CN114325875A - Weather station equipment control method and equipment - Google Patents
Weather station equipment control method and equipment Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a control method and equipment for meteorological station equipment, wherein the method comprises the following steps: the method comprises the steps of obtaining audio and video data, obtaining collected meteorological data collected by a meteorological sensor of a target meteorological station, obtaining estimated meteorological data according to the audio and video data, verifying the collected meteorological data according to the estimated meteorological data, and sending the collected meteorological data in response to the fact that the collected meteorological data is successfully verified. The technical scheme can improve the reliability of the uploaded meteorological data.
Description
Technical Field
The disclosure relates to the technical field of atmospheric detection and atmospheric remote sensing, in particular to a control method and equipment for meteorological station equipment.
Background
In recent years, with the rapid progress of the construction work of meteorological stations in China, the number and the types of meteorological sensors arranged in the meteorological stations are more and more, the data volume of sensor data acquired by the meteorological sensors is increased, a large amount of sensor data is uploaded in a concurrent mode, and great pressure is applied to the transmission bandwidth of the meteorological stations.
In the related art, a weather station device equipped with a weather integrated processor may be provided at a weather station, and the weather station device may receive sensor data uploaded by a weather sensor, summarize and process the sensor data uploaded by the weather sensor, and upload the processed weather data to a weather management platform at an upper level. In this solution, although the data amount of the weather data processed by the weather integration processor is small, in practical applications, a situation may occur in which the value of the sensor data uploaded by the weather sensor exceeds a reasonable value range, that is, a situation in which the value of the sensor data uploaded by the weather sensor is greatly different from the value of the sensor data in a normal situation, and when such a situation occurs, the weather integration processor cannot determine whether the situation is caused by extreme weather at the location of the weather station or caused by a weather sensor fault, thereby reducing the reliability of the weather data uploaded by the weather integration processor.
Disclosure of Invention
The embodiment of the disclosure provides a control method and equipment for meteorological station equipment.
In a first aspect, an embodiment of the present disclosure provides a weather station device control method, including:
acquiring audio and video data, wherein the audio and video data comprise at least one of a target image and a target audio, the target image is acquired by image acquisition equipment located at a target weather station, and the target audio is acquired by audio acquisition equipment located at the target weather station;
acquiring collected meteorological data collected by a meteorological sensor of a target meteorological station;
acquiring estimated meteorological data according to the audio and video data, and verifying the acquired meteorological data according to the estimated meteorological data;
and sending the collected meteorological data in response to the successful verification of the collected meteorological data.
In one implementation of the present disclosure, audio and video data is obtained, including;
receiving a target image sent by image acquisition equipment through a wireless fidelity Wi-Fi network;
and/or receiving target audio sent by the audio acquisition equipment through the wireless fidelity Wi-Fi network.
In one implementation of the present disclosure, verifying collected meteorological data according to estimated meteorological data includes:
and verifying the collected meteorological data according to the estimated meteorological data in response to the fact that the data value of the collected meteorological data does not belong to the preset meteorological data value interval.
In one implementation of the present disclosure, the meteorological sensor includes at least one of a wind speed sensor, a wind direction sensor, an air pressure sensor, an air particle sensor, an air hazard sensor, an atmospheric temperature sensor, a surface temperature sensor, an underground 1 meter temperature sensor, an underground 2 meter temperature sensor, an underground 5 meter temperature sensor, a humidity sensor, a rainfall sensor, an ultraviolet sensor, and an infrared sensor.
In one implementation of the present disclosure, the target image includes at least one set of weather sensors, or the target image includes at least a portion of the target weather station;
and/or the distance between the audio acquisition device and the meteorological sensor is less than or equal to the audio acquisition distance threshold.
In one implementation of the present disclosure, estimated weather data is obtained from audio and video data, including;
and acquiring a pre-trained meteorological data estimation model, inputting audio and video data serving as input into the meteorological data estimation model, and acquiring estimated meteorological data output by the meteorological data estimation model.
In an implementation manner of the present disclosure, before acquiring audio/video data, the method further includes:
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
and training the initial meteorological data estimation model to acquire the meteorological data estimation model by taking historical audio and video data as input and historical meteorological data corresponding to the historical audio and video data as output.
