Digital construction site construction layout method based on Internet of Things and equipment thereof

Abstract

The invention discloses a digital construction site construction layout method and equipment based on the Internet of Things, relates to the technical field of construction management, and aims to comprehensively investigate and understand the construction site environment of a construction site. Designing a layout scheme for construction site construction according to the site environment; deploying Internet of Things monitoring equipment at a monitoring end of a construction site; an intelligent management platform for construction site layout management is built; according to the method, environmental data and construction conditions of the construction site are comprehensively obtained through site investigation, comprehensive and accurate data are provided for subsequent construction layout, data are collected through the unmanned aerial vehicle and the remote sensing equipment, it is ensured that geographic data and meteorological data of the construction site are comprehensively mastered, and the construction layout is more accurate. The obtained research data facilitates the subsequent formulation of a construction layout scheme, improves the operation efficiency and safety of a construction site, and facilitates the reasonable allocation of resources in the construction process through the checking of construction equipment and operators, so as to better carry out the construction layout.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management, and in particular to a digital construction site construction layout method and equipment based on the Internet of Things. Background Art

[0002] With the rapid development of the construction industry and the continuous advancement of information technology, the traditional construction site management model can no longer meet the safety, efficiency and precision requirements of modern engineering construction. Digital construction site layout is an advanced construction management method. It integrates Internet of Things technology, building information modeling, and big data analysis technology to realize the intelligence, refinement and visualization of the construction process. Internet of Things technology uses sensors, RFID tags, and smart devices to achieve real-time monitoring and data analysis of the construction site. Building information modeling integrates information on the entire life cycle of design, construction, operation and maintenance by creating a three-dimensional building information model. Big data analysis technology provides a scientific basis for construction management by mining and analyzing massive construction data. A Chinese patent discloses a construction site management system with application number: CN202011044196.6. This patent realizes intelligent online monitoring and management functions such as risk avoidance, analytical decision-making, correction and warning, experience summary and data feedback for engineering project management.

[0003] However, currently, when managing the construction layout of a construction site, it is impossible to effectively investigate and understand the on-site environment of the construction site, resulting in an inability to obtain environmental and climate data on the construction site. As a result, the current construction environment cannot be managed during the subsequent construction layout. At the same time, when obtaining IoT monitoring data, the traditional single data acquisition method can easily lead to incomplete data acquisition, affecting the overall layout of the construction and causing potential dangers at the construction site that cannot be discovered. Summary of the Invention

[0004] The present invention provides a digital construction site layout method and equipment based on the Internet of Things, which can effectively solve the problem raised in the above background technology that during the current construction layout management of the construction site, it is impossible to effectively investigate and understand the on-site environment of the construction site, resulting in the inability to obtain environmental data and climate data on the construction site, resulting in the inability to manage the current construction environment during the subsequent construction layout. At the same time, when obtaining Internet of Things monitoring data, the traditional single data acquisition method is likely to lead to incomplete data acquisition, affecting the overall construction layout, and also leading to the problem that potential dangers exist in the construction site but cannot be discovered.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a digital construction site layout method based on the Internet of Things, which utilizes Internet of Things technology to intelligently monitor and manage construction site construction and implement the construction layout of the digital construction site, comprising the following steps:

[0006] Step 1: Conduct a comprehensive investigation and understanding of the construction site environment;

[0007] Step 2: Design a layout plan for the construction site based on the on-site environment;

[0008] Step 3: Deploy IoT monitoring equipment at the monitoring end of the construction site;

[0009] Step 4: Build an intelligent management platform for construction site layout management;

[0010] Step five: Establish acceptance criteria and select a single pilot for verification.

[0011] According to the above technical solution, the first step is to investigate and understand the construction site environment to provide data support for the subsequent construction, specifically including collecting environmental data of the construction site and taking inventory of the construction conditions at the construction site;

[0012] When collecting environmental data on the construction site, drones and satellite remote sensing equipment are used to obtain the site's topographical features and satellite image information, as well as the site's climate data;

[0013] When taking inventory of the construction conditions at the construction site, the effective construction equipment on the construction site is counted through manual survey, and the number and location of the equipment are recorded. At the same time, the number of workers on the construction site and the types of skills required for the work are counted.

