Construction site emergency management method, device and equipment based on micro-service architecture and medium

Abstract

The present application relates to the technical field of emergency management, and discloses a construction site emergency management method based on a micro-service architecture, comprising: obtaining historical event data and constructing a dynamic digital plan library; based on the modular system framework, applying the dynamic digital plan library to the corresponding module to construct a structured event matching rule; when an emergency event exists, determining the required emergency equipment and computing resources according to the structured event matching rule to generate an elastic resource management instruction; obtaining data cockpit resources, integrating the data cockpit resources based on the modular system framework to generate a full-dimensional state visualization view of the construction site; obtaining double-blind drilling data and emergency response records, finding problems existing in the AI model and the plan logic, and performing emergency management. The present application also proposes a construction site emergency management device, equipment and storage medium based on the micro-service architecture. The present application can improve the risk response speed.

Description

Technical Field

[0001] The present invention relates to the field of emergency management technology, and in particular to a construction site emergency management method, device, equipment and medium based on a microservice architecture. Background Art

[0002] With the rapid advancement of smart construction sites and the increasing requirements for construction safety management, construction site emergency management is placing higher demands on intelligent, real-time, and collaborative response capabilities. The dynamic construction environment and complex safety risk scenarios require emergency management systems that can rapidly integrate multi-source data, accurately match response plans, and achieve flexible resource allocation. However, traditional construction site emergency management relies heavily on manual experience and static plans, resulting in core issues such as poor data flow, low response efficiency, and unbalanced resource allocation.

[0003] While existing information systems have incorporated digital tools, they generally suffer from high system coupling, insufficient modularity, and a lack of closed-loop optimization mechanisms, making them unable to meet the emergency management needs of complex construction scenarios. For example, microservice architectures and containerized deployment technologies are not fully applied to emergency scenarios, limiting system scalability. AI models and dynamic emergency plan libraries lack real-time data-driven iterative optimization, hindering the continuous improvement of emergency response accuracy. Summary of the Invention

[0004] The present invention provides a construction site emergency management method, device, equipment and medium based on a microservice architecture, the main purpose of which is to improve risk response speed.

[0005] To achieve the above objectives, the present invention provides a construction site emergency management method based on a microservice architecture, comprising:

[0006] Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy.

[0007] Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library;

[0008] Based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules;

[0009] When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions;

[0010] Acquire data cockpit resources, integrate them using the modular system framework based on the data cockpit resources, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional status visualization view of the construction site;

[0011] Obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0012] Optionally, the microservice architecture and containerized deployment solution are designed based on the preset construction site emergency management requirements to obtain a modular system framework and resource scheduling strategy, including:

[0013] Split the construction site emergency management requirements, obtain independent functional modules in the construction site emergency management requirements, and clarify the interaction relationship between each functional module to obtain a functional module list and a module interaction relationship diagram;

[0014] Select the corresponding microservice design pattern based on the functional module list and module interaction diagram, and define the service boundary of each functional module to obtain a service boundary definition document;

[0015] Design a RESTful API based on the service boundaries of the functional modules to obtain API design data;

[0016] Based on the API design data and service boundary definition document, Docker is selected as the containerization tool, and the preset Kubernetes cluster is used for container orchestration to obtain a modular system framework and resource scheduling strategy.

[0017] Optionally, the method of training a preset AI model using the historical event data in combination with the resource scheduling strategy to construct a dynamic digital emergency plan library includes:

[0018] Extracting event-related data from the historical event data to obtain a historical event data set, and collecting sensor data in real time through a preset Internet of Things device to obtain real-time sensor data, and integrating the real-time sensor data to obtain a real-time sensor data stream;

[0019] Cleaning and normalizing the historical event dataset and the real-time sensor data stream, and extracting key features of the historical event dataset and the real-time sensor data stream to obtain a cleaned dataset and a feature vector, wherein the key features include event type, event sequence, and spatial location;

[0020] Construct historical data based on the cleaned dataset and feature vectors, and use the historical data to train the AI ​​model, optimize the model parameters, and perform incremental training using real-time sensor data to obtain a trained model;

[0021] By training the model, the preset general emergency plan process is decomposed, key nodes are extracted, and the development trend and impact range of events are predicted. The plan library is constructed to obtain a dynamic digital plan library.

