A method, device, equipment and medium for visualizing image supervision of project progress

Abstract

The present application relates to the field of image processing technology, and in particular to a method, device, equipment and medium for visualizing images of project progress, wherein the method comprises identifying the completed construction progress and the latest project image of each construction project within a first preset time period; determining the newly added construction content of each construction project according to the preset construction plan and completed construction progress of each construction project on each monitoring date, and determining the construction prediction image of each construction project on each monitoring date based on each newly added construction content and the latest project image; identifying the target construction prediction image of each construction project corresponding to the target monitoring date and integrating them to obtain the predicted overall construction image; matching the actual overall construction image with the predicted overall construction image, and generating monitoring feedback information according to the matching result. The present application can reduce the workload of relevant supervisors in the supervision process, thereby improving the accuracy of supervision.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a method, device, equipment and medium for visualizing image supervision of engineering progress. Background Art

[0002] The construction of municipal engineering projects may have an impact on urban traffic and residents' lives. If the construction progress is delayed, it may lead to longer closures of the construction area and traffic congestion, causing inconvenience to citizens. In addition, the construction process may involve many complex processes and technologies. If the operation is improper or the material quality is not up to standard, project quality problems may occur. Therefore, by supervising the construction process, these problems can be discovered and corrected in a timely manner to ensure that the project quality meets relevant standards and specifications. Therefore, the construction progress of municipal engineering projects is an indicator that engineering managers pay close attention to. Relevant managers need to pay close attention to the construction progress, discover problems in a timely manner and take measures to ensure that the project is completed on time and with quality.

[0003] In the related art, construction images are generally collected in real time by cameras installed at the construction site, and the image content is then observed and analyzed to monitor the construction progress of the construction site. However, since there are many personnel, building materials, and construction areas at the municipal engineering construction site, and different construction stages may have different construction progress standards, it is necessary to refer to multiple construction progress standards when observing the on-site images to determine whether the construction progress of each construction area at different construction stages meets the standards. These construction progress standards may not be consistent, and therefore, the workload of relevant supervisors may increase, which may affect the accuracy of supervision. Summary of the invention

[0004] In order to reduce the workload of relevant supervisory personnel during the supervision process and thus improve the accuracy of supervision, the present application provides a method, device, equipment and medium for visualizing image supervision of engineering progress.

[0005] In the first aspect, the present application provides a method for visualizing an image of a project progress, which adopts the following technical solution:

[0006] A method for visualizing an image of a project progress, comprising:

[0007] Acquire a construction image within a first preset time period, and a preset construction plan corresponding to each construction project included in the construction image on each monitoring date, wherein the construction image includes at least one construction project, and each monitoring date is a date within a second preset time period;

[0008] According to the construction images, identifying the completed construction progress and the latest project images of each construction project within the first preset time period;

[0009] Determine the newly added construction content of each construction project on each monitoring date according to the preset construction plan and completed construction progress of each construction project on each monitoring date, and determine the construction forecast image of each construction project on each monitoring date based on the newly added construction content and the corresponding latest project image of each construction project on each monitoring date;

[0010] Identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain the predicted overall construction image corresponding to the target monitoring date;

[0011] The actual overall construction image corresponding to the target monitoring date is acquired, the actual overall construction image is matched with the predicted overall construction image, and monitoring feedback information is generated according to the matching result.

[0012] By adopting the above technical scheme, the construction conditions corresponding to each monitoring date in the future period are predicted based on the actual construction conditions, so as to improve the adaptability between the prediction results and the corresponding construction conditions in the future period. Moreover, by distinguishing the prediction results corresponding to each monitoring date, it is convenient for relevant supervisors to flexibly call and view the construction progress corresponding to each monitoring date. In addition, through the newly added construction content of each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date can be predicted, so as to intuitively display the prediction results corresponding to each construction project on each monitoring date, so as to facilitate relevant supervisors to view the prediction results. Finally, by matching the actual overall construction image corresponding to the target monitoring date with the predicted overall construction image, it is convenient to timely discover possible problems in the construction process, and generate monitoring feedback information based on the matching results. By collecting construction images and predicting based on the collected content, the construction process is visualized, without the need for relevant supervisors to check each construction project based on the construction standards corresponding to each construction stage, so as to reduce the workload of relevant supervisors in the supervision process, and thus improve the supervision accuracy.

