TWI720324B - Operation method of pollution source analyzing system for multi-point air quality detection - Google Patents

Abstract

The present invention provides an operation method of pollution source analyzing system for multi-point air quality detection. The method includes the following the steps: define at least one measuring point at adjacent areas, and then measure an air quality value, a wind speed value, a wind direction value, a pressure value, a humidity value, a temperature value and a geographical information, in which a location information, terrain information and a time information involved; acquire at least one air flow information corresponding to the measuring point from an instantaneous airflow database; and collect the measuring values of each measuring points, to estimate the location of the air pollution source. The present invention can calculate the location of specific air pollution sources according to the measuring values of the measuring points by big data analytics and algorithm. It can also be combined with weather forecast data to estimate the possible area air pollution may affect in the future. As a result, the present invention can be of help eliminating air pollution aimed at pollution sources or countermeasures figured out for affected areas in the future, so as to reduce pollution and its impact, thus enhance the public's health and safety.

Description

Operation method of pollution source analysis system with multi-point air quality detection

The present invention provides an operation method of a pollution source analysis system with multi-point air quality detection, especially a method for air quality value, wind speed value, wind direction value, pressure value, humidity value, temperature value, location information and air flow information. By which the location of the air pollution source can be estimated.

According to the fact that air quality has been declining in recent years, there are many sources of air pollution, including: smog, industrial emissions, power generation, transportation, etc., which all affect air quality; among them, particulate matter (PM) is widespread. Refers to particles suspended in the air, and PM2.5 is fine suspended particles with a diameter less than or equal to 2.5 microns; suspended particles include naturally formed dust, sea salt, volcanoes or ashes from combustion, and human factors include humans’ use of fossil fuels , Such as: coal, oil, natural gas, or the combustion of garbage; due to its extremely small particle size and large surface area, it is easy to absorb toxic substances in the air and directly enter the bronchus of the human body. It diffuses to the wall of the bronchioles and interferes with the gas exchange in the lungs, or passes through the lungs to other organs; PM1 is the general term for particles with a diameter of less than or equal to 1 micron in the air. It is also called lung-enterable particulate matter, which means, It can enter the alveolar blood, so it has a greater impact on the human body and the environment. There is even more evidence that the smallest suspended particles (100 nanometers or less in diameter, 0.1 micron) will pass through the cell membrane and be transmitted to other human organs. ,contain The brain, and it may cause symptoms such as brain damage, it is obvious that aerosols do have a huge impact on the environment and organisms.

In addition, when the haze occurs, due to the decrease of atmospheric pressure, the sudden increase of fine particles in the air and the poor air mobility, harmful bacteria and viruses spread slowly to the surrounding area, resulting in the concentration of bacteria, viruses, and pathogenic microorganisms in the air. The increase will make the risk of disease spread very high. According to statistics from the Beijing Municipal Health Bureau, every time a severe haze weather occurs, the number of respiratory-related patients in major hospitals in the city increases by 20 to 50%. Furthermore, the haze will have a serious impact on human cardiovascular and cerebrovascular diseases. It may also reduce the intensity of ultraviolet rays near the ground, increase the activity of infectious pathogens in the air, and increase the number of infectious diseases. In addition, the smog can also affect people's mental health, causing feelings of dullness and depression, and can stimulate or aggravate the state of mental depression.

To solve the air pollution problem, the primary goal is to analyze the pollution source and the proportion of each pollution source, so as to help formulate countermeasures to deal with air pollution.

The existing analysis of air pollution is mainly carried out by air box, which is mainly to make up for the lack of air pollution monitoring by government units. The Information Institute of the Academia Sinica pointed out that, as far as China is concerned, the Environmental Protection Agency has set up 76 monitoring stations throughout Taiwan. It mainly measures environmental background values. Most of them are placed at an altitude of 10-15 meters. However, what people care about is the air quality near their homes. The air box can be installed by itself, so that people or professionals can search on the Internet and develop applications. , Its monitoring data can be analyzed through big data to accurately detect the current status of air pollution at the location; the air box project will gradually expand from one base, and now there are more than 1,500 bases in Taiwan, while expanding to 26 overseas countries, which can be combined with academic research The application of the Internet of Things in, communities, industries and governments to facilitate the real-time monitoring of air pollution around the world to help grasp and improve air quality.

