Construction management system and method based on artificial intelligence

Abstract

The invention relates to the technical field of urban intelligent management, and discloses a construction management system and method based on artificial intelligence, and the system comprises a data collection module which is used for collecting the data of urban environment, traffic and citizen behaviors, and a classification module which is used for carrying out the disturbance removal data processing of the data and classifying the collected data. The city monitoring module is used for monitoring city public information data in real time, analyzing the monitored city public information data and optimizing resource configuration, and the evaluation and response module is used for monitoring city public safety hidden dangers and risks in real time and responding and coordinating emergencies. The safety module is used for protecting the safety of urban public information data, and the feedback module is used for receiving urban public information potential safety hazards and citizen feedback and further carrying out optimization and model training parameter adjustment on the urban monitoring module, so that intelligent management of civilized urban construction is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of urban intelligent management, and discloses a construction management system and method based on artificial intelligence. Background Art

[0002] With the development of intelligent systems, they have an important position in industry, medical care, aviation and urban construction. For this reason, management systems based on artificial intelligence have become an important direction of intelligent management. Among them, the civilized city creation management system plays an important role in promoting urban civilization construction. With the improvement of people's living standards, urban management and civilized city creation are also in urgent need of deployment. At present, there are some shortcomings in the creation of civilized cities. For example, the civilized city creation management system requires a large amount of data support, including citizen behavior data, environmental monitoring data, etc. However, sometimes the data acquisition is not comprehensive and timely, or the degree of integration and utilization between data is not high enough, resulting in the depth and accuracy of system analysis being limited. This is why the urban management system needs to optimize the algorithm and predict the public data in the city. At the same time, the supervision and evaluation mechanism of the civilized city creation management system is not sound, which may lead to inaccurate work performance evaluation, inadequate supervision, and inability to timely discover problems and improvement measures. Therefore, while monitoring and predicting urban public data, the evaluation and feedback unit needs to feedback the monitored and predicted data to optimize the urban management system.

[0003] For example, the existing patent with the publication number CN117974075A, which is related to the field of data processing, especially a smart city public information management system based on big data. By establishing a target DFTGCN smart city public information identification model; obtaining real-time public information data in the city server, inputting the real-time public information data into the standard DFTGCN smart city public information identification model for identification, and obtaining the city public status data; judging whether the public transportation status of the smart city is in a congested state based on the city public status data, if it is judged to be in a congested state, the public transportation status is input into the public broadcasting system, the public media communication system and the traffic bureau command system. Real-time monitoring and prediction of traffic flow in smart cities can be achieved, providing strong support for traffic planning and scheduling. Through in-depth mining and analysis of traffic data, the bottlenecks and causes of traffic congestion can be found, and corresponding optimization measures and solutions can be formulated.

[0004] The above patent uses public status data to judge the safety of public transportation in a city, and transmitting traffic status information to the public broadcasting system, public media communication system and traffic bureau command system requires efficient system integration and fast response speed. If the system integration is not perfect or the response speed is too slow, it may affect the effectiveness of timely traffic management measures; the effectiveness of the system is highly dependent on the accuracy and real-time nature of the real-time public information data obtained. If there is a delay in the data source or the data quality is poor, it may cause the accuracy of traffic status identification to decrease, affecting the effectiveness of traffic management. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In order to solve the above technical problems, the main purpose of the present invention is to provide a construction management system based on artificial intelligence, comprising:

[0007] A data collection module, used to collect urban data, including urban environment data, traffic data and citizen behavior data;

[0008] A classification module, the classification module includes a data processing unit and a data classification unit, the data processing unit is used to perform disturbance removal data processing on the urban data, and the data classification unit is used to classify the collected urban data;

[0009] A monitoring module, the monitoring module includes a data monitoring unit and a city optimization unit, the data monitoring unit is used to monitor the city public information data in real time, and the city optimization unit is used to analyze the monitored city public information data and optimize resource allocation;

[0010] An analysis module, the analysis module includes a risk assessment model and an emergency response unit, the risk assessment model is used to monitor urban public safety hazards and risks in real time, and the emergency response unit is used to quickly respond to and coordinate emergencies;

[0011] Security module, used to protect the security of urban public information data;

[0012] The feedback module is used to receive urban public information security risks and citizen feedback, and then tune the urban monitoring module and adjust the parameters of model training.

