CN115392676A - Intelligent engineering cost management system and method based on cloud computing and big data - Google Patents

Intelligent engineering cost management system and method based on cloud computing and big data Download PDF

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CN115392676A
CN115392676A CN202210990897.1A CN202210990897A CN115392676A CN 115392676 A CN115392676 A CN 115392676A CN 202210990897 A CN202210990897 A CN 202210990897A CN 115392676 A CN115392676 A CN 115392676A
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王敏
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Abstract

The invention relates to an intelligent management system and method for construction cost based on cloud computing and big data, which comprises the steps of calculating the difference between the time limit of a task item input by a user and the time limit of an estimated task item according to the time required by tasks in the engineering quantity stage, and sending an alarm signal to a client if the difference is greater than a preset value; automatically budgeting task item cost and project total cost in a stage according to project material information, project quantity information and construction deadline information, and sending an alarm signal to a client if cost excess occurs; the method and the system can calculate in real time according to the actual progress information filled by the constructors, update the actual total construction period and the actual cost, delay the actual construction period, send an alarm signal to the client side, and automatically generate the actual task item construction period time.

Description

Intelligent engineering cost management system and method based on cloud computing and big data
Technical Field
The invention relates to an intelligent engineering cost management system and method based on cloud computing and big data.
Background
The management of the construction cost is an important component link of the construction management of the building engineering, the construction cost is generally estimated and managed through manual accounting in the prior art, so that the workload is large, the manual method is low in efficiency and prone to error, and particularly the problems of construction period time, cost and the like of the engineering project are solved, and the workload is large and complicated for the conventional manual accounting.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an intelligent engineering cost management system and method based on cloud computing and big data.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the intelligent engineering cost management system based on cloud computing and big data comprises a drawing input module, a material computing module, a construction plan module, an engineering plan evaluation module, an engineering cost evaluation module, an engineering project tracking module and a client; wherein the content of the first and second substances,
the drawing input module is used for receiving an architectural design drawing input by a user and inputting a system, extracting the architectural type and the size information marked on the drawing, and sending the architectural type information and the architectural size information to the model construction module;
the model construction module is used for acquiring a building template according to the building type information, labeling the building template according to the building size information and calculating the building project material information;
the construction plan module is used for importing a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module is used for evaluating the project quantity of the stage task item, calculating the difference between the period of the user input task item and the period of the estimated task item according to the time required by the project quantity stage task, and sending an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module is used for automatically budgeting task item cost and project total cost in the stage according to project material information, project quantity information and construction deadline information, and sending an alarm signal to the client if cost excess occurs;
the engineering project tracking module is used for calculating in real time according to the actual progress information filled by the constructors, updating the actual total construction period and the actual cost, delaying the actual construction period, sending an alarm signal to the client side, and automatically generating a time table of the actual task project construction period.
Further, according to the time required by the tasks at the engineering quantity stage, calculating the difference between the term of the user input task item and the term of the estimated task item, specifically, firstly estimating the time required by the tasks at the engineering quantity stage, and pre-configuring a progress estimation function for each stage task, wherein the progress estimation function is used for inputting finished project material information, engineering quantity information and construction term information and outputting a result expected for the future construction progress, and the progress estimation function sets different main function models and different dynamic adjustment parameters for different stage tasks;
further, the project plan evaluation module is used for modifying the dynamic adjustment parameters of the progress estimation function, specifically, the project plan evaluation module periodically obtains historical data of 'the expected result of the future construction progress of the phase task', compares the calculated result of the actual construction progress of the current phase with the previously corresponding 'the expected result of the future construction progress of the phase task', and feeds back and modifies the dynamic adjustment parameters according to the difference.