However, the detection of air pollution by conventional knowledge is only through the establishment of AQI observation stations to measure or predict local air pollution, and as described in the "Provision of Air Quality Information" In the case of "Communication System", a plurality of mobile devices with actuation sensor modules are used to sense single-point air information at their respective locations and send them to a cloud processing device to generate various derivatives that are beneficial to users. Information, including: direction of travel, designated route, air quality information, air quality abnormal notification information or evacuation route; however, it cannot accurately find the source of pollution, and cannot accurately observe or predict the scope of air pollution impact; in addition, its main Transmission is via Wi-Fi, which consumes a lot of power, and if large-scale installation is carried out, a lot of power will be consumed.

In view of this, our inventors devoted themselves to further research on air pollution measurement, and proceeded to develop and improve, hoping to develop a better invention to solve the above problems, and after continuous experimentation and modification, the present invention came out.

The purpose of the present invention is to solve the aforementioned problems. In order to achieve the above objectives, our inventors provide a method for operating a pollution source analysis system with multi-point air quality detection. The steps include: (a) a plurality of neighbors At least one measurement point is defined in the area, and an air quality value, a wind speed value, a wind direction value, a pressure value, a humidity value, a temperature value and a geographic information are measured at the measurement points respectively; the geographic information Contains a position information, a terrain information and a time information; (b) retrieves at least one air flow information corresponding to the measuring point and the time information from a real-time air flow database; and (c) based on the same time The information collects one measurement value of each of the measurement points, the measurement value includes the air quality value, wind speed value, wind direction value, pressure value, humidity value, temperature value, geographic information and airflow information, and the The measured value is analyzed by air diffusion function and big data to calculate the location of an empty pollution source.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, the steps (b) and (c) are through a transmission device through a Low-Power Wide-Area Network (Low-Power Wide-Area Network). LPWAN) to capture the airflow information of the area and transmit the measured value to a server, so that the server calculates the location of the air pollution source based on the measured value.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, the low-power wide area network adopts NB-IoT (Narrow Band Internet of Things, Narrow Band Internet of Things), LoRa (Long Range, ultra-long Distance low-power data transmission technology), Sigfox Internet of Things communication network, Weightless, HaLow or RPMA (Random Phase Multiple Access, random phase multiple access).

According to the above-mentioned operation method of a pollution source analysis system with multi-point air quality detection, the geographic information is obtained by a GNSS (Global Navigation Satellite System) locator or a GPS locator.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, the measuring points are dynamic or static points arranged at intervals in the area.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, the big data analysis is performed by the backward pass neural network.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, it further includes the steps of: (d) measuring the air quality value of the corresponding measuring point by at least one first client, Wind speed value, wind direction value, air pressure value, humidity value, temperature value and geographic information; (e) A server acquires the airflow information and collects the measured value of the measurement point, and calculates the air pollution source Location; and (f) setting at least one second client to connect to the server, so as to obtain at least one of the measured values and the location of the air pollution source through the server.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, it further includes the steps of: (g) setting a positioning information on at least one of the second clients to mark the at least one of the second clients The location of the client; (h) the server calculates an air quality information corresponding to the location information based on the location information and the measured value of the measurement point; (i) at least one of the second client settings At least one threshold value corresponding to the air quality information; and (j) when the air quality information reaches the corresponding threshold value, the second client that sets the threshold value is caused to issue a warning.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, it further includes the steps of: (k) extracting at least one meteorological information of the measuring point from a meteorological forecast database, and the measured value It includes the meteorological information; and (1) The measured value is analyzed by an air diffusion function and big data to calculate a future pollution range.

