Construction process monitoring system and method for constructional engineering

Abstract

The invention belongs to the technical field of construction process monitoring, and particularly relates to a construction process monitoring system and method for constructional engineering, and the system comprises a data collection module, a data transmission layer module, a data processing and analysis module, a business application module, a user interaction module, and a system management and integration module. According to the invention, active prevention and control of construction risks are realized through Internet of Things + AI multi-source data fusion; progress-resource-cost integrated closed-loop control is carried out, and intelligent linkage of engineering elements is realized based on BIM and machine learning; a multi-terminal collaborative efficient management closed loop is achieved, and a three-level collaborative chain of'field-management-decision 'is opened; the invention discloses an edge-cloud collaborative lightweight intelligent architecture, and solves the bottleneck of calculation and transmission in a complex environment of a construction site.

Description

Technical Field

[0001] The present invention belongs to the technical field of construction process monitoring, and specifically refers to a construction process monitoring system and method for a building project. Background Art

[0002] Construction engineering is the dynamic process of transforming a building from a blueprint into a physical object through the collaborative work of manpower, materials, and machinery, in accordance with design drawings and technical specifications. This process is characterized by long cycles, complex procedures, numerous participants, and a volatile environment. Traditional management models, which primarily rely on manual inspections and the circulation of paper documents, have significant drawbacks: Passive post-event response: Safety risks and quality issues often rely on post-event inspections for detection. Hidden dangers such as excessive structural displacement and illegal worker operations are difficult to detect in a timely manner, resulting in a high rate of underreporting. Delayed responses often lead to increased losses. Extensive progress monitoring: Progress management relies on manual weekly reporting, resulting in delayed data collection. By the time actual construction deviations are discovered, the optimal intervention window has already been missed, causing average construction duration to exceed schedules. Fragmented information transmission: Paper checklists, acceptance records, change visas, and other documents are scattered among various parties. This fragmented information leads to low collaboration efficiency. Tracing quality issues requires cross-departmental document review, which takes a long time on average. Resource scheduling is empirical: The allocation of labor, machinery, and materials relies on managers' subjective experience, resulting in frequent on-site idleness and supply interruptions, and low resource utilization. Weak decision-making support: There is a lack of real-time data analysis for key indicators such as cost overruns and safety risks. Management decisions rely on fragmented reports, making it difficult to dynamically optimize construction strategies. Summary of the Invention

[0003] In view of the above situation, the present invention provides a construction process monitoring system for a building project.

[0004] The technical solution adopted by the present invention is as follows: The present invention provides a construction process monitoring system for a construction project, comprising: Data acquisition module: responsible for obtaining various types of data from the physical world in real time; Data transmission layer module: responsible for transmitting the collected data to the cloud; Data processing and analysis module: responsible for data storage, management, cleaning, fusion, calculation and intelligent analysis; Business application module: implements specific monitoring and management functions based on underlying data and capabilities; User interaction module: provides users with access and usage interface; System management and integration module: ensures stable operation of the system and interconnection with other systems.

[0005] Furthermore, the data acquisition module includes: IoT sensor units‌‌; Video surveillance and AI vision unit‌: An AI analysis server deployed on-site, running a convolutional neural network recognition algorithm; Mobile terminal collection unit: used for reporting progress, filling in quality inspection records, safety hazards, material acceptance, clocking in and out, and receiving notifications; Automation equipment interface unit.

[0006] Furthermore, the data transmission layer module includes: Construction site network unit‌‌‌; Data transmission protocol and gateway unit‌.

[0007] Furthermore, the data processing and analysis module includes: ‌Data storage and management unit‌; Data Integration and ETL Unit: Integrate data from different sources, cleanse, transform, and standardize data; BIM engine unit: Lightweight BIM model parsing and rendering, providing an API for other modules to access model information, and supporting the association and attachment of progress, quality, and safety data with BIM model components; Business rule engine unit: defines and executes business logic; Machine Learning Unit: This unit uses a visual geometry group network running in the cloud to perform safety behavior recognition and progress image recognition, and predict progress trends, cost deviations, and potential risks based on historical data and current status. Geographic Information System Unit: Processes spatial data and supports progress display, equipment positioning, and regional management of large linear projects on GIS maps.

