Intelligent building engineering progress dynamic management and control system

Abstract

The invention relates to the technical field of engineering management, and discloses an intelligent building engineering progress dynamic management and control system, which comprises a data acquisition layer used for acquiring dynamic information of a construction site, including personnel, equipment, materials and environmental data; the data processing layer is used for receiving, cleaning, storing, analyzing and processing the data acquired by the data acquisition layer; and the application layer is used for providing visual display and man-machine interaction functions of dynamic management and control of the construction progress. According to the invention, through the high-precision sensor and the Internet of Things technology, real-time acquisition and updating of construction site data are realized, and the problems of data lag and errors caused by a traditional manual recording mode are solved; meanwhile, a dynamic tracking module of equipment and personnel adopts GPS, Beidou and UWB technologies, centimeter-level positioning precision is achieved, and a material monitoring module is combined with an RFID technology and various sensors, so that whole-course accurate management of inventory and circulation of building materials is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering management, and in particular to a dynamic control system for the progress of intelligent building engineering. Background Art

[0002] Engineering management methods refer to systematic methods for effectively allocating and dynamically controlling engineering resources through scientific organizational and management techniques in the planning, design, construction and operation stages of engineering projects in order to achieve project goals (such as quality, schedule, cost and safety). Its core lies in optimizing resource utilization efficiency, reducing project risks and maximizing project benefits in a complex and changing engineering environment.

[0003] With the acceleration of urbanization, the scale and complexity of construction projects are constantly increasing, and traditional engineering management methods have gradually exposed many limitations. Traditional construction project progress control mainly relies on manual records and regular reports. The data collection method is inefficient and has a lag, making it difficult for managers to grasp the real dynamics of the construction site in a timely manner. At the same time, due to the subjectivity of manual statistics and experience judgment, the accuracy of construction data is difficult to guarantee. This management method that relies on experience is very likely to lead to progress deviations, waste of resources and delays in the face of complex projects. In addition, construction projects involve multiple participants, such as design units, construction teams, material suppliers and owners. The information transmission between the parties is not smooth, and the communication and collaboration efficiency is low, which further exacerbates the uncertainty in the execution of construction plans. Summary of the invention

[0004] In order to make up for the above shortcomings, the present invention provides an intelligent building project progress dynamic management and control system, which aims to improve the traditional construction project progress control which mainly relies on manual records and regular reports, and the data collection method is inefficient and has lags.

[0005] In a first aspect, the present invention provides the following technical solution, a dynamic control system for intelligent building project progress, comprising:

[0006] The data collection layer is used to obtain dynamic information of the construction site, including personnel, equipment, materials and environmental data;

[0007] The data processing layer is used to receive, clean, store, analyze and process the data acquired by the data collection layer;

[0008] The application layer is used to provide visualization and human-computer interaction functions for dynamic control of construction progress;

[0009] The data collection layer includes:

[0010] The location tracking module uses high-precision GPS and Beidou navigation system dual-mode positioning modules combined with ultra-wideband UWB technology to track the location of construction equipment and personnel in real time;

[0011] The material monitoring module collects building material inventory, circulation information and concrete pouring progress data through UHF RFID readers, pressure sensors, liquid level sensors and flow sensors;

[0012] The environmental perception module monitors construction environment data through temperature and humidity sensors, light sensors, wind speed and direction sensors, and dust sensors;

[0013] The data processing layer includes:

[0014] Data access and cleaning module, used to clean and eliminate abnormalities in received multi-source data;

[0015] Big data analysis and mining module, used to predict construction progress and risk assessment based on the long short-term memory network (LSTM) model;

[0016] Risk warning and emergency response module, used to generate construction delay warnings and trigger emergency linkage responses;

[0017] The application layer includes:

[0018] Project management module, which is used to display dynamic Gantt charts and provide comparison between construction plan and actual progress;

[0019] On-site execution module, used to receive construction notices and report quality and safety hazards;

[0020] The owner monitoring module is used to monitor the project progress and capital flow in real time.

[0021] Preferably, the location tracking module in the data collection layer further includes:

[0022] High-precision sensors installed on construction machinery components to monitor equipment trajectory, speed and status;

[0023] The positioning chip installed on the construction workers' safety helmets or work badges is used to record the workers' working hours and location information in real time.

