Particulate matter concentration monitoring method, apparatus, terminal device, and readable storage medium

Abstract

The application belongs to the field of particulate matter concentration monitoring, and particularly relates to a particulate matter concentration monitoring method and device, a terminal device and a readable storage medium. The method is applied to a terminal device, and the terminal device is configured with a camera assembly. The method comprises the following steps: acquiring image information of particulate matter collected by the camera assembly; determining the type of the particulate matter according to the image information; determining the mass of each type of the particulate matter based on the type of the particulate matter; and determining the concentration of each type of the particulate matter according to the mass of each type of the particulate matter and the space occupied by the particulate matter. That is, the image information of the particulate matter is collected by the camera assembly configured on the terminal device, the mass of each type of the particulate matter is determined according to the image information, the concentration of each type of the particulate matter is determined according to the mass of each type of the particulate matter and the space occupied by the particulate matter, and the particulate matter concentration is monitored in real time in the terminal device.

Description

Technical Field

[0001] This application belongs to the field of particulate matter concentration monitoring, and in particular relates to a particulate matter concentration monitoring method, device, terminal equipment and readable storage medium. Background Technology

[0002] Air quality affects people's quality of life. The meteorological bureau releases ambient air quality data daily, but this data is only based on average values ​​calculated from a few monitoring stations to reflect air quality over a large area. It is difficult to accurately and in real time reflect the air quality in a local area.

[0003] Many manufacturers have launched miniaturized devices for monitoring PM2.5, PM10, and other particulate matter in localized areas. However, these miniaturized devices cannot be integrated with terminal equipment and cannot monitor particulate matter concentration in real time. Summary of the Invention

[0004] This application provides a method, apparatus, terminal device, and readable storage medium for monitoring particulate matter concentration, which can monitor particulate matter concentration in real time in the terminal device.

[0005] In a first aspect, embodiments of this application provide a method for monitoring particulate matter concentration, applied to a terminal device, the terminal device being equipped with a camera component; the method includes:

[0006] Acquire image information of particulate matter captured by the camera component;

[0007] Based on the image information, determine the type of particulate matter;

[0008] Based on the type of particulate matter, determine the mass of each type of particulate matter;

[0009] The concentration of each type of particulate matter is determined based on the mass of each type of particulate matter and the space occupied by the particulate matter.

[0010] In one possible implementation of the first aspect, after acquiring the image information of particulate matter captured by the camera component, the following is included:

[0011] Obtain the clarity of particles in the image information;

[0012] Based on the clarity of the particles, the particles are filtered to obtain image information showing that the particles are located within the depth of field of the camera assembly.

[0013] The step of determining the concentration of each type of particulate matter based on its mass and the space it occupies includes:

[0014] Determine the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera assembly;

[0015] The space occupied by the particles is determined based on the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera assembly.

[0016] The concentration of each type of particulate matter is determined based on the mass of each type of particulate matter and the space occupied by the particulate matter.

[0017] The terminal device is configured with a physical cavity, and a measurement cavity is configured within the physical cavity. The measurement cavity is located within the field of view and depth of field of the camera assembly. Acquiring image information of particulate matter captured by the camera assembly includes:

[0018] Image information of particulate matter within the measurement chamber is acquired.

[0019] The concentration of each type of particulate matter is determined based on its mass and the space it occupies, including:

[0020] Determine the volume of the measuring cavity;

[0021] The concentration of the particulate matter is determined based on the mass of each type of particulate matter and the volume of the measuring chamber.

[0022] The step of determining the type of particulate matter based on the image information includes:

[0023] Based on the image information, the type of particulate matter and the quantity of each type of particulate matter are determined.

[0024] The step of determining the mass of each type of particulate matter based on its type includes:

[0025] The mass of each type of particulate matter is determined based on the type of particulate matter, the average density of each type of particulate matter, and the quantity of each type of particulate matter.

[0026] The camera component includes a macro lens.

[0027] Secondly, embodiments of this application provide a particulate matter concentration monitoring device, applied to a terminal device, the terminal device being equipped with a camera component; the device includes:

[0028] The acquisition module is used to acquire image information of particulate matter collected by the camera component;

[0029] The first determining module is used to determine the type of particulate matter based on the image information;

[0030] The second determining module is used to determine the mass of each type of particulate matter based on the type of particulate matter.

[0031] The third determining module is used to determine the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter.

[0032] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the particulate matter concentration monitoring method as described in the first aspect.

[0033] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the particulate matter concentration monitoring method as described in the first aspect.

