Method and system for automatically detecting protection state of edge hole, and electronic equipment

Abstract

The invention provides an automatic detection method and system for the protection state of a limb hole, and electronic equipment. The method comprises the steps of obtaining a first image of a construction area; and processing the first image by using the mathematical model, and obtaining a pixel region possibly containing an unprotected limb hole as a target region. According to the scheme, the information of the non-protected edge hole in the construction area can be obtained based on the first image of the construction area, so that construction management personnel can master the protection state of the edge hole in real time so as to handle the edge hole with potential safety hazards in time; in addition, according to the scheme, the protection state of the edge hole does not need to be manually inspected, so that the detection efficiency of the protection state of the edge hole is improved, missing detection caused by human errors in manual inspection can be reduced, and the stability of a detection result of the protection state of the edge hole is improved. Therefore, by adopting the technical scheme provided by the invention, the requirement of timely and efficiently checking the edge hole with the potential safety hazard can be met.

Description

Technical Field

[0001] This application relates to the field of engineering construction safety monitoring technology, specifically to an automatic detection method, system, and electronic equipment for the protection status of openings near edges. Background Technology

[0002] In construction sites, openings near edges are typically high-altitude work areas, posing risks of falls from heights and falling objects. To ensure the safety of personnel and equipment at construction sites, it is necessary not only to install protective devices around these openings but also to regularly inspect the installation status of these devices. Therefore, inspecting the protective status of openings near edges is a key aspect of edge edge protection monitoring.

[0003] Currently, the inspection of edge protection at openings is mostly carried out manually on a regular basis through on-site inspections to identify openings without protective devices, i.e., unprotected openings, and thus eliminate such safety hazards. However, for unprotected openings, manual inspection not only suffers from the problem of delayed detection leading to the inability to rectify safety hazards in a timely manner, but also suffers from high inspection costs due to low inspection efficiency. Summary of the Invention

[0004] To address the aforementioned issues, this application provides an automatic detection method, system, and electronic device for the protection status of edge openings. This enables construction management personnel to monitor the protection status of edge openings in real time, allowing for timely handling of edge openings with safety hazards. Furthermore, it improves both the detection efficiency and the stability of the detection results for edge opening protection status.

[0005] According to a first aspect of this application, an automatic detection method for the protection status of an edge opening is provided, comprising: acquiring a first image of a construction area; processing the first image using a mathematical model to obtain a pixel region that may contain an unprotected edge opening as a target region, wherein the edge opening is an area in the construction site where there is a risk of falling.

[0006] In one implementation of the first aspect, the edge opening is at least one of the following: floor edge, roof edge, balcony edge, elevator edge, foundation pit edge, reserved opening, elevator shaft opening, passageway opening, and stairwell opening.

[0007] In one implementation of the first aspect, the first image is processed using a mathematical model to obtain pixel regions that may contain unprotected openings as target regions. This includes: processing the first image using a first mathematical model to obtain pixel regions that may contain openings and confidence levels of unprotected openings that correspond one-to-one with the pixel regions that may contain openings; if the confidence level of unprotected openings is greater than a first preset threshold, then the pixel regions that may contain openings are set as target regions.

[0008] In one implementation of the first aspect, the first image is processed using a mathematical model to obtain pixel regions that may contain unprotected openings as target regions. This includes: processing the first image using a second mathematical model to obtain pixel regions that may contain openings and the confidence levels of openings that correspond one-to-one with the pixel regions that may contain openings; if the confidence level of the openings is greater than a second preset threshold, the first image is further processed using a third mathematical model to obtain the confidence levels of unprotected openings that correspond one-to-one with the pixel regions that may contain openings; if the confidence level of the unprotected openings is greater than a third preset threshold, the pixel regions that may contain openings are set as target regions.

[0009] According to a first aspect of this application, after processing the first image using a mathematical model to obtain a pixel region that may contain unprotected adjacent openings as a target region, the method further includes: obtaining the location information of the target region to send a warning message.

[0010] In one implementation of the first aspect, the location information of the target area includes at least one of the following: project information, building number information, floor information, and specific location information.

