Air pollution and nuisance investigation equipment and system
By using air pollution and nuisance investigation equipment, and leveraging multi-parameter sensors and AI prediction models, the equipment can automatically move in a directional manner, solving the problems of safety risks and low efficiency in traditional investigations, and achieving rapid and accurate location of pollution sources.
Patent Information
- Application Number
- CN202423284777.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-30
- Publication Date
- 2025-12-30
- Estimated Expiration
- 2034-12-30
AI Technical Summary
Traditional air pollution and nuisance investigations rely on manual searches, which pose safety risks and are inefficient. Existing gas detectors provide limited information, making it difficult to quickly and accurately locate pollution sources.
The system employs air pollution and nuisance investigation equipment, including multiple air intake units, sensor units, central processing units, and motion units. It uses concentration data measured by multi-parameter sensors, combined with AI prediction models, to achieve automatic directional movement to quickly locate pollution sources.
It enables rapid and accurate identification and location of pollution sources without human intervention, improving investigation efficiency and reducing safety risks for staff.
Smart Images
Figure CN223743082U_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The embodiment of the utility model relates to air pollutant or nuisance source identification and detection technical field, especially relates to air pollution and nuisance investigation equipment and system. BACKGROUND
[0002] Environmental protection departments and agencies around the world receive numerous complaints about environmental air nuisance, most of which are not explicitly sourced, resulting in many affected people experiencing symptoms such as discomfort, nausea, and even dizziness. In some cases, it is crucial to identify the source of pollution promptly in order to stop the nuisance quickly, especially when it involves vulnerable children.
[0003] Traditionally, investigators rely mainly on their sense of smell to track and identify pollution sources. Long-term investigations can pose a threat to the safety and health of frontline workers, especially when dealing with environmental nuisances such as Mysterious Gas Incidents (MGIs). Although gas detectors can be used to measure the concentration of certain known pollutants, they provide limited information, only measuring the concentration of certain identified or suspected pollutants, which subsequent investigators still need to manually select and analyze based on concentration data. Therefore, the existing technology has great limitations in predicting and tracking pollution sources, and the investigation work still highly depends on manual searching and the experience of investigators. SUMMARY
[0004] The embodiment of the utility model provides air pollution and nuisance investigation equipment and system, can realize the identification and investigation of real-time pollution or nuisance source without manual intervention.
[0005] To solve the above technical problems, one technical scheme adopted by the utility model is to provide air pollution and nuisance investigation equipment, comprising:
[0006] At least two air intake units and a sensor unit corresponding to each air intake unit;
[0007] A central processing unit; and
[0008] A motion unit;
[0009] Among them, the at least two air intake units are inclined in different directions, collecting at least two air samples from different directions and different positions; the central processing unit is connected with each sensor unit and the motion unit respectively.
[0010] Optionally, the air intake unit comprises a directional air inlet and a forced air intake module, the directional air inlet is inclined in a preset direction, and the forced air intake module controls the air sample to enter the corresponding sensor unit at a preset flow rate.
[0011] Optionally, the sensor unit comprises a multi-parameter gas sensor.
[0012] Optionally, the sensor unit is mounted on a stabilizer.
[0013] Optionally, further comprising a communication unit.
[0014] Optionally, the communication unit comprises a 5G antenna and a 5G router.
[0015] Optionally, further comprising a camera and / or a laser radar.
[0016] Optionally, the motion unit comprises any one of a push-type motor, a drone motor or a ship motor.
[0017] Optionally, the air pollution and nuisance investigation device is realized in the form of a robot dog.
[0018] To solve the above technical problems, another technical scheme adopted by the utility model is: providing an air pollution and nuisance investigation system, comprising the air pollution and nuisance investigation device and a control terminal in communication connection with the air pollution and nuisance investigation device.
[0019] The air pollution and nuisance investigation device provided by the utility model embodiment can collect at least two air samples from different directions and different positions, accurately and efficiently detect the concentration data of a plurality of air pollutants, and effectively move towards the pollution source by using the concentration data to control the device, without turning to different directions for traversal, so that the position of the pollution source can be quickly located, and the investigation efficiency is improved. BRIEF DESCRIPTION OF DRAWINGS
[0020] In order to more clearly illustrate the technical scheme of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced as follows. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the drawings.