In an implementation manner of the present disclosure, before acquiring audio/video data, the method further includes:
receiving an update weight parameter sent by the edge server, and updating the private meteorological data estimation model according to the update weight parameter to obtain an updated private meteorological data estimation model;
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
taking historical audio and video data as input, taking historical meteorological data corresponding to the historical audio and video data as output, and training the updated private meteorological data estimation model;
when the trained private meteorological data estimation model is not converged, acquiring a gradient update vector according to the trained private meteorological data estimation model, and sending the gradient update vector, wherein the edge server is used for aggregating the gradient update vector, and updating the weight parameters of the common meteorological data estimation model of the edge server according to the aggregated gradient update vector to acquire updated weight parameters;
and when the trained private meteorological data estimation model is converged, acquiring the meteorological data estimation model according to the trained private meteorological data estimation model.
In one implementation of the present disclosure, before receiving an update weight parameter sent by an edge server, and updating a private meteorological data estimation model according to the update weight parameter to obtain an updated private meteorological data estimation model, the method further includes:
receiving a private data uploading instruction;
responding to a private data uploading instruction, and acquiring at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data;
the method comprises the steps that at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data are sent, an edge server is used for inputting the sampling historical audio and video data, outputting the historical meteorological data corresponding to the sampling historical audio and video data, training an initial meteorological data estimation model to obtain a common meteorological data estimation model, obtaining an initial weight parameter according to the common meteorological data estimation model and sending the initial weight parameter;
receiving an initial weight parameter sent by an edge server;
and updating the initial meteorological data estimation model according to the initial weight parameters to obtain a private meteorological data estimation model.
In a second aspect, an embodiment of the present invention provides a weather station device control apparatus, including:
the first data acquisition module is configured to acquire audio and video data, wherein the audio and video data comprise at least one of a target image and a target audio, the target image is acquired by image acquisition equipment located at a target weather station, and the target audio is acquired by audio acquisition equipment located at the target weather station;
a second data acquisition module configured to acquire collected weather data collected by weather sensors of a target weather station;
the third data acquisition module is configured to acquire estimated meteorological data according to the audio and video data and verify the acquired meteorological data according to the estimated meteorological data;
and the data transmitting module is configured to respond to the verification success of the collected meteorological data and transmit the collected meteorological data.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement any one of the methods in the first aspect.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for use by any one of the above apparatuses, the computer instructions, when executed by a processor, being configured to implement the method of any one of the above aspects.
In a fifth aspect, the disclosed embodiments provide a computer program product comprising computer instructions that, when executed by a processor, implement the method of any one of the above aspects.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the method comprises acquiring audio/video data including at least one of a target image acquired by an image acquisition device located at a target weather station and a target audio acquired by the image acquisition device located at the target weather station, acquiring acquired weather data acquired by a weather sensor at the target weather station, acquiring estimated weather data according to the audio/video data, and acquiring estimated weather data according to the audio/video data, wherein the estimated weather data is weather data estimated according to at least one of an image acquired at the target weather station and an audio, since the image and the audio acquired at the target weather station are not affected by a failure of the weather sensor, the estimated weather data is close to weather data corresponding to a real weather environment at the target weather station, and when the verification is passed, the collected meteorological data does not have a large difference with the meteorological data corresponding to the real meteorological environment at the target meteorological station, and the meteorological sensor for collecting the meteorological data does not have a fault and can respond to the successful verification of the collected meteorological data and send the collected meteorological data. Therefore, the technical scheme provided by the embodiment of the disclosure can improve the reliability of the uploaded meteorological data.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 shows a flow chart of a weather station apparatus control method according to an embodiment of the present disclosure;
FIG. 2 is a schematic block diagram of a weather station equipment control device according to an embodiment of the present disclosure;
FIG. 3 shows a schematic block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 4 shows a schematic structural diagram of an electronic device for implementing a weather station device control method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, actions, components, parts, or combinations thereof, and do not preclude the possibility that one or more other features, numbers, steps, actions, components, parts, or combinations thereof are present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In recent years, with the rapid progress of the construction work of meteorological stations in China, the number and the types of meteorological sensors arranged in the meteorological stations are more and more, the data volume of sensor data acquired by the meteorological sensors is increased, a large amount of sensor data is uploaded in a concurrent mode, and great pressure is applied to the transmission bandwidth of the meteorological stations.
