Dynamic cost management system and method in project cost settlement process

Abstract

The invention relates to the technical field of engineering settlement, in particular to a dynamic cost management system and method for an engineering cost settlement process, and aims to ensure that key information such as construction data and approval records cannot be tampered through a block chain technology and improve data credibility; a multi-dimensional deviation analysis algorithm comprehensively evaluates deviations of building materials, manpower, construction periods and the like, an approval process is automatically started when a threshold value is triggered, and abnormity is quickly responded; the optimal approver is automatically matched, and the flow time consumption is shortened; electronic signature and process monitoring support mobile terminal signing and real-time uploading, paper file delay is avoided, a reminding mechanism is automatically triggered when time is out, and the approval progress is ensured; the visual interaction module visually displays cost deviation and progress comparison through a thermodynamic diagram, a Gantt chart and other tools; automatic report generation and settlement support are achieved, manual accounting errors are reduced, and therefore the problem that in the existing project cost settlement process, cost dynamic management is low in practicability is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of project settlement, and particularly to a cost dynamic management system and method for project cost settlement during the project construction process. Background Art

[0002] The construction project cost refers to the construction cost of a construction project, that is, the comprehensive cost required to complete a construction project, including construction works, installation works and other related costs. As is well known, it is an important economic and technical indicator to measure a construction project. Controlling the cost of a construction project within a scientific and reasonable range is a complex and systematic project, which runs through all stages and links of the construction project. Therefore, it is necessary to comprehensively and systematically understand the characteristics of each stage and link, formulate corresponding control and management measures, and implement dynamic management in order to effectively control the project cost.

[0003] Currently, the existing cost dynamic management method for project cost settlement during the project construction process relies on manual data collection, resulting in lagging and inaccurate information. The analysis process relies on manual experience, with low efficiency and prone to errors, thus leading to low practicability of the existing cost dynamic management for project cost settlement during the project construction process. Summary of the Invention

[0004] The purpose of the present invention is to provide a cost dynamic management system and method for project cost settlement during the project construction process, aiming to solve the problem of low practicability of the existing cost dynamic management for project cost settlement during the project construction process.

[0005] To achieve the above purpose, in the first aspect, the present invention provides a cost dynamic management system for project cost settlement during the project construction process, including a data acquisition module, a blockchain evidence storage module, an AI analysis engine module, an intelligent approval platform and a visual interaction module. The data acquisition module, the blockchain evidence storage module, the AI analysis engine module, the intelligent approval platform and the visual interaction module are connected in sequence;

[0006] The data acquisition module is used to obtain construction data and market information in real time;

[0007] The blockchain evidence storage module is used to ensure that the obtained data cannot be tampered with;

[0008] The AI analysis engine module performs prediction, deviation analysis and dynamic optimization based on the obtained data;

[0009] The intelligent approval platform automatically assigns tasks based on the portrait of the approval personnel and supports mobile electronic signatures;

[0010] The visual interaction module multi-dimensionally displays the cost trend, deviation heat map and risk warning.

[0011] Among them, the data acquisition module includes a sensor acquisition unit, an API data access unit, and a data preprocessing unit. The sensor acquisition unit and the API data access unit are respectively connected to the data preprocessing unit;

[0012] The sensor acquisition unit is used to collect construction progress, equipment operation status, and environmental data in real time.

[0013] The API data access unit is used to dynamically obtain external information such as steel / cement price indices, labor cost fluctuations, and sudden policy and regulation changes.

[0014] The data preprocessing unit performs denoising, normalization, and time series alignment processing on the original data.

[0015] Among them, the blockchain evidence storage module includes a data uploading unit, a consensus verification unit, and a hash anchoring unit. The data uploading unit, the consensus verification unit, and the hash anchoring unit are connected in sequence;

[0016] The data uploading unit is used to encapsulate the cleaned construction data into blockchain transactions and broadcast them through private chain nodes;

[0017] The consensus verification unit uses the construction party, the supervision party, and the owner as verification nodes to conduct multi-party voting confirmation on the data authenticity and prevent single-point fraud;

[0018] The hash anchoring unit is used to synchronize the hash values of the key data of the private chain to the Ethereum public chain to protect privacy data.