[0021] Figure 1 An exemplary block structure diagram of the air pollution and nuisance investigation device is shown;
[0022] Figure 2 An exemplary schematic diagram of an air pollution and nuisance investigation robot dog is shown;
[0023] Figure 3An exemplary schematic diagram of the training and prediction process of the AI prediction model is shown.
[0024] Figure 4 An exemplary schematic diagram of data annotation by placing the multi-parameter gas sensor at a known pollution source in multiple scenarios is shown.
[0025] Figure 5 An exemplary schematic diagram of an integrated user interface for air pollution and nuisance investigation is shown. DETAILED DESCRIPTION
[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.
[0027] Please refer to Figure 1 and Figure 2 , Figure 1 An exemplary structure of the air pollution and nuisance investigation device 100 is shown, Figure 2 An exemplary schematic diagram of the air pollution and nuisance investigation robot dog is shown. As shown in Figure 1 and Figure 2 , the air pollution and nuisance investigation device 100 comprises at least two air intake units 101, and a sensor unit 102, a central processing unit 103, and a motion unit 104 connected to each air intake unit 101. Among them, the at least two air intake units 101 are arranged at different positions and are inclined in different directions, collecting at least two air samples from different directions and different positions, the sensor unit 102 detects the air sample collected by the air intake unit corresponding to it, obtains the concentration data of one or more air pollutants and / or nuisance sources in the air sample, the central processing unit 103 is connected to each sensor unit 102 and motion unit 104, generates a motion signal according to the difference between the concentration data of the at least two air samples, and sends the motion signal to the motion unit 104, and the motion unit 104 controls the air pollution and nuisance investigation device 100 to be directional and mobile according to the motion signal.
[0028] In one embodiment, the air intake unit 101 comprises a directional air inlet and a forced air intake module, the directional air inlet is inclined in a preset direction, and the forced air intake module controls the air sample to enter the corresponding sensor unit 102 at a preset flow rate. For example, Figure 2The air pollution and nuisance investigation robotic dog includes two directional air inlets arranged on the left and right sides of the camera, wherein the left directional air inlet is directed to the left side relative to the front of the robotic dog, and the right directional air inlet is directed to the right side relative to the front of the robotic dog. In one embodiment, the preset flow rate is 3 liters per minute. In another embodiment, the inclination direction and angle of the directional air inlets can be adjusted to more effectively infer the direction of the target air pollution and / or nuisance source.
[0029] In one embodiment, the sensor unit 102 includes a multi-parameter gas sensor that can simultaneously measure the concentrations of multiple parameters, including: (1) hydrogen sulfide (H2S), (2) volatile organic compounds (VOCs), (3) particulate matter PM1.0, (4) particulate matter PM2.5, (5) particulate matter PM10, (6) nitrogen dioxide (NO2), (7) ozone (O3), (8) carbon monoxide (CO), (9) hydrocarbons (CxHy), and (10) ammonia (NH3).
[0030] In another embodiment, the sensor unit 102 can simultaneously measure the concentrations of one or more air pollutants and / or nuisance sources, including: (1) hydrogen sulfide (H2S), (2) volatile organic compounds (VOCs), (3) particulate matter (PM1.0, PM2.5, PM10), (4) nitrogen dioxide (NO2), (5) ozone (O3), (6) carbon monoxide (CO), (7) hydrocarbons (CxHy), (8) ammonia (NH3), (9) sulfur dioxide (SO2), (10) carbon dioxide (CO2), and (11) hydrogen chloride (HCl).
[0031] In one embodiment, the sensor unit 102 is mounted on a stabilizer to reduce interference with the sensors, thereby more accurately collecting concentration data of air pollutants and / or nuisance sources that can be compared between multiple sensors.
[0032] In one embodiment, the motion unit 104 can be implemented with a propulsion motor with a mechanical arm, wheels, tracks, or other means, so that the air pollution and nuisance investigation device 100 can move towards the pollution or nuisance source on land or water, on different types of terrain. In a specific embodiment, the air pollution and nuisance investigation device 100 is implemented in the form of a robotic dog, as shown in Figure 2
[0033] In another embodiment, the motion unit 104 is implemented in the form of a drone motor, so that the air pollution and nuisance investigation device 100 moves towards the pollution or nuisance source in the air.
[0034] In yet another embodiment, the motion unit is implemented in the form of a ship motor, so that the air pollution and nuisance investigation device 100 moves towards the pollution or nuisance source on water.
