CN114241157A - Air quality visual display method, device and equipment - Google Patents
Air quality visual display method, device and equipment Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the invention provides a visual display method, a visual display device and visual display equipment for air quality. The method comprises the steps of constructing a three-dimensional space coordinate system corresponding to a target monitoring area and establishing a three-dimensional grid model; acquiring air quality data of a target monitoring area, and taking the air quality data at the central point of each cubic grid as the air quality monitoring data of the cubic grid; converting the air quality monitoring data at the central point of each cubic grid into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model to obtain an air quality monitoring rendering map of a target monitoring area; and according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid. In this way, the air quality can be monitored and the air quality situation can be visually demonstrated.
Description
Technical Field
The present invention relates generally to the field of atmospheric environment technology, and more particularly, to a method, an apparatus and a device for visually displaying air quality.
Background
With the development of times, various industries in China are rapidly developed, but a plurality of environmental problems are brought at the same time, particularly the problem of air quality is serious, and the air quality monitoring is particularly important for the health of people in China.
Traditional air quality monitoring process is the aassessment of going on to the whole quality level of air to carry out the early warning based on the assessment result, however under this kind of early warning mechanism, when certain subentry pollutant exceeds standard, probably can't embody in the assessment result of the whole quality of air, lead to the early warning untimely, the early warning result is inaccurate, and can't carry out the audio-visual show to the air quality condition, can't satisfy people's requirement to air quality monitoring.
Disclosure of Invention
According to an embodiment of the present invention, an air quality visualization display scheme is provided. This scheme can carry out visual demonstration to the air quality to carry out the show directly perceived to the air quality condition.
In a first aspect of the invention, an air quality visualization display method is provided. The method comprises the following steps:
constructing a three-dimensional space coordinate system corresponding to a target monitoring area, and establishing a three-dimensional grid model in the three-dimensional space coordinate system;
acquiring air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid;
converting the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model according to the corresponding relation between the color attribute values and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area;
and according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid.
Further, the building a three-dimensional space coordinate system corresponding to the target monitoring area, and building a three-dimensional mesh model in the three-dimensional space coordinate system includes:
establishing a three-dimensional space coordinate system by taking an axis parallel to the direction of the longitude line as an X axis, taking an axis parallel to the direction of the latitude line as a Y axis and taking a direction vertical to the longitude line and the latitude line as a Z axis, so that the target monitoring area is in the three-dimensional space coordinate system;
constructing a three-dimensional grid model in the three-dimensional space coordinate system according to the longitude and latitude information and the preset step length information; the three-dimensional grid model comprises a plurality of cube grids which are closely arranged and have the same size, and the side length of each cube grid is equal to the step length.
Further, the converting the air quality data at the central point of each cube grid in the three-dimensional grid model into a corresponding color attribute value includes:
and respectively processing the air quality monitoring data of each cubic grid into corresponding integers between 0 and 255 through a down-rounding function to serve as the color attribute values.
Further, the color attribute value includes a color RGB value.
Further, the color filling is performed on the cubic grid of the three-dimensional grid model according to the corresponding relationship between the color attribute value and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area, and the method includes:
utilizing a preset mapping library to correspond the air quality monitoring data of the cubic grid of the three-dimensional grid model to different grades of colors;
and filling color to the cubic grid of the three-dimensional grid model according to the corresponding color to obtain an air quality monitoring rendering map of the target monitoring area.
Further, the presetting process of the mapping library comprises the following steps:
setting air quality grade according to the air quality data;
and generating a corresponding grading color bar for each air quality grade, and representing different air quality data in the air quality grade through the grading gradual change color bar.
Further, the performing an air quality pollution early warning prompt on the region corresponding to the cubic grid according to the relationship between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value includes:
calculating the concentration index of each pollutant in the air quality monitoring data of the cubic grid in the three-dimensional grid model, and selecting the maximum value of the pollutant concentration index to determine the concentration index of the corresponding pollutant;
and if the concentration index of the pollutants exceeds the early warning threshold value of the concentration of the pollutants, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid.
