Digital construction site construction layout method based on internet of things and device thereof

Abstract

The application 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 comprehensively investigates and understands the construction site environment; a layout scheme for the construction site construction is designed according to the site environment; the Internet of Things monitoring equipment is deployed at the monitoring end of the construction site; an intelligent management platform for the construction site layout management is built; acceptance standards are formulated and a single pilot is selected for verification; the application comprehensively obtains environmental data and construction conditions of the construction site through field investigation, provides comprehensive and accurate data for subsequent construction layout, uses the unmanned aerial vehicle and remote sensing equipment to collect data, ensures comprehensive grasp of geographical data and meteorological data of the construction site, and facilitates subsequent formulation of the construction layout scheme, improves the operation efficiency and safety of the construction site, and through inventory of the construction equipment and workers, resources can be reasonably configured in the construction process, so that the construction layout is better.

Description

Technical Field

[0001] This invention relates to the field of construction management technology, specifically to a digital construction site layout method and equipment based on the Internet of Things. Background Technology

[0002] With the rapid development of the construction industry and the continuous advancement of information technology, traditional construction site management models can no longer meet the requirements of modern engineering construction for safety, efficiency, and precision. Digital construction site layout is an advanced construction management method that integrates Internet of Things (IoT) technology, Building Information Modeling (BIM), and big data analytics to achieve intelligent, refined, and visualized construction processes. IoT technology uses sensors, RFID tags, and smart devices to achieve real-time monitoring and data analysis of the construction site. BIM integrates information from the entire lifecycle of design, construction, and operation and maintenance by creating a three-dimensional building information model. Big data analytics provides a scientific basis for construction management by mining and analyzing massive amounts of construction data. A Chinese patent discloses a construction site management system, application number CN202011044196.6, which realizes intelligent online monitoring and management functions such as risk avoidance, analysis and decision-making, correction and early warning, experience summarization, and data feedback for engineering project management.

[0003] However, in current construction site layout management, the inability to effectively survey and understand the on-site environment of the construction site leads to the inability to obtain environmental and climate data. This results in the inability to manage the current construction environment during subsequent construction layout. At the same time, when acquiring IoT monitoring data, the traditional single data acquisition method is prone to incomplete data acquisition, affecting the overall construction layout and causing potential dangers at the construction site to go undetected. Summary of the Invention

[0004] This invention provides a digital construction site layout method and equipment based on the Internet of Things (IoT). It can effectively solve the problems mentioned in the background art, such as the inability to effectively investigate and understand the on-site environment of the construction site, resulting in the inability to obtain environmental and climate data, which leads to the inability to manage the current construction environment during subsequent construction layout. At the same time, when acquiring IoT monitoring data, the traditional single data acquisition method is prone to incomplete data acquisition, affecting the overall construction layout and causing potential dangers at the construction site to go undetected.

[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 (IoT), which utilizes IoT technology to intelligently monitor and manage construction site operations, thereby realizing a digital construction site layout, comprising the following steps:

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

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

[0008] Step 3: Deploy IoT monitoring equipment at the monitoring terminal on the construction site;

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

[0010] Step 5: Develop acceptance criteria and select a single pilot project for verification.

[0011] According to the above technical solution, step one involves conducting a survey of the construction site environment to provide data support for subsequent work. This includes collecting environmental data from the construction site and taking stock of the construction conditions at the site.

[0012] When collecting environmental data at the construction site, we use drones and satellite remote sensing equipment to obtain terrain features and satellite imagery information, as well as climate data.

[0013] When assessing the construction conditions at the construction site, an inventory of the available construction equipment is conducted through manual inspection, and the quantity and location of the equipment are recorded. At the same time, statistics are compiled on the number of workers on site and the types of skills they perform.

[0014] According to the above technical solution, step two involves optimizing the resource allocation of the construction site by designing the site layout, thereby improving the operational efficiency and safety of the construction site.

[0015] When designing the construction layout, a customized construction plan that meets the site construction requirements is designed based on the results of the environmental survey. The construction route and drainage system are planned in combination with the terrain and climate.

[0016] At the same time, the construction work areas on the construction site are reasonably divided, and the types of work in different areas are clearly defined to ensure that different construction work projects on the construction site can work in a coordinated and synchronous manner, and to prevent interference and risks caused by cross-operations.