According to the above-mentioned operation method of the pollution source analysis system with multi-point air quality detection, it further includes the steps of: (m) setting a positioning information on at least one of the second clients to mark the at least one of the second clients The location of the client, and the second client obtains the future pollution range through the server; and (n) when the location information of at least one of the second clients is within the future pollution range, Make the corresponding second client to issue an alert.

Based on the above description and settings, it is obvious that the present invention mainly has the following advantages and effects, which are described in detail as follows:

1. The present invention further captures the wind speed, wind direction, air pressure, humidity and temperature values, and cooperates with the airflow information of the existing real-time airflow database. Through air diffusion function and big data analysis, further calculations can be made The location of the pollutant source and the scope of future pollution will enable relevant units to eliminate air pollution sources or respond to their countermeasures to reduce pollution and improve people's health and safety.

2. Since many measurement points need to be set up to obtain the location of the air pollution source and the future pollution range through big data analysis, in order to reduce power consumption, the present invention uses a low-power wide-area network for data transmission, so it can greatly Reduce the power consumption of data transmission, which can achieve the effect of energy saving and carbon reduction.

3. The present invention allows the second client, such as the user’s smart phone or computer, to set the threshold or positioning information by itself, so that the air quality information can reach the corresponding threshold, or in the When the positioning information is within the future pollution range, the corresponding second client is issued a warning, so that the user can respond to the pollution in time to ensure its health and safety.

1: the first client

1’: body

11: Air quality measurement device

12: Wind direction and speed measurement unit

13: Air pressure measuring device

14: Humidity measuring device

15: Temperature measuring device

16: positioning device

17: Transmission device

18: Processing unit

2: server

3: Real-time airflow database

4: The second client

5: Weather forecast database

A: area

G: Large observatory

L: location

M: Observation point

P: measuring point

S001~S005: steps

Figure 1 is a schematic diagram of the structure of the present invention.

Figure 2 is a schematic front view of the present invention.

Figure 3 is a schematic diagram of a process of the present invention.

Figure 4 is a schematic diagram of the use state of the present invention.

Figure 5 is a schematic diagram of a backward pass neural network.

Figure 6 is a schematic diagram of another process of the present invention.

Regarding the technical means of our inventors, several preferred embodiments are described in detail below in conjunction with the drawings, so as to provide a thorough understanding and approval of the present invention.

Please refer to Figures 1 to 3 first. The present invention is an operation method of a pollution source analysis system with multi-point air quality detection. The steps include: S001: Define at least one measurement point P in a plurality of adjacent areas A , The measuring point P can be a self-built observation point M, or a large-scale observation station G of a government agency; a first client 1 is set up at the measuring point P and measured at the measuring point P An air quality value, a wind speed value, a wind direction value, a pressure value, a humidity value, a temperature value and a geographic information; in a preferred embodiment, as shown in Figure 4, the observation point is set up by itself M is to set up the main body 1'separately, the main body 1'can be a set-top box located in the first client 1, and the measuring points P are dynamic or static points arranged at intervals in the area A; As shown in Figure 4, the measuring point P, whether it is the main body 1'or the large observation station G, can be erected outside the building, on a telegraph pole, or by an aerial vehicle in a dynamic or static position outdoors, such as high altitude, depending on the situation; The observation station G and the body 1'are respectively provided with an air quality measuring device 11, a wind direction and wind speed measuring unit 12, an air pressure measuring device 13, a humidity measuring device 14, a temperature measuring device 15 and a Positioning device 16; to measure the air quality value, wind speed value, wind direction value, pressure value, humidity value, temperature value and geographic information corresponding to the measurement point P; for the wind direction and wind speed measurement unit 12, it is the The wind direction and wind speed measuring unit 12 is a Hall anemometer or a tube anemometer, which can measure the wind speed value and the wind direction value at the same time; in another embodiment, as shown in Figure 2, it may include an anemometer 121 and an anemometer 122, but it is only an example and not a limitation; Regarding the positioning device 16, in one embodiment, it can be a GNSS (Global Navigation Satellite System, Global Navigation Satellite System) locator or a GPS locator to obtain its geographic information through positioning; wherein, the geographic information Contains a location information, a terrain information and a time information; therefore, if you know, the location information is the location you are in; the terrain information is the height of the location; and the time information is used to define the measurement point P Since the geographic location may have positioning errors, in one embodiment, the geographic location of the observation point M can be obtained by the relative position of the geographic location located by the large observation station G, but it is only For illustration, this is not a limitation.

