CN113421299A - Water depth measuring system and method based on water level gauge and camera - Google Patents
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Abstract
The invention discloses a water depth measuring system and method based on a water level gauge and a camera, wherein the system comprises the following modules: a wireless digital water level gauge; a water depth value transmission module; a camera; an image transmission module; a data receiving module; and a background processing module. The method can measure the regional flooding depth in the camera picture and generate the regional flooding equal-depth line schematic diagram. The method can be used for evaluating urban waterlogging conditions and provides basis for government decision-making departments to make policies such as urban drainage, emergency rescue and relief, traffic control and the like. The urban area flooding condition determined by the invention can be provided for the public, and references are provided for public trip, danger avoidance and the like.
Description
Technical Field
The invention belongs to the technical field of computer vision, and particularly relates to a water depth measuring system and method based on a water level gauge and a camera.
Background
In recent years, with the development of artificial intelligence technology, various industries are gradually combined with artificial intelligence technology to realize intellectualization, and smart cities are also greatly developed. Early warning and treatment of urban waterlogging in municipal management are problems frequently encountered in many cities, loss of lives and properties of citizens can be caused if the urban waterlogging cannot be found and early warned in time, and the site investigation of municipal personnel is time-consuming and labor-consuming, so that the flooding depth needs to be intelligently estimated through a water level gauge and a camera, information such as the position and the depth of a flooding area in the city is gathered, and the method has practical significance for emergency rescue and disaster relief or early warning of the citizens.
The method can measure the regional flooding depth in the camera picture and generate the regional flooding equal-depth line schematic diagram. The method can be used for evaluating urban waterlogging conditions and provides basis for government decision-making departments to make policies such as urban drainage, emergency rescue and relief, traffic control and the like. The urban area flooding condition determined by the invention can be provided for the public, and references are provided for public trip, danger avoidance and the like.
Disclosure of Invention
The invention aims to provide an intelligent flooded depth measuring system and method based on a water level gauge and a camera.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
a water depth measuring system based on a water level gauge and a camera comprises the following modules:
a water level gauge for measuring water depth;
the water depth value transmission module is used for transmitting the measured water depth value of the water level gauge to the receiving module;
the camera is used for acquiring an area image of the water level meter area;
the image transmission module is used for transmitting the regional image data of the water level meter region acquired by the camera to the receiving module;
the data receiving module is used for transmitting the received data to the background processing module;
and the background processing module is used for processing the data of the water level gauge and the camera.
In order to optimize the technical scheme, the specific measures adopted further comprise:
the camera acquires images in a snapshot mode.
The camera mounting height and angle cover the corresponding water gauge area.
The camera calibrates the position of the covered water level gauge.
The water level meter uses a wireless digital water level meter.
The water level meter transmits the water depth reading at regular time and is used for controlling whether the camera captures the image or not;
the water level meter is provided with a water depth threshold value, when the reading of the water level meter is smaller than the threshold value, the camera does no work, when the reading of the water level meter is larger than the water depth threshold value, the camera shoots an image, and the current reading of the water level meter and the image shot by the camera are transmitted to the background processing module through the receiving module.
The background processing module comprises a water surface area segmentation model and is used for detecting the water surface area in the image and updating the water depth isobologram according to the reading of the current water level gauge.
The water surface area segmentation model adopts an improved UNet model to segment a flooded area in a snapshot image of a camera, and the water surface area segmentation model specifically comprises the following steps:
the improved UNet model is filled with zero values in a convolution layer, the size of a feature map after convolution is consistent with that of input, and point-by-point addition calculation is used during feature map fusion with the same size during jump connection;
the improved UNet model, after convolutional layers, uses an attention mechanism, including channel attention and spatial attention;
the attention of the channel is that global maximum pooling is used for each channel of the feature map, the attention weight of each channel is output after the full connection layer is connected, and then the attention weight is multiplied by the input feature map;
the spatial attention is characterized in that the maximum pooling along a channel and the average pooling along the channel are used for each spatial pixel position of the feature map, the two features are spliced according to the channel, the attention weight of each spatial pixel position is output after the convolution layer is connected, and then the attention weight is multiplied by the input feature map;
the use of the channel attention and the space attention can improve the performance of the model and is beneficial to learning the feature representation which is more robust to recognition and positioning by the model.
