Engineering monitoring data information management platform based on cloud storage and construction method

Abstract

The invention belongs to the technical field of engineering monitoring, and particularly relates to an engineering monitoring data information management platform based on cloud storage and a construction method, and the platform comprises a background cloud server, a local server, a data collection port and a mobile terminal. The background cloud server is used for dividing data areas according to engineering types and storing engineering information; the data acquisition port monitors engineering data and construction environment data in real time in an engineering construction area and is provided with an information transmission port; dividing local servers according to engineering types, wherein the local servers are used for centralizing data acquired by the data acquisition ports, processing the data and managing accounts; the mobile terminal provides an identity recognition service and is used for manually inputting and reading data and compensating data of a data acquisition port; through cooperation of the cloud server, the local server, the data acquisition port and the mobile terminal, big data application and data mining can be facilitated, and the project quality safety prediction and forecast level can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering monitoring, and specifically relates to an engineering monitoring data information management platform based on cloud storage and a construction method thereof. Background Art

[0002] Safety monitoring abroad began with dam construction in the 1890s. Safety monitoring in my country also began with dam construction. In the early 1950s, only traditional measurements such as displacement and settlement were conducted on concrete dams such as Fengman, Fuziling and Meishan. With the development of large-scale urban rail transit, municipal engineering (pipeline networks, bridges), urban construction (deep foundation pits, high-rise buildings, structural reinforcement, cultural relics protection and restoration), natural disaster prevention and control, and highway and railway construction, safety monitoring has also experienced seventy or eighty years of development, and its importance has become increasingly prominent.

[0003] First, the working mode of most monitoring units in China is relatively extensive. The general process is: after the on-site manual test is completed, the professional technicians return to the room to use CAD, Word or Excel and other software to calculate and process the data, and then further use Word or Excel and other software to manually make monitoring reports. The results are summarized simply, and the conclusions and suggestions are roughly analyzed. As a result, the feedback of monitoring and early warning information is not timely, and the results cannot be expressed in multiple dimensions.

[0004] Secondly, the so-called automated monitoring in current projects is only implemented in some test contents, lacks compatibility, and the related instruments and data collection processing and analysis are not perfect;

[0005] Secondly, since there are many projects that need to be monitored, each monitoring project has many monitoring contents and measurement and testing methods, and the monitoring information is extremely scattered. At present, the management of monitoring project information by all construction parties is still in the manual management stage or file system management stage, and there is a lack of unified standards for data management, which makes it difficult to manage engineering construction monitoring information.

[0006] To this end, the present invention provides an engineering monitoring data information management platform based on cloud storage and a construction method. Summary of the invention

[0007] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0008] The technical solution adopted by the present invention to solve its technical problem is: the engineering monitoring data information management platform based on cloud storage described in the present invention includes a background cloud server, a local server, a data acquisition port and a mobile terminal;

[0009] The backend cloud server divides the data area according to the project type and stores the project information;

[0010] Data collection port, real-time monitoring of engineering data and construction environment data in the construction area, and setting up information transmission port;

[0011] Divide local servers according to project types. Local servers are used to centralize data collected by data collection ports, process data, and manage accounts;

[0012] Mobile terminal, providing identity recognition services for manual data entry and data reading, and compensating data collection port data;

[0013] The backend cloud server includes a data repository, a resource integration module, a cache library, and an information interaction module. The data in the data repository is synchronized with the Internet;

[0014] The data repository is divided into sub-databases based on the engineering type as the database boundary, and the sub-database data is organized through the data integration module;

[0015] The sub-database interacts with the local server through the information interaction module;

[0016] The mobile terminal transmits data to the cache through the information interaction module, and the local server downloads the information in the cache through the information interaction module;

[0017] The local database transmits data to the cache library through the information interaction module, and the mobile terminal downloads the information in the cache library through the information interaction module.

[0018] Preferably, the data acquisition port includes a structural safety monitoring module, an environmental monitoring module, a construction process monitoring module and a personnel monitoring module;

[0019] Safety monitoring module, used to monitor stress-strain data, displacement deformation data and crack data;

[0020] Environmental monitoring module, used to monitor meteorological environmental data and address environmental data;

[0021] The construction process monitoring module is used to monitor construction progress data, construction quality data and construction equipment operation data.