[0019] Among them, the AI analysis engine module includes a prediction model unit, a deviation analysis unit, and an optimization decision-making unit. The prediction model unit, the deviation analysis unit, and the optimization decision-making unit are connected in sequence;

[0020] The prediction model unit, based on the input historical building material prices and construction period data, outputs a cost fluctuation curve for the next 30 days, and integrates meteorological satellite data and supply chain public opinion analysis to generate a dynamic risk budget;

[0021] The deviation analysis unit calculates the comprehensive deviation value based on a formula;

[0022] The optimization decision-making unit, according to the deviation results, simulates multiple adjustment plans and simulates the optimal coping strategies in extreme scenarios.

[0023] Among them, the intelligent approval platform includes a task assignment unit, an electronic signature unit, and a process monitoring unit. The task assignment unit, the electronic signature unit, and the process monitoring unit are connected in sequence;

[0024] The task allocation unit dynamically allocates tasks based on the portrait constructed from historical data;

[0025] The electronic signature unit uses a signed digital certificate and stores the signing record on the chain in real time for evidence;

[0026] The process monitoring unit is used to display the approval flow chart in real time. If the approval times out, it will automatically trigger the SMS / email reminder escalation mechanism.

[0027] Among them, the visual interaction module includes a data visualization unit and a warning prompt unit;

[0028] The data visualization unit displays the regional cost deviation through a heat map, and dynamically presents the comparison between the progress of each process and the plan through a Gantt chart;

[0029] The warning prompt unit is used to generate daily / weekly reports.

[0030] In a second aspect, a method for dynamically managing the cost of a project cost settlement process, which is used for the system for dynamically managing the cost of a project cost settlement process described in the first aspect, includes the following steps:

[0031] Based on historical data and real-time market information, dynamically generate a process-level cost plan through an AI prediction model;

[0032] Use Internet of Things devices to collect construction progress data in real time, and synchronize it to the blockchain platform for encrypted storage and verification;

[0033] Compare the actual expenditure with the planned value, use a multi-dimensional deviation analysis algorithm to calculate the comprehensive deviation value. If it exceeds the threshold, the smart contract will automatically trigger a hierarchical approval process and dynamically allocate tasks based on the historical response efficiency of the approval personnel;

[0034] According to the approval result, dynamically adjust the subsequent process plan through a reinforcement learning model to generate an optimized cost plan.

[0035] A cost dynamic management system for project cost settlement in the present invention. The present invention ensures the immutability of key information such as construction data and approval records through blockchain technology, and through the dual evidence storage mechanism of private chain and public chain, it protects privacy and enhances credibility; multi-party consensus verification eliminates single-point fraud, improves data credibility, and reduces the risk of disputes; AI prediction and deviation analysis generate a cost fluctuation curve for the next 30 days based on historical data and real-time market information, and dynamically adjust the budget to reduce the risk of overspending; multi-dimensional deviation analysis algorithm comprehensively evaluates deviations in building materials, labor, construction period, etc., and automatically starts the approval process when the threshold is triggered to quickly respond to anomalies; intelligent task assignment uses the portrait of approval personnel to automatically match the optimal approver, shortening the process time; electronic signature and process monitoring support mobile signing and real-time chain-up, avoiding delays in paper documents, and automatically triggering a reminder mechanism when overtime occurs to ensure the approval progress; the visual interaction module intuitively displays cost deviations and progress comparisons through tools such as heat maps and Gantt charts to help managers quickly locate problem areas; dynamic risk budget integrates external information such as meteorological data and supply chain public opinion, simulates extreme scenario response strategies, and enhances the risk resistance ability; data collection and preprocessing uniformly integrate multi-source data through sensors and APIs, eliminate information silos, and improve data consistency; automated report generation and settlement support reduce manual calculation errors and provide a complete traceability basis for audits, thus solving the problem of low practicality of cost dynamic management in the existing project cost settlement process. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 It is a schematic diagram of a cost dynamic management system for project cost settlement provided by the present invention.

