Flying dust noise online monitoring control method and system based on industrial internet of things

Abstract

The invention discloses a flying dust and noise online monitoring control method and system based on the industrial Internet of Things, and the method comprises the following steps: obtaining a positioning detection instruction of a flying dust pollution source and / or a noise pollution source in response to a flying dust monitoring alarm and / or a noise monitoring alarm; in response to the positioning detection instruction of the flying dust pollution source, obtaining a first initial orientation of the flying dust pollution source; controlling the unmanned aerial vehicle to fly towards the first initial direction so as to confirm the actual position information of the flying dust pollution source; obtaining a second initial orientation of the noise pollution source in response to a positioning detection instruction of the noise pollution source; and controlling the unmanned aerial vehicle to fly towards the second initial orientation so as to confirm the actual position information of the noise pollution source, and the method has the advantage that the orientation of the pollution source can be rapidly and accurately positioned.

Description

Technical Field

[0001] This application relates to the field of dust and noise monitoring technology, and in particular to a method and system for online monitoring and control of dust and noise based on the Industrial Internet of Things. Background Technology

[0002] In construction operations, it is necessary to monitor dust and noise pollution in real time in order to promptly warn construction workers to operate in a standardized manner or to replenish noise reduction and dust suppression facilities. However, existing dust and noise monitoring methods can only detect whether dust and noise exceed the standards and are only suitable for monitoring within a small area. When the source of dust and noise pollution is far away, it is difficult to quickly and accurately locate the source. After receiving the alarm information, staff still need to manually check and confirm the location of the pollution source, resulting in poor timeliness. Summary of the Invention

[0003] The main purpose of this application is to provide a method and system for online monitoring and control of dust and noise based on the Industrial Internet of Things, which aims to solve the technical problem that existing dust and noise monitoring methods are unable to quickly and accurately locate the source of pollution.

[0004] To achieve the above objectives, this application provides an online monitoring and control method for dust and noise based on the Industrial Internet of Things, used to control a dust and noise monitoring device. The device includes an AGV vehicle, a column is installed on the top of the AGV vehicle, a control cabinet is installed on the column, a drone is installed inside the control cabinet, the drone is equipped with a camera and a noise detector, and a dust detector and a noise detector are also installed on the control cabinet. The method includes the following steps: In response to dust monitoring alarms and / or noise monitoring alarms, obtain location detection commands for dust pollution sources and / or noise pollution sources; In response to the location detection command of the dust pollution source, the initial location of the dust pollution source is obtained; Control the drone to fly towards the initial orientation to confirm the actual location information of the dust pollution source; In response to the noise pollution source location detection command, the second initial location of the noise pollution source is obtained; Control the drone to fly towards the second initial orientation to confirm the actual location information of the noise pollution source.

[0005] Optionally, the first initial location of the dust pollution source is obtained, including: Obtain current wind direction information; Based on the current wind direction information, a straight detection trajectory is planned; the straight detection trajectory is perpendicular to the current wind direction. Multiple first detection points with preset spacing are uniformly selected on the straight detection trajectory, and the AGV is controlled to move to each first detection point to obtain the dust concentration detected at different first detection points. The first detection point corresponding to the maximum value among multiple dust concentrations detected at different first detection points is used as the first reference point to obtain the first initial orientation of the dust pollution source; wherein, the first initial orientation is perpendicular to the straight detection trajectory and opposite to the current wind direction.

[0006] Optionally, the first detection point corresponding to the maximum value among multiple dust concentrations is used as the first reference point to obtain the first initial location of the dust pollution source, including: Based on the first reference point, a second reference point is obtained; wherein, the second reference point is the first detection point corresponding to the larger value of the dust concentration among the two first detection points adjacent to the first reference point; Multiple second detection points are evenly selected between the first and second reference points; The AGV is controlled to move to each of the second detection points to obtain the dust concentration detected at different second detection points; The second detection point corresponding to the maximum value among multiple dust concentrations detected at different second detection points is used as the third benchmark point; Determine whether the dust concentration corresponding to the third reference point is greater than the dust concentration corresponding to the first reference point. If so, the third reference point is used as the starting point of the first initial orientation. If not, the first reference point is used as the starting point of the first initial orientation.

