CN114187524B

CN114187524B - Household air conditioner identification method, device, equipment, storage medium and product

Info

Publication number: CN114187524B
Application number: CN202210140021.8A
Authority: CN
Inventors: 杨飞
Original assignee: Institute of Geographic Sciences and Natural Resources of CAS
Current assignee: Institute of Geographic Sciences and Natural Resources of CAS
Priority date: 2022-02-16
Filing date: 2022-02-16
Publication date: 2022-06-10
Anticipated expiration: 2042-02-16
Also published as: CN114187524A

Abstract

The present disclosure provides a method, apparatus, device, storage medium and product for identifying a home air conditioner, the method comprising: acquiring an identification request; acquiring a remote sensing image corresponding to the area identifier according to the identification request, and determining the outline and height of each building in the area to be identified according to the remote sensing image; according to the identification request, obtaining a street view picture corresponding to the area identification, and determining the number of household air conditioners corresponding to each street building in the street view picture; determining the outline and the height of the buildings along the street in the remote sensing image according to the position information of the buildings along the street; determining the mapping relation between the number of the household air conditioners and the outline and the height; calculating the number of target household air conditioners corresponding to each building according to the outline and the height corresponding to each building; and determining the sum of the target household air conditioner quantity corresponding to each building as the total quantity of the household air conditioners in the area to be identified. The accurate extraction of the using amount and the spatial distribution condition of the urban household air conditioner is emphatically solved, and the using and surveying efficiency of the household air conditioner is effectively improved.

Description

Household air conditioner identification method, device, equipment, storage medium and product

Technical Field

The present disclosure relates to the field of image processing, and in particular, to a method, an apparatus, a device, a storage medium, and a product for identifying a home air conditioner.

Background

The risk threat of extreme high temperature disasters to human life safety is aggravated by climate change, and the household air conditioner is an effective means for residents to deal with extreme temperature events and is also an important mode of power energy consumption in high temperature periods in summer. The accurate control of the quantity and the spatial distribution of the household air conditioners has important significance for scientifically scheduling energy, saving energy, reducing emission, improving the response of residents to extreme temperature disasters and the like. However, the number of the used air conditioners and the spatial distribution data are very short, and how to determine the use data and the spatial distribution of the household air conditioners becomes a problem to be solved urgently.

The existing household air conditioner identification method is mainly based on traditional manpower sampling survey and user survey, sample points are few, a survey result has high uncertainty, the survey is time-consuming and labor-consuming, and the traditional identification method is difficult to accurately master the spatial distribution rule of the number of air conditioners.

Disclosure of Invention

The invention provides a household air conditioner identification method, a household air conditioner identification device, household air conditioner identification equipment, a storage medium and a household air conditioner identification product, which are used for solving the technical problems that an existing determination method for household air conditioner use data and space distribution is not high in accuracy, human resources are consumed, and efficiency is low.

A first aspect of the present disclosure is to provide a home air conditioner identification method, including:

acquiring an identification request, wherein the identification request comprises an area identifier of an area to be identified;

acquiring a remote sensing image corresponding to the area identifier according to the identification request, determining the outline of each building in the area to be identified according to the remote sensing image, and determining the height of each building according to the remote sensing image;

acquiring at least one street view picture corresponding to the area identifier according to the identification request, and determining the number of household air conditioners corresponding to each street building in the street view picture according to the at least one street view picture;

determining the outline and the height of each buildings along the street in the remote sensing image according to the position information of the buildings along the street;

determining the mapping relation between the number of the household air conditioners and the profile and the height according to the profile and the height corresponding to each buildings along the street and the number of the household air conditioners;

aiming at each building in the area to be identified, calculating the number of target household air conditioners corresponding to each building according to the corresponding outline and height of each building;

and determining the sum of the target household air conditioner quantity corresponding to each building as the total quantity of the household air conditioners in the area to be identified.

A second aspect of the present disclosure is to provide a home air conditioner recognition device, including:

the device comprises an acquisition module, a recognition module and a processing module, wherein the acquisition module is used for acquiring a recognition request, and the recognition request comprises an area identifier of an area to be recognized;

the remote sensing image processing module is used for acquiring a remote sensing image corresponding to the area identifier according to the identification request, determining the outline of each building in the area to be identified according to the remote sensing image, and determining the height of each building according to the remote sensing image;

the street view picture processing module is used for acquiring at least one street view picture corresponding to the area identifier according to the identification request and determining the number of household air conditioners corresponding to each street building in the street view picture according to the at least one street view picture;

the matching module is used for determining the outline and the height of each buildings along the street in the remote sensing image according to the position information of the buildings along the street;

the determining module is used for determining the mapping relation between the number of the household air conditioners and the profile and the height according to the profile and the height corresponding to each buildings along the street and the number of the household air conditioners;

the calculation module is used for calculating the number of target household air conditioners corresponding to each building according to the outline and the height corresponding to each building aiming at each building in the area to be identified;

and the processing module is used for determining the sum of the target household air conditioner quantity corresponding to each building as the total quantity of the household air conditioners in the area to be identified.

