants, including particulate matter and gaseous pollutants, etc.;
j-a panelist;
Eij-a certain(ii) the total exposure (mg) of a certain (i) atmospheric pollutant of the investigational object (j);
CAi-monitored concentration of outdoor atmospheric contaminants (i) (. mu.g/m)3)；
tAj-daily outdoor exposure time (min) for a certain surveyor (j);
picontaminant (i) permeability coefficient inside and outside the room (the ratio of contaminants permeating from the outside into the room);
tIj-indoor exposure time (min) of a certain surveyor (j);
IR-respiratory volume (L/min) of the population at different states of activity.
Preferably, the method further comprises the step of rendering the exposure level result by the APP or the user webpage end, and specifically comprises the following steps:
s71: acquiring an exposure level form, and confirming the exposure time, the exposure concentration and the corresponding monitoring station of each segment;
s72: acquiring the concentration corresponding to the monitoring station or the corresponding calculated concentration, carrying out coordinate positioning on the monitoring station and filling a map with the corresponding concentration thermodynamic diagram by using the concentration;
s73: and analyzing the driving path of the user, filling color according to the concentration of the driving path, performing path gradual change correction, and finally generating an exposure level change graph.
Preferably, the APP or user webpage end can also review historical exposure level intake of the ordinary user and provide personal exposure level trend analysis for the ordinary user.
On the other hand, the invention also provides an atmospheric environment health monitoring system, which comprises a server side and a client side;
the server comprises a server data acquisition unit, an environmental motion monitoring model, a report, an interface and user management; the data acquisition unit comprises environmental data acquisition, motion data acquisition and longitude and latitude data acquisition; the environment motion monitoring model comprises an environment protection environment detection model, a motion detection model, a concentration parameter longitude and latitude calculation model, a motion information model parameter configuration, a motion information model weight configuration, a default motion information model configuration and a model verification; the report forms comprise a map rendering report form, a user motion analysis report form and an environment detection matching report form; the interface comprises an environment data crawling interface, a longitude and latitude data map acquiring interface, a user information interface and a report interface;
the user management comprises report user management, administrator management and user management; the client comprises an APP machine or a related webpage; the APP machine or the related webpage comprises a client data acquisition unit, a user movement behavior report and a user health monitoring report; the client data acquisition unit comprises a map data acquisition unit, a motion data acquisition unit, a user data acquisition unit and a data acquisition and pushing unit; the user motion behavior report comprises user track planning, user motion behavior segmentation and user motion configuration information configuration; the user health monitoring report comprises a user current monitoring report, a user historical monitoring report and a user summarizing, analyzing and monitoring report.
Compared with the prior art, the invention has the following beneficial effects:
(1) the monitoring method and the monitoring system provided by the invention can realize pre-estimation of the exposure of the atmospheric pollutants before the action, real-time dynamic evaluation in the action and a report of the total exposure after the exposure. And according to different behavior characteristics (sitting, standing, walking, bicycles, buses and the like) of different attribute characteristics (gender and age) of the user at different time intervals (concentration levels), giving a segmented behavior pollutant exposure report according to different exposure parameters and the outdoor proportional characteristics of pollutants. The atmospheric pollution exposure evaluation method can meet the use of common users and scientific research users on different demand levels.
(2) The monitoring method and the system provided by the invention analyze the relative exposure level intakes of various emissions of the human motion situation, thereby evaluating the relative research of the relative health situation of the human body, the system divides the time period of the daily behavior track and the behavior mode of the human body based on the relative positioning function and the path planning function of a hundred-degree map, evaluates the relative exposure time and the exposure concentration, calculates the relative exposure level intakes according to relative parameters, and comprehensively analyzes the relative exposure level, thereby ensuring the comprehensive analysis of sites and the human body and ensuring that the exposure level intakes obtain sufficient scientific research and argumentation.