In the related art, a weather station device equipped with a weather integrated processor may be provided at a weather station, and the weather station device may receive sensor data uploaded by a weather sensor, summarize and process the sensor data uploaded by the weather sensor, and upload the processed weather data to a weather management platform at an upper level. In this solution, although the data amount of the weather data processed by the weather integration processor is small, in practical applications, a situation may occur in which the value of the sensor data uploaded by the weather sensor exceeds a reasonable value range, that is, a situation in which the value of the sensor data uploaded by the weather sensor is greatly different from the value of the sensor data in a normal situation, and when such a situation occurs, the weather integration processor cannot determine whether the situation is caused by extreme weather at the location of the weather station or caused by a weather sensor fault, thereby reducing the reliability of the weather data uploaded by the weather integration processor.
To solve the above problems, the present disclosure acquires audio/video data including at least one of a target image acquired by an image acquisition device located at a target weather station and a target audio acquired by the image acquisition device located at the target weather station, acquires acquired weather data acquired by a weather sensor at the target weather station, acquires estimated weather data based on the audio/video data, and acquires estimated weather data based on the audio/video data, wherein the estimated weather data is weather data estimated based on at least one of an image acquired at the target weather station and an audio, since the image and the audio acquired at the target weather station are not affected by a malfunction of the weather sensor, the estimated weather data is close to weather data corresponding to a real weather environment at the target weather station, the acquired weather data is verified based on the estimated weather data, when the verification is passed, the fact that the difference between the collected meteorological data and the meteorological data corresponding to the real meteorological environment at the target meteorological station is not large indicates that the meteorological sensor for collecting the meteorological data does not have a fault, and the collected meteorological data can be transmitted in response to the successful verification of the collected meteorological data. Therefore, the technical scheme provided by the embodiment of the disclosure can improve the reliability of the uploaded meteorological data.
The details of the embodiments of the present disclosure are described in detail below with reference to specific embodiments.
Fig. 1 shows a flowchart of a weather station apparatus control method according to an embodiment of the present disclosure, and as shown in fig. 1, the weather station apparatus control method includes the following steps S101 to S104:
in step S101, audio-video data is acquired.
The audio and video data comprises at least one of a target image and a target audio, the target image is collected by an image collecting device located at the target weather station, and the target audio is collected by an audio collecting device located at the target weather station.
In an embodiment of the present disclosure, the obtaining of the audio/video data may be reading pre-stored audio/video data, or receiving audio/video data sent by other devices or systems. For example, the weather station device may receive the target image transmitted by the image capture device at the target weather station and the target audio transmitted by the target image audio capture device via a wired or wireless connection.
In step S102, collected weather data collected by weather sensors of a target weather station is acquired.
In one embodiment of the present disclosure, the acquisition of the collected weather data collected by the weather sensor of the target weather station may be to read the collected weather data stored in advance, or to receive the collected weather data transmitted by other devices or systems. For example, the weather station device may receive collected weather data collected by the weather sensors of the target weather station via a wired or wireless connection, and transmitted by the weather sensors.
In one embodiment of the present disclosure, the meteorological sensor includes at least one of a wind speed sensor, a wind direction sensor, an air pressure sensor, an air particle sensor, an air noxious substance sensor, an atmospheric temperature sensor, a surface temperature sensor, an underground 1 meter temperature sensor, an underground 2 meter temperature sensor, an underground 5 meter temperature sensor, a humidity sensor, a rainfall sensor, an ultraviolet sensor, and an infrared sensor.
In step S103, estimated weather data is acquired according to the audio/video data, and the collected weather data is verified according to the estimated weather data.
In one embodiment of the present disclosure, the estimated meteorological data is obtained according to the audio/video data, which may be searched in a pre-stored audio/video data database according to the audio/video data to obtain the estimated meteorological data, wherein the audio/video data database is used to indicate a corresponding relationship between the audio/video data and the meteorological data; or calculation can be performed based on a pre-acquired algorithm and audio/video data to acquire estimated meteorological data. For example, when the audio/video data includes a target image, the target image may be identified based on a pre-acquired image identification algorithm, and the estimated weather data may be acquired according to the identification result.
In an embodiment of the present disclosure, the collected meteorological data is verified according to the estimated meteorological data, a data difference between a data value of the estimated meteorological data and a data value of the collected meteorological data is calculated, and when the data difference is smaller than or equal to a preset data difference threshold, it is determined that the data value in the collected meteorological data satisfies a verification condition, and the collected meteorological data is verified successfully. Further, when the collected meteorological data includes a plurality of different types of data values, it may be determined that the collected meteorological data is verified successfully when the number of types of data values satisfying the verification condition in the collected meteorological data is greater than the type number threshold.