[0013] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0014] The urban environmental data includes real-time monitoring of environmental parameters and uploading the data to the system;

[0015] The traffic data includes real-time monitoring of vehicle flow, vehicle speed, and traffic congestion, and extracting vehicle driving status and traffic event information through image recognition technology;

[0016] The citizen behavior data collects citizen behaviors and demands through video surveillance.

[0017] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0018] The data processing unit is used to remove noise and outliers from the urban data, and clean the processed urban data. The urban data cleaning includes deduplication, missing value completion and data format unification operations, integrating urban data from different data sources, building an urban data set, extracting and converting features of different types of urban data, and converting raw data into feature representations for analysis. The feature representation includes feature extraction of time series data and feature conversion of image data. After the feature conversion, high-dimensional data is reduced in dimension and compressed.

[0019] The data classification unit classifies and labels the data through time series data classification and intelligent monitoring algorithms.

[0020] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0021] The data monitoring unit includes urban environment monitoring, traffic monitoring and citizen behavior monitoring;

[0022] Receiving the urban environment data processed by the data processing unit and the data classification unit as monitoring data basis and inputting it into the urban environment monitoring model, outputting regional real-time data through the urban environment monitoring model, and then optimizing the urban environment through the urban optimization unit, performing correlation analysis on urban environment monitoring, traffic monitoring and citizen behavior monitoring by setting correlation functions, and finally analyzing the urban environment monitoring model;

[0023] The calculation expression of the urban environment monitoring model is as follows:

[0024]

[0025] Among them, F(x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, ω i is the characteristic value of the environmental parameter of the i-th area of ​​the city, x i is the real-time environmental data of area i in the city, Δγ irepresents the environmental error of the i-th area of ​​the city, f(x) is the urban environmental optimization function, i is 1, 2, 3, ..., n, and n is any positive integer;

[0026] The urban traffic monitoring model consists of a traffic data time series matrix of j streets in region i, and then monitors the street traffic in the city. The calculation expression of the urban traffic monitoring model is as follows:

[0027]

[0028] Among them, G(s) is the street traffic situation in the output area of ​​the traffic monitoring model, s 11 (t) is the traffic data of the first street in urban area 1 at time t, s ij (t) is the traffic data of the jth street in the i-th area of ​​the city at time t, and g(s) is the traffic optimization function;

[0029] The citizen monitoring model monitors citizen attributes, citizen behaviors, and citizen possessions. Citizens are monitored by establishing a citizen attribute set. The calculation expression of the citizen monitoring model is as follows:

[0030] H(z)={z1,z2,z3,...,z t}

[0031] Among them, H(z) is the real-time data of citizen behavior monitoring, z1 is the citizen behavior data at the first moment, z2 is the citizen behavior data at the second moment, z3 is the citizen behavior data at the third moment, and z t is the citizen behavior data at time t;

[0032] Citizen behavior data includes citizen attributes, citizen behavior, and citizen possessions. The calculation expression is as follows:

[0033] z n ={a,b,c,...,λ}

[0034] Among them, z n To retrieve the behavior data of citizens, a is the citizen's gender data, b is the citizen's posture data, c is the citizen's holdings data, and λ is the citizen's other characteristic data.

[0035] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0036] The city optimization unit includes an urban environment optimization function and a traffic optimization function;

[0037] The calculation expression of the urban environment optimization function is as follows:

[0038]

[0039] Among them, f(x) is the urban environment optimization function, F c (x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, F′(x) is the predicted value of urban environmental monitoring, n is an arbitrary positive integer, and c is 1, 2, 3, ······, n;

[0040] By minimizing the urban environment optimization function, the optimal result of environmental adjustment can be obtained;

[0041] receiving the traffic data processed by the data processing unit and the data classification unit as monitoring data basis and inputting it into the urban traffic monitoring model, and optimizing the traffic monitoring model through the traffic optimization function;

[0042] The traffic optimization function, the calculation expression is as follows:

[0043]

[0044] Among them, g(s) represents the traffic optimization function, is the traffic optimization gradient value, To find the sign of the partial derivative, E is the loss value between the traffic prediction value and the actual value.

