A safety configuration management method for the construction phase of an adaptive environment

Abstract

The present invention provides a method for managing safety configuration in an adaptive environment construction phase, including: extracting construction environment features and converting them into feature vectors, and identifying construction environment categories based on the feature vectors based on a pre-trained environment recognition model; establishing a configuration template library, the configuration template library including configuration templates under different construction environments, each configuration template containing specific configuration items and parameters under the construction environment; selecting a matching configuration template from the template library based on an adaptation engine according to the construction environment recognition result, and loading it into memory; dynamically parsing the loaded configuration template, and adjusting configuration items and parameters according to construction environment characteristics or safety specification requirements; injecting the adjusted configuration parameters into a connector or application in real time through reflection or configuration management API to complete configuration update. The method of the present invention can realize automation and intelligence of configuration management, and improve the efficiency and quality of software deployment and maintenance.

Description

Technical Field

[0001] The present invention relates to the fields of computer software engineering and cloud computing, and in particular to a security configuration management method for an adaptive environment construction phase. Background Art

[0002] In the modern software development and deployment process, system integration is a key link to ensure the smooth migration of applications between different environments. Traditional configuration management methods rely on manual adjustments, which are not only time-consuming but also prone to errors. Especially in multi-environment deployments, configuration differences between different environments may lead to configuration omissions, conflicts, and other problems, seriously affecting system stability and deployment efficiency. Although some configuration management tools support environment variable configuration and version control, they often lack the ability to automatically identify the environment and cannot dynamically adjust the configuration according to environmental changes. Specifically, there are the following defects:

[0003] 1) Lack of automatic environment recognition mechanism, unable to automatically adjust configuration when the environment changes, increasing the complexity of deployment and maintenance;

[0004] 2) The management and application of configuration templates are not intelligent enough and cannot dynamically match the optimal configuration based on environmental characteristics;

[0005] 3) Lack of effective configuration change monitoring and feedback mechanism makes it difficult to discover and correct configuration errors in real time. Summary of the invention

[0006] Based on the above background, the technical problem solved by the present invention is to provide a security configuration management method for the construction phase of an adaptive environment. By integrating environmental perception, intelligent adaptation, dynamic configuration update and monitoring feedback mechanism, a high degree of automation and intelligence of configuration management is achieved, thereby improving the efficiency and quality of software deployment and maintenance.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] A safety configuration management method for an adaptive environment construction phase, comprising:

[0009] Extract construction environment features and convert them into feature vectors, and identify the construction environment category according to the feature vectors based on a pre-trained environment recognition model;

[0010] Establishing a configuration template library, wherein the configuration template library includes configuration templates under different construction environments, and each configuration template includes specific configuration items and parameters under the construction environment;

[0011] According to the identification results of the construction environment, the matching configuration template is selected from the template library based on the adaptation engine and loaded into the memory;

[0012] Dynamically parse the loaded configuration template and adjust the configuration items and parameters according to the construction environment characteristics or safety regulations;

[0013] Through reflection or configuration management API, the adjusted configuration parameters are injected into the connector or application in real time to complete the configuration update.

[0014] Furthermore, the construction environment characteristics include one or more of geographical location characteristics, stage characteristics, safety equipment characteristics or equipment category characteristics;

[0015] The geographical location characteristics include several or all of the following: country code, province code, city code, address latitude and longitude, altitude, terrain type, soil type, average annual temperature or average annual precipitation;

[0016] The phase characteristics include several or all of the project phase number, phase name, phase start date, phase estimated end date or key nodes;

[0017] The safety equipment characteristics include the models and parameters of various types of safety equipment;

[0018] The equipment category characteristics include the models and parameters of various types of construction machinery.

[0019] Furthermore, the extraction of construction environment features and conversion into feature vectors includes:

[0020] Obtain construction environment characteristic data from the project management information system through RESTful API;

[0021] Based on the specification files in the project document management system, the acquired construction environment characteristic data are integrated to form a construction environment characteristic data set;

[0022] The Scikit-learn library is used to convert the construction environment features in the construction environment feature dataset into feature vectors.

