A method and system for monitoring concrete curing operations based on edge computing

Abstract

This invention provides a method and system for monitoring concrete curing operations based on edge computing, relating to the field of edge computing technology. The method includes: receiving emergency processing tasks sent by an edge computing terminal; parsing the emergency processing tasks and determining the execution device; and controlling the execution device to execute the emergency processing tasks. The generation process of the emergency processing tasks is as follows: receiving monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time; when the temperature difference between the inside and outside is greater than or equal to a threshold, acquiring an image of the corresponding concrete area; analyzing the image to determine abnormal events; and determining emergency processing tasks based on an abnormal event processing library. This invention enables the monitoring of concrete curing operations to ensure their effective implementation.

Description

Technical Field

[0001] This invention relates to the field of edge computing technology, and in particular to a method and system for monitoring concrete curing operations based on edge computing. Background Technology

[0002] Currently, the construction of gas-fired combined cycle power plants in high-temperature desert areas involves the pouring of large volumes of concrete, such as the concrete for gas turbine foundations and the concrete foundation layer for waste heat boiler pits. For the curing of gas turbine foundation concrete, temperature sensors are typically embedded in the concrete. Three sets are installed for the foundation, with the sensors embedded at the following heights: 30cm below the top surface of the foundation, at the center of the foundation, and 30cm above the bottom surface. Dedicated personnel regularly monitor the temperature to control internal temperature changes. The difference between the core temperature and the surface temperature must not exceed 20℃, and the maximum internal temperature of the concrete must be controlled at 60℃, not exceeding the limit temperature of 65℃. If any abnormal temperature is detected, additional covering should be added immediately. The concrete hydration temperature and ambient temperature must be measured and recorded until the core and surface temperatures are almost identical, but not less than 10 days later. Eight hours after the gas turbine foundation is poured, the concrete surface is covered with plastic sheeting and blankets and watered. Watering is repeated after covering to achieve the desired heat and moisture retention for curing. To ensure proper insulation and moisture retention, the tarpaulin should be kept moist at all times. After removing the reinforcing scaffold pipes, the sides of the foundation should be covered with tarpaulins for insulation and moisture retention. The tarpaulins should be tightly wrapped, with the bottom firmly pressed down, and the overlapping edges tied with ropes to prevent strong winds from penetrating and increasing the temperature difference between the inside and outside of the concrete. During the curing period, the temperature inside and outside of the concrete should be monitored, controlling the temperature difference to not exceed 20℃. Temperature should be measured every 2 hours for the first 3 days of curing, and every 4 hours thereafter, with records kept. The curing time depends on the temperature readings. During the curing period, a dedicated person should monitor the concrete temperature changes regularly, day and night, and keep detailed temperature records. When the temperature difference between the inside and outside of the concrete approaches 20℃, external insulation should be strengthened immediately. The foundation formwork can only be removed after the temperature of the foundation concrete has stabilized. The above techniques mainly rely on manual labor for concrete curing, heavily depending on the initiative of personnel. Therefore, there is an urgent need for a concrete curing operation monitoring method and system based on edge computing to ensure the effective implementation of concrete curing operations. Summary of the Invention

[0003] One of the objectives of this invention is to provide a method and system for monitoring concrete curing operations based on edge computing, so as to realize the monitoring of concrete curing operations and ensure the effective implementation of concrete curing operations.

[0004] This invention provides a method for monitoring concrete curing operations based on edge computing, comprising: Receive emergency response tasks sent by edge computing terminals; Analyze emergency response tasks and determine the execution devices; The control and execution device performs emergency response tasks; The process of generating emergency response tasks is as follows: It receives monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time. When the temperature difference between the inside and outside of the monitored area is greater than or equal to the threshold, an image of the corresponding concrete area is acquired. Analyze the images to identify anomalous events; Based on the exception event handling library, emergency response tasks are determined.

