CN112580995A - Construction safety big data monitoring system and safety risk dynamic evaluation method - Google Patents

Construction safety big data monitoring system and safety risk dynamic evaluation method Download PDF

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CN112580995A
CN112580995A CN202011545376.2A CN202011545376A CN112580995A CN 112580995 A CN112580995 A CN 112580995A CN 202011545376 A CN202011545376 A CN 202011545376A CN 112580995 A CN112580995 A CN 112580995A
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王延博
郑音
杨冬梅
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Xi'an Maple Tree Electronical Technology Development Co ltd
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Abstract

The invention discloses a construction safety big data supervision system which comprises terminals, side ends and cloud-side related equipment, wherein the terminals refer to various information acquisition systems arranged on a construction site; the side end is a centralized processor which is arranged on a construction site and has certain data processing capacity, and is used for processing information acquired by a construction site terminal to realize identification of dangerous states of the construction site; the cloud end is composed of related network servers and used for storing various information data of a construction site and displaying various information and dangerous states of the construction site. The invention also discloses a dynamic safety risk assessment method based on the construction safety big data supervision system. The system, namely the method, realizes the acquisition of construction site information and the sharing of big data, realizes the dynamic evaluation of the safety of the construction site, and improves the real-time property, the objectivity and the accuracy of the safety evaluation of the construction site.

