Control room large-screen display system and method for comprehensively displaying safety supervision information

Abstract

The invention relates to the technical field of safety, in particular to a control room large-screen display system and method for comprehensively displaying safety supervision information, which realize electronization of plan establishment and management through application of a plan table subsystem so as to improve the plan management efficiency and improve the plan management efficiency. And the effect of the pre-arranged plan on reducing accident loss can be more effectively exerted. Meanwhile, the triggered pre-arranged plan is automatically displayed, so that an accident handling operator on duty can accurately master the accident condition, the panic is effectively avoided, and the efficiency and accuracy of safety supervision are further improved.

Description

Technical Field

[0001] The present invention belongs to the field of safety technology, and in particular relates to a control room large-screen display system and method for comprehensively displaying safety supervision information. Background Art

[0002] The importance of safety monitoring systems in various industrial production, public facility operations and many other scenarios is obvious. These systems ensure the safety of production processes and facility operations through real-time monitoring and recording. Whether in the fields of petrochemicals, electric power, transportation or urban infrastructure, safety monitoring systems play a vital role. They can detect potential safety hazards in a timely manner and prevent accidents, thereby protecting the lives of employees and the property of the company. In addition, these systems can also provide detailed data recording and analysis to help managers conduct risk assessment and decision-making, and further improve the overall safety management level.

[0003] At present, the information related to safety supervision is scattered in various modules, making it difficult for managers to quickly and comprehensively grasp the safety status, resulting in delayed discovery of problems and inefficient handling. Traditional safety supervision methods mainly rely on manual inspections, which not only consumes a lot of manpower and material resources, but is also prone to omissions. Summary of the invention

[0004] The present invention provides a control room large-screen display system and method for comprehensively displaying safety supervision information. The technical problem to be solved is: how to comprehensively display safety supervision information and improve the efficiency and accuracy of safety supervision.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: A control room large screen display system for comprehensively displaying safety supervision information, comprising: Data collection module, used to obtain personnel flow information, on-site violation information, equipment operation failure information and hot spot operation information; The emergency plan data module includes an emergency plan database, in which the treatment plans corresponding to dangerous scenarios are written - emergency plan tables; The plan triggering subsystem is used to analyze the data collected by the data acquisition module in real time to determine whether a plan has been triggered. If a plan is triggered, the corresponding plan table is called out; The plan tracking subsystem is used to dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level represents the accident level and corresponds to the graded plan contents. The plan triggering subsystem periodically reads the monitoring data and compares it with the plan table triggering conditions. If the monitoring data meets the triggering conditions, the corresponding plan table is triggered. The display subsystem is used to display the triggered plan table.

[0006] A further improvement of the present invention is that the plan triggering subsystem includes an on-site violation information detection system for detecting whether the workers wear safety helmets as required.

[0007] A further improvement of the present invention is that the on-site violation information detection system comprises: A data acquisition unit, used to acquire the public data set PDSW and collect worker identity information and worker images monitored by the real-name system entrance; The preprocessing unit is used to add labels to the images in the public dataset PDSW, save the collected images with the worker identity information, and perform standardization processing; A system architecture building unit for creating a neural network model for identifying helmet wearing based on the RetinaNet and EfficientNetB0 neural network algorithms; The training unit is used to train RetinaNet on the public dataset PDSW and input the labeled PDSW dataset images into RetinaNet; the images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0; The detection unit is used to authenticate the identity of personnel entering the construction site using the modified neural network model and to detect the helmets of personnel entering the construction site.

[0008] A further improvement of the present invention is that the plan triggering subsystem also includes a fire point detection system.