[0017] It is also necessary to plan the usage periods of different mechanical equipment in construction operations, and to display the planned usage periods of different mechanical equipment through Gantt charts;

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

[0019] According to the above technical solution, step three involves deploying IoT monitoring equipment on the construction site to achieve real-time collection of the working environment and work data, including sensor installation, deployment of monitoring equipment, and establishment of communication modules.

[0020] According to the above technical solution, the installation of sensors involves installing various types of 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 to follow the grid layout principle so that the sensing and monitoring range covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors.

[0021] The 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 coverage monitoring of the construction site, while the thermal imaging cameras can monitor nighttime construction and provide early warning in the event of a fire.

[0022] The establishment of the communication module is achieved by deploying a 5G wireless communication module to ensure that the data information acquired by the IoT monitoring device can be transmitted in a timely manner. At the same time, an edge computing gateway is deployed inside the communication module to preprocess the data.

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

[0024] The data preprocessing process is based on a weighted scheduling and queue management fusion model, and its overall optimization objective is to minimize the total communication latency T. total The definition is as follows:

[0025]

[0026] in:

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

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

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

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

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

[0032] To ensure that various 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 adopted:

[0033]

[0034] in:

[0035] B tot Total available bandwidth;

[0036] θ i The importance weight of the i-th data type;

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

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

[0039] This function introduces a three-factor joint mechanism of task type weight, queue length and waiting time, which realizes dynamic optimal allocation of resources and can prioritize the scheduling of critical sensing data when emergencies occur.

[0040] In addition, to enhance the ability to monitor fires at construction sites at night, the edge processing module connected to the thermal imaging equipment also introduces a space-time collaborative temperature anomaly identification function, defined as follows:

[0041]

[0042] in:

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

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

[0045] For space temperature gradient;

[0046] The time derivative represents the rate of temperature increase;

[0047] α, β, and γ are weighting 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 via the 5G module, achieving efficient fire early warning response at night;

[0049] Through the above optimization strategies, this invention significantly improves the data transmission efficiency, anomaly response timeliness, and system operation stability of the construction site IoT 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 provide an overall score for the site environment status at any given time:

[0051]

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

[0053] M represents the number of sensor types;

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

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

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

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

[0058] ω i φ i The frequency and phase of this disturbance term are used to dynamically adapt the model to the on-site rhythm.

[0059] According to S MEAS(t) The output value can be used to classify the warning level:

[0060]

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

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

[0063] According to the above technical solution, the construction of the Internet of Things (IoT) platform involves building an IoT platform that uses a unified interface to access device data, enabling the connection and management of various IoT devices, ensuring centralized data processing and transmission, guaranteeing data transmission security, and reducing transmission load.

[0064] The data analysis and processing utilizes big data technology to analyze and process the collected monitoring sensor data. By setting monitoring thresholds for networked monitoring devices through big data technology, an early warning is automatically triggered when the monitoring data collected by the monitoring devices exceeds the threshold, identifying potential hazards at the construction site and providing data support for construction management.

[0065] The construction progress and quality monitoring involves real-time monitoring of construction progress and quality to make timely adjustments and optimizations, thereby ensuring both construction quality and progress.

[0066] Specifically, when monitoring progress and quality, the system automatically pushes delay warnings by comparing the BIM model with the actual construction progress. At the same time, it compares the actual construction accuracy with the BIM model to obtain the judgment result of construction quality.

[0067] According to the above technical solution, step five is to verify the construction procedures at the construction site by formulating acceptance standards. The verification is used to determine whether the construction procedures meet 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.

[0068] The established acceptance criteria 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 five, when conducting pilot verification, a single construction process at 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 established acceptance standards, it means that the acceptance result is unsuccessful. Feedback measures need to be initiated to provide feedback, and continuous rectification and optimization should be carried out to ensure the effective implementation of the construction layout on the site.

[0071] Specifically, when the PM2.5 level in the construction site environment does not meet the acceptance standards, it is necessary to start the spray dust suppression machine to reduce dust.

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

[0073] A digital construction site layout device based on the Internet of Things includes a processor and a memory coupled to the processor, the memory storing program instructions that can be executed by the processor;

[0074] The processor implements a digital construction site layout method when it executes the program instructions stored in the memory.