[0011] According to a second aspect of this application, an automatic detection system for the protection status of edge openings is provided. The system includes: an acquisition module for acquiring a first image of a construction area; and a processing module for processing the first image using a mathematical model to acquire pixel areas that may contain unprotected edge openings as target areas, wherein the edge opening is an area in the construction site where there is a risk of falling.

[0012] According to a second aspect of this application, the system further includes: a warning module for acquiring location information of the target area to send a warning message.

[0013] According to a third aspect of this application, an electronic device is provided, comprising a memory and a processor, the memory for storing a computer program, the processor for running the computer program to cause the electronic device to perform an automatic detection method for the protection status of an edge opening as provided in the first aspect of this application.

[0014] According to a fourth aspect of this application, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements an automatic detection method for the protection status of an edge opening as provided in the first aspect of this application.

[0015] According to a fifth aspect of this application, a computer program product is provided, the computer program product including instructions that, when executed by a processor of an electronic device provided in a third aspect of this application, enable the electronic device to implement an automatic detection method for the protection status of an edge opening as provided in a first aspect of this application.

[0016] This application provides an automatic detection method, system, and electronic device for the protection status of edge openings. The automatic detection method can acquire information on unprotected edge openings in the construction area based on a first image of the construction area. This allows construction managers to monitor the protection status of edge openings in real time and address potential safety hazards promptly. Furthermore, this solution eliminates the need for manual inspection of edge opening protection status, thus improving detection efficiency and reducing missed detections due to human error during manual inspections, thereby enhancing the stability of the detection results. Therefore, the technical solution provided in this application can meet the need for timely and efficient investigation of edge openings with potential safety hazards. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 The diagram shown is a flowchart illustrating an automatic detection method for the protection status of an opening near an edge, according to an embodiment of this application.

[0019] Figure 2 The diagram shown is a flowchart illustrating a method for obtaining an unprotected edge opening according to an embodiment of this application.

[0020] Figure 3 The diagram shown is a flowchart illustrating a method for obtaining an unprotected edge opening according to another embodiment of this application.

[0021] Figure 4 The diagram shown is an automatic detection system for the protection status of an opening near an edge, according to an embodiment of this application.

[0022] Figure 5The diagram shown is a block diagram of an exemplary electronic device provided in an embodiment of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0024] The embodiments of this application can be applied to the scenario of automatically identifying unprotected edge openings in the construction area through images collected in real time in the construction area. For ease of understanding, the edge openings mentioned in the embodiments of this application will be described in detail first.

[0025] Edge openings refer to the edges created during construction work, either by excavation or construction at ground level or at a height. Edges typically include building edges, roof edges, balcony edges, elevator shaft edges, and foundation pit edges; openings typically include reserved openings, elevator shaft openings, passageway openings, and stairwell openings. Edge openings are among the most common locations for fall accidents on construction sites. If protective measures are inadequate, workers may easily fall through these openings, as may items on the construction site, causing serious injuries or fatalities. This can also lead to project delays, increased costs, and damage to the company's reputation. Therefore, to ensure the safety of personnel and equipment on construction sites, it is essential not only to install protective devices around edge openings but also to regularly inspect the installation status of these devices.

[0026] In the embodiments of this application, the edge opening is at least one of the following: floor edge, roof edge, balcony edge, elevator edge, foundation pit edge, reserved opening, elevator shaft opening, passageway opening, and staircase opening.

[0027] Figure 1 The diagram shown is a flowchart illustrating an automatic detection method for the protection status of an adjacent opening according to an embodiment of this application. This method is executed by an automatic detection system (e.g., a server) for detecting the protection status of adjacent openings. Figure 1 As shown, the method may include the following steps S110 to S120:

[0028] Step S110: Obtain the first image of the construction area.

[0029] The construction area is the area where it is necessary to detect whether there are any unprotected openings at the edge. The first image is obtained by periodically collecting images of the construction area using an image acquisition device. The first image can be one or more images of the construction area, and the number is not specifically limited in this application.