[0022] Preferably, the detailed steps of construction progress data monitoring include:

[0023] A1. Divide the project into multiple sub-projects and formulate an expected project progress plan based on the project;

[0024] A2. Set a monitoring cycle, monitor according to the monitoring cycle, obtain the actual progress of the project, and compare the actual progress of the project with the expected progress of the project;

[0025] A3. Determine the factors that affect the implementation speed of the project based on the sub-project type. j (j=1, 2, ...n), calculate the functional relationship between the frequency of occurrence of each influencing factor and the engineering speed;

[0026] A4. Monitor influencing factors and events in real time through data collection ports and mobile terminals, and formulate remedial plan recommendations based on influencing factors and events.

[0027] Preferably, the influencing factor F j Occurrence frequency f j The steps for calculating the functional relationship between and engineering speed include:

[0028] B1. Obtain the frequency of occurrence of influencing factors of various types of sub-projects from the Internet through the data repository data j and engineering speed v j data;

[0029] B2. Integrate the data of engineering speed and frequency of occurrence of influencing factors, and then assume a functional relationship;

[0030] B3. Establish a system of equations based on the data, solve the coefficients, derive the function expression, and draw a function curve graph.

[0031] Preferably, in step B1, the assumed functional relationship is:

[0032] = ;

[0033] In step B2, the integrated data is:

[0034] ( , )、( , ),…,( , );

[0035] In step B3, the set of equations established is:

[0036] .

[0037] Preferably, in step B3, the method of solving the coefficient derivation function expression is:

[0038] calculate and The mean of :

[0039] = ;

[0040] = ;

[0041] The coefficient b is calculated as:

[0042] = ;

[0043] coefficient The calculation method is:

[0044] = + ;

[0045] The coefficient and Substitution = , inverse the function expression.

[0046] Preferably, in step A4, the implementation steps of the remediation plan recommendations include:

[0047] C1. Based on the data in the data repository, obtain the remediation plan recommendations from the Internet when the impact factors of various types of sub-projects occur;

[0048] C2, the data collection port and the mobile terminal collect the number of occurrences of the influencing factors, and calculate the frequency of occurrence of the influencing factors through the local server;

[0049] C3, substitute the frequency of the influencing factor into the function expression in step B3, and calculate the engineering speed at the frequency;

[0050] C4. The frequency of occurrence of the influencing factors is uploaded to the local server, and the remediation plan suggestion is downloaded and then transmitted to the mobile terminal.

[0051] Preferably, the data repository has a data learning and updating function:

[0052] The steps of data repository data learning update include:

[0053] E1. After implementing the remediation plan recommendations, record the actual time taken to complete the sub-project;

[0054] E2. Obtain the estimated completion time based on the project progress forecast plan developed in step A1;

[0055] E3. Calculate the difference between the time required to complete the project after the influencing factors occur and the actual time required to complete the project;

[0056] E4. Calculate the difference between the actual completion time and the estimated completion time;

[0057] E5. Upload the two sets of difference collaborative remediation plan recommendations from step E3 and step E4 to the data repository.

[0058] Preferably, in step E5, the method of comparing the two sets of differences in step E3 and step E4 is:

[0059] The actual completion time of the sub-project is T 实 ;

[0060] The estimated completion time is T 预 ;

[0061] Time to complete after the influencing factor occurs T 影 ;

[0062] The data compared include T 实 -T 预 and T 实 -T 影 .

[0063] A method for constructing a cloud storage-based engineering monitoring data information management platform, the method adopts the above-mentioned cloud storage-based engineering monitoring data information management platform, and includes the following steps:

[0064] G1. Establish a backend cloud server and have Internet access to download project engineering data and remediation plan proposal data;

[0065] G2. Establish a local server at the target project site, enter administrator information, and activate the mobile terminal according to the administrator information;

[0066] G3. Install the data acquisition port equipment at the target project site, and then conduct a trial run. Put it into use after passing the trial run.