[0075] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0076] 1. Comprehensive on-site surveys are conducted to obtain environmental data and construction conditions at the construction site, providing a comprehensive and accurate data foundation for subsequent construction layout. The use of drones and remote sensing equipment to collect data ensures a complete understanding of the geographical and meteorological data of the construction site. The obtained survey data facilitates the development of subsequent construction layout plans, improving the operational efficiency and safety of the construction site. Furthermore, inventorying construction equipment and personnel facilitates the rational allocation of resources during the construction process, enabling better subsequent construction layout.

[0077] 2. By designing the construction layout, it is convenient to rationally divide the construction work areas, clarify the work types of different areas, avoid interference between different work projects, and ensure the synchronous and coordinated progress of different construction work procedures. With the help of Gantt charts, the usage time of different construction machinery and equipment can be effectively planned to ensure the efficiency of work tasks. Furthermore, the human resources required for construction can be rationally allocated according to the number and skill types of workers, which facilitates the optimization of human resource allocation and ensures the safety and continuity of the construction process.

[0078] 3. By installing various sensors in key areas of the construction site, the environmental conditions of the construction site can be monitored, which facilitates the real-time collection of work environment and work data, ensures the accuracy of sensor placement, and ensures the comprehensiveness of sensor detection range by following the grid layout principle so that the sensor monitoring range can cover the entire construction site. Furthermore, by deploying high-definition video and thermal imaging monitoring equipment, the safety of nighttime construction can be improved so as to provide timely fire warnings.

[0079] 4. By building an IoT platform, we can achieve unified access and management of equipment, ensure secure and reliable data transmission, analyze sensor data with big data technology, identify potential safety hazards, provide accurate data support for construction management, monitor construction progress in real time, compare the BIM model with the actual construction progress, and automatically push early warnings to ensure the stability of quality and schedule.

[0080] By setting quantitative acceptance standards, the quality and safety of construction procedures are ensured. Furthermore, by reviewing the results of pilot verifications, feedback and adjustment measures can be initiated in a timely manner when standards are not met, thus facilitating the achievement of the expected building construction layout.

[0081] 5. The multimodal sensing data is normalized and a periodic disturbance function is introduced to model 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 commands, giving the construction site system the intelligent control capability of "self-sensing, self-judgment and self-response". Attached Figure Description

[0082] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0083] In the attached diagram:

[0084] Figure 1 This is a flowchart of the construction layout method of the present invention. Detailed Implementation

[0085] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0086] Example: Figure 1 As shown, this invention provides a technical solution: a digital construction site layout method based on the Internet of Things (IoT). This method utilizes IoT technology for intelligent monitoring and management of construction sites, realizing a digital construction site layout. The method includes the following steps:

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

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

[0089] Step 3: Deploy IoT monitoring equipment at the monitoring terminal on the construction site;

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

[0091] Step 5: Develop acceptance criteria and select a single pilot project for verification.

[0092] Based on the above technical solution, the first step is to conduct a survey of the construction site environment to provide data support for the subsequent work. This includes collecting environmental data of the construction site and taking stock of the construction conditions at the construction site.

[0093] When collecting environmental data at the construction site, we use drones and satellite remote sensing equipment to obtain terrain features and satellite imagery information, as well as climate data.

[0094] When assessing the construction conditions at the construction site, an inventory of the available construction equipment is conducted through manual inspection, and the quantity and location of the equipment are recorded. At the same time, statistics are compiled on the number of workers on site and the types of skills they perform.

[0095] Based on the above technical solution, step two involves optimizing the resource allocation at the construction site by designing the site layout, thereby improving the operational efficiency and safety of the site.

[0096] When designing the construction layout, a customized construction plan that meets the site construction requirements is designed based on the results of the environmental survey. The construction route and drainage system are planned in combination with the terrain and climate.

[0097] At the same time, the construction work areas on the construction site are reasonably divided, and the types of work in different areas are clearly defined to ensure that different construction work projects on the construction site can work in a coordinated and synchronous manner, and to prevent interference and risks caused by cross-operations.

[0098] It is also necessary to plan the usage periods of different mechanical equipment in construction operations, and to display the planned usage periods of different mechanical equipment through Gantt charts;

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

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

[0101] Based on the above technical solution, the installation of sensors involves installing various types of 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 to follow the grid layout principle so that the sensing and monitoring range covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors.

[0102] The deployment of monitoring equipment involves installing video surveillance cameras and thermal imaging cameras in key areas of the construction site. The video surveillance cameras provide real-time and comprehensive coverage 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 a 5G wireless communication module to ensure the timely transmission of data acquired by IoT monitoring devices. Simultaneously, an edge computing gateway is deployed within the communication module to preprocess the data.