[0007] Optionally, obtaining the second initial location of the noise pollution source includes: A circular detection trajectory with a preset radius is planned with the current position of the AGV as the center point; Multiple third detection points are uniformly selected in the circular detection trajectory, and two third detection points whose connecting lines pass through the center point are grouped together. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group; The group of third detection points with the largest difference is selected, and the third detection point corresponding to the larger of the two noise decibel values ​​in the group of third detection points is taken as the fourth reference point. Based on the fourth reference point, the second initial orientation of the noise pollution source is obtained; wherein, the second initial orientation is the radial direction away from the circular detection trajectory.

[0008] Optionally, based on the fourth reference point, a second initial orientation of the noise pollution source is obtained, including: Based on the fourth reference point, the fifth reference point is obtained; wherein, the fifth reference point is the third detection point corresponding to the larger value of the corresponding noise decibel value among the two third detection points adjacent to the fourth reference point; Multiple fourth detection points are evenly selected between the fourth and fifth reference points; The noise decibel values ​​detected at different fourth detection points were obtained respectively; The fourth detection point corresponding to the maximum value among multiple noise decibel values ​​detected at different fourth detection points is taken as the sixth reference point; Determine whether the noise decibel value corresponding to the sixth reference point is greater than the noise decibel value corresponding to the fourth reference point. If so, the sixth reference point is taken as the starting point of the second initial orientation. If not, the fourth reference point is taken as the starting point of the second initial orientation.

[0009] Optionally, the difference between the two noise decibel values ​​corresponding to the third detection point in each group is obtained, including: The AGV is controlled to move to each of the third detection points to obtain the noise decibel values ​​detected at different third detection points; Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

[0010] Optionally, the column is rotatably mounted on the AGV vehicle, and the AGV vehicle is equipped with a drive assembly for driving the column to rotate. Telescopic rods are connected to opposite sides of the top of the control cabinet, and noise detectors are installed at the ends of the telescopic rods. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group, including: The AGV is positioned at the center point, and the drive assembly is controlled to rotate the column sequentially by the corresponding angles, so that the two noise detectors are located at the two third detection points in the same group, thereby obtaining two noise decibel values ​​corresponding to each group of third detection points. Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

[0011] Optionally, the drone is controlled to fly towards a first initial orientation to confirm the actual location information of the dust pollution source, including: While controlling the drone to fly toward the initial orientation, environmental monitoring images are continuously acquired through the camera. Based on environmental monitoring images, identify the target features corresponding to dust pollution sources to confirm the actual location information of the dust pollution sources.

[0012] Optionally, the drone is controlled to fly towards a second initial orientation to confirm the actual location information of the noise pollution source, including: During the process of controlling the drone to fly towards the second initial orientation, the noise detection value is obtained in real time through the noise detector on the drone, and the position with the largest noise detection value is used as the temporary stopping point of the drone. Based on the temporary parking point, images of the surrounding environment are acquired through cameras; Based on images of the surrounding environment, identify suspected features of noise pollution sources to confirm their actual location.

[0013] To achieve the above objectives, this application also provides an online monitoring and control system for dust and noise based on the Industrial Internet of Things, used to control a dust and noise monitoring device. The device includes an AGV vehicle, a column is installed on the top of the AGV vehicle, a control cabinet is installed on the column, a drone is installed inside the control cabinet, the drone is equipped with a camera and a noise detector, and a dust detector and a noise detector are also installed on the control cabinet. The system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The management platform includes: The detection command acquisition module is used to acquire the location detection command of the dust pollution source and / or noise pollution source in response to the dust monitoring alarm and / or noise monitoring alarm. The first location acquisition module is used to obtain the first initial location of the dust pollution source in response to the location detection command of the dust pollution source. The dust location acquisition module is used to control the drone to fly towards the first initial orientation in order to confirm the actual location information of the dust pollution source; The second orientation acquisition module is used to acquire the second initial orientation of the noise pollution source in response to the positioning and detection command of the noise pollution source. The noise location acquisition module is used to control the drone to fly towards the second initial orientation in order to confirm the actual location information of the noise pollution source.

[0014] To achieve the above objectives, this application also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0015] To achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program, on which a processor executes the computer program to implement the above-described method.