[0022] Optionally, based on the modular system framework, applying the dynamic digital plan library to the module corresponding to the dynamic digital plan library to construct structured event matching rules includes:

[0023] Extracting event features and plan processes from the dynamic digital plan library based on the modular system framework, extracting real-time monitoring data and response strategies from a preset intelligent response engine, and cleaning and structuring preset historical event data to obtain structured event feature data and plan process data;

[0024] Based on structured event feature data and plan process data, the preset AI model is used to perform pattern recognition on event features, extract key features, and construct event feature vectors;

[0025] An event matching rule is generated based on the event feature vector and the plan process data, and a trigger condition and a response strategy are defined to obtain a structured event matching rule.

[0026] Optionally, when an emergency event occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and a preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions, including:

[0027] Determine the required emergency equipment and computing resources based on the structured event matching rules, install and configure the Kubernetes cluster, and ensure that Docker is installed on each node to obtain a configured Kubernetes cluster;

[0028] Obtain a Docker image and deploy a Docker container using the configured Kubernetes cluster to obtain a deployed Docker container;

[0029] Set resource requests and resource limits in the preset Pod configuration to obtain the configured Pod resource requirements;

[0030] According to the Pod resource requirement adjustment completed configuration, the deployed Docker container is adjusted, and the instruction content for automatically expanding or reducing the deployed Docker container is obtained, and the elastic resource management instruction is obtained.

[0031] Optionally, after the required emergency equipment and computing resources are determined according to the structured event matching rule, the preset Kubernetes cluster is used to arrange the Docker container service, and the elastic resource management instruction is generated.

[0032] The business access request is obtained, and it is judged whether the user identity of the preset user passes according to the business access request;

[0033] If it passes, the business access request is responded;

[0034] If it does not pass, identity authentication redirection is performed, and unified identity authentication is performed, and it is judged whether the unified identity authentication passes;

[0035] If it passes, the identity authentication token is obtained;

[0036] If it does not pass, access is denied, and the step is ended.

[0037] Optionally, based on the data cockpit resource, the modular system framework is used for integration, and according to the elastic resource management instruction, the real-time state of resource allocation and emergency treatment is displayed, and the full-dimensional state visualization view of the construction site is generated, including:

[0038] The Internet of Things device data is obtained by using a preset sensor acquisition device to collect the running state and environmental parameters of the construction site, wherein the environmental parameters include dust, noise and water level;

[0039] Based on the safety event and progress deviation reported by the preset mobile terminal or broadcast, the safety event and construction progress input by the artificial are obtained, and the artificial reporting information is obtained.

[0040] The data cockpit resource, the Internet of Things device data and the artificial reporting information are integrated into the pre-constructed data cockpit platform, and data correlation and visualization processing are performed through BIM+GIS technology, and the fused construction site state data is obtained.

[0041] The key elements in the fused construction site state data are displayed in real time on the preset screen, and the full-dimensional state visualization view of the construction site is obtained.

[0042] In order to solve the above problems, the application also provides a construction site emergency management device based on a micro-service architecture, the device comprising:

[0043] The database construction module is used to design a microservice architecture and containerized deployment solution based on the preset construction site emergency management requirements, thereby obtaining a modular system framework and resource scheduling strategy.

[0044] Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library;

[0045] A management instruction generation module is used to apply the dynamic digital plan library to the module corresponding to the dynamic digital plan library based on the modular system framework to construct a structured event matching rule;

[0046] When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions;

[0047] A visual map generation module is used to obtain data cockpit resources, integrate the data cockpit resources using the modular system framework, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional visualization of the construction site status;

[0048] The emergency management module is used to obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0049] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0050] at least one processor; and,

[0051] a memory communicatively connected to the at least one processor; wherein,

[0052] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the construction site emergency management method based on the microservice architecture as described above.

[0053] In order to solve the above problems, the present invention also provides a computer-readable storage medium, including a data storage area and a program storage area, the data storage area stores created data, and the program storage area stores a computer program; it is characterized in that when the computer program is executed by a processor, it implements the construction site emergency management method based on the microservice architecture as described above.

