CN112769930A - Pollution trend prediction method and device, and pollution event monitoring device and equipment - Google Patents
Pollution trend prediction method and device, and pollution event monitoring device and equipment Download PDFInfo
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Abstract
The application provides a pollution trend prediction method and device, a pollution event monitoring device and equipment, which are applied to the field of air quality monitoring, and the method comprises the following steps: acquiring environmental data and position data; when the environmental data represent that the current environment has a pollution event, controlling a video acquisition device to acquire a video of the environment; identifying the video by using a pollution event identification model to obtain image data of the identified pollution event and a corresponding pollution event type; and predicting the pollution trend and sending a prediction result to the data platform. In the scheme, the video is acquired at the pollution site, and the pollution event is identified by using the image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading the video, and the cost for monitoring the pollution event is reduced. Meanwhile, the pollution trend can be predicted according to the data obtained by identification and the environmental data obtained by collection, so that the pollution can be controlled from the source.
Description
Technical Field
The application relates to the field of air quality monitoring, in particular to a pollution trend prediction method and device and a pollution event monitoring device and equipment.
Background
Road dust is one of the important reasons influencing air quality, and the road dust sources mainly come from dust pollution of construction sites, scattering and leakage of transport vehicles, uncovered soil and the like at present. At present, the method for solving the problem of road dust emission is to inhibit the dust emission by means of fog gun cars, watering lorries and the like, but the method cannot control pollution from the source.
Most of dust monitoring devices in the current market can only realize the function of monitoring pollutant concentration indexes, and cannot further predict the pollution trend of the current environment in real time. Wherein only a few devices are equipped with cameras, which can be used to discover contamination events. However, such monitoring devices equipped with a camera need to transmit real-time video data to a video data center through a wireless network, which causes high traffic cost, resulting in high cost of the monitoring device.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for predicting a pollution tendency, and a device and an apparatus for monitoring a pollution event, so as to solve the technical problem that the cost of monitoring the pollution event and predicting the pollution tendency is high.
In order to achieve the above purpose, the technical solutions provided in the embodiments of the present application are as follows:
in a first aspect, an embodiment of the present application provides a pollution tendency prediction method, including: acquiring environmental data acquired by a data acquisition device and position data acquired by a positioning device; when the environmental data represent that a pollution event exists in the current environment, controlling a video acquisition device to acquire a video of the environment; identifying the acquired video by using a pre-trained pollution event identification model to obtain image data of the identified pollution event and a corresponding pollution event type; and predicting a pollution trend according to the image data, the pollution event type, the environment data and the position data, and sending a prediction result to a data platform. In the scheme, the video is acquired at the pollution site, and the pollution event is identified by using the image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading the video, and the cost for monitoring the pollution event is reduced. Meanwhile, the pollution trend can be predicted according to the data obtained by identification and the environmental data obtained by collection, so that the pollution can be controlled from the source.
In an optional embodiment of the present application, the acquiring environmental data acquired by the data acquisition device includes: and receiving air pollution concentration data collected by a sensor for monitoring air pollution, wind speed and direction data collected by a wind speed and direction sensor and position data collected by a positioning device. In the above scheme, the pollution event monitoring equipment can be provided with a sensor for monitoring air pollution, a wind speed and direction sensor and a positioning device which are respectively used for acquiring air pollution concentration data, wind speed and direction data and position data, so that the processor can predict the pollution trend according to the acquired data and the result of image recognition, and pollution control from the source is realized.
In an alternative embodiment of the present application, the method further comprises: after a pollution event is monitored, an identification instruction is sent to other pollution event monitoring devices within a preset range, so that the other pollution event monitoring devices control the video acquisition device to acquire videos of the surrounding environment and identify the pollution event. In the above scheme, after one pollution event monitoring device monitors a pollution event, other surrounding pollution event monitoring devices can be directly informed to enter an identification mode, so that the comprehensive and multi-angle monitoring and image identification of the pollution event are realized.
In an optional embodiment of the present application, the predicting a pollution tendency according to the image data, the pollution event type, the environmental data, and the location data, and sending a prediction result to a data platform includes: determining a corresponding pollution trend prediction model according to the pollution event type; superposing the environmental data and the position data into the image data by using the pollution trend prediction model to obtain superposed data; and predicting the next place where the pollution event occurs according to the superposed data. In the above scheme, after the pollution event monitoring device collects environmental data such as air pollution concentration data, wind speed and direction data, position data and the like, the processor can predict the pollution trend according to the collected data and the result of image recognition, so that pollution control from the source is realized.