[0005] Preferred edge computing-based concrete curing operation monitoring methods also include: By integrating images of the concrete surface captured by the edge computing terminal, a global image is obtained; Monitor and analyze the global image to determine the operation time, operation type, and operation requirements; Based on the job time, job type, and job requirements, generate job tasks and job monitoring instructions; The job task is sent to the job receiving end, and the job monitoring instructions are sent to the edge computing terminal.

[0006] Preferably, when the edge computing terminal receives a job monitoring instruction, it performs the following operations: Analyze the job monitoring instructions to determine the job time, job type, and job requirements; Based on the job type and job requirements, please configure the job monitoring library; Determine the monitoring time for the task based on the task time; Based on job monitoring time and job monitoring database, job tasks are monitored.

[0007] Preferred edge computing-based concrete curing operation monitoring methods also include: Images of the maintenance work during the preparatory stage are obtained through an edge computing terminal; Analyze the images of the operation to construct a three-dimensional monitoring model of the maintenance operation; The monitoring data sent by the edge computing terminal is labeled in the three-dimensional monitoring model to form a visualization model; When an abnormal event occurs, the investigation points are analyzed based on the 3D monitoring model; Based on the investigation points, investigation tasks are generated and sent to the execution device simultaneously.

[0008] Preferably, the analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. An analysis dataset is constructed based on the maintenance measures and monitoring data corresponding to the finite element elements. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; Match the reference dataset with the analysis datasets of other finite element elements; The locations of finite element elements that meet the preset conditions and correspond to the concrete are used as inspection points.

[0009] The present invention also provides a concrete curing operation monitoring system based on edge computing, comprising: a receiving module, a parsing module, and a control module; wherein, the receiving module receives emergency processing tasks sent by the edge computing terminal; the parsing module parses the emergency processing tasks and determines the execution device; and the control module controls the execution device to execute the emergency processing tasks. The emergency response task generation process is as follows: receiving monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time; when the temperature difference between the inside and outside of the concrete is greater than or equal to a threshold, acquiring an image of the corresponding concrete area; analyzing the image to identify abnormal events; and determining the emergency response task based on the abnormal event processing library.

[0010] Preferably, the edge computing-based concrete curing operation monitoring system also includes: an operation analysis module; The job analysis module performs the following operations: By integrating images of the concrete surface captured by the edge computing terminal, a global image is obtained; Monitor and analyze the global image to determine the operation time, operation type, and operation requirements; Based on the job time, job type, and job requirements, generate job tasks and job monitoring instructions; The job task is sent to the job receiving end, and the job monitoring instructions are sent to the edge computing terminal.

[0011] Preferably, when the edge computing terminal receives a job monitoring instruction, it performs the following operations: Analyze the job monitoring instructions to determine the job time, job type, and job requirements; Based on the job type and job requirements, please configure the job monitoring library; Determine the monitoring time for the task based on the task time; Based on job monitoring time and job monitoring database, job tasks are monitored.

[0012] Preferably, the edge computing-based concrete curing operation monitoring system also includes: a visualization monitoring module and a troubleshooting and analysis module; The visualization monitoring module performs the following operations: acquiring operation images during the preparatory stage of maintenance work through the edge computing terminal; analyzing the operation images to construct a three-dimensional monitoring model of the maintenance work; marking the monitoring data sent by the edge computing terminal in the three-dimensional monitoring model to form a visualization model; the investigation and analysis module is used to analyze investigation points based on the three-dimensional monitoring model when abnormal events occur; and generating investigation tasks based on the investigation points and sending them synchronously to the execution device.

[0013] Preferably, the analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. An analysis dataset is constructed based on the maintenance measures and monitoring data corresponding to the finite element elements. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; Match the reference dataset with the analysis datasets of other finite element elements; The locations of finite element elements that meet the preset conditions and correspond to the concrete are used as inspection points.