[0009] A further improvement of the present invention is that the hot spot detection system comprises: The first judgment module is used to obtain the fire sensor data of the target operation area and judge whether there is a fire risk in the target operation area based on the data; The second judgment module is used to detect the smoke data and temperature data of the target operation area if there is a fire risk, judge the fire situation of the target operation area according to the smoke data and temperature data, and obtain a first judgment result; The third judgment module is used to make a second judgment on the fire situation based on the thermal image of the target operation area to obtain a second judgment result; The evaluation module is used to comprehensively evaluate whether there is a fire accident in the target operation area based on the first judgment result and the second judgment result; if there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation in the target operation area based on the smoke data and temperature data, and before obtaining the first judgment result, obtain the environmental data of the target operation area within the normal indicator range, and store the environmental data in a preset database; determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data based on the prerequisites; use the environmental data to build an initial model, and use the prerequisites for the occurrence of fire in the target operation area and the change value of the environmental data as the input of the model to train the initial model to obtain a fire abnormality prediction model; use sample data to test the fire abnormality prediction model, and determine the accuracy of the fire abnormality prediction model based on the test results.

[0010] A control room large screen display method for comprehensively displaying safety supervision information, comprising: Obtain information on personnel flow, on-site violation information, equipment operation failure information, and hot spot operation information; Construct a plan database, which contains the corresponding treatment plans for dangerous scenarios - plan tables; Analyze the data collected by the data acquisition module in real time to determine whether any plan has been triggered. If a plan is triggered, call up the corresponding plan table; Dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level indicates the accident level and corresponds to the graded plan contents. The plan trigger subsystem periodically reads the monitoring data and compares it with the trigger conditions of the plan table. If the monitoring data meets the trigger conditions, the corresponding plan table is triggered; The display subsystem displays the triggered plan table.

[0011] A further improvement of the present invention is that detecting whether a worker wears a safety helmet as required comprises the following steps: Obtain the public dataset PDSW and collect worker identity information and worker images monitored by real-name entry; Label the images in the public dataset PDSW, save the collected images with the worker’s identity information, and perform standardization. Create a neural network model for identifying helmet wearing based on RetinaNet and EfficientNetB0 neural network algorithms; RetinaNet is trained on the public dataset PDSW, and the labeled PDSW dataset images are input into RetinaNet; the images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0; The modified neural network model is used to authenticate the identity of personnel entering the construction site and to detect the safety helmets of personnel entering the construction site.

[0012] A further improvement of the present invention is that the plan triggering subsystem includes a fire point detection system, and the fire point detection system includes the following steps: Obtain fire sensor data of the target operation area and determine whether there is a fire risk in the target operation area based on the data; If there is a fire risk, detecting smoke data and temperature data of the target operation area, judging the fire situation of the target operation area according to the smoke data and temperature data, and obtaining a first judgment result; Secondarily judge the fire situation based on the thermal image of the target operation area to obtain a second judgment result; Comprehensively assess whether there is a fire accident in the target operation area based on the first judgment result and the second judgment result; If there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation of the target operation area according to the smoke data and temperature data, obtain environmental data of the target operation area within a normal indicator range before obtaining the first judgment result, and store the environmental data in a preset database; Determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data according to the prerequisites; An initial model is constructed using the environmental data, and the prerequisites for the occurrence of fire in the target operation area and the change values ​​of the environmental data are used as inputs of the model to train the initial model to obtain a fire abnormality prediction model; The abnormal fire situation prediction model is tested using sample data, and the accuracy of the abnormal fire situation prediction model is determined based on the test results.

[0013] A computer-readable storage medium stores a computer program, which implements the steps of the method when executed by a processing device.

[0014] A computer program product comprises a computer program, which implements the steps of the method when executed by a processing device.