In step S104, in response to the verification of the collected weather data being successful, the collected weather data is transmitted.
The method comprises acquiring audio/video data including at least one of a target image acquired by an image acquisition device located at a target weather station and a target audio acquired by the image acquisition device located at the target weather station, acquiring acquired weather data acquired by a weather sensor at the target weather station, acquiring estimated weather data according to the audio/video data, and acquiring estimated weather data according to the audio/video data, wherein the estimated weather data is weather data estimated according to at least one of an image acquired at the target weather station and an audio, since the image and the audio acquired at the target weather station are not affected by a failure of the weather sensor, the estimated weather data is close to weather data corresponding to a real weather environment at the target weather station, and when the verification is passed, the collected meteorological data does not have a large difference with the meteorological data corresponding to the real meteorological environment at the target meteorological station, and the meteorological sensor for collecting the meteorological data does not have a fault and can respond to the successful verification of the collected meteorological data and send the collected meteorological data. Therefore, the technical scheme provided by the embodiment of the disclosure can improve the reliability of the uploaded meteorological data.
In one implementation manner of the present disclosure, in step S101, obtaining audio/video data may be implemented by the following steps;
receiving a target image sent by image acquisition equipment through a wireless fidelity Wi-Fi network;
and/or receiving target audio sent by the audio acquisition equipment through the wireless fidelity Wi-Fi network.
In an embodiment of the present disclosure, a Wi-Fi module of a weather integration processor in a weather Station device may be set to a Wireless Access Point (AP) mode, and Wi-Fi modules on an image acquisition device and an audio acquisition device may be set to a workstation (STA) mode, so that the weather integration processor in the weather Station device serves as a central node of a Wi-Fi network, and the image acquisition device and the audio acquisition device can join the Wi-Fi network.
In the embodiment, the target image sent by the image acquisition equipment is received through the wireless fidelity Wi-Fi network, and the target audio sent by the audio acquisition equipment is received through the wireless fidelity Wi-Fi network, so that the weather station equipment can be ensured to be simultaneously communicated with a large number of image acquisition equipment and audio acquisition equipment, and the communication quality is good.
In one implementation manner of the present disclosure, in step S103, verifying the collected meteorological data according to the estimated meteorological data may be implemented by:
and verifying the collected meteorological data according to the estimated meteorological data in response to the fact that the data value of the collected meteorological data does not belong to the preset meteorological data value interval.
In an embodiment of the present disclosure, the preset meteorological data value interval may be obtained by reading a preset meteorological data value interval stored in advance, or may be a preset meteorological data value interval transmitted by another device or system.
In the embodiment, the data value of the collected meteorological data is not within the preset meteorological data value interval, and the data value of the collected meteorological data can be considered to be normal without verification; the data value of the collected meteorological data does not belong to the preset meteorological data value interval, and the data value of the collected meteorological data can be considered to be abnormal.
In one implementation of the present disclosure, the target image includes at least one set of weather sensors, or the target image includes at least a portion of the target weather station;
and/or the distance between the audio acquisition device and the meteorological sensor is less than or equal to the audio acquisition distance threshold.
In an embodiment of the present disclosure, the target image may include at least one set of weather sensors by setting a lens direction of an image capturing device for capturing the target image to be directed to the at least one set of weather sensors. Alternatively, the target image may include at least a portion of the target weather station by orienting the lens of the image capture device used to capture the target image to point at any portion of the target weather station.
For example, a plurality of lens directions of the lens of the image acquisition device pointing to different weather sensors can be determined according to the position information of the image acquisition device and the position information of each weather sensor in the target weather station, and the operation of the pan-tilt of the image acquisition device is controlled based on the plurality of lens directions, so that the lens of the image acquisition device sequentially points to the plurality of lens directions, and the image acquisition device is controlled to acquire a target image when the lens of the image acquisition device points to each lens direction.
For example, a portion of the target weather station may be a level ground in the target weather station, or a portion of the target weather station may be an inclined ground with an inclination angle of a preset angle in the target weather station, or a portion of the target weather station may be a level ground with a drainage speed of a preset drainage speed in the target weather station, and a target image including the level ground, the inclined ground, or the level ground with the preset drainage speed may be used to estimate weather data such as precipitation of the target weather station.