[0024] Preferably, the material monitoring module in the data acquisition layer also includes:

[0025] UHF RFID tags are attached to building materials, and the tags store the material specifications, models, batch numbers, and storage time;

[0026] Pressure sensors, liquid level sensors and flow sensors are installed on concrete tankers and pouring equipment to monitor the mixing status, transportation status and pouring flow of concrete in real time.

[0027] Preferably, the big data analysis and mining module in the data processing layer predicts the construction progress in the following ways:

[0028] Use historical construction data and real-time data to train the long short-term memory network LSTM model;

[0029] Combine construction site environmental parameters, resource allocation and equipment status data to predict construction progress and risks in different time periods in the future.

[0030] Preferably, the project management module in the application layer further includes:

[0031] Dynamic Gantt chart function unit, used to mark the normal, warning and delayed status of construction tasks with color grading;

[0032] Data visualization unit used to display critical paths, construction node countdowns, and resource allocation.

[0033] Preferably, the communication technologies used are Wi-Fi, Bluetooth, ZigBee, LoRa and 5G networks, and the optimal data transmission path is dynamically selected through an intelligent routing algorithm.

[0034] Preferably, the risk warning and emergency response module is implemented in the following manner:

[0035] Analyze potential construction risks based on multi-source data fusion, including equipment failure, material supply delays, and environmental changes;

[0036] Automatically trigger a notification message to the responsible person and execute the emergency plan.

[0037] In a second aspect, the present invention provides the following technical solution, a method for dynamically controlling the progress of an intelligent building project, comprising the following steps:

[0038] S1. Data Collection

[0039] S101. Deploy various types of sensors at the construction site, including high-precision GPS, Beidou navigation system, UWB positioning chip, ultra-high frequency RFID tag, pressure sensor, liquid level sensor, temperature and humidity sensor, wind speed and direction sensor and dust sensor;

[0040] S102, collecting construction equipment location, personnel trajectory, building material flow information, construction environment parameters and concrete pouring status data in real time through sensors;

[0041] S103, transmitting the collected data to the data processing layer via Wi-Fi, Bluetooth, ZigBee, LoRa or 5G communication network;

[0042] S2. Data Processing

[0043] S201, denoising, removing outliers and verifying logical relationships of collected data through a data access and cleaning module to generate cleaned data;

[0044] S202. Analyze the cleaned data based on the long short-term memory network (LSTM) model to predict future construction progress trends and potential risk points;

[0045] S203. Combine environmental parameters, equipment status and historical data to quantitatively assess the risk of construction delay and generate corresponding risk warning information;

[0046] S3, Data Application

[0047] S301. In the project management module, dynamically update the Gantt chart and mark the real-time status of the construction task: normal, warning, delayed;

[0048] S302: In the on-site execution module, push construction adjustment notifications to construction personnel through the mobile terminal, and receive reporting information on quality and safety hazards;

[0049] S303. In the owner monitoring module, a visual chart is generated to show the relationship between investment progress and image progress, and real-time video monitoring images of the construction site and information on capital flow are provided.

[0050] In the third aspect, the invention provides the following technical solution: a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for dynamic control of the progress of intelligent building projects when executing the computer program.

[0051] In a fourth aspect, the present invention provides the following technical solution: a readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the above-mentioned method for dynamic control of the progress of an intelligent building project.

[0052] The present invention has the following beneficial effects:

[0053] 1. In the present invention, through high-precision sensors and Internet of Things technology, real-time collection and updating of construction site data are realized, solving the data lag and error problems caused by traditional manual recording methods; at the same time, the dynamic tracking module of equipment and personnel adopts GPS, Beidou and UWB technology to achieve centimeter-level positioning accuracy, and the material monitoring module combines RFID technology with a variety of sensors to realize the full-process precise management of building material inventory and circulation.

[0054] 2. In the present invention, the construction progress prediction module of the system uses the LSTM deep learning model to dynamically analyze historical data and real-time data, identify construction anomalies in advance and propose optimization strategies, which significantly improves the intelligent level of construction management. At the same time, the risk warning and emergency response module integrates multi-source data, can quickly identify potential risks such as equipment failure, material delays, and bad weather, and link relevant personnel and resources through a multi-level warning mechanism to minimize the probability of construction delays and safety accidents.

