A construction engineering cost feedback system and method based on quantity analysis

Abstract

This invention discloses a construction project cost feedback system and method based on quantity analysis; it includes a drawing acquisition module for acquiring multiple versions of drawing data generated at different design stages of a construction project; and a quantity analysis engine connected to the drawing acquisition module for automatically extracting quantity data from any version of drawing data based on preset building component identification rules in response to the import of such data; the quantity data includes at least the amount of building materials used and the corresponding construction quantities; by directly connecting the quantity analysis engine to the drawing acquisition module, this invention achieves automatic quantity calculation upon import of design drawings, and simultaneous pricing by the cost calculation engine, enabling designers to obtain the corresponding project cost amount while completing the design of any version of drawings, transforming the traditional serial process of "design-delivery-quantity calculation-feedback" into a parallel process of "design-quantity calculation-feedback", significantly shortening the design iteration cycle.

Description

Technical Field

[0001] This invention relates to the field of engineering cost technology, specifically to a construction engineering cost feedback system and method based on engineering quantity analysis. Background Technology

[0002] Construction cost management is a crucial aspect of project implementation, directly impacting the project's economic benefits and the safety of investors' funds. Traditional cost calculation methods typically involve professional cost engineers calculating quantities and costs manually or semi-automatically using software (such as Glodon and Luban) based on the completed architectural drawings, construction specifications, and market information. This sequential "design first, then calculate" workflow has long suffered from the following inherent flaws in practice: The separation of design and cost leads to uncontrollable budgets. When creating designs, designers often focus on building function, spatial layout, structural safety, and aesthetic effects, lacking immediate and accurate feedback on the associated costs. Designers can only rely on their past construction experience to make a rough cost estimate for the client. Such estimates rely heavily on individual subjective experience, lack precise data support, and are prone to significant errors. Once the design is completed and construction begins, the actual construction cost often far exceeds the initial estimate, leading to budget overruns, straining the owner's cash flow, and even causing disputes, seriously affecting the owner's satisfaction and the smooth progress of the project.

[0003] Furthermore, the actual implementation of projects is often hampered by delays and inefficiencies in responding to design changes. In real-world projects, especially during communication and interaction with the client, scheme optimization, or to meet specific requirements, design drawings often undergo multiple iterations and modifications (such as version 1, version 2, etc.). Whenever drawings change, the traditional cost calculation process must be restarted. Cost engineers must manually identify the changed parts, recalculate the quantities, and update the pricing. This is not only labor-intensive and inefficient, but also prone to omissions and errors due to human negligence. It is also difficult to provide timely and accurate feedback to the design team and the client on the impact of design changes on the total project cost, making the idea of ​​dynamically adjusting the budget as a ceiling difficult to achieve.

[0004] Furthermore, precise cost control is challenging, and traditional cost calculation methods struggle to support such precise cost control during the design phase. For instance, when the client has a fixed budget ceiling, designers may want to explore ways to enhance project value or living experience by adjusting design schemes (such as optimizing spatial layout, changing building structure, or adjusting decorative materials) while keeping the total budget constant. However, due to the lack of real-time cost feedback mechanisms, designers cannot directly see the specific impact of each design decision (such as adjusting wall partitions or changing the number of rooms) on costs for steel, cement, labor, and machinery. Consequently, it is difficult to make optimal decisions that balance functionality and cost.

[0005] This leads to insufficient comprehensive cost estimation for the entire project. Traditional quantity calculations and pricing mainly focus on major building materials (such as steel bars and cement) and standard construction procedures. Derivative costs closely related to specific design schemes, such as additional labor hours based on the complexity of specific steel bar binding, changes in construction water, electricity, and machinery consumption due to structural changes, and vehicle transportation costs due to changes in transportation distance, are often difficult to accurately estimate during the design phase, resulting in significant discrepancies between the final cost estimate and the actual costs incurred.

[0006] In summary, existing technologies lack an intelligent system and method capable of rapidly, accurately, and dynamically calculating the quantity and cost of construction work during the architectural design process, especially when faced with multiple versions of drawings. The traditional model of separating design and cost control can no longer meet the urgent needs of modern construction projects for refined, visualized, and proactive cost management, a problem that is particularly pronounced in the field of small-scale construction where cost control and user experience are emphasized.

[0007] Therefore, the market urgently needs an intelligent solution that can deeply integrate design and cost, and achieve synchronous calculations as the design version iterates.

[0008] In view of the problems exposed in the use of the current construction project cost feedback system and method based on quantity analysis, it is necessary to iterate and optimize the construction project cost feedback system and method based on quantity analysis. Summary of the Invention

[0009] To address the aforementioned technical problems, this invention provides a construction project cost feedback system and method based on engineering quantity analysis, which features dynamic cost control.

[0010] To achieve the above objectives, the present invention provides the following technical solution: a construction project cost feedback system based on engineering quantity analysis, comprising: The drawing acquisition module is used to acquire multiple versions of drawing data generated at different design stages of a building project. The quantity analysis engine, connected to the drawing acquisition module, is used to automatically extract the quantity data from any version of the drawing data in response to the import of any version of the drawing data, based on preset building component identification rules; the quantity data includes at least the amount of building materials used and the corresponding construction work quantity; The cost calculation engine, connected to the engineering quantity analysis engine, is used to receive the engineering quantity data, call the preset cost database, and combine dynamic variable factors to calculate and generate the current engineering cost amount corresponding to this version of the drawings. The feedback and interaction module is used to visually display the current project cost to the user and compare it with a preset budget ceiling threshold. When the current project cost exceeds the budget ceiling threshold, an early warning signal is generated; When the current project cost does not exceed the budget ceiling threshold, record the cost data for this version of the drawings and provide a cost adjustment reference for the next version of the drawings.

[0011] As a preferred technical solution of the construction project cost feedback system based on engineering quantity analysis according to the present invention, the engineering quantity analysis engine specifically includes: The hard decoration analysis unit is used to analyze the drawings of the building frame, calculate the material consumption of the main structure based on the layout parameters of steel bars and cement, and estimate the on-site construction labor hours required for the corresponding material consumption based on the preset labor hour coefficient table. The interior design analysis unit is used to analyze the interior decoration drawings and obtain the list of interior materials and the corresponding installation work. The variable calculation unit is used to calculate the required auxiliary resource consumption based on the material usage and the construction workload; the auxiliary resources include one or more of the following: construction electricity, construction water, and vehicle transportation frequency.

[0012] As a preferred technical solution of the construction engineering cost feedback system based on engineering quantity analysis of the present invention, the cost calculation engine includes a dynamic variable factor library; The dynamic variable factor library further includes multiple sub-databases, and the multiple sub-databases include at least: The labor hour coefficient sub-library is used to store the standard labor hour benchmark values ​​corresponding to different construction procedures; The difficulty adjustment coefficient sub-library is used to store adjustment coefficients for different building structure complexities, which are obtained by fitting historical construction data. The adjustment coefficients are generated after regression analysis based on the number of different structural nodes, steel reinforcement density grade and floor height variables in historical projects. The environmental and resource consumption sub-database is used to store auxiliary resource consumption coefficients corresponding to different construction seasons, transportation distances, and on-site operating conditions. The cost calculation engine also includes a complexity identification unit, which is used to receive engineering quantity data from the engineering quantity analysis engine, analyze the building structure features in the engineering quantity data, and extract index parameters to characterize the complexity of the drawings; the index parameters include at least the number of steel bar nodes per unit area, the proportion of irregular components, or the coefficient of variation of floor net height. The cost calculation engine also includes a dynamic correction unit, which is used to match the corresponding target adjustment coefficient in the difficulty adjustment coefficient sub-library according to the index parameters extracted by the complexity identification unit. The target adjustment coefficient is applied to the standard labor hour baseline value in the labor hour coefficient sub-library to generate a corrected labor cost that dynamically adapts to the complexity of the current version of the drawing. Simultaneously, based on the construction season parameters and transportation distance parameters corresponding to the current version of the drawings, the corresponding auxiliary resource consumption coefficients are called from the environmental and resource loss sub-library to synchronously correct the electricity, water, and vehicle transportation costs required for construction.

[0013] As a preferred technical solution of the construction engineering cost feedback system based on engineering quantity analysis of the present invention, the feedback and interaction module further includes a visualization comparison sub-module; The visualization comparison submodule includes a split-screen display unit, which is used to generate a first display area and a second display area on the same user interface in a left-right or top-bottom split-screen layout. The first display area is used to load and display the first three-dimensional building model corresponding to the first version of the drawings, and to display the first project cost amount in a floating layer at a preset position of the first three-dimensional building model; The second display area is used to load and display the second three-dimensional building model corresponding to the second version of the drawings, and to display the second project cost amount in a floating layer at a preset position of the second three-dimensional building model; The visualization comparison submodule also includes a difference analysis engine, which is connected to the engineering quantity analysis engine and the cost calculation engine. It is used to automatically compare the engineering quantity differences between the first version of the drawings and the second version of the drawings at the component level, and generate a cost difference dataset that includes at least material usage difference items, labor hour difference items and auxiliary resource consumption difference items. Based on the cost difference dataset, in the first display area and the second display area, a preset visual coding rule is used to differentiate the highlighting color of building components whose costs have changed; wherein components with increased costs are highlighted with the first color level, and components with decreased costs are highlighted with the second color level. The visualization comparison submodule also includes an associated positioning unit, which is used to automatically identify the drawing modification location corresponding to the component in response to the user's click or hover operation on a highlighted component in any display area. In another display area, the corresponding component corresponding to the modified position is simultaneously located and highlighted, and a comparison card showing the cost changes of this component between the two versions pops up in the sidebar of the interface.