Drawings
FIG. 1 is a flow chart of a method for monitoring the health of an atmospheric environment according to the present invention;
FIG. 2 is a flow chart of the positioning information collection provided by the present invention;
FIG. 3 is a flow chart of path analysis and path planning provided by the present invention;
FIG. 4 is a flow chart of exposure concentration and monitoring station matching provided by the present invention;
FIG. 5 is a flow chart of exposure parameter configuration and distribution provided by the present invention;
FIG. 6 is a flow chart of exposure level calculation provided by the present invention;
FIG. 7 is a main flow chart of the APP terminal;
FIG. 8 is a flow chart of exposure level calculation and rendering for the APP side;
FIG. 9 is a main flow chart of the user web page side;
FIG. 10 is a block diagram of an atmospheric health monitoring system according to the present invention;
FIG. 11 is a diagram of a server structure provided by the present invention;
FIG. 12 is a diagram of the APP terminal structure provided by the present invention;
fig. 13 is a structure diagram of a user web page according to the present invention.
Detailed Description
The following detailed description of the present invention will be made with reference to the accompanying drawings 1-13.
Referring to fig. 1, fig. 1 is a flow chart of an atmospheric environmental health monitoring method provided by the present invention; in one aspect, the invention provides an atmospheric environment health monitoring method, which comprises the following steps:
s1: the server side continuously acquires the acquired positioning information; if the acquisition is not completed, the acquisition is continued until the completion, and then the step S2 is performed;
s2: analyzing the track information and time according to the positioning information acquired in the step S1; if the analysis is not completed, continuing the analysis until the analysis is completed, and then performing step S3;
s3: performing monitoring station and concentration matching calculation according to the track information and time in the step S2 until the calculation is completed, performing exposure time attribution calculation, and performing a step S4 when the exposure time attribution calculation is completed;
s4: configuring the exposure parameters until the configuration of the exposure parameters is completed, and then performing step S5;
s5: calculating the exposure level until the exposure level calculation is completed, proceeding to step S6;
s6: and generating an exposure level report, and completing the exposure level analysis.
The steps in the invention are executed by the server.
As a preferred embodiment, the step S1 (positioning information acquisition) provided in the present invention specifically includes the following steps: referring to fig. 2, fig. 2 is a flow chart of positioning information acquisition provided by the present invention;
s11: starting a mobile phone APP, collecting positioning information, connecting a map interface, and collecting the longitude and latitude of the mobile phone;
s12: sending the longitude and latitude information to a server at the speed of 30s once, and judging whether the sent longitude and latitude information is unchanged beyond 20 nim; if the mobile phone is determined not to be moved, step S13 is performed:
s13: and segmenting the time and the position of the movement and the non-movement through the mobile phone, sending the recorded time and the recorded position to the server, and completing the segmented acquisition of the positioning information.
The positioning information acquisition uses a Baidu area to acquire the corresponding longitude and latitude, judges whether the corresponding longitude and latitude has a stay behavior, if the corresponding longitude and latitude stays for more than 20 minutes, judges that the corresponding longitude and latitude is inactive, divides a related path into an active path and an inactive path, and calculates related time and period according to exposure parameters and related parameters.
If the latitude and longitude information is failed to be sent in step S12, the relevant timestamp is added to the time when the communication is possible.
And when the longitude and latitude coordinates are smaller than a certain variation range, starting a timer, determining that the mobile terminal is not moved after 20 minutes, carrying out time segmentation on the mobile terminal and the non-mobile terminal, and recording the initial coordinates and the initial time for path planning and path analysis.
As a preferred embodiment, step S2 (path analysis and path planning) provided in the present invention specifically includes the following steps: referring to fig. 3, fig. 3 is a flow chart of path analysis and path planning provided by the present invention;
s21: according to the positioning information segment table obtained in the step S13; configuring a behavior corresponding to the positioning information segment; the behaviors are mainly traffic behaviors, namely stopping, sitting, riding, walking and the like;
s22: acquiring behaviors and segments according to the step S21, and performing path segmentation and time calculation by using a path planning function of a map;
s23: and matching the path segments to the corresponding monitoring stations according to the monitoring station segment models to finally obtain the exposure time of each monitoring station, finishing the calculation of the exposure time, and outputting an exposure time table, wherein the period comprises station information and station exposure time so as to calculate the related exposure level intake value.