[0023] Furthermore, the construction environment characteristic data acquired based on the specification file in the project document management system is integrated to form a construction environment characteristic data set, including:

[0024] Read specification files in the project document management system and use text parsing tools to extract text information;

[0025] Preprocessing the extracted text information, including removing format noise, standardizing text, identifying and correcting errors;

[0026] The preprocessed text data is associated and matched with the construction environment feature data to form a unified construction environment feature data set.

[0027] Furthermore, the use of the Scikit-learn library to convert the construction environment features in the construction environment feature dataset into a feature vector includes:

[0028] Use the StandardScaler function in the Scikit-learn library to standardize numerical features to eliminate the impact of dimension;

[0029] The categorical features are encoded using the OneHotEncoder function in the Scikit-learn library and converted into a binary matrix. Each category corresponds to a column in the matrix. If a category appears, the value of the corresponding column is 1, otherwise it is 0.

[0030] The standardized values ​​of the numerical features and the encoded values ​​of the categorical features are combined to form a feature vector.

[0031] Furthermore, the establishment of the configuration template library includes:

[0032] Design a Jinja2 template as a basic configuration template, which contains multiple configuration items and parameters to be filled in, and uses placeholders to represent variable parts;

[0033] Acquire various construction environment characteristic parameters under different construction environment categories, fill the parameters of the basic configuration template, and form configuration templates corresponding to different construction environment categories;

[0034] A NoSQL database is used to store various configuration templates to form a configuration template library, where the configuration templates are organized in JSON format.

[0035] Further, obtaining various construction environment characteristic parameters under different construction environment categories and filling configuration items and parameters in the basic configuration template include:

[0036] Collect construction environment characteristic data of multiple ongoing construction projects or historical construction projects;

[0037] Preprocessing the acquired data, wherein the preprocessing includes data cleaning, missing value processing, standardization processing, outlier processing, data conversion or data verification;

[0038] Structural processing is performed on the preprocessed data, and specific configuration items and parameters corresponding to different construction environments are screened out;

[0039] The selected specific configuration items and parameters corresponding to different construction environments are filled into the basic configuration template.

[0040] Furthermore, the method of selecting a matching configuration template from a template library based on the adaptation engine according to the construction environment identification result and loading it into the memory includes:

[0041] The pre-trained environment recognition model is used as an adaptation engine, and the matching configuration template is obtained based on the adaptation engine;

[0042] Using database query language to locate matching templates from the template library;

[0043] The selected matching template is dynamically loaded into memory through the API.

[0044] Furthermore, the dynamically parsing the loaded configuration template and adjusting the configuration items and parameters according to the construction environment characteristics include:

[0045] Continuously collect information on construction site environment, equipment operation, workers' behavior patterns, project progress, and safety incidents;

[0046] Perform real-time analysis of collected data to identify abnormal patterns and potential security threats;

[0047] Modify the variable configuration items and parameters in the configuration template based on the identification results.

[0048] Furthermore, the continuous collection of construction site environment information, equipment operation information, worker behavior pattern information, project progress information, and safety incident information includes:

[0049] Collect site environmental information, including temperature, humidity, light and weather information, based on pre-deployed sensors and monitoring equipment;

[0050] Collect equipment operating status and performance indicator information based on equipment control systems or IoT devices;

[0051] Collect information about workers’ behavior patterns, including working hours, rest periods, or movement paths, based on video surveillance or wearable sensors;

[0052] Collect basic project information and project progress information based on the project management information system;

[0053] Collect safety incident information based on the safety management system, including accident reports, violations or potential risk point information.

[0054] Furthermore, the real-time analysis of the collected data to identify abnormal patterns and potential security threats includes:

[0055] Analyze construction site environmental information to obtain abnormal high temperatures, strong light exposure, or safety risks such as strong winds, heavy rain, heavy snow, and hail;

[0056] Analyze equipment operating status and performance indicator information to predict possible failures or performance degradation;

[0057] Analyze worker behavior pattern information to identify unsafe or abnormal behaviors of workers;

[0058] Analyze the basic information and progress information of the project, and obtain the corresponding security configuration information according to the project progress;

[0059] Analyze security event information and identify potential security threats to current configuration items and parameters.