In an embodiment of the present disclosure, the target image may also include the sky directly above the target weather station, and the target image including the sky may be used to estimate weather data such as cloud conditions above the target weather station.
In an embodiment of the present disclosure, the target image may also include plants near the target weather station, for example, the target weather station may include a plant growing area, the plant terminating area includes a plurality of sub-areas, each sub-area is used for growing a corresponding kind of plants, a planting density of each sub-area is a preset planting density corresponding to the sub-area, a planting period of each sub-area is a preset planting density period corresponding to the sub-area, a target image including the plant growing area may be collected by directing a lens of the image collecting device to the plant growing area, a growth condition of plants of different kinds, different planting periods and different planting densities may be determined according to the target image, and a plant lodging rate under at least one of the growth conditions (for example, frost, snow, dew, ice, rain, hail, rime and rime) is determined according to the growth condition, Plant mortality, etc.) can determine the corresponding meteorological data.
In this embodiment, the target image includes at least one set of weather sensors, or the target image includes at least a portion of the target weather station, which may ensure that the information in the target image is closely associated with the target weather station, facilitating the estimation of the corresponding weather data. The distance between the audio acquisition equipment and the meteorological sensor is smaller than or equal to the audio acquisition distance threshold value, so that the audio acquired by the audio acquisition equipment is ensured to be the audio in the working environment of the meteorological sensor, and the corresponding meteorological data can be estimated.
In one implementation manner of the present disclosure, in step S103, obtaining estimated meteorological data according to the audio/video data may be implemented by the following steps;
and acquiring a pre-trained meteorological data estimation model, inputting audio and video data serving as input into the meteorological data estimation model, and acquiring estimated meteorological data output by the meteorological data estimation model.
In an embodiment of the present disclosure, the meteorological data estimation model may be a Neural Network (NN) model, and specifically, the neural network model may be a pre-training network model in a Convolutional Neural Network (CNN) model, such as an iceposition model, a resnet model, and the like.
In an embodiment of the present disclosure, the pre-trained meteorological data estimation model may be obtained by reading a meteorological data estimation model stored in advance, or by receiving a meteorological data estimation model transmitted by another device or system. The meteorological data estimation model can be understood as a model which learns the rule between the audio and video data and the estimated meteorological data through pre-training.
In this embodiment, by acquiring the pre-trained meteorological data estimation model and inputting the audio/video data as input to the meteorological data estimation model to acquire the estimated meteorological data output by the meteorological data estimation model, it is possible to ensure that the accuracy of the estimated meteorological data acquired by the meteorological data estimation model is high.
In one implementation manner of the present disclosure, before acquiring the audio/video data in step S101, the method further includes the following steps:
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
and training the initial meteorological data estimation model to acquire the meteorological data estimation model by taking historical audio and video data as input and historical meteorological data corresponding to the historical audio and video data as output.
In an embodiment of the present disclosure, the obtaining of at least one group of historical audio/video data and historical meteorological data corresponding to each group of historical audio/video data may be reading at least one group of historical audio/video data stored in advance and historical meteorological data corresponding to each group of historical audio/video data, or may be receiving at least one group of historical audio/video data sent by the data storage server and historical meteorological data corresponding to each group of historical audio/video data.
In the optional implementation mode, at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data are acquired; the historical audio and video data are used as input, the historical meteorological data corresponding to the historical audio and video data are used as output, the initial meteorological data estimation model is trained to obtain the meteorological data estimation model, and the high accuracy of the estimated meteorological data obtained through the meteorological data estimation model can be ensured.
In an implementation manner of the present disclosure, before acquiring audio/video data, the method further includes the following steps:
receiving an update weight parameter sent by the edge server, and updating the private meteorological data estimation model according to the update weight parameter to obtain an updated private meteorological data estimation model;
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
taking historical audio and video data as input, taking historical meteorological data corresponding to the historical audio and video data as output, and training the updated private meteorological data estimation model;
when the trained private meteorological data estimation model is not converged, acquiring a gradient update vector according to the trained private meteorological data estimation model, and sending the gradient update vector, wherein the edge server is used for aggregating the gradient update vector, and updating the weight parameters of the common meteorological data estimation model of the edge server according to the aggregated gradient update vector to acquire updated weight parameters;
and when the trained private meteorological data estimation model is converged, acquiring the meteorological data estimation model according to the trained private meteorological data estimation model.