[0014] As a preferred technical solution of the construction engineering cost feedback system based on engineering quantity analysis according to the present invention, the system further includes an intelligent auxiliary design sub-module; The intelligent auxiliary design submodule is connected to the feedback and interaction module and includes an over-budget cause analysis unit. The over-budget cause analysis unit is used to receive the current project cost amount and the corresponding cost difference item data when the feedback and interaction module generates an early warning signal, and to sort the cost difference items by weight to identify the key cost items that cause the budget over-budget and their corresponding building components. The intelligent assisted design submodule also includes an optimization strategy rule base, which stores multiple preset optimization strategy mapping relationships. The optimization strategy mapping relationship includes the correspondence between cost item type and optimization action, wherein structural cost exceeding the standard corresponds to space reconstruction optimization action, material cost exceeding the standard corresponds to material replacement optimization action, and labor cost exceeding the standard corresponds to process simplification optimization action. Optimize the relationship between actions and building component adjustment parameters. Among them, spatial reconstruction optimization actions should be associated with at least wall deletion parameters, room merging parameters, or opening parameters. The intelligent auxiliary design submodule also includes an optimization scheme generation engine, which is connected to the excess cause analysis unit and the optimization strategy rule base respectively, and is used to match the corresponding target optimization action in the optimization strategy rule base according to the identified key cost item and its corresponding building component. Based on the target optimization action and the current design parameters of the building components, the preset building code constraints are invoked to automatically generate at least one optimized design scheme that meets the code requirements. The optimized design schemes include, but are not limited to, a space reconstruction scheme that reduces the amount of masonry structure work by reducing room partitions; a layout optimization scheme that reduces the number of load-bearing walls or shortens pipeline paths by adjusting the unit layout; and a material replacement scheme that generates a material replacement scheme by selecting the same type and specifications of building materials with lower unit prices from a preset list of replaceable materials. The intelligent assisted design submodule also includes a scheme preview and switching unit, which is used to push the generated optimized design scheme to the feedback and interaction module, and preview and display it in the visualization comparison submodule in the form of a three-dimensional model overlay. The optimization scheme responds to the user's selection operation by automatically replacing the corresponding building components in the current version of the drawings with the component parameters in the optimized design scheme, generating a new optimized version of the drawings, and triggering the engineering quantity analysis engine and cost calculation engine to recalculate the cost of the new version in real time.

[0015] As a preferred technical solution of the construction project cost feedback system based on engineering quantity analysis according to the present invention, the drawing acquisition module supports drawing version management, including: A version data structure definition unit is used to define a unified version data storage structure for each version of the drawing; the version data storage structure includes at least: The version metadata area is used to store the version number, version creation time, version modification author, and version modification notes. The drawing design data area is used to store the drawing files and parametric data of building components corresponding to this version. The cost snapshot data area is used to store the engineering quantity analysis results and engineering cost amount associated with this version of the drawings. The cost snapshot data includes at least the details of the cost of each item of the project and the total cost. The version difference data area is used to store a summary of the changes made in this version compared to the previous version, as well as the corresponding cost change details; The drawing acquisition module also includes a version snapshot generation unit, which is connected to the engineering quantity analysis engine and the cost calculation engine respectively. It is used to automatically trigger the version snapshot generation command in response to the import of any version of the drawing and the completion of the cost calculation. Obtain intermediate data of the quantity analysis of this version of the drawing from the quantity analysis engine, and obtain the project cost amount and details of this version of the drawing from the cost calculation engine. The intermediate data of the project quantity analysis, the project cost amount and details, together with the file data of the current version of the drawings and the version remarks information entered by the user, are encapsulated according to the version data storage structure to generate a historical snapshot of the project cost for this version. The drawing acquisition module further includes a version association and tracing unit, which is used for: Record the inheritance relationship between the historical snapshots of the project cost for each version, forming a version association tree with the initial version as the root node and the iterative versions as branch nodes; In response to the user's selection operation on any historical version node in the version association tree, load and display the drawing data and cost snapshot data corresponding to this historical version; In response to the user's version comparison command, any two selected versions are extracted from the version association tree, and the summary of the modified content and the details of cost changes are read from the corresponding version difference data area. The results are then pushed to the visualization comparison submodule of the feedback and interaction module for difference display.

[0016] As a preferred technical solution of the construction project cost feedback system based on engineering quantity analysis according to the present invention, the engineering quantity analysis engine supports the analysis of engineering quantities for sub-items of the project, specifically including: A project structure decomposition unit is used to decompose a construction project into multiple levels of sub-item engineering nodes from top to bottom according to a preset construction project bill of quantities pricing specification or internal enterprise quota standard; the multiple levels include at least: Unit project layer nodes correspond to the entire building unit; The sub-project level nodes include at least the foundation and substructure sub-project, the main structure sub-project, the building decoration and finishing sub-project, and the building roof sub-project; The sub-item engineering layer node, under the main structure sub-section, includes at least the cast-in-place concrete formwork sub-item, the steel reinforcement fabrication and installation sub-item, the concrete pouring sub-item, and the masonry construction sub-item; The engineering quantity analysis engine also includes a component attribution identification unit, which is used to receive the geometric parameters, material properties and spatial positioning data of each building component extracted from the drawings; Based on the type label and spatial location of the building components, each building component is automatically mapped to the corresponding sub-item project layer node; among them, frame columns and frame beams are mapped to the steel reinforcement and concrete sub-item of the main structure sub-section, infill wall components are mapped to the masonry sub-item, and wall plaster layer is mapped to the plastering sub-item of the decoration and finishing sub-section. The engineering quantity parsing engine also includes a sub-item data encapsulation unit, which is used to summarize the engineering quantity of the building components to which each sub-item engineering layer node belongs, and generate the engineering quantity list corresponding to the sub-item. The bill of quantities is pushed to the cost calculation engine to obtain the detailed cost of the corresponding sub-item; the detailed cost of the sub-item is associated and encapsulated with the corresponding sub-item layer node, and a unique sub-item identifier is assigned and stored in the cost snapshot data area. The feedback and interaction module allows users to click and view the real-time cost details of any specific sub-item of the project, specifically including: A sub-item level drill-down unit is used to display the sub-item project nodes of multiple levels generated by the project structure decomposition unit in a tree directory or waterfall layout on the user interface. In response to a user's click operation on any of the sub-item project layer nodes, the corresponding sub-item project cost details data are retrieved in real time from the cost snapshot data area according to the sub-item identification code corresponding to the node; A detailed breakdown display unit is used to display the detailed breakdown cost of the clicked sub-item project in a preset area of ​​the current interface, in the form of a card-style overlay or a sidebar panel. The detailed cost breakdown of each item of work shall include at least: the name and code of the item, the total cost of the item, the bill of quantities and unit price analysis of various building components under the item, and the details of labor costs, material costs, machinery costs and management fees for the item. A component-level associated highlighting unit is used to simultaneously highlight all building components belonging to a certain sub-item in the drawing display area or 3D model display area when the sub-item detail display unit displays the cost details of a certain sub-item; In response to a user's hovering or clicking operation on a specific bill of quantities item in the detailed cost breakdown of the sub-project, the single or multiple building components corresponding to that bill of quantities item are further located and highlighted in the drawing display area; A dynamic update unit is used to automatically update the bill of quantities and detailed cost of each sub-item of the project structure decomposition unit when the current version of the drawings undergoes design changes and triggers a recalculation of the quantities and costs. Ensure that the detailed cost breakdown of each project item retrieved by the user through the sub-item level drilling unit is always consistent with the current version of the drawings in real time.

[0017] As a preferred technical solution of the construction engineering cost feedback system based on engineering quantity analysis of the present invention, the system adopts a hybrid deployment architecture and supports deployment on cloud servers or local clients; When the system is deployed on a cloud server, it includes: A cloud service access unit is used to manage access requests from multiple concurrent users through load balancing technology and allocate an independent computing resource instance to each access session; the drawing acquisition module further includes a web-based upload submodule, which is used to receive multiple versions of drawing files uploaded by users from their local terminals through a file upload interface provided by a browser; the uploaded drawing files are format-verified and virus-scanned; files that pass verification are temporarily stored in a cloud-based distributed storage system; a unique cloud storage path and access credential are generated for each successfully uploaded drawing file; and the identity of the uploading user and the upload timestamp are recorded. The quantity analysis engine and cost calculation engine are deployed in a backend service cluster on a cloud server, including: An asynchronous task queue is used to queue and process received drawing parsing requests and cost calculation requests in order to avoid service blocking in high-concurrency scenarios; Multiple stateless computing nodes are used to pull tasks from the asynchronous task queue, execute engineering quantity analysis and cost calculation in parallel, and write the calculation results back to the cloud database; A result caching unit is used to store the cost results of multiple recently calculated versions of drawings in a Redis cache to accelerate subsequent repeated queries of the same version; The feedback and interaction module further includes a web-based real-time push submodule, which is used to establish a full-duplex communication channel with the user's browser via the WebSocket protocol. When a task in the asynchronous task queue is completed, the current project cost and the corresponding cost details are actively pushed to the user's browser through the WebSocket channel. The user's browser can receive and dynamically render the updated cost data and visualization charts in real time without refreshing the page. When the system is deployed on a local client, it includes: A local offline execution unit is used to independently complete all functions of drawing acquisition, quantity analysis, cost calculation and feedback interaction by calling the computing resources of the local client in an environment without network connection or with an unstable network. A local data storage unit is used to store multiple versions of drawing data, intermediate data of quantity analysis, and historical snapshots of project cost in a local file system or embedded database (such as SQLite); A data synchronization unit is used to automatically synchronize the locally stored incremental version data and cost snapshots to the cloud server according to a preset conflict resolution strategy when the network connection is restored. The system also includes a deployment mode adaptive unit, which automatically detects the current network status and server reachability when the system starts up or during operation, and automatically switches between cloud online mode and local offline mode according to a preset switching strategy, or provides an availability prompt for the current mode when the user manually selects a mode. When switching back from offline mode to online mode, the system automatically triggers the data synchronization unit to perform data synchronization operations to ensure the consistency of cloud and local data.

[0018] As a preferred technical solution of the construction project cost feedback method based on engineering quantity analysis according to the present invention, it includes the following steps: Step S1: Obtain multiple versions of drawing data generated at different design stages of the architectural project; Step S2: In response to the import of any version of drawing data, based on the preset building component identification rules, automatically extract the engineering quantity data in this version of the drawing; the engineering quantity data includes at least the amount of building materials used and the corresponding construction engineering quantity; Step S3: Receive the engineering quantity data, call the preset cost database, and calculate the current engineering cost amount corresponding to this version of the drawings by combining dynamic variable factors; Step S4: Visually display the current project cost to the user and compare it with the preset budget ceiling threshold; If the threshold is exceeded, an early warning signal is generated and adjustments are prompted; if the threshold is not exceeded, the cost data for this version of the drawing is recorded and used as a reference for the next version of the drawing iteration.

[0019] As a computer-readable storage medium of the present invention, a preferred technical solution of a computer program is stored thereon, and when the program is executed by a processor, it implements the method described in claim 9.

[0020] Compared with the prior art, the beneficial effects of the present invention are: 1. This technical solution effectively achieves real-time collaboration between design and cost estimation, breaking the traditional serial process. In the traditional construction project cost calculation model, design work and cost calculation are separated. Usually, cost engineers can only manually calculate quantities and prices after all drawings are completed, resulting in a serious lag in cost information during the design phase. This invention directly connects the quantity analysis engine with the drawing acquisition module, realizing automatic quantity calculation upon importing design drawings, and simultaneous price calculation by the cost calculation engine. This allows designers to obtain the corresponding project cost amount as soon as they complete any version of the design drawings, transforming the traditional serial process of "design-delivery-quantity calculation-feedback" into a parallel process of "design-quantity calculation-feedback", significantly shortening the design iteration cycle.

