Project engineering data monitoring management method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a project engineering data monitoring management method and device, equipment and a storage medium, and the method comprises the steps: creating a target project and a target monitoring scene based on a project creation instruction, and associating the target monitoring scene with a target data source; based on the algorithm template configuration instruction, performing algorithm template configuration on the target monitoring scene by using an algorithm template configuration engine to obtain a target algorithm template; constructing a mapping relation between the target algorithm template and the target data source; processing the real-time data of the target data source based on the mapping relation by utilizing a real-time data processing engine to obtain a data processing result, and performing business application; and performing early warning processing and closed-loop management in response to the condition that the data processing result meets a preset early warning condition. According to the embodiment of the invention, the system operation process can be simplified, the project construction management usability is improved, the learning cost is reduced, the algorithm development time is shortened, the project construction management development cost is reduced, and the algorithm reuse rate is improved.

Description

Technical Field

[0001] This disclosure relates to computer project construction management technology, and in particular to a method, apparatus, equipment, and storage medium for monitoring and managing project engineering data. Background Technology

[0002] Traditional construction monitoring project management faces the following technical challenges: a single data-centric architecture lacks flexible business logic organization, resulting in poor system scalability and long development cycles for new functions; the early warning algorithm uses hard coding, which cannot adapt to diverse monitoring scenarios, such as concrete temperature measurement and high formwork monitoring, which require the independent development of project construction management modules, leading to high costs of repeated development and low algorithm reuse rate. Summary of the Invention

[0003] This disclosure provides a method, apparatus, equipment, and storage medium for monitoring and managing project engineering data to solve the above-mentioned problems.

[0004] A first aspect of this disclosure provides a method for monitoring and managing project engineering data, including: Based on the project creation instructions, create a target project and target monitoring scenarios under the target project, and associate the target monitoring scenarios with the target data source; Based on the algorithm template configuration instructions, the algorithm template configuration engine is used to configure the algorithm template for the target monitoring scenario to obtain the target algorithm template for the target monitoring scenario. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration and early warning value configuration. Construct a mapping relationship between the target algorithm template and the target data source; Using a real-time data processing engine, the real-time data of the target data source is processed based on the mapping relationship to obtain data processing results, and business applications are carried out based on the data processing results. The business applications include generating business forms and displaying the real-time data in a visual manner. In response to the data processing result meeting the preset early warning conditions, early warning processing and closed-loop management are performed, wherein the closed-loop management includes generating work orders, recording the processing process and result data.

[0005] In some embodiments of this disclosure, the step of creating a target project and a target monitoring scenario under the target project based on project creation instructions, and associating the target monitoring scenario with a target data source, includes: Based on the project entity creation instruction, the project basic information table and personnel permission configuration table of the target project are created through the database model. Based on the business logic matching the target project, the target monitoring scenario is created for the target project; Construct a mapping table between the target monitoring scenario and the target data source; The permission model is used to configure permissions based on the personnel permission configuration table.

[0006] In some embodiments of this disclosure, the metadata configuration includes template name configuration, description configuration, and applicable scenario configuration; the data source configuration includes data source selection and establishing a data source mapping relationship table; the calculation method configuration includes calculation formula configuration; and the warning value configuration includes configuring warning values ​​through a warning threshold configuration interface.

[0007] In some embodiments of this disclosure, constructing the mapping relationship between the target algorithm template and the target data source includes: The abstract variables in the target algorithm template are associated with the interface of the target data source in the target monitoring scenario through a mapping algorithm, and parameter adjustment instructions are received through the parameter configuration interface to adjust the parameters.

[0008] In some embodiments of this disclosure, the step of using a real-time data processing engine to process real-time data from the target data source based on the mapping relationship, obtaining data processing results, and performing business applications based on the data processing results includes: Real-time data from the target data source is obtained through a scheduled task method. Using the real-time data processing engine, expression parsing and real-time calculation processing are performed based on the calculation expression corresponding to the real-time data to obtain the data processing result; Based on the data processing results and preset warning conditions, determine whether to issue a warning; Using a form template, generate the business form based on the data processing results; The trend and status of the real-time data are displayed in the form of charts or curves using a chart rendering engine.

[0009] In some embodiments of this disclosure, the early warning processing includes sending early warning information through multiple channels via message queues and push interfaces; the work order is a hidden danger handling work order generated through a work order template, and the hidden danger handling work order includes abnormal data analysis and processing suggestions.

[0010] In some embodiments of this disclosure, it also includes: By using a cross-scenario data analysis engine, correlation analysis is performed on data from different scenarios to determine the relationships between data from different scenarios; A predictive model for construction risks and development trends is built based on historical project engineering data.

