Emergency exercise intelligent management and control system and method for colored heavy metal safety standardization information

Abstract

This invention discloses an intelligent management and control system and method for emergency drills related to the standardization of safety information for non-ferrous heavy metals, belonging to the field of enterprise safety production and emergency management information technology. The invention includes: automatically generating emergency drill scenario data through a data model; generating drill plans for different positions based on pre-defined job-responsibility mapping relationships; pushing the plans and associated quantitative evaluation index system to training participants after an automated approval process; collecting multi-source data such as action trajectories, time consumption, and video footage in real time during the drill execution phase; integrating and analyzing the collected data based on the approved index system and automatically generating a quantitative evaluation report; and automatically collecting all electronic data throughout the process to form a traceable digital archive. This invention achieves a fully digital and intelligent closed-loop management of emergency drills from scenario construction to evaluation and archiving, significantly improving the relevance, standardization, and objective evaluation capabilities of drills, and effectively ensuring the enterprise's emergency response level for safety production.

Description

Technical Field

[0001] This invention relates to the field of enterprise safety production and emergency management information technology, specifically to an intelligent control system and method for emergency drills of non-ferrous heavy metal safety standardization information. Background Technology

[0002] In industries such as non-ferrous heavy metal smelting, high temperatures, high pressures, toxic and hazardous substances, and flammable and explosive materials coexist, making emergency drills a crucial step in improving companies' ability to respond to emergencies and ensuring employee safety. Currently, most companies still rely on traditional models for emergency drill management, including manual organization, paper records, and offline coordination.

[0003] The aforementioned traditional model has several inherent flaws: First, the design of exercise scenarios is simplistic and highly homogenized, making it difficult to simulate complex, multi-layered risk scenarios. This leads to employees exhibiting a "performance-oriented" tendency in the exercises, limiting the improvement of their practical skills. Second, the management process is rudimentary, with omissions and inconsistencies in time records easily occurring in the approval, training, and execution record stages of the exercise plan. This not only creates a disconnect between "actual compliance and recorded violations" but also poses compliance risks to government regulatory review. Third, the exercise process relies on manual recording, making key data prone to distortion or loss. Effectiveness evaluation mainly depends on subjective experience, lacking objective quantitative evidence and making it difficult to scientifically measure the applicability of the plan. Finally, the rectification of problems discovered during the exercises is delayed, and the optimization of the plan lacks data support, failing to form an effective closed-loop management and iteration mechanism.

[0004] Therefore, there is an urgent need for an emergency drill solution that can achieve full-process digital and intelligent management and control to solve the above-mentioned problems of traditional methods and effectively improve the emergency response capabilities of enterprises. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent management and control system and method for emergency drills of non-ferrous heavy metal safety standardization information, so as to solve the above-mentioned problems existing in the prior art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information includes the following steps: S1: Based on the enterprise safety standardization information stored in the database, emergency drill scenario data containing at least one multi-layered risk superposition scenario is automatically generated through the data model, and the scenario data is stored in the contingency plan database; S2: Retrieve scenario data from the contingency plan library to generate an initial exercise plan, and generate corresponding protection learning materials based on the risk types contained in the scenario data. Differentiate the initial plan according to the preset job-responsibility mapping relationship to generate job-specific exercise plans corresponding to different jobs. S3: Based on the predefined organizational approval process, the job-specific drill plan and the associated quantitative evaluation index system are pushed to the corresponding user terminals for approval, and the approval operation behavior and the corresponding precise timestamp are recorded to generate an approval process record; S4: After approval, the approved job-specific drill plan and the protective learning materials will be pushed to the participants' terminals and electronic check-in data will be recorded. S5: During the execution phase of the exercise, the movement trajectory data of the participants, the time consumption data of each handling step, and the video data of the exercise process are collected through the pre-set positioning module, timer and video acquisition module. S6: Call the approved quantitative evaluation index system to perform fusion analysis on the collected action trajectory data, time consumption data and image data, and automatically generate an evaluation report containing quantitative scores and problem diagnosis through image processing technology; S7: Based on the assessment report, automatically generate an electronic rectification notice and push it to the terminal of the designated person in charge, track the rectification progress, and complete the closed-loop record after receiving the rectification feedback evidence; S8: Automatically collect all electronic data and documents from S1 to S7, associate and encrypt them according to timeline and business logic, and store them in the database to form a traceable digital archive of the exercise.

