Engineering data management system and method based on big data

Abstract

The invention discloses an engineering data management system and method based on big data, relates to the technical field of engineering project management, and solves the problem that in engineering data management, dynamic allocation of task load is difficult to carry out according to the working efficiency of each engineering team in a project, and the project efficiency is low. And the influence condition of the engineering project on the environment is difficult to obtain through analysis. The method comprises the following steps: performing exception processing on basic data, calculating the basic data after exception processing to obtain an efficiency factor and a resource utilization factor of each engineering team, synthesizing the efficiency factor and the resource utilization factor into an evaluation factor, and performing dynamic allocation of task load on each engineering team based on the evaluation factor; analyzing the environment data to obtain an environment influence factor of the engineering project, and sending out early warning information based on the environment influence factor; according to the method, project resource allocation is improved, production efficiency is improved, environmental influence is analyzed, and environmental risks are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering project management, and specifically relates to an engineering data management system and method based on big data. Background Art

[0002] With the development of science and technology and the increasing complexity of engineering construction, the management of engineering data has become increasingly important. Traditional engineering data management methods usually rely on paper documents and manual operations, which are not only inefficient, but also prone to errors and may also pose a risk of data loss. With the development of information and digital technology, engineering data management systems based on big data are becoming more and more popular among enterprises. Enterprises can manage projects through engineering data management systems, which improves the processing efficiency and safety of engineering projects.

[0003] At present, with the increasing complexity of projects and increasing attention to environmental protection, most engineering data management systems based on big data find it difficult to dynamically allocate tasks according to the work efficiency of each engineering team in the project, and cannot reasonably allocate the subsequent workload, resulting in inefficient engineering teams occupying a large amount of resources, which cannot help companies effectively manage and allocate resources, thereby affecting the efficiency of project completion; at the same time, most engineering data management systems based on big data ignore the impact of engineering projects on the environment in engineering data management, and it is difficult to obtain the impact of engineering projects on the environment through analysis, which increases the environmental risks of the projects. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an engineering data management system and method based on big data, which is used to solve the technical problems that it is difficult to dynamically allocate the amount of tasks according to the work efficiency of each engineering team in the project in engineering data management, and it is difficult to obtain the impact of the engineering project on the environment through analysis. The present invention performs exception processing on basic data, calculates the basic data after exception processing to obtain the efficiency factor and resource utilization factor of each engineering team, integrates the efficiency factor and resource utilization factor into an evaluation factor, and dynamically allocates the amount of tasks to each engineering team based on the evaluation factor; analyzes environmental data to obtain the environmental impact factor of the engineering project, and issues early warning information based on the environmental impact factor to solve the above problems.

[0005] To achieve the above-mentioned object, the first aspect of the present invention provides an engineering data management system based on big data, comprising: an engineering management module, and a data collection module, an environment monitoring module and a database connected thereto;

[0006] The data collection module is used to collect basic data and environmental data of the project and transmit the basic data and environmental data to the database; the basic data includes the project design progress, daily usage of building materials, and daily completion progress; the environmental data includes noise value, dust concentration, and water pollutant concentration;

[0007] The engineering management module is used to perform exception processing on basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception processing, combine the efficiency factor and resource utilization factor into an evaluation factor, and dynamically allocate the task volume to each engineering team based on the evaluation factor;

[0008] The environmental monitoring module is used to analyze environmental data to obtain environmental impact factors of engineering projects and issue early warning information based on the environmental impact factors.

[0009] Preferably, the collection of basic data and environmental data of the engineering project includes:

[0010] Obtain the daily project design progress of each engineering team in the current project through the database, and obtain the daily usage of construction materials and daily completion progress of each engineering team through the digital project log of each engineering team;

[0011] The noise value collected once within the set time is obtained through a noise detector; the dust concentration collected once within the set time is obtained through a dust detector; the water pollutant concentration of the water body around the construction site collected once within the set time is obtained through a water quality detector; among them, the set time is obtained manually, and the area around the construction site is obtained manually.

[0012] It should be noted that progress can be understood as a ratio. The daily project design progress is the ratio of the daily design workload of each engineering team to the total workload. The daily completion progress is the ratio of the daily completed workload of each engineering team to the daily design workload. The ratio can be used to compare engineering teams with different work tasks, avoiding the difference in efficiency caused by different work tasks, which in turn affects the fairness of the analysis.

[0013] Preferably, the abnormal processing of the basic data includes:

[0014] A1: Extract the daily usage CYL and daily completion progress RWD of each engineering team. Determine whether the daily usage CYL or daily completion progress RWD of the building materials is 0. If yes, jump to A2. If no, do nothing.

