Constructional engineering management system based on real-time recording technology

Abstract

The invention relates to a building engineering management system based on a real-time recording technology. The building engineering management system mainly comprises a data acquisition module, a local processing module, a local storage module, a data transmission module and a cloud server module. According to the system, monitoring data are collected in real time on a construction engineering site through the data collection module, and after standardization processing and key data extraction are carried out through the local processing module, the monitoring data are stored in a monitoring database constructed by the local storage module. The key monitoring data is wirelessly transmitted to the cloud server module through the data transmission module, intelligent analysis is carried out, and abnormal and predictive analysis results are generated and visually displayed in a dynamic report form. The system has an efficient data processing capability and an intelligent analysis function, and improves the real-time level of construction engineering field management.

Description

Technical Field

[0001] The present invention relates to the technical field of construction engineering management, and in particular to a construction engineering management system based on real-time recording technology. Background Art

[0002] In traditional construction project management systems, data recording is the basis of system operation. Traditional methods usually rely on manual data entry, such as workers using spreadsheets to record daily workload, material usage, etc. This manual data entry method is not only inefficient, but also prone to errors, which affects data accuracy. Although some systems have begun to use automated equipment to collect data seamlessly, this method will cause huge data transmission pressure once the number of data collection terminals increases, and eventually lead to data transmission blockage and errors, affecting the real-time and reliability of data recording in the construction project management process, and cannot fully meet the needs of construction project management. Summary of the invention

[0003] In view of the above problems, the present invention aims to provide a construction project management system based on real-time recording technology.

[0004] The purpose of the present invention is achieved by the following technical solutions:

[0005] The present invention shows a construction engineering management system based on real-time recording technology, including: a data acquisition module, a local processing module, a local storage module, a data transmission module and a cloud server module; wherein,

[0006] The data acquisition module is arranged at the construction site, and is used to collect monitoring data of the construction site in real time, and transmit the collected monitoring data to the local processing module;

[0007] The local processing module is used to perform standardization processing according to the acquired monitoring data to obtain standardized monitoring data, and store all the standardized monitoring data in the local storage module; and further perform key data extraction processing according to the obtained standardized monitoring data to obtain the key monitoring data contained therein, and transmit the obtained key monitoring data to the data transmission module;

[0008] The local storage module is used to locally store and process the acquired standard monitoring data and build a local monitoring database for construction projects;

[0009] The data transmission module is used to upload key monitoring data to the cloud server module via wireless transmission;

[0010] The cloud server module is used to perform intelligent analysis based on the key monitoring data obtained, obtain intelligent analysis results, and further generate dynamic reports based on the key monitoring data and intelligent analysis results and perform visual presentation; the intelligent analysis results include abnormal analysis results and predictive analysis results.

[0011] Preferably, the data acquisition module includes a sensor unit; wherein,

[0012] The key areas of the construction site include the construction area, material storage area, equipment operation area, etc. The monitoring data include construction site environmental monitoring data, structure monitoring data, material consumption data and personnel activity data, etc.

[0013] A data communication connection is established between each sensor unit and the local processing module through the wireless Internet of Things, and the collected monitoring data is transmitted to the local processing module in real time.

[0014] Preferably, the local processing module includes a standardization processing unit and a key data extraction unit; wherein,

[0015] The standardization processing unit is used to perform standardization processing according to the acquired monitoring data, including converting the acquired monitoring data into a unified format, adjusting the dimension of the data, correcting errors in the data, etc., to obtain annotated monitoring data; and transmitting all standardized monitoring data to the local storage module, which locally stores the standardized monitoring data;

[0016] The key data extraction unit is used to perform key data extraction processing based on the obtained standardized monitoring data, including performing data identification processing on the monitoring data based on data standards, marking the monitoring data that meets the data standards or is associated with the data standards as key monitoring data, and transmitting the acquired key monitoring data to the data transmission module; wherein the data standards include standard data types, standard indicators or standard numerical ranges, etc.

[0017] Preferably, the local storage module is used to perform localized backup processing on all acquired monitoring data, wherein the acquired standard monitoring data is organized in order to construct a local monitoring database for construction projects, wherein the data in the local monitoring database for construction projects is stored according to a preset logical structure.