[0007] Furthermore, the enterprise safety standardization information mentioned in S1 includes job operation procedures, equipment and facility operating parameters, process flow diagrams, and historical accident data.

[0008] Furthermore, the differentiation process described in S2 generates specific operation instructions and task objectives corresponding to the responsibilities of different positions based on the preset job-responsibility mapping relationship.

[0009] Furthermore, the quantitative score mentioned in S6 is calculated based on quantitative parameters, which include at least one of the following: deviation of personnel action route, time consumption compliance rate of handling process, and standardization rate of operation actions.

[0010] Furthermore, the deviation of the personnel's movement route is calculated using the following formula: Deviation = (Actual route length - Standard route length) / Standard route length × 100%.

[0011] Another objective of this invention is to provide an intelligent management and control system for emergency drills of non-ferrous heavy metal safety standardization information. When the system is executed, it implements the aforementioned intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information, comprising: processor; A memory on which computer programs are stored; In addition, a database, a positioning module, a timer, and a video acquisition module are communicatively connected to the processor; When the processor executes the computer program, it controls the system to implement the intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information.

[0012] Furthermore, the processor, by executing the computer program, implements the following functional modules: The intelligent scenario generation module is used to generate emergency drill scenario data through data models; The scheme management module is used to generate and differentiate the training schemes for different job positions; The approval control module is used to manage the approval process and generate approval process records; The training management module is used to push materials to specific groups and record electronic attendance data. The data acquisition and control module is used to control the positioning module, timer, and video acquisition module to acquire data. The assessment and analysis module is used to integrate and analyze data and generate assessment reports; The rectification tracking module is used to track the rectification process in a closed loop. The data archiving module is used to collect and encrypt the data throughout the entire process to form digital archives.

[0013] Furthermore, the evaluation and analysis module is configured to perform image recognition analysis on the image data, specifically to automatically identify whether the operation actions are standardized from the images acquired by the video acquisition module, and use the recognition results as the basis for generating the evaluation report.

[0014] Another objective of this invention is to provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the aforementioned intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information.

[0015] The intelligent management and control system and method for emergency drills of non-ferrous heavy metal safety standardization information provided by this invention have the following advantages compared with the prior art: Comprehensive improvement of compliance and traceability: Through automated approval and archiving, the problems of approval omissions, record time discrepancies and chaotic paper document management in the traditional model have been completely solved, forming an immutable full-process electronic traceability chain that fully meets the compliance requirements of government supervision. Significantly enhances the practical effectiveness of drills: Based on intelligent scenario generation technology, it is possible to design complex scenarios that are realistic and contain multiple layers of overlapping risks, effectively avoiding the phenomenon of "drills outweighing training" caused by a single scenario, and enabling employees to substantially improve their practical emergency response capabilities. Achieving objective and quantitative assessment and optimization: The system automatically collects and analyzes objective data such as action routes and response times, replacing traditional subjective experience-based assessments and making the effectiveness of drills quantifiable. For example, indicators such as personnel action route deviation and response time compliance rates provide scientific data support for the precise optimization of contingency plans. An efficient management loop was established: A rectification and tracking mechanism ensured that problems identified during drills were addressed promptly and effectively, driving continuous iteration and optimization of the emergency management system. The entire system significantly reduced the cost of manual communication, shortening data retrieval time from hours to minutes, achieving a dual improvement in compliance and efficiency. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0018] This embodiment provides an intelligent management and control system for emergency drills of non-ferrous heavy metal safety standardization information, including: a processor; a memory storing a computer program thereon; and a database, a positioning module, a timer, and a video acquisition module communicatively connected to the processor; wherein, when the processor executes the computer program, it controls the system to implement the intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information.

[0019] The processor, by executing the computer program, implements the following software functional modules, including: The intelligent scenario generation module is used to generate emergency drill scenario data through data models; The scheme management module is used to generate and differentiate the training schemes for different job positions; The approval control module is used to manage the approval process and generate approval process records; The training management module is used to push materials to specific groups and record electronic attendance data. The data acquisition and control module is used to control the positioning module, timer, and video acquisition module to acquire data. The assessment and analysis module is used to integrate and analyze data and generate assessment reports; The rectification tracking module is used to track the rectification process in a closed loop. The data archiving module is used to collect and encrypt the data throughout the entire process to form digital archives.