[0014] According to the above technical solution, in step 2, by designing the layout of the construction site, the resource allocation of the construction site is optimized to improve the efficiency and safety of the construction site;

[0015] When designing the construction layout, we will design a customized construction plan that meets the construction requirements of the site based on the results of the environmental survey. We will also plan the construction route and drainage system in consideration of the terrain and climate.

[0016] At the same time, the construction operation areas on the construction site are reasonably divided, and the operation types in different divided areas are clearly defined to ensure that different construction projects on the construction site can coordinate and operate synchronously to prevent interference and risks caused by cross-operation;

[0017] It is also necessary to plan the use periods of different mechanical equipment for construction work and display the planned use periods of different mechanical equipment through Gantt charts;

[0018] In addition, based on the statistical records of the number and skill types of construction site workers, the human resources required for construction site construction can be reasonably allocated, and the working hours and work locations of the workers can be planned.

[0019] According to the above technical solution, step three is to realize real-time collection of working environment and working data by deploying Internet of Things monitoring equipment on the construction site, including sensor installation, deployment of monitoring equipment and establishment of communication module.

[0020] According to the above technical solution, the installation of sensors is to install various sensors in key areas to monitor the environmental conditions of the construction site. When arranging various sensors, it is necessary to select and determine their arrangement positions according to the type of sensor, and it is necessary to follow the grid layout principle so that the range of sensor monitoring covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors;

[0021] The monitoring equipment deployment is achieved by installing video surveillance cameras and thermal imaging cameras in key areas of the construction site. The video surveillance cameras can achieve real-time and comprehensive monitoring of the construction site, while the thermal imaging cameras can monitor construction at night and provide early warning in the event of a fire.

[0022] The communication module is established by deploying a 5G wireless communication module to ensure that the data information monitored by the IoT monitoring equipment can be transmitted in a timely manner. At the same time, an edge computing gateway is deployed inside the communication module to pre-process the data.

[0023] Furthermore, the communication module internally deploys an edge computing gateway for performing dynamic priority scheduling and traffic distribution control on the data before transmission;

[0024] The data preprocessing process is based on a weighted scheduling and queue management fusion model, whose overall optimization goal is to minimize the total communication delay T total , defined as follows:

[0025]

[0026] in:

[0027] Q i (t) represents the cache length of the i-th task in the edge queue;

[0028] μ i ,λ i are service rate and arrival rate respectively;

[0029] P i is the average size of the i-th type of data packet;

[0030] B i (t) is the data bandwidth allocated to it at time t;

[0031] N is the total number of data source categories;

[0032] To ensure that all types of critical data (such as vibration, thermal imaging, and noise) can be uploaded in a timely manner with high priority, the following adaptive bandwidth allocation function is used:

[0033]

[0034] in:

[0035] B tot is the total available bandwidth;

[0036] θ i is the importance weight of the i-th category data;

[0037] τ i (t) is the waiting time of this type of data at the edge gateway;

[0038] k i is the waiting delay penalty factor;

[0039] This function also introduces a three-factor joint mechanism: task type weight, queue length, and waiting time. This achieves dynamic optimal allocation of resources and prioritizes the dispatch of key perception data when emergencies occur.

[0040] In addition, to enhance the nighttime fire monitoring capability of the construction site, the edge processing module connected to the thermal imaging device also introduces a spatial-temporal collaborative temperature anomaly recognition function, which is defined as follows:

[0041]

[0042] in:

[0043] T(x,y,t) is the current temperature value of the pixel in the thermal imaging image;

[0044] T avg (t) is the average temperature of the entire frame image;

[0045] is the spatial temperature gradient;

[0046] is the time derivative, indicating the rate of temperature rise;

[0047] α, β, and γ are weight parameters;

[0048] When S anomaly When (x, y, t) ≥ δ, the edge device automatically triggers a local alarm signal and reports it to the cloud control platform in real time through the 5G module, achieving efficient fire warning response at night;

[0049] Through the above optimization strategy, the present invention significantly improves the data transmission efficiency, abnormal response timeliness and system operation stability of the construction site Internet of Things monitoring system, and has good adaptability and scalability in complex construction scenarios;

[0050] In the edge computing module, to uniformly evaluate multi-source data from different sensors, the following weighted normalized nonlinear anomaly fusion function is proposed to comprehensively score the construction site environment status at any time:

[0051]

[0052] S MEAS(t) is the total environmental anomaly score at time t;