[0015] Compared with the prior art, the present invention has at least the following beneficial technical effects: The present invention provides a control room large-screen display system and method for comprehensively displaying safety supervision information. Through the application of the plan table subsystem, the electronic establishment and management of the plan is realized, thereby improving the efficiency of plan management and enabling the plan to play a more effective role in reducing accident losses. At the same time, by automatically displaying the triggered plan, it ensures that the accident handling duty personnel can accurately grasp the accident situation, effectively avoiding the occurrence of panic, thereby improving the efficiency and accuracy of safety supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a logic diagram of a control room large-screen display method for comprehensively displaying safety supervision information. DETAILED DESCRIPTION

[0017] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0018] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0019] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0020] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0021] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0022] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0023] Example 1 The present invention provides a control room large-screen display system for comprehensively displaying safety supervision information, comprising: The data collection module is used to obtain personnel flow information, on-site violation information, equipment operation failure information and hot spot operation information.

[0024] Specifically, the flow of personnel information is collected through the access control system to record the entry and exit of personnel, and the data acquisition module obtains the access control system records. In addition, an information acquisition device is arranged at the work site, and the information acquisition device includes a smoke sensor and a combustible gas sensor; the information acquisition device transmits the detected data to the data acquisition module in real time. The equipment comes with a monitoring system to monitor the equipment operating parameters in real time. When the parameters are abnormal, the major defect information of the equipment is automatically generated and sent to the data acquisition module. A hot spot detection module is provided, which includes a flame detector and a combustible gas detector. The flame detector and the combustible gas detector are used to monitor the safety status of the work site in real time. Personnel engaged in hot work and high-risk operations are required to be equipped with positioning equipment so that their location dynamics can be grasped in real time.

[0025] The emergency plan data module includes an emergency plan database, which contains the treatment plans corresponding to dangerous scenarios - emergency plan tables.

[0026] The plan triggering subsystem is used to analyze the data collected by the data acquisition module in real time to determine whether a plan has been triggered. If a plan is triggered, the corresponding plan table is called out; The plan tracking subsystem is used to dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level represents the accident level and corresponds to the graded plan contents. The plan trigger subsystem periodically reads the monitoring data and compares it with the plan table trigger conditions. If the monitoring data meets the trigger conditions, the corresponding plan table is triggered.

[0027] Display subsystem, used to display the triggered plan table; In summary, through the application of the plan table subsystem, the electronic establishment and management of the plan is realized, thereby improving the efficiency of plan management and making the plan more effective in reducing accident losses. At the same time, by automatically displaying the triggered plan, it ensures that the accident handling staff on duty can accurately grasp the accident situation, effectively avoiding panic, and thus improving the efficiency and accuracy of safety supervision.

[0028] Furthermore, the plan triggering subsystem includes an on-site violation information detection system for detecting whether the workers wear safety helmets as required. On-site violation information detection system, including: The data acquisition unit is used to obtain the public data set PDSW and collect worker identity information and worker images monitored by the real-name entrance.

[0029] The preprocessing unit is used to add labels to the images in the public dataset PDSW, save the collected images with the worker identity information, and perform standardization. System architecture building unit for creating a neural network model for identifying helmet wearing based on RetinaNet and EfficientNetB0 neural network algorithms.

[0030] The training unit is used to train RetinaNet on the public dataset PDSW and input the labeled PDSW dataset images into RetinaNet. The images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0. The modified neural network model is used to authenticate the identity of personnel entering the construction site and to detect the safety helmets of personnel entering the construction site. In summary, the system can quickly acquire public data sets (such as PDSW) and simultaneously collect worker identity information and worker images for real-name entrance monitoring, greatly improving the efficiency of data collection. Through advanced neural network algorithm architectures, such as the combination of RetinaNet and EfficientNetB0, a large number of images can be processed and analyzed in a short period of time. After training on public data sets, the labeled data set images can be quickly input into RetinaNet for detection, which greatly shortens the detection time and ensures timely identity verification and helmet detection for personnel entering the construction site.