[0045] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0046] The risk assessment model evaluates urban risks by inputting real-time data on urban environment, traffic and citizen behavior and integrating real-time monitoring data, establishing a risk indicator system, and identifying potential safety risks and problems in the city through forecasting data. It also sets up citizen feedback channels and establishes data sets as reference data to input into the risk assessment model;

[0047] The emergency response unit combines the output results of the risk assessment model and provides intelligent decision support through networking to help decision makers make emergency response decisions based on real-time situations.

[0048] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0049] The security module includes data transmission encryption, data storage encryption, data access encryption and identity authentication and authorization;

[0050] The data transmission encryption uses a secure transmission protocol to encrypt data during transmission;

[0051] The data storage encryption encrypts sensitive data stored in a database or file system;

[0052] The data access encryption establishes an access control mechanism to limit access rights to data, allowing only authorized users or systems to access sensitive data;

[0053] The identity authentication and authorization use an identity authentication mechanism.

[0054] As a preferred solution of the construction management system based on artificial intelligence of the present invention, wherein:

[0055] The feedback module includes a traffic optimization function, an urban environment optimization function and a citizen feedback channel;

[0056] By establishing correlation functions, we conduct correlation analysis on traffic, environment and citizen feedback, and then complete intelligent management of the city.

[0057] As a preferred solution of the construction management method based on artificial intelligence of the present invention, wherein:

[0058] S1. Collect data on urban environment, traffic and citizen behavior, and pre-process the collected data;

[0059] S2. Use the pre-processed data of urban environment, traffic and citizen behavior as the basic data for model establishment and training, and then realize the monitoring of the environment, traffic and citizen behavior in multiple regions and time series of the city;

[0060] S3. By fitting the minimum loss value between the predicted value and the actual value, the environment and traffic data are optimized, and the citizen behavior data are retrieved and monitored by establishing a data set of citizen attributes, citizen behavior, and citizen possessions;

[0061] S4, the risk assessment model receives data from real-time monitoring of the urban environment, traffic, and citizen behavior to make risk assessments;

[0062] S5. If risks occur or are predicted to occur, early warning of the risks will be provided through online emergency response decisions and the best decision to resolve the risks will be provided as a reference;

[0063] S6. Complete the monitoring of multi-dimensional urban data and build a civilized city.

[0064] Beneficial effects of the present invention:

[0065] The present invention provides scientific decision-making support for city managers by setting up a monitoring module to analyze big data in real time, including urban environmental data, citizen behavior data, etc. Through data-driven decision-making, the city's operating status can be more accurately understood, and civilized city construction plans and measures can be formulated in a targeted manner;

[0066] The present invention can monitor the city's operating status in real time through data prediction and issue early warning information in a timely manner. The intelligent monitoring system monitors the city's environment, traffic conditions, etc. Once an abnormal situation is found, the system can immediately issue an early warning to remind relevant departments to take timely measures, thereby reducing the possibility of accidents.

[0067] The present invention realizes the rational utilization and conservation of resources by setting up a feedback module to intelligently analyze and optimize the configuration of urban resources. For example, the intelligent traffic management system optimizes the timing of traffic signals to reduce traffic congestion and energy consumption; the intelligent environmental monitoring system optimizes the use of public facilities to reduce energy consumption and environmental pollution, thereby realizing efficient utilization of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0069] Figure 1 This is a system composition diagram of a construction management system based on artificial intelligence of the present invention;

[0070] Figure 2 This is a flow chart of a construction management method based on artificial intelligence of the present invention;

[0071] Figure 3 The present invention is a data simulation bar graph of the construction management system based on artificial intelligence before and after optimization of urban environment and traffic. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Embodiment 1:

[0076] like Figure 1 As shown, a construction management system based on artificial intelligence includes:

[0077] A data collection module, used to collect urban data, including urban environment data, traffic data and citizen behavior data;