A third aspect of the present disclosure is to provide an electronic device, including: a memory, a processor;

a memory; a memory for storing the processor-executable instructions;

wherein the processor is configured to call the program instructions in the memory to perform the home air conditioner identification method according to the first aspect.

A fourth aspect of the present disclosure is to provide a computer-readable storage medium having stored therein computer-executable instructions for implementing the home air conditioner identification method according to the first aspect when the computer-executable instructions are executed by a processor.

A fifth aspect of the present disclosure is to provide a computer program product comprising a computer program which, when executed by a processor, implements the home air conditioner identification method as described in the first aspect.

According to the household air conditioner identification method, the household air conditioner identification device, the household air conditioner identification equipment, the household air conditioner storage medium and the household air conditioner storage medium, an efficient and accurate household air conditioner space statistics investigation method based on deep learning and space statistics methods is achieved by means of high-resolution satellite remote sensing images and internet map street view picture information, accurate extraction of urban household air conditioner usage and space distribution conditions is emphatically achieved, household air conditioner usage investigation efficiency is effectively improved, and the management and control level of urban residents and management departments for dealing with extreme high-temperature events, reasonable scheduling of electric power energy and the like is further improved.

Drawings

In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art according to the drawings.

FIG. 1 is a schematic diagram of a system architecture upon which the present disclosure is based;

fig. 2 is a schematic flow chart of a household air conditioner identification method according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of an outline of a building in an area to be identified according to an embodiment of the present disclosure;

fig. 4 is a schematic flow chart of a household air conditioner identification method according to a second embodiment of the present disclosure;

fig. 5 is a schematic flow chart of a household air conditioner identification method according to a third embodiment of the present disclosure;

fig. 6A is a schematic structural view of a satellite and the sun being on opposite sides according to an embodiment of the present disclosure;

fig. 6B is a schematic structural diagram of the sun and the satellite on the same side provided in the embodiment of the present disclosure;

fig. 7 is a schematic flowchart of a household air conditioner identification method according to a fourth embodiment of the present disclosure;

fig. 8 is a schematic structural diagram of a household air conditioner identification device according to a fifth embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present disclosure.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments obtained based on the embodiments in the disclosure belong to the protection scope of the disclosure.

In view of the above-mentioned problem that in the existing testing method, due to the fact that a large amount of repeated information is stored in the data list for testing, the utilization rate of the data information of the data list by the test case in the testing process is low, and the maintenance and management of the problem of maintenance and management of the data list are inconvenient, the present disclosure provides a household air conditioner identification method, apparatus, device, storage medium and product.

It should be noted that the present disclosure provides a method, an apparatus, a device, a storage medium, and a product for identifying a home air conditioner, which can be applied in a scenario of testing application software in each application.

The air conditioner is a main measure for urban residents to cope with extremely high temperature, but the using quantity and the spatial distribution data of the air conditioners are very deficient at present, the air conditioner use survey still adopts the traditional manual means, statistical data obtained by sampling survey estimation is adopted, the survey means is backward, the uncertainty of survey data is large, and the spatial distribution rule of the household air conditioners is unclear.

In the process of solving the technical problems, the inventor finds that the high-resolution remote sensing image contains rich shape structure and texture information of the earth surface target through research, so that the high-resolution remote sensing image becomes an important data source for urban research, and high-resolution aerial remote sensing images, satellite remote sensing images, unmanned aerial vehicle remote sensing images, radar images and the like are widely applied to extracting the contour of urban buildings. The city street view picture also contains more detailed information, and is gradually applied to city information extraction in recent years, such as extraction of traffic lights, roadside buildings, street lamps, the number of streets and the like. The high-resolution satellite remote sensing image and internet map street view picture information can be utilized, and the efficient and accurate household air conditioner space statistics and investigation method based on the deep learning and space statistics method emphasizes on solving the problem of accurate extraction of the usage amount and the space distribution condition of urban household air conditioners, effectively improves the household air conditioner usage and investigation efficiency, and further improves the management and control level of urban residents and management departments for dealing with extreme high-temperature events, reasonably scheduling electric power energy and the like.

Fig. 1 is a schematic diagram of a system architecture based on the present disclosure, as shown in fig. 1, the system architecture based on the present disclosure at least includes: terminal equipment 11, server 12, remote sensing image data server 13 and street view picture data server 14. Wherein, the server 12 is provided with a household air conditioner identification device which can be written by C/C + +, Java, Shell or Python; the terminal device 11 may be a desktop computer, a tablet computer, or the like. The remote sensing image data server 13 may be a cloud server or a server cluster, in which remote sensing images of a plurality of areas are stored. Street view image data server 14 may be a cloud server or a server cluster, in which street view images of multiple regions are stored.

Fig. 2 is a schematic flowchart of a household air conditioner identification method according to an embodiment of the present disclosure, and as shown in fig. 2, the method includes:

step 201, obtaining an identification request, wherein the identification request includes an area identifier of an area to be identified.