[0015] A2: Extract the highest temperature and rainfall of the project location today from the database; determine whether the highest temperature GW or rainfall JY exceeds the corresponding judgment threshold; if yes, do nothing; if no, jump to A3; the judgment thresholds include temperature judgment threshold and rainfall judgment threshold, and both are set manually;

[0016] A3: Determine whether today is a rest day set by the current engineering team; if yes, do nothing; if no, jump to A4;

[0017] A4: Determine whether the current engineering team's daily completion progress RWD is 0; if yes, extract the highest temperature QGW and rainfall QJY of the previous working day of the current engineering team, obtain the progress reference value JCZ based on the formula JCZ=QRWD×(α1×GW / QGW+α2×JY / QJY), assign the progress reference value JCZ to today's daily completion progress to update and obtain the daily completion progress RWD after abnormal processing; if no, add zero to update today's daily completion progress RWD; wherein, α1 and α2 are both proportional adjustment coefficients greater than 0; QRWD is the daily completion progress of the previous working day; the units of GW and QGW are ℃, the units of JY and QJY are mm, and the units of JCZ, RWD and QRWD are %;

[0018] A5: Determine whether the current engineering team's daily construction material usage CYL is 0; if yes, mark the historical working days in which the current engineering team's daily construction material usage CYL and daily completion progress RWD in the current project are not 0 as reference working days, extract the daily construction material usage CCYL and daily completion progress CRWD of the reference working day closest to today, obtain the mutual influence factor HYZ based on the formula HYZ=CCYL / CRWD, extract the updated daily completion progress RWD of today, and obtain today's daily construction material usage CYL based on the formula CYL=HYZ×RWD; if no, do nothing.

[0019] It is worth noting that in step A5, the mutual influence factors are obtained by using the daily usage and daily completion progress of the reference working day closest to today, rather than the average daily usage and daily completion progress of the current engineering team's historical working days. This is because the mutual influence factors of the daily usage and daily completion progress of the engineering team's construction materials can be understood as the daily completion progress that should be achieved under a certain daily usage of construction materials, or the daily usage of construction materials that should be achieved under a certain daily completion progress. The correlation between the two will cause certain fluctuations due to personnel changes, work changes or temperature changes in the engineering team. Because the working day with the smallest changes in personnel, work and temperature of the engineering team at the current time is the reference working day closest to today, the mutual influence factors obtained by using the daily usage and daily completion progress of the reference working day closest to today can best reflect the potential correlation between today's daily usage and daily completion progress of construction materials.

[0020] Preferably, the efficiency factor and resource utilization factor of each engineering team are calculated from the basic data after the abnormal processing, including:

[0021] Extract the daily completion progress RWD and project design progress SJD of each engineering team in the current project, calculate the average value of the project design progress SJD of each engineering team to obtain the average design progress PJD; obtain the efficiency factor JDZ of each engineering team based on the formula JDZ=β×(exp(SJD / PJD)-1)×RWD; where β is the amplitude adjustment factor of the exp(*) function;

[0022] The historical working days of each engineering team in the current project are extracted in turn, and the daily usage of building materials CYL and the daily completion progress RWD in the historical working days are cleaned and calculated to obtain the resource utilization factor of each engineering team.

[0023] It is worth noting that the efficiency factor in the present invention can be understood as the embodiment of the work efficiency of each engineering team. The efficiency factor of the present invention is obtained by analysis based on the daily completion progress and the project design progress, because the project design progress can indirectly reflect the amount of tasks assigned to the engineering team today. The more tasks and the higher the completion progress, the higher the work efficiency of the corresponding engineering team. Moreover, this efficiency is a nonlinear growth, because the more tasks there are, the greater the pressure on the engineering team. This pressure will show an exponential growth. If the tasks can be completed under the pressure of exponential growth, it can prove that the efficiency factor of the current engineering team is higher than that of the engineering team that cannot overcome the pressure.