In a second aspect, an embodiment of the present application provides a pollution tendency prediction apparatus, including: the acquisition module is used for acquiring the environmental data acquired by the data acquisition device and the position data acquired by the positioning device; the control module is used for controlling the video acquisition device to carry out video acquisition on the environment when the environmental data represent that the current environment has a pollution event; the identification module is used for identifying the acquired video by using a pre-trained pollution event identification model to obtain the image data of the identified pollution event and the corresponding pollution event type; and the prediction module is used for predicting the pollution trend according to the image data, the pollution event type, the environment data and the position data and sending a prediction result to a data platform. In the scheme, the video is acquired at the pollution site, and the pollution event is identified by using the image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading the video, and the cost for monitoring the pollution event is reduced. Meanwhile, the pollution trend can be predicted according to the data obtained by identification and the environmental data obtained by collection, so that the pollution can be controlled from the source.
In an optional embodiment of the present application, the obtaining module is further configured to: and receiving air pollution concentration data collected by a sensor for monitoring air pollution, wind speed and direction data collected by a wind speed and direction sensor and position data collected by a positioning device. In the above scheme, the pollution event monitoring equipment can be provided with a sensor for monitoring air pollution, a wind speed and direction sensor and a positioning device which are respectively used for acquiring air pollution concentration data, wind speed and direction data and position data, so that the processor can predict the pollution trend according to the acquired data and the result of image recognition, and pollution control from the source is realized.
In an optional embodiment of the present application, the pollution tendency prediction apparatus further comprises: and the sending module is used for sending an identification instruction to other pollution event monitoring devices within a preset range after monitoring the pollution event so as to enable the other pollution event monitoring devices to control the video acquisition device to carry out video acquisition on the surrounding environment and identify the pollution event. In the above scheme, after one pollution event monitoring device monitors a pollution event, other surrounding pollution event monitoring devices can be directly informed to enter an identification mode, so that the comprehensive and multi-angle monitoring and image identification of the pollution event are realized.
In an optional embodiment of the present application, the prediction module is further configured to determine a corresponding pollution trend prediction model according to the pollution event type; superposing the environmental data and the position data into the image data by using the pollution trend prediction model to obtain superposed data; and predicting the next place where the pollution event occurs according to the superposed data. In the above scheme, after the pollution event monitoring device collects environmental data such as air pollution concentration data, wind speed and direction data, position data and the like, the processor can predict the pollution trend according to the collected data and the result of image recognition, so that pollution control from the source is realized.
In a third aspect, an embodiment of the present application provides a pollution event monitoring device, including: a processor for performing the pollution tendency prediction method as described in the first aspect; a memory coupled to the processor; and the communication device is connected with the processor and the memory and is used for transmitting data to a data platform. In the above scheme, the processor in the pollution event monitoring device can identify the pollution event by using an image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading videos, and the cost of monitoring the pollution event is reduced. Meanwhile, the processor can predict the pollution trend according to the data obtained by identification and the environmental data obtained by collection, thereby realizing the control of pollution from the source.
In an alternative embodiment of the present application, the method further comprises: and the positioning device is connected with the processor. In the above scheme, the pollution event monitoring device can also be provided with a positioning device for collecting position information to realize positioning of the pollution event, thereby realizing pollution control from a source.
In a fourth aspect, embodiments of the present application provide a contamination event monitoring device, including: an apparatus body; a contamination event monitoring device as recited in the third aspect, provided inside the apparatus body; the data acquisition device is arranged in the equipment body, is connected with the processor in the pollution event monitoring device and is used for acquiring environmental data; and the video acquisition device is arranged outside the equipment body, is connected with the processor and is used for acquiring environmental video data. In the above solution, the pollution event monitoring device may include a pollution event monitoring apparatus, configured to identify a pollution event by using an image identification technology; the system can also comprise a video acquisition device for acquiring videos so as to realize real-time monitoring of pollution events; the system can also comprise a data acquisition device, so that the pollution trend can be predicted by combining the video and the acquired data, and pollution control from the source is realized.