In a preferred embodiment, the main body 1'is provided with a transmission device 17 and a processing unit 18, and the processing unit 18 is coupled to the air quality measurement device 11, the wind direction and speed measurement unit 12, and the air pressure measurement device 13. Humidity measurement device 14, temperature measurement device 15, positioning device 16 and the transmission device 17; S002: create a server 2, which can be connected to a real-time airflow database 3 through the network to capture the corresponding State at least one airflow information at the location of the measurement point P; among them, the real-time airflow database 3 is an existing global open source database, such as open data such as environmental protection and sanitation units of various governments, Windyty or EarthWindMap; it is captured by the server 2 The airflow information must correspond to the distribution area of the measuring point P. Therefore, in one embodiment, a connection with the body 1'of the first client 1 needs to be established, or through the first client 1 Register to obtain the geographic location of the measurement point P, and then obtain the distribution range of all the measurement points P, thereby facilitating the acquisition of airflow information corresponding to the measurement point P. Therefore, the body 1'of the first client 1 The transmission device 17 is used to connect to the real-time airflow database 3 through the network to obtain the airflow information corresponding to the measuring point P; As far as the network transmission of the transmission device 17 is concerned, since the wider the area A is installed, the more the number of measurement points P, the more detailed the number of data obtained, so the range of analysis can be wider, and the calculation result is also The more precise, therefore, if the large-scale installation is carried out, the power consumption will be greatly increased; the present invention can achieve the effect of energy saving and carbon reduction, so the transmission device 17 adopts a low-power wide-area network (Low-Power Wide-Area Network). , LPWAN) for data and network transmission. In one embodiment, the low-power wide-area network can be NB-IoT (Narrow Band Internet of Things), LoRa (Long Range, ultra-long range, low power consumption). Data transmission technology), Sigfox Internet of Things communication network, Weightless, HaLow or RPMA (Random Phase Multiple Access); in addition, in one embodiment, the power source of the main body 1'can also be A solar power generation unit is installed to supply the operation of the internal device of the main body 1'by solar power generation, so as to further achieve the effect of energy saving and carbon reduction; however, it is only an example and not a limitation.

S003: Collect the measurement value of each measurement point P based on the same time information through the server 2, so as to ensure that the measurement value is indeed at the same time point; wherein the measurement value includes the air quality quantity Value, wind speed value, wind direction value, pressure value, humidity value, temperature value and geographic information, which are respectively analyzed, calculated and aggregated by the processing unit 18, so as to facilitate the collection, and use the transmission device 17 to measure the point P The measured value is transmitted to the server 2, and the server 2 will collect, analyze, calculate, and integrate the airflow information corresponding to the measured value of each measurement point P, and will cover the measured value of the airflow information The air diffusion function and big data analysis are used to estimate the location of an empty pollution source; therefore, in one embodiment, the server 2 can be configured as a computing center with artificial intelligence to aggregate the measured values and calculate Find the location of the air pollution source; As for the aggregation of the measured values, the time information in the positioning device 16 is used to synchronize the measured values of all the measuring points P. Because the measured values must be dependent on time, they can be based on the same time. Click to estimate the location of the air pollution source, so the server 2 collects and synchronizes the measured value of each of the measurement points P with the corresponding time information according to the corresponding time information, and calculates based on the measured value The position of the empty pollution source can be used to calibrate all the measured values at the same time point to prevent the time difference between the measured values, thereby improving the overall accuracy of the present invention; for the integration between the airflow information and the aforementioned measured values In one embodiment, because the measured value has geographic information, which includes location information, and the airflow information itself contains information of meteorological coordinates, the meteorological coordinates and position information can be integrated to make the measurement The measured value can include airflow information.