[0034] The beneficial effects of this application embodiment compared with the prior art are as follows: The terminal device of this application is equipped with a camera component; it acquires image information of particulate matter collected by the camera component; it determines the type of particulate matter based on the image information; it determines the mass of each type of particulate matter based on the type of particulate matter; and it determines the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter. In other words, this application acquires image information of particulate matter through the camera component configured in the terminal device, determines the mass of each type of particulate matter based on the image information, and determines the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter, thereby realizing real-time monitoring of particulate matter concentration in the terminal device. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic diagram illustrating an application scenario of the particulate matter concentration monitoring method provided in an embodiment of this application;

[0037] Figure 2 This is a schematic flowchart of a particulate matter concentration monitoring method provided in an embodiment of this application;

[0038] Figure 3 This is a schematic diagram of the structure of a particulate matter concentration monitoring device provided in an embodiment of this application;

[0039] Figure 4 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0040] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary detail. In other instances, specific technical details in various embodiments can be referred to mutually, and specific systems not described in one embodiment can be referred to in other embodiments.

[0041] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0042] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0043] References to "embodiments of this application" or "some embodiments" in this specification mean that one or more embodiments of this application include specific features, structures, or characteristics described in connection with that embodiment. Therefore, phrases such as "in other embodiments," "an embodiment of this application," and "other embodiments of this application" appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0044] Furthermore, in the description of this application and the appended claims, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0045] Air quality affects people's quality of life. The meteorological bureau releases ambient air quality data daily, but this data is only based on average values ​​calculated from a few monitoring stations to reflect air quality over a large area. It is difficult to accurately and in real time reflect the air quality in a local area.

[0046] Many manufacturers have launched miniaturized devices for monitoring PM2.5, PM10, and other particulate matter in localized areas. However, these miniaturized devices cannot be integrated with terminal equipment and cannot monitor particulate matter concentration in real time.

[0047] To address the aforementioned deficiencies, the inventive concept of this application is as follows:

[0048] This application acquires image information of particulate matter through a camera component configured in a terminal device, determines the mass of each type of particulate matter based on the image information, and determines the concentration of each type of particulate matter based on the mass and the space occupied by the particulate matter, thereby enabling real-time monitoring of particulate matter concentration in the terminal device.

[0049] To illustrate the technical solution of this application, specific embodiments are described below.

[0050] Please refer to Figure 1 , Figure 1 This is a schematic diagram illustrating an application scenario of the particulate matter concentration monitoring method provided in an embodiment of this application. For ease of explanation, only the parts relevant to this application are shown. The application scenario includes a terminal device 10, which can be a mobile phone, tablet computer, other terminal device, in-vehicle device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), or other terminal device. This application embodiment does not impose any restrictions on the specific type of terminal device.

[0051] For example, the terminal device may be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a set-top box (STB), customer premises equipment (CPE), and / or other devices used for communication over a wireless system, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Network (PLMN) networks.

[0052] As an example and not a limitation, when the terminal device is a wearable device, the term "wearable device" can also refer to any device that utilizes wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices worn directly on the body or integrated into a user's clothing or accessories. Wearable devices are not merely hardware devices; they achieve powerful functions through software support, data interaction, and cloud interaction. Broadly defined, wearable smart devices include those with comprehensive functions, large sizes, and the ability to perform complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those focused on a specific application function that require interaction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0053] The terminal device 10 is specifically used to acquire image information of particulate matter collected by the camera component, process the image information, and determine the concentration of each type of particulate matter.

[0054] The terminal device 10 includes a camera assembly 101, a physical cavity 102, and a measurement cavity 103.

[0055] The camera assembly 101 can be a binocular camera, a trinocular camera, or other multi-view cameras, etc. This application embodiment does not limit the structural type of the camera assembly 101. The camera assembly 101 is connected to the solid cavity 102 and is used to photograph particulate matter within the solid cavity 102. In some embodiments, the camera assembly includes a microscope lens for photographing smaller diameter particles, such as PM2.5.

[0056] In this application scenario, there are two ways for particulate matter to enter the solid cavity 102. The first is that a fan or air pump installed inside the solid cavity 102 draws particulate matter from outside the solid cavity 102 into the solid cavity 102 through the air inlet. The second is that the particulate matter diffuses freely into the solid cavity 102 through the air inlet. Compared with the first method, the particulate matter in the solid cavity is more uniform in the second method.