[0031] Furthermore, the plan triggering subsystem includes a fire point detection system, and the fire point detection system includes the following: The first judgment module is used to obtain the fire sensor data of the target operation area and judge whether there is a fire risk in the target operation area based on the data; The second judgment module is used to detect the smoke data and temperature data of the target operation area if there is a fire risk, judge the fire situation of the target operation area according to the smoke data and temperature data, and obtain a first judgment result; The third judgment module is used to make a second judgment on the fire situation based on the thermal image of the target operation area to obtain a second judgment result; An evaluation module, used for comprehensively evaluating whether there is a fire accident in the target operation area according to the first judgment result and the second judgment result; If there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation of the target operation area according to the smoke data and temperature data, obtain environmental data of the target operation area within a normal indicator range before obtaining the first judgment result, and store the environmental data in a preset database; Determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data according to the prerequisites; An initial model is constructed using the environmental data, and the prerequisites for the occurrence of fire in the target operation area and the change values ​​of the environmental data are used as inputs of the model to train the initial model to obtain a fire abnormality prediction model; The abnormal fire situation prediction model is tested using sample data, and the accuracy of the abnormal fire situation prediction model is determined based on the test results.

[0032] Example 2 The present invention provides a control room large-screen display method for comprehensively displaying safety supervision information, comprising the following steps: Obtain information on personnel flow, on-site violation information, equipment operation failure information, and hot spot operation information.

[0033] Specifically, the flow of personnel information is collected through the access control system to record the entry and exit of personnel, and the data acquisition module obtains the access control system records. In addition, an information acquisition device is arranged at the work site, and the information acquisition device includes a smoke sensor and a combustible gas sensor; the information acquisition device transmits the detected data to the data acquisition module in real time. The equipment comes with a monitoring system to monitor the equipment operating parameters in real time. When the parameters are abnormal, the major defect information of the equipment is automatically generated and sent to the data acquisition module. A hot spot detection module is provided, which includes a flame detector and a combustible gas detector. The flame detector and the combustible gas detector are used to monitor the safety status of the work site in real time. Personnel engaged in hot work and high-risk operations are required to be equipped with positioning equipment so that their location dynamics can be grasped in real time.

[0034] Construct a plan database, which contains the corresponding treatment plans for dangerous scenarios - plan tables.

[0035] Analyze the data collected by the data acquisition module in real time to determine whether any plan has been triggered. If a plan is triggered, call up the corresponding plan table; Dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level indicates the accident level and corresponds to the graded plan contents. The plan trigger subsystem periodically reads the monitoring data and compares it with the trigger conditions of the plan table. If the monitoring data meets the trigger conditions, the corresponding plan table is triggered.

[0036] The display subsystem displays the triggered plan table; Further, checking whether the workers are wearing safety helmets as required includes the following steps: Obtain the public dataset PDSW and collect worker identity information and worker images monitored by real-name entrance.

[0037] The images in the public dataset PDSW are labeled, and the collected images are saved and named with the workers' identity information and standardized. A neural network model for identifying helmet wearing was created based on the RetinaNet and EfficientNetB0 neural network algorithms.

[0038] RetinaNet is trained on the public dataset PDSW, and the labeled PDSW dataset images are input into RetinaNet. Images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0. The modified neural network model is used to authenticate the identity of personnel entering the construction site and to detect the safety helmets of personnel entering the construction site. In summary, the system can quickly acquire public data sets (such as PDSW) and simultaneously collect worker identity information and worker images for real-name entrance monitoring, greatly improving the efficiency of data collection. Through advanced neural network algorithm architectures, such as the combination of RetinaNet and EfficientNetB0, a large number of images can be processed and analyzed in a short period of time. After training on public data sets, the labeled data set images can be quickly input into RetinaNet for detection, greatly shortening the detection time and ensuring timely identity verification and helmet detection for personnel entering the construction site.