[0060] Furthermore, the dynamically parsing the loaded configuration template and adjusting the configuration items and parameters according to the safety specification requirements include:

[0061] Get the latest safety regulations by subscribing to government or industry safety regulations update services;

[0062] When new safety regulations are detected, analyze the regulations to determine their impact on the existing construction environment configuration template;

[0063] Based on the analysis results, update the relevant parameters in the configuration template.

[0064] Furthermore, the adjusted configuration parameters are injected into the connector or application in real time through reflection or configuration management API to complete the configuration update, including:

[0065] Use Ansible's file module to set permissions and ownership of configuration files to ensure that only authorized users and system services can access and modify configuration files;

[0066] Use Ansible's copy module to copy the local configuration file to the specified directory of the remote server;

[0067] Use Ansible's service module or execute a system restart command to apply the new configuration file;

[0068] Perform health checks to verify that the service is running properly and that the new configuration has not caused any anomalies or service interruptions;

[0069] If problems occur after the service is restarted, perform troubleshooting, including viewing log files, checking configuration file syntax, and rolling back to a previous stable configuration.

[0070] Furthermore, the method also includes:

[0071] Regularly evaluate the performance of configuration templates in actual environments, optimize configuration templates based on performance data and user feedback, and improve overall configuration efficiency and quality;

[0072] Record the details of each configuration change, including the change time, operator, and configuration differences before and after the change, for auditing and tracing;

[0073] When configuration changes fail or the system runs abnormally, timely alarms are issued via email, SMS or system notifications, and fault diagnosis suggestions are provided.

[0074] Beneficial effects of the present invention:

[0075] The present invention significantly improves the flexibility and reliability of software deployment through automatic environment identification, intelligent adaptive configuration, real-time monitoring and dynamic adjustment, reduces manual configuration errors, shortens the deployment cycle, and reduces maintenance costs. At the same time, the system's intelligent management mechanism promotes the standardization and continuous optimization of configuration templates, enhances the maintainability and scalability of the system, and has important value in promoting the development of software engineering and cloud computing. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a schematic flow chart of a method for managing safety configuration in an adaptive environment construction phase according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more related listed items.

[0079] See also Figure 1 The embodiment of the present invention provides a method for managing security configuration in an adaptive environment construction phase, comprising the following steps:

[0080] S1. Extract construction environment features and convert them into feature vectors, and identify the construction environment category according to the feature vectors based on a pre-trained environment recognition model.

[0081] In some embodiments, the construction environment characteristics include one or more of geographical location characteristics, stage characteristics, safety equipment characteristics, or equipment category characteristics; wherein

[0082] Geographic location features include country code, province code, city code, address latitude and longitude, altitude, terrain type (such as "mountain", "plain"), soil type (such as "clay", "sand"), average annual temperature (such as "15℃") or average annual precipitation;

[0083] Phase characteristics include some or all of the following: project phase number (e.g. "S01" for construction preparation phase), phase name (e.g. "construction preparation"), phase start date, phase estimated end date or key milestones (e.g. "foundation acceptance", "structure topping out");

[0084] Safety equipment features include the models and parameters of various safety equipment, such as helmets (type "hard shell", applicable head circumference), safety belts, protective glasses (impact protection level "1", UV protection factor "UV400"), protective gloves (cut resistance level "5", anti-slip performance "high"), etc.;

[0085] Equipment category features include the models and parameters of various types of construction machinery, such as excavators (model "EX300", operating weight "30 tons", maximum digging depth "20 meters"), cranes (model "TCX-500", maximum lifting capacity "500 tons", maximum working radius "80 meters"), mixer trucks (capacity "10 cubic meters", model "JSY-10", power type "diesel"), etc.

[0086] In some embodiments, extracting construction environment features and converting them into feature vectors includes:

[0087] Obtain construction environment characteristic data from the project management information system through RESTful API;

[0088] Based on the specification files in the project document management system, the acquired construction environment characteristic data are integrated to form a construction environment characteristic data set, including:

[0089] Read specification documents from the project document management system, including construction safety standards, equipment usage specifications, etc., which may be in PDF, Word or HTML format; use text parsing tools (such as Python's PyPDF2 or python-docx) to extract key text information;

[0090] Preprocessing the extracted text information, including removing format noise, standardizing text, identifying and correcting errors;

[0091] The preprocessed text data is associated and matched with the construction environment feature data to form a unified construction environment feature data set.