When the water surface region segmentation model updates the water depth isobath, the latest reading of the water level gauge and the output mask of the water surface region segmentation model are received at the same time, and the method specifically comprises the following steps:
the water depth isobologram is used for displaying, when the reading of the water level meter exceeds a water depth threshold value for the first time, initialization is carried out, and the depth values of the output masks of the water surface area segmentation model at the moment are all set as the current reading of the water level meter;
the water depth isobologram shows that when a new water surface area mask is received, intersection is calculated with the existing mask, and a water surface extension area at the moment is generated after the intersection is subtracted from the new water surface area;
the water depth isobologram shows that when a new reading of the water level gauge is received, the difference value between the reading of the water level gauge and the previous reading is calculated, and the difference value is taken as the depth value of the water surface extension area at the moment;
and when a new reading of the water level gauge is received, calculating a difference value with the previous reading, updating the depth values of different depth areas in the existing isobologram by using the difference value, and adding the depth values of the different areas of the existing isobologram and the difference value to obtain a new depth value.
A water depth determination method based on a water level gauge and a camera comprises the following steps:
s1: the background processing module acquires the reading of the water level gauge at regular time, when the reading of the water level gauge is lower than a water depth threshold value, the situation that the problem of flooding does not occur is indicated, the camera is not started to take a snapshot, and when the reading of the water level gauge is higher than the water depth threshold value, the situation that the problem of flooding occurs is indicated, and the camera is started to take a snapshot;
s2: the camera acquires a regional image of a water level meter region in a snapshot mode;
s3: the background processing module adopts an improved UNet model to segment a flooded area in a snapshot image of the camera;
s4: and the background processing module updates the water depth contour map according to the reading of the current water level meter.
The invention has the following beneficial effects:
the method can automatically determine the depth of the flooded area and generate the isobologram, does not need the time-consuming and labor-consuming field survey of municipal workers, can provide a flooded general map for government departments, provides decision bases for traffic control, rescue and relief, urban drainage and the like, and can guide public danger avoidance and travel planning.
Drawings
FIG. 1 is a schematic diagram of the overall system of the present invention.
FIG. 2 is a system flow diagram of the present invention.
FIG. 3 is a water depth contour plot generated by the present invention.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings.
As shown in fig. 1, a water depth measuring system based on a water level gauge and a camera comprises the following modules:
a water level gauge for measuring water depth;
the water depth value transmission module is used for transmitting the measured water depth value of the water level gauge to the receiving module;
the camera is used for acquiring an area image of the water level meter area;
the image transmission module is used for transmitting the regional image data of the water level meter region acquired by the camera to the receiving module;
the data receiving module is used for transmitting the received data to the background processing module;
and the background processing module is used for processing the data of the water level gauge and the camera.
In an embodiment, the data source is a water level meter measuring water depth readings, and regional image data.
In the embodiment, the camera acquires images in a snapshot mode, and compared with a video mode, the calculation amount and the storage amount can be reduced.
In an embodiment, the camera mounting height and angle cover the corresponding water gauge area.
In an embodiment, the camera is used for calibrating the position of the covered water level gauge.
In the embodiment, the water level meter uses a wireless digital water level meter, so that the water depth value can be conveniently acquired and transmitted.
In the embodiment, the water level meter transmits water depth reading at regular time and is used for controlling whether the camera captures an image or not;
the water level meter is provided with a water depth threshold value, when the reading of the water level meter is smaller than the threshold value, the camera does no work, when the reading of the water level meter is larger than the water depth threshold value, the camera shoots an image, and the current reading of the water level meter and the image shot by the camera are transmitted to the background processing module through the receiving module.