[0014] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of a concrete curing operation monitoring method based on edge computing in an embodiment of the present invention; Figure 2 This is a schematic diagram of a concrete curing operation monitoring system based on edge computing, as described in an embodiment of the present invention. Detailed Implementation

[0017] 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.

[0018] Example 1: This embodiment of the invention provides a method for monitoring concrete curing operations based on edge computing, such as... Figure 1 As shown, it includes: Step 1: Receive emergency handling tasks sent by the edge computing terminal; The edge computing terminal is set up next to the concrete pouring body and connected to temperature sensors embedded in the concrete and temperature sensors set on the outside of the concrete to monitor the internal and external temperature of the concrete. When an anomaly is detected, it sends an emergency handling task to the platform. Step 2: Analyze the emergency response task and determine the execution device; After receiving an emergency response task, the platform parses the task. The parsing mainly determines the following information: First, it determines the location of the monitoring area of ​​the edge computing device that sent the emergency response task, and then determines the execution device responsible for that area. Only in this way can the emergency response task be responded to quickly. Step 3: Control the actuator to perform emergency response tasks; Emergency response tasks are executed by controlling actuators, which include automatic sprinkler carts, automatic film covering equipment, and mobile terminals for staff. When the device is a mobile terminal for staff, it essentially serves to notify staff to carry out the task.

[0019] The process of generating emergency response tasks is as follows: It receives monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time; wherein, the temperature sensors can be embedded in a preset position inside the concrete and installed in a position outside the concrete; they can be embedded at different depths. When the temperature difference between the inside and outside of the monitored area is greater than or equal to a threshold (any value between 10 and 25), an image of the corresponding concrete area is acquired; the image can be acquired by a configured image acquisition device for photographing the concrete area. The image is analyzed to identify abnormal events. The analysis includes: detecting cracks and water stains on the covering. When the area of ​​a crack or non-water stain area is greater than a preset area threshold, it is identified as an anomaly, and different anomalies are identified as different abnormal events depending on the type of anomaly. Emergency response tasks are determined based on an exception handling library. This library is pre-configured, and emergency response tasks are associated with specific exceptions within it.

[0020] The edge computing-based concrete curing operation monitoring method in this embodiment monitors the internal and external temperatures of the concrete. When an abnormality occurs, the control and execution device is adjusted to carry out emergency handling, thereby achieving monitoring of the concrete curing operation and ensuring its effective implementation.

[0021] Example 2: A concrete curing operation monitoring method based on edge computing further includes: integrating images of the concrete surface taken by the edge computing terminal to obtain a global image; monitoring and analyzing the global image to determine the operation time, operation type and operation requirements; generating operation tasks and operation monitoring instructions based on the operation time, operation type and operation requirements; sending the operation tasks to the operation receiving end and sending the operation monitoring instructions to the edge computing terminal.

