CN117330714B - Regional environment monitoring and early warning system and method based on big data - Google Patents
Regional environment monitoring and early warning system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of environmental monitoring, in particular to a regional environmental monitoring and early warning system and method based on big data, comprising the following steps: the system comprises a monitoring information acquisition module, a database, an environment monitoring module, a collaborative monitoring judging module and a collaborative monitoring planning module, wherein the monitoring information acquisition module is used for acquiring regional environment monitoring site information and information of unmanned aerial vehicles to be collaborative for monitoring regional environments of the collaborative monitoring sites, the database is used for storing all received data, the environment monitoring module is used for carrying out regional environment monitoring by utilizing the monitoring sites, the collaborative monitoring judging module is used for judging whether unmanned aerial vehicles are needed to carry out atmospheric environment monitoring, the collaborative monitoring planning module is used for planning the number of unmanned aerial vehicles to be collaborative monitored when judging that the unmanned aerial vehicles are needed, the unmanned aerial vehicles are used for carrying out atmospheric environment collaborative monitoring, the problems of insufficient coverage of a monitoring range and inaccurate monitoring data are solved, and unnecessary monitoring cost is reduced while monitoring efficiency is improved.
Description
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to a regional environmental monitoring and early warning system and method based on big data.
Background
The atmospheric environment monitoring is a measuring process for observing and analyzing the concentration of pollutants in the atmospheric environment and for measuring the environmental influence, in the atmospheric environment monitoring, the reasonable arrangement of the positions and the number of sampling points is one of important procedures for completing the monitoring purpose and guaranteeing the representativeness of data, and the atmospheric environment monitoring is carried out on a certain area by arranging a proper monitoring station, so that the environmental monitoring of the area can be better facilitated;
however, existing environmental monitoring methods still have some drawbacks: in the prior art, atmospheric environment monitoring is carried out on an area by utilizing a fixed monitoring station, the problem that the pollution exceeds standard in a local area but is not monitored by any monitoring station possibly caused by insufficient coverage of a monitoring range is likely to occur, so that the accuracy of monitoring data is influenced, and even if the problem that the pollution exceeds standard in an uncovered local area is checked later, the environmental monitoring cannot be continued on the polluted area later because the monitoring station is fixed, and the comprehensiveness and accuracy of the environmental monitoring data are not guaranteed.
Therefore, a regional environment monitoring and early warning system and method based on big data are needed to solve the above problems.
Disclosure of Invention
The invention aims to provide a regional environment monitoring and early warning system and method based on big data, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a big data based regional environmental monitoring and early warning system, the system comprising: the system comprises a monitoring information acquisition module, a database, an environment monitoring module, a collaborative monitoring judgment module and a collaborative monitoring planning module;
the output end of the monitoring information acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the environment monitoring module and the collaborative monitoring planning module, the output end of the environment monitoring module is connected with the input end of the collaborative monitoring judgment module, and the output end of the collaborative monitoring judgment module is connected with the input end of the collaborative monitoring planning module;
collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for monitoring regional environment by the monitoring information collecting module, and transmitting all collected data to the database;
storing all received data by the database;
the environment monitoring module is used for monitoring regional environment by using a monitoring site, and early warning is carried out when the regional pollution which is not covered by the monitoring range of the monitoring site is monitored to exceed the standard;
judging whether the unmanned aerial vehicle collaborative monitoring station is required to monitor the atmospheric environment or not through the collaborative monitoring judging module: if necessary, carrying out environment monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle;
and when the cooperation of the unmanned aerial vehicles is judged to be needed by the cooperation monitoring planning module, planning the number of the unmanned aerial vehicles which are monitored cooperatively.
Further, the monitoring information acquisition module comprises a site information acquisition unit, an equipment information acquisition unit and a historical monitoring data acquisition unit;
the output ends of the site information acquisition unit, the equipment information acquisition unit and the historical monitoring data acquisition unit are connected with the input end of the database;
the station information acquisition unit is used for acquiring all monitoring station position information for monitoring the atmospheric environment of the fixed area and monitoring range information of the monitoring stations;
the equipment information acquisition unit is used for acquiring the endurance time information of the unmanned aerial vehicle to be cooperated, which is used for monitoring the atmosphere environment of the fixed area by the cooperated monitoring station;
the history monitoring data acquisition unit is used for acquiring the number of unmanned aerial vehicles, the area of a monitoring area and the endurance time information of the unmanned aerial vehicles which are monitored in the past in one-time manner;
the one-time completion of atmospheric environmental monitoring means that the unmanned aerial vehicle can complete the atmospheric environmental monitoring work of the area to be monitored under the condition of no charging.