As a preferred embodiment, step S3 (site monitoring and concentration matching calculation) provided in the present invention specifically includes the following steps: referring to fig. 4, fig. 4 is a flow chart of exposure concentration and monitoring station matching provided by the present invention;
s31: positioning longitude and latitude by adopting a mobile phone map, detecting whether a monitoring station exists within 5km of the periphery, and if so, directly adopting the exposure concentration of the station of the monitoring station; if not, go to step S32;
s32: and reading the longitude and latitude, reversely inquiring the regional information of the mobile phone, inquiring 3 monitoring stations closest to the mobile phone, calculating the center matching concentration according to a concentration diffusion formula, and finishing the acquisition of the exposure concentration by taking the center matching concentration as the existing exposure concentration.
The concentration diffusion formula in the invention is (1-u-v) P1+ u P2+ v P3(1)
Wherein P is the central matching concentration, P1, P2 and P3 are respectively the exposure concentrations of three monitoring stations, u and v are respectively the weight contributions of the monitoring stations to acquisition points, wherein u is more than or equal to 0, v is more than or equal to 0, u + v is less than or equal to 1, and (1-u-v) is set as the weight of P1 to P, u is the weight of P2 to P, and v is the weight of P3 to P;
the solving mode of u and v is as follows:
defining 3 monitoring stations nearest to the mobile phone to form a triangular area, wherein the location of the mobile phone is the concentration to be monitored, the location of the mobile phone is located in the triangular area, the longitude and latitude coordinates of the mobile phone are P ', the longitude and latitude coordinates of the three monitoring stations are P1', P2 'and P3', respectively,
solving u and v according to the following linear equation of two-dimentional
P’·x＝(1-u-v)*P1’·x+u*P2’·x+v*P3’·x
P’·y＝(1-u-v)*P1’·y+u*P2’·y+v*P3’·y
As a preferred embodiment, step S4 (exposure parameter configuration and distribution) provided in the present invention specifically includes the following steps: referring to fig. 5, fig. 5 is a flow chart illustrating configuration and distribution of exposure parameters according to the present invention;
s41: sequentially configuring behavior types, respiratory volumes and crowd characteristics;
s42: and (4) performing path planning analysis matching, monitoring station matching and exposure time segmentation calculation and matching in sequence according to the behavior type, the respiration volume and the crowd characteristics in the step S41 until the exposure parameter configuration is completed.
Wherein, the exposure parameters in the invention are related scientific research corresponding analysis parameters, different graduations are carried out aiming at behaviors, respiration volume and population characteristics, and the intake volume and the detailed information are finally confirmed to be shown in tables 1 and 2;
as a preferred embodiment, step S5 (exposure level calculation) exposure level calculation provided in the present invention is a correlation calculation section of the present invention for the relevant discharge intake amount of the human body, and the corresponding exposure level is cumulatively calculated by the product of the exposure parameter, the exposure time, and the exposure concentration;
referring to fig. 6, fig. 6 is a flowchart of exposure level calculation provided by the present invention; the method specifically comprises the following steps:
s51: confirming the exposure time according to step S2;
s52: confirming the exposure concentration according to step S3;
s53: confirming the exposure parameters according to step S4;
s54: multiplying the exposure time in the step S51, the exposure concentration in the step S52, and the exposure parameter in the step S53, and then accumulating to calculate the exposure level;
s55: and checking whether the monitoring station or the concentration information is missing or not, and if the monitoring station or the concentration information is complete, generating an exposure level calculation result.