[0021] 2. This solution can improve the accuracy and intelligence of engineering cost calculation. Traditional cost calculation often uses fixed quotas or simple coefficients, which are difficult to reflect the personalized characteristics of different projects. This invention innovatively introduces a dynamic variable factor library into the cost calculation engine, including a sub-library of labor hour coefficients, a sub-library of difficulty adjustment coefficients, and a sub-library of environmental and resource consumption, realizing multi-dimensional and multi-level dynamic correction. Through the complexity identification unit, the structural features of the building in the engineering quantity data are automatically analyzed, and quantitative indicators such as node density, proportion of irregular components, and net height variation coefficient are extracted. This transforms the traditional experience-based "qualitative judgment" into calculable and traceable "quantitative analysis," providing a scientific basis for subsequent dynamic correction and making the cost calculation results more objective and repeatable.

[0022] 3. When using this solution, it can effectively enhance budget control capabilities and achieve proactive optimization with the budget as the ceiling. Through real-time budget threshold comparison and intelligent early warning, the project cost is automatically compared with the preset budget while generating the project cost amount. When the cost exceeds the budget, an early warning signal is generated in real time and pushed to relevant personnel through a visual interface, turning passive over-limit into proactive early warning and saving valuable adjustment time for all parties involved in the project. When a budget overrun is detected, the intelligent assisted design submodule can automatically generate multiple optimized design solutions based on cost discrepancies, including reducing room partitions, adjusting unit layouts, and replacing similar building materials. It also supports solution preview and one-click switching. This feature upgrades the traditional "problem detection - manual analysis - manual modification" process to a semi-automated decision-making model of "problem detection - intelligent suggestions - selection and confirmation," significantly reducing the trial-and-error costs for designers and truly achieving proactive optimization with the budget as the ceiling.

[0023] 4. The visualization comparison submodule in the solution supports displaying the project cost and 3D building model of different versions of drawings side by side on the same interface, and highlights the cost changes through color gradation differences. This function allows designers, owners, and construction parties to intuitively understand the specific impact of design changes on costs in the same view, greatly improving the efficiency of multi-party communication and avoiding misunderstandings and disputes caused by information asymmetry.

[0024] 5. This system supports both cloud deployment and local client deployment modes, and can automatically detect network status and switch modes accordingly. In cloud mode, multiple users can access the system concurrently, and computing resources can be elastically scaled. In offline mode, the local client can still independently complete all functions, and data is automatically synchronized after the network is restored. This hybrid deployment architecture meets the real-time needs of team collaboration while ensuring availability in weak network environments such as construction sites.

[0025] 6. This solution can effectively promote the digital transformation of the industry, accumulate data assets, and continuously accumulate and optimize historical construction data and models. As the system is continuously applied in multiple projects, the adjustment coefficients in the dynamic variable factor library can be iteratively optimized based on actual settlement data, forming a positive cycle of increasing accuracy with use. The difficulty adjustment coefficient sub-library is continuously updated through regression analysis, and the environmental and resource loss sub-library becomes increasingly rich with the accumulation of regional and seasonal data, accumulating valuable data assets for enterprises. This invention organically integrates the quantity analysis engine, cost calculation engine, and feedback interaction module to construct a closed-loop system of design-quantity calculation-feedback-optimization. While improving the accuracy of cost calculation, it also realizes real-time budget control and proactive optimization of design schemes, providing an intelligent, visual, and collaborative innovative solution for the field of construction project cost management. Attached Figure Description

[0026] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0027] Figure 1 This is a schematic diagram of the overall architecture of the present invention; Figure 2 This is a schematic diagram of the internal structure and data flow of the engineering quantity analysis engine in this invention; Figure 3 This is a schematic diagram of the comprehensive data flow of the internal structure of the cost calculation engine in this invention; Detailed Implementation The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Example like Figure 1-3 As shown, the construction project cost feedback system based on engineering quantity analysis disclosed in this invention includes an implementation method for a drawing acquisition module: The drawing acquisition module is used to acquire multiple versions of drawing data generated at different design stages of the construction project. Specifically, in a typical application scenario of this embodiment, the architect of a residential community project uses AutoCAD software to complete the scheme design and generates a first version drawing file ("Residential Project_Unit Scheme_v1.0.dwg"). The architect logs into the system through a web browser, clicks the "Upload Drawing" button, and selects the file to upload.

[0029] After receiving the upload request, the drawing acquisition module performs the following operations: Format verification: Checks whether the uploaded file extension is a supported format such as .dwg or .dxf, and whether the file is corrupted. If the verification passes, the file is temporarily stored in the temporary storage area.

[0030] Version identifier parsing: The file name is matched with "v1.0" using a regular expression to obtain the version number. The upload time (2020-XX-XX14:XX:XX) and the upload user ID (designer_001) are also recorded.

[0031] Version Management Storage: Store this version of the drawing file in the version management database and generate a unique version ID (VER2020XXXX001). Simultaneously, establish metadata records for this version, including: project ID, version number, upload time, upload author, and file storage path.

[0032] When the designer subsequently modifies the design scheme, generates a second version of the drawings ("Residential Project_Floor Plan_v2.0.dwg") and uploads it again, the drawing acquisition module performs the same operation as above, automatically identifies the version update, and establishes a link between the new version and the old version to form a version chain.

[0033] It also includes the implementation method of the quantity analysis engine: The quantity analysis engine is connected to the drawing acquisition module and is used to automatically extract the quantity data in the drawing of any version in response to the import of drawing data of any version, based on the preset building component identification rules; the quantity data includes at least the amount of building materials used and the corresponding construction work quantity.

[0034] Specifically, taking the first version of the drawings (v1.0) as an example, after the drawing acquisition module completes storage, the quantity analysis engine is automatically triggered to start the analysis task. The quantity analysis engine calls the built-in CAD graphic recognition component to read the layer information, block definitions, line segments, polylines, fills, and other graphic elements in the drawing file, and performs recognition based on the preset building component recognition rule library: Wall recognition: Identifies closed areas with the layer name "WALL" or a continuous double line, extracts the wall centerline, thickness, and height parameters, and determines the wall material.

[0035] For example, it identifies the partition wall between the living room and bedroom as a 200mm thick aerated concrete block wall; column recognition: it identifies filled rectangles or closed polylines in the layer named "COLUMN" and extracts the column cross-section dimensions (500mm×500mm), height (story height 3m), and concrete strength grade (C30); beam recognition: it identifies line segments and their labeled text in the layer named "BEAM" and extracts the beam cross-section dimensions (250mm×600mm) and span; door and window recognition: it identifies blocks in the layer named "WINDOW" or "DOOR" and extracts the door and window opening dimensions (1500mm×2100mm) and type (casement window, sliding door).

[0036] After component identification is completed, the quantity analysis engine automatically calculates the quantity of each identified component according to preset calculation rules: This plan also includes calculations of building material usage: For concrete walls, columns, and beams, their volume (cross-sectional area × height / length) is calculated, resulting in a total C30 concrete usage of 125.6 cubic meters. Based on the volume and reinforcement ratio of the concrete components (extracted from the drawings or pre-defined rules), the total steel reinforcement usage is estimated to be 18.5 tons. For block wall components, their masonry area (wall length × wall height - door and window opening area) is calculated, resulting in a block usage of 320 square meters.

[0037] This plan also includes the calculation of construction work volume: based on the total amount of steel bars used, which is 18.5 tons, and combined with the preset steel bar binding labor quota (each ton of steel bar requires 2.5 man-hours for binding), the estimated steel bar binding construction work volume is 46.25 man-hours.

[0038] Based on the concrete volume of 125.6 cubic meters, the estimated concrete pouring construction work volume is 125.6 cubic meters.

[0039] Based on the area of ​​the block wall being 320 square meters, the estimated construction work volume is 320 square meters.

[0040] Finally, the quantity analysis engine encapsulates the above calculation results according to a preset data structure, generates a structured quantity dataset containing the amount of building materials used and the corresponding construction quantities, and sends it to the cost calculation engine.

[0041] This solution also includes an implementation method for the cost calculation engine: The cost calculation engine is connected to the quantity analysis engine to receive quantity data, call a preset cost database, and calculate and generate the current project cost amount corresponding to this version of the drawings, in combination with dynamic variable factors.

[0042] Specifically, after receiving the aforementioned engineering quantity dataset, the cost calculation engine first calls the preset cost database. This database stores the latest material prices, labor market reference prices, and machinery operating costs for the current region. For example: C30 concrete: 480 yuan / cubic meter; steel reinforcement: 4200 yuan / ton; blocks: 85 yuan / square meter; steel reinforcement tying labor: 280 yuan / hour; concrete pouring labor (including vibration and curing): 65 yuan / cubic meter; masonry labor: 95 yuan / square meter. Then, the cost calculation engine combines dynamic variable factors to perform cost calculations. In this embodiment, the cost calculation engine includes a dynamic variable factor library, which stores adjustment coefficients obtained by fitting historical construction data.

[0043] Specifically, based on the structural characteristics of the current version of the drawings, the complexity index is extracted: After analysis, there are a total of 86 beam-column nodes and beam-beam nodes in this drawing. The calculated rebar node density per unit area is 86 nodes ÷ 320 square meters = 0.27 nodes / square meter. According to the preset difficulty adjustment coefficient table (node ​​density < 0.2 corresponds to coefficient 1.0, 0.2-0.3 corresponds to coefficient 1.15, > 0.3 corresponds to coefficient 1.3), the matching difficulty adjustment coefficient is 1.15.

[0044] Based on the above basic unit price and dynamic variable factors, the cost calculation engine performs the following calculations: Material cost calculation: Concrete material cost: 125.6m³ × 480 yuan / m³ = 60,288 yuan; Steel reinforcement material cost: 18.5t × 4200 yuan / t = 77,700 yuan; Block material cost: 320m² × 85 yuan / m² = 27,200 yuan; Subtotal of material costs: 165,188 yuan; Labor cost calculation (applying adjustment coefficient): Basic steel reinforcement tying labor cost: 46.25 man-hours × 280 yuan / man-hour = 12,950 yuan; Adjusted steel reinforcement tying labor cost: 12,950 yuan × 1.15 (difficulty coefficient) = 14,800 yuan. 92.5 yuan; Concrete pouring labor cost: 125.6m³ × 65 yuan / m³ = 8,164 yuan; Masonry labor cost: 320m² × 95 yuan / m² = 30,400 yuan; Subtotal of labor costs: 53,456.5 yuan; Calculation of auxiliary resource costs: Based on empirical formulas, estimate the construction water, electricity, and vehicle transportation costs at 5% of the sum of labor and material costs: (165,188 + 53,456.5) × 5% = 10,932.23 yuan; Total project cost: 165,188 + 53,456.5 + 10,932.23 = 229,576.73 yuan (approximately 229,600 yuan); The cost calculation engine encapsulates the calculation results into an engineering cost dataset containing the total price and details, and sends it to the feedback and interaction module.