The execution main body of the embodiment is a household air conditioner identification device, the household air conditioner identification device can be coupled in a server, and the server can be in communication connection with the terminal equipment, so that the number of household air conditioners in an area to be identified can be identified according to an identification request triggered by a user on the terminal equipment.

In the embodiment, in order to accurately extract the usage amount and the spatial distribution condition of the urban household air conditioner, the management and control levels of urban residents and management departments for dealing with extreme high-temperature events, reasonably scheduling electric power energy and the like are further improved. The household air conditioner identification device can obtain an identification request, wherein the identification request can be triggered by a user on a terminal device. The identification request may specifically include an area identifier of the area to be identified. For example, it may be a cell identity, a community identity, etc.

Step 202, obtaining a remote sensing image corresponding to the area identifier according to the identification request, determining the outline of each building in the area to be identified according to the remote sensing image, and determining the height of each building according to the remote sensing image.

In the present embodiment, the home air conditioner is generally provided with an air conditioner outdoor unit outside the building, and the statistics of the number of air conditioners in the area to be identified can be realized by identifying the air conditioner outdoor unit outside the building. Because the high-resolution remote sensing image contains rich shape structure and texture information of the earth surface target, the information such as the outline of each building in the area to be identified can be realized through the remote sensing image.

Specifically, after the identification request is acquired, the remote sensing image corresponding to the area identifier may be acquired according to the identification request. The remote sensing image also includes contents such as position information corresponding to each building. And carrying out image recognition operation on the remote sensing image to determine the outline of each building and the height of each building in the area to be recognized.

Step 203, obtaining at least one street view picture corresponding to the area identifier according to the identification request, and determining the number of household air conditioners corresponding to each street building in the street view picture according to the at least one street view picture.

In this embodiment, the city street view picture also contains more detailed information, which may include, for example, traffic lights, street lights, buildings along the street, and so on. The recognition of the air conditioner outdoor unit arranged on the buildings along the street can be realized by combining the deep learning method and the street view picture.

Specifically, after the identification request is obtained, at least one street view picture corresponding to the area identifier may be obtained according to the identification request. And identifying the street view picture in a deep learning mode to determine the number of household air conditioners on one side of the street building in the street view picture. Further, the number of the air-conditioning outdoor units on the other three sides of the buildings along the street can be identified and counted manually. And determining the sum of the number recognized by deep learning and the number recognized manually as the number of the household air conditioners corresponding to each buildings along the street.

And 204, determining the outline and the height of each buildings along the street in the remote sensing image according to the position information of the buildings along the street.

In this embodiment, the buildings along the street in the street view picture have position information, and the position information can be compared with the position information of the buildings in the remote sensing image to determine the outline and height of each street view building in the remote sensing image.

And step 205, determining the mapping relation between the number of the household air conditioners and the profile and the height according to the profile and the height corresponding to each buildings along the street and the number of the household air conditioners.

After the outline, the height and the number of the household air conditioners corresponding to each buildings along the street are respectively determined, the mapping relation between the number of the household air conditioners and the outline and the height can be established. Wherein, the corresponding outline of the buildings along the street comprises the length and the width of the buildings in the remote sensing image.

And step 206, aiming at each building in the area to be identified, calculating the number of target household air conditioners corresponding to each building according to the outline and the height corresponding to each building.

In the present embodiment, after the contour and the height of each building in the area to be identified and the mapping relationship between the number of the home air conditioners and the contour and the height are obtained, the target number of the home air conditioners corresponding to each building in the area to be identified may be calculated. The mapping relationship may be an algorithm relationship between the mapping relationships between the number of the household air conditioners and the profiles and heights.

And step 207, determining the sum of the target household air conditioner quantity corresponding to each building as the total quantity of the household air conditioners in the area to be identified.

In this embodiment, after the target number of home air conditioners corresponding to each building is obtained through calculation, the sum of the target number of home air conditioners corresponding to each building may be determined as the total number of home air conditioners in the area to be identified.

Optionally, the distribution situation of the household air conditioners in each building can be identified by performing identification operation on the high-resolution satellite remote sensing image and the street view picture.

According to the household air conditioner identification method provided by the embodiment, the high-efficiency and accurate household air conditioner space identification method based on the deep learning and space statistical method is mainly used for solving the problem that the usage amount and the space distribution condition of the urban household air conditioner are accurately extracted, the use investigation efficiency of the household air conditioner is effectively improved, and the control level of urban residents and management departments for dealing with extreme high-temperature events, reasonably scheduling electric power energy and the like is further improved.

Further, on the basis of the first embodiment, the buildings along the street comprise a first building along the street and a second building along the street, the number of the household air conditioners corresponding to the first building along the street is the number of the first household air conditioners, and the number of the household air conditioners corresponding to the second building along the street is the number of the second household air conditioners; the first buildings and the second buildings are different in shape; step 205 comprises:

and determining the mapping relation between the first household air conditioner quantity corresponding to the first buildings along the street and the profile and the height of the first household air conditioners according to the profile and the height corresponding to the first buildings along the street and the quantity of the household air conditioners.