[0011] A second aspect of this disclosure provides a monitoring and management system for project engineering data, comprising: The project construction management module is used to create target projects and target monitoring scenarios under the target projects based on project creation instructions, and to associate the target monitoring scenarios with target data sources; The algorithm template configuration module is used to configure the algorithm template for the target monitoring scenario based on the algorithm template configuration instructions and the algorithm template configuration engine, so as to obtain the target algorithm template for the target monitoring scenario. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration and early warning value configuration. Template data mapping relationship, used to construct the mapping relationship between the target algorithm template and the target data source; The real-time business data and business application module is used to process the real-time data of the target data source based on the mapping relationship using a real-time data processing engine to obtain data processing results, and to perform business applications based on the data processing results. The business applications include generating business forms and displaying the real-time data in a visual manner. The early warning response and closed-loop management module is used to respond to the data processing results meeting preset early warning conditions, and to perform early warning processing and closed-loop management, wherein the closed-loop management includes generating work orders, recording the processing process and result data.

[0012] In some embodiments of this disclosure, the project construction management module includes: The project management unit is used to create a basic information table and a personnel permission configuration table for the target project based on the project entity creation instruction and through a database model. The scenario management unit is used to create the target monitoring scenario for the target project based on the business logic that matches the target project; The data management unit is used to construct a mapping relationship data table between the target monitoring scenario and the target data source; The permission management unit is used to configure permissions based on the personnel permission configuration table using the permission model.

[0013] In some embodiments of this disclosure, the metadata configuration includes template name configuration, description configuration, and applicable scenario configuration; the data source configuration includes data source selection and establishing a data source mapping relationship table; the calculation method configuration includes calculation formula configuration; and the warning value configuration includes configuring warning values ​​through a warning threshold configuration interface.

[0014] In some embodiments of this disclosure, the template data mapping module is used to associate the abstract variables in the target algorithm template with the interface of the target data source in the target monitoring scenario through a mapping algorithm, and to receive parameter adjustment instructions through the parameter configuration interface to adjust the parameters.

[0015] In some embodiments of this disclosure, the real-time business data and business application module includes: A data acquisition unit is used to acquire real-time data from the target data source through a timed task scheduling method; The expression calculation unit is used to use the real-time data processing engine to perform expression parsing and real-time calculation processing based on the calculation expression corresponding to the real-time data, and obtain the data processing result. The early warning judgment unit is used to determine whether to issue an early warning based on the data processing results and preset early warning conditions; A business form generation unit is used to generate the business form based on the data processing results using a form template. The data visualization unit is used to display the trends and status of the real-time data in the form of charts or curves using a chart rendering engine.

[0016] In some embodiments of this disclosure, the early warning processing includes sending early warning information through multiple channels via message queues and push interfaces; the work order is a hidden danger handling work order generated through a work order template, and the hidden danger handling work order includes abnormal data analysis and processing suggestions.

[0017] In some embodiments of this disclosure, the project engineering data monitoring and management system further includes: The management and analysis module is used to perform correlation analysis on data from different scenarios using a cross-scenario data analysis engine, and to determine the correlation between data from different scenarios. The predictive model building module is used to build predictive models of construction risks and development trends based on historical project engineering data.

[0018] A third aspect of this disclosure provides an electronic device, comprising: Memory, used to store computer program products; A processor is configured to execute a computer program product stored in the memory, and when the computer program product is executed, to implement the method described in the first aspect above.

[0019] A fourth aspect of this disclosure provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the method described in the first aspect above.

[0020] A fifth aspect of this disclosure provides a computer program product including computer program instructions that, when executed by a processor, cause the processor to perform the method described in the first aspect.

[0021] The project engineering data monitoring and management method, apparatus, equipment, and storage medium disclosed in this embodiment simplify system operation processes, significantly improve the usability of project construction management, and reduce user learning costs through a three-level project construction management architecture design of project-scenario-data source; shorten algorithm development time and significantly reduce project construction management development costs through templated configuration and component-based reuse mechanisms, and improve algorithm reuse rate; reduce data processing error rate, significantly improve the quality of project construction management data processing, shorten system response time, improve project management performance, and significantly enhance the accuracy of cross-scenario data association, providing users with intelligent decision support.

[0022] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0023] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0024] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein: Figure 1 This is a flowchart illustrating the monitoring and management method for project engineering data in some embodiments of this disclosure; Figure 2 This is a structural block diagram of a project engineering data monitoring and management device in some embodiments of this disclosure; Figure 3 This is a structural block diagram of an electronic device in some embodiments of this disclosure. Detailed Implementation

[0025] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0026] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0027] It should also be understood that in the embodiments disclosed herein, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0028] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.

[0029] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship.

