An automatic service engineering cost consulting device

Abstract

The present invention provides an automatic service engineering cost consulting device, which relates to the field of engineering cost technology. The automatic service engineering cost consulting device includes a support rod and a consulting display mechanism, wherein an armrest plate is fixedly provided at the upper end of the support rod, and a pentagonal support column is fixedly provided at the center of the upper end surface of the armrest plate; the consulting display mechanism includes a touch display screen, and a connecting seat is rotatably provided at the rear center of the touch display screen, and an extension rod is hingedly provided at the rear end of the connecting seat. The technology of the present invention realizes the comprehensive intelligence of project management, cost estimation, risk management and smart contracts through the collaborative work of front-end applications and back-end modules, combines multi-source data docking and big data analysis technology to ensure the real-time and accuracy of data, and provides high-precision cost forecasts and risk management suggestions. Moreover, the device can be viewed more clearly, saves space, and facilitates communication.

Description

Technical Field

[0001] The invention relates to the technical field of engineering cost, in particular to an automatic service engineering cost consulting device. Background Art

[0002] Engineering cost consulting refers to the provision of professional services on engineering cost by professional consulting organizations or individuals to owners, contractors, design units, etc. during the construction process, including investment estimation, design budget, construction drawing budget, bill of quantities compilation, engineering final accounts, cost control, contract management, engineering claims processing, etc., aiming to ensure the effective use of project investment and cost control. Existing engineering cost consulting data collection mainly obtains relevant data automatically through manual input of user interface and data interface. Data storage uses relational databases and data warehouses to store project data, material prices, labor costs and other information. Cost estimation is based on rule engines and expert systems, and models are established for calculation based on industry standards and historical data. Risk management analyzes historical project data and assesses potential risks by manually inputting risk points and using data analysis tools.

[0003] In terms of data collection in engineering cost consulting, existing technologies rely on manual input of large amounts of project data, which is prone to errors and inefficient. At the same time, the data interface with external systems may be imperfect, and data acquisition may be untimely or inaccurate. In terms of cost estimation, the rule engine is based on fixed formulas and conditions and may not be able to adapt to complex project situations, resulting in inaccurate estimates. The performance of the expert system depends on the experience and knowledge updates of industry experts, and it is difficult to obtain the latest market data in real time. In terms of risk management, it relies on users to manually identify and input risk points, which is easy to miss important risk factors, and the existing risk assessment models are mostly static models with poor adaptability. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides an automatic service engineering cost consulting device, which solves the problem of low evaluation quality in the prior art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an automatic service engineering cost consulting device, comprising a support rod and a consulting display mechanism, wherein an armrest board is fixedly arranged at the upper end of the support rod, and a pentagonal support column is fixedly arranged at the center of the upper end surface of the armrest board;

[0006] The consulting display mechanism includes a touch display screen, a connecting seat is rotatably provided at the rear center of the touch display screen, an extension rod is hingedly provided at the rear end of the connecting seat, a telescopic rod is hingedly provided at the rear end of the extension rod, and a fixed seat is hingedly provided at the rear end of the telescopic rod.

[0007] Preferably, an annular groove is provided at the edge of the lower end surface of the armrest plate, a slide bar is slidably provided inside the annular groove, and a storage box is fixedly provided on the lower end surface of the slide bar through a plurality of connecting rods.

[0008] Preferably, a support seat is fixedly provided at the lower end of the support rod, a plurality of reinforcing angle irons are fixedly provided between the support seat and the support rod, and a top plate is fixedly provided at the upper end of the pentagonal support column.

[0009] Preferably, the hinges and rotations of the connecting seat, the extension rod, the telescopic rod and the fixed seat are all provided with a certain damping force, and one end of the fixed seat away from the telescopic rod is fixedly arranged on the outer surface of the pentagonal support column.

[0010] An automatic service engineering cost consulting system includes a front-end application, the front-end application is connected to an API gateway, the API gateway is connected to a multi-source data docking module, and the multi-source data docking module is respectively connected to a project management module, a cost estimation module, a risk management module and a contract module;

[0011] The project management module, cost estimation module, risk management module and contract module are connected to a data processing layer, the data processing layer is connected to a data analysis and prediction module, and the data analysis and prediction module is connected to a data storage module.