In an embodiment of the present disclosure, the obtaining of at least one group of historical audio/video data and historical meteorological data corresponding to each group of historical audio/video data may be reading at least one group of historical audio/video data stored in advance and historical meteorological data corresponding to each group of historical audio/video data, or may be receiving at least one group of historical audio/video data sent by the data storage server and historical meteorological data corresponding to each group of historical audio/video data.
In an embodiment of the present disclosure, an edge server may correspond to a plurality of weather station devices (that is, a weather station device corresponding to the same edge server only performs interaction of updating a weight parameter and a gradient update vector with the edge server), and for example, may be divided according to positions of the weather station devices, so that the weather station devices in a certain area range correspond to the same edge server. Furthermore, the meteorological station equipment with the altitude within a certain area range belonging to a preset altitude interval can be enabled to correspond to the same edge server.
In an embodiment of the present disclosure, the private meteorological data estimation model and the common meteorological data estimation model may be a neural network model, and specifically, the neural network model may be a pre-training network model in a convolutional neural network model, such as an iceposition model, a resnet model, and the like.
In an embodiment of the present disclosure, the weather data estimation model is obtained according to the trained private weather data estimation model, which may be stored as the weather data estimation model or directly identified as the weather data estimation model.
In the embodiment, the updating weight parameters sent by the edge server are received by the weather station equipment control devices, the edge server is aggregated according to the gradient updating vectors sent by the plurality of weather station equipment control devices, and the weight parameters of the common weather data estimation model of the edge server are updated according to the aggregated gradient updating vectors, so that the updated common weather data estimation model can reflect the common weather data rule between the historical audio and video data acquired by the plurality of weather station equipment control devices and the historical weather data corresponding to the historical audio and video data learned by the common weather data estimation model of the edge server in the previous training; the historical audio and video data is used as input, the historical meteorological data corresponding to the historical audio and video data is used as output, and the updated private meteorological data estimation model is trained, so that on the basis that the updated private meteorological data estimation model learns the common audio and video meteorological data rule, the audio and video data acquired by the meteorological station equipment control device and the historical meteorological data corresponding to each group of audio and video data can be learned individually, and the trained private meteorological data estimation model can learn the private audio and video meteorological data rule of the historical meteorological data acquired by the meteorological station equipment control device and corresponding to the historical audio and video data; when the trained private meteorological data estimation model is not converged, the trained private meteorological data estimation model still needs to be trained, a gradient update vector is obtained according to the trained private meteorological data estimation model, and the gradient update vector is sent, so that the edge server can continuously obtain corresponding update weight parameters based on the gradient update vectors uploaded by the plurality of meteorological station equipment control devices, and further the private meteorological data estimation models of the meteorological station equipment control devices continue to be trained; when the trained private meteorological data estimation model converges, the converged private meteorological data estimation model can acquire corresponding estimated meteorological data based on the input audio and video data, and therefore the converged private meteorological data estimation model is used as a meteorological data estimation model.
In one implementation of the present disclosure, before receiving an update weight parameter sent by an edge server, and updating a private meteorological data estimation model according to the update weight parameter to obtain an updated private meteorological data estimation model, the method further includes the following steps:
receiving a private data uploading instruction;
responding to a private data uploading instruction, and acquiring at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data;
the method comprises the steps that at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data are sent, an edge server is used for inputting the sampling historical audio and video data, outputting the historical meteorological data corresponding to the sampling historical audio and video data, training an initial meteorological data estimation model to obtain a common meteorological data estimation model, obtaining an initial weight parameter according to the common meteorological data estimation model and sending the initial weight parameter;
receiving an initial weight parameter sent by an edge server;
and updating the initial meteorological data estimation model according to the initial weight parameters to obtain a private meteorological data estimation model.
In an embodiment of the present disclosure, the initial meteorological data estimation model may be a neural network model, and specifically, the neural network model may be a pre-trained network model in a convolutional neural network model, such as an icept model, a resnet model, and the like. The initial meteorological data estimation model may be understood as an untrained model.
