CN117727162A - Atmospheric pollution risk early warning method and system - Google Patents
Atmospheric pollution risk early warning method and system Download PDFInfo
- Publication number
- CN117727162A CN117727162A CN202311824577.XA CN202311824577A CN117727162A CN 117727162 A CN117727162 A CN 117727162A CN 202311824577 A CN202311824577 A CN 202311824577A CN 117727162 A CN117727162 A CN 117727162A
- Authority
- CN
- China
- Prior art keywords
- atmospheric
- concentration
- pollutant
- grid
- obtaining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 24
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 147
- 231100000719 pollutant Toxicity 0.000 claims abstract description 147
- MWUXSHHQAYIFBG-UHFFFAOYSA-N nitrogen oxide Inorganic materials O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 claims description 12
- 238000009792 diffusion process Methods 0.000 claims description 10
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims description 8
- 239000000356 contaminant Substances 0.000 claims description 7
- 239000011159 matrix material Substances 0.000 claims description 7
- 238000003915 air pollution Methods 0.000 claims description 4
- 239000012855 volatile organic compound Substances 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 3
- 238000004062 sedimentation Methods 0.000 claims description 3
- 238000012876 topography Methods 0.000 claims description 3
- 238000004836 empirical method Methods 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 description 24
- 238000004891 communication Methods 0.000 description 9
- 238000004458 analytical method Methods 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 239000010419 fine particle Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 description 1
- 239000000809 air pollutant Substances 0.000 description 1
- 231100001243 air pollutant Toxicity 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000013618 particulate matter Substances 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to an atmospheric pollution risk early warning method and system, wherein the method comprises the following steps: acquiring the concentration of the atmospheric pollutants in a region to be early-warned, and carrying out grid division on the region to be early-warned to acquire a grid region which does not exceed the threshold value of the concentration of the atmospheric pollutants; and predicting the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted grade of each grid area according to the weight of each atmospheric pollutant, and carrying out atmospheric pollutant emission early warning. The invention can accurately early warn the risk of atmospheric pollution.
Description
Technical Field
The invention relates to the technical field of early warning of atmospheric pollution risks, in particular to an early warning method and system of atmospheric pollution risks.
Background
In recent years, with the rapid development of economy, the air quality is bad all over the country, haze weather often appears, and the physical health of people is seriously affected, wherein the large total emission amount of air pollutants is the main reason for poor air quality.
At present, the monitoring of the satellite remote sensing data (such as MODIS, VIIRS and the like) of the main atmospheric environment at home and abroad can achieve the maximum resolution of 375 meters at 1 time per day, the maximum resolution of 1 km at the concentration of the fine particles in the atmosphere, and the related weather forecast data can also achieve the hour-by-hour and km level within 24 hours, so that the requirements of regional atmospheric pollution risk prediction can be met.
The existing atmospheric pollution risk early warning is mainly based on real-time measurement of ground monitoring stations or atmospheric environmental pollution risk research analysis of an atmospheric environmental model simulation technology, but the prediction accuracy is low, and on one hand, the existing atmospheric pollution risk early warning is only based on ground limited station data mainly distributed in a region to be detected, so that the coverage degree of the region is insufficient; on the other hand, the atmospheric pollution risk early warning is only weather forecast data in the evaluation method, and the dynamic change of a pollution source and the spatial distribution change of the air quality of the real-time reference environment of the concentration of the atmospheric fine particles are not considered, so that the traditional atmospheric pollution risk early warning cannot accurately early warn the regional atmospheric pollution risk.
Disclosure of Invention
The invention aims to provide an atmospheric pollution risk early warning method and system, which can accurately early warn the atmospheric pollution risk.
In order to achieve the above object, the present invention provides the following solutions:
an atmospheric pollution risk early warning method comprises the following steps:
acquiring the concentration of the atmospheric pollutants in a region to be early-warned, and carrying out grid division on the region to be early-warned to acquire a grid region which does not exceed the threshold value of the concentration of the atmospheric pollutants;
and predicting the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted grade of each grid area according to the weight of each atmospheric pollutant, and carrying out atmospheric pollutant emission early warning.
Optionally, the atmospheric contaminants include: PM2.5, PM10, VOCs, nitrogen oxides and sulfur dioxide.