[0022] The platform integrates images from all edge computing terminals to obtain a global image of the concrete pouring body. It monitors and analyzes the global image, mainly to guide the generation of emergency operations such as blowing off the covering and curing operations such as spraying at specified time intervals. The operation receiving end can be automated operation equipment (automatic spraying cart, etc.) or the mobile terminal of the staff. At this time, when the edge computing terminal receives the job monitoring instruction, it performs the following operations: The task monitoring instructions are parsed to determine the task time, task type, and task requirements. When the task monitoring instructions are generated on the platform, the data of task time, task type, and task requirements are included. The edge computing terminal only needs to extract the data corresponding to task time, task type, and task requirements by parsing the task monitoring instructions. Based on the job type and job requirements, a job monitoring library is requested to be configured; the edge computing terminal requests the configuration of the job monitoring library from the platform, and the configured job monitoring library must correspond to the job type and job requirements. The monitoring time for a task is determined based on the task time; the monitoring time can be configured to run from half an hour before the start time of the task to half an hour after the end time of the task. Based on the job monitoring time and job monitoring database, job tasks are monitored. The process starts at the beginning of the job monitoring time and analyzes the job images collected by the edge computing terminal according to the job monitoring database to determine whether the job has been performed and whether it is performed in accordance with regulations. This embodiment monitors job behavior through an edge computing terminal to ensure effective execution of the job. Specifically, monitoring of job tasks is based on job monitoring time and a job monitoring library. This includes: extracting an event monitoring time sequence table, model invocation rules, and analysis models corresponding to each monitoring event from the job monitoring library; sequentially invoking the analysis models according to the model invocation rules and the event monitoring time sequence table to analyze the job image and obtain the result codes corresponding to the analysis results of each monitoring event; forming coded data of the monitoring results for the job task based on the result codes corresponding to the analysis results; and reducing the communication pressure between the edge computing terminal and the platform when the edge computing terminal transmits the monitoring results back to the platform. Taking the maintenance operation of controlling an automatic sprinkler cart as an example, the event monitoring sequence is as follows: Monitoring event 1: Automatic sprinkler cart detected; Monitoring event 2: Automatic sprinkler cart sprays concrete; Monitoring event 3: The trajectory of the automatic sprinkler cart's spraying operation matches the pre-configured trajectory; Monitoring event 4: Automatic sprinkler cart moves out of the monitoring area. The model calling rule is as follows: First, the model corresponding to monitoring event 1 is called. After the result code of the model corresponding to monitoring event 1 corresponds to the completion status of monitoring event 1, the models corresponding to monitoring events 2 and 3 are called for synchronous recognition. After the pre-configured time value, the recognition model corresponding to monitoring event 4 is called for recognition. By configuring different model calling rules for each operation monitoring, the use of models is optimized, avoiding excessive consumption of the edge computing terminal's computing power. Furthermore, calling small models can ensure the accuracy of behavior recognition. And specificity; the models used for recognition are all pre-trained and converged. The result codes corresponding to each monitoring event are obtained by recognizing the image. The result codes correspond to the recognition results of the monitoring events. Taking monitoring event 1 as an example, the result codes are BBBB101A01 and BBBB101A02. Among them, BBBB101 represents the model recognition number, A01 indicates that the automatic sprinkler cart was recognized, and A02 indicates that the automatic sprinkler cart was not recognized. The encoded data includes two parts, one part represents the time, and the other part is the result code. For example, the encoded data is in the following order: the completion time of monitoring event 1, the result code of monitoring event 1, the total duration of monitoring event 2 (the total time for the automatic sprinkler cart to spray the concrete), the result code of monitoring event 2, the completion time of monitoring event 3, the result code of monitoring event 3, the completion time of monitoring event 4, and the result code of monitoring event 4.

[0023] When the platform receives the returned encoded data, it can determine whether the corresponding job has been executed by checking whether the encoded data contains the results of all monitoring events (completed). Furthermore, it can determine whether there are any anomalies in the job by analyzing the time corresponding to each monitoring event.