[0018] Preferably, in the process of the data transmission module transmitting the key monitoring data to the cloud server module, the wireless transmission methods used include 5G, LoRa, etc.; the transmission protocols used include HTTP, HTTPS, FTP, etc.

[0019] Preferably, the cloud server module includes an intelligent analysis unit and a visualization unit; wherein,

[0020] The intelligent analysis unit includes an abnormal analysis unit and a predictive analysis unit;

[0021] The abnormality analysis unit compares and analyzes the acquired key monitoring data with the corresponding set abnormal thresholds or abnormality rules, marks the key monitoring data that deviates from the normal range as abnormal monitoring data, and marks the key monitoring data within the standard range as normal monitoring data, thereby obtaining abnormality analysis results of the key monitoring data;

[0022] The prediction analysis unit is used to perform data prediction based on the trained prediction model, combining the historical monitoring data of the same type and the key monitoring data obtained in real time, predict the change trend of the key monitoring data, and obtain the prediction analysis results of the key monitoring data;

[0023] The visualization unit is used to integrate the real-time key monitoring data and the corresponding abnormal analysis results and predictive analysis results into the corresponding display templates by combining data display templates such as icons, maps, and dials, and to update the data displayed by the display templates in real time.

[0024] Preferably, the cloud server module also includes a data retrieval unit;

[0025] The retrieval unit is used to transmit data retrieval instructions to the corresponding local storage module according to the provided data retrieval instructions, so that the local storage module transmits the standard monitoring data corresponding to the data retrieval instructions to the cloud server module according to the data retrieval instructions; wherein the data retrieval instructions include the data type and conditions required to be retrieved.

[0026] The beneficial effects of the present invention are as follows: the present invention can record the monitoring data of the construction project site in real time and comprehensively by setting a data acquisition module at the construction project site. Based on the local processing module, the monitoring data obtained can first be subjected to preliminary standardization processing and key monitoring data extraction, thereby extracting the monitoring data with key features and further uploading them to the cloud server module for further analysis and processing, and for other acquired monitoring data, local storage is performed through the local storage module, thereby improving the intelligence level of the preliminary processing and storage of the monitoring data. For the key monitoring data, the cloud server module is used to perform in-depth intelligent analysis and processing, and the key monitoring data can be accurately and intelligently analyzed based on the cloud server, thereby obtaining the intelligent analysis results of the construction project monitoring management, and finally by visually displaying the intelligent analysis results, it is helpful to assist managers in comprehensively controlling the construction project and improving the management level of the construction project. At the same time, the mode of performing preliminary key data extraction based on the local processing module and then performing in-depth analysis of the key monitoring data in combination with the cloud server module can help reduce the pressure of the entire management system on the transmission and processing of monitoring data, thereby improving the real-time and reliability of the intelligent management of the construction project. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0028] Figure 1 This is a framework diagram of a construction project management system based on real-time recording technology shown in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The present invention is further described in conjunction with the following application scenarios.

[0030] See also Figure 1 , which shows a construction engineering management system based on real-time recording technology, including: a data acquisition module, a local processing module, a local storage module, a data transmission module and a cloud server module; wherein,

[0031] The data acquisition module is arranged at the construction site, and is used to collect monitoring data of the construction site in real time, and transmit the collected monitoring data to the local processing module;

[0032] The local processing module is used to perform standardization processing according to the acquired monitoring data to obtain standardized monitoring data, and store all the standardized monitoring data in the local storage module; and further perform key data extraction processing according to the obtained standardized monitoring data to obtain the key monitoring data contained therein, and transmit the obtained key monitoring data to the data transmission module;

[0033] The local storage module is used to locally store and process the acquired standard monitoring data and build a local monitoring database for construction projects;

[0034] The data transmission module is used to upload key monitoring data to the cloud server module via wireless transmission;

[0035] The cloud server module is used to perform intelligent analysis based on the key monitoring data obtained, obtain intelligent analysis results, and further generate dynamic reports based on the key monitoring data and intelligent analysis results and perform visual presentation; the intelligent analysis results include abnormal analysis results and predictive analysis results.