In an optional embodiment of the present application, the data acquisition device comprises: the sensor is used for monitoring air pollution and is used for acquiring air pollution concentration data of the environment; and the wind speed and direction sensor is used for acquiring wind speed and direction data of the environment. In the above scheme, the pollution event monitoring equipment can be provided with a sensor for monitoring air pollution and a wind speed and direction sensor which are respectively used for acquiring air pollution concentration data and wind speed and direction data, so that the pollution event monitoring device can predict the pollution trend according to the acquired data and the result of image recognition, and pollution control from the source is realized.
In an optional embodiment of the present application, the video capture device comprises: the holder is arranged outside the equipment body; the video acquisition module is arranged on the holder; and the holder is used for driving the video acquisition module to move when receiving the control instruction sent by the processor. In the above scheme, video acquisition device can include the cloud platform, and the cloud platform can drive the video acquisition module of setting on the cloud platform to make video acquisition module can gather the omnidirectional video, thereby can improve the scope of monitoring, prevent to miss examining.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a block diagram of a contamination event monitoring apparatus according to an embodiment of the present disclosure;
FIG. 2 is a schematic view of a contamination event monitoring apparatus according to an embodiment of the present application;
fig. 3 is a flowchart of a pollution tendency prediction method according to an embodiment of the present application;
FIG. 4 is a flow chart of another pollution tendency prediction method provided in the embodiments of the present application;
fig. 5 is a block diagram of a pollution tendency prediction apparatus according to an embodiment of the present application.
Icon: 100-a contamination event monitoring device; 110-a processor; 120-a memory; 130-a communication device; 140-a positioning device; 200-a contamination event monitoring device; 210-an equipment body; 220-a data acquisition device; 221-sensors to monitor air pollution; 222-wind speed and direction sensor; 230-a video capture device; 231-a pan-tilt; 232-video capture module.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a block diagram of a contamination event monitoring device according to an embodiment of the present disclosure, in which the contamination event monitoring device 100 may include: a processor 110, a memory 120, and a communication device 130.
Specifically, the processor 110 provided in the embodiment of the present application may be an integrated circuit chip having signal processing capability. The Processor 110 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also 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. Which may implement or perform the various methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
As one embodiment, the processor 110 may include both CPUs and embedded Neural-Network Processors (NPUs). The CPU is used for receiving data sent by external equipment, sending the data to the data platform, sending a control instruction to the external equipment and the like; the NPU is used for performing image recognition, trend prediction and other steps. The specific steps respectively executed by the CPU and the NPU are not specifically limited in the embodiment of the present application, and those skilled in the art may appropriately adjust the steps according to actual situations.
As another embodiment, the processor 110 may include only a CPU, that is, all steps performed by the processor 110 are performed by the CPU.
The Memory 120 provided in the embodiment of the present application may include, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The memory 120 may be connected to the processor 110, and the processor 110 may send data to the memory 120 for storage after receiving data sent by an external device or obtaining processed data; the processor 110 may also read corresponding data from the memory 120 when needed.
The communication device 130 provided by the embodiment of the application can communicate with external devices in Wi-fi, bluetooth, mobile communication networks (2G, 3G, 4G, 5G), Lora and other manners. The communication device 130 may be connected to the processor 110 and the memory 120, and is used for transmitting data in the processor 110 and the memory 120 to a data platform.
The processor 110 can perform related processing on the data, so that the data sent to the data platform by the pollution event monitoring device is processed data, a large amount of flow is not consumed in the data transmission process, and the data platform can directly summarize and analyze the data after receiving the data sent by the pollution event monitoring devices, so that the computation load of the data platform is reduced. The data platform can also form a relevant decision for processing the pollution event according to the received data and sends the decision to the manager, so that the manager can timely perform field processing, and the pollution event is favorably processed.
It is understood that the contamination event monitoring device provided in the embodiment of the present application may be a motherboard, and the processor 110, the memory 120, and the communication device 130 are all a template on the motherboard; the contamination event monitoring device provided by the embodiments of the present application may also be composed of a plurality of independent parts, for example: the processor 110 is a single chip, the memory 120 and the communication device 130 are disposed on the same motherboard, which is not limited in this embodiment.
Therefore, the processor in the pollution event monitoring device can identify the pollution event by using an image identification technology, and therefore, the pollution event monitoring cost can be reduced by uploading the pollution event to a data platform instead of directly uploading a video. Meanwhile, the processor can predict the pollution trend according to the data obtained by identification and the environmental data obtained by collection, thereby realizing the control of pollution from the source.