[0054] The embodiment of the present invention constructs a dynamic digital emergency plan library by acquiring historical event data; based on the modular system framework, the dynamic digital emergency plan library is applied to the corresponding module to construct structured event matching rules; when an emergency event occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and elastic resource management instructions are generated; data cockpit resources are acquired, and based on the data cockpit resources, the modular system framework is used for integration to generate a full-dimensional status visualization view of the construction site; double-blind drill data and emergency response records are acquired, problems in the AI ​​model and the plan logic are found, and emergency management is performed. Therefore, the construction site emergency management method, device, electronic device and computer-readable storage medium based on the microservice architecture proposed in the present invention form a modular system framework by designing a microservice architecture and containerized deployment, build a dynamic emergency plan library and structured matching rules in combination with AI model training, use Kubernetes to achieve elastic resource scheduling, integrate the data cockpit to achieve full-dimensional visualization, and based on double-blind drills and emergency record closed-loop optimization, ultimately form an efficient, intelligent, flexibly scalable and continuously iterative construction site emergency management system, improve risk response speed and disposal accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a process flow of a construction site emergency management method based on a microservice architecture provided by one embodiment of the present invention;

[0056] Figure 2 A schematic diagram of a module of a construction site emergency management device based on a microservice architecture according to an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of the internal structure of an electronic device for implementing a construction site emergency management method based on a microservice architecture provided by one embodiment of the present invention.

[0058] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0059] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0060] The embodiment of the present application provides a construction site emergency management method based on a microservice architecture. The execution subject of the construction site emergency management method based on the microservice architecture includes but is not limited to at least one of the electronic devices such as the server and the terminal that can be configured to execute the method provided by the embodiment of the present application. Among them, the server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms. In other words, the construction site emergency management method based on the microservice architecture can be executed by software or hardware installed on a remote device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0061] Reference Figure 1 FIG. 1 is a flow chart of a construction site emergency management method based on a microservice architecture according to an embodiment of the present invention. In this embodiment, the construction site emergency management method based on a microservice architecture includes the following steps S1-S6:

[0062] S1. Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution are designed to obtain a modular system framework and resource scheduling strategy.

[0063] It is understandable that by designing a microservice architecture and containerized deployment solution based on the preset construction site emergency management needs, functional decoupling can be achieved through modular splitting, which can improve development efficiency and system maintainability and support on-demand expansion. With the help of containerization technology, environmental isolation and elastic resource scheduling can be achieved to ensure stable system operation under high concurrency and dynamically match the resource requirements of emergency scenarios. In combination with resource scheduling strategies, computing and equipment resource allocation can be optimized to shorten emergency response time and enhance real-time data processing. Ultimately, a flexible, scalable, efficient, stable and intelligent management system that can quickly respond to complex emergency scenarios is formed, which significantly improves the scientific nature and collaborative efficiency of construction site emergency management.

[0064] In an embodiment of the present invention, the construction site emergency management needs refer to a series of needs arising in the construction site scenario in order to effectively respond to various emergency situations, protect the lives of personnel, reduce property losses, and ensure the smooth progress of the project, specifically including risk monitoring and early warning needs, personnel safety management needs, emergency materials and equipment management needs, emergency response and command needs, data management and analysis needs, etc.

[0065] Microservices architecture is a software architectural style that splits a single application into multiple small, autonomous services. Each service is built around a specific business function, has independent development, deployment, and operation capabilities, and can collaborate with each other through lightweight communication mechanisms such as HTTP / REST and message queues.

[0066] In this embodiment of the present invention, the containerized deployment solution is a technical solution that packages an application and its dependencies into a single container unit, deploying and running it in different environments. In construction site emergency management systems, containerized deployment is typically implemented using container technologies such as Docker, combined with container orchestration tools such as Kubernetes for cluster management.

[0067] Furthermore, based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution are designed to obtain a modular system framework and resource scheduling strategy, including:

[0068] Split the construction site emergency management requirements, obtain independent functional modules in the construction site emergency management requirements, and clarify the interaction relationship between each functional module to obtain a functional module list and a module interaction relationship diagram;

[0069] Select the corresponding microservice design pattern based on the functional module list and module interaction diagram, and define the service boundary of each functional module to obtain a service boundary definition document;

[0070] Design a RESTful API based on the service boundaries of the functional modules to obtain API design data;

[0071] Based on the API design data and service boundary definition document, Docker is selected as the containerization tool, and the preset Kubernetes cluster is used for container orchestration to obtain a modular system framework and resource scheduling strategy.

[0072] In this embodiment, the functional module list breaks down the construction site emergency management system into independent, reusable modules based on business functions. This list includes module names, functional descriptions, inputs and outputs, and responsibility boundaries. Each module corresponds to a core emergency management task (such as data collection, emergency plan management, and resource scheduling), forming the foundation of microservices architecture design.

[0073] Among them, the module interaction relationship diagram refers to the description of the communication method, data flow and dependency relationship between modules in a graphical way (such as UML component diagram, flow chart), clarifying how modules work together through interfaces or message mechanisms.

[0074] S2. Obtain historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital plan library.