Optionally, acquiring the grid region that does not exceed the contaminant concentration threshold comprises:
setting a pollutant concentration threshold, comparing the atmospheric pollutant concentration in the grid area with the pollutant concentration threshold, judging whether the atmospheric pollutant concentration in the grid area is larger than the pollutant concentration threshold, if the atmospheric pollutant concentration in the grid area is larger than the pollutant concentration threshold, carrying out atmospheric pollutant emission early warning on the grid area exceeding the pollutant concentration threshold, and if the atmospheric pollutant concentration in the grid area is smaller than the pollutant concentration threshold, acquiring the grid area not exceeding the pollutant concentration threshold.
Optionally, obtaining the predicted concentration includes:
and collecting geographic data of the area to be pre-warned, acquiring a pollutant diffusion matrix, inputting the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold and the pollutant diffusion matrix into an SSMI model, and acquiring the pollutant diffusion concentration, namely the predicted concentration.
Optionally, the geographic data includes: topography characteristics, temperature, humidity, wind speed, wind direction, air pressure, rainfall, pollution source height and dry and wet sedimentation of atmospheric particulates.
Optionally, obtaining the weight of the atmospheric contaminant comprises:
and obtaining the weight of the atmospheric pollutants according to the overrun value of the predicted concentration and an empirical method and an analytic hierarchy process.
Optionally, obtaining the atmospheric pollutant prediction rating for each grid zone and controlling atmospheric pollutant emissions comprises:
and carrying out early warning on the emission of the atmospheric pollutants in the grid area with the atmospheric pollutant prediction grade being at risk, and carrying out no treatment on the grid area with the atmospheric pollutant prediction grade being at no risk.
In order to achieve the above object, the present invention further provides an air pollution risk early warning system, including:
the grid region acquisition unit is used for acquiring the concentration of the atmospheric pollutants in the region to be pre-warned, and carrying out grid division on the region to be pre-warned to acquire a grid region which does not exceed the threshold value of the concentration of the atmospheric pollutants;
the risk early warning unit is used for predicting the concentration of the atmospheric pollutants in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted level of each grid area according to the weight of each atmospheric pollutant and carrying out atmospheric pollutant emission early warning;
the grid region acquisition unit is connected with the risk early warning unit.
The beneficial effects of the invention are as follows:
according to the method, the atmospheric pollutant concentration in the grid area is compared with the pollutant concentration threshold value, the grid area exceeding the atmospheric pollutant concentration threshold value obtained through real-time detection is early-warned in time, the grid area with risk is obtained based on the combination of the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold value and the pollutant diffusion matrix, the atmospheric pollutant emission early warning is carried out, and the atmospheric pollutant risk is accurately early-warned in a mode of combining the actually measured atmospheric pollutant concentration with the predicted atmospheric pollutant concentration.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an air pollution risk early warning method according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the invention discloses an air pollution risk early warning method, which comprises the following steps: acquiring the concentration of the atmospheric pollutants in the area to be early-warned, and performing grid division on the area to be early-warned to acquire a grid area which does not exceed the threshold value of the concentration of the atmospheric pollutants; predicting the concentration of the atmospheric pollutants in the grid area which does not exceed the threshold value of the concentration of the atmospheric pollutants, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the predicted grade of the atmospheric pollutants in each grid area according to the weight of each atmospheric pollutant, and carrying out atmospheric pollutant emission early warning; wherein, atmospheric pollutants include: PM2.5, PM10, VOCs, nitrogen oxides and sulfur dioxide.
The method for obtaining the atmospheric pollutant concentration of the area to be pre-warned comprises the following steps: the system comprises a transmitting aircraft, wherein the aircraft carries a wireless communication device and a sensor for monitoring atmospheric pollutants in a target area, the wireless communication device is connected with a data center in a wireless communication mode through a ground base station, and the data center is used for storing atmospheric pollutant data monitored by the sensor received through wireless communication.