[0030] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0031] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0032] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0033] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0034] The embodiments disclosed herein can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0035] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0036] Figure 1 This is a flowchart illustrating the monitoring and management method for project engineering data in some embodiments of this disclosure. For example... Figure 1 As shown, the monitoring and management method for project engineering data includes the following steps: S1: Based on the project creation command, create the target project and the target monitoring scenario under the target project, and associate the target monitoring scenario with the target data source.

[0037] In some optional embodiments of this disclosure, step S1 includes: S1-1: Based on the project entity creation command, create the basic project information table and personnel permission configuration table of the target project through the database model.

[0038] The project construction management platform provides project entity creation functionality, and designs basic project information tables and personnel permission configuration tables through a database model.

[0039] S1-2: Based on the business logic of matching the target project, create a target monitoring scenario for the target project.

[0040] Based on business logic requirements, the project construction management platform creates virtual monitoring scenarios under the project, such as "large volume concrete pouring", "high formwork construction", and "foundation pit excavation", and establishes scenario configuration data models.

[0041] S1-3: Construct a data table showing the mapping relationship between target monitoring scenarios and target data sources.

[0042] The project construction management platform associates each scenario with a corresponding data source interface, establishing a mapping table between the data source and the scenario. S1-4: Utilize the permission model to configure permissions based on the personnel permission configuration table.

[0043] The project construction management platform uses the RBAC permission model project construction management framework to assign corresponding functional module access permissions to different personnel roles, such as project personnel, enterprise managers, and operation and maintenance managers, thereby implementing a fine-grained permission control algorithm.

[0044] S2: Based on algorithm template configuration instructions, the algorithm template configuration engine is used to configure the algorithm template for the target monitoring scenario, resulting in the target algorithm template for the target monitoring scenario. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration, and warning value configuration.

[0045] In some optional embodiments of this disclosure, step S2 includes: S2-1: The project construction management platform provides a template basic information configuration interface, and stores metadata such as template name, description, and applicable scenarios through a database template information table.

[0046] S2-2: The project construction management platform provides a drop-down selection box component that supports multiple data source selection. Each data source corresponds to a specific monitoring point, such as point1 representing monitoring point 1, point2 representing monitoring point 2, and point3 representing monitoring point 3. A data source mapping relationship table is established.

[0047] S2-3: The project construction management platform allows configuration of calculation expressions through a visual form interface, supporting selection of calculation methods (such as subtraction, addition, average, etc.) via checkboxes. It automatically generates calculation expressions such as "Temperature difference = point2 - point1", and the backend uses an expression parsing engine for calculation. S2-4: The project construction management platform provides an early warning threshold configuration interface, supporting the setting of early warning thresholds in numerical input boxes, such as "temperature difference ≤ 25". Dynamic early warning judgment is achieved through condition parsing algorithms. S2-5: The project construction management platform adopts a plug-and-play modular design pattern, encapsulating algorithm templates into independent scenario algorithm plugins, supporting dynamic loading, unloading, and hot updates of these plugins. Each plugin contains complete data source definitions, calculation logic, alert conditions, and business form templates, achieving true plug-and-play functionality. Plugins interact with the platform through standardized interfaces, supporting seamless reuse across projects and scenarios. The plugin registration mechanism and version management ensure algorithm scalability and backward compatibility. S2-6: The project construction management platform serializes and stores the configured algorithm templates into the database template library, supports template import and export functions, and enables template reuse across projects.

[0048] S3: Construct the mapping relationship between the target algorithm template and the target data source.

[0049] In some optional embodiments of this disclosure, step S3 includes: S3-1: The project construction management platform provides a template library retrieval function, which selects the algorithm template suitable for the current business scenario through matching algorithms.

[0050] S3-2: The project construction management platform uses a mapping algorithm to associate abstract variables in the template with specific data source interfaces in the current project scenario, such as mapping "point1" to "data source interface 1". S3-3: The project construction management platform provides a parameter configuration interface, supports real-time adjustment of early warning thresholds and action configurations, and achieves parameter persistence through configuration management algorithms.

[0051] S3-4: The project construction management platform enables the configured early warning rules and begins real-time data processing and monitoring through the rule engine.

[0052] S4: Utilizing a real-time data processing engine, real-time data from the target data source is processed based on mapping relationships to obtain data processing results, which are then used for business applications. These business applications include generating business forms and visually displaying real-time data.

[0053] In some optional embodiments of this disclosure, step S4 includes: S4-1: The project construction management platform provides a standardized data interface and obtains real-time data from various data sources through a scheduled task algorithm.

[0054] S4-2: The project construction management platform performs real-time calculations on the collected data based on the calculation expressions in the algorithm template through expression parsing and calculation engines.

[0055] S4-3: The project construction management platform will match the calculation results with the early warning conditions using a comparison algorithm to determine whether the early warning process is triggered.