[0030] It should be understood that the acquisition cycle of the first image can be determined according to the actual needs of the construction area. This application embodiment does not specifically limit the acquisition cycle of the first image. Specifically, it can be acquired once a day, for example, every morning before the start of construction to ensure that the safety protection status of the edge opening is qualified before the start of construction; or it can be acquired multiple times a day, for example, once each in the morning, noon and evening to increase the acquisition density and thus strengthen the detection of the edge opening protection status, so as to better ensure the safety of construction personnel.

[0031] It should be understood that the selection of image acquisition equipment can also be determined based on the actual needs of the construction area. This application embodiment does not specifically limit the acquisition cycle of the first image.

[0032] In one embodiment, the image acquisition device may be an AI measurement and monitoring panoramic camera. This camera has an image acquisition module for acquiring images of the construction area and a processing module for further processing of the acquired first image of the construction area. Exemplarily, the image acquisition module may consist of one or more cameras, and the processing module may be one or more processors. The image acquisition module and the processing module may be integrated into a single physical device for easy installation, or they may exist separately in different physical devices to flexibly adapt to various construction areas and thus obtain more powerful camera and processing capabilities.

[0033] In another embodiment, the image acquisition device may also include only an image acquisition module. The first image obtained by the image acquisition module can be sent to a corresponding server for subsequent image processing. In this case, the processing module can be located in the server.

[0034] Furthermore, the first image should be able to cover the entire construction area in order to detect the protection status of the openings at the edges of the entire construction area.

[0035] In one embodiment, the image acquisition device may include a pan-tilt unit. When the construction area is large, the pan-tilt unit can be rotated so that the camera can be aimed at different areas of the construction area to acquire images separately, thereby enabling the first image to cover the entire construction area.

[0036] For example, the image acquisition device can be fixed at a preset location within the construction area. For instance, the preset location could be the tower crane cab, or the top of a completed building within the construction area, to facilitate image acquisition of the entire construction area by the image acquisition device.

[0037] In one embodiment, images of multiple different regions can be stitched together to form a first image, or images of each region can be used as the first image.

[0038] In another embodiment, the image acquisition device may not include a pan-tilt unit. When the construction area is large, the number of image acquisition devices can be increased. Each image acquisition device can be aimed at a certain area of ​​the construction area to acquire images, so that the first image acquired by multiple image acquisition devices can cover the entire construction area.

[0039] In another embodiment, the entire construction area can be scanned periodically, and the automatic detection method of this embodiment can be executed in each cycle.

[0040] Step S120: Process the first image using a mathematical model to obtain pixel regions that may contain unprotected openings at the edges as target regions, wherein the openings at the edges are areas in the construction site where there is a risk of falling.

[0041] The mathematical model can be one or more trained deep learning-based convolutional neural network models, such as object detection models or classification models. The mathematical model can be pre-trained on a dataset containing a large number of different image samples, or it can be pre-trained on a dataset containing a large number of different image samples and then fine-tuned on a task-specific dataset. The trained mathematical model can detect and / or classify pixel regions that may contain unprotected adjacent openings from the input first image.

[0042] For example, a dataset containing a large number of different image samples includes images of at least one of the following types: openings with incomplete but adequate protective devices; openings with incomplete but inadequate protective devices; openings with incomplete but no protective devices; openings with complete and adequate protective devices; openings with complete but inadequate protective devices; openings with complete but inadequate protective devices; openings without any protective devices; openings without openings but with adequate protective devices; and openings without openings but with inadequate protective devices. Inadequate protective devices refer to devices that are present but insufficient to eliminate safety hazards, such as protective devices with a height lower than industry standards, protective devices with a width smaller than the width of the opening, or protective devices with obvious gaps. It should be noted that openings with inadequate protective devices and openings without any protective devices are both considered unprotected openings.

[0043] The mathematical model, trained on a dataset containing a large number of different image samples, learns a large number of pre-defined features that include unprotected openings. Therefore, in practical applications, it can quickly and accurately identify similar or related image content, thereby improving the accuracy and efficiency of detection and / or classification.

