Building equipment management system based on artificial intelligence

Abstract

The invention discloses a building equipment management system based on artificial intelligence, and relates to the technical field of administrative data processing systems, and the building equipment management system comprises a block chain and relates to an administrative data processing system, and the building equipment management system comprises a data collection module, a comprehensive evaluation prediction module, an intelligent decision module and a user interface module. Data are collected from building equipment and an office environment, administrative efficiency and economic feasibility of a block chain technology are evaluated through a comprehensive evaluation prediction and optimization module, an optimization adjustment index TZ is output, and a resource allocation and time management strategy is adjusted according to the optimization adjustment index TZ. The block chain management cost prediction unit and the time management and resource configuration optimization unit output result values, an optimization strategy is formulated through the intelligent decision module, the optimization strategy is converted into a specific operation instruction, the system performance is monitored in real time, and the optimization strategy is adjusted again according to feedback.

Description

Technical Field

[0001] The present invention relates to the technical field of administrative data processing systems, and particularly to an artificial intelligence-based construction equipment management system. Background Art

[0002] In the current administrative, commercial, financial, management, monitoring, and prediction fields, data processing systems play a crucial role. Especially in construction equipment management systems, traditional methods often rely on manual monitoring and manual adjustment, which are not only inefficient but also error-prone. With the development of technology, artificial intelligence-based data processing systems have gradually become the mainstream. They can automatically collect, analyze, and process large amounts of data to optimize equipment performance, improve management efficiency, and reduce costs.

[0003] However, existing construction equipment management systems do not have data processing systems specifically applicable to the administrative, commercial, financial, management, monitoring, and prediction fields, and there are still many problems and deficiencies in evaluating administrative efficiency, predicting blockchain management costs, and optimizing time management and resource allocation. Specifically, traditional methods usually rely on subjective judgments or simple statistical indicators and cannot comprehensively and objectively reflect the true situation of administrative efficiency, resulting in inaccurate evaluation of administrative efficiency. The introduction of blockchain technology has brought new opportunities to construction equipment management but also challenges in cost prediction. Existing systems often lack effective prediction models and are difficult to accurately estimate the economic feasibility of blockchain technology, resulting in inaccurate prediction of blockchain management costs. In the case of limited resources, how to reasonably allocate time and resources to maximize benefits is a key issue. Existing systems often lack intelligent decision support and cannot dynamically adjust and optimize strategies based on real-time data, resulting in insufficient time management and resource optimization. Summary of the Invention

[0004] The purpose of the present invention is to provide an artificial intelligence-based construction equipment management system to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: a construction equipment management system including a blockchain and related to an administrative data processing system; It includes a data acquisition module, a comprehensive evaluation and prediction module, an intelligent decision-making module, and a user interface module; The specific implementation steps are as follows: Through the data acquisition module, collect data from construction equipment and the office environment; Through the comprehensive evaluation, prediction and optimization module, evaluate the administrative efficiency and the economic feasibility of blockchain technology, and output the optimization adjustment index TZ. According to the optimization adjustment index TZ, adjust the resource allocation and time management strategies. The comprehensive evaluation, prediction and optimization module includes a comprehensive administrative efficiency evaluation unit, a blockchain management cost prediction unit, and a time management and resource allocation optimization unit; Based on the result values output by the comprehensive administrative efficiency evaluation unit, the blockchain management cost prediction unit, and the time management and resource allocation optimization unit, formulate an optimization strategy through the intelligent decision-making module, convert the optimization strategy into specific operation instructions, monitor the system performance in real time, and optimize the strategy again according to the feedback adjustment; The user interface module provides a user-friendly interface, generates detailed reports, and allows users to set parameters and adjust strategies through the interface; The devices used in the data collection module include sensors, cameras, and RFID tags; The devices used in the comprehensive evaluation, prediction and optimization module include servers and network devices; The devices used in the user interface module include workstations.

[0006] Optionally, the calculation formula of the comprehensive administrative efficiency evaluation unit is as follows: XZX = [YC × (BF / BB)] / [XY × (1 + YJB / BB)]; YC = (YCS × ZL) / (BS × BZL); XY = YM / ZXM; ; Where: XZX is the administrative efficiency index; YC is the email processing efficiency index; BF is the office workload, and BF reflects the total amount of current office tasks; BB is the target processing efficiency, and BB reflects the amount of tasks that can be processed daily and hourly as set; XY is the project delay rate; YJB is the email response delay index; YCS is the email processing speed, ZL is the processing accuracy rate, BS is the standard processing speed, and BZL is the standard processing accuracy rate; YM is the total number of delayed projects, and ZXM is the total project index; m is the total number of emails, SX i is the actual response time of the i-th time, BX i is the target response time of the i-th time.