[0067] The beneficial effects of the present invention are as follows:

[0068] 1. The present invention uses a cloud server, a local server, a data acquisition port and a mobile terminal to upload the data collected manually and automatically on site to the data repository in real time through the Internet, ensuring the automation, real-time and informationization of engineering monitoring data, building an engineering monitoring database and information management platform based on cloud storage, realizing the classified and unified management of monitoring data, automatic error checking, ensuring the security and reliability of data, so as to query relevant data according to needs, and realizing the multi-dimensional expression of monitoring results based on technologies such as oblique photography contour cloud maps, building a quality and safety prediction, forecast and early warning system for the engineering construction process, which can facilitate big data application and data mining, and improve the level of engineering quality and safety prediction and forecasting;

[0069] 2. The present invention obtains information through the data repository and calculates the influencing factor F j Occurrence frequency f jThe functional relationship between the frequency of influencing factors and the project speed is obtained by calculating the functional relationship between the frequency of influencing factors and the project speed. The function curve can be drawn to directly estimate the project speed after the influencing factors occur, and then the time to complete the construction can be estimated, which is helpful to formulate a more practical and executable project plan. Through reasonable estimation of the project progress, resources can be better planned and allocated. By estimating the construction speed through data, an effective and reasonable construction plan can be formulated to reduce the difficulty of project construction management and improve the efficiency of project construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The present invention will be further described below in conjunction with the accompanying drawings.

[0071] Figure 1 It is a framework diagram of the platform of the present invention;

[0072] Figure 2 It is a flow chart of the construction progress data monitoring steps in the present invention;

[0073] Figure 3 It is a flow chart of the functional relationship calculation steps in the present invention;

[0074] Figure 4 is a flow chart of a proposed implementation method of the remediation plan of the present invention;

[0075] Figure 5 is a flow chart of the data learning and updating steps of the data repository in the present invention;

[0076] Figure 6 It is a flow chart of the construction method in the present invention. DETAILED DESCRIPTION

[0077] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0078] like Figures 1 to 5 As shown, the present invention includes a backend cloud server, a local server, a data acquisition port and a mobile terminal;

[0079] The backend cloud server divides data areas according to project types and stores project information.

[0080] Among them, common project types include but are not limited to bridge construction, building construction and reservoir dam construction.

[0081] The backend cloud server includes a data repository, a resource integration module, a cache library and an information interaction module. The data in the data repository is synchronized with the Internet, representative engineering construction data is obtained through the Internet, and data resources are integrated through the resource integration module.

[0082] The data repository is divided into sub-databases based on the engineering type as the database boundary. The sub-database data is organized through the data integration module, thereby forming multiple sub-databases in the data repository, which can reduce the query time when querying and obtaining data.

[0083] The data collection port monitors the engineering data and construction environment data in real time within the engineering construction area, and sets up an information transmission port.

[0084] Among them, the data acquisition port includes a structural safety monitoring module, an environmental monitoring module, a construction process monitoring module, and a personnel monitoring module;

[0085] Safety monitoring module, used to monitor stress-strain data, displacement deformation data and crack data;

[0086] Environmental monitoring module, used to monitor meteorological environmental data and address environmental data;

[0087] Construction process monitoring module, used to monitor construction progress data, construction quality data and construction equipment operation data;

[0088] In this way, various numerical values ​​of the project engineering can be obtained in real time, and the data collected manually and automatically on-site (including pictures, videos and other image materials) can be uploaded to the data repository in real time through the Internet, ensuring the automation, real-time and informationization of engineering monitoring data, and building an engineering monitoring database and information management platform based on cloud storage. The classified and unified management of monitoring data and automatic error detection can be achieved to ensure the security and reliability of data, so that relevant data can be queried according to needs, and multi-dimensional expression of monitoring results can be achieved based on technologies such as oblique photography contour cloud maps, and a quality and safety prediction, forecast and early warning system for the engineering construction process can be built. The engineering monitoring management cloud platform can facilitate big data applications and data mining, and improve the level of engineering quality and safety prediction and forecasting.

[0089] Divide local servers according to project types. Local servers are used to centralize data collected by data collection ports, process data, and manage accounts;

[0090] Mobile terminal, providing identity recognition services for manual data entry and data reading, and compensating data collection port data;

[0091] The data repository is divided into sub-databases based on the engineering type as the database boundary, and the sub-database data is organized through the data integration module;

[0092] The sub-database interacts with the local server through the information interaction module;

[0093] The mobile terminal transmits data to the cache library through the information interaction module, and the local server downloads the information in the cache library through the information interaction module. The staff can carry the mobile terminal to record data at the construction site and compare the data recorded by the mobile terminal with the data collection port to improve the accuracy of data collection;

[0094] The local database transfers data to the cache library through the information interaction module, and the mobile terminal downloads the information in the cache library through the information interaction module. The local database is a common computer set up in the project engineering, generally the project department office.