[0038] Figure 2 It is a schematic diagram of the data collection module.

[0039] Figure 3 It is a schematic diagram of the blockchain evidence storage module.

[0040] Figure 4 It is a schematic diagram of the AI analysis engine module.

[0041] Figure 5 It is a schematic diagram of the intelligent approval platform.

[0042] Figure 6 It is a schematic diagram of the visual interaction module.

[0043] Figure 7 It is a flowchart of a method for dynamic cost management in the process of project cost settlement provided by the present invention.

[0044] In the figure: 1 - Data acquisition module, 2 - Blockchain evidence storage module, 3 - AI analysis engine module, 4 - Intelligent approval platform, 5 - Visual interaction module, 11 - Sensor acquisition unit, 12 - API data access unit, 13 - Data preprocessing unit, 21 - Data on-chain unit, 22 - Consensus verification unit, 23 - Hash anchoring unit, 31 - Prediction model unit, 32 - Deviation analysis unit, 33 - Optimization decision-making unit, 41 - Task assignment unit, 42 - Electronic signature unit, 43 - Process monitoring unit, 51 - Data visualization unit, 52 - Early warning prompt unit. Specific implementation manners

[0045] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present invention, but should not be construed as limiting the present invention.

[0046] Please refer to Figures 1 to 6 , in the first aspect, the present invention provides a system for dynamic cost management in the process of project cost settlement, including a data acquisition module 1, a blockchain evidence storage module 2, an AI analysis engine module 3, an intelligent approval platform 4 and a visual interaction module 5. The data acquisition module 1, the blockchain evidence storage module 2, the AI analysis engine module 3, the intelligent approval platform 4 and the visual interaction module 5 are connected in sequence;

[0047] The data acquisition module 1 is used to obtain construction data and market information in real time;

[0048] The blockchain evidence storage module 2 is used to ensure that the obtained data cannot be tampered with;

[0049] The AI analysis engine module 3 performs prediction, deviation analysis and dynamic optimization based on the obtained data;

[0050] The intelligent approval platform 4 automatically assigns tasks based on the portraits of approval personnel and supports mobile electronic signatures;

[0051] The visual interaction module 5 multi-dimensionally displays cost trends, deviation heat maps and risk warnings.

[0052] In this embodiment, the present invention ensures the immutability of key information such as construction data and approval records through blockchain technology. Through the dual deposit and proof mechanism of private chain and public chain, it not only protects privacy but also enhances credibility. Square consensus verification eliminates single-point fraud, improves data credibility, and reduces the risk of disputes. AI prediction and deviation analysis generate a cost fluctuation curve for the next 30 days based on historical data and real-time market information, and dynamically adjusts the budget to reduce the risk of overspending. The multi-dimensional deviation analysis algorithm comprehensively evaluates deviations in building materials, labor, construction period, etc., and automatically starts the approval process when the threshold is triggered, quickly responding to anomalies. Intelligent task allocation uses the portrait of approval personnel to automatically match the optimal approver, shortening the process time. Electronic signature and process monitoring support mobile signing and real-time chain-up, avoiding delays in paper documents. An automatic reminder mechanism is triggered when the time limit is exceeded to ensure the approval progress. The visual interaction module 5 intuitively displays cost deviations and progress comparisons through tools such as heat maps and Gantt charts, helping managers quickly locate problem areas. The dynamic risk budget integrates external information such as meteorological data and supply chain public opinion, simulates extreme scenario response strategies, and enhances the risk resistance ability. Data collection and preprocessing uniformly integrate multi-source data through sensors and APIs, eliminate information silos, and improve data consistency. Automated report generation and settlement support reduce manual calculation errors and provide a complete traceability basis for audits, thus solving the problem of low practicality of dynamic cost management in the existing project cost settlement process.