[0053] M is the number of sensor types;

[0054] f i (t) is the reading of the i-th sensor at time t;

[0055] μ i , σ i are the historical mean and standard deviation of this type of sensor, used for normalization;

[0056] θ i The weight of this type of data in the scoring;

[0057] ηi is the disturbance coefficient, which is used to express the influence of periodic factors;

[0058] ω i 、φ i is the frequency and phase of the disturbance term, which is used to dynamically adapt the model to the on-site rhythm;

[0059] According to S MEAS(t) The output value can be divided into warning levels:

[0060]

[0061] Among them, θ1, θ2, and θ3 are empirical thresholds, which are set based on historical data training or manual experience.

[0062] According to the above technical solution, the fourth step, when building an intelligent management platform, includes the construction of an Internet of Things platform, data analysis and processing, and construction progress and quality monitoring.

[0063] According to the above technical solution, the IoT platform construction is to build an IoT platform, access device data through a unified interface, realize the connection and management of various IoT devices, ensure the centralized processing and transmission of data, ensure data transmission security, and reduce transmission load;

[0064] The data analysis and processing utilizes big data technology to analyze and process the collected monitoring sensor data. The monitoring threshold of the networked monitoring equipment is set through big data technology. When the monitoring data collected by the monitoring equipment exceeds the threshold, an early warning is automatically triggered to identify potential dangers on the construction site and provide data support for construction management.

[0065] The construction progress and quality monitoring is to make timely adjustments and optimizations by real-time monitoring of the construction progress and quality to ensure the construction quality and progress;

[0066] Specifically, when monitoring progress and quality, delay warnings are automatically pushed by comparing the BIM model with the actual construction progress. At the same time, the actual construction accuracy is compared with the BIM model to obtain the judgment results of the construction quality.

[0067] According to the above technical solution, the fifth step is to verify the construction process of the construction site by formulating acceptance standards, and to determine whether the construction process meets the acceptance standards through verification. When specifying the acceptance standards, it is necessary to determine the data collection completeness rate, early warning accuracy rate, construction efficiency and safety accident rate;

[0068] The acceptance standards established include a data collection completeness rate of no less than 95%, an early warning accuracy rate of more than 85%, a 10% increase in construction efficiency, and a 20% reduction in the safety accident rate.

[0069] According to the above technical solution, in step 5, during the pilot verification, a single process of the construction site is selected for trial operation, and feedback data information after the process is completed is collected;

[0070] If the feedback information does not meet the acceptance criteria, it means that the acceptance result has failed. Feedback measures need to be initiated to provide feedback and continuous rectification and optimization to ensure the implementation of the construction layout of the construction site;

[0071] Specifically, when the PM2.5 level in the construction environment does not meet the acceptance standards, a spray dust suppression machine needs to be activated to achieve dust reduction;

[0072] When the displacement of the foundation pit at the construction site exceeds the threshold, an early warning is automatically triggered and the hydraulic support equipment is automatically started to make displacement adjustments.

[0073] A digital construction site layout device based on the Internet of Things includes a processor and a memory coupled to the processor, wherein the memory stores program instructions executable by the processor;

[0074] When the processor executes the program instructions stored in the memory, a digital construction site construction layout method is implemented.

[0075] Compared with the prior art, the present invention has the following beneficial effects:

[0076] 1. Through on-site surveys, we can fully obtain the environmental data and construction conditions of the construction site, which can provide a comprehensive and accurate data basis for the subsequent construction layout. The use of drones and remote sensing equipment to collect data ensures a comprehensive grasp of the geographical data and meteorological data of the construction site. The obtained survey data will facilitate the subsequent formulation of construction layout plans and improve the efficiency and safety of construction site operations. By taking inventory of construction equipment and workers, it is convenient to rationally allocate resources during the construction process, so as to better carry out the subsequent construction layout.

[0077] 2. By designing the construction layout, it is convenient to reasonably divide the construction operation area, clarify the operation types in different divided areas, avoid interference between different operation projects, and ensure the synchronous coordination between different construction operation processes. With the help of Gantt chart, the use time of different construction machinery and equipment can be effectively planned to ensure the execution efficiency of the operation tasks. The human resources required for site construction can be reasonably allocated according to the number and skill types of the operators, which facilitates the optimization of human resource allocation and ensures the safety and consistency of the construction process.