[0055] 3. In the present invention, through the integrated collaboration platform, the system realizes information sharing and efficient collaboration among multiple parties such as project management, on-site execution and owner monitoring, breaking the information island problem in traditional construction projects. The dynamic Gantt chart intuitively displays the deviation between the construction plan and the actual progress by color grading and real-time marking of critical paths, significantly improving management efficiency and construction transparency. At the same time, multi-terminal support enables all participants to obtain updated information at any time on the PC and mobile terminals. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a system framework diagram of the intelligent building project progress dynamic control system proposed by the present invention;

[0057] Figure 2 A detailed system framework diagram of the intelligent building project progress dynamic control system proposed by the present invention;

[0058] Figure 3 This is a method flow chart of the method for dynamic control of intelligent building project progress proposed by the present invention. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Embodiment 1

[0061] Reference Figure 1-Figure 2In the first embodiment of the present invention, the present invention provides a dynamic control system for the progress of intelligent building projects, including:

[0062] The data collection layer is used to obtain dynamic information of the construction site, including personnel, equipment, materials and environmental data;

[0063] The data processing layer is used to receive, clean, store, analyze and process the data obtained by the data collection layer;

[0064] The application layer is used to provide visualization and human-computer interaction functions for dynamic control of construction progress;

[0065] The data collection layer includes:

[0066] The location tracking module uses high-precision GPS and Beidou navigation system dual-mode positioning modules combined with ultra-wideband UWB technology to track the location of construction equipment and personnel in real time;

[0067] The material monitoring module collects building material inventory, circulation information and concrete pouring progress data through UHF RFID readers, pressure sensors, liquid level sensors and flow sensors;

[0068] The environmental perception module monitors construction environment data through temperature and humidity sensors, light sensors, wind speed and direction sensors, and dust sensors;

[0069] The data processing layer includes:

[0070] Data access and cleaning module, used to clean and eliminate abnormalities in received multi-source data;

[0071] Big data analysis and mining module, used to predict construction progress and risk assessment based on the long short-term memory network (LSTM) model;

[0072] Risk warning and emergency response module, used to generate construction delay warnings and trigger emergency linkage responses;

[0073] The application layer includes:

[0074] Project management module, which is used to display dynamic Gantt charts and provide comparison between construction plan and actual progress;

[0075] On-site execution module, used to receive construction notices and report quality and safety hazards;

[0076] The owner monitoring module is used to monitor the project progress and capital flow in real time.

[0077] Specifically, the intelligent building project progress dynamic control system of the present invention includes three layers: data collection layer, data processing layer and application layer.

[0078] Data collection layer: The data collection layer is the foundation layer of the entire system, responsible for comprehensively capturing real-time information of the construction site. To ensure the integrity and real-time nature of the data, this layer includes the following core modules:

[0079] Personnel and equipment tracking module: Using high-precision GPS modules and Beidou navigation system, it can realize real-time tracking of the position, movement trajectory, speed and steering angle of large construction equipment (such as tower cranes, excavators, concrete pump trucks, etc.). Equipped with UWB (ultra-wideband) positioning chips in the safety helmets or work badges of construction workers, combined with RFID (radio frequency identification) technology, it can realize accurate monitoring of personnel working hours, work area distribution and activity trajectory, and the positioning error is controlled within 30 cm.

[0080] Material monitoring module: UHF RFID readers installed at building material storage points and warehouses can automatically identify and record the status of materials. Material tags store information such as specifications, models, batch numbers, and storage time. Pressure sensors, liquid level sensors, and flow sensors are also deployed in the concrete construction process to monitor the concrete mixing status, transportation process, and pouring rate in real time to ensure accurate control of the progress of key processes.

[0081] Environmental perception module: Environmental perception devices including temperature and humidity sensors, wind speed and direction sensors, dust monitoring sensors and light sensors are deployed in key areas of the construction site to collect weather, air quality and environmental change data in real time. These data directly affect the adjustment of construction technology and the optimization of resource allocation.