[0036] The above-mentioned embodiment of the present invention can record the monitoring data of the construction project site in real time and comprehensively by setting a data acquisition module at the construction project site. Based on the local processing module, the monitoring data obtained can first be subjected to preliminary standardization processing and key monitoring data extraction, thereby extracting the monitoring data with key features and further uploading them to the cloud server module for further analysis and processing, and for other acquired monitoring data, local storage is performed through the local storage module, thereby improving the intelligence level of the preliminary processing and storage of the monitoring data. For the key monitoring data, the cloud server module is used to perform in-depth intelligent analysis and processing, and the key monitoring data can be accurately and intelligently analyzed based on the cloud server, thereby obtaining the intelligent analysis results of the construction project monitoring management, and finally by visually displaying the intelligent analysis results, it is helpful to assist managers in comprehensively controlling the construction project and improving the management level of the construction project. At the same time, the mode of performing preliminary key data extraction based on the local processing module and then performing in-depth analysis of the key monitoring data in combination with the cloud server module can help reduce the pressure of the entire management system on the transmission and processing of monitoring data, thereby improving the real-time and reliability of the intelligent management of the construction project.

[0037] Preferably, the data acquisition module includes a sensor unit; wherein,

[0038] The key areas of the construction site include the construction area, material storage area, equipment operation area, etc. The monitoring data include construction site environmental monitoring data, structure monitoring data, material consumption data and personnel activity data, etc.

[0039] A data communication connection is established between each sensor unit and the local processing module through the wireless Internet of Things, and the collected monitoring data is transmitted to the local processing module in real time.

[0040] The data acquisition module is set at the key location of the construction site to monitor and collect various monitoring data of the construction site in a comprehensive and real-time manner. The deployment location of the module is carefully planned to ensure that all important areas of the construction site are covered. These locations may include construction areas, material storage areas, equipment operation areas, etc., as well as any areas that may affect the quality and safety of the project. Through the diversified design of the data acquisition module, the data acquisition module can capture various types of data on the construction site in real time, including but not limited to environmental parameters (such as temperature, humidity, noise, light), structural parameters (such as stress, displacement, vibration), construction progress data, material consumption data, personnel activity data, etc., based on advanced acquisition technology to ensure the real-time nature of the data. Whether it is automatically collected by sensors or captured by cameras, the current status of the construction site can be reflected instantly.

[0041] The data acquisition module can collect monitoring data from the construction site based on real-time recording technology, realize comprehensive collection of monitoring data from the construction site, and help provide an accurate and real-time data foundation for the entire construction project management system, thereby supporting more efficient and intelligent project management decisions.

[0042] In one embodiment, in a data acquisition module, each sensor unit forms a wireless Internet of Things ad hoc network, and each sensor unit serves as a data node in the ad hoc network, wherein the construction site is divided into multiple sub-areas, and the data nodes in each sub-area are provided with a cluster head node. In each sub-area, after the data node transmits its own collected data to the corresponding cluster head node, the cluster head node further transmits the aggregated monitoring data to the data receiving node of the local processing module.

[0043] Data nodes are established through sensor units, and a wireless Internet of Things ad hoc network is composed of multiple data nodes. The data interaction function between data nodes is completed through the ad hoc network, and the data is directed to the local processing module. On the one hand, the real-time performance of data collection can be improved. On the other hand, the completion of data transmission through the ad hoc network also helps to improve the reliability of data transmission and reduce the energy consumption of the entire data acquisition module. Among them, cluster head nodes are further established in the data nodes to assist in the data collection and transmission of data nodes in the ad hoc network, which can further improve the performance of data transmission in the ad hoc network.

[0044] Among them, considering that the environment at the construction site is usually more complex, and the reliability of the sensor unit will be reduced in a complex working environment (such as high dust concentration or electromagnetic interference environment, etc.), it is easy to have transient failures or other abnormal situations. Therefore, if the traditional cluster head node assignment technology is applied to the sensor units at the construction site, there will be a higher probability that the cluster head node will have transient failures due to the influence of the on-site conditions, causing abnormal situations such as the occurrence of abnormal situations, affecting the integrity and reliability of the data collection of all sensor units under the corresponding clustering.

