WO2016119107A1 - 一种噪音地图绘制方法及装置 - Google Patents
一种噪音地图绘制方法及装置 Download PDFInfo
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- WO2016119107A1 WO2016119107A1 PCT/CN2015/071568 CN2015071568W WO2016119107A1 WO 2016119107 A1 WO2016119107 A1 WO 2016119107A1 CN 2015071568 W CN2015071568 W CN 2015071568W WO 2016119107 A1 WO2016119107 A1 WO 2016119107A1
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- 238000010586 diagram Methods 0.000 description 8
- 238000004458 analytical method Methods 0.000 description 5
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/06—Transformation of speech into a non-audible representation, e.g. speech visualisation or speech processing for tactile aids
- G10L21/10—Transforming into visible information
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/21—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being power information
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
Definitions
- the invention belongs to the technical field of noise maps, and in particular relates to a method and a device for drawing noise maps.
- noise map shows the noise of the local area for their travel and other daily arrangements as a guide, just like the road real-time status map.
- the improvement of hardware storage capacity and computing power, the development of cloud technology and big data technology, the development of various new data excavator learning and even deep mining technology provide the basis for the realization of position-dependent noise map drawing.
- the existing noise map drawing method cannot distinguish between indoor environmental noise and outdoor environmental noise, and is not conducive to improving the drawing accuracy of the noise map.
- the reason is that the existing noise map drawing method does not distinguish between indoor environmental noise and outdoor environmental noise, and only draws environmental noise uniformly to generate a noise map.
- the noise is different from the weather, road conditions and other information.
- the noise is very sensitive to the location. It may be separated by a wall. The noise will be significantly different. The noise will also be abruptly changed for different reasons. Therefore, the noise map related to the location is drawn. Need to distinguish between indoor environmental noise and outdoor environmental noise.
- the purpose of the embodiments of the present invention is to provide a noise map drawing method, which aims to solve the existing noise map drawing method, and can not distinguish between indoor environmental noise and outdoor environmental noise, and is not conducive to improving the drawing accuracy of the noise map.
- a noise map drawing method includes:
- the ambient noise includes a noise value, time information, and location information
- the ambient noise is recognized as indoor environmental noise
- the ambient noise is recognized as outdoor ambient noise, or when the picture is an invalid picture, the ambient noise is recognized as outdoor ambient noise, or when the picture is a valid picture and the When the picture is taken outdoors, the ambient noise is recognized as outdoor ambient noise;
- a noise map is drawn based on the indoor environmental noise and the outdoor environmental noise.
- Another object of the present invention is to provide a noise map drawing apparatus, including:
- An acquiring module configured to acquire ambient noise uploaded by the terminal, where the ambient noise includes a noise value, time information, and location information;
- An effective picture detecting module configured to detect, when the terminal uploads a picture corresponding to the ambient noise, whether the picture is a valid picture
- the indoor ambient noise module is configured to identify the ambient noise as indoor ambient noise when the picture is a valid picture and the picture is taken indoors;
- An outdoor ambient noise module configured to identify the ambient noise as outdoor ambient noise when the picture is absent, or to identify outdoor ambient noise when the picture is an invalid picture, or when When the picture is a valid picture and the picture is taken outdoors, the ambient noise is recognized as outdoor ambient noise;
- a noise mapping module is configured to draw a noise map according to the indoor environmental noise and the outdoor environmental noise.
- the noise map is drawn according to the indoor environmental noise and the outdoor environmental noise, and the existing noise map drawing method is solved, and the indoor environmental noise and the outdoor environmental noise cannot be distinguished, which is not conducive to improving the noise map drawing.
- the problem of precision The noise associated with the location of the noise map is more accurate, which not only improves the accuracy of the noise map but also improves the reliability of the noise map.
- FIG. 1 is a flowchart of implementing a noise map drawing method according to an embodiment of the present invention
- FIG. 2 is a flowchart of an implementation of a noise map drawing method S102 according to an embodiment of the present invention
- FIG. 3 is a flowchart of an implementation of a noise map drawing method S103 according to an embodiment of the present invention.
- FIG. 4 is a first structural block diagram of a noise map drawing apparatus according to an embodiment of the present invention.
- FIG. 5 is a second structural block diagram of a noise map drawing apparatus according to an embodiment of the present invention.
- FIG. 6 is a third structural block diagram of a noise map drawing apparatus according to an embodiment of the present invention.
- FIG. 7 is a fourth structural block diagram of a noise map drawing apparatus according to an embodiment of the present invention.
- FIG. 1 is a flowchart of an implementation of a noise map drawing method according to an embodiment of the present invention, which is described in detail as follows:
- step S101 acquiring environmental noise uploaded by the terminal, where the ambient noise includes a noise value, time information, and location information;
- the time information indicates the time information of the environmental noise record, which may be specific to the minute, that is, the year, month, day, and hour, or may be specific to the second, that is, the year, month, day, hour, minute, and second.
- the time unit of the time information is not limited.
- Location information includes, but is not limited to, latitude and longitude and geographic location.
- the server may be any type of server, including but not limited to a physical server and a virtual server.
- the virtual server can be a cloud server.
- connection between the terminal and the server can be established by any wired connection, or by any wireless connection.
- Wireless connection methods include, but are not limited to, Bluetooth connection mode, WIFI connection mode, 3G connection mode, 4G connection mode, and 5G connection mode.
- step S102 when the terminal uploads a picture corresponding to the ambient noise, detecting whether the picture is a valid picture;
- the server detects whether the terminal uploads a picture corresponding to the ambient noise, and when the terminal uploads a picture corresponding to the ambient noise, the picture is associated with the ambient noise, and is recorded and stored.
- step S103 when the picture is a valid picture and the shooting location of the picture is indoor, the environmental noise is recognized as indoor environmental noise;
- the image recognition algorithm is used to identify the content of the image. When the shooting location of the image in the recognition result is indoor, it indicates that the environmental noise uploaded by the terminal is indoor environmental noise.
- step S104 when there is no picture, the environmental noise is recognized as outdoor environmental noise, or when the picture is an invalid picture, the environmental noise is recognized as outdoor environmental noise, or when the picture is When the effective picture is taken and the shooting location of the picture is outdoor, the ambient noise is recognized as outdoor ambient noise;
- the image recognition algorithm is used to identify the content of the image.
- the shooting location of the image in the recognition result is outdoor, it indicates that the ambient noise uploaded by the terminal is outdoor environmental noise.
- step S105 a noise map is drawn based on the indoor environmental noise and the outdoor environmental noise.
- the noise map includes the noise value, the time and latitude and longitude corresponding to the noise value.
- the indoor area is used to draw the indoor environmental noise
- the outdoor area is adopted.
- the outdoor ambient noise is plotted to map a noise, the indoor area and the outdoor area being different areas of the drawing area.
- the noise map is drawn according to the indoor environmental noise and the outdoor environmental noise, so that the noise related to the location of the noise map is more accurate, thereby improving the accuracy of drawing the noise map and improving the noise map. Reliability.
- FIG. 2 is a flowchart of an implementation of a noise map drawing method S102 according to an embodiment of the present invention, which is described in detail as follows:
- step S201 it is detected whether the picture carries a generated flag of the rear camera
- step S202 when the generated flag of the rear camera is carried in the picture, it is determined that the photo is a valid photo, and when the generated flag of the rear camera is not carried in the picture, the photo is determined to be an invalid photo. .
- the generated flag of the rear camera When the generated flag of the rear camera is carried in the picture, it indicates that the picture is generated by calling a rear camera of the terminal, and determining that the picture is a valid photo;
- the generated flag of the rear camera When the generated flag of the rear camera is not carried in the picture, it indicates that the picture is generated by calling a rear camera of the terminal, and the photo is determined to be an invalid photo.
- the photos are distinguished and divided into valid photos and invalid images, so that the indoor environment noise can be acquired according to the effective photos, thereby improving the effectiveness of indoor environmental noise collection.
- the environmental noise mining model including at least one of an environmental noise clustering model, a noise decibel mean model, and a noise weighting model;
- the environmental noise clustering model is:
- the value of the noise value can be obtained at different distances. .
- Adjusting the value of ⁇ i can give different weights to the noise value of each dimension, reflecting the robustness and continuation of the algorithm.
- the value of ⁇ i is larger, when the acquisition time of the environmental noise is The larger the time difference of the current time is, the smaller the value of ⁇ i is, and the smaller the time difference between the acquisition time of the environmental noise and the current time is, the larger the value of ⁇ i is.
- a plurality of noise values may be collected within a certain time range or a certain geographical range, and each noise value is clustered as one-dimensional data.
- the similarity ⁇ is less than a preset threshold, the heart can be expressed. Depicting the set and using the obtained class as the noise value of the time range of the geographical range;
- the cloud-stored vector may also be used as a group of data to be clustered, and the obtained class of heart is used as the noise value of the time range of the geographical range, and thus the location and time point corresponding to the finally obtained noise value.
- noise decibel mean model is:
- value is the noise decibel mean
- value i is the noise value in the ith ambient noise
- n is the number of ambient noises
- the noise weighting model is:
- value' is the noise weighting value
- value i is the noise value in the i-th ambient noise
- n is the number of environmental noises
- ⁇ i is the weight of each noise value
- ⁇ i 1.
- the time difference between the distance from the target position and the current time is known, and the farther the distance and the earlier the reference value of the environmental noise is, the smaller the reference value is.
- Different distances and different time periods are used to assign weights to the noise values in each ambient noise, and generate noise weighting values according to the noise values with weights, so as to avoid the failure of the current noise decibel value in a short time.
- FIG. 3 is a flowchart of an implementation of a noise map drawing method S103 according to an embodiment of the present invention, which is described in detail as follows:
- a noise weighting value is obtained according to the indoor environmental noise, the outdoor environmental noise, and a pre-configured environmental noise mining model, and the noise weighting value includes noise weighting value of indoor environmental noise and noise of outdoor environmental noise. Weighted value
- step S302 mining the association rule between the noise weighting value and the indoor environmental noise and the outdoor environmental noise
- Any existing data mining algorithm may be used to mine the association rule between the noise weighting value of the indoor environmental noise and the indoor environmental noise, and to mine the noise weighting value of the outdoor environmental noise and the outdoor environmental noise.
- step S303 a noise map is drawn based on the indoor environmental noise, the outdoor environmental noise, and the association rule.
- the noise weighting value includes the noise weighting value of the indoor environmental noise and the outdoor environmental noise. Noise weighting value.
- the geographical location, time, and the latest digging noise weighting value are displayed on the noise map, which further improves the validity and accuracy of the noise map.
- the embodiment of the invention mainly describes a flowchart for implementing the noise map drawing method in practical applications, which is described in detail as follows:
- the terminal invokes the rear camera of the smart terminal before sending the photo, it is determined that the photo is a valid photo, and if the terminal calls the photo transmission from the local photo library or uses the front camera to take a photo, it is determined that the photo is invalid. photo.
- Environmental noise from the same geographic location is classified using techniques for image analysis and geographic coordinate comparison.
- the ambient noise is divided into different dimensions.
- the first dimension is the season/month dimension
- the second dimension is the time dimension
- the third dimension is whether it is a public holiday
- the fourth dimension is a geographic dimension. Then pass After analyzing the environmental noise of different dimensions using the environmental noise mining algorithm, it is possible to obtain a noise reference value/experience value for a certain period of time in a certain season.
- the ambient noise is divided into different dimensions.
- the first dimension is the season/month dimension
- the second dimension is the time dimension
- the third dimension is whether it is a public holiday
- the fourth dimension is a geographic dimension.
- the collected ambient noise becomes an environmental noise warehouse. Then, by using the environmental noise mining algorithm for different levels of environmental noise analysis, the noise reference value/experience value of a certain time in a certain season can be obtained.
- the value displayed on the noise map will not change immediately. Instead, the new value will be included in the environmental noise database, and then analyzed to determine the location of the new value in the environmental noise warehouse. When the new value is incremented to a certain extent or after a fixed period of time, a new noise reference/experience value is calculated by a machine learning algorithm.
- the terminal wants to check the current environmental noise of a certain place, take the recently uploaded multiple sets of environmental noise near the location, calculate the mean and variance of the ambient noise, and when the variance is small, return the noise mean to the terminal, when the variance When it is large, it represents a sudden change in the noise environment at the location, and when the average value is returned to the terminal, the terminal is notified that the environmental noise is abrupt.
- the first scenario the scene of obtaining a location-related noise map, is detailed as follows:
- the terminal invokes the rear camera of the smart terminal before sending the photo, it is determined that the photo is a valid photo, and if the terminal calls the photo transmission from the local photo library or uses the front camera to take a photo, it is determined that the photo is invalid. photo.
- Environmental noise from the same geographic location is classified using techniques for image analysis and geographic coordinate comparison.
- the ambient noise is divided into different dimensions.
- the first dimension is the season/month dimension
- the second dimension is the time dimension
- the third dimension is whether it is a public holiday
- the fourth dimension is a geographic dimension. Then, by using the environmental noise mining algorithm for different levels of environmental noise analysis, it is possible to obtain a noise reference value/experience value for a certain period of time in a certain season.
- the ambient noise is divided into different dimensions.
- the first dimension is the season/month dimension
- the second dimension is the time dimension
- the third dimension is whether it is a public holiday
- the fourth dimension is a geographic dimension.
- the collected ambient noise becomes an environmental noise warehouse. Then, by using the environmental noise mining algorithm for different levels of environmental noise analysis, the noise reference value/experience value of a certain time in a certain season can be obtained.
- a position-dependent noise map can be obtained, which has different performances in different dimensions.
- the specific value of the noise can be divided into high, medium and low third gears. Whenever different colors are used, different noise values are marked on the noise distribution map for the terminal.
- the user views the scene of the current noise environment in a certain place, as detailed below:
- the mean of the data is returned to the user as the noise value at the current position.
- the user views the entire noise map, as detailed below:
- the noise value at the corresponding position on the screen will be read from the cloud, and returned to the device used by the user, and displayed to the corresponding position of the current map;
- the cloud When the user chooses to enter a building to view the noise distribution inside the cloud, the cloud automatically switches to the noise value inside the building, and then reads the noise value inside the building and displays it to the current user interface, so that Checked by the user.
- FIG. 4 is a first structural block diagram of a noise map drawing device provided by an embodiment of the present invention, and the noise map drawing device can be run in a server. For the convenience of explanation, only the parts related to the present embodiment are shown.
- the noise mapping device includes:
- the obtaining module 41 is configured to acquire ambient noise uploaded by the terminal, where the ambient noise includes a noise value, time information, and location information;
- the effective picture detecting module 42 is configured to detect, when the terminal uploads a picture corresponding to the ambient noise, whether the picture is a valid picture;
- the indoor ambient noise module 43 is configured to identify the ambient noise as indoor ambient noise when the picture is a valid picture and the shooting location of the picture is indoor;
- An outdoor ambient noise module 44 configured to recognize the ambient noise as outdoor when the picture is absent Ambient noise, or when the picture is an invalid picture, the ambient noise is recognized as outdoor ambient noise, or when the picture is a valid picture and the picture is taken outdoors, the ambient noise is identified as Outdoor environmental noise;
- the noise map drawing module 45 is configured to draw a noise map according to the indoor environmental noise and the outdoor environmental noise.
- FIG. 5 is a second structural block diagram of a noise map drawing apparatus according to an embodiment of the present invention.
- the effective picture detecting module 42 include:
- the detecting unit 421 is configured to detect whether the picture carries a generated flag of the rear camera
- the determining unit 422 is configured to determine that the photo is a valid photo when the generated flag of the rear camera is carried in the picture, and determine that the photo is invalid when the generated flag of the rear camera is not carried in the picture photo.
- the noise map drawing module 45 is specifically configured to: according to the indoor environmental noise, the outdoor environmental noise, and a pre-configured environmental noise mining model And generating a noise map, the environmental noise mining model including at least one of an environmental noise clustering model, a noise decibel mean model, and a noise weighting model.
- FIG. 6 is a third structural block diagram of a noise map drawing device according to an embodiment of the present invention, where the noise map drawing device further includes:
- An environmental noise mining model configuration module 46 configured to configure an environmental noise mining model, the environmental noise mining model including at least one of an environmental noise clustering model, a noise decibel mean model, and a noise weighting model;
- the environmental noise clustering model is:
- noise decibel mean model is:
- value is the noise decibel mean
- value i is the noise value in the ith ambient noise
- n is the number of ambient noises
- the noise weighting model is:
- value' is the noise weighting value
- value i is the noise value in the i-th ambient noise
- n is the number of environmental noises
- ⁇ i is the weight of each noise value
- ⁇ i 1.
- FIG. 7 is a fourth structural block diagram of a noise map drawing device according to an embodiment of the present invention.
- the noise map drawing module 45 include:
- the noise weighting value obtaining unit 451 is configured to obtain a noise weighting value according to the indoor environmental noise, the outdoor environmental noise, and a pre-configured environmental noise mining model, where the noise weighting value includes a noise weighting value of indoor environmental noise and an outdoor Noise-weighted value of environmental noise;
- the association rule mining unit 452 is configured to mine an association rule between the noise weighting value and the indoor environmental noise and the outdoor environmental noise;
- the noise map drawing unit 453 is configured to draw a noise map according to the indoor environmental noise, the outdoor environmental noise, and the association rule.
- the present invention can be implemented by means of software plus necessary general hardware.
- the program may be stored in a readable storage medium such as a random access memory, a flash memory, a read only memory, a programmable read only memory, an electrically erasable programmable memory, a register, or the like.
- the storage medium is located in a memory, the processor reads information in the memory, and in conjunction with its hardware, performs the methods described in various embodiments of the present invention.
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Abstract
Description
Claims (10)
- 一种噪音地图绘制方法,其特征在于,包括:获取终端上传的环境噪音,所述环境噪音包括噪音值、时间信息以及位置信息;当所述终端上传与所述环境噪音对应的图片时,检测所述图片是否为有效图片;当所述图片为有效图片且所述图片的拍摄地点为室内时,所述环境噪音识别为室内环境噪音;当没有所述图片时,所述环境噪音识别为室外环境噪音,或者,当所述图片为无效图片时,所述环境噪音识别为室外环境噪音,或者,当所述图片为有效图片且所述图片的拍摄地点为室外时,所述环境噪音识别为室外环境噪音;根据所述室内环境噪音、所述室外环境噪音,绘制噪音地图。
- 如权利要求1所述的噪音地图绘制方法,其特征在于,当所述终端上传与所述环境噪音对应的图片时,检测所述图片是否为有效图片,具体为:检测所述图片是否携带了后置摄像头的生成标记;当所述图片中携带了后置摄像头的生成标记时,判断所述照片为有效照片,当所述图片中没有携带后置摄像头的生成标记时,判断所述照片为无效照片。
- 如权利要求1所述的噪音地图绘制方法,其特征在于,在所述根据所述室内环境噪音、所述室外环境噪音,绘制噪音地图,具体为:根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,绘制噪音地图,所述环境噪音挖掘模型包括环境噪音聚类模型、噪音分贝均值模型以及噪音加权值模型中的至少一种。
- 如权利要求3所述的噪音地图绘制方法,其特征在于,在所述根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,绘制噪音地图之前,所述噪音地图绘制方法,还包括:配置环境噪音挖掘模型,所述环境噪音挖掘模型包括环境噪音聚类模型、噪音分贝均值模型以及噪音加权值模型中的至少一种;其中,所述环境噪音聚类模型为:其中,所述噪音分贝均值模型为:其中,value为噪音分贝均值,valuei为第i个环境噪音中的噪音值,n为环境噪音的个数;其中,所述噪音加权值模型为:其中,value’为噪音加权值,valuei为第i个环境噪音中的噪音值,n为环境噪音的个数,ωi是每个噪音值的权值,且∑ωi=1。
- 如权利要求3或4所述的噪音地图绘制方法,其特征在于,当所述环境噪音挖掘模型采用所述噪音加权值模型时,所述根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,绘制噪音地图,具体为:根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,获取噪音加权值,所述噪音加权值包括室内环境噪音的噪音加权值和室外环境噪音的噪音加权值;挖掘所述噪音加权值与所述室内环境噪音、所述室外环境噪音的关联规则;根据所述室内环境噪音、所述室外环境噪音以及所述关联规则,绘制噪音地图。
- 一种噪音地图绘制装置,其特征在于,包括:获取模块,用于获取终端上传的环境噪音,所述环境噪音包括噪音值、时间信息以及位置信息;有效图片检测模块,用于当所述终端上传与所述环境噪音对应的图片时,检测所述图片是否为有效图片;室内环境噪音模块,用于当所述图片为有效图片且所述图片的拍摄地点为室内时,所述环境噪音识别为室内环境噪音;室外环境噪音模块,用于当没有所述图片时,所述环境噪音识别为室外环境噪音,或者,当所述图片为无效图片时,所述环境噪音识别为室外环境噪音,或者,当所述图片为有效图片且所述图片的拍摄地点为室外时,所述环境噪音识别为室外环境噪音;噪音地图绘制模块,用于根据所述室内环境噪音、所述室外环境噪音,绘制噪音地图。
- 如权利要求6所述的噪音地图绘制装置,其特征在于,所述有效图片检测模块,包括:检测单元,用于检测所述图片是否携带了后置摄像头的生成标记;判断单元,用于当所述图片中携带了后置摄像头的生成标记时,判断所述照片为有效照片,当所述图片中没有携带后置摄像头的生成标记时,判断所述照片为无效照片。
- 如权利要求6所述的噪音地图绘制装置,其特征在于,所述噪音地图绘制模块,具体用于根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,绘制噪音地图,所述环境噪音挖掘模型包括环境噪音聚类模型、噪音分贝均值模型以及噪音加权值模型中的至少一种。
- 如权利要求8所述的噪音地图绘制装置,其特征在于,所述噪音地图绘制装置,还包括:环境噪音挖掘模型配置模块,用于配置环境噪音挖掘模型,所述环境噪音挖掘模型包括环境噪音聚类模型、噪音分贝均值模型以及噪音加权值模型中的 至少一种;其中,所述环境噪音聚类模型为:其中,所述噪音分贝均值模型为:其中,value为噪音分贝均值,valuei为第i个环境噪音中的噪音值,n为环境噪音的个数;其中,所述噪音加权值模型为:其中,value’为噪音加权值,valuei为第i个环境噪音中的噪音值,n为环境噪音的个数,ωi是每个噪音值的权值,且∑ωi=1。
- 如权利要求8或9所述的噪音地图绘制装置,其特征在于,所述噪音地图绘制模块,包括:噪音加权值获取单元,用于根据所述室内环境噪音、所述室外环境噪音以及预配置的环境噪音挖掘模型,获取噪音加权值,所述噪音加权值包括室内环境噪音的噪音加权值和室外环境噪音的噪音加权值;关联规则挖掘单元,用于挖掘所述噪音加权值与所述室内环境噪音、所述室外环境噪音的关联规则;噪音地图绘制单元,用于根据所述室内环境噪音、所述室外环境噪音以及所述关联规则,绘制噪音地图。
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