[0082] Data transmission mechanism: The collected data is transmitted to the data processing layer through a variety of communication methods (such as Bluetooth, Wi-Fi, ZigBee, LoRa and 5G networks). For short-distance and low-power scenarios, ZigBee or Bluetooth communication is preferred; for scenarios with large amounts of data and high real-time requirements, 5G high-speed transmission technology is used.

[0083] Data processing layer: As the middle core layer of the system, the data processing layer mainly cleans, stores, analyzes and predicts the collected multi-source data, thereby converting the original data into valuable decision-making basis. Its main modules include:

[0084] Data cleaning module: Use intelligent cleaning algorithms to process the collected raw data, including removing outliers, filling missing values, and eliminating duplicate data to ensure data accuracy and consistency. For example, sensors may generate noise values ​​due to signal interference, and the system automatically corrects these erroneous data through historical data comparison and logical relationship analysis.

[0085] Progress prediction module: Based on the long short-term memory network (LSTM) algorithm, a construction progress prediction model is built, combining historical data and real-time data to generate a progress trend forecast for the next 7 days to 1 month. This module can identify potential delay risks during the construction process and provide a scientific basis for construction decision-making by quantitatively evaluating the impact of different risk factors.

[0086] Risk warning module: By integrating multi-source data (such as equipment status, material flow, and environmental parameters), it can identify unexpected problems that may be encountered during construction in advance, such as equipment failure, delayed material supply, and bad weather. The system generates specific risk warnings based on the warning level and pushes them to relevant managers.

[0087] Application layer: The application layer is the user interaction layer of the system, which provides customized functions according to the needs of different users (such as project managers, construction personnel and owners) to ensure the ease of use and practicality of the system. Its main modules include:

[0088] Project management module: Provides dynamic visual management of the overall project progress. The dynamic Gantt chart intuitively displays the comparison between the planned progress and the actual progress, and the color grading display (green for normal, yellow for warning, and red for delay) allows managers to quickly identify problem points. In addition, it also integrates the critical path analysis function to automatically mark the potential impact of construction delays on subsequent processes.

[0089] On-site execution module: Supports construction site personnel to receive instant task notifications, risk warnings and process adjustment instructions through mobile devices. Workers can quickly report quality and safety hazards by taking photos and recording audio, and related issues are automatically distributed to the responsible person to ensure timely handling of problems.

[0090] Owner monitoring module: An interface designed specifically for owners, including real-time progress display of the construction site, capital investment and output analysis, and high-definition video monitoring functions. Owners can grasp the overall situation of the project in real time through remote access, enhancing project transparency and trust.

[0091] Multi-level data integration: The data collection layer, data processing layer and application layer collaborate efficiently through standardized interfaces. The real-time collected data is processed and analyzed to generate visual results and management suggestions, which are displayed to users of different roles through the application layer, forming a closed loop of data circulation to ensure efficient control of the construction process.

[0092] System hardware and software architecture:

[0093] Hardware architecture: includes high-performance server clusters, distributed sensor networks and edge computing devices.

[0094] Software architecture: Build back-end services based on SpringBoot, Django and other frameworks, combine Vue.js or React to build the front-end interactive interface, and realize the separation of front-end and back-end through RESTfulAPI.

[0095] The location tracking module in the data collection layer further includes:

[0096] High-precision sensors installed on construction machinery components to monitor equipment trajectory, speed and status;

[0097] The positioning chip installed on the construction workers' safety helmets or work badges is used to record the workers' working hours and location information in real time.

[0098] Specifically, device positioning:

[0099] Install high-precision GPS and Beidou dual-mode navigation modules at key locations of construction machinery (such as tower cranes, excavators, and concrete pump trucks) to obtain the equipment's geographic location, operating trajectory, speed, and status in real time.

[0100] Built-in gyroscope and accelerometer sensors further enhance the accuracy of dynamic monitoring of the device.

[0101] Personnel positioning:

[0102] UWB positioning chips are integrated into construction workers’ safety helmets or work badges to achieve construction workers’ working hour statistics and regional distribution monitoring through high-precision positioning.

[0103] UWB positioning technology controls the error within 30 cm in complex environments, ensuring that the positioning data is accurate and reliable.