[0016] The beneficial effects that this application can achieve are as follows: This application is based on the ability of a dust and noise monitoring device to issue an alarm when it detects that the dust concentration and / or noise decibel level exceeds the standard. Simultaneously, in response to the dust monitoring alarm and / or noise monitoring alarm, it obtains location detection commands for the dust pollution source and / or noise pollution source. When it is necessary to locate and detect a dust pollution source, the dust and noise monitoring device can first determine the initial location of the dust pollution source, then control a drone to fly towards the initial location, and further detect during the flight to ultimately confirm the actual location information of the dust pollution source. Similarly, when it is necessary to locate and detect a noise pollution source, a second initial location of the noise pollution source is first obtained. The device first obtains the initial location of the pollution source using a dust and noise monitoring device. Considering potential positioning errors due to distance and environmental factors, the device then uses a drone to fly towards the initial location. During flight, the camera and noise detector on the drone further determine the specific location of the pollution source. Therefore, this application effectively expands the monitoring range through the coordinated operation of the dust and noise monitoring device and the drone, enabling rapid and accurate location of the pollution source. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0018] Figure 1 This is a flowchart illustrating an online dust and noise monitoring and control method based on the Industrial Internet of Things (IIoT) in an embodiment of this application. Figure 2 This is a schematic diagram of the structure of the dust and noise monitoring device in the embodiments of this application; Figure 3 This is a schematic diagram of another structure of the dust and noise monitoring device in the embodiments of this application; Figure 4 This is a schematic diagram illustrating the principle of obtaining the first initial location of a dust pollution source in an embodiment of this application. Figure 5 This is a schematic diagram illustrating the principle of obtaining the second initial location of a noise pollution source in an embodiment of this application; Figure 6 This is a schematic diagram of the framework of the industrial Internet of Things system involved in the embodiments of this application.

[0019] Figure label: 110 - AGV vehicle, 120 - column, 130 - control cabinet, 140 - drone, 150 - dust detector, 160 - noise detector, 170 - drive assembly, 180 - telescopic pole.

[0020] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0022] It should be noted that if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0023] Example 1 Reference Figures 1-5 This embodiment provides a method for online monitoring and control of dust and noise based on the Industrial Internet of Things, used to control a dust and noise monitoring device. The device includes an AGV vehicle 110, a column 120 on the top of the AGV vehicle 110, a control cabinet 130 on the column 120, a drone 140 inside the control cabinet 130, a camera and a noise detector 160 mounted on the drone 140, and a dust detector 150 and a noise detector 160 also mounted on the control cabinet 130. The method includes the following steps: In response to dust monitoring alarms and / or noise monitoring alarms, obtain location detection commands for dust pollution sources and / or noise pollution sources; In response to the location detection command of the dust pollution source, the initial location of the dust pollution source is obtained; Control the drone 140 to fly towards the first initial orientation to confirm the actual location information of the dust pollution source; In response to the noise pollution source location detection command, the second initial location of the noise pollution source is obtained; Control the drone 140 to fly toward the second initial orientation to confirm the actual location information of the noise pollution source.

[0024] In this embodiment, the dust and noise monitoring device can issue an alarm when it detects that the dust concentration and / or noise level exceeds the standard. Simultaneously, in response to the dust monitoring alarm and / or noise monitoring alarm, it obtains location detection commands for the dust pollution source and / or noise pollution source. When it is necessary to locate and detect the dust pollution source, the dust and noise monitoring device can first locate the first initial location of the dust pollution source, then control the drone 140 to fly towards the first initial location, and further detect during the flight to finally confirm the actual location information of the dust pollution source. Similarly, when it is necessary to locate and detect the noise pollution source, the second initial location of the noise pollution source is first obtained, then the drone 140 is controlled to fly towards the second initial location, and finally confirmed during the flight. In summary, this embodiment uses a dust and noise monitoring device to first obtain the initial location of the pollution source. Considering the potential for positioning deviations due to distance and environmental factors, a drone 140 is then used to fly towards the initial location. During the flight, the camera and noise detector 160 mounted on the drone 140 further determine the specific location of the pollution source. Therefore, this embodiment effectively expands the monitoring range through the coordinated operation of the dust and noise monitoring device and the drone 140, thereby enabling rapid and accurate location of the pollution source. Finally, the actual location information of the dust and / or noise pollution sources can be sent to management personnel to quickly locate the pollution source and implement further control measures.