[0039] Furthermore, the plan triggering subsystem includes a fire point detection system, and the fire point detection system includes the following steps: Obtain fire sensor data of the target operation area and determine whether there is a fire risk in the target operation area based on the data; If there is a fire risk, detecting smoke data and temperature data of the target operation area, judging the fire situation of the target operation area according to the smoke data and temperature data, and obtaining a first judgment result; Secondarily judge the fire situation based on the thermal image of the target operation area to obtain a second judgment result; Comprehensively assess whether there is a fire accident in the target operation area based on the first judgment result and the second judgment result; If there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation of the target operation area according to the smoke data and temperature data, obtain environmental data of the target operation area within a normal indicator range before obtaining the first judgment result, and store the environmental data in a preset database; Determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data according to the prerequisites; An initial model is constructed using the environmental data, and the prerequisites for the occurrence of fire in the target operation area and the change values ​​of the environmental data are used as inputs of the model to train the initial model to obtain a fire abnormality prediction model; The abnormal fire situation prediction model is tested using sample data, and the accuracy of the abnormal fire situation prediction model is determined based on the test results.

[0040] Example 3 The present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processing device, it is the steps of the above method.

[0041] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0042] The present application is described with reference to the flowcharts and / or block diagrams of the methods, systems and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0043] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0044] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0045] Example 4 A computer program product provided by the present invention includes a computer program, characterized in that the computer program implements the steps of the above method when executed by a processing device.

[0046] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0047] In addition, it should be understood that although this specification is described in accordance with the implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation modes that can be understood by those skilled in the art. The above content is only to illustrate the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A control room large screen display system for comprehensively displaying safety supervision information, characterized in that: include: Data collection module, used to obtain personnel flow information, on-site violation information, equipment operation failure information and hot spot operation information; The emergency plan data module includes an emergency plan database, in which the treatment plans corresponding to dangerous scenarios are written - emergency plan tables; The plan triggering subsystem is used to analyze the data collected by the data acquisition module in real time to determine whether a plan has been triggered. If a plan is triggered, the corresponding plan table is called out; The plan tracking subsystem is used to dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level indicates the accident level and corresponds to the graded plan contents. The plan trigger subsystem periodically reads the monitoring data and compares it with the trigger conditions of the plan table. If the monitoring data meets the trigger conditions, the corresponding plan table is triggered; The display subsystem is used to display the triggered plan table.

2. According to claim 1, a control room large screen display system for comprehensively displaying safety supervision information is characterized in that: The plan triggering subsystem includes an on-site violation information detection system, which is used to detect whether workers wear safety helmets as required.

3. A control room large screen display system for comprehensively displaying safety supervision information according to claim 2, characterized in that: On-site violation information detection system, including: A data acquisition unit, used to acquire the public data set PDSW and collect worker identity information and worker images monitored by the real-name system entrance; The preprocessing unit is used to add labels to the images in the public dataset PDSW, save the collected images with the worker identity information, and perform standardization processing; A system architecture building unit for creating a neural network model for identifying helmet wearing based on the RetinaNet and EfficientNetB0 neural network algorithms; The training unit is used to train RetinaNet on the public dataset PDSW and input the labeled PDSW dataset images into RetinaNet; the images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0; The detection unit is used to authenticate the identity of personnel entering the construction site using the modified neural network model and to detect the helmets of personnel entering the construction site.

4. A control room large screen display system for comprehensively displaying safety supervision information according to claim 2, characterized in that: The plan triggering subsystem also includes a fire point detection system.

5. A control room large screen display system for comprehensively displaying safety supervision information according to claim 4, characterized in that: The hot spot detection system includes: The first judgment module is used to obtain the fire sensor data of the target operation area and judge whether there is a fire risk in the target operation area based on the data; The second judgment module is used to detect the smoke data and temperature data of the target operation area if there is a fire risk, judge the fire situation of the target operation area according to the smoke data and temperature data, and obtain a first judgment result; The third judgment module is used to make a second judgment on the fire situation based on the thermal image of the target operation area to obtain a second judgment result; The evaluation module is used to comprehensively evaluate whether there is a fire accident in the target operation area based on the first judgment result and the second judgment result; if there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation in the target operation area based on the smoke data and temperature data, and before obtaining the first judgment result, obtain the environmental data of the target operation area within the normal indicator range, and store the environmental data in a preset database; determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data based on the prerequisites; use the environmental data to build an initial model, and use the prerequisites for the occurrence of fire in the target operation area and the change value of the environmental data as the input of the model to train the initial model to obtain a fire abnormality prediction model; use sample data to test the fire abnormality prediction model, and determine the accuracy of the fire abnormality prediction model based on the test results.