[0024] Example 3: A method for monitoring concrete curing operations based on edge computing, which further includes: Images of the preparatory stage of the maintenance operation are obtained through an edge computing terminal; the preparatory stage includes the operation of covering the concrete after it has been poured. The images of the operation are analyzed to construct a three-dimensional monitoring model of the curing operation. The three-dimensional monitoring model of the curing operation is essentially a model with a covering added to the three-dimensional model of the concrete pouring body. The covering is generally a part covering the concrete pouring body. The monitoring data sent by the edge computing terminal is labeled in the three-dimensional monitoring model to form a visualization model; When an abnormal event occurs, the investigation points are analyzed based on the 3D monitoring model. Abnormal events include: abnormal temperature, abnormal humidity, cracks, etc. The investigation points are those that may have the same probability as the location where the abnormal event occurred, based on the analysis of the 3D monitoring model. Based on the checkpoints, check tasks are generated and simultaneously sent to the execution device. Sending the checkpoints to the execution device allows for remedial action before anomalies occur. The analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. The segmentation rules include: segmenting the model once with the sensor installation location as the center and the center of the pre-configured mesh as the center; then radiating outward from the sensor installation location; and merging the segmented mesh at the radiation boundary of two adjacent sensors to obtain the finite element elements at the boundary location. An analysis dataset is constructed based on maintenance measures and monitoring data corresponding to finite element elements (FElement elements). For example, maintenance measures, such as coverings, can be quantified based on the location of the FElement element within the covering (distance from the nearest covering boundary). This yields four quantization parameters, corresponding to the distances to the nearest covering boundary in four directions. Monitoring data includes water stain severity data obtained from image analysis, as well as temperature and humidity data detected by embedded sensors. For water stain severity data quantification, the image region corresponding to the FElement element is compared with a pre-configured standard region image in a water stain quantization library to obtain the quantization parameters associated with the standard region image. Temperature and humidity data are obtained by radiating outwards from the FElement element with embedded sensors as reference units. Furthermore, to improve the accuracy of identifying inspection points, monitoring data from multiple time points can be used in the construction of the analysis dataset. For example, three monitoring data points are obtained at half-hour intervals. The analysis parameter set consists of the quantization parameters corresponding to the maintenance measures, the first monitoring data, the second monitoring data, and the third monitoring data. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; The reference dataset is matched with the analysis datasets of other finite element elements; the matching can be achieved by calculating similarity, for example, using the cosine similarity calculation method. The locations of finite element elements that match the preset conditions and correspond to the concrete are used as check points. When the similarity is greater than a preset threshold, the matching condition is considered to be met.

[0025] Specifically, data filling is performed by radiating outwards from finite element units with embedded sensors as reference units. For cases under the same cover, the quantitative parameters of the maintenance measures for the finite element unit to be filled are combined with the quantitative parameters of the maintenance measures for the reference unit (using a pre-configured analysis correspondence table) to obtain the filling coefficient. The filling data is then obtained by multiplying the filling coefficient by the monitoring data of the reference unit. For cases under different covers, the finite element unit located below the cover boundary between the two is identified as a transition unit. Based on the reference unit, the filling data of the transition unit is determined, and then the filling data of the finite element unit is determined using the transition unit as a reference for filling. This embodiment analyzes images taken during the preparatory stage of curing operations to construct a three-dimensional monitoring model for curing monitoring. Based on this model, a visual monitoring model is generated to achieve intuitive visual monitoring. When an anomaly occurs, it can also be used to determine the investigation points and conduct lateral investigation of anomalies to ensure the effective progress of concrete curing.

[0026] Example 4: The present invention also provides a concrete curing operation monitoring system based on edge computing, such as... Figure 2 As shown, it includes: a receiving module 1, a parsing module 2, and a control module 3; wherein, the receiving module 1 receives the emergency processing task sent by the edge computing terminal; the parsing module 2 parses the emergency processing task and determines the execution device; the control module 3 controls the execution device to execute the emergency processing task; The emergency response task generation process is as follows: receiving monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time; when the temperature difference between the inside and outside of the concrete is greater than or equal to a threshold, acquiring an image of the corresponding concrete area; analyzing the image to identify abnormal events; and determining the emergency response task based on the abnormal event processing library.

[0027] To enable the generation and execution of operations that are adapted to the actual conditions of concrete curing, the edge computing-based concrete curing operation monitoring system also includes: an operation analysis module; The job analysis module performs the following operations: By integrating images of the concrete surface captured by the edge computing terminal, a global image is obtained; Monitor and analyze the global image to determine the operation time, operation type, and operation requirements; Based on the job time, job type, and job requirements, generate job tasks and job monitoring instructions; The job task is sent to the job receiving end, and the job monitoring instructions are sent to the edge computing terminal.

[0028] At this time, when the edge computing terminal receives the job monitoring instruction, it performs the following operations: Analyze the job monitoring instructions to determine the job time, job type, and job requirements; Based on the job type and job requirements, please configure the job monitoring library; Determine the monitoring time for the task based on the task time; Based on job monitoring time and job monitoring database, job tasks are monitored.