[0045] Therefore, the present invention also particularly proposes a data transmission method based on a wireless Internet of Things self-organizing network in a construction project site environment to improve the reliability and performance of data transmission.

[0046] Preferably, the data acquisition module further includes:

[0047] A cluster head node is selected from the data nodes in each sub-area of ​​the construction site, and the data nodes and cluster head nodes in the sub-area are combined into a data cluster. The cluster head node aggregates the monitoring data collected by each data node in its cluster and further transmits the monitoring data to the data receiving node of the local processing module.

[0048] Among them, the cluster head nodes are selected from the data nodes in each sub-region of the construction site, specifically including:

[0049] Every fixed time period TG, each data node in the sub-region detects its own first cluster head ability value and broadcasts the cluster head ability value in itself to other data nodes in the sub-region. Among them, the calculation method of the first cluster head ability value is:

[0050]

[0051] In the formula, AB t (k) represents the first cluster head ability value of the k-th data node, Eng t (k) represents the remaining energy percentage of the k-th data node at the current moment t, EngB represents the set energy standard value, Eng t-1 (k) represents the remaining energy percentage of the k-th data node at the previous time period moment t - 1; EnhGB represents the set energy change standard value, COND1(Eng t (k)>EngB,Eng t (k)-Eng t-1 (k)<EngGB) represents a judgment function. When both Eng t (k)>EngB and Eng t (k)-Eng t-1 (k)<EngGB are satisfied, the judgment function takes the value of 2. When Eng t (k)>EngB or Eng t (k)-Eng t-1 (k)<EngGB are satisfied, the judgment function takes the value of 1. Otherwise, when both Eng t (k)>EngB and Eng t (k)-Eng t-1 (k)<EngGB are not satisfied, the judgment function takes the value of 0; R zoon represents the radius distance of the sub-region, D toMa (k) represents the distance of the k-th data node from the center position of the sub-region, maxD toOP (k) represents the maximum distance of the k-th data node from other data nodes in the sub-region, Send t (k) represents the data transmission rate of the k-th data node at the current moment t; ω E 、ω D 、ω S respectively represent preset quantization adjustment factors, which are used to adjust the sizes of each part in the calculation formula to the target range. Among them, ω E ×COND1(Eng t (k)>EngB,Engt (k)-Eng t-1 (k) <EngGB)∈[0,20], ω S ×Send t (k)∈[0,10];

[0052] The data node is selected as the first cluster head node G1 of the current time period according to the first cluster head capability values ​​of itself and other data nodes. When the first cluster head capability value of the data node is the largest, the data node is selected as the first cluster head node G1 of the current time period. The first cluster head node broadcasts its own selection information to other data nodes in the sub-area, so that other data nodes in the sub-area become cluster nodes of the first cluster head node, wherein the selection information includes the ID information of the first cluster head node.

[0053] Other data nodes detect the fitness value between themselves and the first cluster head node according to the election information of the first cluster head node, and transmit the obtained fitness value back to the first cluster head node; the fitness value calculation function used is:

[0054] Math toG1 (k) = ω D ×Send toG1 (k)+ω s ×(2R zoon -D toG1 (k))

[0055] Among them, Math toG1 (k) represents the fitness value between the kth data node and the current first cluster head node, Send toG1 (k) represents the data transmission rate between the kth data node and the current first cluster head node, D toG1 (k) represents the distance between the kth data node and the current first cluster head node, ω D ,ω S They represent preset quantitative adjustment factors, which are used to adjust the size of each part in the calculation formula to the target range, where ω D ×Send toG1 (k)∈[0,10],ω S ×(2R zoon -D toG1 (k))∈[0,10];

[0056] The first cluster head node further calculates the second cluster head capability value of each data node based on the received fitness value information of each data node and the first cluster head capability value information of each data node received previously, wherein the second cluster head capability value calculation function used is:

[0057] CB t (k) = ω A×AB t (k)+ω M ×Math toG1 (k)