6. A control room large screen display method for comprehensively displaying safety supervision information, characterized in that: include: Obtain information on personnel flow, on-site violation information, equipment operation failure information, and hot spot operation information; Construct a plan database, which contains the corresponding treatment plans for dangerous scenarios - plan tables; Analyze the data collected by the data acquisition module in real time to determine whether any plan has been triggered. If a plan is triggered, call up the corresponding plan table; Dynamically update the triggered plan table and record the number of times the corresponding plan is triggered; The plan table subsystem includes a plan table editing unit and a plan table storage unit. The plan table includes plan object information, trigger conditions, levels, upgrade conditions, graded plan contents and release conditions. The trigger conditions are conditions that the monitoring data must meet when the plan is triggered, the upgrade conditions are conditions that the monitoring data must meet when the plan is upgraded, and the release conditions are conditions that the monitoring data must meet when the plan is released. The level indicates the accident level and corresponds to the graded plan contents. The plan trigger subsystem periodically reads the monitoring data and compares it with the trigger conditions of the plan table. If the monitoring data meets the trigger conditions, the corresponding plan table is triggered; The display subsystem displays the triggered plan table.

7. A control room large screen display method for comprehensively displaying safety supervision information according to claim 6, characterized in that: Check whether workers are wearing safety helmets as required, including the following steps: Obtain the public dataset PDSW and collect worker identity information and worker images monitored by real-name entry; Label the images in the public dataset PDSW, save the collected images with the worker’s identity information, and perform standardization. Create a neural network model for identifying helmet wearing based on RetinaNet and EfficientNetB0 neural network algorithms; RetinaNet is trained on the public dataset PDSW, and the labeled PDSW dataset images are input into RetinaNet; the images detected as face areas by RetinaNet are used as face recognition training sets to train EfficientNetB0; The modified neural network model is used to authenticate the identity of personnel entering the construction site and to detect the safety helmets of personnel entering the construction site.

8. A control room large screen display method for comprehensively displaying safety supervision information according to claim 6, characterized in that: The plan triggering subsystem includes a fire point detection system, which includes the following steps: Obtain fire sensor data of the target operation area and determine whether there is a fire risk in the target operation area based on the data; If there is a fire risk, detecting smoke data and temperature data of the target operation area, judging the fire situation of the target operation area according to the smoke data and temperature data, and obtaining a first judgment result; Secondarily judge the fire situation based on the thermal image of the target operation area to obtain a second judgment result; Comprehensively assess whether there is a fire accident in the target operation area based on the first judgment result and the second judgment result; If there is a fire risk, detect the smoke data and temperature data of the target operation area, judge the fire situation of the target operation area according to the smoke data and temperature data, obtain environmental data of the target operation area within a normal indicator range before obtaining the first judgment result, and store the environmental data in a preset database; Determine the prerequisites for the occurrence of fire in the target operation area, and determine the change value of the environmental data according to the prerequisites; An initial model is constructed using the environmental data, and the prerequisites for the occurrence of fire in the target operation area and the change values ​​of the environmental data are used as inputs of the model to train the initial model to obtain a fire abnormality prediction model; The abnormal fire situation prediction model is tested using sample data, and the accuracy of the abnormal fire situation prediction model is determined based on the test results.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which implements the steps of the method according to any one of claims 6 to 8 when executed by a processing device.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processing device, the steps of the method according to any one of claims 5 to 7 are implemented.

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