Description

Construction safety big data monitoring system and safety risk dynamic evaluation method
Technical Field
The invention relates to the technical field of building construction safety supervision, relates to a construction safety big data supervision system, and further relates to a safety risk dynamic evaluation method based on the construction safety big data supervision system.
Background
The building industry is one of the economically important prop industries in China, however, due to the intensive construction labor and the high mobility, the safety accidents are not only of various types, but also occur randomly, and the construction safety situation is severe. The safety of a construction site relates to various factors such as human, machine, material, ring, method and the like, at present, construction safety supervision adopts an expert field inspection method to score various aspects such as equipment, personnel, material management and the like of the construction site, and then experience is utilized to compare. The mode has strong subjectivity and can not accurately reflect the safety condition of the construction site. Meanwhile, in the construction process, various state factors related to safety are likely to change at any time, and the original expert inspection mode is poor in real-time performance and cannot dynamically reflect the safety condition of a construction site. The state encouraged to pursue the intelligent construction site in 2018, and then technologies such as a hoisting machinery safety monitoring system, a labor worker real-name management system, video monitoring and environment monitoring are applied to a construction site.
At present, a digital billboard of an intelligent construction site is available, the situation of a construction site can be remotely monitored through a network, data display is simply realized, and a single point of safety risk of the construction site is monitored; however, construction safety is a multi-factor fusion, complex and dynamic problem, risk prediction by using construction site big data is an important means for preventing safety accidents, and currently, an analytic hierarchy process is adopted to evaluate construction safety, but the method has too strong subjectivity for weight determination, so that the accuracy of dynamic evaluation of construction site safety is insufficient.
Disclosure of Invention
The invention aims to provide a construction safety big data monitoring system, which solves the problems that the subjectivity of weight determination is too strong when the construction safety is evaluated in the prior art, and the accuracy of construction site safety dynamic evaluation is difficult to meet the requirement.
The invention also aims to provide a dynamic safety risk assessment method based on a construction safety big data monitoring system, which realizes construction site data acquisition, data analysis and remote end data sharing, accurately assesses the construction site safety and guides safe production monitoring work.
The technical scheme adopted by the invention is that the construction safety big data monitoring system comprises terminals, side ends and cloud-end related equipment, wherein the terminals refer to various information acquisition systems arranged on a construction site; the side end is a centralized processor which is arranged on a construction site and has certain data processing capacity, and is used for processing information acquired by a construction site terminal to realize identification of dangerous states of the construction site; the cloud end is composed of related network servers and used for storing various information data of a construction site and displaying various information and dangerous states of the construction site.
The invention adopts another technical scheme that a safety risk dynamic evaluation method based on a construction safety big data monitoring system is implemented based on the construction site big data monitoring system according to the following steps:
step 1: collecting related literature data and field accident cases, and sorting out main influence factors and probability of typical safety accidents which are most likely to occur on a construction field;
step 2: constructing a hierarchical structure model for construction safety evaluation,
constructing a hierarchical structure model for construction safety evaluation according to the construction safety influence factors and influence degrees obtained in the step 1, wherein a target layer is the safety of a construction site; the criterion layer is divided into four parts of personnel, machine equipment, management and environmental factors; the index layer is subdivided into personnel qualification, skill and experience, safety behavior, overhaul and maintenance, a safety protection device, equipment safety monitoring, safety management system execution, emergency measure training, safety training management, field arrangement, climate conditions and field working conditions;
and step 3: calculating the index evaluation weight by adopting a fuzzy analytic hierarchy process,
row and matrix H of fuzzy complementary matrix aiAnd the column sum matrix L of the fuzzy complementary matrix AjThe calculation is as follows:
Figure BDA0002855522910000031
calculating a transformation matrix BijThe expression is:
Figure BDA0002855522910000032
calculating the weight, wherein the expression is as follows:
Figure BDA0002855522910000033
calculating the weight w of the index layer by using the formula (1) and the formula (2)ijI.e. the weight of the j index under the ith criterion layer; or calculating the weight w of the criterion layeriI.e. the weight of the ith criterion layer;
and 4, step 4: intelligently scoring the evaluation index by adopting a rule engine Drools technology,
an intelligent scoring system is constructed by utilizing a Drools technology, data is called from a cloud big database, inspection is carried out according to rules, rule calculation is carried out, intelligent scoring of evaluation indexes is realized, and Q is usedijA score representing a j index under an i criterion layer;
and 5: the construction site safety is dynamically evaluated and analyzed,
obtaining a construction site dynamic index score Q by using site dynamic information acquired by a big data monitoring system and a rule engine Drools technology in step 4ijTherefore, dynamic evaluation on the safety of the construction site is realized, and the evaluation expression is as follows:
the criterion layer evaluates the score:
Figure BDA0002855522910000034
the safety assessment score of the construction site is as follows:
Figure BDA0002855522910000035
and obtaining the relevant evaluation score, namely.
The beneficial effects of the invention are as follows: 1) constructing a construction site cloud-edge-end integrated big data monitoring system, and realizing construction site information acquisition and big data sharing; 2) the construction safety dynamic evaluation method based on big data comprises the following steps: the dynamic analysis method improves the real-time performance, objectivity and accuracy of safety assessment.