[0078] 3. By installing various sensors in key areas of the construction site to monitor the environmental conditions of the site, it is convenient to collect the working environment and working data in real time, ensure the accuracy of the sensor layout, and by following the grid layout principle, the sensor monitoring range can cover the entire construction site, ensuring the comprehensiveness of the sensor detection range. By deploying high-definition video and thermal imaging monitoring equipment, the safety of nighttime construction is improved, so as to provide timely warning of fire.

[0079] 4. Through the construction of the Internet of Things platform, unified access and management of equipment are achieved to ensure secure and reliable data transmission. With the help of big data technology, sensor data is analyzed to identify potential safety hazards, providing accurate data support for construction management. By monitoring the construction progress in real time and comparing the BIM model with the actual construction progress, early warnings are automatically issued to ensure the stability of quality and progress.

[0080] By setting quantitative acceptance standards, the quality and safety of the construction process are ensured. By reviewing the results of the pilot verification, feedback and adjustment measures can be initiated in a timely manner when the standards are not met, so as to achieve the expected construction layout.

[0081] 5. Normalize the multimodal perception data and introduce a periodic disturbance function to model the unstable environmental factors on site, which has higher robustness. The scoring output can be directly linked with the scheduling system, edge devices and on-site instructions, giving the construction site system the intelligent control capability of "self-perception, self-judgment and self-response". BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0083] In the attached figure:

[0084] Figure 1 It is a flow chart of the steps of the construction layout method of the present invention. DETAILED DESCRIPTION

[0085] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0086] Example: Figure 1 As shown, the present invention provides a technical solution, a digital construction site construction layout method based on the Internet of Things, which uses the Internet of Things technology to intelligently monitor and manage the construction site and realize the construction layout of the digital construction site, including the following steps:

[0087] Step 1: Conduct a comprehensive investigation and understanding of the construction site environment;

[0088] Step 2: Design a layout plan for the construction site based on the on-site environment;

[0089] Step 3: Deploy IoT monitoring equipment at the monitoring end of the construction site;

[0090] Step 4: Build an intelligent management platform for construction site layout management;

[0091] Step five: Establish acceptance criteria and select a single pilot for verification.

[0092] Based on the above technical solution, step one is to investigate and understand the construction site environment to provide data support for subsequent construction, including collecting environmental data on the construction site and taking inventory of the construction conditions on the construction site;

[0093] When collecting environmental data on the construction site, drones and satellite remote sensing equipment are used to obtain the site's topographical features and satellite image information, as well as the site's climate data;

[0094] When taking inventory of the construction conditions at the construction site, the effective construction equipment on the construction site is counted through manual survey, and the number and location of the equipment are recorded. At the same time, the number of workers on the construction site and the types of skills required for the work are counted.

[0095] Based on the above technical solution, in step 2, by designing the layout of the construction site, the resource allocation of the construction site is optimized to improve the efficiency and safety of the construction site;

[0096] When designing the construction layout, we will design a customized construction plan that meets the construction requirements of the site based on the results of the environmental survey. We will also plan the construction route and drainage system in consideration of the terrain and climate.

[0097] At the same time, the construction operation areas on the construction site are reasonably divided, and the operation types in different divided areas are clearly defined to ensure that different construction projects on the construction site can coordinate and operate synchronously to prevent interference and risks caused by cross-operation;

[0098] It is also necessary to plan the use periods of different mechanical equipment for construction work and display the planned use periods of different mechanical equipment through Gantt charts;

[0099] In addition, based on the statistical records of the number and skill types of construction site workers, the human resources required for construction site construction can be reasonably allocated, and the working hours and work locations of the workers can be planned.

[0100] Based on the above technical solution, step three is to realize real-time collection of working environment and working data by deploying IoT monitoring equipment on the construction site, including sensor installation, deployment of monitoring equipment and establishment of communication module.

[0101] Based on the above technical solution, the installation of sensors is to install various sensors in key areas to monitor the environmental conditions of the construction site. When arranging various sensors, it is necessary to select and determine their placement according to the type of sensor, and it is necessary to follow the grid layout principle to ensure that the sensor monitoring range covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors;

[0102] Monitoring equipment is deployed by installing video surveillance cameras and thermal imaging cameras in key areas of the construction site. The video surveillance cameras provide real-time and comprehensive monitoring of the construction site, while the thermal imaging cameras can monitor nighttime construction and provide early warning in the event of a fire.