[0075] In an embodiment of the present invention, historical event data refers to the recorded data of various safety accidents, abnormal events and emergency response processes that occur at a construction site during the construction period, covering structured and unstructured information such as the time, location, type (such as fire, collapse, fall from height), triggering cause, scope of impact, response process, resource scheduling records, casualties and property losses.

[0076] Among them, the sources of historical event data include accident investigation reports, sensor monitoring logs (such as records of abnormal tower crane tilt angles), video surveillance recordings, manual reporting forms, emergency drill records, etc.

[0077] Furthermore, by extracting the "event type-response measures-handling effect" relationship in historical events (such as "foundation pit collapse → start rescue equipment A → take 30 minutes to complete personnel transfer"), training data is provided for the AI ​​model to support the construction of a dynamic digital plan library.

[0078] In this embodiment of the present invention, an AI model refers to an algorithmic model built using techniques such as machine learning and deep learning. It is used to analyze, predict, and make decisions based on historical event data and real-time sensor data, enabling intelligent construction site emergency management. In this solution, the AI ​​model focuses on event feature extraction, trend prediction, and emergency plan generation.

[0079] Furthermore, by training AI models, the "experiential knowledge" in historical events can be converted into quantifiable algorithmic logic (such as "when sensor data meets conditions A+B+C, trigger step Y of plan X"), supporting the intelligent generation and updating of a dynamic digital plan library.

[0080] In an embodiment of the present invention, a dynamic digital plan library refers to a system that converts traditional text-based emergency plans into a structured, automatically executable digital plan set based on the results of AI model training. It has the capabilities of real-time updating, intelligent matching, and dynamic adjustment, and can quickly generate targeted disposal plans based on real-time event characteristics.

[0081] In an embodiment of the present invention, the method of training a preset AI model using the historical event data in combination with the resource scheduling strategy to construct a dynamic digital emergency plan library includes:

[0082] Extracting event-related data from the historical event data to obtain a historical event data set, collecting sensor data in real time through a preset Internet of Things device to obtain real-time sensor data, and integrating the real-time sensor data to obtain a real-time sensor data stream;

[0083] The historical event data set and the real-time sensor data stream are cleaned and normalized, and key features of the historical event data set and the real-time sensor data stream are extracted, to obtain a cleaned data set and a feature vector, wherein the key features include event type, event sequence and spatial position.

[0084] Based on the cleaned data set and the feature vector, historical data is constructed, and an AI model is trained using the historical data, model parameters are optimized, and incremental training is performed through real-time sensor data, to obtain a trained model.

[0085] The trained model is used to flow the decomposition of the preset general emergency plan, extract key nodes, predict event development trend and influence range, construct a plan library, and obtain a dynamic digital plan library.

[0086] In the embodiment of the application, the historical event data set refers to the record data of safety accidents, abnormal events and emergency disposal processes that have occurred on the construction site in the past, which is formed into a structured data set after standardization processing. It is a digital abstraction of historical events, used to summarize emergency management experience and support AI model training and plan optimization.

[0087] The incremental training using real-time data can improve the adaptability of the model.

[0088] Further, the real-time sensor data stream refers to the real-time collection of site environment, equipment and personnel state data by Internet of Things devices (such as sensors, cameras, RFID tags, etc.), which is transmitted to the system in a continuous and high-frequency manner to form a dynamic data sequence for real-time risk monitoring and emergency response triggering.

[0089] S3, based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library, and a structured event matching rule is constructed.

[0090] The modular system framework refers to the splitting of a complex construction site emergency management system into multiple independent, reusable and loosely coupled modules according to business functions, technical logic or data processing processes. The modules interact and cooperate through standardized interfaces to form a systematic architecture that can be flexibly combined, expanded and replaced. The core is to divide the whole system into functionally cohesive and clearly defined module units through the design concept of "divide and conquer", each module focuses on solving specific problems (such as data collection, plan matching, resource scheduling, etc.), and finally realizes complete emergency management functions through module combination.

[0091] In an embodiment of the present invention, structured event matching rules convert the "event characteristics" and "handling plans" in construction site emergency management into a standardized, automatically executable set of logical conditions. Through clear input and output formats and trigger mechanisms, this allows for rapid and accurate matching of real-time events with emergency plans. At its core, this system uses AI models to extract patterns from historical events and features from real-time monitoring data, constructing a "condition-action" mapping relationship. This allows the system to automatically identify the event type, level, and impact range when an event occurs, and invoke the corresponding handling process. This serves as a key technical bridge connecting "intelligent monitoring" and "emergency response."