[0020] The evaluation and analysis module is configured to perform image recognition analysis on the image data. Specifically, it is used to automatically identify whether the operation actions are standardized from the images acquired by the video acquisition module, and use the recognition results as the basis for generating the evaluation report.

[0021] In one specific embodiment, the control system's hardware foundation includes, but is not limited to: one or more application servers (serving as the core carrier of the processor), a database server (for building the database), network equipment, and various terminals and sensing devices. Terminal devices include personal computers, smartphones, or tablets (collectively referred to as user terminals) used by approvers, managers, and participants. Key sensing devices include: Positioning module: UWB (Ultra-Wideband) indoor precision positioning base stations and tags, or GPS / BeiDou positioning modules, can be used to track the location of people in real time.

[0022] Timer: A high-precision clock built into the system, used to record the time consumed in each stage.

[0023] Video capture module: including fixed network cameras deployed at key nodes in the factory area, and mobile explosion-proof surveillance cameras that can be temporarily deployed, for recording the entire exercise footage.

[0024] The system software runs on a server operating system (such as Linux or Windows Server) and adopts a B / S (Browser / Server) or C / S (Client / Server) architecture. The computer program (i.e., the system software) is stored in the server's memory (such as a hard disk or solid-state drive), and when the program is loaded and executed by a processor (such as a CPU), the following methods are implemented.

[0025] This embodiment also provides an intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information. The system implements this management and control method during execution, such as... Figure 1 As shown, it includes: S1: Based on the enterprise safety standardization information stored in the database, emergency drill scenario data containing at least one multi-layered risk superposition scenario is automatically generated through the data model, and the scenario data is stored in the contingency plan database; S2: Retrieve scenario data from the contingency plan library to generate an initial exercise plan, and generate corresponding protection learning materials based on the risk types contained in the scenario data. Differentiate the initial plan according to the preset job-responsibility mapping relationship to generate job-specific exercise plans corresponding to different jobs. S3: Based on the predefined organizational approval process, the job-specific drill plan and the associated quantitative evaluation index system are pushed to the corresponding user terminals for approval, and the approval operation behavior and the corresponding precise timestamp are recorded to generate an approval process record; S4: After approval, the approved job-specific drill plan and the protective learning materials will be pushed to the participants' terminals and electronic check-in data will be recorded. S5: During the execution phase of the exercise, the movement trajectory data of the participants, the time consumption data of each handling step, and the video data of the exercise process are collected through the pre-set positioning module, timer and video acquisition module. S6: Call the approved quantitative evaluation index system to perform fusion analysis on the collected action trajectory data, time consumption data and image data, and automatically generate an evaluation report containing quantitative scores and problem diagnosis through image processing technology; S7: Based on the assessment report, automatically generate an electronic rectification notice and push it to the terminal of the designated person in charge, track the rectification progress, and complete the closed-loop record after receiving the rectification feedback evidence; S8: Automatically collect all electronic data and documents from S1 to S7, associate and encrypt them according to timeline and business logic, and store them in the database to form a traceable digital archive of the exercise.

[0026] The eight steps of the method described in this invention form a tightly connected, data-driven organic whole, and its specific implementation and coordination mechanism are as follows.

[0027] I. Based on the enterprise safety standardization information stored in the database, emergency drill scenario data, which includes at least one multi-layered risk scenario, is automatically generated through a data model, and the scenario data is stored in the contingency plan database. The enterprise safety standardization information refers to standardized data formed in the enterprise's safety production management, including but not limited to job operation procedures, real-time operating parameters of equipment and facilities, process flow diagrams, and historical accident data.

[0028] The intelligent scene generation module accesses the database through a data interface service to obtain multi-dimensional enterprise safety standardization information. This information is not only static parameters, but also dynamically updated: equipment and facility operating parameters are obtained in real time from DCS (Distributed Control System) and SCADA (Supervisory Control and Data Acquisition System), such as electrolytic cell current density and temperature; the process flow diagram is a dynamic P&ID diagram, including all valve and instrument tag numbers; and historical accident data is structured and classified using natural language processing technology.