[0008] Furthermore, the business application module: Progress Monitoring and Management Unit: used for progress plan import and maintenance, actual progress collection and reporting, progress comparison and analysis, deviation calculation, and lag warning; Quality management and control unit: used for mobile inspection records, key process acceptance control, actual measurement data management, and pass rate analysis; Security management and monitoring unit: used for real-name system and personnel positioning management, AI behavior safety identification and alarm management, mechanical equipment operation monitoring and alarm, and environmental monitoring and alarm.

[0009] Resource Management Unit: used for labor management, machinery and equipment management, and material management; Cost management unit: used for target cost maintenance, actual cost collection, cost deviation analysis, output value calculation, and progress payment management; Collaboration and document management unit: used for task assignment and tracking; Reporting and decision support unit: customized report designer, data visualization dashboard, multi-dimensional data analysis, forecasting and simulation results display.

[0010] Furthermore, the user interaction module includes: Web management platform: provides comprehensive monitoring views, data analysis, reporting, and system configuration functions; Mobile application: used for progress reporting, quality inspection, safety inspection, problem reporting, material acceptance, receiving notifications, viewing drawings / specifications, and clocking in and out; Large-screen visualization system: centrally displays key project KPIs, real-time monitoring images, early warning information, and BIM visualization.

[0011] Furthermore, the system management and integration module includes: Configuration management unit: used for user management, role permission management, project configuration, device management, and rule configuration; Operation and maintenance monitoring unit: used to monitor the system's own operating status; API Gateway and Integration Unit: Provides standard APIs for external systems to call.

[0012] Furthermore, the construction site network unit includes: Wired network: used for fixed cameras, sensor aggregation points, and computer rooms; Wireless network: used to cover office areas, living areas, and main work areas.

[0013] Furthermore, the data transmission protocol and gateway module include: IoT Gateway: Aggregates sensor data of different protocols and converts them into standard protocols for uploading; Edge computing nodes: perform preliminary data processing, filtering, and compression to reduce upload bandwidth requirements.

[0014] This solution also discloses an operating method of the construction progress monitoring system of a construction project, which mainly includes the following steps: Step A1: Initialize and deploy the system, build the construction site network, and deploy and activate sensors, AI cameras, edge nodes, and gateway hardware devices; Step A2: Configure the software platform, import BIM models, GIS data, project plans, cost budgets, and configure the business rule engine and database; Step A3: Sensors automatically collect environmental / structural / equipment data, AI cameras identify safety behaviors in real time, and mobile terminals manually report progress, quality, safety issues, and material information. Step A4: Edge and cloud data processing: edge nodes perform real-time AI analysis and preliminary data processing; the cloud platform performs data cleaning and fusion, rule engine judgment, machine learning prediction, and triggers automatic warnings. Step A5: Link the BIM model to achieve progress visualization and deviation warning, enforce the quality acceptance process for key processes, and link positioning and AI monitoring to ensure the safety of personnel and equipment; Step A6: Multi-terminal interaction and response: On-site personnel receive alerts and execute tasks via mobile devices; managers view analytical dashboards and real-time status via the web platform; and the system automatically executes linkage control and generates business documents.

[0015] Step A7: Collaborative task closed-loop management. The system automatically assigns rectification and other tasks and tracks the closed loop, associates documents with BIM versions to ensure consistency, and dynamically adjusts resource scheduling plans.

[0016] Step A8: System operation and maintenance monitoring, monitoring the system's own operating status and equipment online status, and regularly backing up data; Step A9: Data-driven optimization iteration, using historical data to train and optimize the prediction model, and exchange data with external systems through the API gateway.

[0017] The beneficial effects achieved by the present invention using the above structure are as follows: The present invention provides a construction process monitoring system for a construction project, achieving the following beneficial effects: (1) Actively prevent and control construction risks through the fusion of IoT + AI multi-source data.

[0018] (2) Integrated closed-loop control of progress, resources and costs, and intelligent linkage of engineering elements based on BIM and machine learning.

[0019] (3) An efficient management closed loop with multi-terminal collaboration opens up the three-level collaboration chain of “site-management-decision-making”.