[0092] Furthermore, based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules, including:

[0093] Extracting event features and plan processes from the dynamic digital plan library based on the modular system framework, extracting real-time monitoring data and response strategies from a preset intelligent response engine, and cleaning and structuring preset historical event data to obtain structured event feature data and plan process data;

[0094] Based on structured event feature data and plan process data, the preset AI model is used to perform pattern recognition on event features, extract key features, and construct event feature vectors;

[0095] An event matching rule is generated based on the event feature vector and the plan process data, and a trigger condition and a response strategy are defined to obtain a structured event matching rule.

[0096] S4. When an emergency event occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate the Docker containerized service to generate elastic resource management instructions.

[0097] In this embodiment of the present invention, elastic resource management instructions refer to resource allocation and adjustment instructions automatically generated within the construction site emergency management system, leveraging the Kubernetes cluster's dynamic scheduling capabilities for Docker containerized microservices, combined with real-time event matching rules and system load. Core to this is the dynamic allocation of computing resources (CPU / memory), storage resources, network bandwidth, and emergency equipment resources through intelligent resource scheduling strategies. This ensures efficient operation of critical services and optimal resource utilization in emergency scenarios, while also preventing resource waste in non-emergency scenarios.

[0098] In an embodiment of the present invention, when an emergency event occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and a preset Kubernetes cluster is used to orchestrate the Docker containerized service to generate elastic resource management instructions, including:

[0099] Determine the required emergency equipment and computing resources based on the structured event matching rules, install and configure the Kubernetes cluster, and ensure that Docker is installed on each node to obtain a configured Kubernetes cluster;

[0100] Obtain a Docker image and deploy a Docker container using the configured Kubernetes cluster to obtain a deployed Docker container;

[0101] Set resource requests and resource limits in the preset Pod configuration to obtain the configured Pod resource requirements;

[0102] The deployed Docker container is adjusted according to the configured Pod resource requirements, and the instruction content for managing the deployed Docker container is automatically expanded or reduced to obtain elastic resource management instructions.

[0103] Furthermore, after determining the required emergency equipment and computing resources according to the structured event matching rules, orchestrating the Docker containerized service using a preset Kubernetes cluster, and generating elastic resource management instructions, the following steps may also be included:

[0104] Obtaining a service access request, and determining whether the user identity of the preset user is approved according to the service access request;

[0105] If approved, respond to the service access request;

[0106] If it fails, identity authentication redirection is performed, and identity authentication is performed uniformly to determine whether the unified identity authentication is passed;

[0107] If passed, get the identity authentication token;

[0108] If not, access is denied and the step ends.

[0109] An authentication token is a security credential used to verify the identity of a user or service. Essentially, it's an encrypted string of characters. In a construction site emergency management system, it represents the user's or service's identity and proves their access to specific resources (such as emergency command functions, sensitive data, and equipment control interfaces). By using a "one-time authentication, multiple-trust" mechanism, the token avoids repetitive password entry and ensures only authorized entities can perform operations. It is a core technical component for single sign-on (SSO) and secure cross-service communication.

[0110] S5. Acquire data cockpit resources, integrate them based on the data cockpit resources using the modular system framework, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional status visualization view of the construction site.

[0111] In this embodiment of the present invention, the data cockpit resource refers to the complete set of elements supporting the operation of the construction site emergency management system's data cockpit, including data assets, visualization tools, computing power, interactive components, and hardware facilities. It is the core vehicle for visualizing the full range of construction site status. By integrating multi-source data and providing real-time analysis and interaction capabilities, it provides an intuitive and efficient information display platform for emergency command and risk decision-making.

[0112] Furthermore, the data cockpit resources are integrated using the modular system framework, and according to the flexible resource management instructions, the real-time status of resource allocation and emergency response is displayed to generate a full-dimensional status visualization view of the construction site, including:

[0113] Utilize sensors at pre-set construction sites to collect equipment operating status and environmental parameters to obtain IoT device data, where the environmental parameters include dust, noise, and water level;

[0114] Based on the preset security events and progress deviations reported by mobile terminals or broadcasts, manually input security events and construction progress are obtained to obtain manually reported information;

[0115] Integrate the data cockpit resources, IoT device data, and manually reported information into the pre-built data cockpit platform, and perform data association and visualization through BIM+GIS technology to obtain integrated site status data;

[0116] The key elements of the integrated construction site status data are displayed in real time on a preset screen to obtain a visual view of the full-dimensional status of the construction site.

