CN112532927A - Intelligent safety management and control system for construction site - Google Patents
Intelligent safety management and control system for construction site Download PDFInfo
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- CN112532927A CN112532927A CN202011282913.9A CN202011282913A CN112532927A CN 112532927 A CN112532927 A CN 112532927A CN 202011282913 A CN202011282913 A CN 202011282913A CN 112532927 A CN112532927 A CN 112532927A
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- 238000010276 construction Methods 0.000 title claims abstract description 39
- 238000001514 detection method Methods 0.000 claims abstract description 15
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- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 4
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- 238000010586 diagram Methods 0.000 description 3
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
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Abstract
The invention provides an intelligent safety management and control system for a construction site, which comprises a video acquisition module, a safety helmet feature identification module, a cloud server, an alarm device module, a video display module, a video storage module and an external terminal, wherein the video acquisition module is connected with the cloud server through the safety helmet feature identification module, the cloud server is also connected with the alarm device module and the external terminal, the safety helmet feature identification module can intelligently identify and detect whether a person entering a construction site wears a safety helmet or not, the alarm device module can send alarm information to the external terminal according to the detection information of the safety helmet feature identification module, and the external terminal is also connected with the video display module and the video storage module. The invention automatically detects whether a constructor wears a safety helmet or not based on an image recognition technology by using an artificial intelligence technology as a basis, and realizes the intelligent management of safety production without manual intervention.
Description
Technical Field
The invention relates to the technical field of access control systems, in particular to an intelligent safety control system for a construction site.
Background
The production operation environment of the transformer substation infrastructure site is complex, the personnel are complex, multiple kinds of cross operation are performed, the number of cooperation parties is large, and the characteristics of scattered construction sites, difficult construction site management and the like are presented. The safety helmet can protect the head of a human body from being injured by falling objects and other specific factors, and the safety helmet must be worn on a production site of a construction site, so that the safety helmet can protect the safety of the human body. The construction site management clearly stipulates that anyone enters a transformer substation production site and must wear a safety helmet, however, often, when the staff enters the construction site, the safety helmet is not worn, the safety consciousness is weak, the supervision personnel cannot supervise the whole site, and great potential safety hazards exist. Most transformer substation construction still depends on a management mode of purely manual inspection or manual work as a main mode and video monitoring as an auxiliary mode, but the management mode can not meet the actual requirement.
Under the existing site safety supervision system, supervisors cannot supervise the whole process of each work site due to factors such as meetings, temporary work tasks, traffic vehicles and the like; since the roads of the infrastructure site are far and the positions are scattered, great difficulty exists in the supervision range, supervision time and times, timely and effective supervision cannot be guaranteed, and a dead zone of safety supervision is easily caused.
There is a need for a novel field safety management and control system which can solve the above problems.
Disclosure of Invention
The invention provides an intelligent safety management and control system for a construction site, which improves the safety standardized management level of a capital construction project site by carrying out technical transformation on the existing construction monitoring and management equipment.
In order to solve the technical problems, the invention specifically adopts the following technical scheme:
an intelligent safety management and control system for a construction site comprises a video acquisition module, a safety helmet characteristic identification module, a cloud server, an alarm device module, a video display module, a video storage module and an external terminal, the video acquisition module is connected with a cloud server through a safety helmet characteristic identification module, the cloud server is also connected with an alarm device module and an external terminal, the safety helmet characteristic identification module can intelligently identify and detect whether a person entering a construction site wears a safety helmet or not, the alarm device module can send alarm information to an external terminal according to the detection information of the safety helmet characteristic identification module, the external terminal is further connected with a video display module and a video storage module, the video display module can display image information collected by the video collection module, and the video storage module can store the image information collected by the video collection module.
Preferably, the video acquisition module comprises a plurality of groups of cameras and sensors, and the plurality of groups of cameras and sensors are respectively distributed and controlled at different positions of the area to be detected.
Preferably, the safety helmet feature identification module comprises an image preprocessing module, an image optimization identification module and a dynamic detection module;
the image preprocessing module can store remark marks of the safety helmet under different light rays and different background environments according to styles, types, categories and colors, and perform corresponding feature representation and feature extraction;
the image optimization and identification module can identify and analyze image data aiming at the environment background difference, which is greatly influenced and comprises factors such as shielding, multi-view angle, illumination, low resolution, dynamic background and the like in the multi-dimensional visual field;
the dynamic detection module can adopt deep learning to train and predict the model to the image data of the collected personnel, judge whether the constructor wears the safety helmet according to the regulation, and can shoot and send to the alarm device module in real time to the personnel who do not wear the safety helmet.
Preferably, the cloud server, the alarm device module, the video display module, the video storage module and the external terminal are all connected through the internet.
Preferably, external terminal includes web end and APP end, the web end sets up in building site computer lab, and the APP end installation sets up on mobile device such as cell-phone, web end and APP end homoenergetic receive the warning message that alarm device module sent in real time.
Preferably, the safety helmet feature recognition module is further connected with an access control system, when the safety helmet feature recognition module recognizes that an entering person judges that the safety helmet is worn, the access control system is opened to pass, and when the safety helmet feature recognition module recognizes that the entering person judges that the safety helmet is not worn, the access control system is prohibited to pass.
Compared with the prior art, the invention has the following beneficial effects:
the front end of the invention is provided with a video acquisition module, a safety helmet characteristic identification module and a cloud server are arranged in a site machine room of a construction site, and the server and the video acquisition module are in the same local area network, access to a video stream of a camera through an RTSP protocol, and acquire, analyze and alarm in real time.
The invention automatically detects whether a constructor wears a safety helmet or not based on an image recognition technology by using an artificial intelligence technology as a basis, and realizes the intelligent management of safety production without manual intervention. Through installing all kinds of monitoring devices at the construction site, establish intelligent monitoring and guard against system, effectively compensate the defect of traditional method and technique in the supervision, accomplish early warning in advance really, the normality detects in the past, the time standard management. The information management is achieved for the safety production of the construction site, the safety of operating personnel is guaranteed, and the safety production management is improved.
1. The invention can be connected with an access control system by deploying helmet wearing detection, and ensures that a worker can open the access control to enter a construction site only by wearing the helmet.
2. The invention has effective safety early warning function on the construction site, thereby further ensuring the personal safety of the work; the investment of manual safety inspection is reduced, the reliability of safety early warning is improved, and the management concept of personnel reduction and efficiency improvement is met.
3. Theories and technologies such as image processing and machine learning are applied, intelligent management of the transformer substation construction site is achieved, management efficiency is improved, and safety of constructors is guaranteed.
4. The engineering field wearing identification analysis technology adopted by the invention can reduce the human capital of enterprises, thereby improving the construction progress and reducing unnecessary economic loss.
In conclusion, the structured feature value extraction is carried out on the field operation video image of the implementing personnel to form value video data accumulation, so that the scene application functions of analyzing and accumulating in advance, tracking in real time in the process, extracting clues after the process and the like are provided for the field operation safety risk scheme, and the capability of managing and controlling the field operation safety risk of the implementing personnel is improved.
Drawings
FIG. 1 is a schematic diagram of the module connection of the present invention;
FIG. 2 is a diagram of an identification message route according to the present invention;
FIG. 3 is a schematic view of a shooting range of the video capture module of the present invention;
FIG. 4 is a schematic diagram of left image and right image acquisition information coordinates according to the present invention;
Detailed Description
The details of the present invention will be described below with reference to the accompanying drawings and examples.
As shown in fig. 1-4, the present embodiment provides an intelligent safety management and control system for a construction site, which includes a video acquisition module, a helmet feature identification module, a cloud server, an alarm device module, a video display module, a video storage module, and an external terminal, the video acquisition module is connected with a cloud server through a safety helmet characteristic identification module, the cloud server is also connected with an alarm device module and an external terminal, the safety helmet characteristic identification module can intelligently identify and detect whether a person entering a construction site wears a safety helmet or not, the alarm device module can send alarm information to an external terminal according to the detection information of the safety helmet characteristic identification module, the external terminal is further connected with a video display module and a video storage module, the video display module can display image information collected by the video collection module, and the video storage module can store the image information collected by the video collection module.
Furthermore, the video acquisition module comprises a plurality of groups of cameras and sensors, and the plurality of groups of cameras and sensors are respectively distributed and controlled to be arranged at different positions of the area to be detected.
The invention establishes a multi-view (including a single-vision model and a double-vision model depending on scenes) vision model and an image technology to realize the monitoring of the normalization of the construction field personnel and the identification function of the personnel safety helmet, and can improve the identification rate of the construction personnel safety helmet. The multi-view vision model is schematically illustrated in figure 3,
as shown in fig. 4, the base line distance B is equal to the distance between the projection centers of the two cameras; the camera focal length is f. Setting two cameras to watch the same characteristic point (x) of space object at the same timec,yc,zc) Images of point P are acquired on the "left eye" and "right eye", respectively, with their image coordinates being P, respectivelyleft＝(Xleft,Yleft)，Pright＝(Xright,Yright). The conversion according to the geometric relationship can obtain: any point on the left camera image plane can determine the three-dimensional coordinates of the point as long as the corresponding matching point can be found on the right camera image plane.
A work area detection algorithm comprising the steps of:
(1) considering the situation that the variability of actual shooting visual angles and multiple people violate construction behaviors simultaneously occur, an integrated detection algorithm with higher robustness is researched on the basis of a general intelligent image recognition analysis algorithm. Aiming at similar behavior characteristics of the safety helmet without wearing, the same network model is adopted for training and detecting, and the integration level of the algorithm is improved. The subject uses the Vibe foreground algorithm to detect the work area. The Vibe algorithm is a foreground detection algorithm based on background updating, and the principle is that a sample set of pixel points is established by extracting pixel values around the pixel points (x, y) and previous pixel values, then the pixel values at the other frame (x, y) are compared with the pixel values in the sample set, if the distance between the pixel values and the pixel values in the sample set is greater than a certain threshold value, the pixel points are regarded as foreground pixel points, and if not, the pixel points are regarded as background pixel points.
(2) The Vibe algorithm uses neighborhood pixels to create a background model, detects the foreground by comparing the background model with the current input pixel values, and can be subdivided into three steps:
1): and initializing a background model of each pixel point in the single-frame image. It is assumed that the pixel values of each pixel and its neighborhood have a similar distribution in the spatial domain. Based on this assumption, each pixel model can be represented by pixels in its neighborhood. In order to ensure that the background model conforms to the statistical rules, the range of the neighborhood is large enough. When the first frame image is input, i.e. when t is 0, the background model of the pixel is:
BKM 0＝f0(xi,yi)|((xi,yi))∈NG(x,y) (1-1)
where NG (x, y) represents spatially adjacent pixel values, and f 0(x j, y j) represents the pixel value of the current point. In the process of initializing N times, the possible number of times that the pixel point in NG (x, y) is selected is L ═ 1,2,3, …, N.
2): and carrying out foreground object segmentation operation on the subsequent image sequence. When t is equal to k, the background model of the pixel point is that the pixel value is. Whether the pixel value is foreground is judged as follows.
Where superscript k is a random value; t is a preset threshold. When f k (x, y) satisfies the background judgment condition, we consider the pixel point as background, otherwise, it is foreground.
3): and (3) updating the background model. Updates to the Vibe algorithm are random in both time and space.
Randomness in time: one background model is randomly selected from the N background models and is used as an image PG, and the x position of the image PG and pixels in the eight neighborhood thereof are shown as follows. When we get a new frame of image Pt, if the pixel Pt (x) corresponding to the x position in the image Pt is determined as the background, PG needs to be updated. This process of decimation represents randomness in time.
Spatial randomness: one pixel PG (r) is randomly extracted from the eight neighborhoods of PG (x), and PG (r) is replaced by Pt (x), so that the randomness of the model updating space is reflected.
This is an update process, i.e., Pt (x) is used to update P (x) and its eight neighbors. By adopting the eight neighborhood updating method, double images and errors generated by the acquired video fine jitter (camera jitter and target micromotion) can be removed, so that the target detection is more accurate.
In general, the background does not change greatly, so the number of background model updates (Update Num) should be similar. Therefore, the number of updating times (Init Num) of the background of the first frame is used as a comparison value, and the background model is reinitialized according to the following formula, so that misjudgment caused by large-area illumination change can be avoided.
Further, the safety helmet feature identification module comprises an image preprocessing module, a picture optimization identification module and a dynamic detection module;
the image preprocessing module can store remark marks of the safety helmet under different light rays and different background environments according to styles, types, categories and colors, and perform corresponding feature representation and feature extraction;
the image optimization and identification module can identify and analyze image data aiming at the environment background difference, which is greatly influenced and comprises factors such as shielding, multi-view angle, illumination, low resolution, dynamic background and the like in the multi-dimensional visual field;
the dynamic detection module can adopt deep learning to train and predict the model to the image data of the collected personnel, judge whether the constructor wears the safety helmet according to the regulation, and can shoot and send to the alarm device module in real time to the personnel who do not wear the safety helmet.
Furthermore, the cloud server, the alarm device module, the video display module, the video storage module and the external terminal are all connected through the internet.
Further, external terminal includes web end and APP end, the web end sets up in the building site computer lab, and the APP end installation sets up on mobile device such as cell-phone, web end and APP end homoenergetic receive the warning message that alarm device module sent in real time.
Furthermore, the safety helmet feature recognition module is also connected with an access control system, when the safety helmet feature recognition module recognizes that an entering person judges that the safety helmet is worn, the access control system is opened to pass, and when the safety helmet feature recognition module recognizes that the entering person judges that the safety helmet is not worn, the access control system is prohibited to pass.
The front end of the embodiment is designed with a video acquisition module, a safety helmet characteristic identification module and a cloud server are arranged in a site machine room of a construction site, and the server and the video acquisition module are in the same local area network, access to video streams of a camera through an RTSP (real time streaming protocol) protocol, and acquire, analyze and alarm in real time.
The embodiment utilizes the artificial intelligence technology as the basis, and based on the image recognition technology, whether automated inspection constructor wears the safety helmet, need not artificial intervention and realizes the intelligent management of safety in production. Through installing all kinds of monitoring devices at the construction site, establish intelligent monitoring and guard against system, effectively compensate the defect of traditional method and technique in the supervision, accomplish early warning in advance really, the normality detects in the past, the time standard management. The information management is achieved for the safety production of the construction site, the safety of operating personnel is guaranteed, and the safety production management is improved.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
The standard parts used in the invention can be purchased from the market, the special-shaped parts can be customized according to the description of the specification and the description of the attached drawings, the specific connection mode of each part adopts conventional means such as mature bolts, rivets, welding and the like in the prior art, the machines, parts and equipment adopt conventional models in the prior art, and the circuit connection adopts the conventional connection mode in the prior art, so that the detailed description is omitted.
In the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "fixed" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; either directly or through an intermediary, either internally or in any other relationship. The specific meaning of the above terms in the present invention can be understood in specific cases for those skilled in the art.
Claims (6)
1. An intelligent safety management and control system for a construction site is characterized by comprising a video acquisition module, a safety helmet characteristic identification module, a cloud server, an alarm device module, a video display module, a video storage module and an external terminal, the video acquisition module is connected with a cloud server through a safety helmet characteristic identification module, the cloud server is also connected with an alarm device module and an external terminal, the safety helmet characteristic identification module can intelligently identify and detect whether a person entering a construction site wears a safety helmet or not, the alarm device module can send alarm information to an external terminal according to the detection information of the safety helmet characteristic identification module, the external terminal is further connected with a video display module and a video storage module, the video display module can display image information collected by the video collection module, and the video storage module can store the image information collected by the video collection module.
2. The intelligent safety management and control system for the construction site according to claim 1, wherein the video acquisition module comprises cameras and sensors, the cameras and the sensors are in a plurality of groups, the plurality of groups of cameras and the sensors are respectively arranged at different directions, and the intersection of shooting areas of the plurality of groups of cameras and the sensors is an area to be detected.
3. The intelligent safety management and control system for the construction site according to claim 1, wherein the safety helmet feature identification module comprises an image preprocessing module, an image optimization identification module and a dynamic detection module;
the image preprocessing module can store remark marks of the safety helmet under different light rays and different background environments according to styles, types, categories and colors, and perform corresponding feature representation and feature extraction;
the image optimization and identification module can identify and analyze image data aiming at the environment background difference, which is greatly influenced and comprises factors such as shielding, multi-view angle, illumination, low resolution, dynamic background and the like in the multi-dimensional visual field;
the dynamic detection module can adopt deep learning to train and predict the model to the image data of the collected personnel, judge whether the constructor wears the safety helmet according to the regulation, and can shoot and send to the alarm device module in real time to the personnel who do not wear the safety helmet.
4. The intelligent safety management and control system for the construction site according to claim 1, wherein the cloud server, the alarm device module, the video display module, the video storage module and the external terminal are connected through the internet.
5. The intelligent safety management and control system for the construction site according to claim 1, wherein the external terminal comprises a web end and an APP end, the web end is arranged in a machine room of the construction site, the APP end is arranged on mobile equipment such as a mobile phone, and both the web end and the APP end can receive the alarm message sent by the alarm device module in real time.
6. The intelligent safety control system for construction sites as claimed in claim 1, wherein the safety helmet characteristic identification module is further connected with a door control system, the door control system is open to pass when the safety helmet characteristic identification module identifies that the entering person determines that the safety helmet is worn, and the door control system is forbidden to pass when the safety helmet characteristic identification module identifies that the entering person determines that the safety helmet is not worn.
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Application publication date: 20210319 |