[0029] A data model refers to a computer model built using machine learning algorithms (such as random forests and Bayesian networks) to automatically generate multi-layered risk chain evolution scenarios based on input information. The built-in data model of the module can be implemented in various ways; in a preferred embodiment, it is a risk superposition model based on the random forest algorithm. The model's construction and training process includes: first, extracting feature variables, such as equipment temperature, pressure thresholds, and historical failure frequencies, from historical accident data and equipment operation logs in the database as model input; second, having safety experts label a large number of potential risk scenarios to form a training sample set; and finally, using the random forest algorithm to train the sample set to generate a model that can predict multi-layered risk chain evolution. This model first uses NLP (Natural Language Processing) technology to parse the operating procedure text, identifying key actions and risk points; then, it performs correlation analysis with real-time equipment parameters to calculate the probability of equipment failure; finally, it uses a Bayesian network to simulate how various initial events (such as "pipeline rupture") trigger secondary and derivative events (such as "toxic gas diffusion" and "fire") through process cascading, thereby dynamically generating multi-layered risk superposition scenarios.

[0030] This process achieves a cognitive leap from "single-point static risk" to "chain-like dynamic risk". By mining deep-seated risk correlations through algorithms, it greatly enhances the complexity and realism of the scenario, enabling the exercise preparation to cope with extremely complex situations.

[0031] Second, scenario data is retrieved from the contingency plan library to generate an initial drill plan. Based on the risk types contained in the scenario data, corresponding protective learning materials are generated. The initial plan is then differentiated according to a pre-defined job-responsibility mapping relationship to generate sub-job drill plans corresponding to different jobs. This differentiation process, based on the pre-defined job-responsibility mapping relationship, generates specific operational instructions and task objectives corresponding to the responsibilities of different jobs.

[0032] The scenario management module, after retrieving the generated scenario data from the contingency plan library, does not simply fill in templates. Based on a constructed emergency knowledge graph, it automatically generates an initial drill plan containing causal logic chains (e.g., first addressing the leak point, then evacuating personnel, and finally conducting environmental monitoring). Subsequently, the module performs in-depth differentiation processing based on a pre-set job-responsibility mapping relationship extended from the Role Access Control (RBAC) model. For example, the sub-plan generated for the "safety officer" focuses on "risk area delineation and monitoring equipment deployment," while the sub-plan generated for the "operator" specifies the precise instruction to "close valve A123 and start the emergency pump." Simultaneously, based on the risk types identified in the scenario data, the system uses a content tagging system to intelligently associate, assemble, and even dynamically generate protective learning materials from a multimedia resource library. For example, for the risk of "sulfuric acid burns," it automatically generates a learning package containing first-aid animations, expert explanation videos, and interactive quizzes.

[0033] This enables the structuring and calculability of emergency knowledge, ensuring the accurate transformation from macro-level plans to micro-level operational instructions. The training content is highly targeted and effectively improves the specialized handling capabilities of personnel in different positions.

[0034] Third, according to the predefined organizational approval process, the job-specific exercise plan and the associated quantitative evaluation index system are pushed to the corresponding user terminals for approval, and the approval operation behavior and the corresponding precise timestamp are recorded to generate an approval process record.

[0035] The core of the approval control module is a configurable workflow engine. Based on a predefined organizational approval process (configurable graphically via drag-and-drop), it treats the job-specific training plan generated in step two and its associated quantitative evaluation index system (pre-set by experts based on regulations and best practices during system initialization and iteratively optimized based on historical training data) as a complete approval package. The system automatically and concurrently pushes approval tasks to the corresponding approvers' user terminals via a message middleware (such as RabbitMQ) and sets timeout reminders. Every approval operation (approval, rejection, modification comments) is recorded, accompanied by a digital signature and precise timestamp, forming an immutable log. This not only automates the approval process but, more importantly, places the confirmation of "evaluation standards" at the approval stage, ensuring the authority and standardization of subsequent evaluations. This process design eliminates the pain points of "vague evaluation standards and subsequent disputes," laying a legitimate foundation for data-driven evaluation.

[0036] 4. After approval, the approved drill plan for each position and the protective learning materials will be pushed to the terminals of the participants and electronic check-in data will be recorded.