[0020] (4) A lightweight intelligent architecture with edge-cloud collaboration can solve the computing and transmission bottlenecks in complex construction site environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of the construction process monitoring system for a building project proposed by the present invention.

[0022] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] Example 1: See also Figure 1 As shown, this embodiment is a construction process monitoring system for a construction project, including a data acquisition module, a data transmission layer module, a data processing and analysis module, a business application module, a user interaction module, and a system management and integration module; Among them, the data acquisition module is responsible for obtaining various types of data from the physical world in real time; Among them, the data transmission layer module is responsible for transmitting the collected data to the cloud; The data processing and analysis module is responsible for data storage, management, cleaning, fusion, calculation, and intelligent analysis. Among them, the business application module implements specific monitoring and management functions based on the underlying data and capabilities; Among them, the user interaction module provides users with an access and usage interface; Among them, the system management and integration module ensures the stable operation of the system and its interconnection with other systems.

[0025] Example 2: See also Figure 1 As shown, this embodiment is a method for using a construction process monitoring system for a construction project, comprising the following steps: Step A1: Initialize and deploy the system, build the construction site network, and deploy and activate sensors, AI cameras, edge nodes, and gateway hardware devices; Step A2: Configure the software platform, import BIM models, GIS data, project plans, cost budgets, and configure the business rule engine and database; Step A3: Sensors automatically collect environmental / structural / equipment data, AI cameras identify safety behaviors in real time, and mobile terminals manually report progress, quality, safety issues, and material information. Step A4: Edge and cloud data processing: edge nodes perform real-time AI analysis and preliminary data processing; the cloud platform performs data cleaning and fusion, rule engine judgment, machine learning prediction, and triggers automatic warnings. Step A5: Link the BIM model to achieve progress visualization and deviation warning, enforce the quality acceptance process for key processes, and link positioning and AI monitoring to ensure the safety of personnel and equipment; Step A6: Multi-terminal interaction and response: On-site personnel receive alerts and execute tasks via mobile devices; managers view analytical dashboards and real-time status via the web platform; and the system automatically executes linkage control and generates business documents.

[0026] Step A7: Collaborative task closed-loop management. The system automatically assigns rectification and other tasks and tracks the closed loop, associates documents with BIM versions to ensure consistency, and dynamically adjusts resource scheduling plans.

[0027] Step A8: System operation and maintenance monitoring, monitoring the system's own operating status and equipment online status, and regularly backing up data; Step A9: Data-driven optimization iteration, using historical data to train and optimize the prediction model, and exchange data with external systems through the API gateway.

[0028] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

[0029] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. The construction process monitoring system of the construction project is characterized by: include: Data acquisition module: responsible for obtaining various types of data from the physical world in real time; Data transmission layer module: responsible for transmitting the collected data to the cloud; Data processing and analysis module: responsible for data storage, management, cleaning, fusion, calculation and intelligent analysis; business application module: based on the underlying data and capabilities, implements specific monitoring and management functions; user interaction module: provides users with access and usage interfaces; system management and integration module: ensures stable system operation and interconnection with other systems.

2. The construction process monitoring system for a construction project according to claim 1, characterized in that: The data acquisition module includes: an IoT sensor unit; a video surveillance and AI vision unit: an AI analysis server deployed on the construction site, running a convolutional neural network recognition algorithm; a mobile terminal acquisition unit: used for reporting progress, filling in quality inspection records, safety hazards, material acceptance, clocking in and out, and receiving notifications; and an automated equipment interface unit.

3. The construction process monitoring system for a construction project according to claim 2, characterized in that: The data transmission layer module includes: construction site network unit; data transmission protocol and gateway unit.

4. The construction process monitoring system for a construction project according to claim 3 is characterized in that: The data processing and analysis module includes: ‌Data Storage and Management Unit‌;‌Data Integration and ETL Unit‌: Integrates data from different sources, cleans, converts, and standardizes data;‌BIM Engine Unit‌: Lightweight BIM model parsing and rendering, provides APIs for other modules to call model information, and supports the association and attachment of progress, quality, and safety data with BIM model components;‌Business Rule Engine Unit‌: Defines and executes business logic;‌Machine Learning Unit‌: Uses a visual geometry group network running in the cloud to perform safety behavior recognition and progress image recognition, and predicts progress trends, cost deviations, and potential risks based on historical data and current status;‌Geographic Information System Unit‌: Processes spatial data and supports progress display, equipment positioning, and regional management of large linear projects on GIS maps.