[0104] Furthermore, the communication module is internally deployed with an edge computing gateway for dynamic priority scheduling and traffic distribution control of the data before transmission, so as to improve the real-time performance, accuracy and network stability of multi-source sensing data in complex construction site environments.

[0105] The data preprocessing process is based on a weighted scheduling and queue management fusion model, and its overall optimization objective is to minimize the total communication latency T. total The definition is as follows:

[0106]

[0107] in:

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

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

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

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

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

[0113] To ensure that various 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 adopted:

[0114]

[0115] in:

[0116] B tot Total available bandwidth;

[0117] θ i The importance weight of the i-th data type;

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

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

[0120] This function introduces a three-factor joint mechanism of task type weight, queue length and waiting time, which realizes dynamic optimal allocation of resources and can prioritize scheduling of key sensing data when sudden events (such as hot spot anomalies or noise surges) occur.

[0121] In addition, to enhance the ability to monitor fires at construction sites at night, the edge processing module connected to the thermal imaging equipment also introduces a space-time collaborative temperature anomaly identification function, defined as follows:

[0122]

[0123] in:

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

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

[0126] For space temperature gradient;

[0127] The time derivative represents the rate of temperature increase;

[0128] α, β, and γ are weighting 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 via the 5G module, achieving efficient fire early warning response at night;

[0130] Through the above optimization strategies, this invention significantly improves the data transmission efficiency, anomaly response timeliness, and system operation stability of the construction site IoT 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 provide an overall score for the site environment status at any given time:

[0132]

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

[0134] M represents the number of sensor types (e.g., temperature, humidity, noise, vibration, etc.);

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

[0136] μ i σ i These 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 its impact on construction safety);

[0138] ηi is the disturbance coefficient, used to express the influence of periodic factors (such as diurnal temperature range, equipment operating cycle);

[0139] ω i φ i The frequency and phase of this disturbance term are used to dynamically adapt the model to the on-site rhythm.

[0140] According to S MEAS(t) The output value can be used to classify the warning level:

[0141]

[0142] θ1, θ2, and θ3 are empirical thresholds, which can be trained based on historical data or set manually based on experience.

[0143] Using a subway tunnel construction site as a test scenario, we built an IoT monitoring system that integrates sensor deployment, thermal imaging equipment deployment, edge computing, and 5G communication modules.

[0144] Sensor deployment scheme and area division:

[0145] The total area of ​​the test area is 80*60=4800 square meters, divided into 8 monitoring sub-areas (A1~A8); the following sensors are deployed in each sub-area:

[0146] Sensor type Number / area Measurement indicator Installation location Temperature sensor 4 -20-80℃ Four corners of the work face Humidity sensor 2 0-100% RH Middle, boundary junction Noise sensor 3 30-130 dB Pile area, material storage area Vibration sensor 4 0-10g Support structure, shield machine base

[0147] Thermal imaging surveillance deployment and anomaly detection:

[0148] High-precision infrared thermal imaging cameras were installed in sub-areas A5 and A6, covering construction machinery, temporary electrical boxes, and nighttime work areas.

[0149] At 22:31 on May 15th, the thermal imaging equipment captured an abnormal local temperature rise. 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℃;

[0152]

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

[0154] Using empirical parameters α = 0.5, β = 0.3, and γ = 0.2, the following calculations were performed:

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

[0156] Based on the set threshold δ=800, the secondary early warning mechanism is triggered, automatically pushing alarm information to the duty personnel's terminal, and at the same time activating the low-voltage power failure protection program.

[0157] Environmental anomaly fusion score calculation:

[0158] At the same time, the sensors in area A5 transmitted the following real-time data (all averaged over one minute):

[0159] Indicator Reading Historical mean μ i ]] Standard deviation σ i ]] weight ω i ]]> Temperature 47.2℃ 43.6℃ 2.1 0.3 Humidity 91％ 74％ 6.2 0.1 Noise 109 dB 92 dB 7.5 0.2 Vibration 6.3g 3.8g 1.9 0.4

[0160] Substituting into the anomaly fusion scoring function (ignoring the perturbation term):

[0161] S MEAS ==2.59

[0162] Combined with 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 triggered a Level 1 warning, and the area was marked as a key observation area in the edge computing gateway. If the score continues to rise within five consecutive minutes, it will be automatically upgraded to a Level 2 warning.