[0117] Among them, the key elements include "people, machines, materials, methods, and environment".

[0118] S6. Obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0119] In this embodiment of the present invention, double-blind drill data refers to the full-process recorded data generated by conducting emergency drills simulating sudden safety incidents (such as fire, collapse, and electric shock) on construction sites without prior notification of the drill time, location, or specific scenario. Its core purpose is to replicate the most realistic emergency response process through "blind drills" (participants are unaware of the drill details, and the command center is unaware of the actual on-site conditions). This data is used to expose system vulnerabilities, test the effectiveness of emergency plans, and verify the collaborative capabilities of personnel.

[0120] Furthermore, through cross-analysis of multi-source data, the "design flaws of simulated scenarios" and "handling loopholes of real accidents" are transformed into quantifiable improvement instructions, realizing the upgrade of emergency management from "experience-driven" to "data-driven".

[0121] The embodiment of the present invention constructs a dynamic digital emergency plan library by acquiring historical event data; based on the modular system framework, the dynamic digital emergency plan library is applied to the corresponding module to construct structured event matching rules; when an emergency event occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and elastic resource management instructions are generated; data cockpit resources are acquired, and based on the data cockpit resources, the modular system framework is used for integration to generate a full-dimensional status visualization view of the construction site; double-blind drill data and emergency response records are acquired, problems in the AI ​​model and the plan logic are found, and emergency management is performed. Therefore, the construction site emergency management method, device, electronic device and computer-readable storage medium based on the microservice architecture proposed in the present invention form a modular system framework by designing a microservice architecture and containerized deployment, build a dynamic emergency plan library and structured matching rules in combination with AI model training, use Kubernetes to achieve elastic resource scheduling, integrate the data cockpit to achieve full-dimensional visualization, and based on double-blind drills and emergency record closed-loop optimization, ultimately form an efficient, intelligent, flexibly scalable and continuously iterative construction site emergency management system, improve risk response speed and disposal accuracy.

[0122] like Figure 2 , which is a module diagram of a construction site emergency management device based on a microservice architecture according to the present invention.

[0123] The microservices-based construction site emergency management device 100 described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the microservices-based construction site emergency management device can include a database construction module 101, a management instruction generation module 102, a visual map generation module 103, and an emergency management module 104. The modules described in the present invention, also referred to as units, refer to a series of computer program segments that can be executed by an electronic device processor and perform fixed functions, and are stored in the electronic device's memory.

[0124] In this embodiment, the functions of each module / unit are as follows:

[0125] The database construction module 101 is used to design a microservice architecture and containerized deployment solution based on preset construction site emergency management requirements, and obtain a modular system framework and resource scheduling strategy;

[0126] Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library;

[0127] The management instruction generation module 102 is used to apply the dynamic digital plan library to the module corresponding to the dynamic digital plan library based on the modular system framework to construct a structured event matching rule;

[0128] When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions;

[0129] A visualization generating module 103 is configured to obtain data cockpit resources, integrate the data cockpit resources using the modular system framework, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional visualization of the construction site status;

[0130] The emergency management module 104 is used to obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0131] In detail, each module in the construction site emergency management device 100 based on the microservice architecture in the embodiment of the present invention is used in the same manner as above. Figure 1 The above-mentioned construction site emergency management method based on microservice architecture has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0132] like Figure 3, which is a structural diagram of an electronic device for implementing a construction site emergency management method based on a microservice architecture according to the present invention.

[0133] The electronic device may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a construction site emergency management program based on a microservice architecture.

[0134] In some embodiments, the processor 10 may be composed of an integrated circuit, such as a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and lines. It executes or executes programs or modules stored in the memory 11 (such as executing a construction site emergency management program based on a microservice architecture) and calls data stored in the memory 11 to perform various functions of the electronic device and process data.

[0135] The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Furthermore, the memory 11 may include both an internal storage unit of the electronic device and an external storage device. The memory 11 can be used not only to store application software and various types of data installed in the electronic device, such as the code of a construction site emergency management program based on a microservice architecture, but also to temporarily store data that has been output or is about to be output.

[0136] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. This bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0137] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0138] Figure 3 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 3 The structure shown does not limit the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0139] For example, although not shown, the electronic device may further include a power source (e.g., a battery) to power various components. Preferably, the power source may be logically connected to the at least one processor 10 via a power management device, thereby enabling functions such as charge management, discharge management, and power consumption management via the power management device. The power source may further include any of one or more DC or AC power sources, a recharging device, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like. The electronic device may also include various sensors, Bluetooth modules, Wi-Fi modules, and the like, which are not further detailed here.