[0025] It should be noted that since the dust and noise monitoring device can be moved as a whole by the AGV vehicle 110, it can perform online patrol-style detection within a certain range. When the dust concentration and / or noise decibel level exceeds the standard at a certain location, the dust and noise monitoring device will stop at that location to proceed to the next step of detecting the pollution source. Because dust and noise pollution sources may originate from the same source, and noise pollution sources are easier and more accurate to detect than dust pollution sources, if both dust and noise monitoring alarms are received simultaneously, the noise pollution source location detection command will be responded to first. After detecting the actual location of the noise pollution source, the location of the dust pollution source will be checked. If not, the dust pollution source location detection command will be responded to, and its actual location will be detected. By rationally planning the detection sequence according to the pollution type, detection efficiency and accuracy are improved. Once the actual location of the dust pollution source and / or noise pollution source is found, the camera can determine whether there are personnel at the pollution source. If so, the personnel can be prompted to operate in accordance with regulations via voice (a voice broadcaster can be mounted on the drone). If not, the actual location information and alarm information of the pollution source are sent to the management personnel. When the dust pollution source is confirmed, a misting dust collector can be mounted on the drone to directly start dust removal work on the dust pollution source. At the same time, depending on the dust concentration, if the dust concentration is greater than a preset threshold, that is, exceeding the atomizing dust removal capacity of the drone, the AGV vehicle 110 can be controlled to move towards the dust pollution source, and the atomizing dust collector set on the column 120 can be used for further dust removal. The movement path of the AGV vehicle 110 can be planned online in real time by collecting the surrounding environmental information during the drone's flight towards the dust pollution source, thereby dynamically linking the drone with the mobile dust and noise monitoring device. It not only has a large-scale monitoring function, but also a combined dust removal and noise reduction function, realizing intelligent management.

[0026] As an optional implementation method, obtaining the first initial location of the dust pollution source includes: Obtain current wind direction information; Based on the current wind direction information, a straight detection trajectory is planned; the straight detection trajectory is perpendicular to the current wind direction. Multiple first detection points with preset spacing are uniformly selected on the straight detection trajectory, and the AGV vehicle 110 is controlled to move to each first detection point to obtain the dust concentration detected at different first detection points. The first detection point corresponding to the maximum value among multiple dust concentrations detected at different first detection points is used as the first reference point to obtain the first initial orientation of the dust pollution source; wherein, the first initial orientation is perpendicular to the straight detection trajectory and opposite to the current wind direction.

[0027] In this embodiment, since the dust will move in the wind direction, a straight detection trajectory perpendicular to the wind direction can be planned based on the current position of the dust noise monitoring device. Then, the AGV 110 is controlled to make the entire dust noise monitoring device detect the corresponding dust concentration data at multiple first detection points along the straight detection trajectory. The position of the first detection point corresponding to the maximum value of multiple dust concentrations can represent the location closest to the dust pollution source. At this time, the first detection point can be used as the first reference point to obtain the first initial orientation of the dust pollution source. The UAV can then fly in a straight line based on the first initial orientation to quickly and efficiently locate the dust pollution source.

[0028] As an optional implementation, a first detection point corresponding to the maximum value among multiple dust concentrations is used as a first reference point to obtain the first initial location of the dust pollution source, including: Based on the first reference point, a second reference point is obtained; wherein, the second reference point is the first detection point corresponding to the larger value of the dust concentration among the two first detection points adjacent to the first reference point; Multiple second detection points are evenly selected between the first and second reference points; The AGV vehicle 110 is controlled to move to each of the second detection points to obtain the dust concentration detected at different second detection points; The second detection point corresponding to the maximum value among multiple dust concentrations detected at different second detection points is used as the third benchmark point; Determine whether the dust concentration corresponding to the third reference point is greater than the dust concentration corresponding to the first reference point. If so, the third reference point is used as the starting point of the first initial orientation. If not, the first reference point is used as the starting point of the first initial orientation.

[0029] In this embodiment, to improve detection efficiency, multiple first detection points are spaced a certain distance apart. The first reference point obtained may not be the theoretical location closest to the dust pollution source. Therefore, to further improve detection accuracy, based on the first reference point, the dust concentrations corresponding to adjacent first detection points on both sides of the first reference point are compared. The first detection point corresponding to the larger value is taken as the second reference point. Thus, there may be a theoretical location closest to the dust pollution source between the first and second reference points. At this time, multiple second detection points are evenly selected between the first and second reference points. Similarly, the AGV vehicle 110 moves to each second detection point to detect the corresponding dust concentration. The second detection point corresponding to the maximum value is taken as the third reference point. Then, it is determined whether the dust concentration corresponding to the third reference point is greater than the dust concentration corresponding to the first reference point. If so, the third reference point is taken as the starting point of the first initial orientation. If not, the first reference point is taken as the starting point of the first initial orientation. Thus, while improving detection efficiency, the detection accuracy of the dust pollution source can be further improved.