[0095] The detailed steps of construction progress data monitoring include:

[0096] A1. Divide the project into multiple sub-projects and formulate an expected project progress plan based on the project;

[0097] Among them, the determination of sub-projects can be based on factors in actual construction, such as construction location, construction time, etc.

[0098] A2. Set a monitoring cycle, monitor according to the monitoring cycle, obtain the actual progress of the project, and compare the actual progress of the project with the expected progress of the project, so as to intuitively obtain the construction speed of the project and estimate whether the project can be completed on time.

[0099] A3. Determine the factors that affect the implementation speed of the project based on the sub-project type. j (j=1, 2, ...n), calculate the functional relationship between the frequency of occurrence of each influencing factor and the engineering speed.

[0100] When the influencing factor is an event, when the influencing factor occurs, the completion time becomes longer, thereby reducing the construction speed and causing project delays. At this time, in order to prevent project delays, a remedial plan needs to be implemented after the event occurs.

[0101] It should be noted that when obtaining the data on influencing factors, force majeure factors need to be excluded.

[0102] A4. Real-time monitoring of influencing factors and events through data collection ports and mobile terminals, and formulation of remediation plan suggestions based on influencing factors and events;

[0103] Among them, the influencing factor F j Occurrence frequency f j The steps for calculating the functional relationship between and engineering speed include:

[0104] B1. Obtain the frequency of occurrence of influencing factors of various types of sub-projects from the Internet through the data repository data j and engineering speed v j data;

[0105] B2. Integrate the data of engineering speed and frequency of occurrence of influencing factors, and then assume a functional relationship;

[0106] B3. Establish a system of equations based on the data, solve the coefficients, derive the function expression, and draw a function curve graph.

[0107] By calculating the functional relationship between the frequency of influencing factors and the construction speed, a function curve is drawn to directly estimate the construction speed after the influencing factors occur, and then estimate the time to complete the construction;

[0108] When the time to complete the construction is less than the expected completion time of the project, the project can be delivered on time and there is no need to adopt a remedial plan. When the time to complete the construction is greater than the expected completion time of the project, a remedial plan needs to be implemented.

[0109] In addition, by estimating the construction speed through data, it is also possible to formulate effective and reasonable construction plans, reduce the difficulty of construction management, and improve the efficiency of construction.

[0110] In step B1, the assumed functional relationship is:

[0111] = ;

[0112] In step B2, the integrated data is:

[0113] ( , )、( , ),…,( , );

[0114] In step B3, the set of equations established is:

[0115] .

[0116] It indicates The theoretical maximum rate at which a project can be completed without the impact of events that reduce the project's progress. It represents the influence coefficient of event frequency on project completion rate.

[0117] In step B3, the method of solving the coefficient derivation function expression is:

[0118] calculate and The mean of :

[0119] = ;

[0120] = ;

[0121] The coefficient b is calculated as: = ;

[0122] coefficient The calculation method is:

[0123] = + ;

[0124] The coefficient and Substitution = , inversely deduce the function expression, and determine the function expression by adopting the least squares data fitting method, so as to facilitate direct calculation after obtaining the data.

[0125] After estimating the construction speed and selecting a remedial plan, the completion time of each stage can be predicted based on the specific requirements of the project, resource conditions, weather and other factors, which helps to formulate a more practical and executable project plan. Through reasonable estimation of the project progress, resources (such as manpower, materials, equipment, etc.) can be better planned and allocated to ensure the rational use of various resources and avoid waste of resources. By analyzing the possible construction speed before construction, the management team can identify possible bottlenecks and delay factors. For example, too slow or too fast construction speed, weather changes, etc. may affect the progress of the project.

[0126] Once potential delay risks are identified, the project team can develop appropriate remedial plans in advance. These plans usually include measures such as overtime, additional labor, and deployment of additional resources to reduce the impact of schedule delays.