[0044] After identifying pixel areas that may contain unprotected openings at adjacent edges as target areas, it is necessary to promptly notify the relevant project site safety officer of these target areas with safety hazards so that the safety officer can handle them in a timely manner. Therefore, optional measures include... Figure 1 As shown in the embodiments of this application, the automatic detection method for the protection status of near openings may further include the following steps:

[0045] Step S130: Obtain the location information of the target area to send a warning message.

[0046] It should be noted that the automatic detection method for the protection status of the edge opening provided in this application embodiment can obtain the positioning information of the target area based on the first image.

[0047] In one embodiment, the location information of the target area includes at least one of the following: project information, building number information, floor information, and specific location information, so that the system can push the target area with safety hazards to the corresponding project construction site safety officer, so that the corresponding project construction site safety officer can handle it in a timely manner, thereby improving the efficiency of project management.

[0048] In another embodiment, the location information of the target area can also be the longitude, latitude, and altitude of the target area calculated based on the distance information measured by the laser rangefinder.

[0049] In another embodiment, when the image acquisition device does not include a pan-tilt unit, since multiple image acquisition devices are needed to capture images of different areas of the construction area so that the first image can cover the entire construction area, the location information of the target area can include the name of the image acquisition device. This also allows the system to push the target area with safety hazards to the corresponding project construction site safety officer, so that the corresponding project construction site safety officer can quickly locate the area with safety hazards based on the name of the image acquisition device and make timely rectifications, thereby improving the efficiency of project management.

[0050] This application provides an automatic detection method, system, and electronic device for the protection status of edge openings. The automatic detection method can acquire information on unprotected edge openings in the construction area based on a first image of the construction area. This allows construction managers to monitor the protection status of edge openings in real time and address potential safety hazards promptly. Furthermore, this solution eliminates the need for manual inspection of edge opening protection status, thus improving detection efficiency and reducing missed detections due to human error during manual inspections, thereby enhancing the stability of the detection results. Therefore, the technical solution provided in this application can meet the need for timely and efficient investigation of edge openings with potential safety hazards.

[0051] Figure 2 The diagram shown is a flowchart illustrating a method for obtaining an unprotected edge opening according to an embodiment of this application.

[0052] In this embodiment, such as Figure 2 As shown, step S120 above may include the following steps:

[0053] Step S210: Process the first image using the first mathematical model to obtain the confidence of pixel regions that may contain edge openings and the unprotected edge openings that correspond one-to-one with the pixel regions that may contain edge openings.

[0054] The first mathematical model can be an object detection model, such as YOLOv8. YOLO (You Only Look Once) is a series of groundbreaking real-time object detection models, and YOLOv8 is an iterative version of the YOLO series, which has cutting-edge performance in terms of accuracy and speed in image detection; another example is EfficientDet; preferably, the first mathematical model adopts the YOLOv8 model.

[0055] The input to the first mathematical model is the first image. The first image can be input sequentially or in batches. This application embodiment does not limit the specific input method of the first image.

[0056] In one embodiment, the first mathematical model may have two output parameters: the first output parameter is the pixel region that may contain an adjacent opening, and the second output parameter is the confidence level of an unprotected adjacent opening that corresponds one-to-one with the pixel region that may contain an adjacent opening. Both output parameters can be used together to determine the target region.

[0057] In another embodiment, the first mathematical model can have three output parameters. The first output parameter is the pixel region that may contain edge openings; the second output parameter is the confidence level of unprotected edge openings corresponding one-to-one with the pixel regions that may contain edge openings; and the third output parameter is the confidence level of protected edge openings corresponding one-to-one with the pixel regions that may contain edge openings. The third output parameter can be used together with the first and second output parameters as parameters for judging the target area, or it can have other uses. For example, the confidence level of protected edge openings can be used alone or together with the first and second output parameters in the subsequent safety protection level evaluation of the project, so as to give timely rewards to construction teams with higher safety protection levels; the confidence level of protected edge openings can also be used alone or together with the first and second output parameters to draw a curve of the safety protection level of a building over multiple days, so as to improve the safety protection in the future.