Further, the environment monitoring module comprises an atmospheric environment monitoring unit, a monitoring range analysis unit and a pollution exceeding early warning unit;
the output ends of the atmospheric environment monitoring unit and the database are connected with the input end of the monitoring range analysis unit, and the output end of the monitoring range analysis unit is connected with the input end of the pollution exceeding early warning unit;
the atmospheric environment monitoring unit is used for monitoring the atmospheric environment of the area by utilizing the monitoring station;
the monitoring range analysis unit is used for analyzing the monitoring range information of all monitoring stations in the corresponding area and confirming the area which is not covered by the monitoring range of the monitoring station;
the pollution exceeding early warning unit is used for transmitting atmospheric environment data monitored by the monitoring station to the monitoring terminal, checking the atmospheric pollution condition in the area, and sending an early warning signal to the collaborative monitoring judging module when the uncovered area pollution exceeding is checked.
Further, the collaborative monitoring judging module comprises a collaborative area screening unit and an unmanned aerial vehicle collaborative monitoring unit;
the input end of the collaborative area screening unit is connected with the output end of the pollution exceeding early warning unit, and the output end of the collaborative area screening unit is connected with the input end of the unmanned plane collaborative monitoring unit;
the collaborative area screening unit is used for judging that the unmanned aerial vehicle is required to perform collaborative monitoring if the early warning signal is received, screening out areas which are not covered by the monitoring range of the monitoring station, and analyzing the total area of the screened areas;
if the early warning signal is not received, judging that the unmanned aerial vehicle is not required to carry out cooperative monitoring;
the unmanned aerial vehicle collaborative monitoring unit is used for monitoring the atmospheric environment of the screened area by using the unmanned aerial vehicle;
controlling the unmanned aerial vehicle to a fixed height position above the screened area, scanning the area by the unmanned aerial vehicle, detecting by utilizing an automatic route planning function, detecting gas by utilizing a sensor, simultaneously opening a high-definition camera to record images, sending acquired detection data and image data to a monitoring terminal, and displaying information such as gas components, concentration and the like of the corresponding area by the monitoring terminal through visual software;
atmospheric environment monitoring is carried out through utilizing unmanned aerial vehicle to cooperate the mode of fixed monitoring website, and fixed monitoring website carries out environmental monitoring to the region in its monitoring range, and unmanned aerial vehicle carries out environmental monitoring to the region that monitoring range does not cover, is favorable to guaranteeing accuracy and the comprehensiveness of final monitoring result.
Further, the collaborative monitoring planning module comprises a historical monitoring data calling unit, an allocation model building unit and an equipment quantity planning unit;
the input end of the history monitoring data calling unit is connected with the output ends of the unmanned aerial vehicle collaborative monitoring unit and the database, the output end of the history monitoring data calling unit is connected with the input end of the distribution model building unit, and the output end of the distribution model building unit is connected with the input end of the equipment quantity planning unit;
the history monitoring data calling unit is used for calling and analyzing the number of unmanned aerial vehicles, the area of a monitoring area and the duration information of the unmanned aerial vehicles which are monitored in the past in one time to the distribution model building unit;
the distribution model building unit is used for building a device quantity distribution model according to the received data;
the equipment quantity planning unit is used for substituting the current duration of the unmanned aerial vehicle to be cooperated with and the total area of the screened area into the equipment quantity distribution model to plan the number of unmanned aerial vehicles for atmospheric environment monitoring corresponding to the screened area.
A regional environment monitoring and early warning method based on big data comprises the following steps:
s1: collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for monitoring regional environment by the cooperated monitoring site;
s2: monitoring regional environment by using a monitoring station, and early warning when the pollution of the region which is not covered by the monitoring range of the monitoring station exceeds the standard is monitored;
s3: judging whether the unmanned aerial vehicle is required to cooperate with a monitoring station to monitor the atmospheric environment or not: if necessary, carrying out environment monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle; if not, executing the step S2;
s4: and planning the number of unmanned aerial vehicles for collaborative monitoring when judging that unmanned aerial vehicles are needed to cooperate.