[0056] S4-4: The project construction management platform automatically generates business forms, such as the "Daily Temperature Measurement Record" and the "Weekly Formwork Safety Report," based on monitoring data and a template engine.

[0057] S4-5: The project construction management platform uses a chart rendering engine to display monitoring data trends and status in the form of charts, curves, etc.

[0058] S5: In response to data processing results meeting preset early warning conditions, perform early warning processing and closed-loop management. Closed-loop management includes generating work orders, recording the processing procedure and result data.

[0059] In some optional embodiments of this disclosure, step S5 includes: S5-1: When the data processing results meet the early warning conditions, the project construction management platform automatically triggers the early warning processing flow through an event-driven mechanism.

[0060] S5-2: According to the preset notification configuration, the project construction management platform sends early warning information through message queues and push interfaces.

[0061] S5-3: The project construction management platform automatically generates "Hazard Handling Work Orders" through the work order template engine, which include information such as abnormal data analysis and handling suggestions.

[0062] S5-4: The project construction management platform records the handling process and result data, and forms a complete early warning and response closed-loop management through state machine algorithm.

[0063] In some embodiments of this disclosure, after step S5, the following may also be included: S6: Cross-scenario data association. In some optional embodiments of this disclosure, step S6 may include: S6-1: The project construction management platform integrates monitoring data from different scenarios within the same project using ETL algorithms to establish a unified data warehouse model.

[0064] S6-2: The project construction management platform uses multi-dimensional analysis algorithms, such as time series and spatial dimensions, to explore the correlation between data in different scenarios.

[0065] S6-3: The project construction management platform utilizes historical data and machine learning algorithms to build predictive models, enabling intelligent prediction of construction risks and development trends. S6-4: The project construction management platform provides data-driven decision support and optimization suggestions for project management through data mining and analysis algorithms.

[0066] In this implementation, the database design of the project construction management platform includes: Algorithm template table: A data structure that stores basic information such as template ID, name, description, calculation expression, and warning conditions.

[0067] Data source configuration table: A data model that stores data source information such as data source ID, data source name, data source type, and interface address; Calculation Method Table: A data structure that stores calculation configurations such as calculation method ID, calculation type (subtraction, addition, average, etc.), and calculation expression template.

[0068] Warning configuration table: A data model that stores warning parameters such as warning ID, warning type, threshold settings, and comparison operators.

[0069] Plugin Registry: A data structure that stores plugin management information such as plugin ID, plugin name, plugin version, and loading status.

[0070] Template Application Table: Stores a data model for application configurations such as application ID, template ID, project ID, scene ID, and data source mapping relationships.

[0071] The execution of the calculation expression adopts a secure project construction management expression parsing engine, which supports basic mathematical operations (+, -, *, / ), comparison operations (>, <, =, >=, <=) and logical operations (AND, OR, NOT). It restricts dangerous function calls through a whitelist mechanism to ensure the security of the project construction management system.

[0072] The front-end and back-end implementation solutions include the following: Front-end interface design: A responsive user interface is built using the Vue.js framework, providing interactive components such as a data source selection dropdown, a calculation method selector, and a warning value input box. A unified interface style is achieved through the Element UI component library.

[0073] Backend API Design: Adopting a RESTful API architecture, it provides template CRUD interfaces, data source management interfaces, computing engine interfaces, etc., and implements a microservice architecture through the Spring Boot framework.

[0074] Real-time calculation and processing: The backend receives the calculation expression configured by the frontend and calculates the monitoring data in real time through the expression parsing engine. For example, the temperature difference value is obtained by subtracting the monitoring point 1 from the monitoring point 2 and compared with the preset threshold to determine whether to trigger an alarm.

[0075] In this embodiment, a three-tiered project construction management architecture—project-scenario-data source—simplifies system operation processes, significantly improves the usability of project construction management, and reduces user learning costs. Through templated configuration and component-based reuse mechanisms, algorithm development time is shortened, project construction management development costs are significantly reduced, and algorithm reuse rate is increased. Furthermore, the data processing error rate is reduced, significantly improving the quality of project construction management data processing, shortening system response time, enhancing project management performance, and greatly improving the accuracy of cross-scenario data association, thus providing users with intelligent decision support.

[0076] To enable those skilled in the art to further understand this disclosure, the following embodiments are provided for illustration.

[0077] [Example 1]: Application of Temperature Monitoring in Construction Management of Large-Volume Concrete Projects Step 1: Scene Creation. Create a "High-Rise Building Project" in the project management module of the project construction management platform. Under this project, create a "Large-Volume Concrete Pouring" monitoring scene through the scene management module and associate it with the corresponding temperature data source interface.