Further, the progress prediction function is built based on a plurality of neuron layers of a deep neural network, the neuron layers are connected through one-to-one mapping, parameters, namely the offset and the weight value of a specific function in each neuron layer, are dynamically adjusted, the neuron layers of the deep neural network are used for inputting the quantized values of finished project material information, engineering quantity information and construction time limit information, an output layer is connected to the downstream of the neuron layers of the deep neural network and used for outputting a result expected by the future construction progress of a stage task, the difference value between the result of the actual construction progress of the current stage and the result expected by the future construction progress of the stage task corresponding to the current stage is calculated on the output layer, and the feedback modification dynamic adjustment parameters are specifically the offset and the weight value modification of the specific function in each neuron layer through back propagation.
The intelligent management method for the construction cost based on the cloud computing and the big data comprises the steps of receiving a building design drawing input by a user, inputting the building design drawing into a system, extracting the building type and the size information marked on the drawing, and sending the building type information and the building size information to a model construction module;
acquiring a building template according to the building type information, labeling the building template according to the building size information, and calculating the building project material information;
the construction plan module imports a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module evaluates the project amount of the task items in the stages, calculates the difference between the period of the task item input by the user and the period of the estimated task item according to the time required by the task in the project amount stage, and sends an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module automatically budgets task item cost and project total cost in the stage according to project material information, project amount information and construction deadline information, and sends an alarm signal to a client if the cost is excessive;
and the engineering project tracking module calculates in real time according to the actual progress information filled by the constructors, updates the actual total construction period and the actual cost, sends an alarm signal to the client side for delaying the actual construction period, and automatically generates an actual task project construction period schedule. .
Advantageous effects
According to the method and the device, the difference value between the task item deadline input by the user and the estimated task item deadline can be calculated according to the task required time in the engineering quantity stage, and if the difference value is greater than a preset value, an alarm signal is sent to the client; automatically budgeting the task item cost and the project total cost in the stage according to the project material information, the project amount information and the construction deadline information, and sending an alarm signal to a client if the cost is excessive; the method and the system can calculate in real time according to the actual progress information filled by the constructors, update the actual total construction period and the actual cost, delay the actual construction period, send an alarm signal to the client side, and automatically generate the actual task item construction period time.
Detailed Description
The application discloses an intelligent engineering cost management system based on cloud computing and big data, which comprises a drawing input module, a material computing module, a construction plan module, an engineering plan evaluation module, an engineering cost evaluation module, an engineering project tracking module and a client side; wherein the content of the first and second substances,
the drawing input module is used for receiving a building design drawing input by a user, inputting the drawing into a system, extracting the building type and the size information marked on the drawing, and sending the building type information and the building size information to the model construction module;
the model building module is used for acquiring a building template according to the building type information, marking the building template according to the building size information and calculating the building project material information;
the construction plan module is used for importing a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module is used for evaluating the project quantity of the stage task item, calculating the difference between the period of the user input task item and the period of the estimated task item according to the time required by the project quantity stage task, and sending an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module is used for automatically budgeting task item cost and project total cost in the stage according to project material information, project amount information and construction deadline information, and sending an alarm signal to a client if the cost is excessive;
the engineering project tracking module is used for calculating in real time according to actual progress information filled by constructors, updating actual total construction period and actual cost, sending an alarm signal to a client side after the actual construction period is delayed, and automatically generating an actual task project construction period schedule.
In specific implementation, a building design drawing input by a user is received and input into a system, the building type and the size information marked on the drawing are extracted, and the building type information and the building size information are sent to a model construction module; acquiring a building template according to the building type information, labeling the building template according to the building size information, and calculating the building project material information; importing a construction schedule, wherein the construction schedule comprises one or more stage task items, and the stage task items comprise task item deadlines; evaluating the engineering quantity of the stage task item, calculating the difference between the time limit of the user input task item and the estimated task item time limit according to the time required by the engineering quantity stage task, and if the difference is greater than a preset value, sending an alarm signal to the client; the project cost evaluation module automatically budgets task item cost and project total cost in the stage according to project material information, project quantity information and construction deadline information, and sends an alarm signal to a client if cost excess occurs; and the engineering project tracking module calculates in real time according to the actual progress information filled by the constructors, updates the actual total construction period and the actual cost, delays the actual construction period, sends an alarm signal to the client and automatically generates the actual task project construction period time.