[0103] The communication module is established by deploying 5G wireless communication modules to ensure that the data information obtained by IoT monitoring equipment can be transmitted in a timely manner. At the same time, the edge computing gateway is deployed inside the communication module to realize data preprocessing.

[0104] Furthermore, the communication module’s internally deployed edge computing gateway is used to dynamically prioritize and control traffic distribution of data before transmission, thereby improving the real-time performance, accuracy, and network stability of multi-source perception data in complex construction site environments.

[0105] The data preprocessing process is based on a weighted scheduling and queue management fusion model, whose overall optimization goal is to minimize the total communication delay T total , defined as follows:

[0106]

[0107] in:

[0108] Q i (t) represents the cache length of the i-th task in the edge queue;

[0109] μ i ,λ i are service rate and arrival rate respectively;

[0110] P i is the average size of the i-th type of data packet;

[0111] B i (t) is the data bandwidth allocated to it at time t;

[0112] N is the total number of data source categories;

[0113] To ensure that all types of critical data (such as vibration, thermal imaging, and noise) can be uploaded in a timely manner with high priority, the following adaptive bandwidth allocation function is used:

[0114]

[0115] in:

[0116] B tot is the total available bandwidth;

[0117] θ i is the importance weight of the i-th category data;

[0118] τ i (t) is the waiting time of this type of data at the edge gateway;

[0119] k i is the waiting delay penalty factor;

[0120] This function also introduces a three-factor mechanism combining task type weight, queue length, and waiting time, achieving dynamic optimal resource allocation and prioritizing the dispatch of critical sensory data when emergencies (such as hot spot anomalies and sudden noise increases) occur.

[0121] In addition, to enhance the nighttime fire monitoring capability of the construction site, the edge processing module connected to the thermal imaging device also introduces a spatial-temporal collaborative temperature anomaly recognition function, which is defined as follows:

[0122]

[0123] in:

[0124] T(x,y,t) is the current temperature value of the pixel in the thermal imaging image;

[0125] T avg (t) is the average temperature of the entire frame image;

[0126] is the spatial temperature gradient;

[0127] is the time derivative, indicating the rate of temperature rise;

[0128] α, β, and γ are weight parameters;

[0129] When S anomaly When (x, y, t) ≥ δ (set threshold), the edge device automatically triggers a local alarm signal and reports it to the cloud control platform in real time through the 5G module, achieving efficient fire warning response at night;

[0130] Through the above optimization strategy, the present invention significantly improves the data transmission efficiency, abnormal response timeliness and system operation stability of the construction site Internet of Things monitoring system, and has good adaptability and scalability in complex construction scenarios;

[0131] In the edge computing module, to uniformly evaluate multi-source data from different sensors, the following weighted normalized nonlinear anomaly fusion function is proposed to comprehensively score the construction site environment status at any time:

[0132]

[0133] S MEAS(t) is the total environmental anomaly score at time t;

[0134] M is the number of sensor types (such as temperature, humidity, noise, vibration, etc.);

[0135] f i (t) is the reading of the i-th sensor at time t;

[0136] μ i , σ i are the historical mean and standard deviation of this type of sensor, used for normalization;

[0137] θ i The weight of this type of data in the scoring (determined based on the degree of impact on construction safety);

[0138] ηi is the disturbance coefficient, which is used to express the influence of periodic factors (such as day and night temperature difference, equipment operation cycle);

[0139] ω i 、φ i is the frequency and phase of the disturbance term, which is used to dynamically adapt the model to the on-site rhythm;

[0140] According to S MEAS(t) The output value can be divided into warning levels:

[0141]

[0142] Among them, θ1, θ2, and θ3 are empirical thresholds, which can be set based on historical data training or manual experience.

[0143] Taking a subway shield construction site as a test scene, a set of IoT monitoring system with sensor layout, thermal imaging equipment deployment, edge computing and 5G communication module integration was constructed.