[0024] Preferably, the resource utilization factor of each engineering team is obtained by cleaning and calculating the daily usage CYL and the daily completion progress RWD of the construction materials in the historical working days, including:

[0025] Extract the daily usage CYL and daily completion progress RWD of the construction materials in the historical working days of each engineering team in turn, and divide the daily usage CYL and daily completion progress RWD of the construction materials into two groups A and B according to their types; among which, group A is the daily usage CYL of construction materials, and group B is the daily completion progress RWD;

[0026] Extract the variance of each group of data and determine whether the variance of the group of data is greater than or equal to the corresponding variance threshold; if yes, remove the data in the group that is most different from the mode of the group of data, recalculate the variance of the group, until the variance of the group is less than the corresponding variance threshold, perform average calculation on the remaining data of the group to obtain the eigenvalue; if no, perform average calculation on the data in the group to obtain the eigenvalue; wherein the variance threshold is set manually;

[0027] The characteristic value of group A is marked as the standard daily usage of building materials BCYL, and the characteristic value of group B is marked as the standard daily completion progress BRWD; the average value of the standard daily usage of building materials BCYL of each engineering team is obtained, and the average value is marked as the average daily usage of building materials PCYL, and the average value of the standard daily completion progress BRWD of each engineering team is obtained, and the average value is marked as the average daily completion progress PRWD;

[0028] The standard daily consumption of construction materials BCYL and the standard daily completion progress BRWD of each engineering team are extracted, and the resource utilization factor ZLZ of each engineering team is obtained based on the formula ZLZ=γ×exp(BCYL / PCYL) / (δ×exp(BRWD / PRWD)); wherein γ and δ are both proportional adjustment coefficients greater than 0.

[0029] It is worth noting that the resource utilization factor obtained by the present invention is obtained by analyzing the daily usage of standard building materials and the standard daily completion progress. When the daily usage of standard building materials is less and the standard daily completion progress is higher, it proves that the resource utilization rate of the current engineering team is higher, which further results in a higher resource utilization factor for scoring. The present invention can help enterprises effectively manage and allocate resources, reduce costs, improve production efficiency, and help achieve the goal of sustainable development.

[0030] Preferably, the efficiency factor and the resource utilization factor are integrated into the evaluation factor, including:

[0031] The efficiency factor JDZ and resource utilization factor ZLZ of each engineering team are extracted, and the evaluation factor PJZ of each engineering team is obtained based on the formula PJZ=ρ1×JDZ+ρ2×ZLZ; wherein ρ1 and ρ2 are proportional adjustment coefficients greater than 0.

[0032] Preferably, the dynamic allocation of tasks to each engineering team based on the evaluation factor includes:

[0033] The workload WGL completed by each engineering team today and the evaluation factor QPJZ of the previous working day are extracted from the database, and the task volume RWL for the next working day is obtained based on the formula RWL=μ×exp((PJZ-QPJZ) / QPJZ)×WGL; where μ is an amplitude adjustment factor greater than 0.

[0034] It should be noted that when today is the first day of the project, the evaluation factor QPJZ of the previous working day is marked as 1.

[0035] Preferably, the environmental impact factors of the engineering project obtained by analyzing the environmental data include:

[0036] Extract the noise value ZY collected once within the set time, and judge whether the noise value ZY collected once exceeds the noise threshold ZDY in turn; if yes, obtain the noise excess value ZCB based on the formula ZCB=ZY-ZDY; if no, do nothing;

[0037] Extract the dust concentration YD collected once within the set time, and judge whether the dust concentration YD collected once exceeds the dust limit threshold YDY; if yes, obtain the dust excess value YCB based on the formula YCB=YD-YDY; if no, do nothing;

[0038] Extract the concentration SD of water pollutants collected once within the set time, and judge in turn whether the concentration SD of water pollutants collected once exceeds the water pollution threshold SDY; if yes, obtain the water pollution excess value SCB based on the formula SCB=SD-SDY; if no, do nothing; among them, the noise threshold ZDY, dust threshold YDY and water pollution threshold SDY are all obtained through manual setting;

[0039] The average value of several calculated noise excess values ​​ZCB is calculated to obtain the average noise excess value PZCB, the average value of several calculated dust boundary thresholds YDY is calculated to obtain the average dust boundary threshold PYDY, and the average value of several calculated water pollution excess values ​​SCB is calculated to obtain the average water pollution excess value PSCB; based on the formula JYZ=σ1×ln(PZCB / ZDY+1)+σ2×ln(PYDY / YDY+1)+σ3×ln(PSCB / SDY+1), the environmental impact factor JYZ is obtained; among them, σ1, σ2, and σ3 are all proportional adjustment factors, and σ1+σ2+σ3=1.

[0040] It is worth noting that the present invention adds the function of environmental impact assessment to the system, which can effectively reduce the calculation cost of enterprises in environmental impact assessment, while improving the speed and accuracy of assessment. The environmental impact factor can remind enterprises to choose construction methods with less environmental impact, thereby improving the green image of enterprises and reducing environmental risks while complying with environmental laws and regulations.