Further, referring to fig. 1, the contamination event monitoring apparatus provided in the embodiment of the present application may further include a positioning device 140.
Specifically, the Positioning device 140 provided in the embodiment of the present application may be implemented by a Global Positioning System (GPS), a beidou satellite navigation System, or the like, which is not specifically limited in the embodiment of the present application. The positioning device 140 may be connected to the processor 110 for collecting position information to position the contamination event, thereby controlling the contamination from the source.
Referring to fig. 2, fig. 2 is a schematic view of a pollution event monitoring device according to an embodiment of the present application, where the pollution event monitoring device 200 may include: an equipment body 210, a pollution event monitoring device 100, a data acquisition device 220, and a video acquisition device 230.
In particular, the shape of the device body 210 may be implemented in various ways, for example: the device body 210 is a vertical pole, the pollution event monitoring device 100 and the data acquisition device 220 can be arranged inside the vertical pole, and the video acquisition device 230 can be arranged outside the vertical pole; alternatively, the apparatus body 210 is a box, and likewise, the contamination event monitoring device 100 and the data collection device 220 may be disposed inside the box, and the video collection device 230 may be disposed outside the box. The embodiments of the present application are not specifically limited, and those skilled in the art can make appropriate adjustments according to actual situations.
It should be understood that the above-mentioned arrangement inside the device body 210 may mean that the pollution event monitoring device 100 and the data acquisition device 220 are arranged inside the device body 210 itself, or that an additional outdoor housing is arranged on the device body 210, and the pollution event monitoring device 100 and the data acquisition device 220 are arranged inside the outdoor housing. In addition, a part of the data acquisition device 220 may be disposed inside the apparatus body 210, and another part may be disposed outside the apparatus body 210; or all of them are arranged inside the device body 210, and the embodiment of the present application can be adjusted appropriately according to the actual situation.
In addition, the material of the device body 210 is not specifically limited in the embodiment of the present application, and those skilled in the art can appropriately select the material according to actual situations. For example, if the contamination event monitoring device 200 is installed outdoors, a waterproof material may be used; if the contamination event monitoring device 200 is located in a region with a relatively high temperature, a material with high temperature resistance may be used.
The data collection device 220 provided in the embodiment of the present application may be connected to the processor 110 in the contamination event monitoring device 100 in the above-mentioned embodiment, and is used for collecting environmental data.
As an embodiment, the data acquisition device 220 may include: a sensor 221 for monitoring air pollution and a wind speed and direction sensor 222. Wherein, the sensor 221 for monitoring air pollution is used for collecting air pollution concentration data of the environment, such as: PM2.5, PM10, TSP, CO, SO2, NO2, O3, TVOC and the like; the wind speed and direction sensor 222 is used for collecting wind speed and direction data of the current environment.
Therefore, a sensor for monitoring air pollution and a wind speed and direction sensor can be arranged on the pollution event monitoring equipment and are respectively used for collecting air pollution concentration data and wind speed and direction data, so that the pollution event monitoring device can predict the pollution trend according to the collected data and the result of image recognition, and pollution control from the source is realized.
The video capture device 230 provided in the embodiment of the present application may be connected to the processor 110 in the pollution event monitoring device 100 in the above-mentioned embodiment, and is configured to capture environmental video data.
As an embodiment, the video capture device 230 may include: a pan-tilt 231 and a video capture module 232. Wherein, video acquisition module 232 can set up on cloud platform 231, and cloud platform 231 can set up outside equipment body 210 for when receiving the control command that processor 110 sent, can drive above-mentioned video acquisition module 232 motion.
Therefore, the video acquisition device can comprise a cloud platform, and the cloud platform can drive the video acquisition module arranged on the cloud platform, so that the video acquisition module can acquire omnibearing video, the monitoring range can be improved, and missing detection is prevented.
As shown in fig. 1, the device body 210 is a vertical rod, and the pollution event monitoring apparatus 100 is connected to a sensor 221 for monitoring air pollution, an air speed and direction sensor 222, a pan-tilt 231, and a video acquisition module 232 through data lines. An outdoor shell is arranged on the vertical rod, the pollution event monitoring device 100 and the sensor 221 for monitoring air pollution are arranged in the outdoor shell, and the sensor 221 for monitoring air pollution can sample ambient air in an air extraction mode; wind speed and direction sensor 222 and pan-tilt 231 are arranged on the vertical rod, and video acquisition module 232 is arranged on pan-tilt 231.