[0104] Data transmission:

[0105] The positioning data is transmitted to the data processing center via Bluetooth, Wi-Fi or ZigBee communication protocols and analyzed in combination with other construction data.

[0106] The material monitoring module in the data acquisition layer also includes:

[0107] UHF RFID tags are attached to building materials, and the tags store the material specifications, models, batch numbers, and storage time;

[0108] Pressure sensors, liquid level sensors and flow sensors are installed on concrete tankers and pouring equipment to monitor the mixing status, transportation status and pouring flow of concrete in real time.

[0109] Specifically, RFID tags and readers:

[0110] Deploy UHF RFID readers at construction sites and warehouses to monitor the inventory and circulation of construction materials.

[0111] Each batch of materials (such as steel bars and cement) is attached with an RFID tag, which records the material's specifications, model, batch number and storage time.

[0112] Concrete Monitoring:

[0113] Install pressure sensors, liquid level sensors and flow sensors on concrete tankers and pouring equipment to monitor the concrete mixing status, transportation status and pouring volume in real time.

[0114] Data is uploaded through the 4G / 5G communication module to ensure precise control of the concrete construction process.

[0115] Material Data Management:

[0116] Data is networked via the ZigBee protocol and uploaded to the data processing center in real time, automatically updating material inventory data and supporting comparative analysis between construction plans and actual material usage.

[0117] The big data analysis and mining module in the data processing layer predicts the construction progress in the following ways:

[0118] Use historical construction data and real-time data to train the long short-term memory network LSTM model;

[0119] Combine construction site environmental parameters, resource allocation and equipment status data to predict construction progress and risks in different time periods in the future.

[0120] Specifically, data cleaning and preprocessing:

[0121] The collected data are formatted and normalized, outliers are removed and deviations are corrected.

[0122] A variety of filling algorithms (such as K-nearest neighbor-based filling method) are used for missing values ​​to ensure data integrity.

[0123] LSTM model construction:

[0124] An LSTM model is built based on TensorFlow, and progress prediction is performed using historical engineering data and real-time construction data.

[0125] The input layer includes time series data (such as daily workload, environmental parameters, man-hours, etc.), and the output layer generates construction progress forecasts for several future time periods.

[0126] Risk Assessment and Optimization:

[0127] The model combines risk assessment factors (such as weather, equipment status, and material supply delays) to quantify schedule risks.

[0128] Based on the analysis results, optimization suggestions are generated, including resource allocation adjustments and construction plan optimization.

[0129] The project management module in the application layer further includes:

[0130] Dynamic Gantt chart function unit, used to mark the normal, warning and delayed status of construction tasks with color grading;

[0131] Data visualization unit used to display critical paths, construction node countdowns, and resource allocation.

[0132] Specific, dynamic update function:

[0133] The dynamic Gantt chart displays the comparison between the construction plan and the actual progress in real time, and marks the status of each task through color grading (green, yellow, red).

[0134] The system automatically updates the progress bar based on the real-time collected data and marks abnormal progress points.

[0135] Data Visualization Unit:

[0136] Provides critical path analysis function to mark key construction nodes and their impact on the overall construction period.

[0137] The allocation of construction resources, capital flow and the relationship between the project progress are displayed in a graphical form, which helps managers to fully grasp the project status.

[0138] It also includes the communication technologies used, such as Wi-Fi, Bluetooth, ZigBee, LoRa and 5G networks, and dynamically selects the optimal data transmission path through intelligent routing algorithms.

[0139] Specifically, the integration of multiple communication technologies:

[0140] Equipment with large data volumes and high real-time requirements (such as tower cranes and concrete pump trucks) will give priority to 5G network transmission to ensure low latency and high reliability.

[0141] Short-range sensors (such as RFID readers, temperature and humidity sensors) use ZigBee or Bluetooth communication technology to reduce power consumption.

[0142] Long-distance data transmission (such as environmental monitoring points) uses LoRa network technology to cover the entire construction site.

[0143] Intelligent routing and dynamic switching:

[0144] The communication path is dynamically selected through the routing algorithm, and the transmission mode is switched according to the network signal strength and bandwidth occupancy to ensure stable data transmission.