[0057] A measurement cavity 103 is disposed within the solid cavity 102. The measurement cavity 103 is located within the viewing angle and depth range of the camera assembly 101. The viewing angle of the camera assembly 101 is its field of view (FOV), and the size of the FOV determines the field of view of the camera assembly 101. FOV is divided into horizontal field of view (HFOV), vertical field of view (VFOV), and diagonal field of view (DFOV).

[0058] The angle of FOV is related to the focal length of the camera module and the size of the imaging surface of the camera module. The angle of FOV can be calculated based on the size of the camera module and the size of the imaging surface of the camera module.

[0059] In other embodiments, the angle of the field of view can also be obtained by measurement. The measuring instrument can be a wide-angle collimator. The specific measurement method is as follows: at one end of the camera assembly 101, observe the scale on the bottom glass plane of the wide-angle collimator, read its angle value, and the maximum scale value is the field of view of the camera assembly.

[0060] In this embodiment of the application, the field of view can be 40 degrees, 60 degrees, and 75 degrees, etc., and the size of the field of view is not limited in this embodiment of the application.

[0061] Depth of field range refers to the range of distances between particles and the camera component 101 when the camera component 101 can obtain a clear image. The depth of field range can be calculated based on the parameters of the camera component 101, such as the lens focal length and the aperture value of the lens. For specific calculation methods, please refer to other embodiments.

[0062] In this application scenario, the particulate matter located in the measuring cavity 103 is clearly imaged in the camera component 101.

[0063] Please refer to Figure 2 , Figure 2 This is a schematic flowchart of a particulate matter concentration monitoring method provided in an embodiment of this application. Figure 2 The execution entity of the method in the middle can be Figure 1 Terminal device 10 in the middle. For example... Figure 2 As shown, the method includes: S201 to S204.

[0064] S201. Acquire image information of particulate matter collected by the camera component.

[0065] Specifically, in this application embodiment, there are two ways to obtain image information of particulate matter collected by the camera component. The first is that the terminal device does not have a physical cavity configured, and the camera component directly collects image information of particulate matter in the air. The camera component transmits the collected image information to the terminal device, and the terminal device can then obtain the image information of particulate matter collected by the camera component.

[0066] After acquiring image information of particulate matter collected by the camera component, the clarity of the particulate matter in the image information is obtained.

[0067] Specifically, when the camera module captures particulate matter, a clear image can only be obtained if the distance between the particulate matter and the camera module is within the depth of field of the camera module. If the particulate matter is too close or too far from the camera module and exceeds the depth of field of the camera module, the particulate matter will appear as a blurry image in the camera module.

[0068] In this embodiment of the application, whether the image of particulate matter formed in the camera component is clear can be measured by sharpness.

[0069] In this embodiment, the sharpness of particles in the image information can be obtained by using the Brenner gradient function, Tenengrad gradient function, and Laplacian gradient function, etc. This embodiment does not limit the method for calculating the sharpness of particles.

[0070] For example, the Brenner gradient function is:

[0071] D(f)=∑ y ∑ x |f(x+2,y)-f(x,y)| 2 .

[0072] Where D(f) is the calculation result of the sharpness of particles in the image information, f(x+2, y) represents the gray value of the pixel (x+2, y) corresponding to the particle, and f(x, y) represents the gray value of the pixel (x+2, y) corresponding to the particle.

[0073] After obtaining the sharpness of particles in the image, the particles are filtered according to their sharpness to obtain image information of the particles within the depth of field of the camera component.

[0074] Specifically, in this embodiment of the application, after obtaining the clarity of particles in the image, the particles can be filtered according to a preset clarity value range. The preset clarity value range is related to the depth of field range of the camera component. The clarity of particles located at the minimum value of the depth of field range is taken as the minimum value of the preset clarity value range, and the clarity of particles located at the maximum value of the depth of field range is taken as the maximum value of the preset clarity value range.

[0075] In this embodiment of the application, after obtaining the clarity of particles in the image, it can be determined whether the clarity of the particles is within a preset clarity value range. If not, the image information of the particles is filtered out, and the image information of that part is replaced by the background image, so as to finally obtain the image information of the particles within the depth range of the camera component.

[0076] The second method involves configuring a physical cavity within the terminal device, and placing a measurement cavity within this cavity. This measurement cavity is located within the field of view and depth of field of the camera assembly. In this method, image information of particulate matter captured by the camera assembly is obtained, including:

[0077] Acquire image information of particulate matter within the measurement chamber.