In an embodiment, the background processing module comprises a water surface region segmentation model for detecting a water surface region in the image and updating the water depth contour map representation according to the current reading of the water level gauge.
In the embodiment, the water surface area segmentation model adopts an improved UNet model to segment a flooded area in a snapshot image of a camera, and the method specifically comprises the following steps:
the improved UNet model is filled with zero values in a convolution layer, the size of a feature map after convolution is consistent with that of input, and point-by-point addition calculation is used during feature map fusion with the same size during jump connection;
the improved UNet model, after convolutional layers, uses an attention mechanism, including channel attention and spatial attention;
the attention of the channel is that global maximum pooling is used for each channel of the feature map, the attention weight of each channel is output after the full connection layer is connected, and then the attention weight is multiplied by the input feature map;
the spatial attention is characterized in that the maximum pooling along a channel and the average pooling along the channel are used for each spatial pixel position of the feature map, the two features are spliced according to the channel, the attention weight of each spatial pixel position is output after the convolution layer is connected, and then the attention weight is multiplied by the input feature map;
the use of the channel attention and the space attention can improve the performance of the model and is beneficial to learning the feature representation which is more robust to recognition and positioning by the model.
In an embodiment, when the water surface region segmentation model updates the water depth isophote, the latest reading of the water level gauge and the output mask of the water surface region segmentation model are received at the same time, which is specifically as follows:
the water depth isobologram is used for displaying, when the reading of the water level meter exceeds a water depth threshold value for the first time, initialization is carried out, and the depth values of the output masks of the water surface area segmentation model at the moment are all set as the current reading of the water level meter;
the water depth isobologram shows that when a new water surface area mask is received, intersection is calculated with the existing mask, and a water surface extension area at the moment is generated after the intersection is subtracted from the new water surface area;
the water depth isobologram shows that when a new reading of the water level gauge is received, the difference value between the reading of the water level gauge and the previous reading is calculated, and the difference value is taken as the depth value of the water surface extension area at the moment;
and when a new reading of the water level gauge is received, calculating a difference value with the previous reading, updating the depth values of different depth areas in the existing isobologram by using the difference value, and adding the depth values of the different areas of the existing isobologram and the difference value to obtain a new depth value.
As shown in fig. 2, the water depth measuring method based on the water level gauge and the camera of the invention comprises the following steps:
s1: acquiring readings of the water level meter at regular time;
in the embodiment, the background processing module acquires the reading of the wireless digital water level meter at regular time and sets a water depth threshold, when the reading of the water level meter is lower than the threshold, the problem of flooding is not generated, the snapshot function of the camera cannot be started, and when the reading of the water level meter is higher than the threshold, the problem of flooding is generated, and the camera is informed to start the snapshot function.
S2: taking a snapshot by a camera;
in the embodiment, the camera acquires images by adopting a snapshot mode instead of a mode of decoding a video stream, and compared with a video mode, the calculation amount and the storage amount can be reduced.
S3: dividing a water surface area;
in the embodiment, the water surface area segmentation adopts an improved UNet model to segment a flooded area in a snapshot image of a camera, and specifically comprises the following steps:
the improved UNet model is filled with zero values in a convolution layer, the size of a feature map after convolution is consistent with that of input, and point-by-point addition calculation is used during feature map fusion with the same size during jump connection;
the improved UNet model, after convolutional layers, uses an attention mechanism, including channel attention and spatial attention;
the attention of the channel is that global maximum pooling is used for each channel of the feature map, the attention weight of each channel is output after the full connection layer is connected, and then the attention weight is multiplied by the input feature map;
the spatial attention is characterized in that the maximum pooling along a channel and the average pooling along the channel are used for each spatial pixel position of the feature map, the two features are spliced according to the channel, the attention weight of each spatial pixel position is output after the convolution layer is connected, and then the attention weight is multiplied by the input feature map;
the use of the channel attention and the space attention can improve the performance of the model and is beneficial to learning the feature representation which is more robust to recognition and positioning by the model.