In a second aspect of the invention, an air quality visual display device is provided. The device includes:
the model establishing module is used for establishing a three-dimensional space coordinate system corresponding to the target monitoring area and establishing a three-dimensional grid model in the three-dimensional space coordinate system;
the data assignment module is used for acquiring air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid;
the color matching module is used for converting the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model according to the corresponding relation between the color attribute values and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area;
and the early warning prompting module is used for carrying out air quality pollution early warning prompting on the area corresponding to the cubic grid according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value.
In a third aspect of the invention, an electronic device is provided. The electronic device at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect of the invention.
In a fourth aspect of the invention, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of the first aspect of the invention.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of any embodiment of the invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present invention will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
fig. 1 shows a flow chart of an air quality visualization display method according to an embodiment of the invention;
fig. 2 shows a block diagram of an air quality visual display device according to an embodiment of the invention;
FIG. 3 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present invention;
of these, 300 is an electronic device, 301 is a CPU, 302 is a ROM, 303 is a RAM, 304 is a bus, 305 is an I/O interface, 306 is an input unit, 307 is an output unit, 308 is a storage unit, and 309 is a communication unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
According to the invention, the air quality can be accurately monitored, and the monitoring result can be visually displayed.
Fig. 1 shows a flow chart of an air quality visualization display method according to an embodiment of the present invention.
The method comprises the following steps:
s101, a three-dimensional space coordinate system corresponding to a target monitoring area is constructed, and a three-dimensional grid model is built in the three-dimensional space coordinate system.
As an embodiment of the present invention, a three-dimensional space coordinate system is established with an axis parallel to the longitude line direction as an X axis, an axis parallel to the latitude line direction as a Y axis, and a direction perpendicular to the longitude line direction as a Z axis, so that the target monitoring area is within the three-dimensional space coordinate system.
And constructing a three-dimensional grid model in the three-dimensional space coordinate system according to the longitude and latitude information and the preset step length information.
The three-dimensional grid model comprises a plurality of cube grids which are closely arranged and have the same size, and the side length of each cube grid is equal to the step length.
In some embodiments, a three-dimensional grid model (longitude 0 ° -360 °, latitude minus 90 ° -plus 90 °) is divided into a plurality of small grid regions using a 0.2 ° × 0.2 ° binning criterion, and the position of the grid is then represented by the center coordinates of each small grid region. The PSCF value for each grid is the number (x) of contamination tracks in the selected investigation region that pass through that grid (ij)ij) Number (y) of all tracks passing on the gridij) The ratio of (a) to (b), namely:
a larger value of PSCF indicates a larger contribution of the grid. The area corresponding to the high PSCF value is a potential source area influencing the research point. WijIs a weight function. Since PSCF is a conditional probability, the number of all traces (y) that pass through a certain gridij) When small, the value of the PSCF can be subject to significant uncertainty. To reduce this uncertainty, a weight function W is introducedijI.e. y in a certain gridijW is used when the number of the average track end points of each grid in the research area is less than 3 timesijTo reduce the uncertainty of the PSCF. For example, if the study area is divided into 1400 small grids of 0.2 ° × 0.2 °, and the number of all trace points in the area is 18000, the average number of trace end points per grid is about 13, i.e., when y isijLess than about 40, a weighting function is used:
s102, obtaining air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid.
As an embodiment of the present invention, the live data of the contaminants may be collected based on environmental monitoring sensors of a ground observation station. Wherein the pollutants comprise PM2.5, PM10, and SO2、NO、CO、O3And the like.
Because the three-dimensional grid model is divided into grids according to the longitude, the latitude and the height, each cubic grid in the three-dimensional grid model corresponds to specific longitude, latitude information and height information, namely each cubic grid can represent the pollutant concentration value in a cubic area formed by the corresponding longitude, the latitude and the height. And taking the pollutant concentration value at the central point of each cubic grid as the air quality monitoring data of the current cubic grid, namely establishing the association relation between the pollutant concentration value and the cubic grid.
S103, converting the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model according to the corresponding relation between the color attribute values and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area.