The aircraft is a rotor type unmanned aerial vehicle, a fixed wing unmanned aerial vehicle, an unmanned fire balloon or an airship, and can be some of the currently mainstream aircrafts, such as rotor type unmanned aerial vehicles, fixed top wing unmanned aerial vehicles, unmanned fire balloons or airships and the like with excellent flight and hovering functions. The aircraft carries a wireless communication device and a sensor for monitoring atmospheric pollutants in a target area, and the wireless communication device establishes wireless communication connection with a data center through a ground base station so as to send monitoring data acquired by the sensor to the data center. The sensors may include cameras, harmful gas (e.g., VOCs, nitrogen oxides, and sulfur dioxide, etc.) concentration sensors, particulate matter concentration (e.g., PM2.5, PM10, etc.) sensors, temperature sensors, humidity sensors, and the like. The sensor monitors the atmosphere on line. Therefore, the aircraft can fly to the upper air of a target area which is difficult to monitor by the conventional means, such as a forest, a lake, an ocean, a building intensive area, a river, a bridge, a chemical plant and the like, and the atmospheric pollutants in the upper air are monitored in real time.
In addition, the aircraft is also provided with a data storage card for storing the atmospheric pollutant data monitored by the sensor so as to ensure the safety of the monitored data. When the aircraft goes offline due to signal occlusion, the system can ensure that the integrity of the monitoring data is not lost, as the monitoring data is first stored in its entirety in a memory card carried by the aircraft itself. When the aircraft re-communicates with the ground base station, the system automatically matches and identifies the data that was not transmitted, and in time, forwards the previous data to the data center. If the aircraft is not communicated with the ground base station all the time, the aircraft can wait for the flight control personnel to retrieve the aircraft, take out the storage card in the aircraft, and backup the data to the data center.
Further, the ground base station may include a self-contained base station, an operator base station, or a combination of both. That is, the operator base station is adopted in the case of having the operator base station, so as to reduce the cost and save the base station deployment time. The data center is used for storing the atmospheric pollutant data monitored by the sensors received through wireless communication. All the monitoring data will be stored in the data center in time sequence to facilitate the query.
The meshing of the area to be early-warned comprises the following steps: and meshing the area where the aircraft walks.
Acquiring the grid region that does not exceed the contaminant concentration threshold includes: setting a pollutant concentration threshold, comparing the atmospheric pollutant concentration in the grid area with the pollutant concentration threshold, judging whether the atmospheric pollutant concentration in the grid area is larger than the pollutant concentration threshold, if so, performing atmospheric pollutant emission early warning on the grid area exceeding the pollutant concentration threshold, and if so, acquiring the grid area not exceeding the pollutant concentration threshold.
Obtaining the predicted concentration includes: collecting geographic data of an area to be pre-warned, acquiring a pollutant diffusion matrix, inputting the atmospheric pollutant concentration and the pollutant diffusion matrix in a grid area which does not exceed an atmospheric pollutant concentration threshold value into an SSMI model, and acquiring the pollutant diffusion concentration, namely, the predicted concentration.
The geographic data includes: topography characteristics, temperature, humidity, wind speed, wind direction, air pressure, rainfall, pollution source height and dry and wet sedimentation of atmospheric particulates.
The method for calculating the overrun value of the predicted concentration comprises the following steps:
wherein A is the overrun value of the predicted concentration, B is the real-time monitoring value mug/m of each atmospheric pollutant 3 C is the concentration limit value of each atmospheric pollutant, mug/m 3 。
The obtaining of the weight of the atmospheric pollutants comprises the following steps: and sequencing the importance degrees of different atmospheric pollutants according to the actual needs of each grid area and expert experience methods, and acquiring the weight of the atmospheric pollutants based on the overrun value of the predicted concentration and the combination of the experience method and the analytic hierarchy process.
Acquiring the atmospheric pollutant prediction grades for each grid zone and controlling atmospheric pollutant emissions includes: and carrying out early warning on the emission of the atmospheric pollutants in the grid area with the predicted level of the atmospheric pollutants at risk, and carrying out no treatment on the grid area with the predicted level of the atmospheric pollutants at no risk.
Obtaining the predicted level of contamination includes: and acquiring the comprehensive weight according to the weight of the atmospheric pollutants, wherein when the comprehensive weight is greater than 0, the atmospheric pollutants are predicted to be at risk, and when the comprehensive weight is less than 0, the atmospheric pollutants are predicted to be at no risk.