S4: updating the contour map representation;
in an embodiment, the water depth isobath update receives the latest water level meter reading and the output mask of the water surface region segmentation model at the same time, which is specifically as follows:
the water depth isobologram is used for displaying, when the reading of the water level meter exceeds a water depth threshold value for the first time, initialization is carried out, and the depth values of the output masks of the water surface area segmentation model at the moment are all set as the current reading of the water level meter;
the water depth isobologram shows that when a new water surface area mask is received, intersection is calculated with the existing mask, and a water surface extension area at the moment is generated after the intersection is subtracted from the new water surface area;
the water depth isobologram shows that when a new reading of the water level gauge is received, the difference value between the reading of the water level gauge and the previous reading is calculated, and the difference value is taken as the depth value of the water surface extension area at the moment;
and when a new reading of the water level gauge is received, calculating a difference value with the previous reading, updating the depth values of different depth areas in the existing isobologram by using the difference value, and adding the depth values of the different areas of the existing isobologram and the difference value to obtain a new depth value. A water depth contour map of an embodiment of the present invention is shown in fig. 3.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (10)
1. A water depth measuring system based on a water level gauge and a camera is characterized by comprising the following modules:
a water level gauge for measuring water depth;
the water depth value transmission module is used for transmitting the measured water depth value of the water level gauge to the receiving module;
the camera is used for acquiring an area image of the water level meter area;
the image transmission module is used for transmitting the regional image data of the water level meter region acquired by the camera to the receiving module;
the data receiving module is used for transmitting the received data to the background processing module;
and the background processing module is used for processing the data of the water level gauge and the camera.
2. A water level gauge and camera based water depth determination system as claimed in claim 1, wherein said camera captures images in a snapshot.
3. A water level gauge and camera based water depth determination system according to claim 1, wherein the camera mounting height and angle covers the respective water gauge area.
4. A water level gauge and camera based water depth determination system according to claim 3, wherein the camera calibrates the covered water level gauge position.
5. The water level gauge and camera-based water depth measuring system of claim 1, wherein the water level gauge uses a wireless digital water level gauge.
6. A water level gauge and camera based water depth determination system as claimed in claim 5, wherein the water level gauge transmits water depth readings periodically for controlling whether the camera takes a snapshot;
the water level meter is provided with a water depth threshold value, when the reading of the water level meter is smaller than the threshold value, the camera does no work, when the reading of the water level meter is larger than the water depth threshold value, the camera shoots an image, and the current reading of the water level meter and the image shot by the camera are transmitted to the background processing module through the receiving module.
7. The water level gauge and camera based water depth determination system of claim 1, wherein the background processing module comprises a water surface region segmentation model for detecting the water surface region in the image and updating the water depth contour map representation based on the current water level gauge reading.
8. The water level gauge and camera based water depth measuring system according to claim 7, wherein the water surface region segmentation model employs an improved UNet model to segment the flooded region in the camera snapshot image as follows:
the improved UNet model is filled with zero values in a convolution layer, the size of a feature map after convolution is consistent with that of input, and point-by-point addition calculation is used during feature map fusion with the same size during jump connection;
the improved UNet model, after convolutional layers, uses an attention mechanism, including channel attention and spatial attention;
the attention of the channel is that global maximum pooling is used for each channel of the feature map, the attention weight of each channel is output after the full connection layer is connected, and then the attention weight is multiplied by the input feature map;
the spatial attention is characterized in that the maximum pooling along a channel and the average pooling along the channel are used for each spatial pixel position of the feature map, the two features are spliced according to the channel, the attention weight of each spatial pixel position is output after the convolution layer is connected, and then the attention weight is multiplied by the input feature map;
the use of the channel attention and the space attention can improve the performance of the model and is beneficial to learning the feature representation which is more robust to recognition and positioning by the model.