[0058] Among them, CB t (k) represents the second cluster head capability value of the kth data node, AB t (k) represents the first cluster head capability value of the kth data node, Math toG1 (k) The fitness value between the kth data node and the current first cluster head node, ω A and ω M Respectively represent the preset weight adjustment factors, which are used to adjust the size of each part of the calculation formula to the target range, where ω A ×AB t (k)∈[0,10],ω M ×Math toG1 (k)∈[0,10];

[0059] According to the second cluster head capability value of each data node, the first cluster head node sends assignment information to two data nodes with the largest second cluster head capability value, so that the two data nodes receiving the assignment information become the second cluster head nodes; the first cluster head node broadcasts the election information of the second cluster head node to all data nodes in its cluster, wherein the election information of the second cluster head node includes the identity ID of the second cluster head node;

[0060] After the data collection node in the sub-area collects the monitoring data, the monitoring data is transmitted to the first cluster head node, which aggregates the monitoring data and further transmits the aggregated monitoring data to the data receiving node of the local processing module; wherein, when the second cluster head node transmits its own monitoring data to the first cluster head node, it also adds tag information TAG1 with the current time and identity ID, and transmits the monitoring data and tag information TAG1 together to the first cluster head node; further, before the first cluster head node transmits the aggregated monitoring data to the local processing module, it further transmits the aggregated monitoring data to the second cluster head node respectively, and the second cluster head node backs up the acquired monitoring data to the cache, wherein the aggregated detection data includes the tag information TAG1;

[0061] The second cluster head node detects the data transmitted from the first cluster head node. When the tag information TGA1 is not detected after the set time interval, it is determined that the current first cluster head node fails. The two second cluster head nodes further compare their first cluster head capability values ​​with each other, so as to determine that the second cluster head node with the larger first cluster head capability value becomes the temporary first cluster head node KG1, and the other second cluster head node continues to remain as the second cluster head node; the temporary first cluster head node KG1 broadcasts the fault information of the first cluster head node and the information that it is elected as the temporary first cluster head node to other data nodes in the sub-area, so that other data nodes can determine whether the sender of the fault information is the previously elected second cluster head node based on the received broadcast information. If so, a cluster relationship is established with the temporary first cluster head node KG1, and the node becomes the cluster node of the temporary first cluster head node KG1; otherwise, the elected information is determined to be unreliable and the elected information of the temporary first cluster head node is ignored; the temporary first cluster head node replaces the original first cluster head node to complete the task of data aggregation and transmission until the end of the current time period.

[0062] Preferably, the temporary first cluster head node further transmits the fault information of the first cluster head node to the local processing module.

[0063] Preferably, when the second cluster head node caches the acquired monitoring data backup, it caches the data in a "first in, first out" manner, that is, when the data storage space of the cache is full, when caching the latest data, it clears the earliest stored data and makes room for the latest data.

[0064] Preferably, the first cluster head node transmits the aggregated monitoring data to the data receiving node of the local processing module, wherein it can be set according to actual conditions that the first cluster head node directly transmits the data to the data receiving node, or the first cluster head node further transmits the data to the first cluster head nodes of other sub-areas, and transmits the data to the data receiving node by multi-hop transmission.