[0058] Step S220: If the confidence level of an unprotected edge opening is greater than the first preset threshold, then set the pixel region that may contain the edge opening as the target region.

[0059] The first preset threshold is a pre-set value, which can be set based on industry experience or based on the pre-training process of the first mathematical model in step S210. For example, the range of the first preset threshold can be [0.5 to 0.9]. Preferably, the first preset threshold can be set to 0.5.

[0060] Taking a first preset threshold of 0.5 as an example, and combining it with step S210, in one example, the pixel regions that may contain edge openings in the output of step S210 are "20, 30, 100, 300". The confidence level of the unprotected edge openings corresponding one-to-one with the pixel regions that may contain edge openings is 0.6, where 20 and 30 represent the upper left pixel coordinates of the pixel regions, and 100 and 300 represent the pixel widths of the regions. Since the confidence level of the unprotected edge openings corresponding one-to-one with these pixel regions is 0.6, which is greater than the first preset threshold, this indicates that the pixel region may contain unprotected edge openings. Therefore, the pixel region that may contain edge openings is set as the target region.

[0061] In one example, in the output of step S210, it is still assumed that the first preset threshold is set to 0.5, and the pixel regions that may contain edge openings are "20, 30, 100, 300". At this time, the confidence level of the unprotected edge openings corresponding one-to-one with the pixel regions that may contain edge openings is 0.2. Since the confidence level of the unprotected edge openings corresponding one-to-one with this pixel region is 0.2, which is less than the first preset threshold, the pixel region that may contain edge openings is not set as the target region.

[0062] exist Figure 2 In the illustrated implementation, a first image of the construction area is first input into a first mathematical model. Then, the output of the first mathematical model is evaluated. Finally, pixel regions in the output that meet preset conditions are set as target regions, i.e., pixel regions that may contain unprotected openings at the edges. This solution can identify pixel regions in the first image that may contain unprotected openings at the edges without manual intervention, thereby improving the detection efficiency of the protection status of openings at the edges and reducing missed detections due to human error during manual inspections, thus improving the stability of the detection results.

[0063] Figure 3 The diagram shown is a flowchart illustrating a method for obtaining an unprotected edge opening according to another embodiment of this application.

[0064] In this embodiment, such as Figure 3 As shown, step S120 above may include the following steps:

[0065] Step S310: Process the first image using the second mathematical model to obtain the pixel regions that may contain adjacent openings and the confidence levels of the adjacent openings that correspond one-to-one with the pixel regions that may contain adjacent openings.

[0066] Specifically, the second mathematical model adopts an object detection model, such as YOLOv8 or EfficientDet; preferably, the second mathematical model adopts the YOLOv8 model.

[0067] The input to the second mathematical model is the first image. The first image can be input sequentially or in batches. This application embodiment does not limit the specific input method of the first image.

[0068] In one embodiment, the second mathematical model has two output parameters: the first output parameter is the pixel region that may contain the adjacent hole, and the second output parameter is the confidence level of the adjacent hole that corresponds one-to-one with the pixel region that may contain the adjacent hole.

[0069] Step S320: If the confidence level of the edge opening is greater than the second preset threshold, the first image is reprocessed using the third mathematical model to obtain the confidence level of the unprotected edge opening that corresponds one-to-one with the pixel regions that may contain the edge opening.

[0070] The second preset threshold is a pre-set value, which can be set based on industry experience or based on the pre-training process of the second mathematical model in step S310; for example, the range of the second preset threshold can be [0.5~0.9], and preferably, the second preset threshold can be set to 0.5.

[0071] Specifically, the third mathematical model adopts a classification model, such as RESNET50 or RESNET18; preferably, the third mathematical model adopts the RESNET50 model.