[0092] For example, if the specification document mentions that a certain type of construction machinery must be used at a specific temperature, this information will be associated and matched to the dataset and used when configuring template matching later.

[0093] Finally, the Scikit-learn library is used to convert the construction environment features in the construction environment feature dataset into feature vectors, including:

[0094] Use the StandardScaler function in the Scikit-learn library to standardize numerical features to eliminate the impact of dimension;

[0095] The categorical features are encoded using the OneHotEncoder function in the Scikit-learn library and converted into a binary matrix. Each category corresponds to a column in the matrix. If a category appears, the value of the corresponding column is 1, otherwise it is 0.

[0096] The standardized values ​​of the numerical features and the encoded values ​​of the categorical features are combined to form a feature vector.

[0097] The Scikit-learn library (formerly known as scikits.learn and also referred to as sklearn) is a free software machine learning library for the Python programming language. It features a variety of classification, regression, and clustering algorithms, including support vector machines, random forests, gradient boosting, k-means, and DBSCAN, and is designed to be used in conjunction with the Python numerical science libraries NumPy and SciPy.

[0098] In some embodiments, the pre-trained environment recognition model may adopt a random forest model, and the training method thereof is:

[0099] The construction environment characteristic data is collected and converted into feature vectors to form a training data set. The data set is divided into a training set and a test set. The training set is used for model training, and the test set is used to evaluate model performance.

[0100] Use the training set data to train the random forest model; during the training process, multiple decision trees are created, and each tree is trained on a random subset of the training data;

[0101] Use the test set to evaluate the performance of the model. Common evaluation indicators include accuracy, recall, F1 score, etc.

[0102] Adjust model parameters such as the number of trees, tree depth, feature selection method, etc. based on the evaluation results to improve the prediction accuracy of the model;

[0103] The trained model is used as an environment recognition model to identify the construction environment category based on the newly input feature vector.

[0104] S2. Establish a configuration template library, wherein the configuration template library includes configuration templates under different construction environments, and each configuration template includes specific configuration items and parameters under the construction environment.

[0105] In some embodiments, establishing a configuration template library includes:

[0106] Design a Jinja2 template as the basic configuration template, which contains multiple configuration items and parameters to be filled in, and uses placeholders to represent variable parts;

[0107] Obtain the characteristic parameters of various construction environments under different construction environment categories, fill the parameters of the basic configuration template, and form configuration templates corresponding to different construction environment categories, including:

[0108] Collect construction environment characteristic data of multiple ongoing construction projects or historical construction projects;

[0109] Preprocess the acquired data, including data cleaning, missing value processing, standardization, outlier processing, data conversion or data verification;

[0110] The preprocessed data is structured, such as forming a dictionary or a list, and specific configuration items and parameters corresponding to different construction environments are screened out based on the network model.

[0111] Fill the selected specific configuration items and parameters corresponding to different construction environments into the basic configuration template;

[0112] Finally, a NoSQL database is used to store various configuration templates to form a configuration template library, where the configuration templates are organized in JSON format.

[0113] In an example shown, for example, it is necessary to filter out configuration items and parameters applicable to a "tunnel construction" environment.

[0114] First, historical data of tunnel construction projects are collected, including construction environment characteristics, safety incidents, construction progress, etc.

[0115] The data is then preprocessed, including data cleaning, missing value processing, standardization, etc., and then the data is converted into feature vectors.

[0116] Train a classification model (Random Forest) using historical data as a training set. The model learns how to predict the required configuration items and parameters based on the characteristics of the construction environment.

[0117] The model may learn that in tunnel construction, if there is a gas risk, specific ventilation systems and gas detection equipment need to be configured;

[0118] When a new tunnel construction project begins, the adaptation engine uses the trained model to predict and filter out the required configuration items and parameters based on the feature vectors of the current construction environment;

[0119] The adaptation engine fills these configuration items and parameters into the configuration template to form a new configuration template.

[0120] In some illustrated examples, when the construction environment is high-altitude work: basic configuration items and parameters include working height (e.g., 100 meters), safety net specifications (e.g., 2 meters × 10 meters), etc.; variable parameters include safety rope length (e.g., 5 meters), safety belt model (e.g., HAR-500), etc.