Further, f monitoring sites are collected in a random fixed area, the total area of the corresponding fixed area is Z, the position information of the f monitoring sites is collected, and the monitoring range of each monitoring site is obtained: the coverage area of a circular area with the monitoring station as the center and the radius r is collected and used for cooperation at presentThe maximum endurance time of the unmanned aerial vehicles to be cooperated with the atmospheric environment of the monitoring station monitoring corresponding to the fixed area is t, the maximum endurance time of all unmanned aerial vehicles to be cooperated is the same, and the number set of the unmanned aerial vehicles which can finish atmospheric environment monitoring once for k times is acquired as B= { B 1 ，B 2 ，…，B k The area of each monitored region is s= { s } 1 ，s 2 ，…，s k The maximum endurance time set of the unmanned aerial vehicle used each time is T= { T 1 ，T 2 ，…，T k The maximum endurance time of all unmanned aerial vehicles used each time is the same.
Further, after atmospheric environment data monitored by the monitoring station are transmitted to the monitoring terminal, the atmospheric pollution condition in the corresponding fixed area is checked, and when the area pollution exceeding standard which is not covered by the monitoring range of the monitoring station is checked, an early warning signal is sent.
Further, if the early warning signal is received, judging that the unmanned aerial vehicle is required to cooperate with the monitoring station to perform atmospheric monitoring, performing environmental monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle, screening out the area which is not covered by the monitoring range of the monitoring station, and according to a formula S ’ =Z-f*(π*r 2 ) Calculating to obtain the screened area S ’ ；
The unmanned aerial vehicle is reused for carrying out environment monitoring on the uncovered area after receiving the early warning signal, because the fixed monitoring site is provided with a certain rationality, the monitored data has a certain representativeness, when the pollution exceeds the standard in the area which is not in the monitoring range, the unmanned aerial vehicle is not required to carry out cooperative monitoring, and when the pollution exceeds the standard in the area which is not in the monitoring range, the unmanned aerial vehicle is reused for carrying out environment monitoring on the area, so that the effectiveness and the meaning of the unmanned aerial vehicle cooperative monitoring are improved.
Further, a device quantity distribution model is established: z=λ 0 +λ 1 *x+λ 2 * y, wherein x and y represent independent variables in the device quantity distribution model, z represents the dependent variables in the device quantity distribution model, λ 0 、λ 1 And lambda (lambda) 2 Representing partial regression coefficients, respectivelySolving lambda 1 、λ 2 And lambda (lambda) 0 Obtaining a final equipment quantity distribution model:
λ 1 =[∑ k i=1 (B i ×T i )∑ k i=1 (s i ) 2 -∑ k i=1 (B i ×s i )∑ k i=1 (T i ×s i )]
/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]；
λ 2 =[∑ k i=1 (B i ×s i )∑ k i=1 (T i ) 2 -∑ k i=1 (B i ×T i )∑ k i=1 (T i ×s i )]
/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]；
λ 0 =(∑ k i=1 B i )/k-λ 1 ×[(∑ k i=1 T i )/k]-λ 2 ×[(∑ k i=1 s i )/k]；
wherein B is i The number s of unmanned aerial vehicles capable of completing atmospheric environment monitoring at one time in the past at the ith time is represented i Represents the area of the region monitored at the ith time, T i Representing the maximum endurance time of the unmanned aerial vehicle used for the ith time, and combining t and S ’ Substituting into the equipment quantity distribution model, let x=t, y=s ’ Obtaining lambda as the number of unmanned aerial vehicles needed for monitoring the currently screened area 0 +λ 1 *t+λ 2 *S ’ For lambda 0 +λ 1 *t+λ 2 *S ’ Rounding to allocate lambda 0 +λ 1 *t+λ 2 *S ’ The individual unmanned aerial vehicle monitors the atmospheric environment of the screened area;
when utilizing unmanned aerial vehicle to carry out collaborative monitoring, because unmanned aerial vehicle's flight time is shorter, the scope of once monitoring is limited, gather and analyze unmanned aerial vehicle duration, unmanned aerial vehicle quantity and the area data that corresponds the monitoring area that can once only accomplish regional environment monitoring work in the past through big data technique, establish equipment quantity distribution model according to historical data, carry out atmospheric environment monitoring for the unmanned aerial vehicle of the regional distribution suitable quantity of current screening, be favorable to helping to once only accomplish the environmental monitoring of corresponding region, unnecessary monitoring cost has been reduced when improving monitoring efficiency.