[0078] Among them, urban environmental data includes air quality monitors, noise monitors and other sensors deployed at various locations in the city to monitor environmental parameters such as air quality and noise levels in real time and upload the data to the system;

[0079] Traffic data includes installing surveillance cameras on major roads and key sections to monitor vehicle flow, speed, traffic congestion, etc. in real time, and extracting vehicle driving status and traffic event information through image recognition technology;

[0080] Citizen behavior data collects citizen behaviors and needs through video surveillance, such as movement trajectories, activity preferences, etc., to provide data support for personalized services;

[0081] It also includes data access from the Transportation Bureau, Environmental Protection Bureau, Urban Management Bureau and other departments, and collects other official data in the city;

[0082] A classification module, including a data processing unit for performing data processing to remove disturbances from urban data, and a data classification unit for classifying the collected urban data;

[0083] Among them, the data processing unit is used to remove noise and outliers from the collected data on urban environment, traffic and citizen behavior to ensure the accuracy and reliability of the data, and then clean the processed data on urban environment, traffic and citizen behavior, including deduplication, missing value completion, data format unification and other operations. At the same time, data from different data sources are integrated to build a complete data set. Finally, feature extraction and feature conversion are performed on different types of data to convert the original data into feature representations that can be used for subsequent analysis, including feature extraction of time series data and feature conversion of image data. After feature conversion, large-scale high-dimensional data is reduced in dimensionality and compressed to reduce storage space and computational complexity while maintaining the main information of the data.

[0084] Furthermore, the data classification unit classifies and labels data through time series data classification and intelligent monitoring algorithms, which can help the system transform large amounts of raw data into useful information and knowledge, providing support for intelligent decision-making and applications.

[0085] The monitoring module includes a data monitoring unit for real-time monitoring of urban public information data and an urban optimization unit for analyzing the monitored urban public information data and optimizing resource allocation;

[0086] Among them, the data monitoring units include urban environment monitoring, traffic monitoring and citizen behavior monitoring;

[0087] The urban optimization unit includes urban environment optimization function and traffic optimization function;

[0088] The urban environment data processed by the data processing unit and the data classification unit are received as monitoring data basis and input into the urban environment monitoring model, and the regional real-time data is output through the urban environment monitoring model, and then the urban environment is optimized through the urban optimization analysis unit. At the same time, since the urban system is a complex relationship network, the urban environment monitoring, traffic monitoring and citizen behavior monitoring are correlated and analyzed by setting the correlation function, and finally the urban environment monitoring model is analyzed;

[0089] Urban environment monitoring model, the calculation expression is as follows:

[0090]

[0091] Among them, F(x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, ω i is the characteristic value of the environmental parameter of the i-th area of ​​the city, x i is the real-time environmental data of area i in the city, △γ i represents the environmental error of the i-th area of ​​the city, f(x) is the urban environmental optimization function, i is 1, 2, 3, ..., n, and n is any positive integer;

[0092] By dividing the city into multiple areas, environmental data of multiple areas are monitored and summarized to complete environmental monitoring of the entire city;

[0093] Urban environment optimization function, the calculation expression is as follows:

[0094]

[0095] Among them, f(x) is the urban environment optimization function, F c (x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, F′(x) is the predicted value of urban environmental monitoring, n is an arbitrary positive integer, and c is 1, 2, 3, ..., n;

[0096] By minimizing the urban environment optimization function, the optimal result of environmental adjustment can be obtained;

[0097] like Figure 3 The figure shows the comparison of good environment rate before and after the optimization of urban environment;

[0098] Receiving the traffic data processed by the data processing unit and the data classification unit as the monitoring data basis and inputting it into the urban traffic monitoring model, and optimizing the traffic monitoring model through the traffic optimization function;

[0099] The urban traffic monitoring model consists of a traffic data time series matrix of j streets in region i, and then monitors the traffic on each street in the city. The calculation expression of the urban traffic monitoring model is as follows:

[0100]

[0101] Among them, G(s) is the street traffic situation in the output area of ​​the traffic monitoring model, s 11 (t) is the traffic data of the first street in urban area 1 at time t, s ij (t) is the traffic data of the jth street in the i-th area of ​​the city at time t, and g(s) is the traffic optimization function;