[0144] Sensor deployment plan and area division:

[0145] The total area of ​​the test area is 80*60=4800 square meters, divided into eight monitoring sub-areas (A1 to A8). The following sensors are deployed in each sub-area:

[0146] Sensor Type Quantity / Area Measurement indicators Installation location Temperature sensor 4 -20-80℃ Four corners of the working surface Humidity sensor 2 0-100% RH Central and border junction Noise sensor 3 30-130dB Piling area, material storage area Vibration Sensor 4 0-10g Support structure, shield machine base

[0147] Thermal imaging monitoring deployment and anomaly detection:

[0148] High-precision infrared thermal imaging cameras are installed in sub-areas A5 and A6, and their visual range covers construction machinery, temporary electrical boxes, and night work areas.

[0149] At 10:31 PM on May 15th, the thermal imaging equipment captured a local temperature rise anomaly. The data for a certain point in the temperature image is as follows:

[0150] T(x,y,t)=89.6℃;

[0151] T avg (t) = 45.3 °C;

[0152]

[0153] Substitute the above data into the anomaly scoring function:

[0154] Taking the empirical parameters α=0.5, β=0.3, γ=0.2, we can calculate:

[0155] S anomaly =980.45+60.46+14.8=1055.71

[0156] According to the set threshold δ=800, the secondary warning mechanism is triggered, and the alarm information is automatically pushed to the on-duty personnel terminal, and the low-voltage power-off protection program is activated at the same time.

[0157] Environmental anomaly fusion score calculation:

[0158] At the same time, the A5 area sensor sent back the following real-time data (all averaged within one minute):

[0159] index reading <![CDATA[Historical mean μ i > <![CDATA[Standard deviation σ i > <![CDATA[Weight ω i <!-- 8 -->]]> temperature 47.2℃ 43.6℃ 2.1 0.3 humidity 91％ 74％ 6.2 0.1 noise 109dB 92dB 7.5 0.2 vibration 6.3g 3.8g 1.9 0.4

[0160] Substitute into the abnormal fusion scoring function (without considering the disturbance term):

[0161] S MEAS = = 2.59

[0162] Combined level settings:

[0163] Normal range: S<3.5

[0164] Level 1 warning: $.5≤S<6

[0165] Level 2 and above: S≥6

[0166] Therefore, this round of detection triggers a level one warning, and the area is marked as a key observation area in the edge computing gateway. If the score continues to rise for five consecutive minutes, it will be automatically raised to a level two warning.

[0167] Successfully implemented a comprehensive joint scoring mechanism for multi-source environmental data such as temperature, humidity, noise, and vibration;

[0168] Thermal imaging equipment can automatically trigger power-off protection and alarm mechanisms after identifying anomalies;

[0169] The overall system response time is less than 3 seconds, bandwidth utilization is increased by about 28%, and the false alarm rate is reduced by 43%, demonstrating extremely high engineering adaptability and practical deployment value.

[0170] Based on the above technical solution, step four, when building an intelligent management platform, includes the construction of the Internet of Things platform, data analysis and processing, and construction progress and quality monitoring.

[0171] Based on the above technical solution, the construction of the IoT platform is to build an IoT platform, access device data through a unified interface, realize the connection and management of various IoT devices, ensure the centralized processing and transmission of data, ensure data transmission security, and reduce transmission load;

[0172] Data analysis and processing uses big data technology to analyze and process the collected monitoring sensor data. This technology is used to set the monitoring threshold of networked monitoring equipment. When the monitoring data collected by the monitoring equipment exceeds the threshold, an early warning is automatically triggered to identify potential dangers on the construction site and provide data support for construction management.

[0173] Construction progress and quality monitoring is to make timely adjustments and optimizations by real-time monitoring of construction progress and quality to ensure construction quality and progress;

[0174] Specifically, when monitoring progress and quality, delay warnings are automatically pushed by comparing the BIM model with the actual construction progress. At the same time, the actual construction accuracy is compared with the BIM model to obtain the judgment results of the construction quality.

[0175] Based on the above technical solution, step five is to verify the construction process of the construction site by formulating acceptance standards. The verification determines whether the construction process meets the acceptance standards. When specifying the acceptance standards, it is necessary to determine the data collection completeness rate, early warning accuracy rate, construction efficiency and safety accident rate;

[0176] The acceptance standards established include a data collection completeness rate of no less than 95%, an early warning accuracy rate of more than 85%, a 10% increase in construction efficiency, and a 20% reduction in the safety accident rate.