[0145] The risk warning and emergency response module is implemented in the following ways:

[0146] Analyze potential construction risks based on multi-source data fusion, including equipment failure, material supply delays, and environmental changes;

[0147] Automatically trigger a notification message to the responsible person and execute the emergency plan.

[0148] Specifically, risk identification:

[0149] Integrate multi-source information such as equipment status, material flow, environmental data, etc., combined with historical data, to identify potential risk points such as mechanical failures, material delays or bad weather.

[0150] The system generates delay warning prompts based on the impact of risk factors.

[0151] Emergency response linkage:

[0152] Early warning information is pushed to project managers and relevant responsible persons simultaneously through mobile and web terminals.

[0153] Automatically generate emergency plan suggestions, including resource reallocation, process adjustment and related personnel scheduling.

[0154] Embodiment 2:

[0155] Reference Figure 2-Figure 3 In a second embodiment of the present invention, the present invention provides a method for dynamic control of intelligent building project progress, comprising the following steps:

[0156] S1. Data Collection

[0157] S101. Deploy various types of sensors at the construction site, including high-precision GPS, Beidou navigation system, UWB positioning chip, ultra-high frequency RFID tag, pressure sensor, liquid level sensor, temperature and humidity sensor, wind speed and direction sensor and dust sensor;

[0158] S102, collecting construction equipment location, personnel trajectory, building material flow information, construction environment parameters and concrete pouring status data in real time through sensors;

[0159] S103, transmitting the collected data to the data processing layer via Wi-Fi, Bluetooth, ZigBee, LoRa or 5G communication network;

[0160] S2. Data Processing

[0161] S201, denoising, removing outliers and verifying logical relationships of collected data through a data access and cleaning module to generate cleaned data;

[0162] S202. Analyze the cleaned data based on the long short-term memory network (LSTM) model to predict future construction progress trends and potential risk points;

[0163] S203. Combine environmental parameters, equipment status and historical data to quantitatively assess the risk of construction delay and generate corresponding risk warning information;

[0164] S3, Data Application

[0165] S301. In the project management module, dynamically update the Gantt chart and mark the real-time status of the construction task: normal, warning, delayed;

[0166] S302: In the on-site execution module, push construction adjustment notifications to construction personnel through the mobile terminal, and receive reporting information on quality and safety hazards;

[0167] S303. In the owner monitoring module, a visual chart is generated to show the relationship between investment progress and image progress, and real-time video monitoring images of the construction site and information on capital flow are provided.

[0168] Specifically, S1 data collection

[0169] S101 Dynamic Tracking of Personnel and Equipment

[0170] High-precision GPS modules, Beidou navigation modules and gyroscope sensors are installed on large construction equipment (such as tower cranes, concrete pump trucks, excavators, etc.) at the construction site to obtain the equipment's geographic coordinates, running trajectory, speed and steering angle.

[0171] Equipped with UWB (ultra-wideband) positioning chips in construction workers' helmets or work badges, the workers' working hours, movement trajectories and locations are monitored in real time.

[0172] The data is uploaded to the data processing center in real time via Bluetooth (BLE), Wi-Fi or ZigBee protocol.

[0173] S102 Dynamic Monitoring of Building Materials

[0174] Ultra-high frequency RFID readers are deployed at key points in material warehouses and construction sites, combined with RFID tags attached to construction materials (such as steel bars, cement, etc.) to record the specifications, batch numbers, warehousing time and inventory status of materials in real time.

[0175] For the concrete construction process, pressure sensors, liquid level sensors and flow sensors are installed on tank trucks and construction sites to monitor the concrete mixing status, liquid level changes during transportation and pouring flow in real time.

[0176] Data is transmitted to the data processing module via the 4G / 5G network to enable dynamic monitoring of key materials.

[0177] S103 Real-time collection of environmental parameters

[0178] Temperature and humidity sensors, wind speed and direction sensors, light sensors and dust sensors are deployed at the construction site to monitor the weather conditions and air quality at the construction site in real time.

[0179] Environmental data is transmitted to the cloud or edge computing nodes via LoRa communication technology to support real-time assessment and adjustment of the construction environment.

[0180] S2 Data Processing

[0181] S201 Data Cleaning and Preprocessing

[0182] Standardize the collected multi-source data, including:

[0183] Outlier detection and elimination: Eliminate abnormal data caused by sensor errors or communication interference by comparing historical data.