[0012] Preferably, the multi-source data docking module is used to automatically acquire and integrate project data, material prices, labor costs and financial information from external data sources such as BIM / ERP systems, material supplier platforms and financial platforms. The data processing layer includes a data cleaning and structuring module and a big data analysis module. The data cleaning and structuring module is used to process and clean the collected data to ensure data quality and convert unstructured data into structured data. The big data analysis module is used to use big data technology to perform cost analysis and market trend forecasting.

[0013] Preferably, the data analysis and prediction module includes a machine learning model and a data visualization module, wherein the machine learning model is used to train and apply the model for cost estimation and prediction, and the data visualization module is used to display key information through charts and dashboards; the project management module includes management functions for project initiation, design, construction and completion stages, and supports project progress management, task allocation and monitoring, communication and collaboration, and document management.

[0014] Preferably, the cost estimation module uses a machine learning framework and a training cost estimation model based on project parameters and market data to automatically calculate cost estimates and support dynamic adjustment and generation of cost reports. The risk management module provides response strategies and risk reports by identifying and evaluating potential risks in the project. The contract module uses blockchain technology to manage contracts, automatically execute terms, and provide detailed audit records of contract execution.

[0015] Preferably, the data storage module includes a database and a data warehouse, the database is used to store real-time data of project data, cost data, and contract data, and the data warehouse is used to store historical project data and market data to support big data analysis.

[0016] The present invention provides an automatic service engineering cost consulting device. It has the following beneficial effects:

[0017] The present invention provides an automatic service engineering cost consulting device. In terms of data collection, the present invention realizes comprehensive data collection by integrating multiple external data sources, and establishes an automatic data update mechanism to ensure the timeliness and accuracy of data and reduce the workload of manual input by users. In terms of cost estimation, a machine learning framework is used to train the cost estimation model to improve the accuracy and reliability of the estimation, and the model parameters are dynamically adjusted according to market data and user feedback to make it more adaptable to different project types and market environments. In terms of risk management, a dynamic risk assessment model based on historical data and market data is established to identify and assess project risks in real time and provide users with intelligent risk response suggestions. In terms of equipment of the present invention, multiple consulting and display mechanisms are provided. While the consulting and display mechanisms can be adjusted at multiple angles, multiple people can watch or operate them, which makes it more convenient to use and more intuitive to watch, saves space, and facilitates communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the front view axle side of the present invention;

[0019] Figure 2 It is a bottom-up axial schematic diagram of the present invention;

[0020] Figure 3 It is a schematic diagram of the axial side of the consulting and display mechanism of the present invention;

[0021] Figure 4 It is a schematic diagram of the system flow of the present invention.

[0022] Among them, 1. support rod; 2. top plate; 3. pentagonal support column; 4. consulting and display mechanism; 5. armrest board; 6. storage box; 7. support seat; 8. reinforced angle iron; 9. slide bar; 10. ring groove; 401. connecting seat; 402. touch display screen; 403. extension rod; 404. telescopic rod; 505. fixed seat. DETAILED DESCRIPTION

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

[0024] Example 1

[0025] like Figure 1-3 As shown, an embodiment of the present invention provides an automatic service engineering cost consulting device, including a support rod 1 and a consulting display mechanism 4, an upper end of the support rod 1 is fixedly provided with an armrest board 5, and a pentagonal support column 3 is fixedly provided at the center of the upper end surface of the armrest board 5;

[0026] The consulting and display mechanism 4 includes a touch display screen 402, a connecting seat 401 is rotatably provided at the rear center of the touch display screen 402, an extension rod 403 is hingedly provided at the rear end of the connecting seat 401, a telescopic rod 404 is hingedly provided at the rear end of the extension rod 403, and a fixed seat 505 is hingedly provided at the rear end of the telescopic rod 404.

[0027] An annular groove 10 is provided at the edge of the lower end surface of the armrest plate 5, and a slide bar 9 is slidably provided inside the annular groove 10, and a storage box 6 is fixedly provided on the lower end surface of the slide bar 9 through a plurality of connecting rods.

[0028] A support seat 7 is fixedly provided at the lower end of the support rod 1 , a plurality of reinforcing angle irons 8 are fixedly provided between the support seat 7 and the support rod 1 , and a top plate 2 is fixedly provided at the upper end of the pentagonal support column 3 .

[0029] The hinges and rotations of the connecting seat 401 , the extension rod 403 , the telescopic rod 404 and the fixed seat 505 are all provided with a certain damping force, and one end of the fixed seat 505 away from the telescopic rod 404 is fixedly arranged on the outer surface of the pentagonal support column 3 .