According to the method and the device, the difference value between the time limit of the task item input by the user and the time limit of the estimated task item can be calculated according to the time required by the task in the engineering quantity stage, and if the difference value is larger than a preset value, an alarm signal is sent to the client; automatically budgeting task item cost and project total cost in a stage according to project material information, project quantity information and construction deadline information, and sending an alarm signal to a client if cost excess occurs; the method and the system can calculate in real time according to the actual progress information filled by the constructors, update the actual total construction period and the actual cost, delay the actual construction period, send an alarm signal to a client, and automatically generate the actual task item construction period time.
Preferably, according to the time required by the task at the engineering quantity stage, calculating the difference between the term of the user input task item and the term of the estimated task item, specifically, firstly estimating the time required by the task at the engineering quantity stage, and pre-configuring a progress estimation function for each stage task, wherein the progress estimation function is used for inputting finished project material information, engineering quantity information and construction term information and outputting a result expected for the future construction progress, and the progress estimation function sets different main function models and different dynamic adjustment parameters for different stage tasks;
preferably, the project plan evaluation module is configured to modify the dynamic adjustment parameter of the progress estimation function, and specifically, the project plan evaluation module periodically obtains historical data of a "result expected for the future construction progress of the phase task", compares the result of calculating the actual construction progress of the current phase with the previously corresponding "result expected for the future construction progress of the phase task", and modifies the dynamic adjustment parameter according to the difference.
Preferably, the progress estimation function is built on the basis of a plurality of neuron layers of a deep neural network, the neuron layers are connected through one-to-one mapping, parameters, namely the offset and weight values of specific functions in the neuron layers, are dynamically adjusted, the neuron layers of the deep neural network are used for inputting the quantized values of finished project material information, engineering quantity information and construction period information, an output layer is connected to the downstream of the neuron layers of the deep neural network and used for outputting a result expected by the future construction progress of a stage task, the difference value between the result of the actual construction progress of the current stage and the result expected by the future construction progress of the stage task corresponding to the current stage is calculated on the output layer, and the dynamic adjustment parameters are fed back and modified, namely the offset and the weight values of the specific functions in the neuron layers are modified through back propagation.
Program code for implementing the functionality of the systems in the present application may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server. In the context of this application, the program code for the functions of the system in the present application is stored on a machine-readable medium, which may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing.
The system is preferably built in the cloud computing server, and the data source is preferably an open-source big data channel.
The application also discloses an intelligent management method for the construction cost based on cloud computing and big data, which comprises the steps of receiving a building design drawing input by a user, inputting the building design drawing into a system, extracting the building type and the size information marked on the drawing, and sending the building type information and the building size information to a model construction module;
acquiring a building template according to the building type information, labeling the building template according to the building size information, and calculating the building project material information;
the construction plan module imports a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module evaluates the project amount of the task items in the stages, calculates the difference between the period of the task item input by the user and the period of the estimated task item according to the time required by the task in the project amount stage, and sends an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module automatically budgets task item cost and project total cost in the stage according to project material information, project amount information and construction deadline information, and sends an alarm signal to a client if the cost is excessive;
and the engineering project tracking module calculates in real time according to the actual progress information filled by the constructors, updates the actual total construction period and the actual cost, delays the actual construction period, sends an alarm signal to the client and automatically generates a construction period schedule of the actual task item. .