For the calculation of the location of the air pollution source, it is obtained by the air diffusion function and big data analysis; in terms of the transfer speed and range of the substance in the air, it will be affected by the air temperature, pressure, and air velocity. It depends on the flow direction, so it can be calculated by the calculation of the air diffusion function and by referring to the measured values of multiple measuring points P, and by big data analysis, the location of the air pollution source can be calculated backward. ; For a specific example of the air diffusion function, in an unsteady state in a one-dimensional space, the concentration equation of the pollutant in the moving medium can be expressed as the following mathematical formula 1:

為污染物排放率；於進行空氣擴散函式之運算時，可直接帶入氣流資訊進行解算，然氣流資訊僅係一大範圍之估算值，故仍需藉由實際所量測到之空氣品質量值、風速值、風向值、氣壓值、濕度值、溫度值進行空氣擴散函式之修正，其 具體推算及分析方式係屬習知技術，故在此不予贅述，本發明主要係用以更進一步導入空氣擴散函式之概念及所需之解算參數，並更進一步參照現有之即時氣流資料庫3，以更進一步推算空汙源位置；另就大數據分析而言，在一實施例中係透過倒傳遞類神經網路所進行，其基本原理為使用最陡坡降法之觀念，將誤差函數予以最小化，如第5圖所示，其架構包含輸入層、隱藏層及輸出層；其中，輸入層係用以表現網路之輸入變數X _i ,i=1,2,3,...,n，其數量依複雜程度而定，於本實施例中，係可以量測值作為輸入變數；隱藏層用以表現輸入變數間之交互影響作用，其數量係依試驗方式決定，其係可帶入前述之空氣擴散函式，以供進行推估、運算及學習；輸出層係用以表現網路之輸出變數Y _i ,i=1,2,3,...,n，其數量可依欲輸出之結果決定，其結果可予較為精確的推算出空汙源位置。 Among them, C _i is the concentration of pollutants of type i; t is the time; U _a is the wind speed; x is the distance; D _x is the turbulence coefficient;

It is the pollutant emission rate; in the calculation of the air diffusion function, the airflow information can be directly brought into the calculation. However, the airflow information is only a large range of estimates, so it still needs to be based on the actual measured air The quality value, wind speed value, wind direction value, air pressure value, humidity value, and temperature value are corrected by the air diffusion function. The specific calculation and analysis methods are conventional technology, so I will not repeat them here. The present invention mainly uses To further introduce the concept of air diffusion function and the required calculation parameters, and to further refer to the existing real-time airflow database 3 to further estimate the location of the air pollution source; in terms of big data analysis, one implementation In the example, it is carried out through a backward pass neural network. The basic principle is to use the concept of the steepest gradient method to minimize the error function. As shown in Figure 5, the structure includes an input layer, a hidden layer, and an output layer. ; Among them, the input layer is used to represent the input variables of the network X _i , i =1,2,3,..., n , the number of which depends on the degree of complexity, in this embodiment, the value can be measured As an input variable; the hidden layer is used to express the interaction between the input variables. The number is determined by the experimental method. It can be brought into the aforementioned air diffusion function for estimation, calculation and learning; the output layer is The output variables Y _i , i =1,2,3,..., n used to represent the network, the number of which can be determined according to the result to be output, and the result can be more accurate to calculate the location of the air pollution source.