[0037] Once approved, the training management module precisely pushes the approved exercise plan and personalized learning materials to participants through the enterprise's unified portal or mobile app. To enhance training effectiveness, the system supports online learning, simulated operations, and online examinations. After completing the training, participants' electronic attendance data (including learning duration, exam scores, attendance location, and time) generates a hash value and is optionally stored in a blockchain-based evidence storage system to ensure the authenticity and non-repudiation of participation records. This utilizes technology to transform traditional "soft requirements" into "hard constraints," effectively guaranteeing the quality and participation of training and providing irrefutable evidence for subsequent accountability.

[0038] V. During the execution phase of the exercise, the movement trajectory data of the participants, the time consumption data of each handling step, and the video data of the exercise process are collected through the pre-set positioning module, timer and video acquisition module.

[0039] After the exercise command is issued, the data acquisition and control module, through an integrated IoT platform, uniformly schedules various sensing devices. The positioning module (UWB / GPS) uploads personnel trajectories in real time at a frequency of 1Hz; timers automatically stamp key action nodes (such as "alarm received," "on-site handling begins," and "handling completed"); and the video acquisition module deployed on-site transmits high-definition images in real time through a streaming media server. All data is tagged with a unified exercise ID and timestamp and fed into a data lake for preprocessing via the Enterprise Service Bus (ESB). This process constructs a "seamless" data acquisition environment, minimizing human interference with the exercise process, ensuring the original objectivity of the data, and providing rich data sources for building digital twin exercise scenarios.

[0040] 6. Using the approved quantitative evaluation index system, the collected action trajectory data, time consumption data and image data are fused and analyzed, and an evaluation report containing quantitative scores and problem diagnosis is automatically generated through image processing technology.

[0041] The evaluation and analysis module is the "brain" of the system. It calls upon the approved quantitative evaluation indicator system from step three to perform fusion analysis on the multi-source data imported into the data lake in step five. The quantitative evaluation indicator system refers to a set of calculation rules for quantitatively scoring exercise performance, consisting of multiple preset evaluation parameters and their respective weights. This quantitative evaluation indicator system is configured by the administrator during system initialization, and its core includes evaluation items, weights, and thresholds. For example, it can be set to 'personnel movement route deviation' (weight 30%, threshold < 15%), 'handling process time compliance rate' (weight 40%, threshold > 90%), and 'operational action standardization rate' (weight 30%, threshold > 95%). The comprehensive quantitative score is calculated by multiplying the scores of each evaluation item by their weights and then summing them. Its core technologies include: 1) Image recognition and analysis: Utilize deep learning models (such as YOLO or CNN algorithms) to perform real-time analysis of video streams, automatically identify the wearing status of safety helmets, protective clothing, respirators, etc., and whether personnel's actions are standardized; 2) Spatial path analysis: Calculate the deviation of personnel's movement routes and compare it with the optimal path; 3) Time series analysis: Check whether the time consumption data of each step exceeds the preset threshold.

[0042] The quantitative score is calculated based on quantitative parameters, which include at least one of the following: deviation from personnel movement routes, time-based compliance rate in handling procedures, and standardization rate of operational actions. Specifically: Personnel Route Deviation: This parameter is used to assess whether the route selection of participating personnel during emergency response is optimal. The system pre-stores standard action routes based on the factory layout map and emergency plan. The formula for calculating the deviation is: Deviation = (Actual route length - Standard route length) / Standard route length × 100%; The closer this value is to zero, the more closely the action path conforms to the preset optimal plan. For example, a calculated deviation of 15% means that the person's actual route was 15% longer than the standard route.

[0043] Handling Time Compliance Rate: This parameter is used to assess the response efficiency of each key handling step. The system presets standard time thresholds for each handling step (such as "alarm confirmation," "personnel evacuation," and "leak control"). The compliance rate is calculated for a single step or the entire process. For example, for a drill containing 5 steps, if the actual time of 4 of the steps is within the standard threshold, the overall time compliance rate is (4 / 5) × 100% = 80%.

[0044] Operational Action Compliance Rate: This parameter is used to evaluate whether the specific operational actions of the participants comply with safety procedures. The judgment is primarily based on image recognition analysis of video data. The system uses a trained deep learning model to identify key actions in the video stream, such as "whether safety protective equipment is worn correctly," "whether operating tools are used according to regulations," and "whether emergency response actions are standard." The compliance rate can be calculated as follows: Standardization rate = (Number of standardized actions identified / Total number of key actions identified) × 100%.