In the embodiment, by receiving a private data uploading instruction and responding to the private data uploading instruction, at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data are obtained, at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data are sent, the edge server can take the sampled historical audio and video data as input and the historical meteorological data corresponding to the sampled historical audio and video data as output, and performing preliminary training on the initial meteorological data estimation model to obtain a common meteorological data estimation model, wherein the common meteorological data estimation model can be understood as a model obtained after preliminary learning on common audio/video meteorological data rules between historical audio/video data obtained by a plurality of meteorological station equipment control devices and historical meteorological data corresponding to the historical audio/video data. Then the meteorological station equipment receives the initial weight parameter sent by the edge server, and updates the initial meteorological data estimation model according to the initial weight parameter obtained by the common audio/video meteorological data rule, so as to obtain the private meteorological data estimation model, at the moment, the private meteorological data estimation model can understand the model which learns the rule learned by the common meteorological data estimation model, namely, the private meteorological data estimation model can also be understood as a model which preliminarily learns the common audio/video meteorological data rule between the historical audio/video data acquired by the plurality of meteorological station equipment control devices and the historical meteorological data corresponding to the historical audio/video data, therefore, the private meteorological data estimation model can be conveniently trained for multiple rounds, training based on the initial meteorological data estimation model is not needed, and the training difficulty is reduced.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
Fig. 2 shows a schematic block diagram of a weather station device control apparatus according to an embodiment of the present disclosure. The weather station equipment control device can be realized as part or all of the electronic equipment through software, hardware or a combination of the software and the hardware. As shown in fig. 2, the weather station apparatus control device 200 includes:
the first data acquisition module 201 is configured to acquire audio and video data, where the audio and video data includes at least one of a target image and a target audio, the target image is acquired by an image acquisition device located at a target weather station, and the target audio is acquired by an audio acquisition device located at the target weather station;
a second data acquisition module 202 configured to acquire collected weather data collected by weather sensors of a target weather station;
the third data acquisition module 203 is configured to acquire estimated meteorological data according to the audio and video data and verify the acquired meteorological data according to the estimated meteorological data;
the data transmitting module 204 is configured to transmit the collected weather data in response to the collected weather data being verified successfully.
The technical solution provided by the embodiment of the present disclosure is to acquire acquired meteorological data acquired by a meteorological sensor of a target meteorological station by acquiring audio/video data including at least one of a target image acquired by an image acquisition device located at the target meteorological station and a target audio frequency acquired by the image acquisition device located at the target meteorological station, acquire estimated meteorological data according to the audio/video data, and acquire estimated meteorological data according to the audio/video data, wherein the estimated meteorological data is meteorological data estimated according to at least one of an image and an audio frequency acquired at the target meteorological station, since the image and the audio frequency acquired at the target meteorological station are not affected by a fault of the meteorological sensor, the estimated meteorological data is close to meteorological data corresponding to a real meteorological environment at the target meteorological station, the acquired meteorological data is verified according to the estimated meteorological data, when the verification is passed, the fact that the difference between the collected meteorological data and the meteorological data corresponding to the real meteorological environment at the target meteorological station is not large indicates that the meteorological sensor for collecting the meteorological data does not have a fault, and the collected meteorological data can be transmitted in response to the successful verification of the collected meteorological data. Therefore, the technical scheme provided by the embodiment of the disclosure can improve the reliability of the uploaded meteorological data.
The present disclosure also discloses an electronic device, fig. 3 shows a schematic structural block diagram of an electronic device according to an embodiment of the present disclosure, as shown in fig. 3, the electronic device 300 includes a memory 301 and a processor 302; wherein the content of the first and second substances,
the memory 301 is used to store one or more computer instructions, which are executed by the processor 302 to implement any of the methods of the embodiments of the present disclosure.
Fig. 4 shows a schematic structural diagram of an electronic device for implementing a weather station device control method according to an embodiment of the present disclosure.
As shown in fig. 4, electronic device 400 includes a processing unit 401, which may be implemented as a CPU, GPU, FPGA, NPU, or other processing unit. The processing unit 401 may execute various processes in the embodiment of any one of the above-described methods of the present disclosure according to a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for the operation of the electronic apparatus 400 are also stored. The processing unit 401, the ROM402, and the RAM403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A driver 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
In particular, according to embodiments of the present disclosure, any of the methods described above with reference to embodiments of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing any of the methods of the embodiments of the present disclosure. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Claims (10)
1. A weather station device control method is characterized by comprising the following steps:
acquiring audio and video data, wherein the audio and video data comprise at least one of a target image and a target audio, the target image is acquired by image acquisition equipment located at a target weather station, and the target audio is acquired by audio acquisition equipment located at the target weather station;
acquiring collected meteorological data collected by a meteorological sensor of the target meteorological station;
acquiring estimated meteorological data according to the audio and video data, and verifying the acquired meteorological data according to the estimated meteorological data;
and responding to the verification success of the collected meteorological data, and sending the collected meteorological data.