[0045] This solution also includes an implementation method for the feedback and interaction module: The feedback and interaction module is used to visually display the current project cost to the user and compare it with a preset budget ceiling threshold; when the current project cost exceeds the budget ceiling threshold, an early warning signal is generated; when the current project cost does not exceed the budget ceiling threshold, the cost data of this version of the drawings is recorded, and a cost adjustment reference is provided for the next version of the drawings.

[0046] Specifically, during the project initiation phase, the client (Party A) enters the project's budget ceiling threshold, such as 200,000 yuan, through the "Project Settings" interface of the feedback and interaction module. The system then stores this threshold in association with the project ID.

[0047] When the feedback and interaction module receives the cost data of 229,600 yuan sent by the cost calculation engine, it performs the following operations: Visualization: The total cost of 229,600 yuan is displayed in the user's browser interface in the form of a dashboard. The top displays the total cost of 229,600 yuan, which is highlighted in red. The budget threshold of 200,000 yuan is displayed below, which is represented by a green reference line. The middle area displays the difference: overspending of 29,600 yuan, with an overspending ratio of 14.8%. The pie chart below shows the details of the proportion of material costs, labor costs, and auxiliary resource costs. The threshold comparison and early warning signal generation, feedback and interaction module's built-in comparator compares 229,600 yuan with 200,000 yuan, determining that it exceeds the threshold; the system immediately executes an early warning operation, popping up a red warning box at the top of the interface, displaying "Budget Overrun Warning! Current cost exceeds budget by 29,600 yuan"; an "!" warning icon is displayed next to overspending items (such as steel reinforcement work); and email and SMS notifications are automatically triggered and sent to the project manager and designer; Cost data is recorded, and the feedback and interaction module encapsulates the calculated cost data (including total price, itemized details, calculation time, and corresponding version ID) into a cost snapshot, stores it in the version management database, and establishes a link with the first version of the drawings (v1.0). This provides a cost adjustment reference for the next version of the drawings: while issuing warnings, the feedback and interaction module analyzes cost discrepancies and generates preliminary adjustment suggestions in the sidebar of the interface. "Recommendation: The amount of steel reinforcement used is relatively large (18.5 tons), accounting for 33.8% of the total cost. It is advisable to optimize the beam and column cross-sectional dimensions or adjust the reinforcement ratio, which is expected to reduce the cost by about 15,000 yuan." "Recommendation: The current construction cost is 229,600 yuan, which exceeds the budget by 29,600 yuan. If the partition wall between the living room and the secondary bedroom is removed, and the three-bedroom unit is converted into a two-bedroom unit, it is estimated that the amount of masonry blocks used can be reduced by 45 square meters, the amount of steel reinforcement used can be reduced by 0.8 tons, and the construction cost can be reduced by about 18,000 yuan." Based on this feedback and adjustment suggestions, designers can initiate targeted design modifications to the second version of the drawings, forming a closed-loop iterative process of "design-quantity calculation-feedback-optimization". Once the second version of the drawings is completed, it is imported into the system again, and the processing flow of each module is repeated to gradually control the project cost within the budget ceiling threshold.

[0048] The engineering quantity analysis engine specifically includes: a hard decoration analysis unit, a soft decoration analysis unit, and a variable calculation unit. This technical solution also includes the implementation method of the hard decoration analysis unit: the hard decoration analysis unit is used to analyze the drawings of the building frame, calculate the material usage of the main structure based on the arrangement parameters of steel bars and cement, and estimate the on-site construction labor hours required for the corresponding material usage based on a preset labor hour coefficient table.

[0049] Specifically, in a typical application scenario of this embodiment, after the first version of the drawings (v1.0) of a residential project is imported into the system, the hard decoration parsing unit is triggered and started, which is specifically responsible for processing the layers and data related to the building frame in the drawings.

[0050] The hard decoration analysis unit performs the following operations: Identifying building frame components. It calls a specialized frame component identification algorithm to filter layers related to the main structure from the drawings, including: Column layer (COLUMN): identifying the location and cross-section of frame columns and structural columns; Beam layer (BEAM): identifying the arrangement and cross-section of frame beams and secondary beams; Slab layer (SLAB): identifying the thickness and extent of floor slabs; Wall layer (WALL): identifying the distribution of load-bearing and non-load-bearing walls; Reinforcement and concrete layout parameter extraction: For each identified frame component, the hard decoration analysis unit further extracts its reinforcement and concrete parameters. For the frame columns (a total of 24), extract the cross-sectional dimensions (500mm×500mm), height (3m), concrete strength grade (C30), main reinforcement configuration (8 HRB400 steel bars with a diameter of 20mm), and stirrup configuration (8mm diameter, 100 / 200mm spacing).

[0051] For the frame beams (36 in total), extract the cross-sectional dimensions (250mm × 600mm), span (ranging from 4.2m to 5.4m), concrete strength grade (C30), bottom reinforcement configuration (3 bars, 22mm diameter), top reinforcement configuration (2 bars, 20mm diameter), and stirrup configuration (8mm diameter, 100 / 200mm spacing). For the floor slabs (total area of ​​320 square meters), extract the slab thickness (120mm), concrete strength grade (C30), and double-layer bidirectional reinforcement configuration (10mm diameter, 150mm spacing).

[0052] Calculation of main structure material usage: Based on the above layout parameters, the hard decoration analysis unit automatically calculates the material usage of the main structure: Cement (concrete) usage calculation: Concrete volume of all frame columns: 24 columns × (0.5m × 0.5m × 3m) = 18 cubic meters; Concrete volume of all frame beams: 36 beams × (0.25m × 0.6m × average span 4.8m) = 25.92 cubic meters; Concrete volume of floor slabs: 320 square meters × 0.12m = 38.4 cubic meters; Total concrete usage (C30): 18 + 25.92 + 38.4 = 82.32 cubic meters; Considering miscellaneous components such as stairs and structural columns, a 5% loss coefficient is added, and the final cement (concrete) usage is 86.44 cubic meters.

[0053] Reinforcement Calculation: Frame column reinforcement: Based on the reinforcement ratio (approximately 2.5%), 18 cubic meters × 2.5% × 7850 kg / m³ = 3,532.5 kg ≈ 3.53 tons; Frame beam reinforcement: Based on the reinforcement ratio (approximately 2.2%), 25.92 cubic meters × 2.2% × 7850 kg / m³ = 4,476.8 kg ≈ 4.48 tons; Floor slab reinforcement: Based on the reinforcement ratio (approximately 1.8%), 38.4 cubic meters × 1.8% × 7850 kg / m³ = 5,425.9 kg ≈ 5.43 tons; Total reinforcement usage: 3.53 + 4.48 + 5.43 = 13.44 tons; On-site construction labor hour estimation: The hard decoration analysis unit has a built-in preset labor hour coefficient table, which is based on a large amount of historical construction data: Rebar tying labor hour coefficient: 2.5 man-hours per ton of rebar; Formwork installation and dismantling labor hour coefficient: 1.2 man-hours per cubic meter of concrete; Concrete pouring labor hour coefficient: 0.8 man-hours per cubic meter of concrete; Based on the above coefficient table, the hard decoration analysis unit estimates the on-site construction labor hours: rebar tying labor hours: 13.44 tons × 2.5 man-hours / ton = 33.6 man-hours; formwork installation and dismantling labor hours: 86.44 cubic meters × 1.2 man-hours / cubic meter = 103.73 man-hours; concrete pouring labor hours: 86.44 cubic meters × 0.8 man-hours / cubic meter = 69.15 man-hours; total hard decoration labor hours: 33.6 + 103.73 + 69.15 = 206.48 man-hours; the hard decoration analysis unit encapsulates the above calculation results (material usage of 86.44 cubic meters of concrete, 13.44 tons of rebar, and 206.48 man-hours) and passes them to the data aggregation module of the engineering quantity analysis engine.

[0054] This technical solution also includes an implementation method for the soft furnishing analysis unit: This unit is used to analyze the interior decoration drawings to obtain a list of soft furnishing materials and the corresponding installation quantities. Specifically, the soft furnishing analysis unit works in parallel with the hard furnishing analysis unit, and is specifically responsible for processing the layers and data related to interior decoration in the drawings.

[0055] The interior decoration analysis unit performs the following operations: Interior decoration component identification: The interior decoration analysis unit calls the decoration component identification algorithm to filter layers related to interior decoration from the drawings, including: Floor layer (FLOOR): Identifies the floor materials of different rooms (floor tiles, wood flooring, carpet); Wall layer (WALL_FINISH): Identifies wall decoration materials (latex paint, wallpaper, ceramic tiles); Ceiling layer (CEILING): Identifies ceiling type and material; Door and window layer (DOOR_WINDOW): Identifies door and window types and sizes; Fixed furniture layer (FURNITURE): Identifies fixed facilities such as cabinets and bathroom fixtures; Soft decoration material list acquisition: Based on the identified decoration components, the interior decoration analysis unit automatically generates a soft decoration material list. Flooring work: Living room, dining room, and hallway areas: tile installation, area 86 square meters, tile size 800mm×800mm, 135 tiles required (including wastage); Bedroom area: engineered wood flooring, area 72 square meters, flooring size 1200mm×165mm, 365 flooring pieces required (including wastage); Kitchen and bathroom: non-slip floor tiles, area 24 square meters, tile size 300mm×300mm, 267 tiles required (including wastage). Wall finishing: All rooms: Latex paint finish, covering an area of ​​482 square meters (calculated by subtracting door and window openings from the wall area), requiring approximately 145 liters of latex paint (calculated at 3.3 square meters per liter); Kitchen and bathroom: Wall tiles, covering an area of ​​86 square meters, with tile sizes of 300mm × 600mm, requiring 478 tiles (including wastage). Ceiling work: Living room and dining room: light steel keel gypsum board ceiling, area 58 square meters; Other areas: latex paint ceiling, area 124 square meters; Doors, windows and fixed facilities: Entrance door: 1 steel-wood security door; Interior doors: 5 solid wood composite doors; Windows: 8 thermally broken aluminum double-glazed windows; Kitchen: 4.2 linear meters of integrated kitchen cabinets; Bathroom: 1 set each of washbasin, toilet and shower. Installation Quantity Calculation: Based on the material list, the soft furnishing analysis unit simultaneously calculates the corresponding installation quantities: Floor tile installation: 86 + 24 = 110 square meters; Wood flooring installation: 72 square meters; Wall tile installation: 86 square meters; Latex paint application: 482 + 124 = 606 square meters; Ceiling installation: 58 square meters; Door installation: 6 doors; Window installation: 8 windows; Cabinet installation: 4.2 linear meters; Bathroom fixtures installation: 3 sets. The soft furnishing analysis unit encapsulates the above soft furnishing material list and corresponding installation quantities, and then passes it to the data aggregation module of the quantity analysis engine.