[0029] To enable intuitive monitoring and to investigate other similar locations when anomalies occur, the edge computing-based concrete curing operation monitoring system also includes: a visualization monitoring module and an investigation and analysis module. The visualization monitoring module performs the following operations: acquiring operation images during the preparatory stage of maintenance work through the edge computing terminal; analyzing the operation images to construct a three-dimensional monitoring model of the maintenance work; marking the monitoring data sent by the edge computing terminal in the three-dimensional monitoring model to form a visualization model; the investigation and analysis module is used to analyze investigation points based on the three-dimensional monitoring model when abnormal events occur; and generating investigation tasks based on the investigation points and sending them synchronously to the execution device.

[0030] The analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. An analysis dataset is constructed based on the maintenance measures and monitoring data corresponding to the finite element elements. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; Match the reference dataset with the analysis datasets of other finite element elements; The locations of finite element elements that meet the preset conditions and correspond to the concrete are used as inspection points.

[0031] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for monitoring concrete curing operations based on edge computing, characterized in that, include: Receive emergency response tasks sent by edge computing terminals; Analyze emergency response tasks and determine the execution devices; The control and execution device performs emergency response tasks; The process of generating emergency response tasks is as follows: It receives monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time. When the temperature difference between the inside and outside of the monitored area is greater than or equal to the threshold, an image of the corresponding concrete area is acquired. Analyze the images to identify anomalous events; Based on the exception event handling library, determine the emergency response tasks; Images of the preparatory stage of the maintenance operation are obtained through an edge computing terminal; the preparatory stage includes the operation of covering the concrete after it has been poured. The operation images are analyzed to construct a three-dimensional monitoring model of the maintenance operation; the three-dimensional monitoring model is essentially a model with a covering material added to a three-dimensional model of the concrete pouring body. The monitoring data sent by the edge computing terminal is labeled in the three-dimensional monitoring model to form a visualization model; When an abnormal event occurs, the investigation points are analyzed based on the 3D monitoring model; Based on the investigation points, investigation tasks are generated and simultaneously sent to the execution device; The analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. Based on the maintenance measures and monitoring data corresponding to the finite element elements, an analysis dataset is constructed. The maintenance measures are quantized according to the location of the finite element elements on the cover, resulting in four quantization parameters. These four parameters correspond to the distances to the nearest cover boundary in four directions. For finite element elements that do not have embedded sensors and require filling, their monitoring data is filled using a radial method radiating outwards from the finite element elements with embedded sensors as reference units. Specifically, for cases where the reference unit and the finite element element to be filled are under the same cover, a filling coefficient is obtained by combining the quantization parameters of the maintenance measures for the finite element element to be filled with those of the reference unit. The filling data for the finite element element to be filled is then obtained by multiplying the filling coefficient by the monitoring data of the reference unit. For cases where they are under different covers, the finite element element located under the cover boundary between them is identified as a transition unit. The filling data of the transition unit is determined based on the monitoring data of the reference unit, and then the filling data of the finite element element to be filled is determined and filled using the transition unit as a reference. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; Match the reference dataset with the analysis datasets of other finite element elements; The locations of finite element elements that match the preset conditions and correspond to the concrete are used as inspection points.

2. The method for monitoring concrete curing operations based on edge computing as described in claim 1, characterized in that, Also includes: By integrating images of the concrete surface captured by the edge computing terminal, a global image is obtained; Monitor and analyze the global image to determine the operation time, operation type, and operation requirements; Based on the job time, job type, and job requirements, generate job tasks and job monitoring instructions; The job task is sent to the job receiving end, and the job monitoring instructions are sent to the edge computing terminal.