[0013] In a possible implementation, determining the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content and the corresponding latest project image of each construction project on each monitoring date includes:

[0014] Determine the average construction rate of each construction project according to the completion progress of each construction project within the first preset time period;

[0015] According to the average construction rate of each construction project, the newly added construction content on each monitoring date and the corresponding preset simulation construction model, the construction process of each construction project when the corresponding newly added construction content is completed on each monitoring date is simulated to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date;

[0016] The simulated newly added construction images corresponding to each construction project on each date are superimposed on the latest project images corresponding to each construction project to obtain the construction prediction images corresponding to each construction project on each monitoring date.

[0017] By adopting the above technical scheme, the construction rate of relevant construction personnel can be analyzed and determined through the construction progress within the first preset time period. In addition, the construction process corresponding to each monitoring date is simulated using the average construction rate and newly added construction content determined by the analysis of the first preset time period, and then the construction prediction image corresponding to each construction project on each monitoring date is determined based on the simulation results, so as to improve the accuracy of construction prediction. Finally, by simulating the construction process of each construction project on each monitoring date, problems in the construction process can be discovered in advance, and adjustments can be made in the actual construction process, thereby improving the efficiency of construction supervision.

[0018] In a possible implementation, after determining the construction prediction image corresponding to each construction project on each monitoring date, the method further includes:

[0019] Classify multiple construction prediction images according to the monitoring date, and obtain an image link list corresponding to each monitoring date according to the classification result and the preset data link list;

[0020] Writing the image chain list corresponding to each monitoring date into a preset time wheel to obtain a monitoring time wheel, wherein the monitoring time wheel includes multiple time bins, each time bin corresponding to a monitoring date;

[0021] Determine the execution interval between corresponding time bins based on each monitoring date;

[0022] An execution time wheel is obtained according to the monitoring time wheel and the execution interval between each time bin in the monitoring time wheel.

[0023] By adopting the above technical solution, by storing the construction prediction images corresponding to each construction project on each monitoring date into the execution time wheel for preservation, it is convenient to improve the standardization of the retrieval process, that is, by selecting the corresponding time bin, all prediction images in the corresponding time bin can be read, without the need to read multiple identifications and screenings from a large number of prediction images, thereby improving the speed and accuracy of the image reading process.

[0024] In a possible implementation, the identifying target construction prediction image of each construction project corresponding to the target monitoring date and integrating all the target construction prediction images include:

[0025] Obtaining the current time bin pointed by the time wheel pointer, and determining whether the current time bin pointed to is the target monitoring date;

[0026] If so, retrieve the image linked list currently pointing to the time bin, obtain multiple target construction prediction images corresponding to the target monitoring date, and identify the construction features contained in each target construction prediction image;

[0027] Multiple target construction prediction images are integrated according to each construction feature.

[0028] By adopting the above technical solution, since the time wheel pointer can rotate according to the execution interval, when the time wheel pointer points to the corresponding time bin, the image integration operation in the corresponding time bin is executed, so that the construction progress can be checked at any time. However, the relevant supervisors can also check the construction progress by randomly selecting the viewing date, so as to improve the flexibility in checking the construction progress. In addition, multiple predicted images are integrated according to the construction characteristics of each construction project, so as to improve the integration rate and the accuracy of the integration results.

[0029] In a possible implementation, matching the actual overall construction image with the predicted overall construction image and generating monitoring feedback information according to the matching result includes:

[0030] Matching the actual overall construction image with the predicted overall construction image, and determining an abnormal area, wherein the degree of matching between the actual overall construction image and the predicted overall construction image in the abnormal area is lower than a preset matching value;

[0031] Identify the abnormal construction projects contained in the abnormal area, and retrieve the actual construction image and the simulation image of each abnormal construction project within a third preset time period, and determine the abnormal starting time and the abnormal tracing image frame corresponding to the abnormal starting time;

[0032] Monitoring feedback information is generated based on the abnormal construction project, the abnormal starting time, and the abnormal tracing image frame corresponding to the abnormal starting time.

[0033] By adopting the above technical solution, the abnormal area can be accurately located by image comparison, and then the construction situation before the abnormality occurred in the abnormal area can be analyzed to trace the cause of the abnormality. Finally, the abnormal construction project, the start time of the abnormality and the abnormal tracing image are fed back together to improve the effectiveness of the monitoring feedback information, so that the relevant supervisory personnel can respond to and resolve abnormal situations in the construction process in a timely manner.

[0034] In one possible implementation, the method further includes:

[0035] Identify the abnormal time bin corresponding to the abnormal construction project from the execution time wheel, and wake up the hidden time bin corresponding to the abnormal time bin, where the observation date corresponding to the hidden time bin is the date between the abnormal time bin and the next time bin;

[0036] Determine the observation frequency corresponding to the hidden time bin according to the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area and a preset mapping relationship, wherein the preset mapping relationship is a corresponding relationship between the matching degree and the observation frequency;

[0037] The hidden time bin is started based on the observation frequency, an observation result corresponding to each observation date is obtained, and each observation result is fed back.