Wherein, the exposure parameters mentioned in step S53 of the present invention refer to behavior type, respiration rate, and crowd characteristics, so as to obtain the respiration rate (L/min) of the crowd in different activity states according to the behavior type, the respiration rate, and the crowd characteristics;
the Time-activity factors Related to Air Exposure (Time-activity factors Related to Air Exposure) provided by the invention comprise indoor and outdoor activity Time, vehicle Time and the like. Under the influence of cultural level, economic level, gender, year , season, hobbies and interests and personal habits, it is difficult to obtain accurate activity information in real time, and the survey of adult activity pattern parameters is generally obtained by questionnaire survey. A commonly used questionnaire is a 24-hour retrospective log method that requires the interviewee to record the time spent in all activities and locations the day before.
Outdoor activity time refers to time other than the time spent in a closed indoor space such as at home, work units, malls, entertainment venues, and the like, and includes outdoor fitness (e.g., walking, running, sports, etc.), leisure (e.g., shopping in a park, etc.), or production, life activities, etc. in business, outdoor work, etc.
The indoor activity time refers to the time of staying in a closed indoor space such as a home, a work unit, a market, an entertainment place and the like.
The traffic travel mode is a traffic mode adopted by traffic travel, and mainly comprises walking, bicycles, electric bicycles, motorcycles, cars, buses, rail transit, water traffic and other transportation means.
Travel time refers to the cumulative time of day that various vehicles are used.
The calculation of the exposure level (also referred to as the total daily exposure dose of the pollutants in the breath-exposed air) in the present invention is specifically as follows:
Eij＝CAi×tAj×IR×10-6+pi×CAi×tIj×IR×10-6(2)
in the formula: i-certain atmospheric pollutants, including particulate matter and gaseous pollutants, etc.;
j-a panelist;
Eij-a certain (i) total exposure (mg) of atmospheric pollutants of a certain investigational object (j);
CAi-monitored concentration of outdoor atmospheric contaminants (i) (μ g/m 3);
tAj-daily outdoor exposure time (min) for a certain surveyor (j);
picontaminant (i) permeability coefficient inside and outside the room (the ratio of contaminants permeating from the outside into the room);
tIj-indoor exposure time (min) of a certain surveyor (j);
IR-respiratory volume (L/min) of the population at different states of activity.
The recommended short-term respiration rate (IR, short-term respiration rate/(L/min)) for different activity states of the population is shown in Table 1;
TABLE 1
| Small counter | For male | Woman | |
| Rest for taking a rest | 5.5 | 6.3 | 5.1 |
| Sitting position | 6.6 | 7.5 | 6.1 |
| Slight movement | 8.2 | 9.4 | 7.6 |
| Activity of middle physical strength | 21.9 | 25.1 | 20.3 |
| Gravity movement | 32.9 | 37.7 | 30.4 |
| Extremely heavy physical activity | 54.8 | 62.8 | 50.7 |
The permeability coefficients (pi) for the different scenarios are shown in table 2;
TABLE 2
Short-term respiratory volumes IR of the population under different activity states can be obtained according to Table 1, and permeability coefficients (pi) of different pollutants under different situations can be obtained according to Table 2.
As a preferred embodiment, the monitoring method provided in the present invention further includes rendering the exposure level result by the APP or the user webpage, as shown in fig. 7 to 9, and specifically includes the following steps:
s71: acquiring an exposure level form, and confirming the exposure time, the exposure concentration and the corresponding monitoring station of each segment;
s72: acquiring the concentration corresponding to the monitoring station or the corresponding calculated concentration, carrying out coordinate positioning on the monitoring station and filling a map with the corresponding concentration thermodynamic diagram by using the concentration;
s73: and analyzing the driving path of the user, filling color according to the concentration of the driving path, performing path gradual change correction, and finally generating an exposure level change graph.
As a preferred embodiment, the APP or user webpage end provided by the invention can also be used for consulting the historical exposure level intake condition of the ordinary user and providing personal exposure level trend analysis for the ordinary user.