The air quality of the target monitoring area can be better displayed by drawing the air quality rendering map, the monitoring function is realized, and the user can obtain better experience.
As an embodiment of the present invention, the air quality monitoring data of each cubic grid is processed into corresponding integers between 0 and 255 as color attribute values, respectively, by a rounding-down function.
Because the air quality monitoring data is generally stored as a binary number of 8 bits (bit), the air quality monitoring data of all cubic grids is processed into integers between 0 and 255, which specifically include:
wherein v is the converted integer value; v is air quality monitoring data of the cubic grid; v. ofminAnd vmaxThe data are monitored for pre-specified minimum and maximum values of air quality. Taking PM2.5 as an example, v may be specifiedmin＝0，vmaxFloor is a floor rounding function, 500. The converted integer value corresponds to an RGB value in the color attribute value.
And extracting the color RGB values corresponding to all cubic grids according to the corresponding relation between the pollutant concentration value and the color RGB values.
And utilizing a preset mapping library to correspond the air quality monitoring data of the cubic grid of the three-dimensional grid model to different grades of colors. And if the air quality monitoring data of the cubic grid falls into the RGB value of a certain grade, filling the color of the corresponding grading color bar into the cubic grid.
And filling color to the cubic grid of the three-dimensional grid model according to the corresponding color to obtain an air quality monitoring rendering map of the target monitoring area.
The preset process of the mapping library comprises the following steps:
setting air quality grade according to the air quality data; specifically, the RGB values may be divided into 1 level every 5 values, i.e., 51 color levels are set in the mapping library. Each color level is a 5-value RGB value.
And generating a corresponding grading color bar for each air quality grade, and representing different air quality data in the air quality grade through the grading gradual change color bar.
The embodiment of the invention realizes accurate acquisition of air quality data, divides the air quality grades, is associated with the color bars, and supports drawing of rendering graphs according to colors of different grades.
As an embodiment of the present invention, a color index corresponding to the air quality prediction data of the cubic grid may also be obtained. Obtaining a corresponding color according to the color index specifically includes:
wherein cIndex represents a color index; v represents air quality monitoring data of the cubic grid; n is a radical ofminRepresents a minimum value of contaminant concentration; n is a radical ofmaxRepresents the maximum value of the contaminant concentration; CLength represents the number of colors of the air quality monitoring rendering graph. The corresponding relation between the color index and the color of the air quality data of each grid is preset, for example, 10 numbers of 1-10 are respectively set, 10 colors are put inside in sequence, and the 6 th color is obtained each time the color is corresponding to the calculated number, for example, the number is 6. The color index corresponding to the air quality monitoring data of the cubic grid is obtained in a formula mode, so that color division is more detailed and scientific, and the cable obtained in the modeThe method is easier to introduce, does not need to manually grade, and has more universality.
And S104, performing air quality pollution early warning prompt on the area corresponding to the cubic grid according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value.
As an embodiment of the present invention, when the air quality monitoring data of the cubic grid in the three-dimensional grid model includes three index values, which are carbon monoxide, PM2.5 and sulfur dioxide, respectively, the step S103 above results in that carbon monoxide is 16, PM2.5 is 150, and sulfur dioxide is 80. And the carbon monoxide threshold value is 20, the PM2.5 threshold value is 60, and the sulfur dioxide threshold value is 20, at this time, it is determined that the detected carbon monoxide is smaller than the carbon monoxide threshold value, the PM2.5 content is greater than the PM2.5 threshold value, and the sulfur dioxide content is greater than the sulfur dioxide threshold value, and then an early warning prompt is performed on the PM2.5 and the sulfur dioxide.
The early warning threshold value of the pollutant concentration can be preset, and can be set according to the air quality target, or according to relevant international standards, national standards or industry standards.
In some embodiments, a pollutant concentration sub-index of each pollutant in the air quality monitoring data of the cubic grid in the three-dimensional grid model is calculated, and a maximum value of the pollutant concentration sub-indexes is selected to determine a concentration index of the corresponding pollutant; and if the concentration index of the pollutants exceeds the early warning threshold value of the concentration of the pollutants, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid.