And determining the mapping relation between the second household air conditioner quantity corresponding to the second buildings along the street and the profile and the height of the second household air conditioner quantity corresponding to the second buildings along the street.

In this embodiment, the buildings along the street in the area to be identified may be divided into a first building along the street and a second building along the street according to their different shapes, wherein the first building along the street is different from the second building along the street in shape. Accordingly, the buildings within the area to be identified may be divided into a first building and a second building according to their different shapes. The first building/first along-street building may be a tower, and the second building/second along-street building may be a plank floor.

Because the tower floor and the plate floor have different shapes, the corresponding household air conditioners are different in number, and therefore mapping relations between different air conditioner numbers, outlines and heights can be built for different types of buildings.

Specifically, for the profile, the height and the number of the household air conditioners corresponding to the first buildings along the street, the mapping relation between the number of the first household air conditioners corresponding to the first buildings along the street and the profile and the height is determined. The mapping relationship between the number of the first household air conditioners and the profile and the height can be specifically shown as formula 1.

Number of first home air conditioners = f first along street building (floor height, floor profile length and width) (1)

And determining the mapping relation between the second household air conditioner quantity corresponding to the second buildings along the street and the profile and the height of the second buildings along the street according to the profile and the height of the second buildings along the street and the quantity of the household air conditioners. The mapping relationship between the number of the second household air conditioners and the profile and the height can be specifically shown as formula 2.

Number of second home air conditioners = f second along street building (floor height, floor profile length and width) (2)

Fig. 3 is a schematic outline diagram of a building in an area to be identified according to an embodiment of the present disclosure, and as shown in fig. 3, the area to be identified may specifically include a turret 31 and a turret 32, where the turret 31 and the turret 32 have different outline shapes.

Further, in the first embodiment, the step 206 includes:

and respectively calculating a first similarity between the building and a first street building and a second similarity between the building and a second street building aiming at each building in the area to be identified.

And classifying the buildings into a first building and a second building according to the first similarity and the second similarity.

And aiming at each first building, calculating the number of the household air conditioners corresponding to the first building according to the corresponding profile and height of the first building and the mapping relation between the number of the first household air conditioners and the profile and the height.

And aiming at each second building, calculating the number of the household air conditioners corresponding to the second building according to the corresponding outline and height of the second building and the mapping relation between the number of the second household air conditioners and the outline and height.

In the present embodiment, the buildings within the area to be identified may be divided into a first building and a second building according to their different shapes. The buildings can be classified according to the similarity between each building and the first buildings and the second buildings along the street. It will be appreciated that if the building has a higher similarity to a first buildings along the street than a second buildings along the street, the building may be characterised as a first building. And vice versa.

Specifically, for each building in the area to be identified, a first similarity between the building and a first street building and a second similarity between the building and a second street building are respectively calculated. Specifically, the fractal dimension may be used to calculate the similarity. The fractal dimension is a good method for measuring the similarity of shapes, has rotation, translation and scale invariance, is consistent with human visual perception, and considers the local structure and the integral self-similarity of elements according to the characteristic of the fractal dimension.

After the classification is completed, for each type of building, the calculation of the number of the home air conditioners corresponding to the building can be realized according to the mapping relation. Specifically, for each first building, the number of the home air conditioners corresponding to the first building is calculated according to the corresponding outline and height of the first building and the mapping relation between the number of the first home air conditioners and the outline and height. And aiming at each second building, calculating the number of the household air conditioners corresponding to the second building according to the corresponding outline and height of the second building and the mapping relation between the number of the second household air conditioners and the outline and height.

Further, on the basis of the first embodiment, step 207 includes:

and respectively calculating a first quantity sum of the target household air-conditioners corresponding to the first building and a second quantity sum of the target household air-conditioners corresponding to the second building.

Determining the sum of the first number sum and the second number sum as the total amount of the household air conditioners in the area to be identified.

In this embodiment, after the classification is completed, for each building in the area to be identified, a first number sum of the target number of home air conditioners corresponding to the first building and a second number sum of the target number of home air conditioners corresponding to the second building may be calculated, respectively. The sum of the first number sum and the second number sum is determined as the total amount of the household air conditioners in the area to be identified.

Optionally, in order to improve the efficiency of identifying the home air conditioners, after the classification of the buildings is completed, the number of the various buildings can be simply counted, the average value of the home air conditioners corresponding to the various buildings is determined, the average value is determined as the number of the home air conditioners corresponding to the buildings, and the total number of the home air conditioners in the area to be identified is calculated according to the number of the various buildings and the number of the corresponding air conditioners.

Specifically, the calculation of the number of all the household air conditioners in the area to be identified can be realized by adopting formula 3:

number of air conditioners in area to be identified =

According to the household air conditioner identification method provided by the embodiment, the buildings are classified according to the shapes of the buildings, and the mapping relations between the number of different air conditioners and the outlines and heights of the buildings are set according to different categories, so that the accuracy of household air conditioner identification can be further improved.

Fig. 4 is a schematic flow chart of a household air conditioner identification method provided in a second embodiment of the present disclosure, and on the basis of the first embodiment, as shown in fig. 4, step 202 includes:

step 401, performing image processing operation on the remote sensing image to obtain a processed remote sensing image, wherein the image processing operation includes geometric correction operation and/or image fusion operation.

And 402, inputting the processed remote sensing image into a preset contour extraction model to obtain the contour of each building.

In this embodiment, after the remote sensing image is acquired, firstly, an image processing operation may be performed on the remote sensing image to obtain a processed remote sensing image. In particular, the image processing operation comprises a geometric correction operation and/or an image fusion operation. The combination, size, scale and direction of the ground feature image information obtained from the remote sensing image and the real ground feature are inconsistent, geometric correction is needed, and more orthometric correction models of the remote sensing image are like a universal polynomial correction model. The high-resolution remote sensing image fusion mainly comprises the step of transforming and fusing the image data with the multispectral wave band and the panchromatic wave band image data with higher resolution so as to improve the information content and the usability of the image. The remote sensing image fusion operation can be realized by adopting any remote sensing image fusion mode, and the remote sensing image fusion operation is not limited by the disclosure.

Further, after the processed remote sensing image is acquired, the processed remote sensing image may be input to a preset contour extraction model. The contour extraction model can extract the contour of the building in the remote sensing image, so that the contour of each building can be obtained after the processed remote sensing image is input into the preset contour extraction model.

Further, on the basis of any of the above embodiments, before the step 402, the method further includes:

the method comprises the steps of obtaining a first training data set, wherein the first training data set comprises a plurality of marked remote sensing images and first marked information corresponding to the marked remote sensing images, and the first marked information is a building outline in the remote sensing images.

And performing iterative training operation on a preset first model to be trained by adopting a first training data set until the first model to be trained is converged to obtain the contour extraction model.

In the present embodiment, before building contour extraction by the contour extraction model, a training operation of the contour extraction model may be performed in advance. Specifically, a first training data set may be obtained, where the first training data set includes a plurality of labeled remote sensing images and first labeling information corresponding to the labeled remote sensing images, and the first labeling information is a building contour in the remote sensing images. And performing iterative training operation on a preset first model to be trained through the first training data set, and continuously adjusting parameters of the first model to be trained according to the loss value of the first model to be trained until the first model to be trained is converged to obtain the contour extraction model.

According to the household air conditioner identification method provided by the embodiment, the remote sensing image is subjected to image processing operation, and the processed remote sensing image is input to the preset contour extraction model to extract the building contour, so that the building contour in the remote sensing image can be accurately acquired, and a foundation is provided for identification of the number of subsequent household air conditioners.

Fig. 5 is a schematic flow chart of a household air conditioner identification method provided in a third embodiment of the present disclosure, and on the basis of any one of the above embodiments, as shown in fig. 5, step 202 includes:

step 501, determining shadow size information corresponding to the buildings according to the outlines of the buildings.

And 502, determining the position relation between the satellite and the sun when the remote sensing image is shot.

And 503, calculating the height of the building according to the position relation and the shadow size information.

In the present embodiment, the number of home air conditioners is different due to buildings of different heights. It will be appreciated that a taller building theoretically corresponds to a greater number of domestic air conditioners. Therefore, in order to accurately recognize the number of the home air conditioners, it is necessary to calculate the height corresponding to each building.

In particular, shadow length calculation is key to inverting building height using shadows. And determining shadow size information corresponding to the buildings according to the outlines of the buildings. The shadow size information may specifically be extracted from the remote sensing image. The method is carried out according to the direction of the solar azimuth angle when the shadow length is measured, the influence of the solar azimuth angle is considered, and the influence of the satellite azimuth angle on the test result is not considered.

Fig. 6A is a schematic structural diagram of a satellite provided in an embodiment of the present disclosure and located on the opposite side of the sun, as shown in fig. 6A, a sun 61 is located on the left side of a building 62, and a satellite 63 is located on the right side of the building 62. Fig. 6B is a schematic structural diagram of the sun and the satellite on the same side provided in the embodiment of the present disclosure, and as shown in fig. 6B, both the sun 64 and the satellite 65 are located on the left side of the building 66. As shown in fig. 6A to 6B, since the shadow size is different when the satellite and the sun are different in positional relationship, it is necessary to determine the positional relationship between the satellite and the sun when the remote sensing image is taken in order to improve the accuracy of the calculated building height. And calculating the height of the building according to the position relation and the shadow size information.

Further, the position relationship comprises that a satellite and the sun are positioned on the same side when a remote sensing image is shot, and the shadow size information comprises the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle; on the basis of any of the above embodiments, step 503 includes:

and calculating the height of the building according to the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle, and a preset first building altitude algorithm.