[0030] As an optional implementation, obtaining the second initial location of the noise pollution source includes: A circular detection trajectory with a preset radius is planned with the current position of AGV vehicle 110 as the center point; Multiple third detection points are uniformly selected in the circular detection trajectory, and two third detection points whose connecting lines pass through the center point are grouped together. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group; The group of third detection points with the largest difference is selected, and the third detection point corresponding to the larger of the two noise decibel values ​​in the group of third detection points is taken as the fourth reference point. Based on the fourth reference point, the second initial orientation of the noise pollution source is obtained; wherein, the second initial orientation is the radial direction away from the circular detection trajectory.

[0031] In this embodiment, when detecting the location of a noise pollution source, a circular detection trajectory with a preset radius is planned with the current position of the AGV vehicle 110 as the center point. Then, multiple third detection points are evenly selected within the circular detection trajectory, such as... Figure 5Eight third detection points (A, B, C, D, E, F, G, and H) were selected. Two third detection points connected by a line passing through the center point were grouped together, i.e., AE, BF, CG, and DH were each group. This yielded the difference in noise decibel values ​​between the two points in each group. Each group of third detection points represents the detection position at either end of the diameter of the circular detection trajectory. The maximum difference in noise decibel values ​​between the two points in each group represents the two detection positions closest to and furthest from the noise pollution source. For example, the difference in noise decibel values ​​between points B and F is the largest. The third detection point corresponding to the larger of the two noise decibel values ​​in this group (e.g., point B) is used as the fourth reference point, representing the position of the third detection point closest to the noise pollution source. This allows for the determination of the second initial orientation of the noise pollution source, achieving accurate and efficient detection of the noise pollution source's location.

[0032] It should be noted that the reason for using the difference between the two noise decibel values ​​corresponding to the third detection point in each group to determine the location of the third detection point closest to the noise pollution source is that if only single-point detection is used, there may be instantaneous noise data or discontinuous noise affecting the detection error. Therefore, comparing the difference between two extreme points has two advantages: firstly, the probability of errors occurring at both extreme points is small, which can reduce the impact of errors; secondly, the difference can amplify the detection data results, preventing the situation where the data value fluctuation of single-point detection is small and difficult to accurately represent the difference, thereby improving the detection accuracy. If single-point detection is used, a relatively dense selection of detection points is required to ensure detection accuracy, but the detection efficiency is greatly reduced. Therefore, this embodiment uses the method of comparing the difference between two extreme points, which can quickly locate the target point (i.e., the third detection point closest to the noise pollution source) and improve detection efficiency. In addition, when acquiring the noise decibel value at each third detection point, it can be collected based on a preset continuous time, and the average value can be used as the noise decibel value of that point to ensure the authenticity and reliability of the data.

[0033] As an optional implementation, obtaining the second initial location of the noise pollution source based on the fourth reference point includes: Based on the fourth reference point, the fifth reference point is obtained; wherein, the fifth reference point is the third detection point corresponding to the larger value of the corresponding noise decibel value among the two third detection points adjacent to the fourth reference point; Multiple fourth detection points are evenly selected between the fourth and fifth reference points; The noise decibel values ​​detected at different fourth detection points were obtained respectively; The fourth detection point corresponding to the maximum value among multiple noise decibel values ​​detected at different fourth detection points is taken as the sixth reference point; Determine whether the noise decibel value corresponding to the sixth reference point is greater than the noise decibel value corresponding to the fourth reference point. If so, the sixth reference point is taken as the starting point of the second initial orientation. If not, the fourth reference point is taken as the starting point of the second initial orientation.

[0034] In this embodiment, to improve detection efficiency, multiple third detection points are spaced a certain distance apart. The detected fourth reference point may not be the theoretical location closest to the noise pollution source. Therefore, to further improve detection accuracy, based on the fourth reference point, the third detection point corresponding to the larger noise decibel value among two adjacent third detection points is selected as the fifth reference point. The theoretical detection point closest to the noise pollution source in the circular detection trajectory is more likely to be between the fourth and fifth reference points. Therefore, multiple fourth detection points are selected between the fourth and fifth reference points, and their corresponding noise decibel values ​​are obtained. The fourth detection point corresponding to the maximum noise decibel value among the multiple noise decibel values ​​is selected as the sixth reference point. It is determined whether the noise decibel value corresponding to the sixth reference point is greater than the noise decibel value corresponding to the fourth reference point. If so, the sixth reference point is used as the starting point of the second initial orientation; otherwise, the fourth reference point is used as the starting point of the second initial orientation. Thus, while improving detection efficiency, the detection accuracy of the noise pollution source can be further improved.