As shown in fig. 10-13. On the other hand, the invention also provides an atmospheric environment health monitoring system, which comprises a server side and a client side;
the server comprises a server data acquisition unit, an environmental motion monitoring model, a report, an interface and user management; the data acquisition unit comprises environmental data acquisition, motion data acquisition and longitude and latitude data acquisition; the environment motion monitoring model comprises an environment protection environment detection model, a motion detection model, a concentration parameter longitude and latitude calculation model, a motion information model parameter configuration, a motion information model weight configuration, a default motion information model configuration and a model verification; the report forms comprise a map rendering report form, a user motion analysis report form and an environment detection matching report form; the interface comprises an environment data crawling interface, a longitude and latitude data map acquiring interface, a user information interface and a report interface;
the user management comprises report user management, administrator management and user management; the client comprises an APP machine or a related webpage; the APP machine or the related webpage comprises a client data acquisition unit, a user movement behavior report and a user health monitoring report; the client data acquisition unit comprises a map data acquisition unit, a motion data acquisition unit, a user data acquisition unit and a data acquisition and pushing unit; the user motion behavior report comprises user track planning, user motion behavior segmentation and user motion configuration information configuration; the user health monitoring report comprises a user current monitoring report, a user historical monitoring report and a user summarizing, analyzing and monitoring report.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. An atmospheric environment exercise health monitoring method is characterized by comprising the following steps:
s1: the server side continuously acquires the acquired positioning information; if the acquisition is not completed, the acquisition is continued until the completion, and then the step S2 is performed;
s2: analyzing the track information and time according to the positioning information acquired in the step S1; if the analysis is not completed, continuing the analysis until the analysis is completed, and then performing step S3;
s3: performing monitoring station and concentration matching calculation according to the track information and time in the step S2 until the calculation is completed, performing exposure time attribution calculation, and performing a step S4 when the exposure time attribution calculation is completed;
s4: configuring the exposure parameters until the exposure parameters are configured, and performing step S5;
s5: calculating the exposure level until the exposure level calculation is completed, proceeding to step S6;
s6: and generating an exposure level report and completing the exposure level analysis.
2. The atmospheric environmental exercise health monitoring method according to claim 1, wherein the step S1 specifically includes the steps of:
s11: starting a mobile phone APP, collecting positioning information, connecting a map interface, and collecting the longitude and latitude of the mobile phone;
s12: sending the longitude and latitude information to a server at the frequency of 30s once, and judging whether the sent longitude and latitude information is unchanged for more than 20 min; if the mobile phone is determined not to be moved, step S13 is performed:
s13: and segmenting the time and the position of the movement and the non-movement through the mobile phone, sending the recorded time and the recorded position to the server, and completing the segmented acquisition of the positioning information.
3. The atmospheric environmental exercise health monitoring method according to claim 2, wherein the step S2 specifically includes the steps of:
s21: according to the positioning information segment table obtained in the step S13; configuring a behavior corresponding to the positioning information segment;
s22: acquiring behaviors and segments according to the step S21, and performing path segmentation and time calculation by using a path planning function of a map;
s23: and matching the path segments to the corresponding monitoring stations according to the monitoring station segment models to finally obtain the exposure time of each monitoring station, and finishing the calculation of the exposure time.
4. The atmospheric environmental exercise health monitoring method according to claim 3, wherein the step S3 specifically includes the steps of:
s31: positioning longitude and latitude by adopting a mobile phone map, detecting whether a monitoring station exists within 5km of the periphery, and if so, directly adopting the exposure concentration of the station of the monitoring station; if not, go to step S32;
s32: reading longitude and latitude, reversely inquiring the regional information of the mobile phone, inquiring 3 monitoring stations nearest to the mobile phone, calculating the center matching concentration according to the concentration diffusion formula (1), and finishing the acquisition of the exposure concentration by taking the center matching concentration as the existing exposure concentration;
P＝(1-u-v)*P1+u*P2+v*P3 (1)
wherein P is the central matching concentration, P1, P2 and P3 are the exposure concentrations of three monitoring stations respectively, and u and v are the weight contributions of the monitoring stations to the acquisition points respectively, wherein u is more than or equal to 0, v is more than or equal to 0, and u + v is less than or equal to 1.