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FIG. 1 is a simplified diagram of a construction site cloud-edge-end integrated big data surveillance system employed in the method of the present invention;
FIG. 2 is a model diagram of a construction safety assessment hierarchy employed in the method of the present invention;
fig. 3 is a result of dynamically evaluating the safety of the construction site by using the evaluation index weights in tables 4 and 5 according to the embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, the construction site big data monitoring system (big data monitoring system for short) based on cloud-edge-end integration adopted by the method of the present invention has a structure including terminals, edge ends and cloud-end related devices, wherein the terminals refer to various information acquisition systems (several devices located on the left side of fig. 1) arranged on a construction site, and the embodiment of fig. 1 includes devices in five aspects: construction machinery operation monitoring system (such as tower machine safety monitoring system, construction elevator safety monitoring system, face frontier defense system), face identification system (such as entrance guard face identification system, construction machinery driver identification system), job site video monitoring system, environmental monitoring system (such as raise dust noise monitoring system, poisonous and harmful gas monitoring system) and relevant safety control system (such as safety inspection APP, safety training APP, safety traffic APP and site environment management APP). The construction machinery operation monitoring system detects the operation state and the equipment maintenance state of equipment through a sensor arranged on construction equipment; the face recognition system collects face biological information of the personnel in the construction site; the construction site video monitoring system is characterized in that a video monitoring video head is arranged at a construction key point to acquire site image information in real time; the environment monitoring system is a sensor system for monitoring various humiture, dust, noise index and toxic and harmful gas arranged on a construction site and provides environment information of the construction site; the safety management system is various APP tools for recording field safety management actions.
The edge end in the construction site big data monitoring system is a centralized processor which is arranged in the middle of fig. 1 and has certain data processing capacity, processes information acquired by a construction site terminal, and realizes identification of dangerous states of the construction site, wherein the centralized processor comprises an equipment management system, a personnel management system and a dangerous behavior and AI identification system (artificial intelligence). The equipment management system transmits the information of equipment operation information through an embedded construction machinery operation monitoring system through a wireless network, and detects, alarms and controls the equipment maintenance state and the dangerous behaviors of a driver; the personnel management system manages the identity, quantity, qualification and the like of the personnel on the construction site; the dangerous behavior and AI identification system is based on construction site image information acquired by a construction site video monitoring system, and utilizes AI to identify various dangerous behaviors and dangerous states on site, such as whether to wear a safety helmet, whether to wear a safe reflective garment, whether to have hidden dangers of fire/personnel gathering and the like.
The cloud in the construction site big data supervision system refers to equipment on the right side of the figure 1, is composed of related network servers, and is used for storing various information data of a construction site and displaying various information and dangerous states of the construction site. The cloud end realizes a safety evaluation model based on construction site big data, and the safety evaluation model comprises big data storage, rule engine intelligent scoring, a safety evaluation model and information and evaluation state display.
The construction site safety dynamic evaluation method is based on the construction site big data monitoring system, firstly, relevant information data are collected to analyze construction site safety influence factors, a hierarchical structure model is constructed, and a fuzzy analytic hierarchy process is adopted to calculate the weight value of the influence factors; then, a real-time intelligent scoring rule is formulated by utilizing big data of a construction site; and finally, realizing dynamic evaluation of the safety risk of the construction site.
The method is based on the construction site big data supervision system, and is implemented according to the working principle and the following steps:
step 1: collecting relevant literature data and scene accident cases, sorting out main influence factors and probability of typical safety accidents which are most likely to occur on a construction site,
in the embodiment, the analysis of the influence factors of six typical safety accidents, namely mechanical injury, high-altitude falling, collapse, object striking, electric shock and lifting injury, is listed and is shown in a table 1;
TABLE 1 analysis of safety-affecting factors in construction sites
Influencing factor Probability of Influencing factor Probability of
Staff member 65％ Organization mechanism 10％
Mechanical equipment 55％ Environmental impact 55％
System management 70％ Material 10％
Technique of 50％ Arrangement of facilities 15％
Step 2: constructing a hierarchical structure model for construction safety evaluation,
according to the construction safety influence factors and the influence degrees obtained in the step 1, a hierarchical structure model for construction safety evaluation is constructed, as shown in figure 2, and comprises three levels;
namely, the target layer (the first layer) is safe for the construction site;
(second level) the criterion layer is divided into four parts, namely personnel, machine equipment, management and environmental factors;
and the index layer (the third layer) is formed by 12 subdivided indexes, namely personnel qualification, skill and experience, safety behavior, overhaul and maintenance, a safety protection device, equipment safety monitoring, safety management system execution, emergency measure training, safety training management, field arrangement, climate conditions and field working conditions.
And step 3: calculating the index evaluation weight by adopting a fuzzy analytic hierarchy process,
the fuzzy analytic hierarchy process calculates the weight by establishing a fuzzy complementary matrix, omits the complicated operation of consistency check, and is more convenient and accurate than the common analytic hierarchy process.