[0078] Specifically, the camera module acquires image information of particles within the physical cavity, including image information of particles within the measurement cavity. Since the measurement cavity is located within the viewing angle and depth of field of the camera module, the clarity of the particles in the image information within the measurement cavity is within a preset clarity value range.

[0079] In this embodiment of the application, the image of the particles in the measurement cavity can be processed by the Region of Interest (ROI) to obtain the image information of the particles in the measurement cavity.

[0080] S202. Determine the type of particulate matter based on the image information.

[0081] Specifically, after acquiring image information using S201, the image information first needs to be preprocessed. Image preprocessing includes image grayscale conversion and grayscale stretching. Image grayscale conversion converts a color image into a grayscale image to speed up subsequent image processing; grayscale stretching enhances image contrast, making the grayscale distribution fill the entire grayscale range, which is beneficial for image feature extraction.

[0082] Secondly, feature extraction is performed on the preprocessed image.

[0083] In this embodiment of the application, feature extraction involves extracting color features, texture features, and edge features from the image.

[0084] In this embodiment, color features can be extracted using grayscale histograms. Texture features can be extracted using methods such as bitmap loading, calculating the grayscale co-occurrence matrix, and calculating texture features. Edge features can be extracted using methods such as the Roberts operator, Sobel operator, and Prewitt operator based on template operators.

[0085] Then, based on the image information, the type of particulate matter and the quantity of each type of particulate matter are determined.

[0086] In this embodiment of the application, after feature extraction is performed on the preprocessed image, the extracted features are input into a trained neural network model, which outputs the type of particulate matter.

[0087] In this application embodiment, particulate matter is classified into different types based on its aerodynamic equivalent diameter in ambient air. In some embodiments, particulate matter is classified into two types: PM2.5 and PM10.

[0088] The neural network model in this embodiment can be a backpropagation (BP) neural network model. When using a BP neural network model to process images, it needs to be trained. The training steps are as follows:

[0089] Acquire multiple sets of PM2.5 sample images (each set of PM2.5 sample images contains a different number of PM2.5 particles) and multiple sets of PM10 sample images (each set of PM10 sample images contains a different number of PM10 particles).

[0090] Preprocessing and feature extraction were performed on multiple sets of PM2.5 sample images and multiple sets of PM10 sample images.

[0091] The extracted features are input into a backpropagation (BP) neural network model for training. The parameters of the neural network are optimized. When the training iterations reach a preset number, training stops, and the optimized parameters are stored. The preset number of iterations in this embodiment can be set according to actual conditions.

[0092] In this embodiment of the application, the extracted features are input into a trained neural network model, and the output particulate matter type may be PM2.5, PM10, or both PM2.5 and PM10.

[0093] In addition to outputting the particulate matter type, it also outputs the quantity of each type of particulate matter.

[0094] For example, the output type is PM2.5 (e.g., quantity is 1000), the output type is PM10 (e.g., quantity is 500), and the output type is both PM2.5 (e.g., quantity is 1000) and PM10 (e.g., quantity is 500).

[0095] S203. Determine the mass of each type of particulate matter based on its type.

[0096] In some embodiments, the mass of each type of particulate matter is determined based on the type of particulate matter, the average density of each type of particulate matter, and the quantity of each type of particulate matter.

[0097] Specifically, the volume of a given type of particulate matter can be calculated based on the type of particulate matter and the quantity of each type.

[0098] For example, if there are 1000 PM2.5 particles in an image, the volume of PM2.5 in the image can be calculated using the following formula:

[0099]

[0100] For example, if there are 500 PM10 particles in an image, the volume of PM10 in the image can be calculated using the following formula:

[0101]

[0102] In this embodiment of the application, the mass of each type of particulate matter can be determined by the volume of each type of particulate matter and the average density of each type of particulate matter.

[0103] In this embodiment of the application, the terminal device pre-stores the average density of each type of particulate matter.

[0104] To calculate the average density of each type of particulate matter in advance, it is necessary to collect each type of particulate matter beforehand, measure the weight of each type of particulate matter and the volume of each type of particulate matter collected. Based on the weight and volume, the average density of each type of particulate matter can be calculated.

[0105] In this embodiment of the application, the weight of each type of particulate matter can be measured by the filter membrane dust measurement method.

[0106] The volume of each type of particulate matter collected can be measured using laser measurement.

[0107] S204. Determine the concentration of each type of particulate matter based on its mass and the space it occupies.

[0108] In this embodiment, the space occupied by particulate matter is calculated in two ways depending on whether the terminal device has a physical cavity. The first method is when the terminal device does not have a physical cavity, the space occupied by particulate matter can be calculated as follows:

[0109] First, determine the permissible circle of confusion diameter, foreground depth of field, and background depth of field of the camera assembly.