[0121] When the construction environment is tunnel operation, the basic configuration items and parameters include tunnel length (for example, 1000 meters), tunnel width (for example, 6 meters), etc.; variable parameters include ventilation equipment type (for example, axial flow fan), lighting intensity (for example, 1000 lux), etc.

[0122] When the construction environment is indoor decoration, the basic parameters include room area (for example, 100 square meters), room height (for example, 3 meters), etc.; variable parameters include fireproof material grade, ventilation requirements, etc.

[0123] S3. According to the identification result of the construction environment, a matching configuration template is selected from the template library based on the adaptation engine and loaded into the memory.

[0124] In some embodiments, this step is implemented as follows:

[0125] The pre-trained environment recognition model acts as an adaptation engine, and a matching configuration template is obtained based on the adaptation engine; for example, if the recognition result is "high-altitude work", the adaptation engine will search for configuration templates related to high-altitude work.

[0126] Using a database query language, such as SQL, by writing a server-side script, execute a query to locate a template matching the construction environment characteristics from a template library;

[0127] Then, the template’s suitability is evaluated, and the matching degree of the template is evaluated using predefined rules or algorithms based on the template’s parameter settings, construction phase, safety requirements, etc.;

[0128] Finally, the template with the highest matching degree is selected and dynamically loaded into the memory through the API.

[0129] The training of the environment recognition model here can refer to the training process of the environment recognition model in the aforementioned step S1, which will not be described in detail here.

[0130] S4. Dynamically parse the loaded configuration template and adjust the configuration items and parameters according to the construction environment characteristics or safety specification requirements.

[0131] In some embodiments, adjusting configuration items and parameters according to construction environment characteristics is implemented in the following manner:

[0132] Continuously collect information on construction site environment, equipment operation, workers' behavior patterns, project progress, and safety incidents, including:

[0133] Continuously collect information on construction site environment, equipment operation, workers' behavior patterns, project progress, and safety incidents;

[0134] Collect site environmental information, including temperature, humidity, light and weather information, based on pre-deployed sensors and monitoring equipment;

[0135] Collect equipment operating status and performance indicator information based on equipment control systems or IoT devices;

[0136] Collect information about workers’ behavior patterns, including working hours, rest periods, or movement paths, based on video surveillance or wearable sensors;

[0137] Collect basic project information and project progress information based on the project management information system, including the project's geographical location such as country, province, city, specific street or construction site, the number of project construction personnel such as the total number of people, the number of people in different types of work, whether it includes high-altitude work, the maximum height of the work, the expected number of days for high-altitude work, etc.;

[0138] Collect safety incident information based on the safety management system, including accident reports, violations or potential risk point information;

[0139] Analyze collected data in real time to identify abnormal patterns and potential security threats, including:

[0140] Analyze construction site environmental information to obtain abnormal high temperatures, strong light exposure, or safety risks such as strong winds, heavy rain, heavy snow, and hail;

[0141] Analyze equipment operating status and performance indicator information to predict possible failures or performance degradation;

[0142] Analyze worker behavior pattern information to identify unsafe or abnormal behaviors of workers;

[0143] Analyze the basic information and progress information of the project, and obtain the corresponding security configuration information according to the project progress;

[0144] Analyze security event information and identify potential security threats to current configuration items and parameters;

[0145] Finally, the variable configuration items and parameters in the configuration template can be modified based on the recognition results.

[0146] In some embodiments, adjusting configuration items and parameters according to security specification requirements is implemented in the following manner:

[0147] Get the latest safety regulations by subscribing to government or industry safety regulations update services;

[0148] When new safety regulations are detected, analyze the regulations to determine their impact on the existing construction environment configuration template;

[0149] Based on the analysis results, update the relevant parameters in the configuration template.

[0150] S5. Through reflection or configuration management API, the adjusted configuration parameters are injected into the connector or application in real time to complete the configuration update.