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, atmospheric environment monitoring is carried out by utilizing the unmanned aerial vehicle to cooperate with the fixed monitoring station, the fixed monitoring station carries out environment monitoring on the area within the monitoring range, and the unmanned aerial vehicle carries out environment monitoring on the area which is not covered by the monitoring range, so that the accuracy and the comprehensiveness of a final monitoring result are ensured; when pollution exceeds standard in an area which is not in the monitoring range of the monitoring site, the unmanned aerial vehicle is utilized to monitor the environment of the area, so that the effectiveness and the significance of collaborative monitoring of the unmanned aerial vehicle are improved; unmanned aerial vehicle duration, unmanned aerial vehicle quantity and the area data of corresponding monitoring area that can once only accomplish regional environmental monitoring work in the past are gathered and analyzed through big data technology, equipment quantity distribution model is established according to historical data, and the unmanned aerial vehicle of suitable quantity is carried out atmospheric environment monitoring for the regional distribution of current screening, and the environmental monitoring of corresponding region is accomplished once only to help, has reduced unnecessary monitoring cost when improving monitoring efficiency.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of an area environment monitoring and early warning system based on big data;
fig. 2 is a flow chart of an area environment monitoring and early warning method based on big data.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The invention is further described below with reference to fig. 1-2 and the specific embodiments.
Example 1: as shown in fig. 1, the present embodiment provides a regional environment monitoring and early warning system based on big data, the system includes: the system comprises a monitoring information acquisition module, a database, an environment monitoring module, a collaborative monitoring judgment module and a collaborative monitoring planning module;
the output end of the monitoring information acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the environment monitoring module and the collaborative monitoring planning module, the output end of the environment monitoring module is connected with the input end of the collaborative monitoring judgment module, and the output end of the collaborative monitoring judgment module is connected with the input end of the collaborative monitoring planning module;
collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for monitoring regional environment by a monitoring information collecting module, and transmitting all collected data to a database;
storing all received data by a database;
the environmental monitoring module is used for monitoring regional environment by using the monitoring site, and early warning is carried out when the regional pollution which is not covered by the monitoring range of the monitoring site exceeds the standard is monitored;
judging whether the unmanned aerial vehicle collaborative monitoring station is required to monitor the atmospheric environment or not through the collaborative monitoring judging module: if necessary, carrying out environment monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle;
and when the unmanned aerial vehicle coordination is judged to be needed by the coordination monitoring planning module, planning the number of the unmanned aerial vehicles which are monitored in a coordination mode.
The monitoring information acquisition module comprises a site information acquisition unit, an equipment information acquisition unit and a historical monitoring data acquisition unit;
the output ends of the site information acquisition unit, the equipment information acquisition unit and the history monitoring data acquisition unit are connected with the input end of the database;
the station information acquisition unit is used for acquiring all monitoring station position information for monitoring the atmospheric environment of the fixed area and monitoring range information of the monitoring stations;
the equipment information acquisition unit is used for acquiring the endurance time information of the unmanned aerial vehicle to be cooperated, which is used for monitoring the atmospheric environment of the fixed area by the cooperated monitoring station;
the history monitoring data acquisition unit is used for acquiring the number of unmanned aerial vehicles, the area of a monitoring area and the endurance time information of the unmanned aerial vehicles which are monitored in the past in one time;
the one-time completion of atmospheric environmental monitoring means that the unmanned aerial vehicle can complete the atmospheric environmental monitoring work of the area to be monitored under the condition of no charging.