In this embodiment, first, the concentration value of the pollutant is compared with the early warning threshold value of the corresponding pollutant concentration, and the pollutant concentration index of each pollutant is calculated correspondingly, which specifically includes:
among them, IAQIpIs the pollutant concentration sub-index of the pollutant item P; cPConcentration value of the pollutant item P; BP (Back propagation) ofHiThe sub-index of the pollutant concentration corresponds to the sum C in the pollutant item concentration limit tablePHigh values of similar contaminant concentration limits; BP (Back propagation) ofL0The sub-index of the pollutant concentration corresponds to the sum C in the pollutant item concentration limit tablePLow values of similar contaminant concentration limits; IAQIHiIn the pollutant item concentration limit value table corresponding to the air quality index and BPHi(ii) a corresponding pollutant concentration sub-index; IAQIL0The sub-index of the pollutant concentration is corresponding to the BP in the pollutant item concentration limit tableL0The corresponding contaminant concentration is divided by index.
According to the obtained pollutant concentration sub-index of each pollutant, selecting the maximum value of the pollutant concentration sub-index to determine the pollutant concentration index, and specifically comprising the following steps:
the pollutant concentration index AQI is calculated by the following formula:
AQI＝max{IAQI1、IAQI2、IAQI3、……、IAQIn}
wherein, IAQI is the pollutant concentration index; n is the number of contaminant items.
According to the embodiment of the invention, the air quality can be accurately monitored, and the monitoring result can be visually displayed.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules illustrated are not necessarily required to practice the invention.
The above is a description of method embodiments, and the embodiments of the present invention are further described below by way of apparatus embodiments.
As shown in fig. 2, the apparatus 200 includes:
the model establishing module 210 is configured to establish a three-dimensional space coordinate system corresponding to the target monitoring area, and establish a three-dimensional grid model in the three-dimensional space coordinate system;
the data assignment module 220 is used for acquiring air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid;
the color matching module 230 is configured to convert the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into a corresponding color attribute value, and perform color filling on the cubic grid of the three-dimensional grid model according to a corresponding relationship between the color attribute value and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area;
and the early warning prompting module 240 is configured to perform an early warning prompt of air quality pollution in a region corresponding to the cubic grid according to a relationship between air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
In the technical scheme of the invention, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations without violating the good customs of the public order.
The invention also provides an electronic device and a readable storage medium according to the embodiment of the invention.
FIG. 3 shows a schematic block diagram of an electronic device 300 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
The device 300 comprises a computing unit 301 which may perform various suitable actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Various components in device 300 are connected to I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, or the like; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 301 executes the respective methods and processes described above, such as the methods S101 to S104. For example, in some embodiments, methods S101-S104 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 300 via ROM 302 and/or communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the methods S101-S104 described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the methods S101-S104 by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An air quality visual display method is characterized by comprising the following steps:
constructing a three-dimensional space coordinate system corresponding to a target monitoring area, and establishing a three-dimensional grid model in the three-dimensional space coordinate system;
acquiring air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid;
converting the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model according to the corresponding relation between the color attribute values and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area;
and according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid.
2. The method of claim 1, wherein the constructing a three-dimensional space coordinate system corresponding to the target monitoring area, and the establishing a three-dimensional mesh model in the three-dimensional space coordinate system comprises:
establishing a three-dimensional space coordinate system by taking an axis parallel to the direction of the longitude line as an X axis, taking an axis parallel to the direction of the latitude line as a Y axis and taking a direction vertical to the longitude line and the latitude line as a Z axis, so that the target monitoring area is in the three-dimensional space coordinate system;
constructing a three-dimensional grid model in the three-dimensional space coordinate system according to the longitude and latitude information and the preset step length information; the three-dimensional grid model comprises a plurality of cube grids which are closely arranged and have the same size, and the side length of each cube grid is equal to the step length.