[0078] Step 2: Algorithm Template Configuration Page Operations. Configure the "Concrete Temperature Monitoring and Early Warning Template" through the web interface, specifically including: Data source selection: Select point1 (internal temperature monitoring point), point2 (surface temperature monitoring point), and point3 (ambient temperature monitoring point) from the drop-down selection box.

[0079] Calculation method configuration: Select "Subtraction" in the calculation method selector, and the system will automatically generate the expression "Internal and external temperature difference = point1 - point2"; select "Change rate calculation" to generate "Temperature rise rate = (point1_current - point1_previous) / time_interval".

[0080] Warning value settings: In the warning value input box, set "internal and external temperature difference ≤ 25" and "temperature rise rate ≤ 2", and select the logical operator "OR".

[0081] Action Configuration: Select the message push method, configure the recipients, and set up automatic generation of the "Temperature Control Adjustment Suggestion" report.

[0082] Plugin saving: The configured algorithm is packaged into a "concrete temperature measurement plugin" and saved to the template library for later reuse.

[0083] Step 3: Template application and data source mapping. Perform the following steps on the project scenario configuration page: Template selection: Select "Concrete Temperature Measurement and Early Warning Template" from the template library drop-down list.

[0084] Data source mapping: Map point1 in the template to the actual "1# Temperature Data Interface", point2 to "2# Temperature Data Interface", and point3 to "Ambient Temperature Data Interface".

[0085] Parameter adjustment: Adjust the warning threshold on the interface according to the actual engineering needs, such as changing "internal and external temperature difference ≤ 25" to "internal and external temperature difference ≤ 20".

[0086] Rule activation: Click the "Enable Rule" button, and the system will begin real-time monitoring and calculation through the rule engine.

[0087] Step 4: Real-time monitoring and computation. This includes the following steps: Data Acquisition: The project construction management system collects temperature data from each monitoring point every 5 minutes by calling the REST API interface through a scheduled task.

[0088] Real-time calculation: The backend expression parsing engine automatically executes the "point2-point1" operation to obtain the internal and external temperature difference value according to the configured calculation method, and calculates "(point1_current-point1_previous) / time_interval" to obtain the temperature rise rate.

[0089] Warning judgment: The calculation results are compared with the preset threshold. When the temperature difference between inside and outside exceeds 25℃ or the temperature rise rate exceeds 2℃ / h, the warning process is triggered.

[0090] Interface display: The front-end Vue.js interface updates the monitoring data in real time, the warning status is highlighted in red, and a warning prompt box pops up.

[0091] Step 5: Business Form Generation. Based on the monitoring data, the "Daily Concrete Temperature Measurement Record" is automatically generated through the business form generation engine. It includes temperature values ​​from various data sources, temperature difference calculation results, early warning records, and other information. The accuracy rate of project construction management data processing reaches 99.5%.

[0092] [Example 2: Application of Deformation Monitoring in High Formwork Frame Projects in Construction Management] Step 1: Scene Creation. Create a "High Formwork Construction Monitoring" scene under the same project using the scene management module, and associate it with displacement data source and tilt data source interfaces.

[0093] Step 2: Algorithm Template Configuration. Create a "Formwork Deformation Early Warning Template" using the algorithm template configuration engine, specifically including: Data source variable definitions: disp1 (horizontal displacement data source), disp2 (vertical displacement data source), angle1 (tilt angle data source).

[0094] Expression parsing configuration: "Total displacement = sqrt(disp1^2 + disp2^2)", "Inclination = tan(angle1)".

[0095] Early warning condition algorithm: "Total displacement > 10" OR "Inclination > 0.015".

[0096] Warning action configuration: Call the message push interface to notify the safety director, trigger the work suspension process, and generate a "Safety Hazard Work Order" through the work order generation algorithm.

[0097] Step 3: Cross-Scenario Correlation Analysis. The project construction management system automatically analyzes the correlation between concrete pouring progress and formwork deformation through a cross-scenario data correlation analysis engine. When the amount of concrete poured increases, the intelligent scheduling algorithm correspondingly increases the monitoring frequency of the formwork, realizing intelligent monitoring strategy adjustment.

[0098] Step 4: Predictive Analysis. Based on historical monitoring data, the project construction management platform uses machine learning prediction model algorithms to predict the deformation trend of the formwork under different load conditions, with a prediction accuracy rate of over 90%, providing a scientific basis for users to adjust their construction plans.

[0099] [Example 3: Plug-in Algorithm Template Reuse] When a new project, "A Commercial Complex Project," commences on the project construction management platform, the following procedures shall be followed: Plugin Import: Import existing "Concrete Temperature Measurement Plugin" and "Formwork Deformation Plugin" through the template management interface.

[0100] Quick configuration: Select the corresponding plugin on the algorithm configuration page, and the system will automatically load the preset calculation method and warning conditions.