The environment monitoring module comprises an atmospheric environment monitoring unit, a monitoring range analysis unit and a pollution exceeding early warning unit;
the output ends of the atmospheric environment monitoring unit and the database are connected with the input end of the monitoring range analysis unit, and the output end of the monitoring range analysis unit is connected with the input end of the pollution exceeding early warning unit;
the atmospheric environment monitoring unit is used for monitoring the atmospheric environment of the area by utilizing the monitoring station;
the monitoring range analysis unit is used for analyzing the monitoring range information of all the monitoring stations in the corresponding area and confirming the area which is not covered by the monitoring range of the monitoring station;
the pollution exceeding early warning unit is used for transmitting atmospheric environment data monitored by the monitoring station to the monitoring terminal, checking the atmospheric pollution condition in the area, and sending an early warning signal to the collaborative monitoring judging module when the uncovered area pollution exceeding is checked.
The collaborative monitoring judging module comprises a collaborative region screening unit and an unmanned aerial vehicle collaborative monitoring unit;
the input end of the collaborative area screening unit is connected with the output end of the pollution exceeding early warning unit, and the output end of the collaborative area screening unit is connected with the input end of the unmanned plane collaborative monitoring unit;
the cooperative area screening unit is used for judging that the unmanned aerial vehicle is required to perform cooperative monitoring if the early warning signal is received, screening out areas which are not covered by the monitoring range of the monitoring station, and analyzing the total area of the screened out areas;
if the early warning signal is not received, judging that the unmanned aerial vehicle is not required to carry out cooperative monitoring;
the unmanned aerial vehicle collaborative monitoring unit is used for monitoring the atmospheric environment of the screened area by using the unmanned aerial vehicle;
controlling unmanned aerial vehicle to the fixed high department in regional top of screening, unmanned aerial vehicle scans the region, utilizes automatic planning route function to detect, opens high definition camera and carries out image record when utilizing the sensor to carry out gas detection, sends detection data and image data that will acquire to monitor terminal, and monitor terminal shows information such as gas composition, the concentration of corresponding region through visual software.
The collaborative monitoring planning module comprises a historical monitoring data calling unit, an allocation model building unit and an equipment number planning unit;
the input end of the history monitoring data calling unit is connected with the output ends of the unmanned aerial vehicle collaborative monitoring unit and the database, the output end of the history monitoring data calling unit is connected with the input end of the distribution model building unit, and the output end of the distribution model building unit is connected with the input end of the equipment quantity planning unit;
the historical monitoring data calling unit is used for calling and analyzing the number of unmanned aerial vehicles, the area of a monitoring area and the endurance time information of the unmanned aerial vehicles which are monitored in the past in one time to the distribution model building unit;
the distribution model building unit is used for building a device quantity distribution model according to the received data;
the equipment number planning unit is used for substituting the duration of the current unmanned aerial vehicle to be cooperated and the total area of the screened area into the equipment number distribution model to plan the number of unmanned aerial vehicles for atmospheric environment monitoring of the corresponding screened area.
Example 2: as shown in fig. 2, the present embodiment provides a regional environment monitoring and early warning method based on big data, which is implemented based on the monitoring and early warning system in the embodiment, and specifically includes the following steps:
s1: collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for cooperating with the monitoring site to monitor regional environment, collecting f monitoring sites in a random fixed region, collecting the position information of the f monitoring sites, and obtaining the monitoring range of each monitoring site, wherein the total area of the corresponding fixed region is Z: the method comprises the steps that a monitoring station is used as a circle center, coverage of a circular area with radius r is covered, the maximum duration of unmanned aerial vehicles to be cooperated for monitoring the atmospheric environment of a corresponding fixed area by the current cooperative monitoring station is t, the maximum duration of all unmanned aerial vehicles to be cooperated is the same, and the number set of unmanned aerial vehicles capable of completing atmospheric environment monitoring once for k times in the past is B= { B 1 ，B 2 ，…，B k The area of each monitored region is s= { s } 1 ，s 2 ，…，s k The maximum endurance time set of the unmanned aerial vehicle used each time is T= { T 1 ，T 2 ，…，T k The maximum endurance time of all unmanned aerial vehicles used each time is the same;
for example: the total area of the corresponding fixed areas is Z=1.4, and the unit is: km 2 The method comprises the steps of collecting position information of 3 monitoring stations, and obtaining the monitoring range of each monitoring station as follows: the coverage area of a circular area with the monitoring station as a circle center and the radius r=0.3 is as follows: km, the maximum endurance time of the unmanned aerial vehicle to be cooperated for monitoring the atmosphere environment of the corresponding fixed area by the current cooperative monitoring station is t=0.8, and the unit is: the number of unmanned aerial vehicles which can finish atmospheric environment monitoring for 3 times in the past is collected as B= { B after being collected for hours 1 ，B 2 ，B 3 The area set of each monitored area is s= { s = {3,6,4} 1 ，s 2 ，s 3 Each time the maximum endurance of the unmanned aerial vehicle used is = {1.05,2.50,1.43}The set is t= { T 1 ，T 2 ，T 3 }={0.60，0.58，0.62}；
S2: the method comprises the steps of utilizing a monitoring station to monitor regional environment, carrying out early warning when monitoring that the regional pollution which is not covered by the monitoring range of the monitoring station exceeds the standard, transmitting atmospheric environment data monitored by the monitoring station to a monitoring terminal, checking the atmospheric pollution condition in a corresponding fixed region, and sending an early warning signal when checking that the regional pollution which is not covered by the monitoring range of the monitoring station exceeds the standard;
s3: judging whether the unmanned aerial vehicle is required to cooperate with a monitoring station to monitor the atmospheric environment or not: if the early warning signal is received, judging that the unmanned aerial vehicle is required to cooperate with the monitoring station to perform atmospheric monitoring, performing environmental monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle, screening out the area which is not covered by the monitoring range of the monitoring station, and according to a formula S ’ =Z-f*(π*r 2 ) Calculating to obtain the screened area S ’ Obtaining S ’ =0.55, unit is: km 2 The method comprises the steps of carrying out a first treatment on the surface of the If the early warning signal is not received, judging that the unmanned aerial vehicle is not required to cooperate with a monitoring station to perform atmosphere monitoring, and executing the step S2;
s4: planning the number of unmanned aerial vehicles to be monitored cooperatively when judging that unmanned aerial vehicles are required to cooperate, and establishing a device number distribution model: z=λ 0 +λ 1 *x+λ 2 * y, wherein x and y represent independent variables in the device quantity distribution model, z represents the dependent variables in the device quantity distribution model, λ 0 、λ 1 And lambda (lambda) 2 Representing partial regression coefficients, respectively solving lambda 1 、λ 2 And lambda (lambda) 0 Obtaining a final equipment quantity distribution model, wherein lambda 1 =[∑ k i=1 (B i ×T i )∑ k i=1 (s i ) 2 -∑ k i=1 (B i ×s i )∑ k i=1 (T i ×s i )]/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]≈1.56、λ 2 =[∑ k i=1 (B i ×s i )∑ k i=1 (T i ) 2 -∑ k i=1 (B i ×T i )∑ k i=1 (T i ×s i )]/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]≈2.05、λ 0 =(∑ k i=1 B i )/k-λ 1 ×[(∑ k i=1 T i )/k]-λ 2 ×[(∑ k i=1 s i )/k]Approximately-0.01, giving z=λ 0 +λ 1 *x+λ 2 *y=-0.01+1.56x+2.05y；
Wherein B is i The number s of unmanned aerial vehicles capable of completing atmospheric environment monitoring at one time in the past at the ith time is represented i Represents the area of the region monitored at the ith time, T i Representing the maximum endurance time of the unmanned aerial vehicle used for the ith time, and combining t and S ’ Substituting into the equipment quantity allocation model, let x=t=0.8, y=s ’ =0.55, resulting in a number λ of unmanned aerial vehicles needed to monitor the currently screened area 0 +λ 1 *t+λ 2 *S ’ And (2) distributing two unmanned aerial vehicles to monitor the atmospheric environment of the screened area.