In the embodiment, a certain target of building construction safety is taken as an example and the structureFuzzy complementary matrix, the next layer of the target has m indexes of b1，b2,…,bmWith aijRepresenting element biAnd bjAnd (3) assigning according to the meaning of '0.1-0.9 scale' of the table 2 relative to the importance scale of the target to obtain a fuzzy complementary matrix: a ═ aij)m×m；
TABLE 2 values on a scale of 0.1 to 0.9
Scale Means of Scale Means of
0.5 The two indexes have the same importance 0.8 Index 1 is significantly more important than index 2
0.6 Index 1 is slightly more important than index 2 0.9 Index 1 is more important than index 2
0.7 Index 1 is more important than index 2 0.1，0.2，0.3，0.4 Inverse comparison
Row and matrix H of fuzzy complementary matrix aiAnd the column sum matrix L of the fuzzy complementary matrix AjThe calculation is as follows:
Figure BDA0002855522910000071
calculating a transformation matrix BijThe expression is:
Figure BDA0002855522910000072
calculating the weight, wherein the expression is as follows:
Figure BDA0002855522910000073
calculating the weight w of the index layer by using the formula (1) and the formula (2)ijI.e. the weight of the j index under the ith criterion layer in fig. 2; or calculating the weight w of the criterion layeriI.e. the weight of the ith criterion layer in fig. 2;
and 4, step 4: intelligently scoring the evaluation index by adopting a rule engine Drools technology,
and (3) formulating the construction safety assessment intelligent scoring rule shown in the table 3 by combining the site information acquired by the cloud-edge-end integrated big data monitoring system of the construction site shown in the figure 1.
TABLE 3 Intelligent Scoring rule for construction safety assessment
Figure BDA0002855522910000074
Figure BDA0002855522910000081
Figure BDA0002855522910000091
The rule engine Drools technology can mark and calculate a business model, an intelligent scoring system is constructed by the Drools technology at the cloud end of a cloud-edge-end integrated big data monitoring system of a construction site, data is called from a cloud end big database, inspection is carried out according to the rules of a table 3, rule calculation is carried out, intelligent scoring of 12 evaluation indexes in the graph 2 is realized, and Q is usedijThe score of the j index under the i criterion layer of fig. 2 is shown.
And 5: the construction site safety is dynamically evaluated and analyzed,
in the construction process of the project, the weighted values obtained in the step 3 are relatively fixed, but the scores of various indexes on the site change at any time, and the on-site dynamic index score Q is finally obtained by utilizing on-site dynamic information obtained by a construction site cloud-edge-end integrated big data monitoring system and the rule engine Drools technology in the step 4ijTherefore, the dynamic evaluation of the safety of the construction site in the figure 2 is realized, and the evaluation expression is as follows:
the criterion layer evaluates the score:
Figure BDA0002855522910000101
the safety assessment score of the construction site is as follows:
Figure BDA0002855522910000102
and obtaining a relevant evaluation score, wherein the larger the evaluation score is, the better the safety of the construction site is, namely.
Examples
Taking a certain project construction site of Tianjin Fuli city real estate development Limited company as an example, in order to dynamically evaluate the safety state of a construction site, a cloud-edge-end integrated big data supervision system of the construction site is constructed. There are 5 tower crowd's tower operations that have the collision relation each other at the scene of construction, 5 sets of tower machine safety monitoring systems of installation, 5 sets of construction elevator safety monitoring systems, 10 sets of construction machinery driver identification system, 2 sets of border protection system, 3 sets of entrance guard face identification system have been installed at the business turn over door, video monitoring system has been installed at 5 monitoring points in the scene of construction, 1 set of raise dust noise monitoring system, 1 cover has poisonous harmful gas monitoring system, project safety control has used safety inspection APP, safety training APP, safety traffic end APP and site environment management APP etc.. A remote big data platform is installed indoors at the project part, and the construction safety condition of the project is supervised and evaluated.
And comparing the relative importance of each index of the scheme layer and the index layer in the figure 2 to obtain a fuzzy complementary matrix, and calculating the weight of each index according to the formula (1) and the formula (2), as shown in tables 4 and 5.
TABLE 4 fuzzy complementary matrix and index weight for each index in the scheme layer
Figure BDA0002855522910000103
Figure BDA0002855522910000111
TABLE 5 fuzzy complementary matrix and index weight for each index in criterion layer
Index (I) B1 B2 B3 B4 Weight Wi
B1 0.5 0.5 0.7 0.8 0.27
B2 0.5 0.5 0.6 0.7 0.23
B3 0.3 0.4 0.5 0.4 0.2333
B4 0.2 0.3 0.6 0.5 0.2667
In the cloud end of the cloud-edge-end integrated big data monitoring system in the construction site, 4 quarters of the project in a certain year are respectively subjected to intelligent scoring to obtain a table 6, and then the evaluation index weights in the tables 4 and 5 are used for carrying out dynamic evaluation on the safety of the construction site, wherein the result is shown in fig. 3.
TABLE 6 project 4 quarterly index level Intelligent Scoring Qij
Index (I) Quarter 1 Quarter 2 Quarter 3 Quarter 4
C11 80 75 78 72
C12 88 85 72 75
C13 90 87 78 80
C21 85 80 86 75
C22 80 90 70 85
C23 86 78 75 76
C31 90 86 85 80
C32 89 90 86 82
C33 87 90 85 85
C41 85 86 89 90
C42 85 80 82 80
C43 84 87 88 91
Finally, the weights of the criterion layer and the index layer in the tables 4 and 5 and the scores of the index layer in the table 6 are used for completing the score evaluation of the safety of the construction site in different time periods according to the formulas (3) and (4), and the result is shown in fig. 3. As can be seen from FIG. 3, the whole project is safe to evaluate in this year, but with the progress of construction, the number of personnel is increased, the number of equipment is increased, the project progress requirements and safety management are relaxed, the safety score value is slightly reduced, and the project department needs to pay attention to the safety score value.
In summary, the construction safety big data monitoring system and the dynamic evaluation method of the safety risk of the invention adopt the cloud-edge-end integrated architecture to construct the construction safety big data monitoring system, and realize the construction site information acquisition and the big data sharing; meanwhile, the construction safety dynamic evaluation method based on the big data realizes dynamic evaluation of construction site safety through safety influence factor analysis, fuzzy hierarchical analysis of weight of influence factors and formulation of real-time intelligent scoring rules of the big data, and improves real-time performance, objectivity and accuracy of construction site safety evaluation.