[0053] Further, the data collection module 1 includes a sensor collection unit 11, an API data access unit 12, and a data preprocessing unit 13. The sensor collection unit 11 and the API data access unit 12 are respectively connected to the data preprocessing unit 13;

[0054] The sensor collection unit 11 is used to collect construction progress, equipment operation status, and environmental data in real time.

[0055] The API data access unit 12 is used to dynamically obtain external information such as steel / cement price indices, labor cost fluctuations, and sudden policy and regulatory changes.

[0056] The data preprocessing unit 13 performs denoising, normalization, and time series alignment processing on the original data.

[0057] In this embodiment, the sensor acquisition unit 11 installs various sensors at the construction site. For example, a progress sensor is used to monitor the construction progress in real time, an equipment status sensor monitors the operation status of the equipment, and an environment sensor collects environmental data such as temperature and humidity. Through these sensors, key information during the construction process can be obtained in a timely manner. The API data access unit 12 establishes an API interface with relevant data providers. For example, it connects to the steel and cement price index release platform, the labor market data platform, and the policy and regulation release website to dynamically obtain external information to cope with market changes and policy adjustments. After receiving the raw data from the sensor acquisition unit 11 and the API data access unit 12, the data preprocessing unit 13 first performs denoising processing to remove the error data generated due to equipment failures or transmission interferences; then performs normalization processing to unify data with different ranges and magnitudes to the same scale; and finally performs time series alignment processing to ensure the consistency of the data in terms of time, providing an accurate data basis for subsequent analysis.

[0058] Further, the blockchain evidence storage module 2 includes a data on-chain unit 21, a consensus verification unit 22, and a hash anchoring unit 23, and the data on-chain unit 21, the consensus verification unit 22, and the hash anchoring unit 23 are connected in sequence;

[0059] The data on-chain unit 21 is used to encapsulate the cleaned construction data into a blockchain transaction and broadcast it through the private chain node;

[0060] The consensus verification unit 22 takes the construction party, the supervision party, and the owner party as verification nodes to conduct multi-party voting confirmation on the data authenticity, eliminating single-point fraud;

[0061] The hash anchoring unit 23 is used to synchronize the hash value of the key data in the private chain to the Ethereum public chain to protect privacy data.

[0062] In this embodiment, the data on-chain unit 21 encapsulates the construction data cleaned by the data preprocessing unit 13 and converts it into a blockchain transaction format. Then it is broadcast through the private chain node so that all participating parties can receive the relevant data. The consensus verification unit 22 sets the construction party, the supervision party, and the owner party as verification nodes, and each party conducts a vote to confirm the authenticity of the data. Only when the majority of the nodes recognize the data as true, the data will be confirmed as true and valid, thus eliminating the possibility of single-point fraud. The hash anchoring unit 23 generates a hash value for the key data in the private chain and synchronizes it to the Ethereum public chain. On the one hand, this protects privacy data, and on the other hand, it uses the immutable feature of the public chain to achieve "dual evidence storage", improving the credibility and security of the data.

[0063] Further, the AI analysis engine module 3 includes a prediction model unit 31, a deviation analysis unit 32, and an optimization decision unit 33, which are connected in sequence;

[0064] The prediction model unit 31 outputs a cost fluctuation curve for the next 30 days based on the input historical building material prices and construction period data, and integrates meteorological satellite data and supply chain public opinion analysis to generate a dynamic risk budget;

[0065] The deviation analysis unit 32 calculates the comprehensive deviation value based on a formula;

[0066] The optimization decision unit 33 simulates multiple adjustment plans according to the deviation results and simulates the optimal coping strategies in extreme scenarios.