[0101] Data source remapping: Simply select the monitoring point of the new project in the data source selection drop-down box, such as remapping point1 to "New Project 1# Temperature Interface".

[0102] Parameter fine-tuning: Adjust the threshold setting in the warning value input box according to the characteristics of the new project.

[0103] One-click deployment: Click the "Application Template" button and the system will automatically complete the algorithm deployment, reducing the configuration time from 2 days to 2 hours.

[0104] [Example 4: Plug-in Application of Foundation Pit Excavation Monitoring] Step 1: Plugin Configuration. Create a "Foundation Pit Deformation Monitoring Plugin", including: Data source definition: point1 (horizontal displacement sensor), point2 (vertical settlement sensor), point3 (tilt angle sensor), point4 (groundwater level sensor).

[0105] The calculation expression configuration is as follows: "Cumulative displacement = sqrt(point1^2 + point2^2)", "Deformation rate = (cumulative displacement_current - cumulative displacement_previous) / time_interval", "Water level change = point4_current - point4_baseline".

[0106] Warning conditions set: "Cumulative displacement > 30mm" OR "Deformation rate > 2mm / day" OR "Water level change > 500mm".

[0107] Business form templates: Automatically generate "Daily Report on Foundation Pit Safety Monitoring" and "Deformation Early Warning Notification".

[0108] Step 2: Plug and Play Deployment. In different foundation pit monitoring scenarios, simply select the "Foundation Pit Deformation Monitoring Plugin," and the system will automatically adapt to the data source interface of the current scenario, enabling plug-and-play algorithm usage. When data changes dynamically, the plugin automatically updates the calculation results and warning status without manual intervention.

[0109] [Example 5: Steel Structure Welding Quality Monitoring Plug-in] Step 1: Plugin Development. Create a "Welding Temperature Monitoring Plugin", including: Data source configuration: point1 (welding zone temperature), point2 (heat-affected zone temperature), point3 (ambient temperature), point4 (cooling time).

[0110] Algorithm logic: "Temperature gradient = (point1-point2) / distance", "Cooling rate = (point1_peak-point1_current) / point4", "Relative temperature difference = point1-point3".

[0111] Early warning mechanism: "Temperature gradient > 50℃ / cm" OR "Cooling rate < 10℃ / min" OR "Relative temperature difference > 200℃".

[0112] Forms generated: "Welding Process Parameter Record Sheet" and "Welding Quality Inspection Report".

[0113] Step 2: Cross-project reuse. This plugin can be used directly in welding scenarios of different projects such as steel structure workshops, bridges, and high-rise buildings. It achieves plug-and-play functionality through data source remapping, ensuring real-time monitoring and early warning of welding quality.

[0114] [Example 6: Concrete Strength Growth Monitoring Plug-in] Step 1: Algorithm Plugin Design. Develop a "Concrete Strength Monitoring Plugin," including: Monitoring parameters: point1 (internal temperature of concrete), point2 (ambient temperature), point3 (humidity), point4 (aging time).

[0115] Calculation models: "Equivalent age = Σ(exp(E / R*(1 / T0-1 / T)))*Δt", "Intensity prediction = f(equivalent age, mix proportion parameter)", "Intensity growth rate = (intensity prediction_current-intensity prediction_previous) / time_interval".

[0116] Warning logic: "Intensity growth rate < standard value * 0.8" OR "Equivalent age deviation > 20%".

[0117] Business applications: Automatically generate "Concrete Strength Growth Curve" and "Recommended Formwork Removal Time Report".

[0118] Step 2: Dynamic Adaptability. The plugin automatically adjusts calculation parameters based on different concrete grades and mix proportions, achieving algorithm adaptability. As monitoring data changes in real time, the predicted strength values ​​and formwork removal suggestions are updated synchronously, providing dynamic support for construction decisions.

[0119] [Example 7: Modular Safety Monitoring System for Tower Cranes] Step 1: Integrated Monitoring Plugin. Construct the "Tower Crane Safety Integrated Monitoring Plugin," including: Multidimensional data sources: point1 (lifting torque), point2 (wind speed and direction), point3 (tower tilt), point4 (wire rope tension), and point5 (rotation angle).

[0120] Composite algorithm: "Safety factor = rated torque / actual torque", "Wind load influence coefficient = f(wind speed, wind direction, tower height)", "Comprehensive safety index = w1 * safety factor + w2 * tilt coefficient + w3 * wind load coefficient".

[0121] Multi-level warning: "Comprehensive safety index <0.8" (yellow warning), "<0.6" (orange warning), "<0.4" (red warning).

[0122] Linkage control: When an early warning is triggered, a "Tower Crane Stop Instruction" and a "Safety Inspection Work Order" are automatically generated.