9. The system according to claim 8, wherein the water level gauge and the camera are used for receiving the latest water level gauge reading and the output mask of the water surface region segmentation model when the water surface region segmentation model updates the water depth isobath, and the method comprises the following steps:
the water depth isobologram is used for displaying, when the reading of the water level meter exceeds a water depth threshold value for the first time, initialization is carried out, and the depth values of the output masks of the water surface area segmentation model at the moment are all set as the current reading of the water level meter;
the water depth isobologram shows that when a new water surface area mask is received, intersection is calculated with the existing mask, and a water surface extension area at the moment is generated after the intersection is subtracted from the new water surface area;
the water depth isobologram shows that when a new reading of the water level gauge is received, the difference value between the reading of the water level gauge and the previous reading is calculated, and the difference value is taken as the depth value of the water surface extension area at the moment;
and when a new reading of the water level gauge is received, calculating a difference value with the previous reading, updating the depth values of different depth areas in the existing isobologram by using the difference value, and adding the depth values of the different areas of the existing isobologram and the difference value to obtain a new depth value.
10. A water depth measuring method based on a water level gauge and a camera is characterized by comprising the following steps:
s1: the background processing module acquires the reading of the water level gauge at regular time, when the reading of the water level gauge is lower than a water depth threshold value, the situation that the problem of flooding does not occur is indicated, the camera is not started to take a snapshot, and when the reading of the water level gauge is higher than the water depth threshold value, the situation that the problem of flooding occurs is indicated, and the camera is started to take a snapshot;
s2: the camera acquires a regional image of a water level meter region in a snapshot mode;
s3: the background processing module adopts an improved UNet model to segment a flooded area in a snapshot image of the camera;
s4: and the background processing module updates the water depth contour map according to the reading of the current water level meter.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006010483A (en) * | 2004-06-25 | 2006-01-12 | Senaa Kk | Method and apparatus for updating information on bottom of water |
| WO2007032595A1 (en) * | 2005-09-16 | 2007-03-22 | Korea Institute Of Construction Technology | System and method for measuring liquid level by image |
| CN102663827A (en) * | 2012-03-02 | 2012-09-12 | 天津大学 | Three-dimensional dynamic whole-process simulation method for storm surge and flood routing in complex flooding areas |
| JP2012185061A (en) * | 2011-03-07 | 2012-09-27 | Mitsubishi Electric Corp | Water level detection device, water level detection system, and water level detection method |
| CN104794753A (en) * | 2015-04-29 | 2015-07-22 | 武汉大学 | Earth rock cofferdam breach flood risk mapping method |
| CN107564052A (en) * | 2017-08-10 | 2018-01-09 | 张立华 | A kind of security assessment method of nautical chart isobath abbreviation |
| CN208172857U (en) * | 2018-02-11 | 2018-11-30 | 南昌市气象局 | A kind of Meteorological Risk Analysis early warning system of urban waterlogging disaster |
| JP2020060463A (en) * | 2018-10-11 | 2020-04-16 | 古野電気株式会社 | Underwater sensor and underwater sensing method |