[0045] Finally, the evaluation and analysis module uses a preset weighting model to weight and fuse one or more selected quantitative parameter values ​​to generate a comprehensive quantitative score. For example, route deviation can be assigned a weight of 30%, time completion rate a weight of 40%, and operational action standardization rate a weight of 30%, and the total score is obtained through weighted calculation.

[0046] The module integrates all analysis results and generates not only an overall quantitative score, but also a detailed "diagnostic report" that points out specific problems such as "Personnel A failed to evacuate according to the prescribed route in the 3rd minute" and "Emergency response in Area B was delayed by 15 seconds".

[0047] The evaluation process has been upgraded from "outcome evaluation" to "process diagnosis," which can not only discover "how well it was done," but also accurately pinpoint "where the problems are" and "why the problems occurred," providing extremely accurate data support for subsequent optimization.

[0048] 7. Based on the assessment report, automatically generate an electronic rectification notice and push it to the terminal of the designated person in charge, track the rectification progress, and complete the closed-loop record after receiving rectification feedback evidence.

[0049] The rectification tracking module automatically creates a rectification task item for each issue generated in step six, generates an electronic rectification notification, and pushes it to the designated responsible person through the workflow. The system has a built-in Kanban board similar to a project management tool, which intuitively displays the rectification progress (pending, in progress, pending verification, completed). The responsible person needs to upload rectification evidence (such as revised procedures, training records, and on-site rectification photos). The module supports the verification and evaluation of the rectification effect. Only when the verification is passed will the system complete the closed-loop recording of the issue and feed the relevant data back to the contingency plan library and evaluation indicator model for optimizing future scenario design and evaluation standards. By implementing the PDCA (Plan-Do-Check-Act) cycle concept into a digital tool, a complete closed loop of "identifying problems - analyzing problems - solving problems - verifying effects - knowledge accumulation" is formed, truly driving the continuous evolution of the emergency management system.

[0050] 8. Automatically collect all electronic data and documents from step one to step seven, associate and encrypt them according to timeline and business logic, and store them in the database to form a traceable digital archive of the exercise.

[0051] The data archiving module acts like an intelligent archivist. Utilizing big data indexing technology (such as Elasticsearch), it automatically aggregates all heterogeneous data (structured approval workflows, unstructured videos, and semi-structured assessment reports) generated throughout the entire process from step one to step seven. The module automatically classifies, tags, associates, and encrypts the data according to a multi-dimensional tagging system based on "exercise event - timestamp - data type" (using the national cryptographic algorithm SM4), ultimately generating a complete, rapidly searchable, and deeply analyzable digital archive of the exercises. Authorized users can search using natural language, such as "find all exercises in the past six months involving 'leakage' risk and with an assessment score below 80," and the system returns results within seconds. Beneficial effects: Transforming scattered, dormant data assets into structured, reusable organizational knowledge significantly improves the efficiency of emergency response knowledge accumulation, retrieval, and utilization, providing strong data support for strategic decision-making and compliance auditing.

[0052] This embodiment provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the aforementioned intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information.

[0053] In summary, this invention constructs an end-to-end intelligent control closed loop. Its core advantage lies in the deep integration of IoT sensing, big data analytics, and artificial intelligence algorithms with safety management practices. It transforms the traditional emergency drill management model, reliant on personal experience and paper records, into a new digital model driven by data, automated execution, intelligent analysis, and continuous optimization. This not only significantly improves the effectiveness of drills and the enterprise's emergency response capabilities but also fundamentally reshapes the paradigm of safety management, providing a solid technical guarantee for the high-quality safety development of enterprises.

[0054] Embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of one or more computer-usable storage media (including, but not limited to, disk storage, etc.) containing computer-usable program code. CD - ROM It takes the form of a computer program product implemented on (such as optical memory, etc.).

[0055] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0056] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0057] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0058] Contents not described in detail in this specification are prior art known to those skilled in the art. It is hereby indicated that the above description is intended to help those skilled in the art understand this invention, but does not limit the scope of protection of this invention. Any equivalent substitutions, modifications, improvements, or simplifications of the above descriptions that do not depart from the essential content of this invention fall within the scope of protection of this invention.