[0035] It should be noted that since the theoretical detection point closest to the noise pollution source has been further narrowed down to between the fourth and fifth reference points, it already has a certain positioning accuracy. Therefore, multiple fourth detection points can be planned directly between the fourth and fifth reference points for single-point detection, without having to use the above method of comparing the difference between the two extreme points. This improves detection efficiency while ensuring a certain positioning accuracy.

[0036] As an optional implementation, the difference between the two noise decibel values ​​corresponding to each group of third detection points is obtained, including: The AGV vehicle 110 is controlled to move to each of the third detection points to obtain the noise decibel values ​​detected at different third detection points; Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

[0037] In this embodiment, the AGV vehicle 110 can be used to move to each third detection point to collect the noise decibel value corresponding to each third detection point. Then, the difference between the two noise decibel values ​​corresponding to the same group of third detection points can be calculated.

[0038] As an optional implementation, the column 120 is rotatably mounted on the AGV vehicle 110, and the AGV vehicle 110 is provided with a drive assembly 170 for driving the column 120 to rotate. Telescopic rods 180 are connected to opposite sides of the top of the control cabinet 130, and noise detectors 160 are provided at the ends of the telescopic rods 180. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group, including: The AGV vehicle 110 is controlled to be in the center position, and the drive component 170 is controlled to drive the column 120 to rotate sequentially by the corresponding angle, so that the two noise detectors 160 are respectively located at the two third detection points in the same group, so as to obtain the two noise decibel values ​​corresponding to each group of third detection points. Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

[0039] In this embodiment, the telescopic rod 180 (which can be a telescopic cylinder or an electric push rod) can extend the noise detectors 160 on both sides to a certain distance. Then, the drive assembly 170 (which can be driven by a motor and gear set) drives the column 120 to rotate, which in turn drives the control cabinet 130 to rotate. This causes the two noise detectors 160 with a certain distance to revolve. Therefore, when the AGV vehicle 110 is at the center point, the drive assembly 170 can be controlled to drive the column 120 to rotate sequentially by the corresponding angle so that the two noise detectors 160 are located at the two third detection points in the same group. That is, the distance between the two noise detectors 160 is the diameter of the circular detection trajectory. This allows the noise decibel values ​​of the two extreme points to be collected at once, and the difference between the two noise decibel values ​​corresponding to each group of third detection points can be calculated. Compared with the above method of controlling the AGV vehicle 110 to move to each third detection point for noise detection, this detection method has higher detection efficiency and avoids data errors caused by deviations during the movement process, thus improving detection efficiency.

[0040] As an optional implementation, the drone 140 is controlled to fly toward a first initial orientation to confirm the actual location information of the dust pollution source, including: While controlling the drone 140 to fly toward the first initial orientation, environmental monitoring images are continuously acquired through the camera. Based on environmental monitoring images, identify the target features corresponding to dust pollution sources to confirm the actual location information of the dust pollution sources.

[0041] In this embodiment, when the drone 140 is controlled to fly in a straight line toward the first initial orientation, environmental monitoring images can be acquired in real time using a camera. Existing image recognition algorithms can be used to identify the target features corresponding to the dust pollution source, and the actual location information of the dust pollution source can be confirmed. Alternatively, the collected environmental monitoring images can be sent to the management backend, and the location of the dust pollution source can be determined in conjunction with manual identification to ensure the accuracy of monitoring.

[0042] As an optional implementation, the drone 140 is controlled to fly toward a second initial azimuth to confirm the actual location information of the noise pollution source, including: During the process of controlling the drone 140 to fly towards the second initial orientation, the noise detection value is obtained in real time through the noise detector 160 on the drone 140, and the position with the largest noise detection value is used as the temporary stopping point of the drone 140. Based on the temporary parking point, images of the surrounding environment are acquired through cameras; Based on images of the surrounding environment, identify suspected features of noise pollution sources to confirm their actual location.

[0043] In this embodiment, when the drone 140 is controlled to fly towards the second initial orientation, the noise detection value can be obtained in real time through the noise detector 160 on the drone 140. The noise detection value detected in the previous part of the path will become larger and larger. If after passing a certain theoretical position point, when the noise detection value gradually decreases, the drone 140 returns to the theoretical position point, that is, the noise detection value at the theoretical position point is the largest. Therefore, the theoretical position point is used as the temporary stopping point of the drone 140. Combined with the camera to obtain the surrounding environment image, the suspected features of the noise pollution source can be identified by using the existing image recognition algorithm. The surrounding environment image can also be sent to the management backend, and the actual location of the noise pollution source can be determined together with manual identification, which improves the monitoring accuracy.