Claims (5)

1. The utility model provides a construction safety big data supervisory systems which characterized in that: the system comprises a terminal, a side end and a cloud end, wherein the terminal refers to various information acquisition systems arranged on a construction site; the side end is a centralized processor which is arranged on a construction site and has certain data processing capacity, and is used for processing information acquired by a construction site terminal to realize identification of dangerous states of the construction site; the cloud end is composed of related network servers and used for storing various information data of a construction site and displaying various information and dangerous states of the construction site.
2. The construction safety big data supervision system according to claim 1, characterized in that: the terminal comprises five aspects of equipment: the construction machine monitoring system comprises a construction machine operation monitoring system, a face recognition system, a construction site video monitoring system, an environment monitoring system and a related safety management system;
the construction machinery operation monitoring system detects the operation state and the equipment maintenance state of equipment through a sensor arranged on construction equipment; the face recognition system collects face biological information of the personnel in the construction site; the construction site video monitoring system is characterized in that a video monitoring video head is arranged at a construction key point to acquire site image information in real time; the environment monitoring system is a sensor system for monitoring various humiture, dust, noise index and toxic and harmful gas arranged on a construction site and provides environment information of the construction site; the safety management system is various APP tools for recording field safety management actions.
3. The construction safety big data supervision system according to claim 1, characterized in that: the side end is a centralized processor which is arranged on a construction site and has certain data processing capacity, processes information acquired by a construction site terminal, and realizes identification of dangerous states of the construction site, wherein the dangerous states comprise an equipment management system, a personnel management system and a dangerous behavior and AI identification system;
the equipment management system transmits the information of equipment operation information through an embedded construction machinery operation monitoring system through a wireless network, and detects, alarms and controls the equipment maintenance state and the dangerous behaviors of a driver; the personnel management system manages the identity, quantity, qualification and the like of the personnel on the construction site; the dangerous behavior and AI identification system is used for identifying various dangerous behaviors and dangerous states on site by utilizing AI based on construction site image information acquired by a construction site video monitoring system.
4. The construction safety big data supervision system according to claim 1, characterized in that: the cloud side realizes a safety evaluation model based on construction site big data, and the safety evaluation model comprises big data storage, rule engine intelligent scoring, a safety evaluation model and information and evaluation state display.
5. A construction safety big data supervision system-based dynamic safety risk assessment method is based on the construction site big data supervision system of any one of claims 1-4, and is characterized by being implemented according to the following steps:
step 1: collecting related literature data and field accident cases, and sorting out main influence factors and probability of typical safety accidents which are most likely to occur on a construction field;
step 2: constructing a hierarchical structure model for construction safety evaluation,
constructing a hierarchical structure model for construction safety evaluation according to the construction safety influence factors and influence degrees obtained in the step 1, wherein a target layer is the safety of a construction site; the criterion layer is divided into four parts of personnel, machine equipment, management and environmental factors; the index layer is subdivided into personnel qualification, skill and experience, safety behavior, overhaul and maintenance, a safety protection device, equipment safety monitoring, safety management system execution, emergency measure training, safety training management, field arrangement, climate conditions and field working conditions;
and step 3: calculating the index evaluation weight by adopting a fuzzy analytic hierarchy process,
row and matrix H of fuzzy complementary matrix aiAnd the column sum matrix L of the fuzzy complementary matrix AjThe calculation is as follows:
Figure FDA0002855522900000021
calculating a transformation matrix BijThe expression is:
Figure FDA0002855522900000022
calculating the weight, wherein the expression is as follows:
Figure FDA0002855522900000023
calculating the weight w of the index layer by using the formula (1) and the formula (2)ijI.e. the weight of the j index under the ith criterion layer; or calculating the weight w of the criterion layeriI.e. the weight of the ith criterion layer;
and 4, step 4: intelligently scoring the evaluation index by adopting a rule engine Drools technology,
an intelligent scoring system is constructed by utilizing a Drools technology, data is called from a cloud big database, inspection is carried out according to rules, rule calculation is carried out, intelligent scoring of evaluation indexes is realized, and Q is usedijA score representing a j index under an i criterion layer;
and 5: the construction site safety is dynamically evaluated and analyzed,
obtaining a construction site dynamic index score Q by using site dynamic information acquired by a big data monitoring system and a rule engine Drools technology in step 4ijTherefore, dynamic evaluation on the safety of the construction site is realized, and the evaluation expression is as follows:
the criterion layer evaluates the score:
Figure FDA0002855522900000031
the safety assessment score of the construction site is as follows:
Figure FDA0002855522900000032
and obtaining the relevant evaluation score, namely.
CN202011545376.2A 2020-12-23 2020-12-23 Construction safety big data monitoring system and safety risk dynamic evaluation method Pending CN112580995A (en)