[0177] Based on the above technical solution, in step five, during the pilot verification, a single process of the construction site is selected for trial operation, and feedback data information after the process is completed is collected;

[0178] If the feedback information does not meet the acceptance criteria, it means that the acceptance result has failed. Feedback measures need to be initiated to provide feedback and continuous rectification and optimization to ensure the implementation of the construction layout of the construction site;

[0179] Specifically, when the PM2.5 level in the construction environment does not meet the acceptance standards, a spray dust suppression machine needs to be activated to achieve dust reduction;

[0180] When the displacement of the foundation pit at the construction site exceeds the threshold, an early warning is automatically triggered and the hydraulic support equipment is automatically started to make displacement adjustments.

[0181] A digital construction site layout device based on the Internet of Things includes a processor and a memory coupled to the processor, wherein the memory stores program instructions that can be executed by the processor;

[0182] The processor implements the digital construction site construction layout method when executing the program instructions stored in the memory.

[0183] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A digital construction site layout method based on the Internet of Things, characterized by: Using IoT technology to intelligently monitor and manage construction sites and implement digital construction site layout includes the following steps: Step 1: Conduct a comprehensive investigation and understanding of the construction site environment; Step 2: Design a layout plan for the construction site based on the on-site environment; Step 3: Deploy IoT monitoring equipment at the monitoring end of the construction site; Step 4: Build an intelligent management platform for construction site layout management; Step five: Establish acceptance criteria and select a single pilot for verification.

2. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: Step 1 is to investigate and understand the construction site environment to provide data support for the subsequent construction, including collecting environmental data on the construction site and taking inventory of the construction conditions on the construction site; When collecting environmental data on the construction site, drones and satellite remote sensing equipment are used to obtain the site's topographical features and satellite image information, as well as the site's climate data; When taking inventory of the construction conditions at the construction site, the effective construction equipment on the construction site is counted through manual survey, and the number and location of the equipment are recorded. At the same time, the number of workers on the construction site and the types of skills required for the work are counted.

3. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: The second step is to optimize the resource allocation of the construction site by designing the layout of the construction site, thereby improving the efficiency and safety of the construction site; When designing the construction layout, we will design a customized construction plan that meets the construction requirements of the site based on the results of the environmental survey. We will also plan the construction route and drainage system in consideration of the terrain and climate. At the same time, the construction operation areas on the construction site are reasonably divided, and the operation types in different divided areas are clearly defined to ensure that different construction projects on the construction site can coordinate and operate synchronously to prevent interference and risks caused by cross-operation; It is also necessary to plan the use periods of different mechanical equipment for construction work and display the planned use periods of different mechanical equipment through Gantt charts; In addition, based on the statistical records of the number and skill types of construction site workers, the human resources required for construction site construction can be reasonably allocated, and the working hours and work locations of the workers can be planned.

4. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: The third step is to realize real-time collection of working environment and working data by deploying Internet of Things monitoring equipment on the construction site, including sensor installation, deployment of monitoring equipment and establishment of communication modules.