[0030] Specifically, the system of the present invention is integrated into the touch display screen 402 of the device. When in use, observers can sit in a circle around the device, with five people in a circle. At this time, there will be a touch display screen 402 in front of each person, and the hands are placed on the armrest board 5. The armrest board 5 can be equipped with a mouse and a keyboard for more convenient control of the touch display screen 402. If the angle is not suitable, the user can rotate the angle of the touch display screen 402, and can also use the extension rod 403 and the telescopic rod 404 to adjust the telescopic angle, so that the user can watch more comfortably and clearly.

[0031] Example 2

[0032] like Figure 4 As shown, an embodiment of the present invention provides an automatic service engineering cost consulting system, including a front-end application, the front-end application is connected to an API gateway, the API gateway is connected to a multi-source data docking module, and the multi-source data docking module is respectively connected to a project management module, a cost estimation module, a risk management module and a contract module;

[0033] The project management module, the cost estimation module, the risk management module and the contract module are connected with a data processing layer, the data processing layer is connected with a data analysis and prediction module, and the data analysis and prediction module is connected with a data storage module.

[0034] The multi-source data docking module is used to automatically acquire and integrate project data, material prices, labor costs and financial information from external data sources such as BIM / ERP systems, material supplier platforms and financial platforms. The data processing layer includes a data cleaning and structuring module and a big data analysis module. The data cleaning and structuring module is used to process and clean the collected data, ensure data quality, and convert unstructured data into structured data. The big data analysis module is used to use big data technology to perform cost analysis and market trend forecasting.

[0035] The data analysis and prediction module includes machine learning models and data visualization modules. The machine learning model is used to train and apply models for cost estimation and prediction. The data visualization module is used to display key information through charts and dashboards. The project management module includes management functions for project initiation, design, construction and completion stages, and supports project progress management, task allocation and monitoring, communication and collaboration, and document management.

[0036] The cost estimation module uses a machine learning framework and training cost estimation models based on project parameters and market data to automatically calculate cost estimates and support dynamic adjustment and generation of cost reports. The risk management module identifies and assesses potential risks in projects, provides response strategies and risk reports, and the contract module uses blockchain technology to manage contracts, automatically execute terms, and provide detailed audit records of contract execution.

[0037] The data storage module includes a database and a data warehouse. The database is used to store real-time data of project data, cost data, and contract data. The data warehouse is used to store historical project data and market data to support big data analysis.

[0038] The API gateway is used to uniformly process requests from front-end applications to ensure the security and efficiency of the requests. The multi-source data docking module is connected to external data sources such as the BIM / ERP system, material supplier platform, and financial platform. Data cleaning and integration uses the Pandas library to clean data and remove noise and erroneous data. Data from multiple data sources are integrated into a unified structured data format.

[0039] The project management module uses Node.js+Express+MongoDB (database) to create projects and set basic project information. Manage project design plans and assign design tasks. Manage construction progress, assign construction tasks, and monitor construction quality. Manage project completion acceptance and generate completion reports. Assign project tasks and monitor the execution of tasks. Provide a platform for project team communication and collaboration. Manage and store all project-related documents, and support version control and permission management.

[0040] The cost estimation module obtains project parameters and market data from user input and multi-source data docking modules. Use pre-trained machine learning models for cost estimation. Dynamically adjust cost estimates based on project progress and market changes. Generate detailed cost reports, including cost details and cost change trends.

[0041] The risk management module automatically identifies potential risks by combining historical data and market data. It assesses the impact and likelihood of risk. Based on the risk assessment results, it generates risk management recommendations. It also generates risk reports for project managers to review and reference.

[0042] The contract module is used to manage and store project contracts to ensure the transparency and traceability of contracts. It automatically executes related operations according to the contract terms to reduce human errors and provide detailed audit records of contract execution.

[0043] The data cleaning and structuring module uses Pandas and Apache Spark to clean data and remove noise and erroneous data. It converts unstructured data into structured data for further processing and analysis. It uses big data technology to analyze the trend of project cost changes and provide improvement suggestions. It combines historical data and market data to predict market changes and help project managers make decisions.

[0044] The data analysis and forecasting module uses machine learning models, uses historical data and market data to train machine learning models, and uses regression and classification algorithms to apply the trained models to cost estimation and forecasting to provide high-precision results. Users can view and analyze project data in real time through the dashboard, which supports dynamic interaction of charts.