[0127] In step A4, the steps for implementing the remediation plan include:

[0128] C1. Based on the data in the data repository, obtain the remediation plan recommendations from the Internet when the impact factors of various types of sub-projects occur;

[0129] C2, the data collection port and the mobile terminal collect the number of occurrences of the influencing factors, and calculate the frequency of occurrence of the influencing factors through the local server;

[0130] C3, substitute the frequency of the influencing factor into the function expression in step B3, and calculate the engineering speed at the frequency;

[0131] C4. The frequency of occurrence of the influencing factors is uploaded to the local server, and the remediation plan suggestion is downloaded and then transmitted to the mobile terminal.

[0132] When influencing factors are detected, remedial plan information is sent to mobile terminals, so that managers can directly obtain plan information and improve the response rate to influencing factors.

[0133] The data repository has data learning update capabilities:

[0134] The steps of data repository data learning update include:

[0135] E1. After implementing the remediation plan recommendations, record the actual time taken to complete the sub-project;

[0136] E2. Obtain the estimated completion time based on the project progress forecast plan developed in step A1;

[0137] E3. Calculate the difference between the time required to complete the project after the influencing factors occur and the actual time required to complete the project;

[0138] E4. Calculate the difference between the actual completion time and the estimated completion time;

[0139] E5. Upload the two sets of difference collaborative remediation plan recommendations from step E3 and step E4 to the data repository.

[0140] Real-time updating of the data repository ensures that the organization always has the latest data, avoids relying on outdated or inaccurate information, and quickly responds to the data needs of engineering projects. At the same time, it helps the organization make more timely and accurate decisions, enabling the data repository to continuously optimize its processing methods based on new data.

[0141] In step E5, the two sets of difference values ​​in step E3 and step E4 are compared as follows;

[0142] The actual completion time of the sub-project is T 实 ;

[0143] The estimated completion time is T 预 ;

[0144] Time to complete after the influencing factor occurs T 影 ;

[0145] The data compared include T 实 -T 预 and T 实 -T 影 .

[0146] When T 实 -T 预 ≥0, the project can be delivered ahead of schedule, T 实 -T 预 ≤0, calculate T 实 -T 影The values ​​of are all negative, reflecting that after the implementation of the remedial plan, although the delivery is delayed, the construction time saved is relative to the real-time remedial plan.

[0147] like Figure 6 As shown, a method for constructing a cloud storage-based engineering monitoring data information management platform, the method adopts the above-mentioned cloud storage-based engineering monitoring data information management platform, and includes the following steps:

[0148] G1. Establish a backend cloud server and have Internet access to download project engineering data and remediation plan proposal data;

[0149] G2. Establish a local server at the target project site, enter administrator information, and activate the mobile terminal according to the administrator information;

[0150] G3. Install the data acquisition port equipment at the target project site, and then conduct a trial run. Put it into use after passing the trial run.

[0151] The above-mentioned front, back, left, right, top and bottom are all based on the figures in the specification. Figure 1 As a benchmark, according to the person's observation perspective, the side of the device facing the observer is defined as the front, the left side of the observer is defined as the left, and so on.

[0152] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the scope of protection of the present invention.

[0153] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. The cloud storage-based engineering monitoring data information management platform is characterized by: Including backend cloud server, local server, data collection port and mobile terminal; The backend cloud server divides the data area according to the project type and stores the project information; Data collection port, real-time monitoring of engineering data and construction environment data in the construction area, and setting up information transmission port; Divide local servers according to project types. Local servers are used to centralize data collected by data collection ports, process data, and manage accounts; Mobile terminal, providing identity recognition services for manual data entry and data reading, and compensating data collection port data; The backend cloud server includes a data repository, a resource integration module, a cache library and an information interaction module, and the data in the data repository is synchronized with the Internet; The data repository is divided into sub-databases based on the engineering type as the database boundary, and the sub-database data is sorted through the data integration module; The sub-database interacts with the local server information via the information interaction module; The mobile terminal transmits data to the cache through the information interaction module, and the local server downloads the information in the cache through the information interaction module; The local database transmits data to the cache library through the information interaction module, and the mobile terminal downloads the information in the cache library through the information interaction module.