[0067] In this embodiment, the prediction model unit 31 inputs information such as historical building material prices and construction period data, and uses machine learning algorithms to output a cost fluctuation curve for the next 30 days. At the same time, it integrates meteorological satellite data to consider the impact of bad weather on the construction progress and cost; conducts supply chain public opinion analysis to evaluate possible problems of suppliers, so as to generate a dynamic risk budget. The deviation analysis unit 32 calculates the comprehensive deviation value according to a specific formula, and evaluates the implementation of the project cost by comparing the actual data with the predicted data. The optimization decision unit 33 simulates multiple adjustment plans according to the deviation results obtained by the deviation analysis unit 32. For example, adjusting the construction progress, replacing building material suppliers, etc., and simulating the optimal coping strategies in extreme scenarios, such as coping measures in case of major natural disasters or policy mutations.

[0068] Further, the intelligent approval platform 4 includes a task assignment unit 41, an electronic signature unit 42, and a process monitoring unit 43, which are connected in sequence;

[0069] The task assignment unit 41 dynamically assigns tasks based on the portrait constructed from historical data;

[0070] The electronic signature unit 42 uses a signed digital certificate and stores the signing record on the chain in real time for evidence;

[0071] The process monitoring unit 43 is used to display the approval flow chart in real time. If the approval times out, it will automatically trigger a text message / email reminder escalation mechanism.

[0072] In this embodiment, the task allocation unit 41 constructs a portrait of the approval personnel based on historical data, analyzes their characteristics such as work efficiency and professional field, and dynamically allocates tasks according to the nature and urgency of the current task to ensure that the tasks are assigned to the most suitable personnel. The electronic signature unit 42 uses digital certificates for signing by the approval personnel, and the signing records will be uploaded to the blockchain in real time for evidence storage, ensuring the authenticity and non-repudiation of the signing process. The process monitoring unit 43 displays the approval flow chart in real time, clearly showing the progress of each approval link. If the approval of a certain link times out, the system will automatically trigger a text message or email reminder and upgrade the reminder mechanism to ensure the efficient progress of the approval process.

[0073] Furthermore, the visual interaction module 5 includes a data visualization unit 51 and a warning prompt unit 52;

[0074] The data visualization unit 51 displays the regional cost deviation through a heat map and dynamically presents the comparison between the progress of each process and the plan through a Gantt chart;

[0075] The warning prompt unit 52 is used to generate daily / weekly reports.

[0076] In this embodiment, the data visualization unit 51 intuitively displays the regional cost deviation through a heat map, and the darker the color, the greater the deviation, which is convenient for managers to quickly locate the problem area. The Gantt chart is used to dynamically present the comparison between the progress of each process and the plan, clearly showing the early or lagging situation of the process. The warning prompt unit 52 automatically generates daily or weekly reports based on the data collected and analyzed by the system, providing comprehensive cost information and analysis results for managers to facilitate decision-making.

[0077] Please refer to Figure 7 , secondly, a method for dynamically managing the cost during the project cost settlement process, which is used for the system for dynamically managing the cost during the project cost settlement process described in the first aspect, includes the following steps:

[0078] S1 Dynamically generate a process-level cost plan through an AI prediction model based on historical data and real-time market information;

[0079] Specifically, an AI prediction model is constructed based on historical data and real-time market information. The historical data includes information such as building material costs, labor costs, and construction periods of past similar projects, and the real-time market information is obtained through the data acquisition module 1. Using these data, the model dynamically generates a process-level cost plan, which details the building material costs, labor costs of each process, and the risk budget considering environmental factors (such as bad weather, policy and regulation changes, etc.).

[0080] S2 Use Internet of Things devices to collect construction progress data in real time and synchronize it to the blockchain platform for encrypted storage and verification;

[0081] Specifically, the construction progress data, such as the completed project quantity and the equipment operation duration, are collected in real time by Internet of Things devices. These data are synchronized to the blockchain platform and encrypted and verified through the blockchain evidence storage module 2 to ensure the authenticity and immutability of the data.