[0038] By adopting the above technical solution, the progress of abnormal construction projects can be monitored by starting the hidden time bin after an abnormality occurs, rather than waiting until the monitoring date to view it. By increasing the supervision frequency, it is convenient to analyze and view the changes in the abnormal construction area to determine whether the abnormal construction area has been corrected in time, thereby avoiding the situation in the abnormal construction area from worsening.

[0039] In the second aspect, the present application provides a project progress visualization image monitoring device, which adopts the following technical solution:

[0040] A project progress visualization image monitoring device, comprising:

[0041] A construction image acquisition module is used to acquire a construction image within a first preset time period, and a preset construction plan corresponding to each construction project contained in the construction image on each monitoring date, wherein the construction image contains at least one construction project, and each monitoring date is a date within a second preset time period;

[0042] A construction progress identification module, used to identify the completed construction progress and the latest project image of each construction project within the first preset time period according to the construction image;

[0043] A construction prediction image determination module is used to determine the newly added construction content corresponding to each construction project on each monitoring date according to the preset construction plan and completed construction progress corresponding to each construction project on each monitoring date, and determine the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image;

[0044] An image integration module is used to identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain the predicted overall construction image corresponding to the target monitoring date;

[0045] The monitoring feedback information generating module is used to obtain the actual overall construction image corresponding to the target monitoring date, match the actual overall construction image with the predicted overall construction image, and generate monitoring feedback information according to the matching result.

[0046] By adopting the above technical scheme, the construction conditions corresponding to each monitoring date in the future period are predicted based on the actual construction conditions, so as to improve the adaptability between the prediction results and the corresponding construction conditions in the future period. Moreover, by distinguishing the prediction results corresponding to each monitoring date, it is convenient for relevant supervisors to flexibly call and view the construction progress corresponding to each monitoring date. In addition, through the newly added construction content of each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date can be predicted, so as to intuitively display the prediction results corresponding to each construction project on each monitoring date, so as to facilitate relevant supervisors to view the prediction results. Finally, by matching the actual overall construction image corresponding to the target monitoring date with the predicted overall construction image, it is convenient to timely discover possible problems in the construction process, and generate monitoring feedback information based on the matching results. By collecting construction images and predicting based on the collected content, the construction process is visualized, without the need for relevant supervisors to check each construction project based on the construction standards corresponding to each construction stage, so as to reduce the workload of relevant supervisors in the supervision process, and thus improve the supervision accuracy.

[0047] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0048] An electronic device, comprising:

[0049] at least one processor;

[0050] Memory;

[0051] At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned project progress visualization image supervision method.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0053] A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the above-mentioned project progress visualization image supervision method.

[0054] In summary, the present application includes at least one of the following beneficial technical effects:

[0055] Based on the actual construction situation, the construction situation corresponding to each monitoring date in the future is predicted, which is convenient for improving the adaptability between the prediction results and the corresponding construction situation in the future. In addition, by distinguishing the prediction results corresponding to each monitoring date, it is convenient for relevant supervisors to flexibly call and view the construction progress corresponding to each monitoring date. In addition, through the newly added construction content of each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date can be predicted, so as to intuitively display the prediction results corresponding to each construction project on each monitoring date, so as to facilitate relevant supervisors to view the prediction results. Finally, by matching the actual overall construction image corresponding to the target monitoring date with the predicted overall construction image, it is convenient to timely discover possible problems in the construction process, and generate monitoring feedback information based on the matching results. By collecting construction images and predicting based on the collected content, the construction process is visualized, without the need for relevant supervisors to check each construction project based on the construction standards corresponding to each construction stage, thereby reducing the workload of relevant supervisors in the supervision process and improving the supervision accuracy.

[0056] The abnormal area can be accurately located through image comparison, and the construction situation before the abnormality occurred in the abnormal area can be analyzed to trace the cause of the abnormality. Finally, the abnormal construction project, the start time of the abnormality and the abnormal tracing image can be fed back together to improve the effectiveness of the monitoring feedback information, so that relevant supervisory personnel can respond to and resolve abnormal situations in the construction process in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flow chart of a method for visualizing an image of a project progress in an embodiment of the present application;

[0058] Figure 2It is a structural diagram of an execution time wheel in an embodiment of the present application;

[0059] Figure 3 This is a schematic diagram of the structure of a project progress visualization image monitoring device in an embodiment of the present application;

[0060] Figure 4 It is a structural schematic diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following is combined with Figure 1-4 This application is described in further detail.