[0102] Traffic optimization function, the calculation expression is as follows:

[0103]

[0104] Among them, g(s) represents the traffic optimization function, is the traffic optimization gradient value, To find the sign of partial derivative, E is the loss value between traffic prediction value and actual value;

[0105] The traffic optimization function optimizes traffic by calculating the gradient of traffic conditions, providing a way to calculate the partial derivative of the loss value between the traffic prediction value and the actual value by calculating the real-time traffic conditions, and then calculate the traffic gradient to optimize traffic.

[0106] like Figure 3 As shown, the traffic quality rate is compared before and after the optimization of urban traffic;

[0107] The citizen monitoring model monitors citizen attributes, citizen behaviors, and citizen possessions. Citizens are monitored by establishing a citizen attribute set. The calculation expression of the citizen monitoring model is as follows:

[0108] H(z)={z1,z2,z3,...,z t}

[0109] Among them, H(z) is the real-time data of citizen behavior monitoring, z1 is the citizen behavior data at the first moment, z2 is the citizen behavior data at the second moment, z3 is the citizen behavior data at the third moment, and z t is the citizen behavior data at time t;

[0110] Citizen behavior data includes citizen attributes, citizen behavior, and citizen possessions. The calculation expression is as follows:

[0111] z n ={a,b,c,...,λ}

[0112] Among them, z n To retrieve the behavior data of citizens, a is the citizen's gender data, b is the citizen's posture data, c is the citizen's holdings data, and λ is the citizen's other characteristic data;

[0113] An analysis module, including a risk assessment model for real-time monitoring of urban public safety hazards and risks, and an emergency response unit for rapid response and coordination to emergencies;

[0114] The risk assessment model integrates the real-time monitoring data by inputting the urban environment, traffic and citizen behavior data, and assesses the urban risks by establishing a risk indicator system. It also identifies the potential safety risks and problems in the city through forecasting data, sets up citizen feedback channels and establishes data sets as reference data. The input refers to the risk assessment model to ensure that the risk assessment model is scientific and in line with the daily living habits of citizens.

[0115] The emergency response unit combines the output of the risk assessment model and provides intelligent decision support through networking to help decision makers make emergency response decisions based on real-time conditions;

[0116] The analysis module can effectively monitor urban public safety hazards and risks, quickly respond to and coordinate emergencies, and effectively enhance the emergency response capabilities of urban management and the level of public safety protection.

[0117] Security module, used to protect the security of urban public information data;

[0118] The security module includes data transmission encryption, data storage encryption, data access encryption, and identity authentication and authorization;

[0119] Transmission encryption uses secure transmission protocols (such as TLS / SSL) to encrypt data during transmission to prevent data from being stolen or tampered with during transmission;

[0120] Storage encryption encrypts sensitive data stored in the database or file system to ensure that even if the database or file system is illegally accessed, the plaintext data cannot be directly obtained;

[0121] Access control Establish a strict access control mechanism to limit access rights to data and only allow authorized users or systems to access sensitive data;

[0122] Authentication and Authorization Use a strong authentication mechanism to ensure that only legitimate users or systems can access sensitive data, and perform permission control based on the role of the user or system.

[0123] Feedback module, used to receive urban public information security risks and citizen feedback, and then optimize the urban monitoring module and adjust the parameters of model training;

[0124] The feedback module includes traffic optimization function, urban environment optimization function and citizen feedback channel;

[0125] By establishing correlation functions, we conduct correlation analysis on traffic, environment and citizen feedback, and then complete intelligent management of the city.