[0082] S3 Compare the actual expenditure with the planned value, calculate the comprehensive deviation value using a multi-dimensional deviation analysis algorithm. If it exceeds the threshold, the smart contract automatically triggers a hierarchical approval process and dynamically assigns tasks based on the historical response efficiency of the approval personnel.

[0083] Specifically, compare the actual expenditure with the planned value, and calculate the comprehensive deviation value using a multi-dimensional deviation analysis algorithm. The multi-dimensional deviation analysis takes into account multiple factors such as building material costs, labor costs, and construction periods. If the comprehensive deviation value exceeds the preset threshold, the smart contract automatically triggers a hierarchical approval process. According to the historical response efficiency of the approval personnel, the task allocation unit 41 dynamically assigns approval tasks to ensure the efficient progress of the approval process.

[0084] S4 According to the approval result, dynamically adjust the subsequent process plan through a reinforcement learning model to generate an optimized cost plan.

[0085] Specifically, according to the approval result, use a reinforcement learning model to dynamically adjust the subsequent process plan. The reinforcement learning model continuously learns and optimizes, simulates the cost changes under different adjustment plans, and generates an optimized cost plan to ensure the smooth completion of the project within the budget.

[0086] Beneficial effects:

[0087] I. Improvement in data authenticity and security:

[0088] Through the blockchain evidence storage module, key information such as construction data and approval records is guaranteed to be immutable. The dual evidence storage mechanism of the private chain and the public chain not only protects privacy but also enhances the credibility. The consensus verification mechanism eliminates single-point fraud, improves data credibility, and effectively reduces the risk of disputes caused by data fraud or tampering.

[0089] II. Enhancement of prediction and decision-making capabilities: The AI analysis engine module can generate a cost fluctuation curve for the next 30 days based on historical data and real-time market information and conduct dynamic risk budgeting. This helps project managers anticipate potential cost risks in advance and take corresponding countermeasures. At the same time, the multi-dimensional deviation analysis algorithm can comprehensively evaluate deviations in building materials, labor, construction periods, etc., and automatically start the approval process when the threshold is triggered, enabling a quick response to anomalies.

[0090] III. Optimization of Approval Process: The intelligent approval platform can automatically match the optimal approver through task assignment based on the portrait of approvers, significantly shortening the time-consuming of the approval process. Electronic signature and process monitoring support mobile signing and real-time blockchain uploading, avoiding the delay of paper documents and ensuring the real-time nature of the approval progress. In addition, the reminder mechanism is automatically triggered when the approval times out, further ensuring the efficient progress of the approval process.

[0091] IV. Visual Interaction and Decision Support: The visual interaction module intuitively displays cost deviations and schedule comparisons through tools such as heat maps and Gantt charts, helping managers quickly locate problem areas. The dynamic risk budget integrates external information, such as meteorological data and supply chain public opinion, simulates extreme scenario response strategies, and enhances the project's risk resistance ability.

[0092] V. Improvement of Data Collection and Processing Efficiency: The data collection module uniformly integrates multi-source data through sensors and APIs, eliminating information silos and improving data consistency. The data preprocessing unit performs denoising, normalization, and time series alignment on the raw data, providing an accurate data basis for subsequent analysis.

[0093] The above-disclosed is only a preferred embodiment of the cost dynamic management system and method in the project cost settlement process of the present invention. Of course, it cannot be used to limit the scope of the rights of the present invention. Those of ordinary skill in the art can understand all or part of the processes of implementing the above embodiments, and the equivalent changes made according to the claims of the present invention still fall within the scope covered by the invention.

Claims

1. A dynamic cost management system for the construction cost settlement process, characterized in that: It includes a data acquisition module, a blockchain evidence storage module, an AI analysis engine module, an intelligent approval platform and a visual interaction module, wherein the data acquisition module, the blockchain evidence storage module, the AI ​​analysis engine module, the intelligent approval platform and the visual interaction module are connected in sequence; The data acquisition module is used to obtain construction data and market information in real time; The blockchain evidence storage module is used to ensure that the acquired data cannot be tampered with; The AI ​​analysis engine module performs prediction, deviation analysis and dynamic optimization based on acquired data; The intelligent approval platform automatically assigns tasks based on the portrait of the approver and supports mobile electronic signatures; The visual interaction module displays cost trends, deviation heat maps and risk warnings in multiple dimensions.