[0044] Example 2 Based on the same inventive concept as the foregoing embodiments, and referring to... Figures 1-6 This embodiment also provides an online monitoring and control system for dust and noise based on the Industrial Internet of Things, used to control a dust and noise monitoring device. The device includes an AGV vehicle 110, a column 120 on the top of the AGV vehicle 110, a control cabinet 130 on the column 120, a drone 140 inside the control cabinet 130, a camera and a noise detector 160 mounted on the drone 140, and a dust detector 150 and a noise detector 160 also mounted on the control cabinet 130. The system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The management platform includes: The detection command acquisition module is used to acquire the location detection command of the dust pollution source and / or noise pollution source in response to the dust monitoring alarm and / or noise monitoring alarm. The first location acquisition module is used to obtain the first initial location of the dust pollution source in response to the location detection command of the dust pollution source. The dust location acquisition module is used to control the UAV 140 to fly towards the first initial orientation in order to confirm the actual location information of the dust pollution source; The second orientation acquisition module is used to acquire the second initial orientation of the noise pollution source in response to the positioning and detection command of the noise pollution source. The noise location acquisition module is used to control the UAV 140 to fly towards the second initial orientation in order to confirm the actual location information of the noise pollution source. It should be noted that the dust and noise online monitoring and control system based on the Industrial Internet of Things (IIoT) in this embodiment also includes a user platform and a service platform that are interconnected. The service platform is interconnected with the management platform, thus forming a standard five-platform structure for the Internet of Things. The physical entities of the user platform include various user terminals, such as mobile phones, computers, and dedicated terminals, which provide user-end services through integration with user information system software. The service platform is the functional platform for service communication. The management platform is the functional platform for managing the operation of the Internet of Things system. In some embodiments, the management platform may include multiple management sub-platforms, each connected to the aforementioned sensor network platform. Each management sub-platform includes a detection command acquisition module, a first location acquisition module, a dust location acquisition module, a second location acquisition module, and a noise location acquisition module. The sensor network platform is the functional platform for sensor communication. The object platform is the functional platform for sensing and control. Here, the object platform may include devices such as AGV vehicles, drones, cameras, noise detectors, and dust detectors.

[0045] The explanations and examples of the modules in this embodiment can be found in the methods of the foregoing embodiments, and will not be repeated here.

[0046] Example 3 Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0047] Example 4 Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer-readable storage medium storing a computer program, and a processor executes the computer program to implement the above-described method.

[0048] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for online monitoring and control of dust and noise based on the Industrial Internet of Things, characterized in that, The device is used to control a dust and noise monitoring device. The device includes an AGV vehicle, a column on the top of the AGV vehicle, a control cabinet on the column, a drone inside the control cabinet, a camera and a noise detector on the drone, and a dust detector and a noise detector on the control cabinet. The method includes the following steps: In response to dust monitoring alarms and / or noise monitoring alarms, obtain location detection commands for dust pollution sources and / or noise pollution sources; In response to the location detection command of the dust pollution source, the initial location of the dust pollution source is obtained; Control the drone to fly towards the initial orientation to confirm the actual location information of the dust pollution source; In response to the noise pollution source location detection command, the second initial location of the noise pollution source is obtained; Control the drone to fly towards the second initial orientation to confirm the actual location information of the noise pollution source.

2. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 1, characterized in that, Obtain the initial location of the dust pollution source, including: Obtain current wind direction information; Based on the current wind direction information, a straight detection trajectory is planned; the straight detection trajectory is perpendicular to the current wind direction. Multiple first detection points with preset spacing are uniformly selected on the straight detection trajectory, and the AGV is controlled to move to each first detection point to obtain the dust concentration detected at different first detection points. The first detection point corresponding to the maximum value among multiple dust concentrations detected at different first detection points is used as the first reference point to obtain the first initial orientation of the dust pollution source; wherein, the first initial orientation is perpendicular to the straight detection trajectory and opposite to the current wind direction.

3. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 2, characterized in that, Using the first detection point corresponding to the maximum value among multiple dust concentrations as the first reference point, the initial location of the dust pollution source is obtained, including: Based on the first reference point, a second reference point is obtained; wherein, the second reference point is the first detection point corresponding to the larger value of the dust concentration among the two first detection points adjacent to the first reference point; Multiple second detection points are evenly selected between the first and second reference points; The AGV is controlled to move to each of the second detection points to obtain the dust concentration detected at different second detection points; The second detection point corresponding to the maximum value among multiple dust concentrations detected at different second detection points is used as the third benchmark point; Determine whether the dust concentration corresponding to the third reference point is greater than the dust concentration corresponding to the first reference point. If so, the third reference point is used as the starting point of the first initial orientation. If not, the first reference point is used as the starting point of the first initial orientation.