[0007] Optionally, the calculation formula of the blockchain management cost prediction unit is as follows: QCY = [(XZX + 1) / 2] × (QJC base + QT eth × QTF eth ); Where: QCY is the cost prediction index; QJC base is the basic blockchain cost, including the costs generated by node maintenance, network bandwidth, and data storage; QT eth is the chain cost, including the costs generated by hardware, electricity, software, network, manpower, security, and exchanges; QTF eth is the weight factor, and QTF eth specifically represents the weight of the chain in the workload, indicating its relative importance among all blockchain technologies.

[0008] Optionally, the calculation formula of the time management and resource allocation optimization unit is as follows: TZ = [QZY × (1 - SG / TC new )] / [XZX × (1 + ZY used / ZY tottal )]; Where: TZ is the optimization adjustment index; SG is the actual management time, and SG reflects the time required for the current management task; TC new is the adjusted new target processing efficiency, and TC new is specifically reset artificially according to the optimization adjustment index TZ; ZY used is the number of resources already used; ZY tottal is the total number of resources.

[0009] Optionally, the adjustment steps based on the optimization adjustment index TZ output by the time management and resource allocation optimization unit are as follows: S1. Set a hyperparameter TC for reference evaluation of the optimization adjustment index TZ and reflecting the cost-benefit ratio. The specific calculation formula of the hyperparameter TC is as follows; TC = QCY × XZX / ZY tottal ; S2. If the hyperparameter TC > the optimization adjustment index TZ, it indicates that with the given amount of resources, higher administrative efficiency has achieved lower management costs and a higher cost-benefit ratio, and existing advantages should be further explored and maintained; S3. If the hyperparameter TC < the optimization adjustment index TZ, it indicates that there is still significant room for improvement in time management and resource optimization. Analyze the reasons for this gap, including administrative inefficiency and unreasonable resource allocation, and take measures for improvement. S4. If the hyperparameter TC = the optimization adjustment index TZ, it indicates that the performance in time management and resource optimization is in a balanced state with potential efficiency and cost - effectiveness. Maintain the balance and look for minor optimization opportunities.

[0010] Optionally, the administrative efficiency index XZX of the comprehensive administrative efficiency evaluation unit directly affects the cost prediction index QCY output by the blockchain management cost prediction unit. Specifically, the higher the administrative efficiency, the lower the blockchain management cost. The cost prediction index QCY output by the blockchain management cost prediction unit affects the optimization adjustment index TZ through the time management and resource allocation optimization unit. If the cost prediction index QCY is high, reduce costs by optimizing time management and resource allocation, that is, increasing the use of efficient blockchain technologies. The output value of the optimization adjustment index TZ will affect the future adjusted new target processing efficiency TCnew and resource allocation strategy. These changes indirectly affect the office workload BF and the project delay rate XY, thereby affecting the administrative efficiency index XZX in the comprehensive administrative efficiency evaluation unit again, forming a closed - loop.

[0011] Optionally, the new target processing efficiency TC after any adjustment new is reset according to the analysis of the optimization adjustment index TZ output by the previous time management and resource allocation optimization unit. The reset needs to analyze the optimization adjustment index TZ and its change trend, understand the system's time management and resource optimization situation, and set a reasonable new target processing efficiency TC after adjustment according to business requirements, resource constraints, and cost - effectiveness factors. new 。

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: First, through the comprehensive administrative efficiency evaluation unit, the system can comprehensively consider multiple factors such as the project delay rate, email response delay rate, email processing efficiency, and total communication load, and then comprehensively and objectively evaluate administrative efficiency. This helps managers promptly discover and solve efficiency bottlenecks, improve overall work efficiency, and ensure the comprehensiveness and objectivity of administrative efficiency evaluation.

[0013] Second, the blockchain management cost prediction unit in the present invention provides a scientific basis for predicting blockchain management costs. By considering the administrative efficiency index XZX, the basic blockchain cost QJC base , the chain cost QT eth and the weight factor QTF eth, enabling the system to more accurately predict the economic feasibility of blockchain technology, providing support for decision-making, and thus ensuring the accuracy of blockchain management cost prediction.