[0123] Step 2: Intelligent Decision Support. The plug-in integrates machine learning algorithms to predict the safety status of tower cranes under different working conditions based on historical data, providing intelligent suggestions for construction planning. Through a plug-and-play mechanism, it can be quickly deployed to different models of tower cranes.

[0124] Figure 2 This is a structural block diagram of a project engineering data monitoring and management device in some embodiments of this disclosure. For example... Figure 2 As shown, the project engineering data monitoring and management device includes: The project construction management module 100 is used to create target projects and target monitoring scenarios under target projects based on project creation instructions, and to associate target monitoring scenarios with target data sources; The algorithm template configuration module 200 is used to configure the algorithm template for the target monitoring scene based on the algorithm template configuration instructions and the algorithm template configuration engine, so as to obtain the target algorithm template for the target monitoring scene. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration and early warning value configuration. Template data mapping module 300 is used to construct the mapping relationship between the target algorithm template and the target data source; The real-time business data and business application module 400 is used to process real-time data from the target data source based on the mapping relationship using the real-time data processing engine, obtain data processing results, and perform business applications based on the data processing results. The business applications include generating business forms and displaying real-time data in a visual way. The early warning response and closed-loop management module 500 is used to respond to data processing results that meet preset early warning conditions, and to perform early warning processing and closed-loop management. The closed-loop management includes generating work orders, recording the processing process and result data.

[0125] In some embodiments of this disclosure, the project construction management module 100 includes: The project management unit is used to create a basic information table and a personnel permission configuration table for the target project based on the project entity creation instructions and through the database model. The scenario management unit is used to create target monitoring scenarios for target projects based on business logic that matches the target project. The data administrator management unit is used to build a data table that maps the target monitoring scenarios to the target data sources. The permission management unit is used to configure permissions based on the personnel permission configuration table using the permission model.

[0126] In some embodiments of this disclosure, metadata configuration includes template name configuration, description configuration, and applicable scenario configuration; data source configuration includes data source selection and establishing a data source mapping relationship table; calculation method configuration includes calculation formula configuration; and warning value configuration includes configuring warning values ​​through a warning threshold configuration interface.

[0127] In some embodiments of this disclosure, the template data mapping module 300 is used to associate the abstract variables in the target algorithm template with the interface of the target data source in the target monitoring scenario through a mapping algorithm, and to receive parameter adjustment instructions through the parameter configuration interface to adjust the parameters.

[0128] In some embodiments of this disclosure, the real-time business data and business application module 400 includes: The data acquisition unit is used to acquire real-time data from the target data source through a scheduled task method. The expression calculation unit is used to perform expression parsing and real-time calculation processing based on the calculation expression corresponding to the real-time data using the real-time data processing engine, and to obtain the data processing result. The early warning judgment unit is used to determine whether to issue an early warning based on the data processing results and preset early warning conditions; The business form generation unit is used to generate business forms based on data processing results using form templates. The data visualization unit is used to display the trends and status of real-time data in the form of charts or curves using a chart rendering engine.

[0129] In some embodiments of this disclosure, the early warning processing includes sending early warning information through multiple channels via message queues and push interfaces; the work order is a hidden danger handling work order generated through a work order template, and the hidden danger handling work order includes abnormal data analysis and handling suggestions.

[0130] In some embodiments of this disclosure, the project engineering data monitoring and management system further includes: The management and analysis module is used to perform correlation analysis on data from different scenarios using a cross-scenario data analysis engine, and to determine the correlation between data from different scenarios. The predictive model building module is used to build predictive models of construction risks and development trends based on historical project engineering data.

[0131] It should be noted that the specific implementation of the project engineering data monitoring and management device in this disclosure is similar to the specific implementation of the project engineering data monitoring and management method in this disclosure, and the technical effects of the project engineering data monitoring and management device in this disclosure are similar to the technical effects of the project engineering data monitoring and management method in this disclosure. For details, please refer to the description of the project engineering data monitoring and management method section. In order to reduce redundancy, it will not be repeated.

[0132] In addition, this disclosure also provides an electronic device, including: Memory, used to store computer programs; A processor is configured to execute a computer program stored in the memory, and when the computer program is executed, to implement the project engineering data monitoring and management method described in any of the above embodiments of this disclosure.

[0133] Below, for reference Figure 3 To describe an electronic device according to embodiments of this disclosure. For example... Figure 3 As shown, the electronic device includes one or more processors and memory.

[0134] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0135] The memory can store one or more computer program products, and the memory can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program products can be stored on the computer-readable storage medium, and the processor can run the computer program products to implement the project engineering data monitoring and management methods of the various embodiments of this disclosure described above, and / or other desired functions.

[0136] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0137] In addition, the input device may also include, for example, a keyboard, a mouse, etc.