Performing an atmospheric pollutant emission warning includes: and when the monitoring data and the prediction data are higher than a preset threshold value and an evaluation level, automatically sending out early warning information. The early warning information can be sent to a user mobile phone or a mailbox and/or displayed on an APP client or a webpage through a short message. The early warning information can comprise monitoring time, coordinate position information, elevation, site images, various atmospheric pollutant monitoring values exceeding a threshold value, predicted evaluation grades and the like of the target area. The data center may include a mobile data center (e.g., a notebook or vehicle server), a stationary data center (e.g., a server installed in a machine room), or a combination of both, to facilitate flexible deployment of the system. The data center can access the Internet in a wireless or wired mode, so that the terminal user can conveniently inquire monitoring data and/or receive early warning information.
The monitoring terminal is in communication connection with the data center through a network and is used for inquiring the atmospheric pollutant data stored in the data center and/or receiving the early warning information sent by the data center. The remote monitoring and analysis center, the remote individual user and the related technicians of the field ground station can access the Internet through different monitoring terminals, so that synchronous inquiry and receiving of monitoring data and early warning information in the data center can be realized. For example, a user may display various monitoring data and analysis charts (e.g., graphs, two-dimensional charts, three-dimensional charts, etc.) through the monitoring terminal in the form of a web page or APP, and through these analysis charts, the atmospheric pollution level of the target area may be intuitively displayed. Meanwhile, the remote monitoring and analyzing center and the remote individual user can synchronize the monitoring and guiding with the personnel of the field ground station according to the analysis of the monitoring information so as to better complete the monitoring, predicting and early warning tasks. The monitoring terminal can comprise a computer, a smart phone or a tablet personal computer and the like.
The invention also discloses an atmospheric pollution risk early warning system, which comprises: the grid region acquisition unit is used for acquiring the atmospheric pollutant concentration of the region to be early-warned, and carrying out grid division on the region to be early-warned to acquire a grid region which does not exceed the atmospheric pollutant concentration threshold value; the risk early warning unit is used for predicting the concentration of the atmospheric pollutants in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted level of each grid area according to the weight of each atmospheric pollutant and carrying out atmospheric pollutant emission early warning; the grid region acquisition unit is connected with the risk early warning unit.
The above embodiments are merely illustrative of the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, but various modifications and improvements made by those skilled in the art to which the present invention pertains are made without departing from the spirit of the present invention, and all modifications and improvements fall within the scope of the present invention as defined in the appended claims.
Claims (8)
1. An air pollution risk early warning method is characterized by comprising the following steps:
acquiring the concentration of the atmospheric pollutants in a region to be early-warned, and carrying out grid division on the region to be early-warned to acquire a grid region which does not exceed the threshold value of the concentration of the atmospheric pollutants;
and predicting the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted grade of each grid area according to the weight of each atmospheric pollutant, and carrying out atmospheric pollutant emission early warning.
2. The method of claim 1, wherein the atmospheric contaminants comprise: PM2.5, PM10, VOCs, nitrogen oxides and sulfur dioxide.
3. The method of claim 1, wherein acquiring a grid region that does not exceed the contaminant concentration threshold comprises:
setting a pollutant concentration threshold, comparing the atmospheric pollutant concentration in the grid area with the pollutant concentration threshold, judging whether the atmospheric pollutant concentration in the grid area is larger than the pollutant concentration threshold, if the atmospheric pollutant concentration in the grid area is larger than the pollutant concentration threshold, carrying out atmospheric pollutant emission early warning on the grid area exceeding the pollutant concentration threshold, and if the atmospheric pollutant concentration in the grid area is smaller than the pollutant concentration threshold, acquiring the grid area not exceeding the pollutant concentration threshold.
4. The method of claim 1, wherein obtaining the predicted concentration comprises:
and collecting geographic data of the area to be pre-warned, acquiring a pollutant diffusion matrix, inputting the atmospheric pollutant concentration in the grid area which does not exceed the atmospheric pollutant concentration threshold and the pollutant diffusion matrix into an SSMI model, and acquiring the pollutant diffusion concentration, namely the predicted concentration.
5. The method of claim 4, wherein the geographic data comprises: topography characteristics, temperature, humidity, wind speed, wind direction, air pressure, rainfall, pollution source height and dry and wet sedimentation of atmospheric particulates.
6. The method of claim 1, wherein obtaining the weight of the atmospheric contaminants comprises:
and obtaining the weight of the atmospheric pollutants according to the overrun value of the predicted concentration and an empirical method and an analytic hierarchy process.