5. The atmospheric environmental exercise health monitoring method according to claim 4, wherein the step S4 specifically includes the steps of:
s41: sequentially configuring behavior types, respiratory volumes and crowd characteristics;
s42: and (4) performing path planning analysis matching, monitoring station matching and exposure time segmentation calculation and matching in sequence according to the behavior type, the respiration volume and the crowd characteristics in the step S41 until the exposure parameter configuration is completed.
6. The atmospheric environmental exercise health monitoring method according to claim 5, wherein the step S5 specifically includes the steps of:
s51: confirming the exposure time according to step S2;
s52: confirming the exposure concentration according to step S3;
s53: confirming the exposure parameters according to step S4;
s54: multiplying the exposure time in the step S51, the exposure concentration in the step S52, and the exposure parameter in the step S53, and then accumulating to calculate the exposure level;
s55: and checking whether the monitoring station or the concentration information is missing or not, if so, continuing checking the monitoring station or the concentration information, and if so, generating an exposure level calculation result.
7. The method for monitoring the exercise health of the atmospheric environment according to claim 1, wherein the exposure level E in the step S54ijDetermined according to equation (2);
Eij＝CAi×tAj×IR×10-6+pi×CAi×tIj×IR×10-6(2)
in the formula: i-certain atmospheric pollutants, including particulate matter and gaseous pollutants, etc.;
j-a panelist;
Eij-a certain (i) total exposure (mg) of atmospheric pollutants of a certain investigational object (j);
CAi-monitored concentration of outdoor atmospheric contaminants (i) (. mu.g/m)3)；
tAj-daily outdoor exposure time (min) for a certain surveyor (j);
picontaminant (i) permeability coefficient inside and outside the room (the ratio of contaminants permeating from the outside into the room);
tIj-indoor exposure time (min) of a certain surveyor (j);
IR-respiratory volume (L/min) of the population at different states of activity.
8. The atmospheric environmental exercise health monitoring method according to claim 1, further comprising rendering the exposure level result by an APP or a user webpage, specifically comprising the steps of:
s71: acquiring an exposure level form, and confirming the exposure time, the exposure concentration and the corresponding monitoring station of each segment;
s72: acquiring the concentration corresponding to the monitoring station or the corresponding calculated concentration, carrying out coordinate positioning on the monitoring station and filling a map with the corresponding concentration thermodynamic diagram by using the concentration;
s73: and analyzing the driving path of the user, filling color according to the concentration of the driving path, performing path gradual change correction, and finally generating an exposure level change graph.
9. The atmospheric exercise health monitoring method of claim 8, wherein the APP or user webpage can also review historical exposure level intake of the general user and provide personal exposure level trend analysis for the general user.
10. A monitoring system for executing the atmospheric environmental exercise health monitoring method according to any one of claims 1 to 9, comprising a server and a client; it is characterized in that the preparation method is characterized in that,
the server comprises a server data acquisition unit, an environmental motion monitoring model, a report, an interface and user management; the data acquisition unit comprises environmental data acquisition, motion data acquisition and longitude and latitude data acquisition; the environment motion monitoring model comprises an environment protection environment detection model, a motion detection model, a concentration parameter longitude and latitude calculation model, a motion information model parameter configuration, a motion information model weight configuration, a default motion information model configuration and a model verification; the report forms comprise a map rendering report form, a user motion analysis report form and an environment detection matching report form; the interface comprises an environment data crawling interface, a longitude and latitude data map acquiring interface, a user information interface and a report interface;
the user management comprises report user management, administrator management and user management; the client comprises an APP machine or a related webpage; the APP machine or the related webpage comprises a client data acquisition unit, a user movement behavior report and a user health monitoring report; the client data acquisition unit comprises a map data acquisition unit, a motion data acquisition unit, a user data acquisition unit and a data acquisition and pushing unit; the user motion behavior report comprises user track planning, user motion behavior segmentation and user motion configuration information configuration; the user health monitoring report comprises a user current monitoring report, a user historical monitoring report and a user summarizing, analyzing and monitoring report.
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