[0110] Specifically, the permissible circle diameter can be calculated using the following formula:

[0111]

[0112] Where δ represents the diameter of the permissible circle of confusion, f represents the focal length of the camera module, H represents the size of the particle, and F represents the aperture number of the camera module.

[0113] The depth of field can be calculated using the following formula:

[0114] ΔL1=f+F*δ*L.

[0115] Where ΔL1 represents the depth of field and L represents the focusing distance.

[0116] The depth of field can be calculated using the following formula:

[0117] ΔL2=fF*δ*L.

[0118] Where ΔL2 represents the back depth of field length.

[0119] Secondly, the space occupied by particles is determined based on the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera component.

[0120] Specifically, since light converges and then diffuses before and after the focal point of the camera component, and the image becomes clearer and then blurrier, there is an allowable circle of confusion before and after the focal point. These two allowable circles of confusion and the focal point form two cones. The space occupied by the particles can be obtained by calculating the volume of the cones.

[0121] The space occupied by particulate matter can be calculated using the following formula:

[0122]

[0123] Where V represents the space occupied by particulate matter.

[0124] The second method involves configuring a physical cavity in the terminal device. When a measuring cavity is configured in the physical cavity, the volume of the measuring cavity is the space occupied by the particulate matter.

[0125] For example, when the measuring cavity configured in the solid cavity is a cuboid, the space occupied by the particulate matter can be calculated using the following formula:

[0126] V = a * b * h

[0127] Where a represents the length of the measuring cavity, b represents the width of the measuring cavity, and h represents the height of the measuring cavity.

[0128] It should be noted that when using the second method to calculate the space occupied by particulate matter, the parameters of the measuring cavity (such as length, width, and height) are pre-stored in the terminal device.

[0129] In this embodiment, the concentration of each type of particulate matter can be determined by determining the mass of each type of particulate matter and the calculated space occupied by the particulate matter in step S203. The concentration of each type of particulate matter can be expressed by the following formula:

[0130]

[0131] In this embodiment of the application, alarm values ​​for the concentration of each type of particulate matter can be pre-stored in the terminal device. If the concentration values ​​of the type of particulate matter monitored by the terminal device exceed the alarm value within a preset time period, an alarm will be triggered.

[0132] For example: the PM2.5 concentration monitored by the terminal device exceeded 75 μg / m³ within 24 hours. 3 If so, an alarm will be triggered.

[0133] In summary, this application acquires image information of particulate matter through a camera component configured in a terminal device, determines the mass of each type of particulate matter based on the image information, and determines the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter, thereby realizing real-time monitoring of particulate matter concentration in the terminal device.

[0134] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0135] Please refer to Figure 3 , Figure 3 This is a schematic diagram of a particulate matter concentration monitoring device provided in an embodiment of this application. The device is applied to a terminal device, which is equipped with a camera assembly. The device includes:

[0136] The acquisition module 31 is used to acquire image information of particulate matter collected by the camera component.

[0137] The first determining module 32 is used to determine the type of particulate matter based on image information.

[0138] The second determining module 33 is used to determine the mass of each type of particulate matter based on the type of particulate matter.

[0139] The third determining module 34 is used to determine the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by each particulate matter.

[0140] The device also includes:

[0141] The acquisition unit is used to acquire the clarity of particles in the image information.

[0142] A filtering unit is used to filter the particles according to their sharpness to obtain image information of the particles within the depth of field of the camera assembly.

[0143] The third determining module 34 is also used to determine the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera component;

[0144] The space occupied by particles is determined based on the permissible circle of confusion diameter, foreground depth of field, and background depth of field of the camera assembly.

[0145] The concentration of each type of particulate matter is determined based on its mass and the space it occupies.

[0146] The terminal device is equipped with a physical cavity, and a measurement cavity is configured inside the physical cavity. The measurement cavity is located within the field of view and depth of field of the camera component. The acquisition module 31 is also used to acquire image information of particulate matter inside the measurement cavity.

[0147] The third determining module 34 is also used to determine the volume of the measuring cavity.

[0148] The concentration of particulate matter is determined based on the mass of each type of particulate matter and the volume of the measuring chamber.

[0149] The first determining module 32 is also used to determine the type of particulate matter and the quantity of each type of particulate matter based on the image information.

[0150] The second determining module 33 is also used to determine the mass of each type of particulate matter based on the type of particulate matter, the average density of each type of particulate matter, and the quantity of each type of particulate matter.