[0041] Preferably, the issuing of warning information based on environmental impact factors includes:

[0042] B1: Extract environmental impact factor JYZ; determine whether environmental impact factor JYZ exceeds environmental judgment threshold 1; if yes, issue a warning that the project construction seriously affects the surrounding environment; if no, jump to B2;

[0043] B2: Determine whether the environmental impact factor JYZ exceeds the environmental judgment threshold 2; if yes, the project construction will have a certain impact on the surrounding environment; if no, no warning will be issued; among them, the environmental judgment threshold 1 and the environmental judgment threshold 2 are both manually set, and the environmental judgment threshold 1 is greater than the environmental judgment threshold 2.

[0044] A second aspect of the present invention provides an engineering data management method based on big data, comprising the following steps:

[0045] S1: Collect basic data and environmental data of the project and transfer them to the database;

[0046] S2: Perform exception processing on the basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception processing, combine the efficiency factor and resource utilization factor into evaluation factors, and dynamically allocate the task volume to each engineering team based on the evaluation factors;

[0047] S3: Analyze environmental data to obtain environmental impact factors of engineering projects, and issue early warning information based on the environmental impact factors.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The present invention performs exception processing on basic data, calculates the basic data after exception processing to obtain the efficiency factor and resource utilization factor of each engineering team, integrates the efficiency factor and resource utilization factor into an evaluation factor, and dynamically allocates the task volume to each engineering team based on the evaluation factor; analyzes environmental data to obtain the environmental impact factor of the engineering project, and issues early warning information based on the environmental impact factor, thereby solving the problems of being difficult to dynamically allocate the task volume according to the work efficiency of each engineering team in the project in engineering data management, and being difficult to obtain the impact of the engineering project on the environment through analysis. The present invention improves project resource allocation and production efficiency while also analyzing environmental impacts to reduce environmental risks.

[0050] 2. The resource utilization factor obtained by the present invention is obtained by analyzing the daily usage of standard building materials and the standard daily completion progress. When the daily usage of standard building materials is less and the standard daily completion progress is higher, it proves that the resource utilization rate of the current engineering team is higher, which further results in a higher resource utilization factor for scoring. The present invention can help enterprises effectively manage and allocate resources, reduce costs, improve production efficiency, and help achieve the goal of sustainable development.

[0051] 3. The present invention adds the function of environmental impact assessment to the system, which can effectively reduce the calculation cost of enterprises in environmental impact assessment, while improving the speed and accuracy of assessment. The environmental impact factor can remind enterprises to choose construction methods with less environmental impact, thereby improving the green image of enterprises and reducing environmental risks while complying with environmental laws and regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0053] Figure 1 It is a schematic diagram of the operation steps of the present invention;

[0054] Figure 2 It is a schematic diagram of the system module of the present invention;

[0055] Figure 3 A schematic diagram of the operation steps for obtaining the resource utilization factor of each engineering team in the present invention;

[0056] Figure 4 The figure is a schematic diagram of the operation steps for obtaining the environmental impact factors of the present invention. DETAILED DESCRIPTION

[0057] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1-Figure 2 , the first aspect of the present invention provides an engineering data management system based on big data, including: an engineering management module, and a data collection module, an environment monitoring module and a database connected thereto;

[0059] Data collection module: used to collect basic data and environmental data of engineering projects, and transmit the basic data and environmental data to the database; the basic data includes project design progress, daily usage of building materials, and daily completion progress; the environmental data includes noise value, dust concentration, and water pollutant concentration;

[0060] Engineering management module: used to handle exceptions to basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception handling, combine the efficiency factor and resource utilization factor into evaluation factors, and dynamically allocate the task volume to each engineering team based on the evaluation factors;

[0061] Environmental monitoring module: used to analyze environmental data to obtain environmental impact factors of engineering projects and issue early warning information based on environmental impact factors.

[0062] For example, there are 5 engineering teams working on the current project, namely, Engineering Team 1, Engineering Team 2, Engineering Team 3, Engineering Team 4, and Engineering Team 5;

[0063] Since the daily usage CYL data of construction materials of Engineering Team 2 today is 0, there may be underreporting, so the basic data of Engineering Team 2 today is processed abnormally. Since the highest temperature and rainfall at the project location today do not exceed the corresponding judgment threshold, and today is not a rest day set by Engineering Team 2, the daily completion progress RWD of Engineering Team 2 today is updated with zero, and the historical working days in which the daily usage CYL and daily completion progress RWD of construction materials of Engineering Team 2 in the current project are not 0 are extracted and marked as reference working days, and the daily usage CCYL and daily completion progress CRWD of the reference working day closest to today are extracted, and the mutual influence factor HYZ is obtained based on the formula HYZ=CCYL / CRWD, and the updated daily completion progress RWD of today is extracted, and the daily usage CYL of construction materials today is obtained based on the formula CYL=HYZ×RWD;