[0184] Missing value filling: Use the filling method based on K-nearest neighbor algorithm to supplement the missing parts of key data.

[0185] Data standardization: unify data units to ensure consistency and comparability of multidimensional data.

[0186] S202 Construction Progress Forecast

[0187] The construction progress prediction module is constructed using the long short-term memory network (LSTM) model, which includes:

[0188] Input layer: receives time series data (such as working hours, completion quantity, material inventory, equipment status, etc.).

[0189] Hidden layer: Multi-layer LSTM units are used to model the dynamic changes of construction progress.

[0190] Output layer: Generate construction progress forecasts for the next 7 to 30 days and mark key processes that may be delayed.

[0191] S203 Risk Assessment and Early Warning

[0192] Based on real-time data and forecast results, the impact of risk factors (such as bad weather, delayed material supply, and equipment failure) is quantified and a risk assessment report is generated.

[0193] The system automatically generates early warning information based on the risk level and pushes it to relevant managers to facilitate timely adjustment measures.

[0194] S3 Application Showcase

[0195] S301 Project Management

[0196] On the manager side, a dynamic Gantt chart is used to show the comparison between the planned construction progress and the actual progress:

[0197] Real-time marking of task status, color grading: green (normal), yellow (warning), red (delay).

[0198] Provides critical path analysis function to mark the process chain that has a significant impact on the overall construction period.

[0199] Supports multi-dimensional data visualization, including the correlation diagram between capital flow and construction progress, countdown of construction period at key nodes, etc.

[0200] S302 On-site Execution

[0201] Push instant notifications to construction personnel, including equipment scheduling adjustments, construction process modifications, and material arrival reminders.

[0202] Construction workers use mobile devices (such as smartphones and tablets) to report construction hazards, including quality issues and equipment failures, and support uploading of multimedia information such as pictures and voice.

[0203] Hidden danger information is automatically distributed to responsible persons and a rectification task list is generated to ensure that problems are resolved in a timely manner.

[0204] S303 Owner Monitoring

[0205] Provides an exclusive visual monitoring interface for the owner to display the construction progress, investment completion ratio and capital input-output ratio.

[0206] It supports real-time viewing of high-definition video streams at the construction site and provides decision-making assistance based on data analysis results.

[0207] The platform provides remote access function, allowing owners to grasp the overall progress of the project at any time.

[0208] Data flow and communication guarantee

[0209] Collaborative application of multiple communication technologies

[0210] For scenarios with large amounts of data or high real-time requirements (such as equipment status monitoring), 5G network transmission is preferred to meet low latency and high bandwidth requirements.

[0211] For data communication between short-distance sensor nodes, ZigBee or Bluetooth protocols are used to reduce device energy consumption and extend sensor battery life.

[0212] For long-distance and low-frequency environmental data collection, LoRa technology is used to expand the communication range.

[0213] Intelligent data routing

[0214] Through intelligent routing algorithms, the optimal data transmission path is dynamically selected and switched in real time according to network signal strength and bandwidth occupancy, ensuring the stability and efficiency of data transmission.

[0215] Embodiment 3

[0216] The third embodiment of the present invention is based on the same inventive concept and proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method for dynamic control of the progress of intelligent building projects in the above-mentioned embodiment are implemented.

[0217] Embodiment 4

[0218] The fourth embodiment of the present invention is based on the same inventive concept. The present invention proposes a computer device, and the terminal includes: a processor and a memory; the processor and the memory communicate with each other; the memory is used to store instructions; the processor is used to execute the instructions in the memory, and execute the method for dynamic control of the progress of intelligent building projects of the above embodiment.