5. The method for digital construction site layout based on the Internet of Things according to claim 4, characterized in that: The installation of sensors is to install various sensors in key areas to monitor the environmental conditions of the construction site. When arranging various sensors, it is necessary to select and determine their placement positions according to the type of sensor, and it is necessary to follow the grid layout principle so that the range of sensor monitoring covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors; The monitoring equipment deployment is achieved by installing video surveillance cameras and thermal imaging cameras in key areas of the construction site. The video surveillance cameras can achieve real-time and comprehensive monitoring of the construction site, while the thermal imaging cameras can monitor construction at night and provide early warning in the event of a fire. The communication module is established by deploying a 5G wireless communication module to ensure that the data information monitored by the IoT monitoring equipment can be transmitted in a timely manner. At the same time, an edge computing gateway is deployed inside the communication module to pre-process the data. Furthermore, the communication module internally deploys an edge computing gateway for performing dynamic priority scheduling and traffic distribution control on the data before transmission; The data preprocessing process is based on a weighted scheduling and queue management fusion model, whose overall optimization goal is to minimize the total communication delay T total , defined as follows: in: Q i (t) represents the cache length of the i-th task in the edge queue; μ i ,λ i are service rate and arrival rate respectively; P i is the average size of the i-th type of data packet; B i (t) is the data bandwidth allocated to it at time t; N is the total number of data source categories; To ensure that all types of critical data (such as vibration, thermal imaging, and noise) can be uploaded in a timely manner with high priority, the following adaptive bandwidth allocation function is used: in: B tot is the total available bandwidth; θ i is the importance weight of the i-th category data; τ i (t) is the waiting time of this type of data at the edge gateway; k i is the waiting delay penalty factor; This function also introduces a three-factor joint mechanism: task type weight, queue length, and waiting time. This achieves dynamic optimal allocation of resources and prioritizes the dispatch of key perception data when emergencies occur. In addition, to enhance the nighttime fire monitoring capability of the construction site, the edge processing module connected to the thermal imaging device also introduces a spatial-temporal collaborative temperature anomaly recognition function, which is defined as follows: in: T(x,y,t) is the current temperature value of the pixel in the thermal imaging image; T avg (t) is the average temperature of the entire frame image; is the spatial temperature gradient; is the time derivative, indicating the rate of temperature rise; α, β, and γ are weight parameters; When S anomaly When (x, y, t) ≥ δ, the edge device automatically triggers a local alarm signal and reports it to the cloud control platform in real time through the 5G module, achieving efficient fire warning response at night; Through the above optimization strategy, the present invention significantly improves the data transmission efficiency, abnormal response timeliness and system operation stability of the construction site Internet of Things monitoring system, and has good adaptability and scalability in complex construction scenarios; In the edge computing module, to uniformly evaluate multi-source data from different sensors, the following weighted normalized nonlinear anomaly fusion function is proposed to comprehensively score the construction site environment status at any time: S MEAS(t) is the total environmental anomaly score at time t; M is the number of sensor types; f i (t) is the reading of the i-th sensor at time t; μ i , σ i are the historical mean and standard deviation of this type of sensor, used for normalization; θ i The weight of this type of data in the scoring; ηi is the disturbance coefficient, which is used to express the influence of periodic factors; ω i 、φ i is the frequency and phase of the disturbance term, which is used to dynamically adapt the model to the on-site rhythm; According to S MEAS(t) The output value can be divided into warning levels: Among them, θ1, θ2, and θ3 are empirical thresholds, which are set based on historical data training or manual experience.

6. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: The fourth step, when building an intelligent management platform, includes the construction of an Internet of Things platform, data analysis and processing, and construction progress and quality monitoring.

7. The method for digital construction site layout based on the Internet of Things according to claim 6, characterized in that: The IoT platform construction is to build an IoT platform, access device data through a unified interface, realize the connection and management of various IoT devices, ensure the centralized processing and transmission of data, ensure data transmission security, and reduce transmission load; The data analysis and processing utilizes big data technology to analyze and process the collected monitoring sensor data. The monitoring threshold of the networked monitoring equipment is set through big data technology. When the monitoring data collected by the monitoring equipment exceeds the threshold, an early warning is automatically triggered to identify potential dangers on the construction site and provide data support for construction management. The construction progress and quality monitoring is to make timely adjustments and optimizations by real-time monitoring of the construction progress and quality to ensure the construction quality and progress; Specifically, when monitoring progress and quality, delay warnings are automatically pushed by comparing the BIM model with the actual construction progress. At the same time, the actual construction accuracy is compared with the BIM model to obtain the judgment results of the construction quality.

8. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: Step five is to verify the construction process of the construction site by formulating acceptance standards, and to determine whether the construction process meets the acceptance standards through verification. When specifying the acceptance standards, it is necessary to determine the data collection completeness rate, early warning accuracy rate, construction efficiency and safety accident rate; The acceptance standards established include a data collection completeness rate of no less than 95%, an early warning accuracy rate of more than 85%, a 10% increase in construction efficiency, and a 20% reduction in the safety accident rate.

9. The method for digital construction site layout based on the Internet of Things according to claim 8, characterized in that: In step 5, during the pilot verification, a single process of the construction site is selected for trial operation, and feedback data information after the process is completed is collected; If the feedback information does not meet the requirements of the acceptance standards, it means that the acceptance result has failed, and feedback measures need to be initiated to provide feedback, and continuous rectification and optimization should be carried out to ensure the implementation of the construction layout of the construction site.

10. A digital construction site layout device based on the Internet of Things, characterized by: comprising a processor and a memory coupled to the processor, wherein the memory stores program instructions executable by the processor; When the processor executes the program instructions stored in the memory, the digital construction site construction layout method according to any one of claims 1 to 9 is implemented.

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