4. A method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in any one of claims 1-3, characterized in that, Obtaining the second initial location of the noise pollution source includes: A circular detection trajectory with a preset radius is planned with the current position of the AGV as the center point; Multiple third detection points are uniformly selected in the circular detection trajectory, and two third detection points whose connecting lines pass through the center point are grouped together. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group; The group of third detection points with the largest difference is selected, and the third detection point corresponding to the larger of the two noise decibel values ​​in the group of third detection points is taken as the fourth reference point. Based on the fourth reference point, the second initial orientation of the noise pollution source is obtained; wherein, the second initial orientation is the radial direction away from the circular detection trajectory.

5. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 4, characterized in that, Based on the fourth reference point, the second initial location of the noise pollution source is obtained, including: Based on the fourth reference point, the fifth reference point is obtained; wherein, the fifth reference point is the third detection point corresponding to the larger value of the corresponding noise decibel value among the two third detection points adjacent to the fourth reference point; Multiple fourth detection points are evenly selected between the fourth and fifth reference points; The noise decibel values ​​detected at different fourth detection points were obtained respectively; The fourth detection point corresponding to the maximum value among multiple noise decibel values ​​detected at different fourth detection points is taken as the sixth reference point; Determine whether the noise decibel value corresponding to the sixth reference point is greater than the noise decibel value corresponding to the fourth reference point. If so, the sixth reference point is taken as the starting point of the second initial orientation. If not, the fourth reference point is taken as the starting point of the second initial orientation.

6. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 4, characterized in that, Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group, including: The AGV is controlled to move to each of the third detection points to obtain the noise decibel values ​​detected at different third detection points; Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

7. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 4, characterized in that, The column is rotatably mounted on the AGV vehicle, and the AGV vehicle is equipped with a drive assembly for driving the column to rotate. Telescopic rods are connected to opposite sides of the top of the control cabinet, and noise detectors are installed at the ends of the telescopic rods. Obtain the difference between the two noise decibel values ​​corresponding to the third detection point in each group, including: The AGV is positioned at the center point. The drive assembly is then controlled to rotate the column sequentially by the corresponding angles, so that the two noise detectors are located at the two third detection points in the same group, thereby obtaining two noise decibel values ​​corresponding to each group of third detection points. Obtain the difference in noise decibel values ​​between two corresponding third detection points in the same group.

8. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 1, characterized in that, Control the drone to fly towards the initial bearing to confirm the actual location information of the dust pollution source, including: While controlling the drone to fly toward the initial orientation, environmental monitoring images are continuously acquired through the camera. Based on environmental monitoring images, identify the target features corresponding to dust pollution sources to confirm the actual location information of the dust pollution sources.

9. The method for online monitoring and control of dust and noise based on the Industrial Internet of Things as described in claim 1, characterized in that, Control the drone to fly towards the second initial orientation to confirm the actual location information of the noise pollution source, including: During the process of controlling the drone to fly towards the second initial orientation, the noise detection value is obtained in real time through the noise detector on the drone, and the position with the largest noise detection value is used as the temporary stopping point of the drone. Based on the temporary parking point, images of the surrounding environment are acquired through cameras; Based on images of the surrounding environment, identify suspected features of noise pollution sources to confirm their actual location.

10. A dust and noise online monitoring and control system based on the Industrial Internet of Things, characterized in that, The device is used to control a dust and noise monitoring device. The device includes an AGV vehicle, a column on the top of the AGV vehicle, a control cabinet on the column, a drone inside the control cabinet, a camera and a noise detector on the drone, and a dust detector and a noise detector on the control cabinet. The system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The management platform includes: The detection command acquisition module is used to acquire the location detection command of the dust pollution source and / or noise pollution source in response to the dust monitoring alarm and / or noise monitoring alarm. The first location acquisition module is used to obtain the first initial location of the dust pollution source in response to the location detection command of the dust pollution source. The dust location acquisition module is used to control the drone to fly towards the first initial orientation in order to confirm the actual location information of the dust pollution source; The second orientation acquisition module is used to acquire the second initial orientation of the noise pollution source in response to the positioning and detection command of the noise pollution source. The noise location acquisition module is used to control the drone to fly towards the second initial orientation in order to confirm the actual location information of the noise pollution source.

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