2. The cloud storage-based engineering monitoring data information management platform according to claim 1, characterized in that: The data acquisition port includes a structural safety monitoring module, an environmental monitoring module, a construction process monitoring module and a personnel monitoring module; The safety monitoring module is used to monitor stress-strain data, displacement deformation data and crack data; The environmental monitoring module is used to monitor meteorological environmental data and address environmental data; The construction process monitoring module is used to monitor construction progress data, construction quality data and construction equipment operation data.

3. The cloud storage-based engineering monitoring data information management platform according to claim 2, characterized in that: The detailed steps of the construction progress data monitoring include: A1. Divide the project into multiple sub-projects and formulate an expected project progress plan based on the project; A2. Set a monitoring cycle, monitor according to the monitoring cycle, obtain the actual progress of the project, and compare the actual progress of the project with the expected progress of the project; A3. Determine the factors that affect the implementation speed of the project based on the sub-project type. j (j=1, 2, ...n), calculate the functional relationship between the frequency of occurrence of each influencing factor and the engineering speed; A4. Monitor influencing factors and events in real time through data collection ports and mobile terminals, and formulate remedial plan recommendations based on influencing factors and events.

4. The cloud storage-based engineering monitoring data information management platform according to claim 3 is characterized in that: Influencing factors j Occurrence frequency f j The steps for calculating the functional relationship between and engineering speed include: B1. Obtain the frequency of occurrence of influencing factors of various types of sub-projects from the Internet through the data repository data j and engineering speed v j data; B2. Integrate the data of engineering speed and frequency of occurrence of influencing factors, and then assume a functional relationship; B3. Establish a system of equations based on the data, solve the coefficients, derive the function expression, and draw a function curve graph.

5. The cloud storage-based engineering monitoring data information management platform according to claim 4 is characterized in that: In step B1, the assumed functional relationship is: = ； In step B2, the integrated data is: （ ， ）、（ ， ），…，（ ， ）； In step B3, the set of equations established is: 。 6. The cloud storage-based engineering monitoring data information management platform according to claim 5, characterized in that: In step B3, the method of solving the coefficient derivation function expression is: calculate and The mean of : = ； = ； The coefficient b is calculated as: = ； coefficient The calculation method is: = + ； The coefficient and Substitution = , inverse the function expression.

7. The cloud storage-based engineering monitoring data information management platform according to claim 6 is characterized in that: In step A4, the steps for implementing the remediation plan include: C1. Based on the data in the data repository, obtain the remediation plan recommendations from the Internet when the impact factors of various types of sub-projects occur; C2, the data collection port and the mobile terminal collect the number of occurrences of the influencing factors, and calculate the frequency of occurrence of the influencing factors through the local server; C3, substitute the frequency of the influencing factor into the function expression in step B3, and calculate the engineering speed at the frequency; C4. The frequency of occurrence of the influencing factors is uploaded to the local server, and the remediation plan suggestion is downloaded and then transmitted to the mobile terminal.

8. The cloud storage-based engineering monitoring data information management platform according to claim 7, characterized in that: The data repository has a data learning update function: The steps of data repository data learning update include: E1. After implementing the remediation plan recommendations, record the actual time taken to complete the sub-project; E2. Obtain the estimated completion time based on the project progress forecast plan developed in step A1; E3. Calculate the difference between the time required to complete the project after the influencing factors occur and the actual time required to complete the project; E4. Calculate the difference between the actual completion time and the estimated completion time; E5. Upload the two sets of difference collaborative remediation plan recommendations from step E3 and step E4 to the data repository.

9. The cloud storage-based engineering monitoring data information management platform according to claim 8, characterized in that: In step E5, the two sets of difference values ​​in step E3 and step E4 are compared as follows; The actual completion time of the sub-project is T 实 ; The estimated completion time is T 预 ; Time to complete after the influencing factor occurs T 影 ; The data compared include T 实 -T 预 and T 实 -T 影 .

10. A method for constructing a cloud storage-based engineering monitoring data information management platform, the method adopting the cloud storage-based engineering monitoring data information management platform of claim 9, characterized in that: The following steps are involved: G1. Establish a backend cloud server and have Internet access to download project engineering data and remediation plan proposal data; G2. Establish a local server at the target project site, enter administrator information, and activate the mobile terminal according to the administrator information; G3. Install the data acquisition port equipment at the target project site, and then conduct a trial run. Put it into use after passing the trial run.

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