[0035] In one embodiment, the central processing unit 103 obtains concentration data of at least two air samples from the at least two sensor units 102, calculates a concentration difference value of the at least two air samples, compares the concentration difference value with a preset difference threshold value, determines a new moving direction based on the air sample with a larger concentration if the concentration difference value is greater than or equal to the difference threshold value, and generates a motion signal according to the new moving direction; or obtains a current moving direction if the concentration difference value is less than the difference threshold value, and generates a motion signal according to the current moving direction.
[0036] The calculation method of the concentration difference value can be set according to requirements. In one embodiment, the concentration difference value is calculated based on the concentrations of all kinds of air pollutants or sources of disturbance. Specifically, a weight coefficient is set for each kind of air pollutant or source of disturbance in advance. The concentration sum of each air sample based on the weight coefficient of all kinds of air pollutants or sources of disturbance is calculated first, and then the difference between the concentration sums of the two air samples is calculated as the concentration difference value of the two air samples. In this embodiment, the new moving direction is determined based on the air sample with a larger concentration sum.
[0037] In another embodiment, the concentration difference value is calculated based on the concentration of a certain kind of air pollutant or source of disturbance. Specifically, the concentration difference of each kind of air pollutant or source of disturbance between the two air samples is calculated first, and then the largest concentration difference is selected as the concentration difference value of the two air samples. In this embodiment, the new moving direction is determined based on the air sample with a larger concentration in the largest concentration difference. In a further embodiment, a kind of air pollutant or source of disturbance can also be selected in advance to calculate the concentration difference value.
[0038] In another embodiment, the central processing unit 103 is built-in with a trained AI (Artificial Intelligence) prediction model. The AI prediction model is capable of predicting the type of pollution or nuisance source according to the concentration data of air pollutants and / or nuisance sources in the unknown source air sample detected by the sensor unit 102. In this embodiment, a “fingerprint” concentration profile is generated for each type of pollution or nuisance source according to the typical concentration of various air pollutants or nuisance sources. When the air pollution and nuisance investigation device 100 is in use, the central processing unit 103 can generate a concentration profile according to the concentration of air pollutants or nuisance sources measured by each sensor unit 102, compare it with the “fingerprint” concentration profile corresponding to the type of pollution or nuisance source predicted by the AI prediction model, determine the concentration profile that is most similar to the “fingerprint” concentration profile, and determine a new moving direction based on the air sample corresponding to the most similar concentration profile. In this embodiment, the air pollution and nuisance investigation device 100 can iteratively move towards the target pollution or nuisance source location according to the type of pollution or nuisance source predicted by the AI.
[0039] When the concentration difference value reaches the difference threshold, the central processing unit 103 controls the motion unit 104 to adjust the direction of the air pollution and nuisance investigation device 100 and move it towards the pollution source. When the concentration difference value does not reach the difference threshold, the central processing unit 103 controls the motion unit 104 to control the air pollution and nuisance investigation device 100 to continue moving forward until the difference threshold is reached, and then make necessary direction adjustment. It can be understood that the distance of each movement can be preset in the air pollution and nuisance investigation device 100.
[0040] In a further embodiment, the central processing unit 103 counts the number of detections of the air sample, and when the count value reaches a preset number, controls the air pollution and nuisance investigation device 100 to stop the investigation work. After the air pollution and nuisance investigation device 100 completes the preset number of iterations and movements, manual analysis and adjustment can be performed before further investigation. This is quite useful when the air pollution and nuisance investigation device 100 reaches a dead end or needs to bypass obstacles to reach the pollution or nuisance source.
[0041] In an embodiment, the air pollution and nuisance investigation device 100 further comprises a computer vision unit, which includes a 4G or 5G camera, a night vision camera, an infrared camera, and / or a LiDAR (Light Detection and Ranging), etc. As shown in the air pollution and nuisance investigation robot dog, it comprises a camera and a LiDAR. The central processing unit 103 is further configured to perform autonomous navigation according to the image data obtained by the computer vision unit, so that the device can adapt to various terrains and avoid obstacles to move to the target location. Figure 2 The central processing unit 103 is further configured to perform autonomous navigation according to the image data obtained by the computer vision unit, so that the device can adapt to various terrains and avoid obstacles to move to the target location.
[0042] In an embodiment, the air pollution and nuisance investigation device 100 further comprises a communication unit to allow seamless communication between devices or between the device and a control terminal carrying a central command system. As Figure 2 The air pollution and nuisance investigation robot dog comprises a 5G router and a 5G antenna. The 5G high-speed connection can support real-time transmission of a large amount of data, which is crucial for real-time monitoring and evaluation.