7. The atmospheric pollution risk warning method of claim 1, wherein obtaining the atmospheric pollution prediction level of each grid area and controlling the atmospheric pollution discharge comprises:
and carrying out early warning on the emission of the atmospheric pollutants in the grid area with the atmospheric pollutant prediction grade being at risk, and carrying out no treatment on the grid area with the atmospheric pollutant prediction grade being at no risk.
8. An atmospheric pollution risk early warning system, characterized by comprising:
the grid region acquisition unit is used for acquiring the concentration of the atmospheric pollutants in the region to be pre-warned, and carrying out grid division on the region to be pre-warned to acquire a grid region which does not exceed the threshold value of the concentration of the atmospheric pollutants;
the risk early warning unit is used for predicting the concentration of the atmospheric pollutants in the grid area which does not exceed the atmospheric pollutant concentration threshold value, obtaining the predicted concentration, calculating the ultra-limit value of the predicted concentration, obtaining the weight of each atmospheric pollutant, obtaining the atmospheric pollutant predicted level of each grid area according to the weight of each atmospheric pollutant and carrying out atmospheric pollutant emission early warning;
the grid region acquisition unit is connected with the risk early warning unit.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311824577.XA CN117727162A (en) | 2023-12-27 | 2023-12-27 | Atmospheric pollution risk early warning method and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311824577.XA CN117727162A (en) | 2023-12-27 | 2023-12-27 | Atmospheric pollution risk early warning method and system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN117727162A true CN117727162A (en) | 2024-03-19 |
Family
ID=90203439
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311824577.XA Pending CN117727162A (en) | 2023-12-27 | 2023-12-27 | Atmospheric pollution risk early warning method and system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117727162A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118097901A (en) * | 2024-04-26 | 2024-05-28 | 成都秦川物联网科技股份有限公司 | Gas leakage detector alarm method, system and equipment based on Internet of things |
-
2023
- 2023-12-27 CN CN202311824577.XA patent/CN117727162A/en active Pending
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118097901A (en) * | 2024-04-26 | 2024-05-28 | 成都秦川物联网科技股份有限公司 | Gas leakage detector alarm method, system and equipment based on Internet of things |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2019025906A1 (en) | Method and system for improving objectivity of atmospheric pollutant monitoring data | |
KR102035693B1 (en) | Method of monitoring air pollution and system for the same | |
CN109932988B (en) | Urban raise dust pollution diffusion prediction system and method | |
CN106595757A (en) | Environment monitoring method and system | |
CN117727162A (en) | Atmospheric pollution risk early warning method and system | |
CN113252851A (en) | Atmospheric pollution monitoring system based on NB-IoT and edge calculation | |
KR20090098127A (en) | Air pollution monitoring system and method | |
CN107315422A (en) | Air automatic detection and sample-leaving system based on unmanned plane | |
CN106971511A (en) | A kind of atmosphere pollution monitoring and early warning system and method based on aircraft | |
De Medeiros et al. | An IoT-based air quality monitoring platform | |
CN113655175A (en) | Gridding air monitoring method, system, computer equipment and storage medium | |
CN109374837A (en) | A kind of miniature air mass monitoring system and analysis method | |
CN106680170A (en) | Air-land real-time wholly monitoring and early warning system and method for regional atmospheric pollution | |
CN209879035U (en) | Real-time road surface weather data acquisition and information push system based on car networking | |
CN114757687A (en) | Atmospheric pollutant tracing system and method based on big data technology | |
KR20200128226A (en) | Fine dust concentration prediction system | |
CN111751498A (en) | Toxic gas distribution detection system and method in toxic environment based on mobile platform | |
KR20200128230A (en) | Fine dust measurement system linked with smartphone | |
CN211292820U (en) | Be used for air quality monitoring unmanned aerial vehicle | |
CN113009100A (en) | Base station type unmanned aerial vehicle watershed water environment monitoring system | |
CN105333900A (en) | Flue gas monitoring system and method based on multi-rotor platform | |
CN115146484A (en) | Environment-friendly monitoring system and monitoring method for detecting environmental parameters | |
CN209858530U (en) | Sky ground integration atmosphere monitoring system | |
CN114813493A (en) | Raise dust on-line monitoring system based on unmanned aerial vehicle unites ground fixed point and deploys | |
CN207623771U (en) | A kind of coal-burning power plant's atmosphere pollution diffusion monitoring system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |