Safety management system for constructors in dangerous area

Abstract

The invention provides a safety management system for construction personnel in a dangerous area, and the system integrates a biological feature recognition module, a somatosensory interaction monitoring module, a safety early warning module, an electronic fence module, a data processing and analysis module, a visual management interface module, an environment monitoring module, an emergency response module, and a virtual reality training module. The system accurately verifies the identity of a constructor through gait and iris recognition technologies, monitors a behavior mode through a 3D induction technology, gives out early warning through an intelligent safety hat and wearable equipment, limits an operation area through an electronic fence module, collects and analyzes safety data through a data processing module, and provides visual monitoring through a visual management interface. The environment monitoring module monitors environment parameters in real time, the emergency response module automatically starts an emergency program, the virtual reality training module improves safety consciousness and emergency processing capacity of constructors through 3D model interaction, and the system effectively improves intelligence, real-time performance and effectiveness of construction safety management in dangerous areas and reduces safety risks.

Description

Technical Field

[0001] The present invention relates to the field of construction safety management, and more specifically, to a safety management system for construction personnel in dangerous areas. Background Art

[0002] With the acceleration of urbanization and the increase in infrastructure construction, construction safety issues have become increasingly prominent. Construction workers in dangerous areas such as high-altitude operations, underground construction, chemical environments, etc. face higher safety risks. Therefore, ensuring the safety of construction workers has become an urgent problem to be solved. When constructing in dangerous areas, due to the complex environment and diverse risks, accidents occur frequently, resulting in casualties and economic losses. These accidents are often caused by the lack of effective safety monitoring and early warning systems.

[0003] With the rapid development of information technology, especially the maturity of technologies such as biometric recognition, the Internet of Things, big data analysis, and virtual reality, new technical support has been provided for construction safety management. Both the market and technology are calling for the emergence of a more intelligent and efficient safety management system.

[0004] The existing dangerous construction areas lack restrictions on the working areas for construction workers, which makes it easy for cross-boundary operations to occur. There is also a lack of safety training for construction workers, and their safety awareness and emergency response capabilities are insufficient. Summary of the invention

[0005] In order to overcome the above technical defects of the prior art, the present invention designs a safety management system for construction workers in dangerous areas which can effectively solve the technical problems of fir trees.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] A safety management system for construction workers in dangerous areas, including: a biometric recognition module, a somatosensory interactive monitoring module, a safety warning module, an electronic fence module, a data processing and analysis module, a visual management interface, an environmental monitoring module, an emergency response module and a virtual reality training module;

[0008] The biometric identification module is used to identify the identity of the construction personnel;

[0009] The somatosensory interaction monitoring module is used to monitor the behavior patterns of construction workers;

[0010] The safety warning module is used to send a warning signal to the construction personnel when a potential risk is detected;

[0011] The electronic fence module is used to define the safe working area for construction workers;

[0012] The data processing and analysis module is used to collect and analyze construction safety data;

[0013] The visual management interface is used to show the safety status of the construction site to the safety manager;

[0014] The environmental monitoring module is used to monitor the environmental parameters of the construction site in real time and issue an alarm when the environmental parameters exceed the safety range;

[0015] The emergency response module is used to automatically start the emergency response program when a safety accident occurs;

[0016] The virtual reality training module is used to simulate the construction site environment through virtual reality technology, and provide safety education and emergency response training to construction personnel to improve their safety awareness and response capabilities.

[0017] Preferably, the biometric recognition module comprises:

[0018] The gait recognition submodule uses gait analysis technology to capture the construction worker's walking pattern through a camera and match it with a preset gait template to achieve identity verification;

[0019] The iris recognition submodule uses a high-resolution camera to capture the iris images of construction workers, and uses an iris recognition algorithm to extract and match features to ensure the uniqueness and accuracy of the identity.

[0020] Preferably, the somatosensory interaction monitoring module includes:

[0021] The body-sensing camera submodule uses 3D sensing technology to capture the movements and postures of construction workers in three-dimensional space;

[0022] The behavior analysis submodule combines machine learning to identify the normal and abnormal behaviors of construction workers in real time and issue early warnings for abnormal behaviors;

[0023] The action prediction submodule uses an action prediction algorithm based on historical behavior data to predict the upcoming behavior of construction workers and provide early warning of possible safety risks.

[0024] Preferably, the safety warning module includes:

[0025] Intelligent safety helmet module, used to receive early warning signals and send out sound and light alarms to construction workers;

[0026] The wearable device submodule is used to receive early warning signals and issue alarms to construction workers through vibration, sound or display.

[0027] Preferably, the electronic fence module includes:

[0028] The position coordinate conversion submodule is used to convert the construction worker's GPS or indoor positioning system coordinates into the precise position coordinates of the construction site;

[0029] The electronic fence setting submodule uses the position coordinates provided by the position coordinate conversion submodule to accurately set the electronic fence at the specified location of the construction site, and ensures that the construction workers do not exceed the safe working area by real-time monitoring of their position coordinates.

[0030] Preferably, the data processing and analysis module includes:

[0031] The data collection submodule is used to collect real-time data from various modules, including identity verification results, behavior patterns, warning signals, and location information;

[0032] A deep learning submodule that analyzes collected real-time data to optimize security policies and response mechanisms;

[0033] The risk assessment submodule evaluates the overall safety risk of the construction site based on the collected real-time data and generates a risk assessment report to provide a scientific basis for safety management.

[0034] Preferably, the visual management interface includes:

[0035] A real-time monitoring view that displays real-time video and safety data from the construction site;

[0036] Security incident records, used to record and analyze security incidents to provide decision support;

[0037] 3D model display shows the structural layout of the construction site in the form of a three-dimensional model, and combines it with real-time monitoring data to provide a more intuitive safety management experience.

[0038] Preferably, the virtual reality training module includes:

[0039] The 3D model integration submodule imports the 3D model in the visual management interface into the virtual reality training environment to ensure the consistency between the training scene and the actual construction site;

[0040] The scene interaction design submodule is used for construction workers to interact with 3D models in a virtual environment;

[0041] The spatial navigation training submodule uses 3D models to help construction workers become familiar with the spatial layout of the construction site in a virtual environment and conduct spatial navigation and positioning training.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: through the position coordinate conversion submodule and the electronic fence setting submodule of the electronic fence module, the working area of ​​the construction personnel is accurately limited, which effectively solves the problem of the lack of restrictions on the working area of ​​the construction personnel in the dangerous construction area in the prior art, and prevents the occurrence of cross-border operations. At the same time, through the 3D model integration submodule, the scene interaction design submodule and the space navigation training submodule of the virtual reality training module, a training environment consistent with the actual construction site is provided, which significantly improves the safety awareness and emergency handling capabilities of the construction personnel, and solves the problem of insufficient safety training. In summary, the technical solution effectively limits the working area of ​​the construction personnel, prevents cross-border operations, and at the same time improves the safety awareness and emergency handling capabilities of the construction personnel, thereby greatly reducing the safety risks of the construction site. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0044] Figure 1 This is a structural diagram of a safety management system for construction workers in dangerous areas; DETAILED DESCRIPTION

[0045] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0046] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0047] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0048] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0049] Example

[0050] A safety management system for construction workers in dangerous areas, such as Figure 1 As shown, it includes: biometric recognition module, somatosensory interaction monitoring module, safety warning module, electronic fence module, data processing and analysis module, visual management interface, environmental monitoring module, emergency response module and virtual reality training module;

[0051] The biometric identification module is used to identify the identity of the construction personnel;

[0052] The somatosensory interaction monitoring module is used to monitor the behavior patterns of construction workers;

[0053] The safety warning module is used to send a warning signal to the construction personnel when a potential risk is detected;

[0054] The electronic fence module is used to define the safe working area for construction workers;

[0055] The data processing and analysis module is used to collect and analyze construction safety data;

[0056] The visual management interface is used to show the safety status of the construction site to the safety manager;

[0057] The environmental monitoring module is used to monitor the environmental parameters of the construction site in real time, such as temperature, humidity, concentration of harmful gases, etc., and to issue an alarm when the environmental parameters exceed the safe range;

[0058] The emergency response module is used to automatically start the emergency response procedure when a safety accident occurs, including but not limited to sending a distress signal to rescue personnel, providing detailed information on the accident site, and guiding construction personnel to evacuate quickly.

[0059] The virtual reality training module is used to simulate the construction site environment through virtual reality technology, and provide safety education and emergency response training to construction personnel to improve their safety awareness and response capabilities.

[0060] The biometric feature recognition module comprises:

[0061] The gait recognition submodule uses gait analysis technology to capture the construction worker's walking pattern through a camera and match it with a preset gait template to achieve identity verification;

[0062] Use a high-definition camera to capture the walking video of the construction workers. To ensure the accuracy of the captured gait information, the camera should be placed in a position where it can clearly record the entire walking process, while avoiding interference from factors such as light and shadow on gait recognition. The captured video is preprocessed, including noise removal, background subtraction, frame difference method, etc., to extract a clear gait contour. These preprocessing steps help reduce the complexity of subsequent gait feature extraction and improve recognition accuracy.

[0063] Spatial features are extracted from the preprocessed gait profile, such as human joint movement, body shape, muscle characteristics, and head shape. These features can reflect the walking posture and body shape of construction workers. In addition to spatial features, the temporal features of the gait also need to be extracted, that is, the change patterns of various features over time during walking, which helps to further distinguish the gait patterns of different individuals.

[0064] The extracted gait features are quantified and constructed into gait templates, which will serve as the basis for subsequent identity authentication. To ensure the accuracy of the templates, multiple walking videos can be collected for feature extraction and template construction, and the captured gait features of the construction workers are matched with the preset gait templates. During the matching process, template matching algorithms or dynamic time warping algorithms can be used to calculate the similarity between features. Based on the similarity threshold, it can be determined whether the construction workers are legal.

[0065] According to the result of gait template matching, the construction worker's identity is authenticated. If the matching degree is higher than the set threshold, the authentication is considered to be successful; otherwise, the authentication is considered to have failed.

[0066] The iris recognition submodule uses a high-resolution camera to capture the iris images of construction workers, and uses an iris recognition algorithm to extract and match features to ensure the uniqueness and accuracy of the identity.

[0067] The somatosensory interaction monitoring module includes:

[0068] The body-sensing camera submodule uses 3D sensing technology to capture the movements and postures of construction workers in three-dimensional space;

[0069] Choose a motion-sensing camera with 3D sensing technology to ensure that it can capture the movements and postures of construction workers in three-dimensional space. Deploy the motion-sensing camera at key locations on the construction site, such as entrances and exits, work areas, etc., to ensure that the camera can fully cover the area that needs to be monitored. Configure the camera, including adjusting the focal length, setting the capture range, adjusting the frame rate, etc., to optimize the capture effect.

[0070] Start the somatosensory camera to capture the movements and postures of construction workers in three-dimensional space. The camera will transmit the captured data to the behavior analysis submodule in real time for subsequent analysis and processing.

[0071] Using 3D reconstruction technology, the captured data is converted into a 3D model to more intuitively display the movements and postures of the construction workers.

[0072] The behavior analysis submodule combines machine learning to identify the normal and abnormal behaviors of construction workers in real time and issue early warnings for abnormal behaviors;

[0073] The motion data of construction workers is obtained from the somatosensory camera submodule and preprocessed, such as normalization and denoising, and the processed data is input into the machine learning model for training.

[0074] Select appropriate machine learning algorithms, such as convolutional neural networks (CNN) and support vector machines (SVM), to build a behavior analysis model. Use labeled normal behavior and abnormal behavior data sets to train the model so that it can accurately identify the behavior of construction workers. Input the real-time captured construction worker motion data into the trained behavior analysis model for behavior recognition. If abnormal behavior is identified, such as not wearing a safety helmet, illegal operation, etc., the early warning mechanism will be triggered immediately and a warning message will be sent to the management personnel.

[0075] The action prediction submodule uses an action prediction algorithm based on historical behavior data to predict the upcoming behavior of construction workers and provide early warning of possible safety risks.

[0076] Obtain historical behavior data from the behavior analysis submodule, organize and analyze it, and preprocess the data, such as normalization and time series analysis, for subsequent use.

[0077] Select appropriate action prediction algorithms, such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), etc., build action prediction models, use historical behavior data to train the model so that it can accurately predict the upcoming behavior of construction workers, and input the real-time captured construction worker action data into the trained action prediction model to perform behavior prediction. If it is predicted that the construction workers are about to perform behaviors that may cause safety risks, the early warning mechanism is immediately triggered and warning information is sent to management personnel so that they can take timely measures to intervene.

[0078] The safety warning module includes:

[0079] Intelligent safety helmet module, used to receive early warning signals and send out sound and light alarms to construction workers;

[0080] The wearable device submodule, such as a smart watch or armband, is used to receive warning signals and alert construction workers through vibration, sound or display.

[0081] The electronic fence module includes:

[0082] The position coordinate conversion submodule is used to convert the construction workers' GPS or indoor positioning system coordinates into the precise position coordinates of the construction site; the original position coordinates provided by the construction workers' personal positioning devices, such as GPS, RFID, UWB, etc., are converted into the specific coordinate system of the construction site, which usually involves the conversion of coordinate systems, such as from the geographic coordinate system to the customized plane coordinate system of the construction area.

[0083] The electronic fence setting submodule uses the position coordinates provided by the position coordinate conversion submodule to accurately set the electronic fence at the specified location of the construction site, and ensures that the construction workers do not exceed the safe working area by real-time monitoring of their position coordinates.

[0084] It allows managers to define the shape of the electronic fence, such as circle, rectangle, polygon, etc., and the size, such as radius, side length, etc., according to the actual situation of the construction site. It provides a user-friendly interface to facilitate managers to select and set the shape and size of the fence.

[0085] Using the position coordinates in the world coordinate system provided by the position coordinate conversion submodule, the electronic fence is accurately set at the specified location on the construction site, and a visual interface is provided to display the position and shape of the electronic fence for managers to confirm and adjust.

[0086] The data processing and analysis module includes:

[0087] The data collection submodule is used to collect real-time data from various modules, including identity verification results, behavior patterns, warning signals, and location information;

[0088] A deep learning submodule that analyzes collected real-time data to optimize security policies and response mechanisms;

[0089] Select appropriate deep learning models according to analysis needs, such as convolutional neural networks (CNN), recurrent neural networks (RNN), etc., and use labeled data sets to train the models so that they can accurately identify and analyze patterns and information in the data.

[0090] The risk assessment submodule evaluates the overall safety risk of the construction site based on the collected real-time data and generates a risk assessment report to provide a scientific basis for safety management.

[0091] The visual management interface includes:

[0092] A real-time monitoring view that displays real-time video and safety data from the construction site;

[0093] Security incident records, used to record and analyze security incidents to provide decision support;

[0094] 3D model display, which displays the structural layout of the construction site in the form of a three-dimensional model and combines it with real-time monitoring data to provide a more intuitive safety management experience;

[0095] Use 3D modeling tools to create an accurate model of the construction site, integrate the 3D model into the visual management interface, allow users to understand the layout of the construction site by rotating, zooming and exploring the model, overlay real-time monitoring data on the 3D model, such as marking the current camera position, personnel distribution and security incident locations on the model, and provide interactive functions to allow users to obtain more detailed information by clicking on specific areas in the model.

[0096] The VR training modules include:

[0097] The 3D model integration submodule imports the 3D model in the visual management interface into the virtual reality training environment to ensure the consistency between the training scene and the actual construction site;

[0098] Export 3D model data from the visual management interface, ensure the accuracy and latest status of the model, and import the 3D model into VR training software such as Unity or Unreal Engine. Ensure that the model in the VR environment is consistent with the actual construction site, including the location of equipment, tools, and safety signs.

[0099] The scene interaction design submodule is used for construction workers to interact with 3D models in a virtual environment;

[0100] Design interactive operations in virtual reality, such as simulating the use of tools, equipment and following safety procedures, develop gesture recognition or controller operation to enable construction workers to interact naturally in the virtual environment, and integrate feedback systems such as visual, auditory or tactile feedback to enhance the realism of the training experience.

[0101] The spatial navigation training submodule uses 3D models to help construction workers become familiar with the spatial layout of the construction site in a virtual environment and conduct spatial navigation and positioning training.

[0102] Use 3D models to create navigation training for simulated construction sites, including planning safe paths and identifying dangerous areas, design training courses that include different scenarios and challenges to test construction workers' spatial awareness and emergency response capabilities, and provide real-time feedback and guidance to help construction workers learn and remember correct navigation and safety behaviors in a virtual environment.

[0103] In the specific implementation, high-definition cameras and gait recognition devices are installed at the entrance of the construction site, iris recognition devices are deployed to ensure that they are connected to the biometric recognition server, 3D body sensing cameras are installed in key areas of the construction site, behavioral analysis algorithms and action prediction algorithms are configured on the monitoring server, smart safety helmets and wearable devices are equipped for construction workers to ensure that they can receive warning signals from the system, GPS or indoor positioning systems are deployed at the construction site, electronic fences are set up, and they are connected to the position coordinate conversion submodule and the electronic fence setting submodule, and data collection submodules are deployed to collect data from various modules. Deep learning submodules and risk assessment submodules are configured on the data processing server, visualization software is developed to ensure that it can display real-time monitoring views, security event records and 3D model displays, environmental monitoring sensors such as temperature and humidity sensors, harmful gas detectors, etc. are installed, and they are connected to the data processing server, emergency response procedures are configured, and they can be automatically started, 3D model integration submodules are created, 3D models of the construction site are imported, and scene interaction and spatial navigation training content are designed.

[0104] During the system operation phase, when construction workers enter the site, their identity is authenticated through gait or iris recognition, and their behavior is monitored in real time. The behavior analysis submodule and the action prediction submodule are used for analysis. Once abnormal behavior is found, an early warning is immediately issued through the safety early warning module. After receiving the early warning signal, the smart safety helmets and wearable devices send sound, light, vibration or display alarms to the construction workers, monitor the location of the construction workers in real time to ensure that they are within the safe working area. Once they cross the boundary, an alarm is immediately issued. Real-time data is collected, and deep learning and risk assessment are carried out to optimize safety strategies. The safety status of the construction site is displayed in real time, safety incidents are recorded, decision support is provided, and environmental parameters are monitored in real time. Once the safety range is exceeded, an alarm is immediately issued. In the event of a safety accident, the emergency response procedure is automatically initiated to guide rescue operations. Construction workers receive safety education and emergency handling training through virtual reality equipment to improve their safety awareness and response capabilities.

[0105] The same or similar reference numerals correspond to the same or similar components;

[0106] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0107] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A safety management system for construction workers in dangerous areas, characterized in that: include: Biometric recognition module, somatosensory interactive monitoring module, safety warning module, electronic fence module, data processing and analysis module, visual management interface, environmental monitoring module, emergency response module and virtual reality training module; The biometric identification module is used to identify the identity of the construction personnel; The somatosensory interaction monitoring module is used to monitor the behavior patterns of construction workers; The safety warning module is used to send a warning signal to the construction personnel when a potential risk is detected; The electronic fence module is used to define the safe working area for construction workers; The data processing and analysis module is used to collect and analyze construction safety data; The visual management interface is used to show the safety status of the construction site to the safety manager; The environmental monitoring module is used to monitor the environmental parameters of the construction site in real time and issue an alarm when the environmental parameters exceed the safety range; The emergency response module is used to automatically start the emergency response program when a safety accident occurs; The virtual reality training module is used to simulate the construction site environment through virtual reality technology, and provide safety education and emergency response training to construction personnel to improve their safety awareness and response capabilities.

2. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The biometric feature recognition module comprises: The gait recognition submodule uses gait analysis technology to capture the construction worker's walking pattern through a camera and match it with a preset gait template to achieve identity verification; The iris recognition submodule uses a high-resolution camera to capture the iris images of construction workers, and uses an iris recognition algorithm to extract and match features to ensure the uniqueness and accuracy of the identity.

3. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The somatosensory interaction monitoring module includes: The body-sensing camera submodule uses 3D sensing technology to capture the movements and postures of construction workers in three-dimensional space; The behavior analysis submodule combines machine learning to identify the normal and abnormal behaviors of construction workers in real time and issue early warnings for abnormal behaviors; The action prediction submodule uses an action prediction algorithm based on historical behavior data to predict the upcoming behavior of construction workers and provide early warning of possible safety risks.

4. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The safety warning module includes: Intelligent safety helmet module, used to receive early warning signals and send out sound and light alarms to construction workers; The wearable device submodule is used to receive early warning signals and issue alarms to construction workers through vibration, sound or display.

5. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The electronic fence module includes: The position coordinate conversion submodule is used to convert the construction worker's GPS or indoor positioning system coordinates into the precise position coordinates of the construction site; The electronic fence setting submodule uses the position coordinates provided by the position coordinate conversion submodule to accurately set the electronic fence at the specified location of the construction site, and ensures that the construction workers do not exceed the safe working area by real-time monitoring of their position coordinates.

6. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The data processing and analysis module includes: The data collection submodule is used to collect real-time data from various modules, including identity verification results, behavior patterns, warning signals, and location information; A deep learning submodule that analyzes collected real-time data to optimize security policies and response mechanisms; The risk assessment submodule evaluates the overall safety risk of the construction site based on the collected real-time data and generates a risk assessment report to provide a scientific basis for safety management.

7. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The visual management interface includes: A real-time monitoring view that displays real-time video and safety data from the construction site; Security incident records, used to record and analyze security incidents to provide decision support; 3D model display shows the structural layout of the construction site in the form of a three-dimensional model, and combines it with real-time monitoring data to provide a more intuitive safety management experience.

8. A safety management system for construction workers in dangerous areas according to claim 1, characterized in that: The VR training modules include: The 3D model integration submodule imports the 3D model in the visual management interface into the virtual reality training environment to ensure the consistency between the training scene and the actual construction site; The scene interaction design submodule is used for construction workers to interact with 3D models in a virtual environment; The spatial navigation training submodule uses 3D models to help construction workers become familiar with the spatial layout of the construction site in a virtual environment and conduct spatial navigation and positioning training.

Images