3. The method for monitoring concrete curing operations based on edge computing as described in claim 2, characterized in that, When the edge computing terminal receives a job monitoring instruction, it performs the following operations: Analyze the job monitoring instructions to determine the job time, job type, and job requirements; Based on the job type and job requirements, please configure the job monitoring library; Determine the monitoring time for the task based on the task time; Based on job monitoring time and job monitoring database, job tasks are monitored.

4. A concrete curing operation monitoring system based on edge computing, characterized in that, include: The system comprises a receiving module, a parsing module, and a control module; the receiving module receives emergency processing tasks sent by the edge computing terminal; the parsing module parses the emergency processing tasks and determines the execution device; and the control module controls the execution device to execute the emergency processing tasks. The emergency response task generation process is as follows: receiving monitoring data from temperature sensors installed inside and outside the concrete to monitor the temperature inside and outside the concrete in real time; when the temperature difference between the inside and outside of the concrete is greater than or equal to a threshold, acquiring an image of the corresponding concrete area; analyzing the image to determine the abnormal event; and determining the emergency response task based on the abnormal event processing library. The edge computing-based concrete curing operation monitoring system also includes: a visualization monitoring module and a troubleshooting and analysis module; The visualization monitoring module performs the following operations: acquiring images of the preparatory stage of the curing operation through an edge computing terminal; the preparatory stage includes the stage of covering the concrete after pouring; analyzing the operation images to construct a three-dimensional monitoring model of the curing operation; the three-dimensional monitoring model is essentially a model with the covering material added to a three-dimensional model of the concrete pouring body; marking the monitoring data sent by the edge computing terminal in the three-dimensional monitoring model to form a visualization model; the investigation and analysis module is used to analyze investigation points based on the three-dimensional monitoring model when abnormal events occur; generating investigation tasks based on the investigation points and synchronously sending them to the execution device; The analysis steps for the investigation points are as follows: The 3D monitoring model is segmented using finite element methods to obtain multiple finite element elements. Based on the maintenance measures and monitoring data corresponding to the finite element elements, an analysis dataset is constructed. The maintenance measures are quantized according to the location of the finite element elements on the cover, resulting in four quantization parameters. These four parameters correspond to the distances to the nearest cover boundary in four directions. For finite element elements that do not have embedded sensors and require filling, their monitoring data is filled using a radial method radiating outwards from the finite element elements with embedded sensors as reference units. Specifically, for cases where the reference unit and the finite element element to be filled are under the same cover, a filling coefficient is obtained by combining the quantization parameters of the maintenance measures for the finite element element to be filled with those of the reference unit. The filling data for the finite element element to be filled is then obtained by multiplying the filling coefficient by the monitoring data of the reference unit. For cases where they are under different covers, the finite element element located under the cover boundary between them is identified as a transition unit. The filling data of the transition unit is determined based on the monitoring data of the reference unit, and then the filling data of the finite element element to be filled is determined and filled using the transition unit as a reference. The analysis dataset of the finite element elements corresponding to the abnormal event is determined as the reference dataset; Match the reference dataset with the analysis datasets of other finite element elements; The locations of finite element elements that match the preset conditions and correspond to the concrete are used as inspection points.

5. The edge computing-based concrete curing operation monitoring system as described in claim 4, characterized in that, Also includes: Job analysis module; The job analysis module performs the following operations: By integrating images of the concrete surface captured by the edge computing terminal, a global image is obtained; Monitor and analyze the global image to determine the operation time, operation type, and operation requirements; Based on the job time, job type, and job requirements, generate job tasks and job monitoring instructions; The job task is sent to the job receiving end, and the job monitoring instructions are sent to the edge computing terminal.

6. The edge computing-based concrete curing operation monitoring system as described in claim 5, characterized in that, When the edge computing terminal receives a job monitoring instruction, it performs the following operations: Analyze the job monitoring instructions to determine the job time, job type, and job requirements; Based on the job type and job requirements, please configure the job monitoring library; Determine the monitoring time for the task based on the task time; Based on job monitoring time and job monitoring database, job tasks are monitored.

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