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CN113537729A (en) * 2021-06-24 2021-10-22 北京安捷工程咨询有限公司 Wisdom construction safety control system
CN114595994A (en) * 2022-03-18 2022-06-07 湖南工研科技有限公司 Based on thing networking wisdom building site cloud platform
CN114783144A (en) * 2022-06-17 2022-07-22 深圳市易智博网络科技有限公司 Intelligent building site safety monitoring method and device and computer equipment
CN114997682A (en) * 2022-06-15 2022-09-02 徐会君 Construction site safety monitoring system and method based on big data
CN115641001A (en) * 2022-11-05 2023-01-24 嘉泰工程技术有限公司 Risk safety assessment system for building and assessment method thereof
CN115766501A (en) * 2022-11-04 2023-03-07 四川川交路桥有限责任公司 Tunnel construction data management system and method based on big data
CN115879643A (en) * 2023-01-06 2023-03-31 中交路桥检测养护有限公司 Intelligent macroscopic safety control method and system for building Shi Gongshu
CN116405242A (en) * 2023-02-13 2023-07-07 西南石油大学 Safety state identification method for data acquisition and monitoring system

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109409756A (en) * 2018-11-02 2019-03-01 河南工程学院 Safety evaluation on building sites method based on AHP
CN111552216A (en) * 2020-05-26 2020-08-18 周中兴 Construction site intelligent supervision system based on 5G

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109409756A (en) * 2018-11-02 2019-03-01 河南工程学院 Safety evaluation on building sites method based on AHP
CN111552216A (en) * 2020-05-26 2020-08-18 周中兴 Construction site intelligent supervision system based on 5G

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刘中艳等: "基于FAHP-TOPSIS的医疗设备制造企业供应商选择研究", 湖南工业大学学报, vol. 29, no. 4, pages 90 - 95 *

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113098913A (en) * 2021-06-10 2021-07-09 睿至科技集团有限公司 Data security analysis and evaluation method and system based on data sharing service platform
CN113537729A (en) * 2021-06-24 2021-10-22 北京安捷工程咨询有限公司 Wisdom construction safety control system
CN113537729B (en) * 2021-06-24 2022-05-17 北京安捷工程咨询有限公司 Wisdom construction safety control system
CN114595994A (en) * 2022-03-18 2022-06-07 湖南工研科技有限公司 Based on thing networking wisdom building site cloud platform
CN114595994B (en) * 2022-03-18 2022-09-30 湖南工研科技有限公司 Based on thing networking wisdom building site cloud platform
CN114997682A (en) * 2022-06-15 2022-09-02 徐会君 Construction site safety monitoring system and method based on big data
CN114783144B (en) * 2022-06-17 2022-09-06 深圳市易智博网络科技有限公司 Intelligent building site safety monitoring method and device and computer equipment
CN114783144A (en) * 2022-06-17 2022-07-22 深圳市易智博网络科技有限公司 Intelligent building site safety monitoring method and device and computer equipment
CN115766501A (en) * 2022-11-04 2023-03-07 四川川交路桥有限责任公司 Tunnel construction data management system and method based on big data
CN115766501B (en) * 2022-11-04 2023-08-25 四川川交路桥有限责任公司 Tunnel construction data management system and method based on big data
CN115641001A (en) * 2022-11-05 2023-01-24 嘉泰工程技术有限公司 Risk safety assessment system for building and assessment method thereof
CN115879643A (en) * 2023-01-06 2023-03-31 中交路桥检测养护有限公司 Intelligent macroscopic safety control method and system for building Shi Gongshu
CN116405242A (en) * 2023-02-13 2023-07-07 西南石油大学 Safety state identification method for data acquisition and monitoring system

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