Claims (5)

1. The intelligent engineering cost management system based on cloud computing and big data is characterized by comprising a drawing input module, a material computing module, a construction plan module, an engineering plan evaluation module, an engineering cost evaluation module, an engineering project tracking module and a client; wherein the content of the first and second substances,
the drawing input module is used for receiving an architectural design drawing input by a user and inputting a system, extracting the architectural type and the size information marked on the drawing, and sending the architectural type information and the architectural size information to the model construction module;
the model building module is used for acquiring a building template according to the building type information, marking the building template according to the building size information and calculating the building project material information;
the construction plan module is used for importing a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module is used for evaluating the project quantity of the stage task item, calculating the difference between the period of the user input task item and the period of the estimated task item according to the time required by the project quantity stage task, and sending an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module is used for automatically budgeting task item cost and project total cost in the stage according to project material information, project quantity information and construction deadline information, and sending an alarm signal to the client if cost excess occurs;
the engineering project tracking module is used for calculating in real time according to the actual progress information filled by the constructors, updating the actual total construction period and the actual cost, delaying the actual construction period, sending an alarm signal to the client side, and automatically generating a time table of the actual task project construction period.
2. The cloud computing and big data based engineering cost intelligent management system according to claim 1, wherein a difference between a user input task item time limit and an estimated task item time limit is calculated according to engineering volume stage task required time, specifically, the engineering volume stage task required time is estimated first, a progress estimation function is configured in advance for each stage task, the progress estimation function is used for inputting finished project material information, engineering volume information and construction time limit information and outputting a result expected for future construction progress, and the progress estimation function sets different main function models and different dynamic adjustment parameters for different stage tasks;
3. the intelligent management system for construction cost based on cloud computing and big data as claimed in claim 2, wherein the engineering plan evaluation module is configured to modify the dynamic adjustment parameter of the progress estimation function, specifically, the engineering plan evaluation module periodically obtains historical data of the "result expected in future construction progress of the phase task", and compares the result of calculating the actual construction progress of the current phase with the previously corresponding "result expected in future construction progress of the phase task" and modifies the dynamic adjustment parameter according to the difference feedback.
4. The cloud computing and big data based engineering cost intelligent management system according to claim 3, wherein the progress estimation function is built based on a plurality of deep neural network neuron layers, each layer of neuron layers is connected through one-to-one mapping, parameters, namely offset and weight values of specific functions in each layer of neuron layers, are dynamically adjusted, the plurality of deep neural network neuron layers are used for inputting quantized values of completed project material information, engineering quantity information and construction period information, an output layer is connected with the downstream of the plurality of deep neural network neuron layers and used for outputting a result expected by the future construction progress of a stage task, a difference value between the result of the actual construction progress of the current stage and the result expected by the future construction progress of the stage task corresponding to the current stage is calculated on the output layer, and the feedback modification dynamic adjustment parameters are specifically offset and weight value modification of specific functions in each layer of neuron layers through back propagation.
5. The intelligent management method for the construction cost based on the cloud computing and the big data is characterized by comprising the steps of receiving a building design drawing input by a user, inputting the building design drawing into a system, extracting the building type and the size information marked on the drawing, and sending the building type information and the building size information to a model construction module;
acquiring a building template according to the building type information, marking the building template according to the building size information, and calculating the building project material information;
the construction plan module imports a construction plan, the construction plan comprises one or more stage task items, and the stage task items comprise task item deadlines;
the project plan evaluation module evaluates the project amount of the task items in the stages, calculates the difference between the period of the task item input by the user and the period of the estimated task item according to the time required by the task in the project amount stage, and sends an alarm signal to the client if the difference is greater than a preset value;
the project cost evaluation module automatically budgets task item cost and project total cost in the stage according to project material information, project quantity information and construction deadline information, and sends an alarm signal to a client if cost excess occurs;
the engineering project tracking module calculates in real time according to the actual progress information filled by the constructors, updates the actual total construction period and the actual cost, sends an alarm signal to the client side for delaying the actual construction period, and automatically generates a schedule of the actual task project construction period.
CN202210990897.1A 2022-08-18 2022-08-18 Intelligent engineering cost management system and method based on cloud computing and big data Withdrawn CN115392676A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115994681A (en) * 2023-03-24 2023-04-21 江苏苏港智能装备产业创新中心有限公司 Engineering cost real-time analysis management method and management system thereof
CN117592948A (en) * 2024-01-18 2024-02-23 一智科技(成都)有限公司 Construction project early warning method, system, device and storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115994681A (en) * 2023-03-24 2023-04-21 江苏苏港智能装备产业创新中心有限公司 Engineering cost real-time analysis management method and management system thereof
CN117592948A (en) * 2024-01-18 2024-02-23 一智科技(成都)有限公司 Construction project early warning method, system, device and storage medium
CN117592948B (en) * 2024-01-18 2024-04-26 一智科技(成都)有限公司 Construction project early warning method, system, device and storage medium

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