[0056] This technical solution also includes an implementation method for a variable calculation unit: the variable calculation unit is used to calculate the required auxiliary resource consumption based on the material usage and construction workload; the auxiliary resources include one or more of the following: construction electricity, construction water, and vehicle transportation frequency.

[0057] Specifically, the variable calculation unit receives output data from the hard furnishing analysis unit and the soft furnishing analysis unit, and calculates the consumption of various auxiliary resources required during construction based on this data. The variable calculation unit performs the following operations: Calculation of construction electricity consumption: The variable calculation unit has a built-in construction electricity estimation model, which calculates based on the configuration of construction machinery and the amount of work. For example: Tower crane electricity consumption: This project is equipped with one QTZ63 tower crane, with a power of 35kW, and an estimated usage time of 120 hours. Electricity consumption: 35kW × 120h = 4,200kWh. Rebar processing machinery electricity consumption: Rebar cutter, bending machine, and straightening machine have a combined power of 15kW, with an estimated usage time of 80 hours. Electricity consumption: 15kW × 80h = 1,200kWh. Concrete vibration machinery electricity consumption: Two immersion vibrators, each with a power of 1.5kW, have an estimated usage time of 60 hours. Electricity consumption: 1.5kW × 2 × 60h = 180kWh. Woodworking machinery electricity consumption: Electric saw, electric planer, etc., have a combined power of 8kW, with an estimated usage time of 50 hours. Electricity consumption: 8kW × 50h = 400kWh. Site lighting and other electricity consumption: Estimated at 10% of the aforementioned electricity consumption: (4,200 + 1,200 + 180 + 400) × 10% = 598kWh. Total electricity consumption for construction: 4,200 + 1,200 + 180 + 400 + 598 = 6,578 kWh.

[0058] Construction water consumption calculation: The variable calculation unit has a built-in construction water estimation model, which calculates the water consumption based on the project volume and water quota: Concrete curing water: Total concrete volume is 86.44 cubic meters. Based on 300 liters of water per cubic meter for curing, the required water consumption is: 86.44 × 300 = 25,932 liters ≈ 25.93 tons. Masonry and plastering water: Masonry work volume is 320 square meters. Based on 50 liters of water per square meter, the required water consumption is: 320 × 50 = 16,000 liters = 16 tons. On-site domestic water: Based on 15 construction workers, a 45-day construction period, and 40 liters of water per person per day, the required water consumption is: 15 × 45 × 40 = 27,000 liters = 27 tons. Total construction water consumption: 25.93 + 16 + 27 = 68.93 tons.

[0059] Vehicle transport frequency calculation: The variable calculation unit calculates the required number of transport times based on the material usage and the load capacity of the transport vehicles: Cement (concrete) transport: Ready-mixed concrete is transported from the mixing plant using 8-cubic-meter tank trucks, requiring 86.44 ÷ 8 = 10.8 transport times, rounded up to 11 truckloads; Steel bar transport: Steel is transported using 10-ton trucks, requiring 13.44 ÷ 10 = 1.34 transport times, rounded up to 2 truckloads; Block transport: The total block area is 320 square meters, equivalent to a volume of approximately 32 cubic meters (calculated at 0.1 cubic meters per square meter), transported using 8-cubic-meter trucks, requiring 32 ÷ 8 = 4 truckloads.

[0060] Transportation of decoration materials: floor tiles, wall tiles, flooring, doors and windows, etc., estimated to require 5 truck trips; total number of vehicle trips: 11+2+4+5=22 truck trips; the variable calculation unit encapsulates the above auxiliary resource consumption (construction electricity 6,578kWh, construction water 68.93 tons, vehicle trips 22) and passes it to the data aggregation module of the engineering quantity analysis engine.

[0061] This technical solution also includes data aggregation and output from the engineering quantity analysis engine: The quantity analysis engine aggregates the output data from the hard furnishing analysis unit, soft furnishing analysis unit, and variable calculation unit to form a complete quantity dataset, which is then used by the cost calculation engine. This dataset includes: Building material usage: 86.44 cubic meters of concrete, 13.44 tons of steel bars, 110 square meters of floor tiles, 72 square meters of flooring, 86 square meters of wall tiles, 606 square meters of latex paint, etc. Construction work volume: 33.6 man-hours for rebar tying, 103.73 man-hours for formwork installation and dismantling, 69.15 man-hours for concrete pouring, 110 square meters for floor tile laying, 72 square meters for flooring installation, and 606 square meters for latex paint application; Auxiliary resource consumption: 6,578 kWh of construction electricity, 68.93 tons of construction water, and 22 vehicle trips. At this point, the quantity analysis engine has completed a comprehensive analysis of the first version of the drawings, providing complete and accurate basic data for subsequent cost calculations.

[0062] The cost calculation engine in this solution includes a dynamic variable factor library; the dynamic variable factor library further includes multiple sub-databases, which include at least: a labor hour coefficient sub-database, a difficulty adjustment coefficient sub-database, and an environmental and resource loss sub-database. The cost calculation engine also includes a complexity identification unit and a dynamic correction unit. Specifically, in this embodiment, the cost calculation engine internally constructs a dynamic variable factor library, which is deployed on a database server using a hybrid storage architecture combining relational databases (such as MySQL) and cache databases (such as Redis) to support high-frequency read / write and query operations. The data stored in the dynamic variable factor library is not static but is periodically (e.g., quarterly) updated and optimized based on historical construction project settlement data, market price fluctuation information, and seasonal factors.

[0063] The dynamic variable factor library is further divided into multiple sub-databases, including at least a sub-database of human working hours coefficient, a sub-database of difficulty adjustment coefficient, and a sub-database of environmental and resource consumption. Each sub-database undertakes different data storage and query functions. Regarding the implementation of the labor hour coefficient sub-database, it is used to store standard labor hour benchmark values ​​corresponding to different construction procedures. Specifically, the labor hour coefficient sub-database stores standard labor hour benchmark values ​​compiled based on the "National Unified Labor Quota for Building Installation Engineering" and the company's historical project statistics. These benchmark values ​​reflect the reference working hours required to complete a unit of work volume under standard construction conditions (ordinary residential buildings, standard floor height, normal season).

[0064] In a typical scenario of this embodiment, some of the data stored in the labor hour coefficient sub-database is shown in the table below: These benchmark values ​​serve as the basis for subsequent dynamic corrections. When the system receives the engineering quantity data, it first multiplies the engineering quantity by the corresponding benchmark value to obtain a preliminary estimate of the labor hours. The difficulty adjustment coefficient sub-library stores adjustment coefficients for different building structural complexities, derived from historical construction data. These coefficients are generated through regression analysis of variables such as the number of structural nodes, rebar density, and floor height in historical projects. Specifically, the data in the difficulty adjustment coefficient sub-library is not subjectively set manually, but rather derived through regression analysis of construction data from 126 residential projects completed over the past three years using machine learning algorithms. The data analysis team collected the following characteristic parameters for each project: Number of structural nodes: refers to the total number of key connection points such as beam-column nodes, beam-beam nodes, and beam-wall nodes, calculated per unit building area.

[0065] Rebar density grades: Classified according to the amount of rebar used per unit building area (kg / m²) into Grade I (<40kg / m²), Grade II (40-60kg / m²), Grade III (60-80kg / m²), and Grade IV (>80kg / m²).

[0066] Floor height variable: refers to the degree of variation in standard floor height. For complex apartment layouts with split floors, staggered floors, or open spaces, the floor height variation coefficient is relatively high.

[0067] Multiple linear regression analysis was used to fit adjustment coefficients corresponding to each complexity index. The final data stored in the difficulty adjustment coefficient sub-database is presented in the form of a multidimensional lookup table, as shown in the following examples: This sub-library supports multi-dimensional combined queries, that is, it automatically matches the corresponding adjustment coefficient based on the input node density, rebar density grade and floor height variation coefficient.

[0068] The Environmental and Resource Consumption Sub-library stores auxiliary resource consumption coefficients corresponding to different construction seasons, transportation distances, and on-site operating conditions. Specifically, the Environmental and Resource Consumption Sub-library stores various coefficients used to correct auxiliary resource consumption (construction electricity, water, and vehicle transportation). These coefficients are generated based on a combination of meteorological data, geographic information, and on-site survey records.

[0069] 1. Construction Season Coefficient Table: 2. Transportation Distance Coefficient Table: 3. On-site operating condition coefficient table: The cost calculation engine also includes a complexity identification unit, which receives engineering quantity data from the engineering quantity analysis engine, analyzes the building structure features in the engineering quantity data, and extracts index parameters to characterize the complexity of the drawings. The index parameters include at least the number of steel bar nodes per unit area, the proportion of irregular components, or the coefficient of variation of the floor net height.

[0070] Specifically, in a typical application scenario of this embodiment, the first version of the drawings (v1.0) of a residential project, after being processed by the quantity analysis engine, generates a quantity dataset containing detailed component information. The complexity identification unit receives this dataset and initiates the structural complexity analysis process: Extraction of the number of rebar nodes per unit area: The complexity identification unit traverses all beam and column components in the engineering quantity data and identifies the locations of nodes with rebar connections.

[0071] According to statistics, there are a total of 48 connection nodes between frame beams and frame columns, 22 connection nodes between secondary beams and frame beams, and 16 connection nodes between beams and walls in this drawing.

[0072] Total number of rebar joints: 48 + 22 + 16 = 86. Querying the project's basic information, the corresponding building area for this drawing is 320 square meters. Calculate the number of rebar joints per unit area: 86 ÷ 320 square meters = 0.27 joints / square meter.

[0073] Extraction of irregular component proportion: The complexity recognition unit identifies non-standard rectangular irregular components in the drawing, including curved beams, inclined columns, and polygonal columns. The drawing was identified as containing 4 curved beams and 2 inclined columns, totaling 6 irregular components.