[0064] If the daily completion progress RWD of engineering team 5 today is 90%, and the project design progress SJD is 0.2%, the average value of the project design progress SJD of each engineering team is calculated to obtain the average design progress PJD=0.19%; based on the formula JDZ=β×(exp(SJD / PJD)-1)×RWD=0.6×(exp(0.2% / 0.19%)-1)×90%=1.007, the efficiency factor JDZ of engineering team 5 is obtained; wherein, in this embodiment, the value of β is 0.6;

[0065] Extract the historical working days of each engineering team in the current project in turn, clean the daily construction material usage CYL and daily completion progress RWD in the historical working days to obtain the standard daily construction material usage BCYL and standard daily completion progress BRWD of each engineering team, and obtain the resource utilization factor ZLZ of each engineering team based on the formula ZLZ = γ × exp (BCYL / PCYL) / (δ × exp (BRWD / PRWD));

[0066] The efficiency factor JDZ and resource utilization factor ZLZ of each engineering team are extracted, and the evaluation factor PJZ of each engineering team is obtained based on the formula PJZ=ρ1×JDZ+ρ2×ZLZ. The workload WGL completed by each engineering team today and the evaluation factor QPJZ of the previous working day are extracted from the database, and the task volume RWL of the next working day is obtained based on the formula RWL=μ×exp((PJZ-QPJZ) / QPJZ)×WGL.

[0067] In this application, exception processing is performed on the basic data, including:

[0068] A1: Extract the daily usage CYL and daily completion progress RWD of each engineering team. Determine whether the daily usage CYL or daily completion progress RWD of each engineering team is 0. If yes, jump to A2. If no, do nothing.

[0069] A2: Extract the highest temperature and rainfall of the project location today from the database; determine whether the highest temperature GW or rainfall JY exceeds the corresponding judgment threshold; if yes, do nothing; if no, jump to A3; the judgment thresholds include temperature judgment threshold and rainfall judgment threshold, and both are set manually;

[0070] A3: Determine whether today is a rest day set by the current engineering team; if yes, do nothing; if no, jump to A4;

[0071] A4: Determine whether the current engineering team's daily completion progress RWD is 0; if yes, extract the highest temperature QGW and rainfall QJY of the previous working day of the current engineering team, obtain the progress reference value JCZ based on the formula JCZ=QRWD×(α1×GW / QGW+α2×JY / QJY), assign the progress reference value JCZ to today's daily completion progress to update and obtain the daily completion progress RWD after abnormal processing; if no, add zero to update today's daily completion progress RWD; wherein, α1 and α2 are both proportional adjustment coefficients greater than 0; QRWD is the daily completion progress of the previous working day; the units of GW and QGW are ℃, the units of JY and QJY are mm, and the units of JCZ, RWD and QRWD are %;

[0072] A5: Determine whether the current engineering team's daily construction material usage CYL is 0; if yes, mark the historical working days in which the current engineering team's daily construction material usage CYL and daily completion progress RWD in the current project are not 0 as reference working days, extract the daily construction material usage CCYL and daily completion progress CRWD of the reference working day closest to today, obtain the mutual influence factor HYZ based on the formula HYZ=CCYL / CRWD, extract the updated daily completion progress RWD of today, and obtain today's daily construction material usage CYL based on the formula CYL=HYZ×RWD; if no, do nothing.

[0073] It should be noted that in step A1, when the daily usage of building materials CYL or the daily completion progress RWD has data of 0, it proves that the current record may have an abnormal situation of omission, which needs further judgment.

[0074] It should be noted that in step A2, when the maximum temperature GW or rainfall JY exceeds the corresponding judgment threshold, it is normal for the current daily construction material usage CYL or daily completion progress RWD to be 0. Construction cannot be carried out due to high temperature or heavy rain, and the material usage or progress will be 0 at this time.

[0075] It should be noted that in step A3, if today is a rest day set by the current engineering team, it is normal for the material usage or progress to be 0.