[0014] III. The time management and resource allocation optimization unit in the present invention realizes the intelligence of time management and resource optimization by comprehensively considering factors such as administrative efficiency, total resources, used resources, target processing capacity, and blockchain management cost, enabling the system to dynamically adjust optimization strategies according to real-time data, reasonably allocate time and resources to maximize benefits, and thus achieve the intelligence of time management and resource optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is the method flow chart of the building equipment management system based on artificial intelligence; Figure 2 is the schematic diagram of the module structure included in the building equipment management system based on artificial intelligence; Figure 3 is the schematic diagram of the structure of the comprehensive evaluation prediction and optimization module of the present invention; Figure 4 is the schematic diagram of the closed loop of the cyclic influence of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Regarding the building equipment management system based on artificial intelligence, different from the existing building equipment management systems, the existing building equipment management systems do not have a data processing system specifically applicable to the fields of administration, commerce, finance, management, supervision, intelligence, and prediction, and there are still many problems and deficiencies in evaluating administrative efficiency, predicting blockchain management costs, and optimizing time management and resource allocation. However, the data processing system constructed by the present algorithm unit based on the comprehensive evaluation of the administrative efficiency unit, the blockchain management cost prediction unit, and the time management and resource allocation optimization unit has significant beneficial effects in the fields of administration, commerce, finance, management, supervision, intelligence, and prediction, can effectively solve the problems and deficiencies in the prior art, and achieve optimization and innovation.

[0018] Example 1, please refer to Figures 1 to 4 , this embodiment provides a building equipment management system based on artificial intelligence, a building equipment management system including a blockchain and involving an administrative data processing system; It includes a data acquisition module, a comprehensive evaluation and prediction module, an intelligent decision-making module, and a user interface module; The specific implementation steps are as follows: Collect data from building equipment and the office environment through the data acquisition module; Evaluate the administrative efficiency and the economic feasibility of blockchain technology through the comprehensive evaluation, prediction, and optimization module, and output the optimization adjustment index TZ. According to the optimization adjustment index TZ, adjust the resource allocation and time management strategies. The comprehensive evaluation, prediction, and optimization module includes a comprehensive administrative efficiency evaluation unit, a blockchain management cost prediction unit, and a time management and resource allocation optimization unit; Based on the respective result values output by the comprehensive administrative efficiency evaluation unit, the blockchain management cost prediction unit, and the time management and resource allocation optimization unit, formulate an optimization strategy through the intelligent decision-making module, convert the optimization strategy into specific operation instructions, monitor the system performance in real time, and optimize the strategy again according to the feedback adjustment; The user interface module provides a user-friendly interface, generates detailed reports, and allows users to set parameters and adjust strategies through the interface; The devices used in the data acquisition module include sensors, cameras, and RFID tags; The devices used in the comprehensive evaluation, prediction, and optimization module include servers and network devices; The devices used in the user interface module include workstations.

[0019] In this embodiment, the system, through the mutual cooperation of three algorithm units, combines the calculation results of XZX, QCY, and TZ. In the artificial intelligence-based construction equipment management system, they respectively undertake important calculation purposes of evaluating administrative efficiency, predicting blockchain management costs, and optimizing time management and resource allocation. These purposes together constitute the comprehensive support of the system for organizational operation management. XZX is the administrative efficiency index. As a quantitative indicator, it provides important decision-making support for managers in formulating management strategies and optimizing work processes, and comprehensively and objectively evaluates the administrative efficiency of the organization. QCY is the cost prediction index, which helps managers evaluate the economic feasibility of blockchain technology, so as to decide whether to introduce the technology and how to control costs. By predicting the future cost trend of blockchain management, it also provides an important reference for managers' long-term strategic planning. TZ is the optimization adjustment index. By optimizing resource allocation and time management, it can ensure that key tasks are given priority, reduce resource waste and waiting time, thereby improving the overall work efficiency. In a complex and changeable market environment, the intelligent adjustment function of the optimization adjustment index TZ helps the organization better cope with uncertain factors and ensure the maximization of benefits under limited resources. Moreover, the calculation result of TZ can also affect and feedback to the calculations of XZX and QCY, making the three algorithms of this system highly correlated and intertwined, enabling the overall algorithm system to perform automated feedback and optimization according to the actual situation to be closer to reality.