[0074] The total number of major components in the drawings is as follows: 24 frame columns, 36 frame beams, and 18 secondary beams, totaling 78. The percentage of irregular components is calculated as: 6 ÷ 78 = 7.7%. The coefficient of variation for floor clear height is extracted using a complexity identification unit that analyzes the clear height data of each room.

[0075] This drawing depicts a single-story residential building, with most areas having a floor height of 3.0 meters. Due to design requirements, the living room area features a partial double-height space with a net height of 4.5 meters. The average net height is calculated as: (3.0 × 7 rooms + 4.5 × 1 living room) ÷ 8 spaces = 3.1875 meters. The standard deviation and coefficient of variation are calculated, yielding a net height coefficient of variation of 0.12. The complexity identification unit encapsulates the three extracted parameters (0.27 units / square meter, 7.7%, and 0.12) and passes them to the dynamic correction unit.

[0076] The implementation method of the dynamic correction unit in this technical solution is as follows: The cost calculation engine also includes a dynamic correction unit. This unit matches the target adjustment coefficient in the difficulty adjustment coefficient sub-library based on the index parameters extracted by the complexity identification unit. It then applies the target adjustment coefficient to the standard labor hour baseline value in the labor hour coefficient sub-library to generate a corrected labor cost dynamically adapted to the complexity of the current version of the drawings. Simultaneously, based on the construction season parameters and transportation distance parameters corresponding to the current version of the drawings, it calls the corresponding auxiliary resource consumption coefficients in the environmental and resource consumption sub-library to synchronously correct the electricity, water, and vehicle transportation costs required for construction. Specifically, after receiving the index parameters from the complexity identification unit, the dynamic correction unit executes the following correction process: (I) Dynamic Adjustment of Labor Costs: Matching Difficulty Adjustment Coefficient: The dynamic adjustment unit uses the indicator parameters (node ​​density 0.27 / m², irregular component ratio 7.7%, net height variation coefficient 0.12) as query conditions and inputs them into the difficulty adjustment coefficient sub-database. According to the preset multi-dimensional matching rules, the node density of 0.27 falls into the "0.25-0.30" range, the irregular component ratio of 7.7% corresponds to the "Level II" rebar density grade (combined with the total rebar usage of 13.44 tons and the building area of ​​320 square meters, the rebar density is 42 kg / m², which belongs to Level II), and the net height variation coefficient of 0.12 falls into the "0.10-0.15" range.

[0077] The difficulty adjustment coefficient table was consulted, and the target adjustment coefficient was found to be 1.15. The standard labor hour baseline values ​​were obtained: the dynamic correction unit retrieved the standard labor hour baseline values ​​for each construction process from the labor hour coefficient sub-database: rebar tying: 2.5 man-hours / ton; formwork installation and dismantling: 1.2 man-hours / cubic meter; concrete pouring: 0.8 man-hours / cubic meter; masonry construction: 0.95 man-hours / square meter; wall plastering: 0.35 man-hours / square meter. The corrected labor cost was then calculated.

[0078] Obtain the engineering quantity data for each process from the engineering quantity analysis engine: steel reinforcement usage: 13.44 tons; concrete usage: 86.44 cubic meters; masonry area: 320 square meters; plastering area: 482 square meters; first calculate the labor cost of the foundation: steel reinforcement binding foundation labor time: 13.44 tons × 2.5 labor hours / ton = 33.6 labor hours; formwork installation and dismantling foundation labor time: 86.44 cubic meters × 1.2 labor hours / cubic meter = 103.73 labor hours; Concrete pouring foundation time: 86.44 cubic meters × 0.8 man-hours / cubic meter = 69.15 man-hours; Masonry foundation time: 320 square meters × 0.95 man-hours / square meter = 304 man-hours; Wall plastering foundation time: 482 square meters × 0.35 man-hours / square meter = 168.7 man-hours; Total foundation time: 33.6 + 103.73 + 69.15 + 304 + 168.7 = 679.18 man-hours; Adjusting the labor cost using a difficulty adjustment factor of 1.15: Total working hours after adjustment: 679.18 working hours × 1.15 = 781.06 working hours; Combined with the labor unit price (280 yuan / working hour), the adjusted labor cost is calculated as follows: Adjusted labor cost: 781.06 working hours × 280 yuan / working hour = 218,696.8 yuan; (ii) Synchronous adjustment of auxiliary resource costs Obtaining construction season parameters: The dynamic correction unit queries project information. The planned construction period for this project is from June to October, spanning summer and autumn. According to the construction schedule, the main structure construction is concentrated in July-August (summer), and the decoration construction is concentrated in September-October (autumn).

[0079] Retrieve the corresponding seasonal coefficients from the environmental and resource depletion sub-database: Summer electricity consumption coefficient: 1.25; Summer water consumption coefficient: 1.40; Autumn electricity consumption coefficient: 0.95; Autumn water consumption coefficient: 0.90; Based on the weighted average of the construction stages, comprehensively determine the following: Comprehensive electricity consumption adjustment coefficient: (1.25×0.6+0.95×0.4)=1.13; Comprehensive water consumption adjustment coefficient: (1.40×0.6+0.90×0.4)=1.20; Obtain transportation distance parameters: The dynamic correction unit queries the project's geographical location. This project is located in the city center area, 18 kilometers from the nearest concrete mixing plant, 22 kilometers from the steel market, and 15 kilometers from the decoration materials market.

[0080] Retrieve the corresponding transportation distance coefficient (average distance approximately 18km, falling within the 10-30km range) from the Environmental and Resource Loss sub-database: Transportation adjustment coefficient: 1.25; Obtain on-site operating condition parameters: The dynamic correction unit queries the project site survey records. This project is an urban construction project with relatively narrow site space and limited material storage space, requiring consideration of secondary handling. Retrieve the corresponding on-site operating condition coefficient from the Environmental and Resource Loss sub-database: Resource consumption coefficient: 1.30; Calculate the corrected auxiliary resource cost; Obtain the basic auxiliary resource consumption from the variable calculation unit: Construction electricity: 6,578kWh, Construction water: 68.93 tons, Vehicle transportation: 22 trips; Apply the comprehensive adjustment coefficient for synchronous correction. Corrected construction power consumption: 6,578 kWh × 1.13 (seasonal coefficient) × 1.30 (site conditions) = 6,578 × 1.469 = 9,663 kWh; Corrected construction water consumption: 68.93 tons × 1.20 (seasonal coefficient) × 1.30 (site conditions) = 68.93 × 1.56 = 107.5 tons; Corrected vehicle transportation: 22 trips × 1.25 (distance coefficient) × 1.30 (site conditions) = 22 × 1.625 = 35.75 trips (rounded to 36 trips); Based on the unit price of resources (electricity 0.8 yuan / kWh, water 4 yuan / ton, transportation 500 yuan / truckload), the corrected auxiliary resource costs are calculated as follows: Corrected electricity cost: 9,663 kWh × 0.8 yuan / kWh = 7,730.4 yuan; Corrected water cost: 107.5 tons × 4 yuan / ton = 430 yuan; Corrected transportation cost: 36 truckloads × 500 yuan / truckload = 18,000 yuan; Total corrected auxiliary resource cost: 7,730.4 + 430 + 18,000 = 26,160.4 yuan. This technical solution also includes the output of the dynamic correction unit: The dynamic correction unit summarizes the above-mentioned corrected labor cost (218,696.8 yuan) and auxiliary resource cost (26,160.4 yuan), together with the material cost (165,188 yuan) obtained directly from the cost database, to generate the complete project cost of the current version of the drawings: Material cost: 165,188 yuan (uncorrected, obtained directly from the cost database); Corrected labor cost: 218,696.8 yuan; Corrected auxiliary resource cost: 26,160.4 yuan; Total project cost: 165,188 + 218,696.8 + 26,160.4 = 410,045.2 yuan (approximately 410,000 yuan).

[0081] The revised cost data is pushed to the feedback and interaction module for users to view and use for subsequent budget control analysis. Through this dynamic correction mechanism, the system achieves accurate response to different levels of drawing complexity, and the accuracy of project cost calculation is improved by approximately 15%-20% compared to the traditional fixed coefficient method.

[0082] Specifically, the feedback and interaction module in this technical solution further includes a visualization comparison submodule; the visualization comparison submodule includes a split-screen display unit, which is used to generate a first display area and a second display area on the same user interface in a left-right or top-bottom split-screen layout; the first display area is used to load and display the first three-dimensional building model corresponding to the first version of the drawings, and to display the first project cost amount in a floating layer at a preset position of the first three-dimensional building model; the second display area is used to load and display the second three-dimensional building model corresponding to the second version of the drawings, and to display the second project cost amount in a floating layer at a preset position of the second three-dimensional building model; The visualization comparison submodule also includes a difference analysis engine, which is connected to the quantity analysis engine and the cost calculation engine. It is used to automatically compare the differences in the quantity of work at the component level between the first version of the drawings and the second version of the drawings, and generate a cost difference dataset that includes at least material usage difference items, labor hour difference items, and auxiliary resource consumption difference items. Based on the cost difference dataset, in the first and second display areas, pre-defined visual coding rules are used to differentiate the highlighting of building components whose costs have changed. Components with increased costs are highlighted in the first color level, while components with decreased costs are highlighted in the second color level. The visualization comparison submodule also includes an associated positioning unit, which is used to respond to the user's click or hover operation on a highlighted component in either display area, automatically identify the drawing modification location corresponding to this component, and simultaneously locate and highlight the corresponding component in the other display area, and display a detailed comparison card of the cost change of this component between the two versions in the sidebar of the interface.