Claims

1. A method for intelligent management and control of emergency drills for standardized safety information of non-ferrous heavy metals, characterized in that, Includes the following steps: S1: Based on the enterprise safety standardization information stored in the database, emergency drill scenario data containing at least one multi-layered risk superposition scenario is automatically generated through the data model, and the scenario data is stored in the contingency plan database; S2: Retrieve scenario data from the contingency plan library to generate an initial exercise plan, and generate corresponding protection learning materials based on the risk types contained in the scenario data. Based on the preset job-responsibility mapping relationship, perform differentiated processing on the initial plan to generate job-specific exercise plans corresponding to different jobs. S3: Based on the predefined organizational approval process, the job-specific drill plan and the associated quantitative evaluation index system are pushed to the corresponding user terminals for approval, and the approval operation behavior and the corresponding precise timestamp are recorded to generate an approval process record; S4: After approval, the approved job-specific drill plan and the protective learning materials will be pushed to the participants' terminals and electronic check-in data will be recorded. S5: During the execution phase of the exercise, the movement trajectory data of the participants, the time consumption data of each handling step, and the video data of the exercise process are collected through the pre-set positioning module, timer and video acquisition module. S6: Call the approved quantitative evaluation index system to perform fusion analysis on the collected action trajectory data, time consumption data and image data, and automatically generate an evaluation report containing quantitative scores and problem diagnosis through image processing technology; S7: Based on the assessment report, automatically generate an electronic rectification notice and push it to the terminal of the designated person in charge, track the rectification progress, and complete the closed-loop record after receiving the rectification feedback evidence; S8: Automatically collect all electronic data and documents from S1 to S7, associate and encrypt them according to timeline and business logic, and store them in the database to form a traceable digital archive of the exercise.

2. The intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information according to claim 1, characterized in that, The enterprise safety standardization information mentioned in S1 includes job operation procedures, equipment and facility operating parameters, process flow diagrams, and historical accident data.

3. The intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information according to claim 1, characterized in that, The differentiation process described in S2 generates specific operation instructions and task objectives corresponding to the responsibilities of different positions based on the preset job-responsibility mapping relationship.

4. The intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information according to claim 1, characterized in that, The quantitative score mentioned in S6 is calculated based on quantitative parameters, which include at least one of the following: deviation of personnel action route, time consumption rate of handling process, and standardization rate of operation actions.

5. The intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information according to claim 4, characterized in that, The deviation of the personnel's movement route is calculated using the following formula: Deviation = (Actual route length - Standard route length) / Standard route length × 100%.

6. An intelligent management and control system for emergency drills of non-ferrous heavy metal safety standardization information, characterized in that, When the system is executed, it implements the emergency drill intelligent control method for non-ferrous heavy metal safety standardization information as described in any one of claims 1-5, including: processor; A memory on which computer programs are stored; In addition, a database, a positioning module, a timer, and a video acquisition module are communicatively connected to the processor; When the processor executes the computer program, it controls the system to implement the intelligent management and control method for emergency drills of non-ferrous heavy metal safety standardization information.

7. The emergency drill intelligent control system for non-ferrous heavy metal safety standardization information as described in claim 6, characterized in that, The processor executes the computer program to implement the following functional modules: The intelligent scenario generation module is used to generate emergency drill scenario data through data models; The scheme management module is used to generate and differentiate the training schemes for different job positions; The approval control module is used to manage the approval process and generate approval process records; The training management module is used to push materials to specific groups and record electronic attendance data. The data acquisition and control module is used to control the positioning module, timer, and video acquisition module to acquire data. The assessment and analysis module is used to integrate and analyze data and generate assessment reports. The rectification tracking module is used to track the rectification process in a closed loop. The data archiving module is used to collect and encrypt the data throughout the entire process to form digital archives.

8. The intelligent control system for emergency drills of non-ferrous heavy metal safety standardization information according to claim 7, characterized in that, The evaluation and analysis module is configured to perform image recognition analysis on the image data. Specifically, it is used to automatically identify whether the operation actions are standardized from the images acquired by the video acquisition module, and use the recognition results as the basis for generating the evaluation report.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the emergency drill intelligent management and control method for non-ferrous heavy metal safety standardization information as described in any one of claims 1-5.

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