[0219] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0220] Finally, it should be noted that the above is only 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, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Intelligent building project progress dynamic control system, characterized by: include: The data collection layer is used to obtain dynamic information of the construction site, including personnel, equipment, materials and environmental data; The data processing layer is used to receive, clean, store, analyze and process the data acquired by the data collection layer; The application layer is used to provide visualization and human-computer interaction functions for dynamic control of construction progress; The data collection layer includes: The location tracking module uses high-precision GPS and Beidou navigation system dual-mode positioning modules combined with ultra-wideband UWB technology to track the location of construction equipment and personnel in real time; The material monitoring module collects building material inventory, circulation information and concrete pouring progress data through UHF RFID readers, pressure sensors, liquid level sensors and flow sensors; The environmental perception module monitors construction environment data through temperature and humidity sensors, light sensors, wind speed and direction sensors, and dust sensors; The data processing layer includes: Data access and cleaning module, used to clean and eliminate abnormalities in received multi-source data; Big data analysis and mining module, used to predict construction progress and risk assessment based on the long short-term memory network (LSTM) model; Risk warning and emergency response module, used to generate construction delay warnings and trigger emergency linkage responses; The application layer includes: Project management module, which is used to display dynamic Gantt charts and provide comparison between construction plan and actual progress; On-site execution module, used to receive construction notices and report quality and safety hazards; The owner monitoring module is used to monitor the project progress and capital flow in real time.

2. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: The location tracking module in the data collection layer further includes: High-precision sensors installed on construction machinery components to monitor equipment trajectory, speed and status; The positioning chip installed on the construction workers' safety helmets or work badges is used to record the workers' working hours and location information in real time.

3. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: The material monitoring module in the data acquisition layer also includes: UHF RFID tags are attached to building materials, and the tags store the material specifications, models, batch numbers, and storage time; Pressure sensors, liquid level sensors and flow sensors are installed on concrete tankers and pouring equipment to monitor the mixing status, transportation status and pouring flow of concrete in real time.

4. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: The big data analysis and mining module in the data processing layer predicts the construction progress in the following ways: Use historical construction data and real-time data to train the long short-term memory network LSTM model; Combine construction site environmental parameters, resource allocation and equipment status data to predict construction progress and risks in different time periods in the future.

5. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: The project management module in the application layer further includes: Dynamic Gantt chart function unit, used to mark the normal, warning and delayed status of construction tasks with color grading; Data visualization unit used to display critical paths, construction node countdowns, and resource allocation.

6. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: It also includes the communication technologies used, such as Wi-Fi, Bluetooth, ZigBee, LoRa and 5G networks, and dynamically selects the optimal data transmission path through intelligent routing algorithms.

7. The intelligent building project progress dynamic control system according to claim 1 is characterized in that: The risk warning and emergency response module is implemented in the following ways: Analyze potential construction risks based on multi-source data fusion, including equipment failure, material supply delays, and environmental changes; Automatically trigger a notification message to the responsible person and execute the emergency plan.

8. A method for dynamic control of the progress of intelligent building projects, characterized in that: The intelligent building project progress dynamic control system used in any one of claims 1 to 7 comprises the following steps: S1. Data Collection S101. Deploy various types of sensors at the construction site, including high-precision GPS, Beidou navigation system, UWB positioning chip, ultra-high frequency RFID tag, pressure sensor, liquid level sensor, temperature and humidity sensor, wind speed and direction sensor and dust sensor; S102, collecting construction equipment location, personnel trajectory, building material flow information, construction environment parameters and concrete pouring status data in real time through sensors; S103, transmitting the collected data to the data processing layer via Wi-Fi, Bluetooth, ZigBee, LoRa or 5G communication network; S2. Data Processing S201, denoising, removing outliers and verifying logical relationships of collected data through a data access and cleaning module to generate cleaned data; S202. Analyze the cleaned data based on the long short-term memory network (LSTM) model to predict future construction progress trends and potential risk points; S203. Combine environmental parameters, equipment status and historical data to quantitatively assess the risk of construction delay and generate corresponding risk warning information; S3, Data Application S301. In the project management module, dynamically update the Gantt chart and mark the real-time status of the construction task: normal, warning, delayed; S302: In the on-site execution module, push construction adjustment notifications to construction personnel through the mobile terminal, and receive reporting information on quality and safety hazards; S303. In the owner monitoring module, a visual chart is generated to show the relationship between investment progress and image progress, and real-time video monitoring images of the construction site and information on capital flow are provided.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for dynamic control of the progress of an intelligent building project as described in claim 8 is implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for dynamically controlling the progress of an intelligent building project as described in claim 8 is implemented.

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