[0083] Specifically, the system in this technical solution also includes an intelligent assisted design submodule; The intelligent auxiliary design submodule is connected to the feedback and interaction module, including an over-budget cause analysis unit. When the feedback and interaction module generates an early warning signal, the over-budget cause analysis unit receives the current project cost amount and the corresponding cost difference item data, sorts the cost difference items by weight, and identifies the key cost items that cause the budget over-budget and their corresponding building components. The intelligent assisted design submodule also includes an optimization strategy rule base, which stores multiple preset optimization strategy mapping relationships. The optimization strategy mapping relationship includes the correspondence between cost item type and optimization action. Among them, structural cost exceeding the standard corresponds to space reconstruction optimization action, material cost exceeding the standard corresponds to material replacement optimization action, and labor cost exceeding the standard corresponds to process simplification optimization action. Optimize the relationship between actions and building component adjustment parameters. Among them, spatial reconstruction optimization actions should be associated with at least wall deletion parameters, room merging parameters, or opening parameters. The intelligent assisted design submodule also includes an optimization scheme generation engine, which is connected to the excess cause analysis unit and the optimization strategy rule base respectively. It is used to match the corresponding target optimization action in the optimization strategy rule base based on the identified key cost items and their corresponding building components. Based on the target optimization action and the current design parameters of the building components, the system calls the preset building code constraints and automatically generates at least one optimized design scheme that meets the code requirements. Optimized design schemes include, but are not limited to, space reconstruction schemes that reduce the amount of masonry structure work by reducing room partitions; layout optimization schemes that reduce the number of load-bearing walls or shorten pipeline paths by adjusting the unit layout; and material replacement schemes generated by selecting the same type and specifications of building materials with lower unit prices from a pre-set list of replaceable materials. The intelligent assisted design submodule also includes a scheme preview and switching unit, which pushes the generated optimized design scheme to the feedback and interaction module, and displays it in the visualization comparison submodule in the form of a 3D model overlay. The optimization scheme responds to the user's selection operation by automatically replacing the corresponding building components in the current version of the drawings with the component parameters in the optimized design scheme, generating a new optimized version of the drawings, and triggering the quantity analysis engine and cost calculation engine to recalculate the cost of the new version in real time.

[0084] Specifically, the drawing acquisition module used in this technical solution supports the implementation of a version management scheme for drawings, including a version data structure definition unit, used to define a unified version data storage structure for each version of the drawing; the version data storage structure includes at least: It also includes a version metadata area, which stores the version number, version generation time, version modification author, and version modification notes; The module includes a drawing design data area for storing the drawing files and parametric data of building components corresponding to this version; a cost snapshot data area for storing the quantity analysis results and project cost associated with this version of the drawings, including at least a breakdown of the cost of each item and the total cost; a version difference data area for storing a summary of the modifications made to this version compared to the previous version, and the corresponding cost change details; the drawing acquisition module also includes a version snapshot generation unit, which is connected to both the quantity analysis engine and the cost calculation engine for: In response to the import and cost calculation completion of any version of drawings, a version snapshot generation command is automatically triggered; intermediate quantity analysis data for this version of drawings is obtained from the quantity analysis engine, and the project cost amount and details for this version of drawings are obtained from the cost calculation engine; the intermediate quantity analysis data, project cost amount and details, together with the file data of the current version of drawings and the version remarks information entered by the user, are encapsulated according to the version data storage structure to generate a historical snapshot of the project cost for this version; the drawing acquisition module also includes a version association tracing unit, which is used to record the inheritance relationship between each version of the project cost historical snapshot, forming a version association tree with the initial version as the root node and the iterative versions as branch nodes; In response to the user's selection of any historical version node in the version association tree, load and display the drawing data and cost snapshot data corresponding to this historical version; In response to the user's version comparison command, any two selected versions are extracted from the version association tree, and the summary of the modified content and the details of cost changes are read from the corresponding version difference data area. The results are then pushed to the visualization comparison submodule of the feedback and interaction module for difference display.

[0085] Specifically, the quantity analysis engine used in this technical solution supports quantity analysis for sub-items of the project, including: A project structure decomposition unit is used to decompose a construction project into multiple levels of sub-item engineering nodes from top to bottom according to a preset construction engineering bill of quantities pricing specification or internal enterprise quota standard. The multiple levels include at least: unit project level nodes, which correspond to the entire building unit; sub-project level nodes, which include at least foundation and foundation sub-sub ... Based on the type label and spatial location of the building components, each building component is automatically mapped to the corresponding sub-item engineering layer node; among them, frame columns and frame beams are mapped to the steel reinforcement and concrete sub-item of the main structure sub-section, infill wall components are mapped to the masonry sub-item, and wall plastering layer is mapped to the plastering sub-item of the decoration and finishing sub-section. The quantity parsing engine also includes a sub-item data encapsulation unit. The sub-item data encapsulation unit is used to summarize the quantities of the building components under each sub-item engineering layer node, generate the corresponding quantity list, push the quantity list to the cost calculation engine to obtain the sub-item engineering cost details, associate the sub-item engineering cost details with the corresponding sub-item engineering layer node, assign a unique sub-item identifier code, and store it in the cost snapshot data area. The feedback and interaction module allows users to click to view the real-time cost details of any specific sub-item of the project, including: A sub-item level drill-down unit is used to display multiple levels of sub-item project nodes generated by the project structure decomposition unit in a tree directory or waterfall layout on the user interface. In response to a user's click on any sub-item project node, the corresponding sub-item project cost details are retrieved in real time from the cost snapshot data area based on the sub-item identifier code corresponding to that node. A detailed breakdown display unit is used to display the detailed breakdown cost of the clicked sub-item project in a preset area of ​​the current interface, in the form of a card-style overlay or a sidebar panel. The detailed cost breakdown for each item of work should include at least: the name and code of the item, the total cost of the item, the bill of quantities and unit price analysis of various building components under the item, and the details of labor costs, material costs, machinery costs and management fees for the item. A component-level associated highlighting unit is used to simultaneously highlight all building components belonging to a certain sub-item in the drawing display area or 3D model display area when the sub-item detail display unit displays the cost details of a certain sub-item project; when the user hovers over or clicks on a specific bill of quantities item in the sub-item project cost details, the single or multiple building components corresponding to that bill of quantities item will be further located and highlighted in the drawing display area; A dynamic update unit is used to automatically update the bill of quantities and detailed cost of each sub-item of the project structure decomposition unit when the current version of the drawings undergoes design changes and triggers a recalculation of quantities and costs; ensuring that the detailed cost of each sub-item retrieved by the user through the sub-item level drill-down unit is always consistent with the current version of the drawings in real time.

[0086] Specifically, the system used in this technical solution adopts a hybrid deployment architecture, supporting deployment on cloud servers or local clients; When the system is deployed on a cloud server, it includes a cloud service access unit, which manages access requests from multiple concurrent users through load balancing technology and allocates an independent computing resource instance to each access session; the drawing acquisition module further includes a web-based upload submodule, which receives multiple versions of drawing files uploaded by users from their local terminals through a file upload interface provided by the browser; it performs format verification and virus scanning on the uploaded drawing files, and files that pass the verification are temporarily stored in the cloud distributed storage system, generating a unique cloud storage path and access credentials for each successfully uploaded drawing file, and recording the identity of the uploading user and the upload timestamp; The quantity parsing engine and cost calculation engine are deployed in the backend service cluster of cloud servers, including an asynchronous task queue, which is used to queue the received drawing parsing requests and cost calculation requests to avoid service blocking in high-concurrency scenarios. Multiple stateless computing nodes are used to pull tasks from the asynchronous task queue, execute engineering quantity analysis and cost calculation in parallel, and write the calculation results back to the cloud database; A result caching unit is used to store the cost results of multiple recently calculated versions of drawings in a Redis cache to accelerate subsequent repeated queries of the same version; The feedback and interaction module further includes a web-based real-time push submodule, which establishes a full-duplex communication channel with the user's browser via the WebSocket protocol. When a task in the asynchronous task queue is completed, it actively pushes the current project cost amount and corresponding cost details to the user's browser via the WebSocket channel. The user's browser can receive and dynamically render the updated cost data and visualization charts in real time without refreshing the page. When the system is deployed on a local client, it includes a local offline running unit, which can independently complete all functions of drawing acquisition, quantity analysis, cost calculation, and feedback interaction by calling the computing resources of the local client in environments with no network connection or unstable network. A local data storage unit is used to store multiple versions of drawing data, intermediate data of quantity analysis, and historical snapshots of project cost in a local file system or embedded database (such as SQLite); A data synchronization unit is used to automatically synchronize the locally stored incremental version data and cost snapshots to the cloud server according to a preset conflict resolution strategy when the network connection is restored. The system also includes a deployment mode adaptive unit, which automatically detects the current network status and server reachability when the system starts up or during operation, and automatically switches between cloud online mode and local offline mode according to a preset switching strategy, or provides availability prompts for the current mode when the user manually selects a mode. When switching back from offline mode to online mode, the data synchronization unit is automatically triggered to perform data synchronization operations to ensure consistency between cloud and local data.

[0087] Specifically, this technical solution also includes a construction project cost feedback method based on engineering quantity analysis, which is applied to the system during the specific implementation of this technical solution. This method includes the following steps: Step S1: Perform drawing data acquisition and version identification by acquiring multiple versions of drawing data generated at different design stages of the architectural project; parse the version identifier for each acquired drawing data to extract the version number, generation time, and author information; store the drawing data and its version identifier information in the version management database and establish a version index for subsequent steps. Step S2: Perform automatic quantity analysis and structured extraction. Responding to the import command for any version of drawing data, call the preset building component recognition rule library; perform graphic recognition and parameter analysis on the imported drawing data, automatically extracting the building components and their geometric parameters, material properties, and spatial location data from this version of the drawing; based on the preset sub-item project decomposition structure, automatically map each extracted building component to the corresponding sub-item project node; summarize the quantities of the building components belonging to each sub-item project node to generate a structured quantity dataset; the quantity dataset includes at least the amount of building materials used and the corresponding construction quantities. Step S3: Perform dynamic cost calculation and correction. Receive the engineering quantity dataset and call the preset cost database to obtain the basic unit prices of various building materials and construction procedures. Read the adjustment coefficients obtained from the dynamic variable factor library based on historical construction data. The dynamic variable factor library includes at least a labor hour coefficient sub-library, a difficulty adjustment coefficient sub-library, and an environmental and resource loss sub-library. Analyze the building structure features in the engineering quantity dataset, extract index parameters to characterize the complexity of the drawings, match the corresponding target adjustment coefficients based on the extracted index parameters, apply the target adjustment coefficients to the basic unit prices, and generate a corrected unit price that dynamically adapts to the complexity of the current version of the drawings. Based on the corrected unit price and the engineering quantity dataset, calculate and generate the current engineering cost amount corresponding to this version of the drawings, and simultaneously generate a detailed breakdown of the engineering cost for each component. Step S4: Cost Feedback and Budget Control Steps. The current project cost is displayed to the user in a visual format, and a preset budget ceiling threshold is shown side-by-side on the same interface. The current project cost is compared with the budget ceiling threshold. If the current project cost exceeds the budget ceiling threshold, an early warning signal is generated, and at least one optimized design scheme is automatically generated and pushed to the user based on the cost difference. If the current project cost does not exceed the budget ceiling threshold, the cost data for this version of the drawings is recorded in the version management database, providing a cost adjustment reference for the next version of the drawings. In response to the user's selection of any historical version, the corresponding drawing data and cost snapshot data are retrieved from the version management database and displayed visually in comparison with the current version. Step S5: Version iteration and dynamic update steps. In response to the import of new version drawings generated by the user based on the optimized design scheme or manual modification, steps S2 to S4 are repeated. After each iteration calculation is completed, the version association tree in the version management database is automatically updated to record the cost difference details between the current version and the previous version. This ensures that as the design drawing version is iterated, the calculation accuracy of the project cost gradually converges and approaches the budget ceiling threshold.