[0020] Please refer to Figures 1 to 4 , and the calculation formula for comprehensively evaluating the administrative efficiency unit is as follows: XZX = [YC × (BF / BB)] / [XY × (1 + YJB / BB)]; YC = (YCS × ZL) / (BS × BZL); XY = YM / ZXM; ; Where: XZX is the administrative efficiency index; YC is the email processing efficiency index; BF is the office workload, and BF reflects the total amount of current office tasks; BB is the target processing efficiency, and BB reflects the amount of tasks that can be processed daily and hourly as set; XY is the project delay rate; YJB is the email response delay index; YCS is the email processing speed, ZL is the processing accuracy rate, BS is the standard processing speed, and BZL is the standard processing accuracy rate; YM is the total number of delayed projects, and ZXM is the total project index; m is the total number of emails, SXi is the actual response time of the ith time, BX i is the i-th target response time.

[0021] In this embodiment: First, in this algorithm unit, YC is the email processing efficiency index. Based on the evaluation of email processing speed and accuracy, a higher email processing efficiency index YC result value indicates that the organization is highly efficient in email management, which helps to improve overall administrative efficiency. On the contrary, if the email processing efficiency index YC result value is low, it indicates that there is a bottleneck in email processing, resulting in a decrease in administrative efficiency. XY is the project delay rate, which indicates the proportion of projects that failed to be completed on time. A higher project delay rate XY reflects deficiencies in project management, including improper resource allocation, unreasonable time planning, or inefficient execution. This situation will significantly reduce administrative efficiency and affect the overall operational effect of the organization. YJB is the email response delay index, which is specifically the difference between the average email response time and the target response time. A higher email response delay index YJB indicates a slow email response speed, which will lead to poor communication and delayed decision-making, thereby affecting the progress of the project and administrative efficiency. Therefore, by reducing the email response delay index YJB, the email response speed can be improved, which helps to improve administrative efficiency. This algorithm unit comprehensively considers multiple factors such as project delay rate XY, email response delay index YJB, email processing efficiency index YC and office load BF, so that the comprehensive evaluation unit of administrative efficiency can comprehensively and objectively evaluate administrative efficiency. This evaluation method avoids the limitations of subjective judgment and single indicators in traditional methods, making the evaluation results more accurate and reliable; The calculation results of the administrative efficiency index XZX can help managers to timely identify bottleneck problems in administrative efficiency, including project delays and poor communication. By taking corresponding measures to address these problems, the overall work efficiency can be significantly improved and unnecessary waste of resources can be reduced. As a quantitative indicator, the administrative efficiency index XZX provides decision-making support for managers. In formulating management strategies and optimizing work processes, the administrative efficiency index XZX can serve as an important reference to help managers make more scientific and reasonable decisions.

[0022] See also Figures 1 to 4 ,The calculation formula of the blockchain management cost prediction unit is as follows: QCY=[(XZX+1) / 2]×(QJC base +QT eth ×QTF eth ); in: QCY is the cost prediction index; QUR baseFor the basic blockchain cost, including the expenses generated by node maintenance, network bandwidth, and data storage; QT eth For the chain cost, including the expenses generated by hardware, electricity, software, network, manpower, security, and exchanges; QTF eth Is the weight factor, QTF eth Specifically, it is the weight of the chain in the workload, indicating its relative importance among all blockchain technologies.

[0023] This algorithm unit constructs a scientific prediction model by introducing the administrative efficiency index XZX as one of the prediction factors and combining the basic blockchain cost QJC base , the chain cost QT eth and the weight factor QTF eth . This model can more accurately predict the economic feasibility of blockchain management and provide a reliable decision-making basis for managers; The prediction result of the cost prediction index QCY helps managers conduct a full economic evaluation before introducing blockchain technology. By comparing the cost-benefit ratios of different solutions, managers can select the optimal solution, effectively control cost expenditures, and avoid unnecessary economic losses; The prediction function of the cost prediction index QCY also supports managers in making long-term strategic plans. By predicting the future cost trends of blockchain management, managers can formulate corresponding development plans to ensure that the organization maintains a leading position in the highly competitive market environment.