[0065] The reliability of data nodes is easily affected by the construction site environment. In the traditional clustered data transmission mode of the wireless Internet of Things self-organizing network, if an abnormal situation occurs in the cluster head (such as temporary failure, etc.) during the clustered data transmission process, it will affect the data collection and transmission of the entire data cluster. The above-mentioned implementation method of the present invention proposes a setting scheme for the data collection module in the construction site environment, and completes the data transmission by collecting and constructing a wireless Internet of Things self-organizing network of regional data through data nodes, effectively improving the overall performance of data transmission and improving the reliability of data transmission. A clustered data transmission technical scheme for data nodes in the sub-area of ​​the construction site is proposed, which can be based on the data node and adaptively select the current first cluster head node according to the data node's own situation to complete the data clustering setting. Further, after the selection of the first cluster head node is completed, two second cluster head nodes are selected based on the first cluster head node to assist the first cluster head node in completing the work of data aggregation, wherein the second cluster head node can cache the data aggregated in the region, which is helpful to realize short-term data backup and improve the reliability of data transmission. At the same time, the second cluster head node can judge the working state of the first cluster head node based on the detection of data TAG. When the first cluster head node is abnormal, the two second cluster head nodes can further replace the temporary first cluster head node according to their own information and take over the data transmission task of the abnormal first cluster head node, which greatly improves the reliability and stability of data cluster data transmission in the sub-region. At the same time, in the process of replacing the second cluster head node, an identity authentication method is also specially designed. When the data node replaces the temporary first cluster head node, it is necessary to first determine whether the node is the current second cluster head node. This method can effectively avoid malicious attacks from external nodes and forcibly hijack the nodes in the cluster, further improving the security and reliability of data cluster transmission in the wireless Internet of Things self-organizing network.

[0066] Preferably, the local processing module includes a standardization processing unit and a key data extraction unit; wherein,

[0067] The standardization processing unit is used to perform standardization processing according to the acquired monitoring data, including converting the acquired monitoring data into a unified format, adjusting the dimension of the data, correcting errors in the data, etc., to obtain annotated monitoring data; and transmitting all standardized monitoring data to the local storage module, which locally stores the standardized monitoring data;

[0068] The key data extraction unit is used to perform key data extraction processing based on the obtained standardized monitoring data, including performing data identification processing on the monitoring data based on data standards, marking the monitoring data that meets the data standards or is associated with the data standards as key monitoring data, and transmitting the acquired key monitoring data to the data transmission module; wherein the data standards include standard data types, standard indicators or standard numerical ranges, etc.

[0069] The local processing module is set up at the construction site. It is responsible for the preliminary standardization and analysis of the monitoring data collected at the construction site to ensure the accuracy and availability of the data. The monitoring data may have different formats and dimensions after collection. The local processing module first standardizes these data. This includes converting the data into a unified format, adjusting the dimensions of the data, correcting errors in the data, etc., so as to obtain standardized monitoring data. The data after standardization is more standardized, which is convenient for subsequent analysis and key data extraction. On the basis of standardized monitoring data, the local processing module further performs key data extraction processing. The data is deeply analyzed and key information is identified. Data that meets the preset data standards and data associated with the data standards are marked as key monitoring data, such as key monitoring data reflecting important indicators of construction progress, statistical data on material consumption; or environmental monitoring data whose monitoring values ​​fall into the preset abnormal standard range or early warning signals for engineering safety. The local processing module can not only efficiently process and store monitoring data, but also identify and transmit key data, effectively reducing the pressure of data transmission and data processing on the cloud server, and improving the effect of real-time processing of monitoring data.

[0070] The acquired monitoring data is first screened through the local processing module, which can effectively extract the key data and transmit it to the cloud server module for further analysis and processing, while other monitoring data are completely and completely stored locally. On the one hand, it can ensure the integrity of the data, and on the other hand, it can help improve the intelligence level of monitoring data analysis and the pressure of cloud server data transmission, ensure the reliability of construction project data management, and improve the effect of monitoring data management.

[0071] Preferably, the local storage module is used to perform localized backup processing on all acquired monitoring data, wherein the acquired standard monitoring data is organized in order to construct a local monitoring database for construction projects, wherein the data in the local monitoring database for construction projects is stored according to a preset logical structure.

[0072] In one scenario, the local storage module uses an efficient data storage architecture, including distributed file systems, relational databases, or NoSQL databases, to meet the needs of data storage of different types and scales. This architecture can provide high concurrent access, data redundancy, and fault recovery capabilities. The local storage module organizes the standard monitoring data in an orderly manner and builds a local monitoring database for construction projects. The data is stored according to a certain logical structure, such as classification by time series, project location, monitoring type, etc., to facilitate rapid retrieval and analysis.

[0073] Preferably, in the process of the data transmission module transmitting the key monitoring data to the cloud server module, the wireless transmission methods used include 5G, LoRa, etc.; the transmission protocols used include HTTP, HTTPS, FTP, etc.