Accordingly, as shown in Figure 4, the calculation of the air quality at each location in the area A can be established based on the above-mentioned measurement values at the measurement point P (including the observation point M and the large-scale observation station G) A space function Q, as shown in the following mathematical formula 2: [Mathematical formula 2] Q=f( M , G )

Among them, M is the measured value of the observation point, and G is the measured value of the large-scale observation station.

The position of the air pollution source can be partially differentiated according to the aforementioned spatial function Q, so as to find the extreme value with a slope of 0 to obtain the air pollution source position.

In this way, it can be helpful for relevant units to explore the location of the air pollution source to eliminate the air pollution source or respond to its countermeasures. In one embodiment, the user can use his communication device (such as a computer or a smart phone), and Configured as a second client 4 to connect to the server 2 via the Internet, Furthermore, real-time or historical air pollution source geographic information can be retrieved, and relevant users can report it, and set up manual or automatic push messages to be sent to users.

In one embodiment, in order to remind the user whether the air quality at the current location exceeds the standard, the user can set a positioning information on the second client 4 to indicate the location L, and the server 2 will use the measurement The location information of point P and the measured value are calculated to correspond to the air quality information of the positioning information. The calculation can be as described above. Substitute the position of the second client 4 into the spatial function Q to obtain the second client 4 The user can set at least one threshold corresponding to the air quality information through the respective second client 4, and the threshold can also be preset by the second client 4, thereby When the air quality information reaches the corresponding threshold, the second client 4 that sets the threshold is made to issue a warning, so that the user can learn its location through the second client 4 The air quality information can be used to respond to, keep away from, or eliminate the factors that are unfavorable to the user.

In another embodiment, as shown in Figures 1 to 6, it is possible to further estimate the range of air pollution that may affect in the future, so it can further include the following steps: S004: Server 2 performs a weather forecast The database 5 retrieves at least one meteorological information of the measurement point P, and the measured value includes the meteorological information; in one embodiment, the meteorological prediction database 5 is also open source data, which can be meteorological information of various countries As mentioned above, the transmission device 17 can be connected to the weather forecast database 5 through the network to obtain the weather information corresponding to the measurement point P; and for the integration of the weather information and the measured value , Also as mentioned above, because the measured value has geographic information, it contains location information, and the weather information book contains the information of weather coordinates, so the weather coordinates and location information can be integrated to make the measured value Meteorological information can be covered.

S005: In this way, the server 2 will also collect the measured value of each measurement point P, and calculate a future pollution range through the air diffusion function and big data analysis; and as mentioned above, the specific calculation and analysis method is Conventional technology, so it will not be repeated here. The present invention mainly introduces further meteorological information to facilitate the calculation of the future pollution range.

In another preferred embodiment, in order to remind the user of the possible pollution range in the future, the user can set a location information in the second client 4 to indicate its location, and continue to receive the information provided by the server 2. The future pollution range, and when the positioning information of the second client 4 is within the future pollution range, the corresponding second client 4 will be issued a warning so that the user knows that its location will be in the future. The pollution level is relatively high, so that users can respond to, remove or stay away early.

In summary, the technical means disclosed in the present invention can effectively solve the conventional problems and achieve the expected purpose and effect. It has not been seen in the publications, has not been used publicly, and has long-term progress before the application. The patent law claims that the invention is correct. Yan filed an application in accordance with the law and prayed that Jun Shanghui would give a detailed examination and grant a patent for the invention.

However, the above are only a few preferred embodiments of the present invention, and should not be used to limit the scope of implementation of the present invention, that is, all equivalent changes and modifications made in accordance with the scope of the patent application of the present invention and the content of the invention specification are It should still fall within the scope of the invention patent.