| CN111080541A (en) * | 2019-12-06 | 2020-04-28 | 广东启迪图卫科技股份有限公司 | Color image denoising method based on bit layering and attention fusion mechanism |
| CN111414504A (en) * | 2020-05-08 | 2020-07-14 | 刘克建 | Building site flood detection system based on block chain and CIM |
| CN112013921A (en) * | 2019-05-30 | 2020-12-01 | 杭州海康威视数字技术股份有限公司 | Method, device and system for acquiring water level information based on water level gauge measurement image |
| CN112598910A (en) * | 2020-11-16 | 2021-04-02 | 河北工程大学 | Guiding method and device for street ponding early warning |
| CN113012172A (en) * | 2021-04-09 | 2021-06-22 | 杭州师范大学 | AS-UNet-based medical image segmentation method and system |
-
2021
- 2021-06-25 CN CN202110712712.6A patent/CN113421299B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006010483A (en) * | 2004-06-25 | 2006-01-12 | Senaa Kk | Method and apparatus for updating information on bottom of water |
| WO2007032595A1 (en) * | 2005-09-16 | 2007-03-22 | Korea Institute Of Construction Technology | System and method for measuring liquid level by image |
| JP2012185061A (en) * | 2011-03-07 | 2012-09-27 | Mitsubishi Electric Corp | Water level detection device, water level detection system, and water level detection method |
| CN102663827A (en) * | 2012-03-02 | 2012-09-12 | 天津大学 | Three-dimensional dynamic whole-process simulation method for storm surge and flood routing in complex flooding areas |
| CN104794753A (en) * | 2015-04-29 | 2015-07-22 | 武汉大学 | Earth rock cofferdam breach flood risk mapping method |
| CN107564052A (en) * | 2017-08-10 | 2018-01-09 | 张立华 | A kind of security assessment method of nautical chart isobath abbreviation |
| CN208172857U (en) * | 2018-02-11 | 2018-11-30 | 南昌市气象局 | A kind of Meteorological Risk Analysis early warning system of urban waterlogging disaster |
| JP2020060463A (en) * | 2018-10-11 | 2020-04-16 | 古野電気株式会社 | Underwater sensor and underwater sensing method |
| CN112013921A (en) * | 2019-05-30 | 2020-12-01 | 杭州海康威视数字技术股份有限公司 | Method, device and system for acquiring water level information based on water level gauge measurement image |
| CN111080541A (en) * | 2019-12-06 | 2020-04-28 | 广东启迪图卫科技股份有限公司 | Color image denoising method based on bit layering and attention fusion mechanism |
| CN111414504A (en) * | 2020-05-08 | 2020-07-14 | 刘克建 | Building site flood detection system based on block chain and CIM |
| CN112598910A (en) * | 2020-11-16 | 2021-04-02 | 河北工程大学 | Guiding method and device for street ponding early warning |
| CN113012172A (en) * | 2021-04-09 | 2021-06-22 | 杭州师范大学 | AS-UNet-based medical image segmentation method and system |
Non-Patent Citations (10)
| Title |
|---|
| "Bulk and Export Production Fluxes in the Gulf of Aqaba, Northern Red Sea", ACS EARTH AND SPACE CHEMISTRY, vol. 4, no. 8 * |
| BIRKETT CM.: "Synergistic remote sensing of Lake Chad: Variability of basin inundation", REMOTE SENSING OF ENVIRONMENT, vol. 72, no. 2 * |
| BIRKETT CM.: "Synergistic remote sensing of Lake Chad: Variability of basin inundation", REMOTE SENSING OF ENVIRONMENT, vol. 72, no. 2, 31 December 2000 (2000-12-31) * |
| TED JOHNSON;IVY KWOK;RAYMOND NG: "Fast Computation of 2-Dimensional Depth Contours", KNOWLEDGE DISCOVERY & DATA MINING CONFERENCES 1995-1998, 31 December 2009 (2009-12-31) * |
| 李昌文;徐照明;甘拯;游中琼;马强;: "洞里萨湖水位与面积和容积的关系研究", 人民长江, no. 04 * |
| 江海洋;刘林海;李红石;: "水位图像识别的场景问题处理方法和技术", 水利信息化, no. 01, 25 February 2020 (2020-02-25) * |
| 王海涛; 李剑; 黄第科: "新型等深线生成方法研究与应用", 中国水运 * |
| 童国庆;: "欧洲城市洪水管理决策支持系统", 水利水电快报, no. 08 * |
| 钮晨霄;孙瑾;丁永晖;: "融合深度与肤色特征的自适应手部跟踪算法", 计算机科学, no. 1, 15 June 2016 (2016-06-15) * |
| 高敏; 罗毅: "S-57格式海图等深线数据向Shape格式的转换", 第十八届中国环境遥感应用技术论坛论文集 * |
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