[0076] See also Figure 3 In this application, the daily usage of building materials CYL and the daily completion progress RWD in the historical working days are cleaned and calculated to obtain the resource utilization factors of each engineering team, including:

[0077] Extract the daily usage CYL and daily completion progress RWD of each engineering team in the historical working days in turn, and divide the daily usage CYL and daily completion progress RWD of building materials into two groups A and B according to their types; among them, Group A is the daily usage CYL of building materials, and Group B is the daily completion progress RWD;

[0078] Extract the variance of each group of data and determine whether the variance of the group of data is greater than or equal to the corresponding variance threshold; if yes, remove the data in the group that is most different from the mode of the group of data, recalculate the variance of the group, until the variance of the group is less than the corresponding variance threshold, perform average calculation on the remaining data of the group to obtain the eigenvalue; if no, perform average calculation on the data in the group to obtain the eigenvalue; wherein the variance threshold is set manually;

[0079] The characteristic value of group A is marked as the standard daily usage of building materials BCYL, and the characteristic value of group B is marked as the standard daily completion progress BRWD; the average value of the standard daily usage of building materials BCYL of each engineering team is obtained, and the average value is marked as the average daily usage of building materials PCYL; the average value of the standard daily completion progress BRWD of each engineering team is obtained, and the average value is marked as the average daily completion progress PRWD;

[0080] The standard daily consumption of construction materials BCYL and the standard daily completion progress BRWD of each engineering team are extracted, and the resource utilization factor ZLZ of each engineering team is obtained based on the formula ZLZ=γ×exp(BCYL / PCYL) / (δ×exp(BRWD / PRWD)); wherein γ and δ are both proportional adjustment coefficients greater than 0.

[0081] It should be noted that when cleaning the data of groups A and B, the variance was judged. When the variance of a group of data is not less than the corresponding variance threshold, it indicates that there are one or more data in the group that affect the stability of the group. At this time, removing these data can obtain a stable data group, and then calculating the average value of this data group can obtain a value that can represent the current data group.

[0082] See also Figure 4 In this application, environmental data is analyzed to obtain the environmental impact factors of the project, including:

[0083] Extract the noise value ZY collected once within the set time, and judge whether the noise value ZY collected once exceeds the noise threshold ZDY in turn; if yes, obtain the noise excess value ZCB based on the formula ZCB=ZY-ZDY; if no, do nothing;

[0084] Extract the dust concentration YD collected once within the set time, and judge whether the dust concentration YD collected once exceeds the dust limit threshold YDY; if yes, obtain the dust excess value YCB based on the formula YCB=YD-YDY; if no, do nothing;

[0085] Extract the concentration SD of water pollutants collected once within the set time, and judge in turn whether the concentration SD of water pollutants collected once exceeds the water pollution threshold SDY; if yes, obtain the water pollution excess value SCB based on the formula SCB=SD-SDY; if no, do nothing; among them, the noise threshold ZDY, dust threshold YDY and water pollution threshold SDY are all obtained through manual setting;

[0086] The average value of several calculated noise excess values ​​ZCB is calculated to obtain the average noise excess value PZCB, the average value of several calculated dust boundary thresholds YDY is calculated to obtain the average dust boundary threshold PYDY, and the average value of several calculated water pollution excess values ​​SCB is calculated to obtain the average water pollution excess value PSCB; based on the formula JYZ=σ1×ln(PZCB / ZDY+1)+σ2×ln(PYDY / YDY+1)+σ3×ln(PSCB / SDY+1), the environmental impact factor JYZ is obtained; among them, σ1, σ2, and σ3 are all proportional adjustment factors, and σ1+σ2+σ3=1.

[0087] It is worth noting that the present invention adds the function of environmental impact assessment to the system, which can effectively reduce the calculation cost of enterprises in environmental impact assessment, while improving the speed and accuracy of assessment. The environmental impact factor can remind enterprises to choose construction methods with less environmental impact, thereby improving the green image of enterprises and reducing environmental risks while complying with environmental laws and regulations.

[0088] A second aspect of the present invention provides a method for managing engineering data based on big data, comprising the following steps:

[0089] S1: Collect basic data and environmental data of the project and transfer them to the database;

[0090] S2: Perform exception processing on the basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception processing, combine the efficiency factor and resource utilization factor into evaluation factors, and dynamically allocate the task volume to each engineering team based on the evaluation factors;

[0091] S3: Analyze environmental data to obtain environmental impact factors of engineering projects, and issue early warning information based on the environmental impact factors.

[0092] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0093] Working principle of the present invention:

[0094] Collect basic data and environmental data of the project and transmit them to the database; perform exception processing on the basic data, calculate the daily completion progress and project design progress of each engineering team in the basic data after exception processing to obtain the efficiency factor of each engineering team, extract the historical working days of each engineering team in the current project in turn, clean and calculate the daily usage of building materials and daily completion progress in the historical working days to obtain the resource utilization factor of each engineering team, combine the efficiency factor and resource utilization factor into an evaluation factor, and dynamically allocate the task volume to each engineering team based on the evaluation factor; analyze the environmental data to obtain the environmental impact factor of the project, and issue early warning information based on the environmental impact factor.