[0072] The input to the third mathematical model is all or part of the pixel region of the first image. Specifically, taking a second preset threshold of 0.5 as an example, combined with step S310, if the output result obtained after inputting the first image into the second mathematical model contains pixel regions that may contain adjacent holes, such as "20, 30, 100, 300", and the confidence level of the adjacent holes corresponding one-to-one with the pixel regions that may contain adjacent holes is 0.6, then the confidence level of 0.6 is greater than the second preset threshold of 0.5. At this time, either the entire first image can be input into the third mathematical model, or the first image located at "20, 30, 300" can be used. The pixel region “100, 300” is input into the third mathematical model; for example, still taking the second preset threshold as 0.5, if the output result obtained after the first image is input into the second mathematical model contains pixel regions that may contain adjacent holes, such as “20, 30, 100, 300”, and the confidence level of the adjacent holes corresponding one-to-one with the pixel regions that may contain adjacent holes is 0.3, then the confidence level value of 0.3 is less than the second preset threshold of 0.5. At this time, the entire first image or the pixel region of the first image located in “20, 30, 100, 300” will not be used as input to the third mathematical model.

[0073] In one embodiment, the third mathematical model may have an output parameter: the confidence level of an unprotected edge opening that corresponds one-to-one with a pixel region that may contain an edge opening. The value of this parameter can be used in subsequent steps to determine the target region.

[0074] In another embodiment, the third mathematical model can have two output parameters. The first output parameter is the confidence level of protected openings corresponding one-to-one with pixel regions that may contain openings, and the second output parameter is the confidence level of unprotected openings corresponding one-to-one with pixel regions that may contain openings. The first and second output parameters are used together as parameters for determining the target area. The first output parameter can also have other uses. For example, the confidence level of protected openings can be used alone or in conjunction with the second output parameter in subsequent safety protection level assessments of the project, so as to promptly reward construction teams with higher safety protection levels. The confidence level of protected openings can also be used alone or in conjunction with the second output parameter to plot a curve of the safety protection level of a building over multiple days, so as to improve subsequent safety protection measures.

[0075] Step S330: If the confidence level of an unprotected edge opening is greater than the third preset threshold, then set the pixel area that may contain the edge opening as the target area.

[0076] The third preset threshold is a pre-set value, which can be set based on industry experience or based on the pre-training process of the third mathematical model in step S320. For example, the range of the third preset threshold can be [0.5~0.9], and preferably, the third preset threshold can be set to 0.6.

[0077] In one embodiment, taking the third preset threshold set to 0.6 as an example, combined with the aforementioned step S320, if the confidence level of the unprotected edge openings corresponding one-to-one with the pixel regions "20, 30, 100, 300" that may contain edge openings in the output result of step S320 is 0.3, then since 0.3 is less than the third preset threshold of 0.6, this means that the pixel regions "20, 30, 100, 300" cannot be used as target regions.

[0078] In another embodiment, taking the third preset threshold set to 0.6 as an example, if the confidence level of the unprotected edge openings corresponding one-to-one with the pixel regions "20, 30, 100, 300" that may contain edge openings in the output result of step S320 is 0.8, then since 0.8 is greater than the fourth preset threshold of 0.6, this means that the pixel regions "20, 30, 100, 300" can be used as target regions.

[0079] exist Figure 3In the illustrated implementation, a first image of the construction area is first input into a second mathematical model. The output of the second mathematical model is then evaluated. If the output meets preset conditions, the first image is input into a third mathematical model to obtain the target area, i.e., the pixel area that may contain unprotected openings. This scheme can identify pixel areas in the first image that may contain unprotected openings without manual intervention, thereby improving the detection efficiency of the protection status of openings and reducing missed detections due to human error during manual inspections, thus improving the stability of the detection results. Furthermore, compared with... Figure 2 Compared to the implementation shown, this scheme first uses a second mathematical model to screen the first image to identify images that may contain pixel regions of adjacent openings. Then, it only needs to input the first images that may contain pixel regions of adjacent openings into the third mathematical model, thereby greatly reducing the input of the third mathematical model and improving the detection efficiency of the third mathematical model, thus further improving the detection efficiency of the protection status of adjacent openings.