[0126] Embodiment 2:

[0127] like Figure 2 As shown, a construction management method based on artificial intelligence includes:

[0128] S1. Collect data on urban environment, traffic and citizen behavior, and pre-process the collected data;

[0129] S2. Use the pre-processed data of urban environment, traffic and citizen behavior as the basic data for model establishment and training, and then realize the monitoring of the environment, traffic and citizen behavior in multiple regions and time series of the city;

[0130] S3. By fitting the minimum loss value between the predicted value and the actual value, the environment and traffic data are optimized, and the citizen behavior data are retrieved and monitored by establishing a data set of citizen attributes, citizen behavior, and citizen possessions;

[0131] S4, the risk assessment model receives data from real-time monitoring of the urban environment, traffic, and citizen behavior to make risk assessments;

[0132] S5. If risks occur or are predicted to occur, early warning of the risks will be provided through online emergency response decisions and the best decision to resolve the risks will be provided as a reference;

[0133] S6. Complete the monitoring of multi-dimensional urban data and build a civilized city.

[0134] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only two embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible, for example, the size, scale, structure, shape and ratio of various elements, and parameter values ​​(e.g., temperature, pressure, etc.), installation arrangement, use of materials, color, directional changes, etc., without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method step can be changed or reordered according to an alternative embodiment. Any "device plus function" clause is intended to cover the structure of the execution function described in this article, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiment. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0135] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0136] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0137] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A construction management system based on artificial intelligence, Features: include: A data collection module, used to collect urban data, including urban environment data, traffic data and citizen behavior data; A classification module, the classification module includes a data processing unit and a data classification unit, the data processing unit is used to perform disturbance removal data processing on the urban data, and the data classification unit is used to classify the collected urban data; A monitoring module, the monitoring module includes a data monitoring unit and a city optimization unit, the data monitoring unit is used to monitor the city public information data in real time, and the city optimization unit is used to analyze the monitored city public information data and optimize resource allocation; An analysis module, the analysis module includes a risk assessment model and an emergency response unit, the risk assessment model is used to monitor urban public safety hazards and risks in real time, and the emergency response unit is used to quickly respond to and coordinate emergencies; Security module, used to protect the security of urban public information data; The feedback module is used to receive urban public information security risks and citizen feedback, and then tune the urban monitoring module and adjust the parameters of model training.

2. According to claim 1, a construction management system based on artificial intelligence, Features: The urban environmental data includes real-time monitoring of environmental parameters and uploading the data to the system; The traffic data includes real-time monitoring of vehicle flow, vehicle speed, and traffic congestion, and extracting vehicle driving status and traffic event information through image recognition technology; The citizen behavior data collects citizen behaviors and demands through video surveillance.

3. According to claim 2, a construction management system based on artificial intelligence, Features: The data processing unit is used to remove noise and outliers from the urban data, and clean the processed urban data. The urban data cleaning includes deduplication, missing value completion and data format unification operations, integrating urban data from different data sources, building an urban data set, extracting and converting features of different types of urban data, and converting raw data into feature representations for analysis. The feature representation includes feature extraction of time series data and feature conversion of image data. After the feature conversion, high-dimensional data is reduced in dimension and compressed. The data classification unit classifies and labels the data through time series data classification and intelligent monitoring algorithms.

4. According to claim 3, a construction management system based on artificial intelligence, Features: The data monitoring unit includes urban environment monitoring, traffic monitoring and citizen behavior monitoring; Receiving the urban environment data processed by the data processing unit and the data classification unit as monitoring data basis and inputting it into the urban environment monitoring model, outputting regional real-time data through the urban environment monitoring model, and then optimizing the urban environment through the urban optimization unit, performing correlation analysis on urban environment monitoring, traffic monitoring and citizen behavior monitoring by setting correlation functions, and finally analyzing the urban environment monitoring model; The calculation expression of the urban environment monitoring model is as follows: Among them, F(x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, ω i is the characteristic value of the environmental parameters of the i-th area of ​​the city, x i is the real-time environmental data of area i in the city, △γ i represents the environmental error of the i-th area of ​​the city, f(x) is the urban environmental optimization function, i is 1, 2, 3, ..., n, and n is any positive integer; The urban traffic monitoring model consists of a traffic data time series matrix of j streets in region i, and then monitors the street traffic in the city. The calculation expression of the urban traffic monitoring model is as follows: Among them, G(s) is the street traffic situation in the output area of ​​the traffic monitoring model, s 11 (t) is the traffic data of the first street in urban area 1 at time t, s ij (t) is the traffic data of the jth street in the i-th area of ​​the city at time t, and g(s) is the traffic optimization function; The citizen monitoring model monitors citizen attributes, citizen behaviors, and citizen possessions. Citizens are monitored by establishing a citizen attribute set. The calculation expression of the citizen monitoring model is as follows: H(z)={z 1 ,With 2 ,With 3 ,...,With t } Among them, H(z) is the real-time data of citizen behavior monitoring, z 1 is the citizen behavior data at the first moment, z 2 is the citizen behavior data at the second moment, z 3 is the citizen behavior data at the third moment, z t is the citizen behavior data at time t; Citizen behavior data includes citizen attributes, citizen behavior, and citizen possessions. The calculation expression is as follows: z n ={a,b,c,...,λ} Among them, z n To retrieve the behavior data of citizens, a is the citizen's gender data, b is the citizen's posture data, c is the citizen's holdings data, and λ is the citizen's other characteristic data.