In this embodiment, the position relationship may specifically include that the satellite is located on the same side as the sun when the remote sensing image is taken, and the shadow size information may specifically include the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle, and the satellite altitude angle. The height of the building may be calculated based on the position information, the shadow size information, and a preset first building height algorithm.

Wherein the first building height algorithm may be as shown in equations 4-5:

A = S–B = H/tanθ–H/tanω （4）

H = A tanθtanω/ (tanω–tanθ) （5）

wherein H is the building height; s is the length of the building shadow on the high-resolution remote sensing image along the sun irradiation direction; a is the length of the shadow on the image; theta is the solar altitude; omega is the satellite altitude.

Further, the position relationship comprises that a satellite and the sun are positioned on different sides when a remote sensing image is shot, and the shadow size information comprises the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle; on the basis of any of the above embodiments, step 503 includes:

and calculating the height of the building according to the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle, and a preset second building height algorithm.

In this embodiment, the position relationship may specifically include that the satellite is located on the same side as the sun when the remote sensing image is taken, and the shadow size information may specifically include the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle, and the satellite altitude angle. The height of the building may be calculated based on the position information, the shadow size information, and a preset second building height algorithm.

Wherein the second building height algorithm may be as shown in equations 6-7:

A = S–B = H/tanθ–H/tanω （6）

H = A tanθ （7）

According to the household air conditioner identification method provided by the embodiment, the calculation of the building height is realized by adopting different algorithms according to different position relations of the satellite and the sun, so that the accuracy of the building height obtained by calculation can be improved, and the accuracy of the number of household air conditioners of the identified building can be improved.

Fig. 7 is a schematic flow chart of a household air conditioner identification method according to a fourth embodiment of the present disclosure, and based on any of the above embodiments, as shown in fig. 7, step 203 includes:

step 701, inputting the street view picture into a preset household air conditioner identification model aiming at each street view picture, and obtaining the number of household air conditioners corresponding to buildings along the street in the street view picture.

Step 702, calculating the average value of the number of the household air conditioners corresponding to the buildings along the street in at least one street view picture, and determining the average value as the number of the household air conditioners corresponding to the buildings along the street in the area to be identified.

In this embodiment, a picture of a hundred-degree street view of a research survey area may be captured by a web crawler. And inputting the street view pictures into a preset household air conditioner identification model aiming at each street view picture to obtain the number of household air conditioners corresponding to buildings along the street in the street view pictures. Specifically, any network model capable of performing image recognition may be adopted as the home air conditioner recognition model to perform the recognition operation of the home air conditioner, which is not limited by the present disclosure. The number of air conditioners in the buildings at the sample points can be used as sample points for air conditioner investigation sampling of the residential area or the regional buildings, and the average of the number of air conditioners in a plurality of buildings along the street at the roadside can be regarded as the average of the number of air conditioners in each building of the residential area. Therefore, the average value of the number of the household air conditioners corresponding to the buildings along the street in the at least one street view picture can be calculated, and the average value is determined as the number of the household air conditioners corresponding to the buildings along the street in the area to be identified.

The household air conditioners in the street view picture are identified by adopting the household air conditioner identification model, so that the spatial distribution of the household air conditioners in the building can be accurately identified on the basis of identifying the number of the household air conditioners. For example, the spatial distribution positions of the home air conditioners in the respective buildings can be identified.

Further, on the basis of any of the above embodiments, before step 602, the method further includes:

and acquiring a second training data set, wherein the second training data set comprises a plurality of marked street building pictures and second marked information corresponding to the marked street building pictures, and the second marked information is the household air conditioner information in the street building pictures.

And performing iterative training operation on a preset second model to be trained by adopting a second training data set until the second model to be trained is converged to obtain the household air conditioner identification model.

In this embodiment, before the identification of the number of the home air conditioners is performed by the home air conditioner identification model, a training operation of the home air conditioner identification model is first required. Specifically, a second training data set may be obtained, where the second training data set includes a plurality of labeled street building pictures and second labeling information corresponding to the labeled street building pictures, and the second labeling information is household air conditioning information in the street building pictures. And performing iterative training operation on a preset second model to be trained by adopting a second training data set, and continuously adjusting parameters of the second model to be trained according to the loss value of the second model to be trained until the second model to be trained is converged to obtain the household air conditioner identification model.

According to the household air conditioner identification method provided by the embodiment, the street view picture is combined with the deep learning, so that the identification of the number of the household air conditioners corresponding to the buildings along the street can be accurately realized.