[0138] This output device can output various information to the outside, including determined distance information, direction information, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0139] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0140] In addition to the methods and devices described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the monitoring and management methods for project engineering data according to various embodiments of this disclosure as described in the foregoing sections of this specification.

[0141] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0142] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the monitoring and management method for project engineering data according to various embodiments of this disclosure as described in the foregoing portion of this specification.

[0143] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0144] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0145] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0146] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0147] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0148] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.

[0149] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0150] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for monitoring and managing project engineering data, characterized in that, include: Based on the project creation instructions, create a target project and target monitoring scenarios under the target project, and associate the target monitoring scenarios with the target data source; Based on the algorithm template configuration instructions, the algorithm template configuration engine is used to configure the algorithm template for the target monitoring scenario to obtain the target algorithm template for the target monitoring scenario. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration and early warning value configuration. Construct a mapping relationship between the target algorithm template and the target data source; Using a real-time data processing engine, the real-time data of the target data source is processed based on the mapping relationship to obtain data processing results, and business applications are carried out based on the data processing results. The business applications include generating business forms and displaying the real-time data in a visual manner. In response to the data processing result meeting the preset early warning conditions, early warning processing and closed-loop management are performed, wherein the closed-loop management includes generating work orders, recording the processing process and result data.

2. The method according to claim 1, characterized in that, The process of creating a target project and target monitoring scenarios under the target project based on project creation instructions, and associating the target monitoring scenarios with the target data source, includes: Based on the project entity creation instruction, the project basic information table and personnel permission configuration table of the target project are created through the database model. Based on the business logic matching the target project, the target monitoring scenario is created for the target project; Construct a mapping table between the target monitoring scenario and the target data source; The permission model is used to configure permissions based on the personnel permission configuration table.

3. The method according to claim 1, characterized in that, The metadata configuration includes template name configuration, description configuration, and applicable scenario configuration; the data source configuration includes data source selection and establishing a data source mapping relationship table; the calculation method configuration includes calculation formula configuration; and the warning value configuration includes configuring warning values ​​through the warning threshold configuration interface.

4. The method according to claim 1, characterized in that, The process of constructing the mapping relationship between the target algorithm template and the target data source includes: The abstract variables in the target algorithm template are associated with the interface of the target data source in the target monitoring scenario through a mapping algorithm, and parameter adjustment instructions are received through the parameter configuration interface to adjust the parameters.

5. The method according to claim 1, characterized in that, The step of using a real-time data processing engine to process real-time data from the target data source based on the mapping relationship, obtaining data processing results, and then applying these results to business applications includes: Real-time data from the target data source is obtained through a scheduled task method. Using the real-time data processing engine, expression parsing and real-time calculation processing are performed based on the calculation expression corresponding to the real-time data to obtain the data processing result; Based on the data processing results and preset warning conditions, determine whether to issue a warning; Using a form template, generate the business form based on the data processing results; The trend and status of the real-time data are displayed in the form of charts or curves using a chart rendering engine.

6. The method according to claim 1, characterized in that, The early warning processing includes sending early warning information through multiple channels via message queues and push interfaces; the work order is a hidden danger handling work order generated through a work order template, and the hidden danger handling work order includes abnormal data analysis and handling suggestions.

7. The method according to claim 1, characterized in that, Also includes: By using a cross-scenario data analysis engine, correlation analysis is performed on data from different scenarios to determine the relationships between data from different scenarios; A predictive model for construction risks and development trends is built based on historical project engineering data.

8. A monitoring and management system for project engineering data, characterized in that, include: The project construction management module is used to create a target project and target monitoring scenarios under the target project based on the project creation command, and to associate the target monitoring scenarios with the target data source; The algorithm template configuration module is used to configure the algorithm template for the target monitoring scenario based on the algorithm template configuration instructions and the algorithm template configuration engine, so as to obtain the target algorithm template for the target monitoring scenario. The algorithm template configuration includes metadata configuration, data source configuration, calculation method configuration and early warning value configuration. Template data mapping relationship, used to construct the mapping relationship between the target algorithm template and the target data source; The real-time business data and business application module is used to process the real-time data of the target data source based on the mapping relationship using a real-time data processing engine to obtain data processing results, and to perform business applications based on the data processing results. The business applications include generating business forms and displaying the real-time data in a visual manner. The early warning response and closed-loop management module is used to respond to the data processing results meeting preset early warning conditions, and to perform early warning processing and closed-loop management, wherein the closed-loop management includes generating work orders, recording the processing process and result data.

9. An electronic device, characterized in that, include: Memory, used to store computer program products; A processor for executing a computer program product stored in the memory, wherein when the computer program product is executed, it implements the method described in any one of claims 1-7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1-7.

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