In the above solution, the pollution event monitoring device may include a pollution event monitoring apparatus, configured to identify a pollution event by using an image identification technology; the system can also comprise a video acquisition device for acquiring videos so as to realize real-time monitoring of pollution events; the system can also comprise a data acquisition device, so that the pollution trend can be predicted by combining the video and the acquired data, and pollution control from the source is realized.
Based on the pollution event monitoring device 100 and the pollution event monitoring apparatus 200, the embodiment of the present application further provides a pollution trend prediction method, which can be applied to the processor 110. Referring to fig. 3, fig. 3 is a flowchart of a pollution tendency prediction method according to an embodiment of the present disclosure, where the pollution tendency prediction method includes the following steps:
step S301: and acquiring environmental data acquired by the data acquisition device and position data acquired by the positioning device.
Step S302: and when the environmental data represent that the current environment has a pollution event, controlling the video acquisition device to acquire the video of the environment.
Step S303: and identifying the acquired video by using a pre-trained pollution event identification model to obtain the image data of the identified pollution event and the corresponding pollution event type.
Step S304: and predicting the pollution trend according to the image data, the pollution event type, the environmental data and the position data, and sending a prediction result to the data platform.
Specifically, the processor may first obtain environmental data collected by the data collection device. The processor may receive the environmental data sent by the data acquisition device, for example; or the data acquisition device uploads the acquired environmental data to the cloud end, and the processor reads the environmental data from the cloud end. This is not particularly limited by the examples of the present application.
As an embodiment, if the data acquisition device includes a sensor for monitoring air pollution and a wind speed and direction sensor, the step of acquiring the environmental data acquired by the data acquisition device may include the steps of:
and receiving air pollution concentration data collected by a sensor for monitoring air pollution and wind speed and direction data collected by a wind speed and direction sensor.
Therefore, a sensor for monitoring air pollution, a wind speed and direction sensor and a positioning device can be arranged on the pollution event monitoring equipment and are respectively used for acquiring air pollution concentration data, wind speed and direction data and position data, so that the processor can predict the pollution trend according to the acquired data and the result of image recognition, and pollution control from the source is realized.
The processor may also obtain the position data collected by the positioning device at the same time, wherein the mode of obtaining the position data is similar to the mode of obtaining the ear canal of the environmental data, and is not described herein again.
It can be understood that the data acquisition device and the positioning device may send data to the processor according to a preset time interval, where the preset time interval may be a time interval preset by a manager, and this is not specifically limited in this embodiment of the application.
After the processor acquires the environmental data, whether the environmental data represent that a pollution event exists in the current environment or not can be judged, and the video acquisition device is controlled to acquire the video of the surrounding environment when the environmental data represent that the pollution event does not exist in the current environment. Taking the sensor for monitoring air pollution as an example, when each index of the air pollution concentration in the air pollution concentration data collected by the sensor for monitoring air pollution exceeds a preset concentration threshold, the environmental data can be considered to represent that a pollution event exists in the current environment. The preset concentration threshold may also be a concentration preset by a manager, and this is not specifically limited in this embodiment of the application.
The processor may then identify the captured video using a pre-trained contamination event identification model. The pre-trained pollution event recognition model is obtained by training a machine learning model by using a training sample, and the training process can adopt the prior art, so that the detailed description is omitted here.
In a road raise dust monitoring scene, the types of pollution events generally include a raise dust pollution event, a slag car non-covering event and a bare soil non-covering event. That is, the input of the contamination time identification model is the video collected by the video collection device, and the output result is the type of the contamination event corresponding to each frame of image. It can be understood that, since the contamination event occurs from a certain time, there may not be a corresponding contamination event in each frame of image in the acquired video, and there may not be a corresponding contamination event in the image of a part of frames, so that the processor may obtain the image with the contamination event while obtaining the type of the contamination event output by the contamination event identification model, and send the image with the contamination event and the corresponding contamination event to the data platform together.
In addition, the processor may also combine the image data, the pollution event type, the environmental data, the location data, and other data obtained in the above embodiments to predict the pollution trend in the surrounding environment. As an implementation manner, referring to fig. 4, fig. 4 is a flowchart of another pollution tendency prediction method provided in an embodiment of the present application, in the pollution tendency prediction method, the step of predicting the pollution tendency according to the image data, the pollution event type, the environmental data, and the location data may include the following steps:
step S401: and determining a corresponding pollution trend prediction model according to the pollution event type.