[0080] The above is an introduction to the automatic detection method for the protection status of edge openings provided in the embodiments of this application. This method can be used by... Figure 4 The automatic detection system for the protection status of the edge opening shown is being implemented.

[0081] Figure 4 The diagram shown is an automatic detection system for the protection status of an edge opening according to an embodiment of this application. Figure 4 As shown, the system 400 includes:

[0082] The acquisition module 410 is used to acquire the first image of the construction area;

[0083] The processing module 420 is used to process the first image using a mathematical model to obtain pixel areas that may contain unprotected openings at the edges as target areas, where the openings at the edges are areas in the construction site where there is a risk of falling.

[0084] Furthermore, as one implementation, when the processing module 420 processes the first image using a mathematical model to obtain a pixel region that may contain unprotected adjacent openings as a target region, the processing module 420 is used to:

[0085] The first image is processed using the first mathematical model to obtain the pixel regions that may contain edge openings and the confidence levels of unprotected edge openings that correspond one-to-one with the pixel regions that may contain edge openings.

[0086] If the confidence level of an unprotected edge opening is greater than the first preset threshold, then the pixel region that may contain the edge opening is set as the target region.

[0087] Furthermore, as another implementation, when the processing module 420 processes the first image using a mathematical model to obtain a pixel region that may contain unprotected adjacent openings as a target region, the processing module 420 is used to:

[0088] The first image is processed using a second mathematical model to obtain the pixel regions that may contain adjacent openings and the confidence levels of the adjacent openings that correspond one-to-one with the pixel regions that may contain adjacent openings.

[0089] If the confidence level of the edge opening is greater than the second preset threshold, the first image is reprocessed using the third mathematical model to obtain the confidence level of the unprotected edge opening that corresponds one-to-one with the pixel regions that may contain the edge opening.

[0090] If the confidence level of an unprotected edge opening is greater than the third preset threshold, then the pixel area that may contain the edge opening is set as the target area.

[0091] Optionally, the above system 400 also includes:

[0092] Warning module 430 is used to obtain the location information of the target area in order to send a warning message.

[0093] When the warning module 430 is used to obtain the location information of the target area to send a warning message, in one embodiment, the location information of the target area includes at least one of the following: project information, building number information, floor information, and specific location information, so that the system can push the target area with safety hazards to the corresponding project construction site safety officer, so that the corresponding project construction site safety officer can make timely rectifications, thereby improving the efficiency of project management.

[0094] When the warning module 430 is used to obtain the location information of the target area to send a warning message, in another embodiment, when the image acquisition device does not include a pan-tilt unit, since multiple image acquisition devices are needed to capture images of different areas of the construction area so that the first image can include the entire construction area, the location information of the target area can include the name of the image acquisition device. This also allows the system to push the target area with safety hazards to the corresponding project construction site safety officer, so that the corresponding project construction site safety officer can quickly locate the area with safety hazards based on the name of the image acquisition device and make timely rectifications, thereby improving the efficiency of project management.

[0095] It should be understood that, for the sake of convenience and brevity, the specific working scenarios, processes, effects, and other details of each module in the above system 400 can be referred to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0096] This application also provides an electronic device. Figure 5 The diagram shown is a block diagram of an exemplary electronic device provided in an embodiment of this application. (Refer to...) Figure 5 The electronic device 500 includes a memory 510 and a processor 520. The memory 510 stores a computer program, and the processor 520 runs the computer program to enable the electronic device 500 to implement the automatic detection method for the protection status of the edge opening provided in any of the foregoing embodiments.

[0097] Electronic device 500 may also include a power supply component configured to perform power management of electronic device 500, a wired or wireless network interface configured to connect electronic device 500 to a network, and an input / output (I / O) interface. Electronic device 500 can operate based on an operating system stored in memory 510, such as Windows Server™, Mac OSX™, Unix™, Linux™, FreeBSD™, or similar.

[0098] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program in the storage medium is executed by the processor 520 of the electronic device 500, the electronic device 500 is able to implement the automatic detection method for the protection status of the edge opening provided in any of the foregoing embodiments.