[0074] The data transmission module uses advanced wireless transmission technologies, such as 5G, LoRa, etc., to provide high-speed and stable wireless connections based on wireless transmission, ensuring the real-time and integrity of the data. The data transmission module supports multiple transmission protocols, such as HTTP, HTTPS, FTP, etc., to adapt to different network environments and server requirements. After the data transmission is completed, the data transmission module will receive confirmation information from the cloud server to ensure that the data has been successfully received. If the cloud server fails to confirm, the module will retransmit the data. Through the setting of the data transmission module, it is ensured that the key monitoring data can be safely and timely transmitted to the cloud server module.

[0075] Preferably, the cloud server module includes an intelligent analysis unit and a visualization unit; wherein,

[0076] The intelligent analysis unit includes an abnormal analysis unit and a predictive analysis unit;

[0077] The abnormality analysis unit compares and analyzes the acquired key monitoring data with the corresponding set abnormal thresholds or abnormality rules, marks the key monitoring data that deviates from the normal range as abnormal monitoring data, and marks the key monitoring data within the standard range as normal monitoring data, thereby obtaining abnormality analysis results of the key monitoring data;

[0078] The prediction analysis unit is used to perform data prediction based on the trained prediction model, combining the historical monitoring data of the same type and the key monitoring data obtained in real time, predict the change trend of the key monitoring data, and obtain the prediction analysis results of the key monitoring data;

[0079] The visualization unit is used to integrate the real-time key monitoring data and the corresponding abnormal analysis results and predictive analysis results into the corresponding display templates by combining data display templates such as icons, maps, and dials, and to update the data displayed by the display templates in real time.

[0080] The main function of the cloud server module is to conduct intelligent analysis based on the key monitoring data obtained, generate dynamic reports, and perform visual display. Among them, the intelligent analysis module uses artificial intelligence algorithms and big data analysis technology to conduct in-depth analysis of key monitoring data, including analyzing monitoring data by setting thresholds and rules, and identifying any abnormal conditions that deviate from the normal range, such as equipment failure, construction progress delays, environmental anomalies, etc. And use historical data and real-time data, combined with machine learning and predictive models, to predict future construction trends, material requirements, cost changes, etc., to provide forward-looking decision support for managers. For the visual display of analysis results, the cloud server module can intuitively present complex monitoring data and analysis results to managers through various forms such as charts, maps, and dashboards, and ensure that managers can obtain the latest engineering information by updating reports and data visualization content in real time.

[0081] Preferably, the cloud server module further includes a data retrieval unit;

[0082] The retrieval unit is used to transmit data retrieval instructions to the corresponding local storage module according to the provided data retrieval instructions, so that the local storage module transmits the standard monitoring data corresponding to the data retrieval instructions to the cloud server module according to the data retrieval instructions; wherein the data retrieval instructions include the data type and conditions required to be retrieved.

[0083] Among them, when necessary, the cloud server can retrieve complete monitoring data from the local storage module for further analysis and management, facilitating further retrieval of data.

[0084] It should be noted that each functional unit / module in each embodiment of the present invention may be integrated into one processing unit / module, or each unit / module may exist physically separately, or two or more units / modules may be integrated into one unit / module. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of software functional unit / module.

[0085] Through the description of the above implementation mode, it can be clearly understood by those skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the process of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein the communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a computer. Computer-readable media can include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should analyze that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. A construction project management system based on real-time recording technology, characterized in that: include: Data acquisition module, local processing module, local storage module, data transmission module and cloud server module; among them, The data acquisition module is arranged at the construction site, and is used to collect monitoring data of the construction site in real time, and transmit the collected monitoring data to the local processing module; The local processing module is used to perform standardization processing according to the acquired monitoring data to obtain standardized monitoring data, and store all the standardized monitoring data in the local storage module; and further perform key data extraction processing according to the obtained standardized monitoring data to obtain the key monitoring data contained therein, and transmit the obtained key monitoring data to the data transmission module; The local storage module is used to locally store and process the acquired standard monitoring data and build a local monitoring database for construction projects; The data transmission module is used to upload key monitoring data to the cloud server module via wireless transmission; The cloud server module is used to perform intelligent analysis based on the key monitoring data obtained, obtain intelligent analysis results, and further generate dynamic reports based on the key monitoring data and intelligent analysis results and perform visual presentation; the intelligent analysis results include abnormal analysis results and predictive analysis results.