[0151] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0152] like Figure 4 As shown, this application embodiment also provides a terminal device 500, including a memory 21, a processor 22, and a computer program 23 stored in the memory 21 and executable on the processor 22. When the processor 22 executes the computer program 23, it implements the particulate matter concentration monitoring methods of the above embodiments.

[0153] The processor 22 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0154] The memory 21 can be an internal storage unit of the terminal device 500. The memory 21 can also be an external storage device of the terminal device 500, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device 500. Furthermore, the memory 21 can include both internal and external storage units of the terminal device 500. The memory 21 is used to store computer programs and other programs and data required by the terminal device 500. The memory 21 can also be used to temporarily store data that has been output or will be output.

[0155] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the particulate matter concentration monitoring methods of the above embodiments.

[0156] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the particulate matter concentration monitoring methods described in the above embodiments.

[0157] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include at least: any entity or device capable of carrying the computer program code to a photographing device / base station, a recording medium, a computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable storage media cannot be electrical carrier signals or telecommunication signals.

[0158] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0159] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0160] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0161] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for monitoring particulate matter concentration, characterized in that, The method is applied to a terminal device, wherein the terminal device is configured with a camera component; the terminal device is a mobile phone or a tablet computer, and the method includes: Acquire image information of particulate matter captured by the camera component; Based on the image information, determine the type of particulate matter; Based on the type of particulate matter, determine the mass of each type of particulate matter; The concentration of each type of particulate matter is determined based on the mass of each type of particulate matter and the space occupied by each particulate matter. The step of acquiring the image information of particulate matter collected by the camera component includes: Obtain the clarity of particles in the image information; Based on the sharpness of the particles and a preset sharpness value range, the particles are filtered to obtain image information of the particles located within the depth of field of the camera component. The preset sharpness value range is related to the depth of field of the camera component. The determination of the concentration of each type of particulate matter based on its mass and the space it occupies includes: Determine the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera assembly; The space occupied by the particles is determined based on the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera assembly. The concentration of each type of particulate matter is determined based on the mass of each type of particulate matter and the space occupied by each type of particulate matter; Determining the mass of each type of particulate matter based on its type includes: determining the type of particulate matter and the quantity of each type of particulate matter based on the image information; The mass of each type of particulate matter is determined based on the type of particulate matter, the average density of each type of particulate matter, and the quantity of each type of particulate matter.

2. The monitoring method according to claim 1, characterized in that, The terminal device is configured with a physical cavity, and a measurement cavity is configured within the physical cavity. The measurement cavity is located within the field of view and depth of field of the camera assembly. Acquiring image information of particulate matter captured by the camera assembly includes: Image information of particulate matter within the measurement chamber is acquired.

3. The monitoring method according to claim 2, characterized in that, Determining the concentration of each type of particulate matter based on its mass and the space it occupies includes: Determine the volume of the measuring cavity; The concentration of the particulate matter is determined based on the mass of each type of particulate matter and the volume of the measuring chamber.

4. The monitoring method according to any one of claims 1 to 3, characterized in that, The camera assembly includes a macro lens.

5. A particulate matter concentration monitoring device, characterized in that, Applied to a terminal device, wherein the terminal device is a mobile phone or tablet computer, and the terminal device is equipped with a camera component; the device includes: The acquisition module is used to acquire image information of particulate matter collected by the camera component; The first determining module is used to determine the type of particulate matter based on the image information; The second determining module is used to determine the mass of each type of particulate matter based on the type of particulate matter. The third determining module is used to determine the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter; The device further includes: The acquisition unit is used to acquire the clarity of particles in the image information; A filtering unit is used to filter the particles according to the sharpness of the particles and a preset sharpness value range, and obtain image information of the particles located within the depth of field of the camera component, wherein the preset sharpness value range is related to the depth of field of the camera component. The third determining module is also used to determine the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera component; determine the space occupied by particulate matter based on the permissible circle of confusion diameter, foreground depth of field length, and background depth of field length of the camera component; and determine the concentration of each type of particulate matter based on the mass of each type of particulate matter and the space occupied by the particulate matter. The first determining module is further configured to determine the type of particulate matter and the quantity of each type of particulate matter based on the image information; The second determining module is further configured to determine the quality of each type of particulate matter based on the type of particulate matter, the average density of each type of particulate matter, and the quantity of each type of particulate matter.

6. A terminal device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the particulate matter concentration monitoring method as described in any one of claims 1 to 4.

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