[0045] How it works

[0046] Users perform project management, cost estimation, and risk assessment operations in the front-end application, and the request is sent to the API gateway through the user interface. The API gateway uniformly processes the front-end requests and forwards them to the corresponding back-end service module according to the request type. The multi-source data docking module in the back-end service module obtains project data, material prices, labor costs, and financial information from external data sources such as the BIM / ERP system, material supplier platform, and financial platform. The data obtained by the multi-source data docking module is transmitted to the data processing layer, the data cleaning and structuring module processes and cleans the data, and the big data analysis module performs cost analysis and market trend forecasting. The data processed by the data processing layer is passed to the business logic layer, and each module (project management module, cost estimation module, risk management module, contract module) performs corresponding business processing according to the user request and the processed data. The data processed by the business logic layer is passed to the data analysis and prediction module, the machine learning model performs cost estimation and prediction, and the data visualization module generates charts and dashboards. The results generated by the data analysis and prediction module are returned to the front-end application through the API gateway, and users can view and analyze the results through the user interface and intelligent assistant.

[0047] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An automatic service engineering cost consulting device, comprising a support rod (1) and a consulting display mechanism (4), characterized in that: An armrest plate (5) is fixedly provided at the upper end of the support rod (1), and a pentagonal support column (3) is fixedly provided at the center of the upper end surface of the armrest plate (5); The consulting display mechanism (4) comprises a touch display screen (402), a connecting seat (401) is rotatably provided at the rear center of the touch display screen (402), an extension rod (403) is hingedly provided at the rear end of the connecting seat (401), a telescopic rod (404) is hingedly provided at the rear end of the extension rod (403), and a fixed seat (505) is hingedly provided at the rear end of the telescopic rod (404).

2. The automatic service engineering cost consulting device according to claim 1 is characterized in that: The lower end surface of the armrest plate (5) is provided with an annular groove (10) near the edge, a slide bar (9) is slidably arranged inside the annular groove (10), and a storage box (6) is fixedly arranged on the lower end surface of the slide bar (9) through a plurality of connecting rods.

3. The automatic service engineering cost consulting device according to claim 1 is characterized in that: A support seat (7) is fixedly provided at the lower end of the support rod (1), a plurality of reinforcing angle irons (8) are fixedly provided between the support seat (7) and the support rod (1), and a top plate (2) is fixedly provided at the upper end of the pentagonal support column (3).

4. The automatic service engineering cost consulting device according to claim 1 is characterized in that: The hinges and rotational locations of the connecting seat (401), the extension rod (403), the telescopic rod (404) and the fixed seat (505) are all provided with a certain damping force, and one end of the fixed seat (505) away from the telescopic rod (404) is fixedly arranged on the outer surface of the pentagonal support column (3).

5. An automatic service engineering cost consulting system, including a front-end application, characterized in that: The front-end application is connected to an API gateway, the API gateway is connected to a multi-source data docking module, and the multi-source data docking module is respectively connected to a project management module, a cost estimation module, a risk management module and a contract module; The project management module, cost estimation module, risk management module and contract module are connected to a data processing layer, the data processing layer is connected to a data analysis and prediction module, and the data analysis and prediction module is connected to a data storage module.

6. The automatic service engineering cost consulting system according to claim 5 is characterized by: The multi-source data docking module is used to automatically acquire and integrate project data, material prices, labor costs and financial information from external data sources such as BIM / ERP systems, material supplier platforms and financial platforms. The data processing layer includes a data cleaning and structuring module and a big data analysis module. The data cleaning and structuring module is used to process and clean the collected data and convert unstructured data into structured data. The big data analysis module is used to use big data technology to perform cost analysis and market trend forecasting.

7. The automatic service engineering cost consulting system according to claim 5 is characterized by: The data analysis and prediction module includes a machine learning model and a data visualization module, wherein the machine learning model is used to train and apply models for cost estimation and prediction, and the data visualization module is used to display key information through charts and dashboards. The project management module includes management functions for project initiation, design, construction and completion stages.

8. The automatic service engineering cost consulting system according to claim 5 is characterized by: The cost estimation module uses a machine learning framework and a training cost estimation model to automatically calculate cost estimates based on project parameters and market data. The risk management module provides response strategies and risk reports by identifying and evaluating potential risks in the project. The contract module uses blockchain technology to manage contracts, automatically execute terms, and provide detailed audit records of contract execution.

9. The automatic service engineering cost consulting system according to claim 5 is characterized by: The data storage module includes a database and a data warehouse. The database is used to store real-time data of project data, cost data, and contract data, and the data warehouse is used to store historical project data and market data.

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