[0088] Specifically, this technical solution also includes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method disclosed in this technical solution.

[0089] The above description is merely a preferred embodiment of the present invention and is not intended to further limit the present invention. All equivalent changes made based on the description and drawings of the present invention are within the protection scope of the present invention.

Claims

1. A construction project cost feedback system based on quantity analysis, characterized in that, include: The drawing acquisition module is used to acquire multiple versions of drawing data generated at different design stages of a building project. The quantity analysis engine, connected to the drawing acquisition module, is used to automatically extract the quantity data from any version of the drawing data in response to the import of any version of the drawing data, based on preset building component identification rules; the quantity data includes at least the amount of building materials used and the corresponding construction work quantity; The cost calculation engine, connected to the engineering quantity analysis engine, is used to receive the engineering quantity data, call the preset cost database, and combine dynamic variable factors to calculate and generate the current engineering cost amount corresponding to this version of the drawings. The feedback and interaction module is used to visually display the current project cost to the user and compare it with a preset budget ceiling threshold. When the current project cost exceeds the budget ceiling threshold, an early warning signal is generated; When the current project cost does not exceed the budget ceiling threshold, record the cost data for this version of the drawings and provide a cost adjustment reference for the next version of the drawings.

2. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The engineering quantity analysis engine specifically includes: The hard decoration analysis unit is used to analyze the drawings of the building frame, calculate the material consumption of the main structure based on the layout parameters of steel bars and cement, and estimate the on-site construction labor hours required for the corresponding material consumption based on the preset labor hour coefficient table. The interior design analysis unit is used to analyze the interior decoration drawings and obtain the list of interior materials and the corresponding installation work. The variable calculation unit is used to calculate the required auxiliary resource consumption based on the material usage and the construction workload; the auxiliary resources include one or more of the following: construction electricity, construction water, and vehicle transportation frequency.

3. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The cost calculation engine includes a dynamic variable factor library; The dynamic variable factor library further includes multiple sub-databases, and the multiple sub-databases include at least: The labor hour coefficient sub-library is used to store the standard labor hour benchmark values ​​corresponding to different construction procedures; The difficulty adjustment coefficient sub-library is used to store adjustment coefficients for different building structure complexities, which are obtained by fitting historical construction data. The adjustment coefficients are generated after regression analysis based on the number of different structural nodes, steel reinforcement density grade and floor height variables in historical projects. The environmental and resource consumption sub-database is used to store auxiliary resource consumption coefficients corresponding to different construction seasons, transportation distances, and on-site operating conditions. The cost calculation engine also includes a complexity identification unit, which is used to receive engineering quantity data from the engineering quantity analysis engine, analyze the building structure features in the engineering quantity data, and extract index parameters to characterize the complexity of the drawings; the index parameters include at least the number of steel bar nodes per unit area, the proportion of irregular components, or the coefficient of variation of floor net height. The cost calculation engine also includes a dynamic correction unit, which is used to match the corresponding target adjustment coefficient in the difficulty adjustment coefficient sub-library according to the index parameters extracted by the complexity identification unit. The target adjustment coefficient is applied to the standard labor hour baseline value in the labor hour coefficient sub-library to generate a corrected labor cost that dynamically adapts to the complexity of the current version of the drawing. At the same time, based on the construction season parameters and transportation distance parameters corresponding to the current version of the drawings, the corresponding auxiliary resource consumption coefficients are called from the environmental and resource loss sub-library to synchronously correct the electricity, water and vehicle transportation costs required for construction.

4. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The feedback and interaction module further includes a visual comparison submodule; The visualization comparison submodule includes a split-screen display unit, which is used to generate a first display area and a second display area on the same user interface in a left-right or top-bottom split-screen layout. The first display area is used to load and display the first three-dimensional building model corresponding to the first version of the drawings, and to display the first project cost amount in a floating layer at a preset position of the first three-dimensional building model; The second display area is used to load and display the second three-dimensional building model corresponding to the second version of the drawings, and to display the second project cost amount in a floating layer at a preset position of the second three-dimensional building model; The visualization comparison submodule also includes a difference analysis engine, which is connected to the engineering quantity analysis engine and the cost calculation engine. It is used to automatically compare the engineering quantity differences between the first version of the drawings and the second version of the drawings at the component level, and generate a cost difference dataset that includes at least material usage difference items, labor hour difference items and auxiliary resource consumption difference items. Based on the cost difference dataset, in the first display area and the second display area, a preset visual encoding rule is used to differentiate the highlighting color of building components whose costs have changed. Components that increase cost are highlighted in the first color level, while components that decrease cost are highlighted in the second color level. The visualization comparison submodule also includes an associated positioning unit, which is used to automatically identify the drawing modification location corresponding to the component in response to the user's click or hover operation on a highlighted component in any display area. In another display area, the corresponding component corresponding to the modified position is simultaneously located and highlighted, and a comparison card showing the cost changes of this component between the two versions pops up in the sidebar of the interface.

5. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The system also includes an intelligent assisted design submodule; The intelligent auxiliary design submodule is connected to the feedback and interaction module and includes an over-budget cause analysis unit. The over-budget cause analysis unit is used to receive the current project cost amount and the corresponding cost difference item data when the feedback and interaction module generates an early warning signal, and to sort the cost difference items by weight to identify the key cost items that cause the budget over-budget and their corresponding building components. The intelligent assisted design submodule also includes an optimization strategy rule base, which stores multiple preset optimization strategy mapping relationships. The optimization strategy mapping relationship includes the correspondence between cost item type and optimization action, wherein structural cost exceeding the standard corresponds to space reconstruction optimization action, material cost exceeding the standard corresponds to material replacement optimization action, and labor cost exceeding the standard corresponds to process simplification optimization action. Optimize the relationship between actions and building component adjustment parameters. Among them, spatial reconstruction optimization actions should be associated with at least wall deletion parameters, room merging parameters, or opening parameters. The intelligent auxiliary design submodule also includes an optimization scheme generation engine, which is connected to the excess cause analysis unit and the optimization strategy rule base respectively, and is used to match the corresponding target optimization action in the optimization strategy rule base according to the identified key cost item and its corresponding building component. Based on the target optimization action and the current design parameters of the building components, the preset building code constraints are invoked to automatically generate at least one optimized design scheme that meets the code requirements. The optimized design schemes include, but are not limited to, a space reconstruction scheme that reduces the amount of masonry structure work by reducing room partitions; a layout optimization scheme that reduces the number of load-bearing walls or shortens pipeline paths by adjusting the unit layout; and a material replacement scheme that generates a material replacement scheme by selecting the same type and specifications of building materials with lower unit prices from a preset list of replaceable materials. The intelligent assisted design submodule also includes a scheme preview and switching unit, which is used to push the generated optimized design scheme to the feedback and interaction module, and preview and display it in the visualization comparison submodule in the form of a three-dimensional model overlay. The optimization scheme responds to the user's selection operation by automatically replacing the corresponding building components in the current version of the drawings with the component parameters in the optimized design scheme, generating a new optimized version of the drawings, and triggering the engineering quantity analysis engine and cost calculation engine to recalculate the cost of the new version in real time.

6. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The drawing acquisition module supports drawing version management, including: A version data structure definition unit is used to define a unified version data storage structure for each version of the drawing; the version data storage structure includes at least: The version metadata area is used to store the version number, version creation time, version modification author, and version modification notes. The drawing design data area is used to store the drawing files and parametric data of building components corresponding to this version. The cost snapshot data area is used to store the engineering quantity analysis results and engineering cost amount associated with this version of the drawings. The cost snapshot data includes at least the details of the cost of each item of the project and the total cost. The version difference data area is used to store a summary of the changes made in this version compared to the previous version, as well as the corresponding cost change details; The drawing acquisition module also includes a version snapshot generation unit, which is connected to the engineering quantity analysis engine and the cost calculation engine respectively. It is used to automatically trigger the version snapshot generation command in response to the import of any version of the drawing and the completion of the cost calculation. Obtain intermediate data of the quantity analysis of this version of the drawing from the quantity analysis engine, and obtain the project cost amount and details of this version of the drawing from the cost calculation engine. The intermediate data of the project quantity analysis, the project cost amount and details, together with the file data of the current version of the drawings and the version remarks information entered by the user, are encapsulated according to the version data storage structure to generate a historical snapshot of the project cost for this version. The drawing acquisition module further includes a version association and tracing unit, which is used for: Record the inheritance relationship between the historical snapshots of the project cost for each version, forming a version association tree with the initial version as the root node and the iterative versions as branch nodes; In response to the user's selection operation on any historical version node in the version association tree, load and display the drawing data and cost snapshot data corresponding to this historical version; In response to the user's version comparison command, any two selected versions are extracted from the version association tree, and the summary of the modified content and the details of cost changes are read from the corresponding version difference data area. The results are then pushed to the visualization comparison submodule of the feedback and interaction module for difference display.

7. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The quantity analysis engine supports quantity analysis for sub-items of a project; The feedback and interaction module allows users to click to view the real-time cost details of any specific sub-item of the project (such as the main structure reinforcement project, masonry project, and decoration project).

8. The construction project cost feedback system based on engineering quantity analysis according to claim 1, characterized in that, The system is deployed on a cloud server or a local client. When deployed on a cloud server, the drawing acquisition module receives drawings uploaded by users through a web interface and pushes the current project cost amount to the user's terminal in real time through the web interface.

9. A construction project cost feedback method based on quantity analysis, applied to the system described in any one of claims 1 to 8, characterized in that, Includes the following steps: Step S1: Obtain multiple versions of drawing data generated at different design stages of the architectural project; Step S2: In response to the import of any version of drawing data, based on the preset building component identification rules, automatically extract the engineering quantity data in this version of the drawing; the engineering quantity data includes at least the amount of building materials used and the corresponding construction engineering quantity; Step S3: Receive the engineering quantity data, call the preset cost database, and calculate the current engineering cost amount corresponding to this version of the drawings by combining dynamic variable factors; Step S4: Visually display the current project cost to the user and compare it with the preset budget ceiling threshold; If the threshold is exceeded, a warning signal will be generated and adjustments will be prompted. If the cost data for this version of the drawing is not exceeded, the cost data for this version of the drawing will be recorded and used as a reference for the next version of the drawing iteration.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When this program is executed by the processor, it implements the method of claim 9.

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