2. A construction project management system based on real-time recording technology according to claim 1, characterized in that: The data acquisition module includes a sensor unit; wherein, The key areas of the construction site include the construction area, material storage area, and equipment operation area; the monitoring data includes the construction site environmental monitoring data, structure monitoring data, material consumption data, and personnel activity data; A data communication connection is established between each sensor unit and the local processing module through the wireless Internet of Things, and the collected monitoring data is transmitted to the local processing module in real time.

3. A construction project management system based on real-time recording technology according to claim 2, characterized in that: In the data acquisition module, each sensor unit forms a wireless Internet of Things ad hoc network, and each sensor unit serves as a data node in the ad hoc network. The construction site is divided into multiple sub-areas, and the data nodes in each sub-area are provided with a cluster head node. In each sub-area, the data node transmits its own collected data to the corresponding cluster head node, and the cluster head node further transmits the aggregated monitoring data to the data receiving node of the local processing module.

4. A construction project management system based on real-time recording technology according to claim 1, characterized in that: The local processing module includes a standardization processing unit and a key data extraction unit; wherein, The standardization processing unit is used to perform standardization processing according to the acquired monitoring data, including converting the acquired monitoring data into a unified format, adjusting the dimension of the data, correcting errors in the data, and obtaining annotated monitoring data; and transmitting all standardized monitoring data to the local storage module, which stores the standardized monitoring data locally; The key data extraction unit is used to perform key data extraction processing based on the obtained standardized monitoring data, including performing data identification processing on the monitoring data based on data standards, marking the monitoring data that meets the data standards or is associated with the data standards as key monitoring data, and transmitting the acquired key monitoring data to the data transmission module; wherein the data standards include standard data types, standard indicators or standard numerical ranges.

5. The construction project management system based on real-time recording technology according to claim 1 is characterized in that: The local storage module is used to perform localized backup processing on all acquired monitoring data, wherein the acquired standard monitoring data is organized in order to construct a local monitoring database for construction projects, wherein the data in the local monitoring database for construction projects is stored according to a preset logical structure.

6. A construction project management system based on real-time recording technology according to claim 1, characterized in that: In the process of the data transmission module transmitting key monitoring data to the cloud server module, the wireless transmission methods used include 5G and LoRa; the transmission protocols used include HTTP, HTTPS, and FTP.

7. A construction project management system based on real-time recording technology according to claim 1, characterized in that: The cloud server module includes an intelligent analysis unit and a visualization unit; wherein, The intelligent analysis unit includes an abnormal analysis unit and a predictive analysis unit; The abnormality analysis unit compares and analyzes the acquired key monitoring data with the corresponding set abnormal thresholds or abnormality rules, marks the key monitoring data that deviates from the normal range as abnormal monitoring data, and marks the key monitoring data within the standard range as normal monitoring data, thereby obtaining abnormality analysis results of the key monitoring data; The prediction analysis unit is used to perform data prediction based on the trained prediction model, combining the historical monitoring data of the same type and the key monitoring data obtained in real time, predict the change trend of the key monitoring data, and obtain the prediction analysis results of the key monitoring data; The visualization unit is used to integrate the real-time key monitoring data and the corresponding abnormal analysis results and predictive analysis results into the corresponding display templates by combining icons, maps, and dial data display templates, and to update the data displayed by the display templates in real time.

8. A construction project management system based on real-time recording technology according to claim 7, characterized in that: The cloud server module also includes a data retrieval unit; The retrieval unit is used to transmit the data retrieval instruction to the corresponding local storage module according to the provided data retrieval instruction, so that the local storage module transmits the standard monitoring data corresponding to the data retrieval instruction to the cloud server module according to the data retrieval instruction; wherein the data retrieval instruction includes the data type and conditions required to be retrieved.

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