[0140] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0141] The construction site emergency management program based on the microservice architecture stored in the memory 11 of the electronic device is a combination of multiple computer programs. When running in the processor 10, it can achieve the following:

[0142] Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy.

[0143] Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library;

[0144] Based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules;

[0145] When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions;

[0146] Acquire data cockpit resources, integrate them using the modular system framework based on the data cockpit resources, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional status visualization view of the construction site;

[0147] Obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0148] Specifically, the specific implementation method of the processor 10 for the above computer program can refer to Figure 1 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0149] Furthermore, if the module / unit integrated into the electronic device is implemented as a software functional unit and sold or used as a standalone product, it may be stored in a non-volatile computer-readable storage medium. The computer-readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0150] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0151] Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy.

[0152] Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library;

[0153] Based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules;

[0154] When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions;

[0155] Acquire data cockpit resources, integrate them using the modular system framework based on the data cockpit resources, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional status visualization view of the construction site;

[0156] Obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

[0157] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0158] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0159] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0160] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0161] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0162] Blockchain, as used in this article, refers to a novel application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each block contains information about a batch of online transactions, used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.

[0163] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, techniques, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results.

[0164] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. Second-order terms are used to indicate names and do not imply any particular order.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A construction site emergency management method based on microservice architecture, characterized in that: The method comprises: Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy. Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library; Based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules; When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions; Acquire data cockpit resources, integrate them using the modular system framework based on the data cockpit resources, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional status visualization view of the construction site; Obtain double-blind drill data and emergency response records, identify problems in the AI ​​model and plan logic based on the full-dimensional status visualization of the construction site, double-blind drill data, and emergency response records, and conduct emergency management; Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy, including: Split the construction site emergency management requirements, obtain independent functional modules in the construction site emergency management requirements, and clarify the interaction relationship between each functional module to obtain a functional module list and a module interaction relationship diagram; Select the corresponding microservice design pattern based on the functional module list and module interaction diagram, and define the service boundary of each functional module to obtain a service boundary definition document; Design a RESTful API based on the service boundaries of the functional modules to obtain API design data; Based on the API design data and service boundary definition document, Docker is selected as the containerization tool, and the preset Kubernetes cluster is used for container orchestration to obtain a modular system framework and resource scheduling strategy; When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate the Docker containerized service to generate elastic resource management instructions, including: Determine the required emergency equipment and computing resources based on the structured event matching rules, install and configure the Kubernetes cluster, and ensure that Docker is installed on each node to obtain a configured Kubernetes cluster; Obtain a Docker image and deploy a Docker container using the configured Kubernetes cluster to obtain a deployed Docker container; Set resource requests and resource limits in the preset Pod configuration to obtain the configured Pod resource requirements; The deployed Docker container is adjusted according to the configured Pod resource requirements, and the instruction content is automatically expanded or reduced to obtain elastic resource management instructions.

2. The construction site emergency management method based on microservice architecture according to claim 1, characterized in that: The method of combining the resource scheduling strategy with the historical event data to train the preset AI model and construct a dynamic digital emergency plan library includes: Extracting event-related data from the historical event data to obtain a historical event data set, and collecting sensor data in real time through a preset IoT device, and integrating the real-time sensor data to obtain a real-time sensor data stream; Cleaning and normalizing the historical event dataset and the real-time sensor data stream, and extracting key features therefrom to obtain a cleaned dataset and a feature vector, wherein the key features include event type, event sequence, and spatial location; Construct historical data based on the cleaned dataset and feature vectors, and use the historical data to train the AI ​​model, optimize the model parameters, and perform incremental training using real-time sensor data to obtain a trained model; By training the model, the preset general emergency plan process is decomposed, key nodes are extracted, and the development trend and impact range of events are predicted. The plan library is constructed to obtain a dynamic digital plan library.

3. The construction site emergency management method based on microservice architecture according to claim 1, characterized in that: Based on the modular system framework, the dynamic digital plan library is applied to the module corresponding to the dynamic digital plan library to construct structured event matching rules, including: Extracting event features and plan processes from the dynamic digital plan library based on the modular system framework, extracting real-time monitoring data and response strategies from a preset intelligent response engine, and cleaning and structuring preset historical event data to obtain structured event feature data and plan process data; Based on structured event feature data and plan process data, the preset AI model is used to perform pattern recognition on event features, extract key features, and construct event feature vectors; An event matching rule is generated based on the event feature vector and the plan process data, and a trigger condition and a response strategy are defined to obtain a structured event matching rule.