5. According to claim 4, a construction management system based on artificial intelligence, Features: The city optimization unit includes an urban environment optimization function and a traffic optimization function; The calculation expression of the urban environment optimization function is as follows: Among them, f(x) is the urban environment optimization function, F c (x) is the real-time monitoring urban area environmental data output by the urban environmental monitoring model, F′(x) is the predicted value of urban environmental monitoring, n is an arbitrary positive integer, and c is 1, 2, 3, ······, n; By minimizing the urban environment optimization function, the optimal result of environmental adjustment can be obtained; receiving the traffic data processed by the data processing unit and the data classification unit as monitoring data basis and inputting it into the urban traffic monitoring model, and optimizing the traffic monitoring model through the traffic optimization function; The traffic optimization function, the calculation expression is as follows: Among them, g(s) represents the traffic optimization function, is the traffic optimization gradient value, To find the sign of the partial derivative, E is the loss value between the traffic prediction value and the actual value.

6. According to claim 5, a construction management system based on artificial intelligence, Features: The risk assessment model evaluates urban risks by inputting real-time data on urban environment, traffic and citizen behavior and integrating real-time monitoring data, establishing a risk indicator system, and identifying potential safety risks and problems in the city through forecasting data. It also sets up citizen feedback channels and establishes data sets as reference data to input into the risk assessment model; The emergency response unit combines the output results of the risk assessment model and provides intelligent decision support through networking to help decision makers make emergency response decisions based on real-time situations.

7. According to claim 6, a construction management system based on artificial intelligence, Features: The security module includes data transmission encryption, data storage encryption, data access encryption and identity authentication and authorization; The data transmission encryption uses a secure transmission protocol to encrypt data during transmission; The data storage encryption encrypts sensitive data stored in a database or file system; The data access encryption establishes an access control mechanism to limit access rights to data, allowing only authorized users or systems to access sensitive data; The identity authentication and authorization use an identity authentication mechanism.

8. According to the artificial intelligence-based construction management system of claim 7, Features: The feedback module includes a traffic optimization function, an urban environment optimization function and a citizen feedback channel; By establishing correlation functions, we conduct correlation analysis on traffic, environment and citizen feedback, and then complete intelligent urban management.

9. A construction management method based on artificial intelligence, based on a construction management system based on artificial intelligence as claimed in any one of claims 1 to 8, Features: include, S1. Collect data on urban environment, traffic and citizen behavior, and pre-process the collected data; S2. Use the pre-processed data of urban environment, traffic and citizen behavior as the basic data for model establishment and training, and then realize the monitoring of the environment, traffic and citizen behavior in multiple regions and time series of the city; S3. By fitting the minimum loss value between the predicted value and the actual value, the environment and traffic data are optimized, and the citizen behavior data are retrieved and monitored by establishing a data set of citizen attributes, citizen behavior, and citizen possessions; S4, the risk assessment model receives data from real-time monitoring of the urban environment, traffic, and citizen behavior to make risk assessments; S5. If risks occur or are predicted to occur, early warning of the risks will be provided through online emergency response decisions and the best decision to resolve the risks will be provided as a reference; S6. Complete the monitoring of multi-dimensional urban data and build a civilized city.

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