Step S402: and superposing the environmental data to the image data by using the pollution trend prediction model to obtain superposed data.
Step S403: and predicting the next place where the pollution event occurs according to the superposed data.
The processor may store a pollution trend prediction model corresponding to each pollution event type, and after the processor acquires the image data and the corresponding pollution event type, the corresponding pollution trend prediction model may be determined according to the pollution event type.
Taking the dust pollution event as an example, because the pollution trend is strongly related to the wind speed and direction data, the wind speed and direction data can be superimposed on the image data to predict the next place where the dust pollution event occurs.
Therefore, after the pollution event monitoring device collects environmental data such as air pollution concentration data, wind speed and direction data, position data and the like, the processor can predict the pollution trend according to the collected data and the result of image recognition, and therefore pollution control from the source is achieved.
The processor can send the predicted result to the data platform, and the data platform can form a decision after receiving the pollution event, the image data, the environmental data and the position data and send the decision to a terminal of a manager, so that the manager can timely go to the site for processing.
In the scheme, the video is acquired at the pollution site, and the pollution event is identified by using the image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading the video, and the cost for monitoring the pollution event is reduced. Meanwhile, the pollution trend can be predicted according to the data obtained by identification and the environmental data obtained by collection, so that the pollution can be controlled from the source.
Further, the pollution tendency prediction method provided by the embodiment of the application may further include the following steps:
after the pollution event is monitored, an identification instruction is sent to other pollution event monitoring devices within a preset range, so that the other pollution event monitoring devices control the video acquisition device to acquire videos of the surrounding environment and identify the pollution event.
Specifically, after a certain pollution event monitoring device monitors a pollution event, other pollution event monitoring devices within a preset range can be informed to start a video acquisition device to perform video acquisition on the surrounding environment and identify the pollution event.
In the above scheme, after one pollution event monitoring device monitors a pollution event, other surrounding pollution event monitoring devices can be directly informed to enter an identification mode, so that the comprehensive and multi-angle monitoring and image identification of the pollution event are realized. The preset range may be a range preset by a manager, and this is not specifically limited in the embodiment of the present application.
In summary, the pollution trend prediction method provided by the embodiment of the application can identify pollution events by using an image identification technology on a pollution site, and uploads the pollution events to a data platform in a pollution event mode instead of a mode of directly uploading a video to the data platform, so that network pressure is reduced, and flow cost is saved. Meanwhile, the uploaded pollution event information is refined and intuitive, and the method has the convenience of directly forming a decision, so that the closed-loop flow of monitoring and treatment of a data platform is simplified, dyeing trend prediction information is formed, and an effective means can be provided for further pollution control. In addition, after a contamination event is discovered, the current trim can inform surrounding devices to perform a contamination event identification mode, locate and track the contamination source in an all-around manner, and finally lock the contamination source.
Referring to fig. 5, fig. 5 is a block diagram illustrating a pollution tendency prediction apparatus according to an embodiment of the present disclosure, where the pollution tendency prediction apparatus includes: an obtaining module 501, configured to obtain environmental data collected by a data collecting device and position data collected by a positioning device; the control module 502 is configured to control the video acquisition device to perform video acquisition on the environment when the environmental data represents that a pollution event exists in the current environment; the recognition module 503 is configured to recognize the acquired video by using a pre-trained pollution event recognition model to obtain image data of the recognized pollution event and a corresponding pollution event type; and the prediction module 504 is configured to predict a pollution trend according to the image data, the pollution event type, the environmental data, and the location data, and send a prediction result to a data platform.
In the embodiment of the application, the video is collected at the pollution site, and the pollution event is identified by using the image identification technology, so that the pollution event can be uploaded to a data platform instead of a mode of directly uploading the video, and the cost for monitoring the pollution event is reduced. Meanwhile, the pollution trend can be predicted according to the data obtained by identification and the environmental data obtained by collection, so that the pollution can be controlled from the source.
Further, the obtaining module 501 is further configured to: and receiving air pollution concentration data collected by a sensor for monitoring air pollution, wind speed and direction data collected by a wind speed and direction sensor and position data collected by a positioning device.
In the embodiment of the application, a sensor for monitoring air pollution, a wind speed and direction sensor and a positioning device can be arranged on the pollution event monitoring equipment and are respectively used for acquiring air pollution concentration data, wind speed and direction data and position data, so that a processor can predict the pollution trend according to the acquired data and the result of image recognition, and pollution control from the source is realized.