Fig. 8 is a schematic structural diagram of a household air conditioner identification device according to a fifth embodiment of the present disclosure, and as shown in fig. 8, the device includes: the system comprises an acquisition module 81, a remote sensing image processing module 82, a street view picture processing module 83, a matching module 84, a determination module 85, a calculation module 86 and a processing module 88. The obtaining module 81 is configured to obtain an identification request, where the identification request includes an area identifier of an area to be identified. And the remote sensing image processing module 82 is used for acquiring a remote sensing image corresponding to the area identifier according to the identification request, determining the outline of each building in the area to be identified according to the remote sensing image, and determining the height of each building according to the remote sensing image. And the street view picture processing module 83 is configured to obtain at least one street view picture corresponding to the area identifier according to the identification request, and determine the number of the household air conditioners corresponding to each street building in the street view picture according to the at least one street view picture. And the matching module 84 is used for determining the outline and the height of each buildings along the street in the remote sensing image according to the position information of the buildings along the street. And the determining module 85 is used for determining the mapping relationship between the number of the household air conditioners and the profile and the height according to the profile and the height corresponding to each buildings along the street and the number of the household air conditioners. And the calculating module 86 is used for calculating the number of target household air conditioners corresponding to each building according to the outline and the height corresponding to each building aiming at each building in the area to be identified. And the processing module 87 is used for determining the sum of the target household air conditioner quantity corresponding to each building as the total quantity of the household air conditioners in the area to be identified.

Further, on the basis of the fifth embodiment, the buildings along the street include a first building along the street and a second building along the street, the number of the household air conditioners corresponding to the first building along the street is the first number of the household air conditioners, and the number of the household air conditioners corresponding to the second building along the street is the second number of the household air conditioners; wherein the first buildings and the second buildings are different in shape. The determination module is to: determining the mapping relation between the number of first household air conditioners corresponding to a first buildings along the street and the profile and the height of the first household air conditioners according to the profile and the height of the first buildings along the street and the number of the household air conditioners;

Further, on the basis of the fifth embodiment, the determining module is configured to: and respectively calculating a first similarity between the building and a first street building and a second similarity between the building and a second street building aiming at each building in the area to be identified. And classifying the buildings into a first building and a second building according to the first similarity and the second similarity. And aiming at each first building, calculating the number of the household air conditioners corresponding to the first building according to the corresponding profile and height of the first building and the mapping relation between the number of the first household air conditioners and the profile and the height. And aiming at each second building, calculating the number of the household air conditioners corresponding to the second building according to the corresponding outline and height of the second building and the mapping relation between the number of the second household air conditioners and the outline and height.

Further, on the basis of the fifth embodiment, the determining module is configured to: and respectively calculating a first quantity sum of the target household air-conditioners corresponding to the first building and a second quantity sum of the target household air-conditioners corresponding to the second building.

And determining the sum of the first number sum and the second number sum as the total amount of the household air conditioners in the area to be identified.

Further, on the basis of any of the above embodiments, the remote sensing image processing module is configured to: carrying out image processing operation on the remote sensing image to obtain a processed remote sensing image, wherein the image processing operation comprises geometric correction operation and/or image fusion operation;

and inputting the processed remote sensing image into a preset contour extraction model to obtain the contour of each building.

Further, on the basis of any of the above embodiments, the remote sensing image processing module is configured to: acquiring a first training data set, wherein the first training data set comprises a plurality of marked remote sensing images and first marking information corresponding to the marked remote sensing images, and the first marking information is a building outline in the remote sensing images; and performing iterative training operation on a preset first model to be trained by adopting a first training data set until the first model to be trained is converged to obtain the contour extraction model.

Further, on the basis of any of the above embodiments, the remote sensing image processing module is configured to: and determining shadow size information corresponding to the buildings according to the outlines of the buildings. And determining the position relation between the satellite and the sun when the remote sensing image is shot. And calculating the height of the building according to the position relation and the shadow size information.

Further, on the basis of any of the above embodiments, the position relationship includes that the satellite is located on the same side as the sun when the remote sensing image is taken, and the shadow size information includes the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar elevation angle, and the satellite elevation angle. The remote sensing image processing module is used for: and calculating the height of the building according to the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle, and a preset first building altitude algorithm.

Further, on the basis of any one of the above embodiments, the position relationship includes that the satellite and the sun are on opposite sides when the remote sensing image is taken, and the shadow size information includes the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar elevation angle and the satellite elevation angle. The remote sensing image processing module is used for: and calculating the height of the building according to the length of the building shadow in the remote sensing image, the length of the building shadow in the sun irradiation direction, the solar altitude angle and the satellite altitude angle, and a preset second building height algorithm.

Further, on the basis of any of the above embodiments, the street view picture processing module is configured to: and inputting the street view picture into a preset household air conditioner identification model aiming at each street view picture to obtain the number of household air conditioners corresponding to buildings along the street in the street view picture. And calculating the average value of the number of the household air conditioners corresponding to the buildings along the street in at least one street view picture, and determining the average value as the number of the household air conditioners corresponding to the buildings along the street in the area to be identified.

Further, on the basis of any of the above embodiments, the street view picture processing module is configured to: acquiring a second training data set, wherein the second training data set comprises a plurality of marked street building pictures and second marked information corresponding to the marked street building pictures, and the second marked information is household air conditioner information in the street building pictures;

and performing iterative training operation on a preset second model to be trained by adopting a second training data set until the second model to be trained is converged, and obtaining the household air conditioner identification model.