[0043] In an embodiment, the central command system corresponds to an integrated user interface. As Figure 5 As shown, the integrated user interface synchronously displays the real-time environmental images captured by the air pollution and nuisance investigation device, and displays on the real-time environmental images the concentration data of air pollutants and / or nuisance sources detected by the left and right multi-parameter gas sensors, the prediction result information obtained by the AI prediction model based on the concentration data, and a plurality of operation buttons. Among them, the direction operation button set in the lower left corner is used to control the moving direction of the robot dog, the function operation button set in the middle of the bottom is used to set the opening or closing of the automatic task, view videos, view photos or browse, etc., the direction operation button set in the lower right corner is used to control the angle of shooting, and the function operation button set in the upper left corner is used to set the posture, speed and moving mode of the robot dog.
[0044] The scheme of the present application can also be implemented as an air pollution and nuisance investigation system, comprising an air pollution and nuisance investigation device 100 and a control terminal, the air pollution and nuisance investigation device 100 and the control terminal are in communication connection, and the air pollution and nuisance investigation device transmits the concentration data of at least two air samples to the control terminal in real time. The integrated user interface described above is implemented on the control terminal, through which the user can monitor and evaluate the environment where the air pollution and nuisance investigation device is located, the detected concentration data and the prediction results in real time, and manually adjust the air pollution and nuisance investigation device through the corresponding operation buttons. In an embodiment, the control terminal is a tablet computer. With Figure 2 Taking the air pollution and nuisance investigation robot dog in China as an example, the robot unit, the central control platform (carried on the robot dog, including the air inlet unit, the sensor unit, the computer vision unit, the communication unit and the central processing unit, etc.) and the control terminal deploying the central command system constitute the air pollution and nuisance investigation system, in which the devices are associated with each other to form an Internet of Things network, and each unit works cooperatively in the network to improve the overall efficiency of the system.
[0045] As Figure 3 shown, the training and prediction process of the AI prediction model, wherein the training process comprises:
[0046] Step 1: Collect, detect and label air samples of various known types of pollution or nuisance sources to obtain labeled data.
[0047] Specifically, the device with air sensors or the air pollution and nuisance investigation equipment in the present application can be deployed to various known pollution source sites to collect concentration data of one or more air pollutants or nuisance sources, and the concentration data can be labeled to obtain labeled data. As shown in FIG. 1, a schematic diagram of data labeling by placing multi-parameter gas sensors at known pollution sources in multiple scenarios is shown. In one embodiment, the pollution or nuisance sources used to train the AI prediction model can include private sewage treatment plants (small), sewage sewers, decoration construction sites, pig farms, poultry farms and ambient air (i.e. baseline environment), etc. In another embodiment, the pollution or nuisance sources used to train the AI prediction model can further include public sewage treatment plants (large), drainage box culverts, drainage outlets, dog kennels, large construction sites, road construction sites, chemical waste storage areas, chemical waste collection points, chemical waste treatment facilities, landfills, repaired landfills, metal plating plants, chimneys, restaurant exhaust outlets and recycling stations, etc. Figure 4
[0048] Step 2: Input the labeled data into the AI prediction model constructed using a machine learning algorithm for training to obtain a trained AI prediction model.
[0049] In one embodiment, the gradient boosting decision tree machine learning method is used to train the AI prediction model. During the training process, the AI prediction model analyzes the patterns and concentration characteristics of various types of pollution or nuisance sources based on the labeled data, so that the AI prediction model can recognize and distinguish different pollution or nuisance sources.
[0050] The prediction process includes:
[0051] Step 1: Collect and detect air samples of unknown types of pollution or nuisance sources to obtain concentration data of unknown types of pollution or nuisance sources, and input the concentration data into the trained AI prediction model.
[0052] Step 2: The AI prediction model analyzes the concentration data of the unknown types of pollution or nuisance sources to predict the types of pollution or nuisance sources.