Further, the pollution tendency prediction apparatus 500 further includes: and the sending module is used for sending an identification instruction to other pollution event monitoring devices within a preset range after monitoring the pollution event so as to enable the other pollution event monitoring devices to control the video acquisition device to carry out video acquisition on the surrounding environment and identify the pollution event.
In the embodiment of the application, after one pollution event monitoring device monitors a pollution event, other surrounding pollution event monitoring devices can be directly informed to enter the identification mode, so that the all-dimensional and multi-angle monitoring and image identification of the pollution event are realized.
Further, the prediction module 504 is further configured to determine a corresponding pollution trend prediction model according to the pollution event type; superposing the environmental data and the position data into the image data by using the pollution trend prediction model to obtain superposed data; and predicting the next place where the pollution event occurs according to the superposed data.
In the embodiment of the application, after the pollution event monitoring device collects environmental data such as air pollution concentration data, wind speed and direction data, position data and the like, the processor can predict the pollution trend according to the collected data and the result of image recognition, so that pollution control from the source is realized.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A pollution tendency prediction method, comprising:
acquiring environmental data acquired by a data acquisition device and position data acquired by a positioning device;
when the environmental data represent that a pollution event exists in the current environment, controlling a video acquisition device to acquire a video of the environment;
identifying the acquired video by using a pre-trained pollution event identification model to obtain image data of the identified pollution event and a corresponding pollution event type;
and predicting a pollution trend according to the image data, the pollution event type, the environment data and the position data, and sending a prediction result to a data platform.
2. The pollution tendency prediction method according to claim 1, wherein the acquiring environmental data collected by the data collection device comprises:
and receiving air pollution concentration data collected by a sensor for monitoring air pollution and wind speed and direction data collected by a wind speed and direction sensor.
3. The pollution tendency prediction method according to claim 1, further comprising:
after a pollution event is monitored, an identification instruction is sent to other pollution event monitoring devices within a preset range, so that the other pollution event monitoring devices control the video acquisition device to acquire videos of the surrounding environment and identify the pollution event.
4. The pollution tendency prediction method according to claim 1, wherein the predicting the pollution tendency based on the image data, the pollution event type, the environmental data, and the location data comprises:
determining a corresponding pollution trend prediction model according to the pollution event type;
superposing the environmental data and the position data into the image data by using the pollution trend prediction model to obtain superposed data;
and predicting the next place where the pollution event occurs according to the superposed data.
5. A pollution tendency prediction apparatus, comprising:
the acquisition module is used for acquiring the environmental data acquired by the data acquisition device and the position data acquired by the positioning device;
the control module is used for controlling the video acquisition device to acquire video of the current environment when the environmental data represent that the current environment has a pollution event;
the identification module is used for identifying the acquired video by using a pre-trained pollution event identification model to obtain the image data of the identified pollution event and the corresponding pollution event type;
and the prediction module is used for predicting the pollution trend according to the image data, the pollution event type, the environment data and the position data and sending a prediction result to a data platform.
6. A contamination event monitoring device, comprising:
a processor for performing the pollution tendency prediction method according to any one of claims 1 to 4;
a memory coupled to the processor;
and the communication device is connected with the processor and the memory and is used for transmitting data to a data platform.
7. The contamination event monitoring device of claim 6, further comprising:
and the positioning device is connected with the processor.
8. A contamination event monitoring apparatus, comprising:
an apparatus body;
the contamination event monitoring device of claim 6 or 7, disposed inside the apparatus body;
the data acquisition device is arranged in the equipment body, is connected with the processor in the pollution event monitoring device and is used for acquiring environmental data;
and the video acquisition device is arranged outside the equipment body, is connected with the processor and is used for acquiring environmental video data.
9. The contamination event monitoring apparatus of claim 8, wherein the data acquisition device comprises:
the sensor is used for monitoring air pollution and is used for acquiring air pollution concentration data of the environment;
and the wind speed and direction sensor is used for acquiring wind speed and direction data of the environment.
10. The contamination event monitoring apparatus of claim 8, wherein the video capture device comprises:
the holder is arranged outside the equipment body;
the video acquisition module is arranged on the holder;
and the holder is used for driving the video acquisition module to move when receiving the control instruction sent by the processor.
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