3. The method of claim 1, wherein converting the air quality data at the center point of each cube grid in the three-dimensional grid model to corresponding color attribute values comprises:
and respectively processing the air quality monitoring data of each cubic grid into corresponding integers between 0 and 255 through a down-rounding function to serve as the color attribute values.
4. A method according to claim 1 or 3, wherein the colour attribute values comprise colour RGB values.
5. The method according to claim 1, wherein the obtaining an air quality monitoring rendering map of a target monitoring area by color filling of the cubic grid of the three-dimensional grid model according to the correspondence between the color attribute values and the air quality monitoring data comprises:
utilizing a preset mapping library to correspond the air quality monitoring data of the cubic grid of the three-dimensional grid model to different grades of colors;
and filling color to the cubic grid of the three-dimensional grid model according to the corresponding color to obtain an air quality monitoring rendering map of the target monitoring area.
6. The method of claim 5, wherein the pre-setting process of the mapping library comprises:
setting air quality grade according to the air quality data;
and generating a corresponding grading color bar for each air quality grade, and representing different air quality data in the air quality grade through the grading gradual change color bar.
7. The method according to claim 1, wherein the performing an air quality pollution early warning prompt on the region corresponding to the cubic grid according to the relationship between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold comprises:
calculating the concentration index of each pollutant in the air quality monitoring data of the cubic grid in the three-dimensional grid model, and selecting the maximum value of the pollutant concentration index to determine the concentration index of the corresponding pollutant;
and if the concentration index of the pollutants exceeds the early warning threshold value of the concentration of the pollutants, carrying out air quality pollution early warning prompt on the area corresponding to the cubic grid.
8. An air quality visual display device, comprising:
the model establishing module is used for establishing a three-dimensional space coordinate system corresponding to the target monitoring area and establishing a three-dimensional grid model in the three-dimensional space coordinate system;
the data assignment module is used for acquiring air quality data of the target monitoring area, and taking the air quality data at the central point of each cubic grid in the three-dimensional grid model as the air quality monitoring data of the cubic grid;
the color matching module is used for converting the air quality monitoring data at the central point of each cubic grid in the three-dimensional grid model into corresponding color attribute values, and performing color filling on the cubic grid of the three-dimensional grid model according to the corresponding relation between the color attribute values and the air quality monitoring data to obtain an air quality monitoring rendering map of a target monitoring area;
and the early warning prompting module is used for carrying out air quality pollution early warning prompting on the area corresponding to the cubic grid according to the relation between the air quality monitoring data of the cubic grid in the three-dimensional grid model and a preset early warning threshold value.
9. An electronic device, at least one processor; and
a memory communicatively coupled to the at least one processor; it is characterized in that the preparation method is characterized in that,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114612586A (en) * | 2022-05-10 | 2022-06-10 | 杭州比智科技有限公司 | Color grading rendering method and system based on data visualization scene |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108802296A (en) * | 2018-07-13 | 2018-11-13 | 无锡太湖学院 | A kind of atmosphere environment supervision method for early warning and system |
| CN109946418A (en) * | 2017-12-21 | 2019-06-28 | 北京航天泰坦科技股份有限公司 | A kind of air quality monitoring and evaluation method and system |
| CN112100306A (en) * | 2020-09-17 | 2020-12-18 | 中科三清科技有限公司 | Air quality drop area forecast map drawing method and device and storage medium |