[0024] Please refer to Figures 1 to 4 , the calculation formula of the time management and resource allocation optimization unit is as follows: TZ = [QZY × (1 - SG / TC new )] / [XZX × (1 + ZY used / ZY tottal )]; Where: TZ is the optimization adjustment index; SG is the actual management time, and SG reflects the time required for the current management task; TC new Is the new target processing efficiency after adjustment, and TC new Is specifically reset artificially according to the optimization adjustment index TZ; ZY used Is the number of resources already used; ZY tottal Is the total number of resources.

[0025] In this embodiment, this algorithm unit first based on the administrative efficiency index XZX and the cost prediction index QCY, considering the actual management time SG, the number of resources already used ZYused and the total number of resources ZY tottal and the adjusted new target processing efficiency TC new , a comprehensive evaluation outputs an optimization adjustment index TZ for adjusting time management and resource allocation according to blockchain management costs and administrative efficiency; In this algorithm unit, by comprehensively considering the administrative efficiency index XZX and the cost prediction index QCY, considering the actual management time SG, the number of used resources ZY used and the total number of resources ZY tottal and the adjusted new target processing efficiency TC new for multiple factors, the intelligence of time management and resource optimization is realized, enabling the system to dynamically adjust the optimization strategy according to real-time data, providing intelligent decision-making support for managers, The calculation result of the optimization adjustment index TZ helps managers reasonably allocate time and resources. By optimizing resource allocation, key tasks can be ensured to be prioritized, while avoiding resource waste and idleness. This optimization configuration method helps improve the overall work efficiency and benefits; In a complex and ever-changing market environment, the intelligent decision-making support function of the optimization adjustment index TZ helps managers better cope with uncertain factors. By adjusting the optimization strategy in real time, managers can flexibly respond to various challenges and changes, ensuring the smooth realization of organizational goals.

[0026] Please refer to Figures 1 to 4 , the adjustment steps based on the optimization adjustment index TZ output by the time management and resource allocation optimization unit are as follows: S1. Set a hyperparameter TC for reference evaluation of the optimization adjustment index TZ and reflecting the cost-benefit ratio. The specific calculation formula of the hyperparameter TC is as follows; TC = QCY × XZX / ZY tottal ; S2. If the hyperparameter TC > the optimization adjustment index TZ, it indicates that with a given amount of resources, higher administrative efficiency achieves lower management costs and a higher cost-benefit ratio, and existing advantages should be further explored and maintained; S3. If the hyperparameter TC < the optimization adjustment index TZ, it indicates that there is still much room for improvement in time management and resource optimization. The reasons for this gap, including low administrative efficiency and unreasonable resource allocation, should be analyzed and measures should be taken for improvement; S4. If the hyperparameter TC = the optimization adjustment index TZ, it indicates that the performance in time management and resource optimization is in a balanced state with potential efficiency and cost-benefit. The balance should be maintained and small optimization opportunities should be sought; The result administrative efficiency index XZX of the comprehensive administrative efficiency evaluation unit directly affects the cost prediction index QCY output by the blockchain management cost prediction unit. Specifically, the higher the administrative efficiency, the lower the blockchain management cost. The cost prediction index QCY output by the blockchain management cost prediction unit affects the optimization adjustment index TZ through the time management and resource allocation optimization unit. If the cost prediction index QCY is relatively high, by optimizing time management and resource allocation, that is, increasing the use of efficient blockchain technology to reduce costs, the output of the result value of the optimization adjustment index TZ will affect the future adjusted new target processing efficiency TC new And resource allocation strategies, these changes indirectly affect the office workload BF and the project delay rate XY, which in turn affect the administrative efficiency index XZX in the comprehensive administrative efficiency evaluation unit again, forming a closed loop.