Yet another embodiment of the present disclosure further provides an electronic device, including: a processor and a memory;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored by the memory, so that the processor executes the household air conditioner identification method according to any one of the embodiments.

Fig. 9 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present disclosure, and as shown in fig. 9, the electronic device 900 may be a terminal device or a server. Among them, the terminal Device may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a Digital broadcast receiver, a Personal Digital Assistant (PDA), a tablet computer (PAD), a Portable Multimedia Player (PMP), a car terminal (e.g., car navigation terminal), etc., and a fixed terminal such as a Digital TV, a desktop computer, etc. The electronic device shown in fig. 9 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 9, the electronic device 900 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 901, which may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 902 or a program loaded from a storage device 908 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data necessary for the operation of the electronic apparatus 900 are also stored. The processing apparatus 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.

Generally, the following devices may be connected to the I/O interface 905: input devices 906 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 907 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 908 including, for example, magnetic tape, hard disk, etc.; and a communication device 909. The communication device 909 may allow the electronic apparatus 900 to perform wireless or wired communication with other apparatuses to exchange data. While fig. 9 illustrates an electronic device 900 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.

In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device 909, or installed from the storage device 908, or installed from the ROM 902. The computer program, when executed by the processing device 901, performs the above-described functions defined in the methods of the embodiments of the present disclosure.

Still another embodiment of the present disclosure further provides a computer-readable storage medium, in which computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the method for identifying a home air conditioner according to any one of the above embodiments is implemented.

It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

Yet another embodiment of the present disclosure further provides a computer program product including a computer program, which when executed by a processor, implements the home air conditioner identification method according to any one of the above embodiments.

The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above embodiments.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of Network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.

Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.

Claims

1. A household air conditioner identification method is characterized by comprising the following steps:

aiming at each building in the area to be identified, calculating the number of target household air conditioners corresponding to each building according to the outline and height corresponding to each building;

2. The method of claim 1, wherein the buildings along the street comprise a first building along the street and a second building along the street, the first building along the street corresponding to the number of the household air conditioners being a first number of the household air conditioners, and the second building along the street corresponding to the number of the household air conditioners being a second number of the household air conditioners; the first buildings and the second buildings are different in shape;

the determining the mapping relation between the number of the household air conditioners and the profile and the height according to the profile and the height corresponding to each buildings along the street and the number of the household air conditioners comprises the following steps:

determining the mapping relation between the number of first household air conditioners corresponding to a first buildings along the street and the profile and the height of the first household air conditioners according to the profile and the height of the first buildings along the street and the number of the household air conditioners;

3. The method according to claim 2, wherein the calculating, for each building in the area to be identified, the target number of home air conditioners corresponding to each building according to the outline and the height corresponding to each building comprises:

respectively calculating a first similarity between the building and a first street building and a second similarity between the building and a second street building aiming at each building in the area to be identified;

classifying the buildings into a first building and a second building according to the first similarity and the second similarity;

aiming at each first building, calculating the number of the household air conditioners corresponding to the first building according to the corresponding outline and height of the first building and the mapping relation between the number of the first household air conditioners and the outline and height;

4. The method according to claim 2 or 3, wherein the determining the sum of the target number of the household air conditioners corresponding to each building as the total number of the household air conditioners in the area to be identified comprises:

respectively calculating a first quantity sum of target household air-conditioners corresponding to the first building and a second quantity sum of target household air-conditioners corresponding to the second building;

5. The method according to any one of claims 1-3, wherein determining the outline of each building in the area to be identified from the remotely sensed image comprises:

carrying out image processing operation on the remote sensing image to obtain a processed remote sensing image, wherein the image processing operation comprises geometric correction operation and/or image fusion operation;

6. A method according to any one of claims 1-3, wherein said determining the height of each building from said remote sensing images comprises:

determining shadow size information corresponding to the buildings aiming at the outlines of the buildings;

determining the position relation between a satellite and the sun when the remote sensing image is shot;

and calculating the height of the building according to the position relation and the shadow size information.

7. The method according to any one of claims 1 to 3, wherein the determining the number of the household air conditioners corresponding to each buildings along the street in the street view picture according to the at least one street view picture comprises:

inputting the street view picture into a preset household air conditioner identification model aiming at each street view picture to obtain the number of household air conditioners corresponding to buildings along the street in the street view picture;

and calculating the average value of the number of the household air conditioners corresponding to the buildings along the street in at least one street view picture, and determining the average value as the number of the household air conditioners corresponding to the buildings along the street in the area to be identified.

8. An identification device for a household air conditioner, comprising:

9. An electronic device, comprising: a memory, a processor;

a memory; a memory for storing the processor-executable instructions;

wherein the processor is configured to call the program instructions in the memory to perform the home air conditioner identification method according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored therein computer-executable instructions for implementing the home air conditioner identification method according to any one of claims 1 to 7 when executed by a processor.