[0099] This application also provides a computer program product, which includes instructions that, when executed by the processor 520 of the electronic device 500, enable the electronic device 500 to implement the automatic detection method for the protection status of the edge opening provided in any of the foregoing embodiments.

[0100] The prompting method in this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in this application are performed, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, network equipment, user equipment, core network equipment, OAM, or other programmable device.

[0101] The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device, a core network device, an OAM (Operational Information Management) system, or other programmable devices.

[0102] The computer program or instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions may be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium may be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a digital video optical disc; or a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0103] It is understood that the specific examples provided in this application are only intended to help those skilled in the art better understand the embodiments of this application, and are not intended to limit the scope of the invention.

[0104] It is understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0105] It is understood that the various embodiments described in this application can be implemented individually or in combination, and the embodiments of this application are not limited in this respect.

[0106] Unless otherwise stated, all technical and scientific terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The term "and / or" as used in this application includes any and all combinations of one or more of the associated listed items. The singular forms "a," "the," and "the" as used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0107] It is understood that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0108] It is understood that the memory in the embodiments of this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Specifically, non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM). It should be noted that the memory in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0109] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0110] For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be indirect couplings or communication connections between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0111] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0113] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] The above description is merely a specific embodiment of this application, but the scope of protection of this invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. An automatic detection method for the protection status of an opening near an edge, characterized in that, include: Obtain the first image of the construction area; The first image is processed using a mathematical model to obtain pixel regions that may contain unprotected openings at the edges as target regions, wherein the openings at the edges are areas in the construction site where there is a risk of falling.

2. The method according to claim 1, characterized in that, The edge opening is at least one of the following: floor edge, roof edge, balcony edge, elevator edge, foundation pit edge, reserved opening, elevator shaft opening, passageway opening, and stairwell opening.

3. The method according to claim 1, characterized in that, The step of processing the first image using a mathematical model to obtain pixel regions that may contain unprotected openings at adjacent edges as target regions includes: The first image is processed using a first mathematical model to obtain the pixel regions that may contain edge openings and the confidence levels of unprotected edge openings that correspond one-to-one with the pixel regions that may contain edge openings. If the confidence level of the unprotected edge opening is greater than a first preset threshold, then the pixel region that may contain the edge opening is set as the target region.

4. The method according to claim 1, characterized in that, The step of processing the first image using a mathematical model to obtain pixel regions that may contain unprotected openings at adjacent edges as target regions includes: The first image is processed using a second mathematical model to obtain pixel regions that may contain adjacent openings and the confidence levels of adjacent openings that correspond one-to-one with the pixel regions that may contain adjacent openings. If the confidence level of the edge opening is greater than the second preset threshold, the first image is reprocessed using the third mathematical model to obtain the confidence level of the unprotected edge opening that corresponds one-to-one with the pixel regions that may contain the edge opening. If the confidence level of the unprotected edge opening is greater than the third preset threshold, then the pixel region that may contain the edge opening is set as the target region.

5. The method according to any one of claims 1 to 4, characterized in that, After processing the first image using a mathematical model to obtain pixel regions that may contain unprotected openings as target regions, the method further includes: obtaining the location information of the target regions to send warning information.

6. The method according to claim 5, characterized in that, The location information of the target area includes at least one of the following: project information, building number information, floor information, and specific location information.

7. An automatic detection system for the protection status of openings near edges, characterized in that, include: The acquisition module is used to acquire the first image of the construction area; The processing module is used to process the first image using a mathematical model to obtain pixel areas that may contain unprotected openings at the edges as target areas, wherein the openings at the edges are areas in the construction site where there is a risk of falling.

8. The system according to claim 7, characterized in that, The system also includes: The warning module is used to obtain the location information of the target area in order to send a warning message.

9. An electronic device, characterized in that, include: Memory; A processor, wherein the memory is used to store a computer program, the processor running the computer program to cause the electronic device to perform an automatic detection method for the protection status of an edge opening as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements an automatic detection method for the protection status of the edge opening as described in any one of claims 1 to 6.

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