Finally, it should be noted that: the foregoing is merely a preferred example of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A regional environment monitoring and early warning method based on big data is characterized in that: the method comprises the following steps:
s1: collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for monitoring regional environment by the cooperated monitoring site;
s2: monitoring regional environment by using a monitoring station, and early warning when the pollution of the region which is not covered by the monitoring range of the monitoring station exceeds the standard is monitored;
s3: judging whether the unmanned aerial vehicle is required to cooperate with a monitoring station to monitor the atmospheric environment or not: if necessary, carrying out environment monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle; if not, executing the step S2;
s4: planning the number of unmanned aerial vehicles to be cooperatively monitored when judging that unmanned aerial vehicles are required to be cooperated;
in step S1: f monitoring stations are collected in a random fixed area, the total area of the corresponding fixed area is Z, the position information of the f monitoring stations is collected, and the monitoring range of each monitoring station is obtained: the method comprises the steps that a monitoring station is used as a circle center, the coverage area of a circular area with the radius r is covered, the maximum endurance time of unmanned aerial vehicles to be cooperated for being used for being cooperated with the monitoring station to monitor the atmospheric environment of a corresponding fixed area is t, and the number set of unmanned aerial vehicles capable of completing atmospheric environment monitoring for k times in the past is B= { B 1 ，B 2 ，…，B k The area of each monitored region is s= { s } 1 ，s 2 ，…，s k The maximum endurance time set of the unmanned aerial vehicle used each time is T= { T 1 ，T 2 ，…，T k }；
In step S2: after atmospheric environment data monitored by the monitoring station are transmitted to the monitoring terminal, checking the atmospheric pollution condition in the corresponding fixed area, and sending an early warning signal when the area pollution which is not covered by the monitoring range of the monitoring station is checked to exceed the standard;
in step S3: if the early warning signal is received, judging that the unmanned aerial vehicle is required to cooperate with the monitoring station to perform atmospheric monitoring, performing environmental monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle, screening out the area which is not covered by the monitoring range of the monitoring station, and according to a formula S ’ =Z-f*(π*r 2 ) Calculating to obtain the screened area S ’ ；
In step S4: establishing a device quantity distribution model: z=λ 0 +λ 1 *x+λ 2 * y, wherein x and y represent independent variables in the device quantity distribution model, z represents the dependent variables in the device quantity distribution model, λ 0 、λ 1 And lambda (lambda) 2 Representing partial regression coefficients, respectively solving lambda 1 、λ 2 And lambda (lambda) 0 Obtaining a final equipment quantity distribution model:
λ 1 =[∑ k i=1 (B i ×T i )∑ k i=1 (s i ) 2 -∑ k i=1 (B i ×s i )∑ k i=1 (T i ×s i )]
/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]；
λ 2 =[∑ k i=1 (B i ×s i )∑ k i=1 (T i ) 2 -∑ k i=1 (B i ×T i )∑ k i=1 (T i ×s i )]
/[∑ k i=1 (T i ) 2 ∑ k i=1 (s i ) 2 -(∑ k i=1 (T i ×s i )) 2 ]；
λ 0 =(∑ k i=1 B i )/k-λ 1 ×[(∑ k i=1 T i )/k]-λ 2 ×[(∑ k i=1 s i )/k]；
wherein B is i The number s of unmanned aerial vehicles capable of completing atmospheric environment monitoring at one time in the past at the ith time is represented i Represents the area of the region monitored at the ith time, T i Representing the maximum endurance time of the unmanned aerial vehicle used for the ith time, and combining t and S ’ Substituting into the equipment quantity distribution model, let x=t, y=s ’ Obtaining the area to be monitored and screened currentlyThe number of unmanned aerial vehicles is lambda 0 +λ 1 *t+λ 2 *S ’ For lambda 0 +λ 1 *t+λ 2 *S ’ Rounding to allocate lambda 0 +λ 1 *t+λ 2 *S ’ The individual unmanned aerial vehicle monitors the atmospheric environment of the screened area.
2. The regional environment monitoring and early warning system based on big data is applied to the regional environment monitoring and early warning method based on big data as claimed in claim 1, and is characterized in that: the system comprises: the system comprises a monitoring information acquisition module, a database, an environment monitoring module, a collaborative monitoring judgment module and a collaborative monitoring planning module;
the output end of the monitoring information acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the environment monitoring module and the collaborative monitoring planning module, the output end of the environment monitoring module is connected with the input end of the collaborative monitoring judgment module, and the output end of the collaborative monitoring judgment module is connected with the input end of the collaborative monitoring planning module;
collecting regional environment monitoring site information and unmanned aerial vehicle information to be cooperated for monitoring regional environment by the monitoring information collecting module, and transmitting all collected data to the database;
storing all received data by the database;
the environment monitoring module is used for monitoring regional environment by using a monitoring site, and early warning is carried out when the regional pollution which is not covered by the monitoring range of the monitoring site is monitored to exceed the standard;
judging whether the unmanned aerial vehicle collaborative monitoring station is required to monitor the atmospheric environment or not through the collaborative monitoring judging module: if necessary, carrying out environment monitoring on the area which is not covered by the monitoring range of the monitoring station by using the unmanned aerial vehicle;
and when the cooperation of the unmanned aerial vehicles is judged to be needed by the cooperation monitoring planning module, planning the number of the unmanned aerial vehicles which are monitored cooperatively.