2. The weather station equipment control method according to claim 1, wherein the acquiring audio and video data includes;
receiving a target image sent by the image acquisition equipment through a wireless fidelity Wi-Fi network;
and/or receiving target audio sent by the audio acquisition equipment through a wireless fidelity Wi-Fi network.
3. The weather station apparatus control method of claim 1, wherein the verifying the collected weather data from the estimated weather data comprises:
and responding to the fact that the data value of the collected meteorological data does not belong to a preset meteorological data value interval, and verifying the collected meteorological data according to the estimated meteorological data.
4. The weather station apparatus control method according to claim 1, wherein the weather sensor includes at least one of a wind speed sensor, a wind direction sensor, an air pressure sensor, an air particle sensor, an air pest sensor, an atmospheric temperature sensor, a surface temperature sensor, an underground 1 meter temperature sensor, an underground 2 meter temperature sensor, an underground 5 meter temperature sensor, a humidity sensor, a rain sensor, an ultraviolet sensor, and an infrared sensor.
5. The weather station apparatus control method according to claim 1, wherein the target image includes at least one set of weather sensors, or the target image includes at least a portion of the target weather station;
and/or the distance between the audio acquisition device and the meteorological sensor is less than or equal to an audio acquisition distance threshold value.
6. The weather station equipment control method according to any one of claims 1 to 5, wherein the obtaining estimated weather data from the audio-visual data comprises:
and acquiring a pre-trained meteorological data estimation model, inputting the audio and video data as input into the meteorological data estimation model, and acquiring estimated meteorological data output by the meteorological data estimation model.
7. The weather station equipment control method according to claim 6, wherein before the acquiring the audio-visual data, the method further comprises:
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
and taking historical audio and video data as input, taking historical meteorological data corresponding to the historical audio and video data as output, and training an initial meteorological data estimation model to obtain the meteorological data estimation model.
8. The weather station equipment control method according to claim 6, wherein before the acquiring the audio-visual data, the method further comprises:
receiving an update weight parameter sent by an edge server, and updating the private meteorological data estimation model according to the update weight parameter to obtain an updated private meteorological data estimation model;
acquiring at least one group of historical audio and video data and historical meteorological data corresponding to each group of historical audio and video data;
taking historical audio and video data as input, taking historical meteorological data corresponding to the historical audio and video data as output, and training the updated private meteorological data estimation model;
when the trained private meteorological data estimation model is not converged, obtaining a gradient update vector according to the trained private meteorological data estimation model, and sending the gradient update vector, wherein the edge server is used for aggregating the gradient update vector, and updating the weight parameters of the shared meteorological data estimation model of the edge server according to the aggregated gradient update vector to obtain the updated weight parameters;
and when the trained private meteorological data estimation model converges, acquiring the meteorological data estimation model according to the trained private meteorological data estimation model.
9. The weather station device control method according to claim 8, wherein before receiving the updated weight parameter sent by the edge server and updating the private weather data estimation model according to the updated weight parameter to obtain the updated private weather data estimation model, the method further comprises:
receiving a private data uploading instruction;
responding to the private data uploading instruction, and acquiring at least one group of sampling historical audio and video data and sampling historical meteorological data corresponding to each group of sampling historical audio and video data;
the edge server is used for inputting the sampled historical audio and video data, outputting the historical meteorological data corresponding to the sampled historical audio and video data, training an initial meteorological data estimation model to acquire the common meteorological data estimation model, acquiring an initial weight parameter according to the common meteorological data estimation model, and transmitting the initial weight parameter;
receiving an initial weight parameter sent by the edge server;
and updating the initial meteorological data estimation model according to the initial weight parameters to obtain the private meteorological data estimation model.
10. An electronic device comprising a memory and at least one processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the at least one processor to implement the method steps of any one of claims 1-9.
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