2. The dynamic management system for construction cost settlement process according to claim 1, characterized in that: The data acquisition module includes a sensor acquisition unit, an API data access unit and a data preprocessing unit, and the sensor acquisition unit and the API data access unit are respectively connected to the data preprocessing unit; The sensor acquisition unit is used to collect construction progress, equipment operating status, and environmental data in real time. The API data access unit is used to dynamically obtain external information such as steel / cement price index, labor cost fluctuations, and sudden policy and regulatory changes. The data preprocessing unit performs denoising, normalization and time series alignment processing on the original data.

3. The dynamic management system for construction cost settlement process according to claim 2, characterized in that: The blockchain evidence storage module includes a data chain unit, a consensus verification unit and a hash anchor unit, and the data chain unit, the consensus verification unit and the hash anchor unit are connected in sequence; The data on-chain unit is used to encapsulate the cleaned construction data into a blockchain transaction and broadcast it through a private chain node; The consensus verification unit uses the construction party, the supervision party, and the owner party as verification nodes to conduct multi-party voting to confirm the authenticity of the data, eliminating single-point fraud; The hash anchoring unit is used to synchronize the key data hash value of the private chain to the Ethereum public chain to protect the privacy data.

4. The dynamic management system for construction cost settlement process according to claim 3 is characterized in that: The AI ​​analysis engine module includes a prediction model unit, a deviation analysis unit and an optimization decision unit, and the prediction model unit, the deviation analysis unit and the optimization decision unit are connected in sequence; The forecasting model unit outputs the cost fluctuation curve for the next 30 days based on the input of historical building material prices and construction period data, and integrates meteorological satellite data and supply chain public opinion analysis to generate a dynamic risk budget; The deviation analysis unit calculates the comprehensive deviation value based on the formula; The optimization decision unit simulates multiple adjustment plans based on the deviation results and simulates the optimal response strategy under extreme scenarios.

5. The dynamic management system for construction cost settlement process according to claim 4 is characterized in that: The intelligent approval platform includes a task allocation unit, an electronic signature unit and a process monitoring unit, and the task allocation unit, the electronic signature unit and the process monitoring unit are connected in sequence; Task allocation unit, which dynamically allocates tasks based on historical data to build profiles; The electronic signature unit uses a signed digital certificate and stores the signature record on the blockchain in real time; The process monitoring unit is used to display the approval process diagram in real time, and automatically trigger the SMS / email reminder upgrade mechanism if the approval timeout.

6. The dynamic management system for construction cost settlement process according to claim 5, characterized in that: The visualization interaction module includes a data visualization unit and an early warning prompt unit; Data visualization unit, which displays regional cost deviations through heat maps and dynamically presents the progress and plan comparison of each process through Gantt charts; The early warning prompt unit is used to generate daily / weekly reports.

7. A method for dynamic cost management in the process of engineering cost settlement, used in the dynamic cost management system in the process of engineering cost settlement according to any one of claims 1 to 6, characterized in that: The following steps are involved: Based on historical data and real-time market information, the process-level cost plan is dynamically generated through the AI ​​prediction model; Use IoT devices to collect construction progress data in real time and synchronize it to the blockchain platform for encrypted storage and verification; Compare the actual expenditure with the planned value, and use a multi-dimensional deviation analysis algorithm to calculate the comprehensive deviation value. If it exceeds the threshold, the smart contract automatically triggers the hierarchical approval process and dynamically allocates tasks based on the historical response efficiency of the approver; According to the approval results, the subsequent process plan is dynamically adjusted through the reinforcement learning model to generate an optimized cost plan.

Images