[0053] In particular, the air pollution and nuisance investigation device 100 of the present application can be used to collect and detect air samples from unknown types of pollution or nuisance sources, and obtain concentration data of air pollutants or nuisance sources in at least two air samples. The concentration data of all or part of the air samples in the at least two air samples are input into the trained AI prediction model, and the AI prediction model analyzes the concentration data of all or part of the air samples in the at least two air samples to predict the type of pollution or nuisance source. In particular, the concentration data of the air sample with the highest concentration in the at least two air samples is input into the trained AI prediction model, and the AI prediction model analyzes the concentration data of the air sample with the higher concentration to predict the type of pollution or nuisance source. As shown in Figure 3
[0054] In one embodiment, the concentration data of air pollutants or nuisance sources collected by the air pollution and nuisance investigation device 100 and the type of pollution or nuisance source confirmed by human can be further used as labeled data for the AI prediction model, so as to improve the AI prediction model for future use.
[0055] In one embodiment, a geographic fence can be constructed in the patrol area of the air pollution and nuisance investigation device 100 or a search range can be set in the self-navigable air pollution and nuisance investigation device 100 to narrow down the area range for searching the location of the pollution or nuisance source.
[0056] In one embodiment, the air pollution and nuisance investigation device 100 or the air pollution and nuisance investigation system can access key information from various sources, including: (1) known air emission lists from environmental protection departments and agencies, (2) real-time weather data, (3) location or terrain data. The accessibility of these data can enable the AI prediction model to better identify and classify pollution or nuisance sources (such as sites, factories or public facilities) and their names and addresses, thereby further improving the efficiency and effectiveness of navigation to the location of the pollution or nuisance source and identification of the type of pollution or nuisance source.
[0057] The air pollution and nuisance investigation equipment provided by the utility model can collect at least two air samples from different directions and different positions, accurately and efficiently detect concentration data of various air pollutants in the air samples, and control the equipment to effectively move towards a pollution source by using the concentration data, without traversing in different directions, so that the position of the pollution source can be quickly located, and the investigation efficiency is improved. When the AI analysis method for determining the type of a pollution or nuisance source is combined with the directional air intake method for determining the position of the pollution or nuisance source, comprehensive and overall analysis of the pollution or nuisance source can be realized without manual intervention, and a dangerous task is replaced by a human being, so that potential risks of occupational safety and health are eliminated. In addition, the equipment can continuously search, and the search efficiency of the pollution or nuisance source is greatly improved.
[0058] It should be noted that the specification and drawings of the utility model provide a preferred embodiment of the utility model, but the utility model can be realized in many different forms, and is not limited to the embodiments described in the specification, the embodiments do not serve as additional limitations on the content of the utility model, and the purpose of providing the embodiments is to make the disclosure of the utility model more thorough and comprehensive. Furthermore, the above technical features continue to be combined with each other to form various embodiments not listed above, which are all regarded as the range disclosed in the specification of the utility model; furthermore, those skilled in the art can improve or transform the above description, and all the improvements and transformations should belong to the protection scope of the claims of the utility model.
Claims
1. An air pollution and nuisance investigation apparatus, characterized by, Comprise: at least two air intake units and a sensor unit connected to each air intake unit; a central processing unit; and a motion unit; wherein the at least two air intake units are tilted in different directions to collect at least two air samples from different directions and different positions, and the central processing unit is connected to each sensor unit and the motion unit respectively.
2. The air pollution and nuisance investigation apparatus of claim 1, wherein, The air intake unit comprises a directional air inlet and a forced air intake module, the directional air inlet is tilted in a preset direction, and the forced air intake module controls the air sample to enter the corresponding sensor unit at a preset flow rate.
3. The air pollution and nuisance investigation apparatus of claim 1, wherein, The sensor unit comprises a multi-parameter gas sensor.
4. The air pollution and nuisance investigation apparatus of claim 1, wherein, The sensor unit is installed on a stabilizer.
5. The air pollution and nuisance investigation apparatus of claim 1, wherein, Further comprising a communication unit.
6. The air pollution and nuisance investigation apparatus of claim 5, wherein, The communication unit comprises a 5G antenna and a 5G router.
7. The air pollution and nuisance investigation apparatus of claim 1, wherein, Further comprising a camera and / or a laser radar.
8. The air pollution and nuisance investigation apparatus of any one of claims 1 to 7, wherein, The motion unit comprises any one of a push type motor, a drone motor or a ship motor.
9. The air pollution and nuisance investigation apparatus of any one of claims 1 to 7, wherein, The air pollution and nuisance investigation equipment is realized in the form of a robot dog.
10. An air pollution and nuisance investigation system characterized by, Comprise the air pollution and nuisance investigation equipment according to any one of claims 1 to 9 and a control terminal in communication connection with the air pollution and nuisance investigation equipment.