[0027] In this embodiment, this algorithm unit is based on the evaluation and adjustment of the optimization adjustment index TZ to achieve the purpose of optimizing time management and resource allocation; Since the calculation of the optimization adjustment index TZ depends on the administrative efficiency index XZX, when the administrative efficiency index XZX increases, the optimization result of the optimization adjustment index TZ will be more significant, and resources and time can be allocated more effectively. This kind of optimization not only improves the current work efficiency, but also creates conditions for further improving the administrative efficiency index XZX by reducing resource waste and waiting time, thus forming a virtuous cycle. On the contrary, if the administrative efficiency index XZX decreases, the optimization strategy of the optimization adjustment index TZ will be adjusted accordingly, focusing on solving the problems that lead to the decrease of the administrative efficiency index XZX, such as increasing the resource input for key tasks and optimizing the communication process, in order to restore and improve the administrative efficiency index XZX; Through the intelligent decision-making support function, the optimization adjustment index TZ can dynamically adjust the optimization strategy based on the administrative efficiency index XZX and other factors. This kind of adjustment not only considers the current administrative efficiency state, but also predicts the possible future change trends, thus helping managers make more scientific and forward-looking decisions. This kind of forward-looking decision is helpful to prevent and solve potential administrative efficiency problems in advance, ensuring that the organization operates efficiently in the complex and changeable market environment; Through the optimized allocation of resources by the optimization adjustment index TZ, it is ensured that key tasks receive sufficient resource support while reducing the resource occupancy of non-key tasks. This kind of optimization not only improves the resource utilization efficiency, but also promotes the improvement of the overall work efficiency. The improvement of the administrative efficiency index XZX further strengthens this optimization effect, because high administrative efficiency means less time waste and resource idleness, thus creating more value for the organization; In a rapidly changing market environment, organizations need to be highly adaptable and competitive to succeed. The optimization adjustment index TZ helps organizations quickly adapt to changes in the external environment by adjusting optimization strategies in real time to cope with changes in the administrative efficiency index XZX. At the same time, the improvement of the administrative efficiency index XZX also enhances the internal operation efficiency and management level of the organization, providing strong support for the organization to stand out in the competition.

[0028] In summary, in the specific implementation process, the cyclic influence of the time management and resource allocation optimization unit on the comprehensive evaluation of the administrative efficiency unit not only promotes the continuous improvement of administrative efficiency and the optimization of resource utilization efficiency, but also enhances the scientificity and forward-looking of decision-making, as well as the adaptability and competitiveness of the organization. This cyclic influence mechanism is an indispensable important part of the construction equipment management system based on artificial intelligence.

[0029] Example 2, please refer to Figures 1 to 4 , the new target processing efficiency TC after any adjustment new is reset according to the analysis of the optimization adjustment index TZ output by the time management and resource allocation optimization unit in the previous time. The resetting requires analyzing the optimization adjustment index TZ and its change trend to understand the time management and resource optimization of the system, and setting a reasonable new target processing efficiency TC after adjustment according to business requirements, resource limitations, and cost-benefit factors. new .

[0030] In this embodiment, the new target processing efficiency TC after adjustment new is the new target processing capacity adjusted according to the optimization adjustment index TZ. It does not directly come from the result of the previous optimization adjustment index TZ, but is a more reasonable or optimized target processing capacity value reset by the system or administrator according to the time management and resource optimization situation reflected by the optimization adjustment index TZ.

[0031] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence-based construction equipment management system, characterized in that A construction equipment management system that includes a blockchain and involves an administrative data processing system; The specific implementation steps are as follows: Use the data collection module to collect data from construction equipment and the office environment; Use the comprehensive evaluation, prediction and optimization module to evaluate the administrative efficiency and the economic feasibility of blockchain technology, and output an optimization adjustment index TZ, and adjust the resource allocation and time management strategy according to the optimization adjustment index TZ; The comprehensive evaluation, prediction and optimization module includes a comprehensive administrative efficiency evaluation unit, a blockchain management cost prediction unit, and a time management and resource allocation optimization unit; Based on the respective result values output by the comprehensive administrative efficiency evaluation unit, the blockchain management cost prediction unit, and the time management and resource allocation optimization unit, formulate an optimization strategy through the intelligent decision-making module, convert the optimization strategy into specific operation instructions, monitor the system performance in real time, and re-optimize the strategy according to the feedback adjustment; Use the user interface module to provide a user-friendly interface, generate a detailed report, and allow users to set parameters and adjust strategies through the interface.

2. An artificial intelligence-based construction equipment management system according to claim 1, wherein: The devices used in the data collection module include sensors, cameras, and RFID tags; The devices used in the comprehensive evaluation, prediction and optimization module include servers and network devices; The devices used in the user interface module include workstations.