5. The construction process monitoring system for a construction project according to claim 4, characterized in that: Business application module: Progress monitoring and management unit: used for progress plan import and maintenance, actual progress collection and reporting, progress comparison analysis, deviation calculation, and lag warning; Quality Management and Control Unit: used for mobile inspection records, key process acceptance process control, actual measurement data management, and pass rate analysis; Safety Management and Monitoring Unit: used for real-name system and personnel positioning management, AI behavior safety identification and alarm management, mechanical equipment operation monitoring and alarm, environmental monitoring and alarm; Resource Management Unit: used for labor management, mechanical equipment management, and material management; Cost Management Unit: used for target cost maintenance, actual cost aggregation, cost deviation analysis, output value calculation, and progress payment management; Collaboration and Document Management Unit: used for task assignment and tracking; Report and Decision Support Unit: customized report designer, data visualization dashboard, multi-dimensional data analysis, forecast and simulation results display.

6. The construction process monitoring system for a construction project according to claim 5, characterized in that: User interaction modules include: Web management platform: providing comprehensive monitoring views, data analysis, reporting, and system configuration functions; mobile application: used for progress reporting, quality inspections, safety inspections, problem reporting, material acceptance, receiving notifications, viewing drawings / specifications, and clocking in and out; large-screen visualization system: centrally displays key project KPIs, real-time monitoring images, early warning information, and BIM visualization.

7. The construction process monitoring system for a construction project according to claim 6, characterized in that: The system management and integration module includes: Configuration Management Unit: used for user management, role and permission management, project configuration, device management, and rule configuration; Operation and Maintenance Monitoring Unit: used to monitor the system's own operating status; API Gateway and Integration Unit: provides a standard API for external system calls.

8. The construction process monitoring system for a construction project according to claim 7, characterized in that: The construction site network units include: wired network: used for fixed cameras, sensor aggregation points, and computer rooms; wireless network: used to cover office areas, living areas, and main work areas.

9. The construction process monitoring system for a construction project according to claim 8, characterized in that: The data transmission protocol and gateway modules include: IoT gateway: aggregating sensor data of different protocols and converting them into standard protocols for uploading; edge computing node: performing preliminary data processing, filtering, and compression to reduce upload bandwidth requirements.

10. A method for operating a construction process monitoring system for a construction project, characterized in that: The operation of the construction process monitoring system of the construction project according to claim 9 mainly includes the following steps: Step A1: Initialize and deploy the system, build the construction site network, and deploy and activate sensors, AI cameras, edge nodes, and gateway hardware devices; Step A2: Configure the software platform, import BIM models, GIS data, project plans, cost budgets, and configure the business rule engine and database; Step A3: Sensors automatically collect environmental / structural / equipment data, AI cameras identify safety behaviors in real time, and mobile terminals manually report progress, quality, safety issues, and material information. Step A4: Edge and cloud data processing: edge nodes perform real-time AI analysis and preliminary data processing; the cloud platform performs data cleaning and fusion, rule engine judgment, machine learning prediction, and triggers automatic warnings. Step A5: Link the BIM model to achieve progress visualization and deviation warning, enforce the quality acceptance process for key processes, and link positioning and AI monitoring to ensure the safety of personnel and equipment; Step A6: Multi-terminal interaction and response: On-site personnel receive alerts and execute tasks via mobile devices; managers view analytical dashboards and real-time status via the web platform; and the system automatically executes linkage control and generates business documents. Step A7: Collaborative task closed-loop management: the system automatically assigns tasks such as rectification and tracks the closed loop, links documents with BIM versions to ensure consistency, and dynamically adjusts resource scheduling plans; Step A8: System operation and maintenance monitoring, monitoring the system's own operating status and equipment online status, and regularly backing up data; Step A9: Data-driven optimization iteration, using historical data to train and optimize the prediction model, and exchange data with external systems through the API gateway.

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