[0151] In some embodiments, the above steps are implemented as follows:

[0152] Use Ansible's file module to set permissions and ownership of configuration files to ensure that only authorized users and system services can access and modify configuration files;

[0153] Use Ansible's copy module to copy the local configuration file to the specified directory of the remote server;

[0154] Use Ansible's service module or execute a system restart command to apply the new configuration file;

[0155] Perform health checks to verify that the service is running properly and that the new configuration has not caused any anomalies or service interruptions;

[0156] If problems occur after the service is restarted, perform troubleshooting, including viewing log files, checking configuration file syntax, and rolling back to a previous stable configuration.

[0157] Ansible is an automated operation and maintenance tool developed based on Python. It combines the advantages of many operation and maintenance tools (puppet, chef, func, fabric), and can realize batch system configuration, batch program deployment, batch command execution and other functions.

[0158] As a further preferred implementation scheme, the adaptive environment construction phase safety configuration management method in this embodiment also includes:

[0159] Regularly evaluate the performance of configuration templates in actual environments, optimize configuration templates based on performance data and user feedback, and improve overall configuration efficiency and quality;

[0160] Automatically record the details of each configuration change, including the change time, operator, configuration differences before and after the change, etc., for auditing and tracing;

[0161] When configuration changes fail or the system runs abnormally, timely alarms are issued via email, SMS or system notifications, and fault diagnosis suggestions are provided.

[0162] It should be noted that the method of the embodiment of the present invention can be performed by a single device, such as a computer or a server. The method of this embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present invention, and the multiple devices will interact with each other to complete the described method.

[0163] It should be noted that some embodiments of the present invention are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0164] The embodiments of the present invention are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should be included in the protection scope of the present invention.

Claims

1. A safety configuration management method for an adaptive environment construction phase, characterized in that: include: Extract construction environment features and convert them into feature vectors, and identify the construction environment category according to the feature vectors based on a pre-trained environment recognition model; Establishing a configuration template library, wherein the configuration template library includes configuration templates under different construction environments, and each configuration template includes specific configuration items and parameters under the construction environment; The pre-trained environment recognition model is used as an adaptation engine. According to the construction environment recognition results, the matching configuration template is obtained based on the adaptation engine. The matching template is located from the template library using the database query language, and the selected matching template is dynamically loaded into the memory through the API. Dynamically parse the loaded configuration template and adjust the configuration items and parameters according to the construction environment characteristics or safety regulations; Through reflection or configuration management API, the adjusted configuration parameters are injected into the connector or application in real time to complete the configuration update.

2. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 1, characterized in that: The construction environment characteristics include one or more of geographical location characteristics, stage characteristics, safety equipment characteristics or equipment category characteristics; The geographical location characteristics include several or all of the following: country code, province code, city code, address latitude and longitude, altitude, terrain type, soil type, average annual temperature or average annual precipitation; The phase characteristics include several or all of the project phase number, phase name, phase start date, phase estimated end date or key nodes; The safety equipment characteristics include the models and parameters of various types of safety equipment; The equipment category characteristics include the models and parameters of various types of construction machinery.

3. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 1, characterized in that: The extraction of construction environment features and conversion into feature vectors comprises: Obtain construction environment characteristic data from the project management information system through RESTful API; Based on the specification files in the project document management system, the acquired construction environment characteristic data are integrated to form a construction environment characteristic data set; The Scikit-learn library is used to convert the construction environment features in the construction environment feature dataset into feature vectors.

4. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 3, characterized in that: The construction environment characteristic data is integrated based on the specification file in the project document management system to form a construction environment characteristic data set, including: Read specification files in the project document management system and use text parsing tools to extract text information; Preprocessing the extracted text information, including removing format noise, standardizing text, identifying and correcting errors; The preprocessed text data is associated and matched with the construction environment feature data to form a unified construction environment feature data set.

5. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 3, characterized in that: The method of using the Scikit-learn library to convert the construction environment features in the construction environment feature dataset into a feature vector includes: Use the StandardScaler function in the Scikit-learn library to standardize numerical features to eliminate the impact of dimension; The categorical features are encoded using the OneHotEncoder function in the Scikit-learn library and converted into a binary matrix. Each category corresponds to a column in the matrix. If a category appears, the value of the corresponding column is 1, otherwise it is 0. The standardized values ​​of the numerical features and the encoded values ​​of the categorical features are combined to form a feature vector.

6. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 1, characterized in that: The step of establishing a configuration template library includes: Design a Jinja2 template as a basic configuration template, which contains multiple configuration items and parameters to be filled in, and uses placeholders to represent variable parts; Acquire various construction environment characteristic parameters under different construction environment categories, fill the parameters of the basic configuration template, and form configuration templates corresponding to different construction environment categories; A NoSQL database is used to store various configuration templates to form a configuration template library, where the configuration templates are organized in JSON format.

7. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 6, characterized in that: Acquiring various construction environment characteristic parameters under different construction environment categories and filling configuration items and parameters in the basic configuration template include: Collect construction environment characteristic data of multiple ongoing construction projects or historical construction projects; Preprocessing the acquired data, wherein the preprocessing includes data cleaning, missing value processing, standardization processing, outlier processing, data conversion or data verification; Structural processing is performed on the preprocessed data, and specific configuration items and parameters corresponding to different construction environments are screened out; The selected specific configuration items and parameters corresponding to different construction environments are filled into the basic configuration template.

8. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 1, characterized in that: The dynamically parsing the loaded configuration template and adjusting the configuration items and parameters according to the construction environment characteristics include: Continuously collect information on construction site environment, equipment operation, workers' behavior patterns, project progress, and safety incidents; Perform real-time analysis of collected data to identify abnormal patterns and potential security threats; Modify the variable configuration items and parameters in the configuration template based on the identification results.

9. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 8, characterized in that: The continuous collection of construction site environment information, equipment operation information, worker behavior pattern information, project progress information, and safety event information includes: Collect site environmental information, including temperature, humidity, light and weather information, based on pre-deployed sensors and monitoring equipment; Collect equipment operating status and performance indicator information based on equipment control systems or IoT devices; Collect information about workers’ behavior patterns, including working hours, rest periods, or movement paths, based on video surveillance or wearable sensors; Collect basic project information and project progress information based on the project management information system; Collect safety incident information based on the safety management system, including accident reports, violations or potential risk point information.

10. The method for managing safety configuration during the construction phase of an adaptive environment as claimed in claim 9, characterized in that: The real-time analysis of collected data to identify abnormal patterns and potential security threats includes: Analyze the construction site environment information to obtain abnormal high temperature and strong light exposure, or safety risks caused by strong wind, heavy rain, heavy snow, and hail; Analyze equipment operating status and performance indicator information to predict possible failures or performance degradation; Analyze worker behavior pattern information to identify unsafe or abnormal behaviors of workers; Analyze the basic information and progress information of the project, and obtain the corresponding security configuration information according to the project progress; Analyze security event information and identify potential security threats to current configuration items and parameters.

11. The method for managing safety configuration during the construction phase of an adaptive environment according to claim 8, characterized in that: The dynamically parsing the loaded configuration template and adjusting the configuration items and parameters according to the safety specification requirements include: Get the latest safety regulations by subscribing to government or industry safety regulations update services; When new safety regulations are detected, analyze the regulations to determine their impact on the existing construction environment configuration template; Based on the analysis results, update the relevant parameters in the configuration template.

12. The method for managing safety configuration during the construction phase of an adaptive environment according to claim 1, characterized in that: The adjusted configuration parameters are injected into the connector or application in real time through reflection or configuration management API to complete the configuration update, including: Use Ansible's file module to set permissions and ownership of configuration files to ensure that only authorized users and system services can access and modify configuration files; Use Ansible's copy module to copy the local configuration file to the specified directory of the remote server; Use Ansible's service module or execute a system restart command to apply the new configuration file; Perform health checks to verify that the service is running properly and that the new configuration has not caused any anomalies or service interruptions; If problems occur after the service is restarted, perform troubleshooting, including viewing log files, checking configuration file syntax, and rolling back to a previous stable configuration.

13. The method for managing safety configuration during the construction phase of an adaptive environment according to any one of claims 1 to 12, characterized in that: Also includes: Regularly evaluate the performance of configuration templates in actual environments, optimize configuration templates based on performance data and user feedback, and improve overall configuration efficiency and quality; Record the details of each configuration change, including the change time, operator, and configuration differences before and after the change, for auditing and tracing; When configuration changes fail or the system runs abnormally, timely alarms are issued via email, SMS or system notifications, and fault diagnosis suggestions are provided.

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