[0095] The above embodiments are only used to illustrate the technical method 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 method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An engineering data management system and method based on big data, characterized in that: include: Engineering management module, and the data collection module, environmental monitoring module and database connected thereto; The data collection module is used to collect basic data and environmental data of the project and transmit the basic data and environmental data to the database; the basic data includes the project design progress, daily usage of building materials, and daily completion progress; the environmental data includes noise value, dust concentration, and water pollutant concentration; The engineering management module is used to perform exception processing on basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception processing, combine the efficiency factor and resource utilization factor into an evaluation factor, and dynamically allocate the task volume to each engineering team based on the evaluation factor; The environmental monitoring module is used to analyze environmental data to obtain environmental impact factors of engineering projects and issue early warning information based on the environmental impact factors.

2. According to the big data-based engineering data management system and method of claim 1, it is characterized in that: The basic data and environmental data of the engineering project are collected, including: Obtain the daily project design progress of each engineering team in the current project through the database, and obtain the daily usage of construction materials and daily completion progress of each engineering team through the digital project log of each engineering team; The noise value collected once within a set time is obtained through the noise detector; the dust concentration collected once within a set time is obtained through the dust detector; and the water pollutant concentration of the water body around the construction site collected once within a set time is obtained through the water quality detector.

3. According to the big data-based engineering data management system and method of claim 1, it is characterized in that: The abnormal processing of basic data includes: A1: Extract the daily usage CYL and daily completion progress RWD of each engineering team. Determine whether the daily usage CYL or daily completion progress RWD of the building materials is 0. If yes, jump to A2. If no, do nothing. A2: Extract the highest temperature and rainfall of the project location today from the database; determine whether the highest temperature GW or rainfall JY exceeds the corresponding judgment threshold; if yes, do nothing; if no, jump to A3; the judgment threshold includes the temperature judgment threshold and the rainfall judgment threshold; A3: Determine whether today is a rest day set by the current engineering team; if yes, do nothing; if no, jump to A4; A4: Determine whether the current engineering team's daily completion progress RWD is 0; if yes, extract the highest temperature QGW and rainfall QJY of the previous working day of the current engineering team, obtain the progress reference value JCZ based on the formula JCZ=QRWD×(α1×GW / QGW+α2×JY / QJY), assign the progress reference value JCZ to today's daily completion progress to update and obtain the daily completion progress RWD after abnormal processing; if no, add zero to update today's daily completion progress RWD; wherein, α1 and α2 are both proportional adjustment coefficients greater than 0; QRWD is the daily completion progress of the previous working day; the units of GW and QGW are ℃, the units of JY and QJY are mm, and the units of JCZ, RWD and QRWD are %; A5: Determine whether the current engineering team's daily construction material usage CYL is 0; if yes, mark the historical working days in which the current engineering team's daily construction material usage CYL and daily completion progress RWD in the current project are not 0 as reference working days, extract the daily construction material usage CCYL and daily completion progress CRWD of the reference working day closest to today, obtain the mutual influence factor HYZ based on the formula HYZ=CCYL / CRWD, extract the updated daily completion progress RWD of today, and obtain today's daily construction material usage CYL based on the formula CYL=HYZ×RWD; if no, do nothing.

4. The engineering data management system and method based on big data according to claim 1 is characterized in that: The efficiency factor and resource utilization factor of each engineering team are calculated by calculating the basic data after abnormal processing, including: Extract the daily completion progress RWD and project design progress SJD of each engineering team in the current project, calculate the average value of the project design progress SJD of each engineering team to obtain the average design progress PJD; obtain the efficiency factor JDZ of each engineering team based on the formula JDZ=β×(exp(SJD / PJD)-1)×RWD; where β is the amplitude adjustment factor of the exp(*) function; The historical working days of each engineering team in the current project are extracted in turn, and the daily usage of building materials CYL and the daily completion progress RWD in the historical working days are cleaned and calculated to obtain the resource utilization factor of each engineering team.