3. The building equipment management system based on artificial intelligence according to claim 2, characterized in that: The calculation formula of the comprehensive administrative efficiency evaluation unit is as follows: XZX = [YC × (BF / BB)] / [XY × (1 + YJB / BB)]; YC = (YCS × ZL) / (BS × BZL); XY = YM / ZXM; ； Where: XZX is the administrative efficiency index; YC is the email processing efficiency index; BF is the office workload, and BF reflects the total amount of current office tasks; BB is the target processing efficiency, and BB reflects the amount of tasks that can be processed daily and hourly as set; XY is the project delay rate; YJB is the email response delay index, and YJB reflects the difference between the average email response time and the target response time; YCS is the email processing speed, ZL is the processing accuracy rate, BS is the standard processing speed, and BZL is the standard processing accuracy rate; YM is the total number of delayed projects, and ZXM is the total project index; m is the total number of emails, SX i is the actual response time for the i-th time, BX i is the target response time for the i-th time.

4. An artificial intelligence-based construction equipment management system according to claim 3, characterized in that: The calculation formula of the blockchain management cost prediction unit is as follows: QCY = [(XZX + 1) / 2]×(QJC base + QT eth × QTF eth ); Where: QCY is the cost prediction index; QJC base As the basic blockchain cost, including the expenses generated by node maintenance, network bandwidth, and data storage; QT eth is the chain cost, including the expenses generated by hardware, electricity, software, network, human resources, security and exchanges; QTF eth is a weight factor, QTF eth Specifically, it is the weight of the chain in the workload, indicating its relative importance among all blockchain technologies.

5. An artificial intelligence-based construction equipment management system according to claim 4, characterized in that: The calculation formula of the time management and resource allocation optimization unit is as follows: TZ = [QZY × (1 - SG / TC new )] / [XZX × (1 + ZY used / ZY tottal )]; Where: TZ is the optimization adjustment index; SG is the actual management time, and SG reflects the time required for the current management task; TC new For the new target processing efficiency after adjustment, TC new It is specifically reset manually according to the optimization adjustment index TZ; ZY used is the number of used resources; ZY tottal is the total number of resources.

6. The building equipment management system based on artificial intelligence according to claim 5, characterized in that: The adjustment steps based on the optimization adjustment index TZ output by the time management and resource allocation optimization unit are as follows: S1. Set a hyperparameter TC for reference evaluation of the optimization adjustment index TZ and reflecting the cost-benefit ratio. The specific calculation formula of the hyperparameter TC is as follows; TC = QCY×XZX / ZY tottal ; S2. If the hyperparameter TC > the optimization adjustment index TZ, it indicates that under the given resource volume, the administrative efficiency is high, the management cost is low, and the cost-benefit is high, and the existing advantages should be maintained; S3. If the hyperparameter TC < the optimization adjustment index TZ, it indicates that there is still room for improvement in time management and resource optimization. The reasons for this gap should be analyzed, including administrative inefficiency and unreasonable resource allocation, and corresponding measures should be taken; S4. If the hyperparameter TC = the optimization adjustment index TZ, it indicates that the performance in time management and resource optimization is in a balanced state with potential efficiency and cost - effectiveness, and the balance should be maintained.

7. An artificial intelligence-based building equipment management system according to claim 6, characterized in that: The administrative efficiency index XZX of the result of the comprehensive administrative efficiency evaluation unit directly affects the cost prediction index QCY output by the blockchain management cost prediction unit. Specifically, the higher the administrative efficiency, the lower the blockchain management cost; The cost prediction index QCY output by the blockchain management cost prediction unit affects the optimization adjustment index TZ through the time management and resource allocation optimization unit. If the cost prediction index QCY is high, the cost can be reduced by optimizing time management and resource allocation, that is, increasing the use of efficient blockchain technologies; The output of the optimized adjustment index TZ result value will affect the future processing efficiency TC of the adjusted new target new and the resource allocation strategy. These changes affect the office workload BF and the project delay rate XY, and in turn affect the administrative efficiency index XZX in the comprehensive evaluation of administrative efficiency unit, forming a closed loop.

8. An artificial intelligence-based construction equipment management system according to claim 7, characterized in that: The new target processing efficiency TC after any adjustment new It is reset according to the optimization adjustment index TZ output by analyzing the previous time management and resource allocation optimization unit. The reset requires analyzing the optimization adjustment index TZ and its change trend to understand the system's time management and resource optimization situation, and setting a reasonable new target processing efficiency TC after adjustment based on business requirements, resource limitations, and cost-benefit factors new .

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