4. The construction site emergency management method based on microservice architecture according to claim 1, characterized in that: After determining the required emergency equipment and computing resources according to the structured event matching rules, orchestrating the Docker containerized service using a preset Kubernetes cluster, and generating elastic resource management instructions, the following steps may also be included: Obtaining a service access request, and determining whether the user identity of the preset user is approved according to the service access request; If approved, respond to the service access request; If it fails, identity authentication redirection is performed, and identity authentication is performed uniformly to determine whether the unified identity authentication is passed; If passed, get the identity authentication token; If not, access is denied and the step ends.

5. The construction site emergency management method based on microservice architecture according to any one of claims 1 to 4, characterized in that: The data cockpit resources are integrated using the modular system framework and, according to the flexible resource management instructions, the real-time status of resource allocation and emergency response is displayed to generate a full-dimensional visualization of the construction site status, including: Utilize sensors at pre-set construction sites to collect equipment operating status and environmental parameters to obtain IoT device data, where the environmental parameters include dust, noise, and water level; Based on the preset security events and progress deviations reported by mobile terminals or broadcasts, manually input security events and construction progress are obtained to obtain manually reported information; Integrate data cockpit resources, IoT device data, and manually reported information into the pre-built data cockpit platform, and use BIM+GIS technology to perform data association and visualization to obtain integrated site status data; The key elements of the integrated construction site status data are displayed in real time on a preset screen to obtain a visual view of the full-dimensional status of the construction site.

6. A construction site emergency management device based on microservice architecture, characterized in that: The device comprises: The database construction module is used to design a microservice architecture and containerized deployment solution based on the preset construction site emergency management requirements, thereby obtaining a modular system framework and resource scheduling strategy. Based on the preset construction site emergency management requirements, a microservice architecture and containerized deployment solution were designed to obtain a modular system framework and resource scheduling strategy, including: Split the construction site emergency management requirements, obtain independent functional modules in the construction site emergency management requirements, and clarify the interaction relationship between each functional module to obtain a functional module list and a module interaction relationship diagram; Select the corresponding microservice design pattern based on the functional module list and module interaction diagram, and define the service boundary of each functional module to obtain a service boundary definition document; Design a RESTful API based on the service boundaries of the functional modules to obtain API design data; Based on the API design data and service boundary definition document, Docker is selected as the containerization tool, and the preset Kubernetes cluster is used for container orchestration to obtain a modular system framework and resource scheduling strategy; Acquire historical event data, and use the historical event data in combination with the resource scheduling strategy to train a preset AI model to build a dynamic digital emergency plan library; A management instruction generation module is used to apply the dynamic digital plan library to the module corresponding to the dynamic digital plan library based on the modular system framework to construct a structured event matching rule; When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate Docker container services to generate elastic resource management instructions; When an emergency occurs, the required emergency equipment and computing resources are determined according to the structured event matching rules, and the preset Kubernetes cluster is used to orchestrate the Docker containerized service to generate elastic resource management instructions, including: Determine the required emergency equipment and computing resources based on the structured event matching rules, install and configure the Kubernetes cluster, and ensure that Docker is installed on each node to obtain a configured Kubernetes cluster; Obtain a Docker image and deploy a Docker container using the configured Kubernetes cluster to obtain a deployed Docker container; Set resource requests and resource limits in the preset Pod configuration to obtain the configured Pod resource requirements; Adjust the deployed Docker container according to the configured Pod resource requirements and automatically expand or reduce the instruction content to obtain elastic resource management instructions; A visual map generation module is used to obtain data cockpit resources, integrate the data cockpit resources using the modular system framework, and display the real-time status of resource allocation and emergency response according to the flexible resource management instructions to generate a full-dimensional visualization of the construction site status; The emergency management module is used to obtain double-blind drill data and emergency response records, find problems in the AI ​​model and plan logic based on the full-dimensional status visualization view of the construction site, double-blind drill data and emergency response records, and perform emergency management.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the construction site emergency management method based on microservice architecture as described in any one of claims 1 to 5.

8. A computer-readable storage medium comprising a data storage area and a program storage area, wherein the data storage area stores created data and the program storage area stores a computer program; When the computer program is executed by a processor, the construction site emergency management method based on a microservice architecture as described in any one of claims 1 to 5 is implemented.

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