[0167] A joint scoring mechanism for multi-source environmental data, including temperature, humidity, noise, and vibration, has been successfully implemented.

[0168] Thermal imaging equipment can automatically trigger power-off protection and alarm mechanisms after identifying an anomaly.

[0169] The system's overall response time is less than 3 seconds, bandwidth utilization is improved 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 solutions, step four, in building an intelligent management platform, includes the construction of an Internet of Things platform, data analysis and processing, and monitoring of construction progress and quality.

[0171] Based on the above technical solutions, the construction of an IoT platform involves building an IoT platform that uses a unified interface to access device data, enabling the connection and management of various IoT devices, ensuring centralized data processing and transmission, guaranteeing data transmission security, and reducing transmission load.

[0172] Data analysis and processing utilizes big data technology to analyze and process the collected monitoring sensor data. By setting monitoring thresholds for networked monitoring devices through big data technology, an early warning is automatically triggered when the monitoring data collected by the monitoring devices exceeds the threshold, identifying potential hazards at the construction site and providing data support for construction management.

[0173] Construction progress and quality monitoring involves real-time monitoring of construction progress and quality to make timely adjustments and optimizations, thereby ensuring both construction quality and schedule.

[0174] Specifically, when monitoring progress and quality, the system automatically pushes delay warnings by comparing the BIM model with the actual construction progress. At the same time, it compares the actual construction accuracy with the BIM model to obtain the judgment result of construction quality.

[0175] Based on the above technical solution, step five is to verify the construction procedures at the construction site by formulating acceptance standards. The verification is used to determine whether the construction procedures meet 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 established acceptance criteria 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, when conducting pilot verification, a single construction process at 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 established acceptance standards, it means that the acceptance result is unsuccessful. Feedback measures need to be initiated to provide feedback, and continuous rectification and optimization should be carried out to ensure the effective implementation of the construction layout on the site.

[0179] Specifically, when the PM2.5 level in the construction site environment does not meet the acceptance standards, it is necessary to start the spray dust suppression machine to reduce dust.

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

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

[0182] The processor executes program instructions stored in memory to implement a digital construction site layout method.

[0183] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A digital construction site layout method based on the Internet of Things, characterized in that: Using IoT technology to intelligently monitor and manage construction sites, and to realize the construction layout of digital construction sites, includes the following steps: Step 1: Conduct a comprehensive survey and understanding of the construction site environment; Step two: Design a layout plan for the construction site based on the site environment; Step 3: Deploy IoT monitoring equipment at the monitoring terminal on the construction site; Step 4: Establish an intelligent management platform for construction site layout management; Step 5: Develop acceptance criteria and select a single pilot project for verification; Step three involves deploying IoT monitoring devices at the construction site to achieve real-time collection of the working environment and work data, including sensor installation, deployment of monitoring equipment, and establishment of communication modules. The establishment of the communication module is achieved by deploying a 5G wireless communication module to ensure that the data information acquired by the IoT monitoring device can be transmitted in a timely manner. At the same time, an edge computing gateway is deployed inside the communication module to preprocess the data. Furthermore, the communication module internally deploys an edge computing gateway for dynamic priority scheduling and traffic distribution control of data before transmission; The data preprocessing process is based on a weighted scheduling and queue management fusion model, with the overall optimization objective being to minimize the total communication latency. The definition is as follows: in: This represents the cache length of the i-th type of task in the edge queue; These are service rate and arrival rate, respectively. Let i be the average size of the i-th type of data packet; The data bandwidth allocated to it at time t; N represents the total number of data source categories; To ensure that all types of critical data are uploaded in a timely manner with high priority, the following adaptive bandwidth allocation function is adopted: in: Total available bandwidth; The importance weight of the i-th data type; This refers to the waiting time for this type of data at the edge gateway; This is the waiting delay penalty factor; In addition, to enhance the ability to monitor fires at construction sites at night, the edge processing module connected to the thermal imaging equipment also introduces a space-time collaborative temperature anomaly identification function, defined as follows: in: This represents the current temperature value of a pixel in the thermal imaging image. The average temperature of the entire image frame; For space temperature gradient; The time derivative represents the rate of temperature increase; α, β, and γ are weighting parameters; when At that time, the edge device automatically triggers a local alarm signal and reports it to the cloud control platform in real time through the 5G module, realizing efficient fire early warning response at night; In the edge computing module, the following weighted normalized nonlinear anomaly fusion function is proposed to perform an overall score on the site environment status at any given time: The total environmental anomaly score at time t; M represents the number of sensor types; Let be the reading of the i-th sensor at time t; , These are the historical mean and standard deviation of this type of sensor, used for normalization; Assigning the weight of this type of data in the scoring; This is the perturbation coefficient, used to express the influence of periodic factors; , The frequency and phase of this disturbance term are used to dynamically adapt the model to the on-site rhythm.

2. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: Step one involves conducting a survey of the construction site environment to provide data support for subsequent work. This includes collecting environmental data from the construction site and taking stock of the construction conditions at the site. When collecting environmental data at the construction site, we use drones and satellite remote sensing equipment to obtain terrain features and satellite imagery information, as well as climate data. When assessing the construction conditions at the construction site, an inventory of the available construction equipment is conducted through manual inspection, and the quantity and location of the equipment are recorded. At the same time, statistics are compiled on the number of workers on site and the types of skills they perform.

3. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: Step two involves optimizing the resource allocation at the construction site by designing the site layout, thereby improving operational efficiency and safety. When designing the construction layout, a customized construction plan that meets the site construction requirements is designed based on the results of the environmental survey. The construction route and drainage system are planned in combination with the terrain and climate. At the same time, the construction work areas on the construction site are reasonably divided, and the types of work in different areas are clearly defined to ensure that different construction work projects on the construction site can work in a coordinated and synchronous manner, and to prevent interference and risks caused by cross-operations. It is also necessary to plan the usage periods of different mechanical equipment in construction operations, and to display the planned usage periods of different mechanical equipment through Gantt charts; Furthermore, based on the statistical records of the number and skill types of construction workers, the human resources required for construction can be rationally allocated, and the working hours and 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 sensor installation involves installing various sensors in key areas to monitor the environmental conditions of the construction site. When deploying various sensors, the placement location needs to be selected and determined according to the type of sensor, and a grid layout principle needs to be followed to ensure that the sensing and monitoring range covers the entire construction site. Specific sensor types include: temperature sensors, humidity sensors, noise sensors, and vibration sensors. The deployment of monitoring equipment involves installing video surveillance cameras and thermal imaging cameras in key areas of the construction site. The video surveillance cameras provide real-time, comprehensive coverage monitoring of the construction site, while the thermal imaging cameras can monitor nighttime construction and provide early warning in the event of a fire. according to The output value can be used to classify the warning level: in The threshold is an experience threshold, set based on historical data training or human experience.

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

6. The method for digital construction site layout based on the Internet of Things according to claim 5, characterized in that: The construction of the IoT platform involves building an IoT platform that accesses device data through a unified interface, enabling the connection and management of various IoT devices, ensuring centralized data processing and transmission, guaranteeing data transmission security, and reducing transmission load. The data analysis and processing utilizes big data technology to analyze and process the collected monitoring sensor data. By setting monitoring thresholds for networked monitoring devices through big data technology, an early warning is automatically triggered when the monitoring data collected by the monitoring devices exceeds the threshold, identifying potential hazards at the construction site and providing data support for construction management. The construction progress and quality monitoring involves real-time monitoring of construction progress and quality to make timely adjustments and optimizations, thereby ensuring both construction quality and progress. Specifically, when monitoring progress and quality, the system automatically pushes delay warnings by comparing the BIM model with the actual construction progress. At the same time, it compares the actual construction accuracy with the BIM model to obtain the judgment result of construction quality.

7. The method for digital construction site layout based on the Internet of Things according to claim 1, characterized in that: Step five involves verifying the construction procedures at the construction site by establishing acceptance standards. The verification process determines whether the construction procedure 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. The established acceptance criteria 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.

8. The method for digital construction site layout based on the Internet of Things according to claim 7, characterized in that: In step five, during the pilot verification, a single construction process at the construction site is selected for trial operation, and feedback data is collected after the process is completed. If the feedback information does not meet the established acceptance standards, it means that the acceptance result is unsuccessful. Feedback measures need to be initiated to provide feedback, and continuous rectification and optimization should be carried out to ensure the effective implementation of the construction layout on the site.

9. A digital construction site layout device based on the Internet of Things, characterized in that: Includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; When the processor executes the program instructions stored in the memory, it implements the digital construction site layout method as described in any one of claims 1 to 8.

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