1‧‧‧First client

1’‧‧‧Ontology

11‧‧‧Air quality measurement device

12‧‧‧Wind direction and speed measuring unit

13‧‧‧Air pressure measuring device

14‧‧‧Humidity measuring device

15‧‧‧Temperature measuring device

16‧‧‧Positioning device

17‧‧‧Transmission device

18‧‧‧Processing unit

2‧‧‧Server

3‧‧‧Real-time airflow database

4‧‧‧Second Client

5‧‧‧Meteorological Forecast Database

Claims (9)

A method for operating a pollution source analysis system with multi-point air quality detection. The steps include: (a) defining at least one measurement point in a plurality of adjacent areas, and measuring an air quality value and a measurement point at the measurement points. Wind speed value, a wind direction value, a pressure value, a humidity value, a temperature value and a geographic information; the geographic information includes a location information, a terrain information and a time information; (b) retrieved from a real-time airflow database At least one airflow information corresponding to the measurement point and the time information; (c) collecting one measurement value of each of the measurement points based on the same time information, the measurement value including the air quality measurement value , Wind speed value, wind direction value, pressure value, humidity value, temperature value, geographic information and airflow information, and the measured value is analyzed by the air diffusion function and big data to calculate the location of an empty pollution source; (d) in A weather forecast database retrieves at least one weather information of the measurement point, and the measurement value includes the weather information; and (e) analyzing the measurement value through an air diffusion function and big data, To calculate a future pollution range. For example, the operation method of the pollution source analysis system with multi-point air quality detection described in item 1 of the scope of patent application, wherein the step (b) and step (c) are through a transmission device through a low-power wide area network (Low- Power Wide-Area Network, LPWAN) to capture the airflow information of the area and transmit the measured value to a server, so that the server can estimate the location of the air pollution source based on the measured value. For example, the operation method of the pollution source analysis system with multi-point air quality detection described in item 2 of the scope of patent application, wherein the low-power wide area network adopts NB-IoT (Narrow Band Internet of Things, Narrowband Internet of Things), LoRa (Long Range, ultra-long-distance low-power data transmission technology), Sigfox Internet of Things communication network, Weightless, HaLow or RPMA (Random Phase Multiple Access, random phase multiple access). For example, the operation method of the pollution source analysis system with multi-point air quality detection described in the scope of patent application, wherein the geographic information is through GNSS (Global Navigation Satellite System, Global Navigation Satellite System) locator or GPS locator And the seeker. The operation method of the pollution source analysis system with multi-point air quality detection described in the first item of the scope of patent application, wherein the measuring points are dynamic or static points arranged at intervals in the area. The operation method of the pollution source analysis system with multi-point air quality detection as described in the first item of the scope of patent application, wherein the big data analysis is performed by a back-propagation neural network. For example, the operation method of the pollution source analysis system with multi-point air quality detection described in any one of items 1 to 6 of the scope of the patent application further includes the steps: (f) measuring the corresponding location by at least one first client The air quality value, wind speed value, wind direction value, air pressure value, humidity value, temperature value, and geographic information of the measurement point; (g) the airflow information is captured by a server and collected at the measurement point The measured value and the location of the air pollution source are estimated; and (h) at least one second client is set to connect to the server, so as to obtain at least one of the measured values and the air pollution source through the server position. For example, the operation method of the pollution source analysis system with multi-point air quality detection described in item 7 of the scope of patent application further includes the steps of: (i) setting a positioning information on at least one of the second clients to indicate the at least one 1. The location of the second client; (j) The server calculates an air quality information corresponding to the positioning information based on the location information and the measured value of the measurement point; (k) At least one of the second clients is set to correspond to the location information; The threshold value of the air quality information; and (1) when the air quality information reaches the corresponding threshold value, the second client that sets the threshold value is issued a warning. For example, the operation method of the pollution source analysis system with multi-point air quality detection described in item 7 of the scope of patent application further includes the steps of: (m) setting a positioning information on at least one of the second clients to indicate the at least one The location of a second client, and the second client obtains the future pollution range through the server; and (n) the location information of at least one of the second clients is located in the future When it is within the pollution range, the corresponding second client is ordered to issue a warning.

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