| CN112559665A (en) * | 2020-12-18 | 2021-03-26 | 中科三清科技有限公司 | Air quality mode forecast data visualization method and device |
| CN112597260A (en) * | 2020-12-17 | 2021-04-02 | 中科三清科技有限公司 | Visualization method and device for air quality mode forecast data |
| CN113159428A (en) * | 2021-04-26 | 2021-07-23 | 青岛大学 | Traffic flow prediction method, electronic device, and storage medium |
| CN113283630A (en) * | 2021-04-09 | 2021-08-20 | 中科三清科技有限公司 | Air quality prediction method, device, equipment and computer readable storage medium |
| CN113516327A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Petrochemical enterprise pollution monitoring and early warning evaluation method, device and system |
| CN113626548A (en) * | 2021-08-04 | 2021-11-09 | 南开大学 | Regional source contribution positioning and quantifying method based on mountain background point location |
| CN113642263A (en) * | 2021-10-18 | 2021-11-12 | 中科三清科技有限公司 | Air quality early warning method and device based on Beidou grid |
| CN113655175A (en) * | 2021-08-05 | 2021-11-16 | 重庆亿森动力环境科技有限公司 | Gridding air monitoring method, system, computer equipment and storage medium |
| CN113688555A (en) * | 2021-10-25 | 2021-11-23 | 清华大学深圳国际研究生院 | Water body pollution diffusion simulation prediction method and device based on concentration analysis |
| CN113688493A (en) * | 2021-05-18 | 2021-11-23 | 武汉理工大学 | Atmospheric pollution potential source area identification method based on pollution process typing |
| CN113740221A (en) * | 2021-09-07 | 2021-12-03 | 天津大学 | Air pollution source region determination method based on fine particulate matters and ozone |
-
2021
- 2021-12-16 CN CN202111544351.5A patent/CN114241157A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109946418A (en) * | 2017-12-21 | 2019-06-28 | 北京航天泰坦科技股份有限公司 | A kind of air quality monitoring and evaluation method and system |
| CN108802296A (en) * | 2018-07-13 | 2018-11-13 | 无锡太湖学院 | A kind of atmosphere environment supervision method for early warning and system |
| CN113516327A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Petrochemical enterprise pollution monitoring and early warning evaluation method, device and system |
| CN112100306A (en) * | 2020-09-17 | 2020-12-18 | 中科三清科技有限公司 | Air quality drop area forecast map drawing method and device and storage medium |
| CN112597260A (en) * | 2020-12-17 | 2021-04-02 | 中科三清科技有限公司 | Visualization method and device for air quality mode forecast data |
| CN112559665A (en) * | 2020-12-18 | 2021-03-26 | 中科三清科技有限公司 | Air quality mode forecast data visualization method and device |
| CN113283630A (en) * | 2021-04-09 | 2021-08-20 | 中科三清科技有限公司 | Air quality prediction method, device, equipment and computer readable storage medium |
| CN113159428A (en) * | 2021-04-26 | 2021-07-23 | 青岛大学 | Traffic flow prediction method, electronic device, and storage medium |
| CN113792929A (en) * | 2021-04-26 | 2021-12-14 | 青岛大学 | Traffic flow prediction method, electronic device, and storage medium |
| CN113688493A (en) * | 2021-05-18 | 2021-11-23 | 武汉理工大学 | Atmospheric pollution potential source area identification method based on pollution process typing |
| CN113626548A (en) * | 2021-08-04 | 2021-11-09 | 南开大学 | Regional source contribution positioning and quantifying method based on mountain background point location |
| CN113655175A (en) * | 2021-08-05 | 2021-11-16 | 重庆亿森动力环境科技有限公司 | Gridding air monitoring method, system, computer equipment and storage medium |
| CN113740221A (en) * | 2021-09-07 | 2021-12-03 | 天津大学 | Air pollution source region determination method based on fine particulate matters and ozone |
| CN113642263A (en) * | 2021-10-18 | 2021-11-12 | 中科三清科技有限公司 | Air quality early warning method and device based on Beidou grid |
| CN113688555A (en) * | 2021-10-25 | 2021-11-23 | 清华大学深圳国际研究生院 | Water body pollution diffusion simulation prediction method and device based on concentration analysis |
Non-Patent Citations (4)
| Title |
|---|
| 国家环境保护局，中国环境科学研究院: "《城市大气污染总量控制方法手册》", 30 April 1991 * |
| 庄国顺: "《大气溶胶和雾霾新论》", 31 December 2019 * |
| 李理，梁红: "《环境监测（新2版）》", 31 December 2018 * |
| 毕硕本等: "气象数据标量场的建模与可视化研究", 《系统仿真学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114612586A (en) * | 2022-05-10 | 2022-06-10 | 杭州比智科技有限公司 | Color grading rendering method and system based on data visualization scene |
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