3. The big data based regional environmental monitoring and early warning system of claim 2, wherein: the monitoring information acquisition module comprises a site information acquisition unit, an equipment information acquisition unit and a historical monitoring data acquisition unit;
the output ends of the site information acquisition unit, the equipment information acquisition unit and the historical monitoring data acquisition unit are connected with the input end of the database;
the station information acquisition unit is used for acquiring all monitoring station position information for monitoring the atmospheric environment of the fixed area and monitoring range information of the monitoring stations;
the equipment information acquisition unit is used for acquiring the endurance time information of the unmanned aerial vehicle to be cooperated, which is used for monitoring the atmosphere environment of the fixed area by the cooperated monitoring station;
the history monitoring data acquisition unit is used for acquiring the number of unmanned aerial vehicles, the area of a monitoring area and the endurance time information of the unmanned aerial vehicles which are monitored in the past in one-time atmospheric environment.
4. The big data based regional environmental monitoring and early warning system of claim 2, wherein: the environment monitoring module comprises an atmospheric environment monitoring unit, a monitoring range analysis unit and a pollution exceeding early warning unit;
the output ends of the atmospheric environment monitoring unit and the database are connected with the input end of the monitoring range analysis unit, and the output end of the monitoring range analysis unit is connected with the input end of the pollution exceeding early warning unit;
the atmospheric environment monitoring unit is used for monitoring the atmospheric environment of the area by utilizing the monitoring station;
the monitoring range analysis unit is used for analyzing the monitoring range information of all monitoring stations in the corresponding area and confirming the area which is not covered by the monitoring range of the monitoring station;
the pollution exceeding early warning unit is used for transmitting atmospheric environment data monitored by the monitoring station to the monitoring terminal, checking the atmospheric pollution condition in the area, and sending an early warning signal to the collaborative monitoring judging module when the uncovered area pollution exceeding is checked.
5. The big data based regional environmental monitoring and early warning system according to claim 4, wherein: the collaborative monitoring judging module comprises a collaborative area screening unit and an unmanned aerial vehicle collaborative monitoring unit;
the input end of the collaborative area screening unit is connected with the output end of the pollution exceeding early warning unit, and the output end of the collaborative area screening unit is connected with the input end of the unmanned plane collaborative monitoring unit;
the collaborative area screening unit is used for judging that the unmanned aerial vehicle is required to perform collaborative monitoring if the early warning signal is received, screening out areas which are not covered by the monitoring range of the monitoring station, and analyzing the total area of the screened areas;
if the early warning signal is not received, judging that the unmanned aerial vehicle is not required to carry out cooperative monitoring;
the unmanned aerial vehicle collaborative monitoring unit is used for carrying out atmospheric environment monitoring on the screened area by utilizing the unmanned aerial vehicle.
6. The big data based regional environmental monitoring and early warning system according to claim 5, wherein: the collaborative monitoring planning module comprises a historical monitoring data calling unit, an allocation model building unit and an equipment number planning unit;
the input end of the history monitoring data calling unit is connected with the output ends of the unmanned aerial vehicle collaborative monitoring unit and the database, the output end of the history monitoring data calling unit is connected with the input end of the distribution model building unit, and the output end of the distribution model building unit is connected with the input end of the equipment quantity planning unit;
the history monitoring data calling unit is used for calling and analyzing the number of unmanned aerial vehicles, the area of a monitoring area and the duration information of the unmanned aerial vehicles which are monitored in the past in one time to the distribution model building unit;
the distribution model building unit is used for building a device quantity distribution model according to the received data;
the equipment quantity planning unit is used for substituting the current duration of the unmanned aerial vehicle to be cooperated with and the total area of the screened area into the equipment quantity distribution model to plan the number of unmanned aerial vehicles for atmospheric environment monitoring corresponding to the screened area.
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