5. The engineering data management system and method based on big data according to claim 4 is characterized in that: The resource utilization factor of each engineering team is obtained by cleaning and calculating the daily usage CYL of construction materials and the daily completion progress RWD in the historical working days, including: Extract the daily usage CYL and daily completion progress RWD of the construction materials in the historical working days of each engineering team in turn, and divide the daily usage CYL and daily completion progress RWD of the construction materials into two groups A and B according to their types; among which, group A is the daily usage CYL of construction materials, and group B is the daily completion progress RWD; Extract the variance of each group of data and determine whether the variance of the group of data is greater than or equal to the corresponding variance threshold; if it is, remove the data in the group that is most different from the mode of the group of data, recalculate the variance of the group, until the variance of the group is less than the corresponding variance threshold, and perform average calculation on the remaining data of the group to obtain the eigenvalue; if not, perform average calculation on the data in the group to obtain the eigenvalue; The characteristic value of group A is marked as the standard daily usage of building materials BCYL, and the characteristic value of group B is marked as the standard daily completion progress BRWD; the average value of the standard daily usage of building materials BCYL of each engineering team is obtained, and the average value is marked as the average daily usage of building materials PCYL, and the average value of the standard daily completion progress BRWD of each engineering team is obtained, and the average value is marked as the average daily completion progress PRWD; The standard daily consumption of construction materials BCYL and the standard daily completion progress BRWD of each engineering team are extracted, and the resource utilization factor ZLZ of each engineering team is obtained based on the formula ZLZ=γ×exp(BCYL / PCYL) / (δ×exp(BRWD / PRWD)); wherein γ and δ are both proportional adjustment coefficients greater than 0.

6. The engineering data management system and method based on big data according to claim 4 is characterized in that: The efficiency factor and resource utilization factor are integrated into the evaluation factor, including: The efficiency factor JDZ and resource utilization factor ZLZ of each engineering team are extracted, and the evaluation factor PJZ of each engineering team is obtained based on the formula PJZ=ρ1×JDZ+ρ2×ZLZ; wherein ρ1 and ρ2 are proportional adjustment coefficients greater than 0.

7. The engineering data management system and method based on big data according to claim 6 is characterized in that: The dynamic allocation of tasks to each engineering team based on the evaluation factors includes: The workload WGL completed by each engineering team today and the evaluation factor QPJZ of the previous working day are extracted from the database, and the task volume RWL for the next working day is obtained based on the formula RWL=μ×exp((PJZ-QPJZ) / QPJZ)×WGL; where μ is an amplitude adjustment factor greater than 0.

8. The engineering data management system and method based on big data according to claim 1 is characterized in that: The environmental impact factors of the engineering project obtained by analyzing the environmental data include: Extract the noise value ZY collected once within the set time, and judge whether the noise value ZY collected once exceeds the noise threshold ZDY in turn; if yes, obtain the noise excess value ZCB based on the formula ZCB=ZY-ZDY; if no, do nothing; Extract the dust concentration YD collected once within the set time, and judge whether the dust concentration YD collected once exceeds the dust limit threshold YDY; if yes, obtain the dust excess value YCB based on the formula YCB=YD-YDY; if no, do nothing; Extract the concentration SD of water pollutants collected once within the set time, and judge whether the concentration SD of water pollutants collected once exceeds the water pollution threshold SDY; if yes, obtain the water pollution exceeding standard value SCB based on the formula SCB=SD-SDY; if no, do nothing; The average value of several calculated noise excess values ​​ZCB is calculated to obtain the average noise excess value PZCB, the average value of several calculated dust boundary thresholds YDY is calculated to obtain the average dust boundary threshold PYDY, and the average value of several calculated water pollution excess values ​​SCB is calculated to obtain the average water pollution excess value PSCB; based on the formula JYZ=σ1×ln(PZCB / ZDY+1)+σ2×ln(PYDY / YDY+1)+σ3×ln(PSCB / SDY+1), the environmental impact factor JYZ is obtained; among them, σ1, σ2, and σ3 are all proportional adjustment factors, and σ1+σ2+σ3=1.

9. The engineering data management system and method based on big data according to claim 8 is characterized in that: The issuing of early warning information based on environmental impact factors includes: B1: Extract environmental impact factor JYZ; determine whether environmental impact factor JYZ exceeds environmental judgment threshold 1; if yes, issue a warning that the project construction seriously affects the surrounding environment; if no, jump to B2; B2: Determine whether the environmental impact factor JYZ exceeds the environmental judgment threshold 2; if yes, issue a warning that the project construction will have a certain impact on the surrounding environment; if no, do not issue a warning; among them, the environmental judgment threshold 1 is greater than the environmental judgment threshold 2.

10. A method for engineering data management based on big data, based on the operation of an engineering data management system based on big data according to any one of claims 1 to 9, characterized in that: S1: Collect basic data and environmental data of the project and transfer them to the database; S2: Perform exception processing on the basic data, calculate the efficiency factor and resource utilization factor of each engineering team based on the basic data after exception processing, combine the efficiency factor and resource utilization factor into evaluation factors, and dynamically allocate the task volume to each engineering team based on the evaluation factors; S3: Analyze environmental data to obtain environmental impact factors of engineering projects, and issue early warning information based on the environmental impact factors.

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