[0062] After reading this specification, those skilled in the art may make modifications to this embodiment without any creative contribution as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0064] Specifically, the embodiment of the present application provides a method for visualizing and supervising the progress of an engineering project, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0065] refer to Figure 1 , Figure 1 : is a flow chart of a method for visualizing an image of a project progress in an embodiment of the present application, the method comprising steps S110 to S150, wherein:

[0066] Step S110: Acquire a construction image within a first preset time period and a preset construction plan corresponding to each construction project contained in the construction image at each monitoring date, wherein the construction image contains at least one construction project and each monitoring date is a date within a second preset time period.

[0067] Specifically, the first preset time period is adjacent to the second preset time period, and the duration corresponding to the first preset time period is shorter than the duration corresponding to the second preset time period. For example, if the first preset time period is from August 1 to August 7, the second preset time period may be from August 8 to August 31. The duration corresponding to the first preset time period and the second preset time is not specifically limited in the embodiment of the present application, and may be set by relevant technical personnel according to actual needs. The construction image within the first preset time period may be collected by an image acquisition device set up at the municipal construction site to be supervised, and then uploaded to an electronic device. The construction projects contained in the construction image are the contents that need to be executed during the construction process. For example, the construction projects may be wall construction, foundation excavation, etc. Different construction sites correspond to different construction projects. The specific construction projects are not specifically limited in the embodiment of the present application, and may be set by relevant technical personnel according to actual construction conditions.

[0068] The monitoring date is the date on which the relevant supervisory personnel need to check the construction progress within the second preset time period. The second preset time period may include multiple monitoring dates. For example, when the second preset time period is from August 8 to August 31, August 18 and August 28 can be set as monitoring dates, and August 13, August 18, August 23 and August 28 can also be set as monitoring dates. The number of monitoring dates is not specifically limited in the embodiments of the present application. The more monitoring dates there are, the higher the monitoring frequency within the second preset time period. The preset construction plan corresponding to each monitoring date can be uploaded to the electronic device by the relevant design personnel. The preset construction plan for each monitoring date is used for the completion of each construction project on the corresponding monitoring date. For example, the completion of construction project 1 on August 13 is 30%.

[0069] Step S120: According to the construction image, the completed construction progress and the latest project image of each construction project within a first preset time period are identified.

[0070] Specifically, the latest project image is the state of the construction project at the last moment in the first preset time period, and can be obtained from the construction image of the first preset time period by video frame extraction. The corresponding construction project features are identified from each latest project image, and the corresponding project construction size is identified based on each construction project feature. According to the matching of the project construction size with the corresponding construction completion standard, the completion progress of each construction project in the first preset time period can be determined.

[0071] Step S130: Determine the newly added construction content corresponding to each construction project on each monitoring date based on the preset construction plan and completed construction progress corresponding to each construction project on each monitoring date, and determine the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image.

[0072] Specifically, the newly added construction content is the construction content that needs to be completed between the last moment of the first preset time period and each monitoring date. For example, the completion progress of Construction Project 1 in the first preset time period is 30%. According to the preset construction plan, it needs to reach 45% on the monitoring date of August 18. The corresponding newly added construction content on August 18 is 45%-30%=15%; it needs to reach 85% on the monitoring date of August 28. The corresponding newly added construction content on August 28 is 85%-30%=55%.

[0073] Since there is a corresponding relationship between the completed construction progress corresponding to the first preset time period and the latest project image of each construction project, the newly added construction content corresponding to each monitoring date can be converted into a project image, and then the construction prediction image corresponding to each construction project on each monitoring date can be obtained by image superposition.

[0074] Furthermore, in order to improve the accuracy of construction prediction, based on the newly added construction content and the corresponding latest project image of each construction project on each monitoring date, the construction prediction image corresponding to each construction project on each monitoring date is determined, which may specifically include:

[0075] According to the completed construction progress of each construction project within the first preset time period, the average construction rate of each construction project is determined; according to the average construction rate of each construction project, the newly added construction content on each monitoring date and the corresponding preset simulation construction model, the construction process of each construction project when the corresponding newly added construction content is completed on each monitoring date is simulated to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date; the simulated newly added construction image corresponding to each construction project on each date is superimposed on the latest project image corresponding to each construction project to obtain the construction prediction image corresponding to each construction project on each monitoring date.

[0076] Specifically, the average construction rate of the construction project can be calculated based on the completion progress and the duration corresponding to the first preset time period. For example, the completion progress of construction project 1 in the first preset time period is 21%, and the duration corresponding to the first preset time period is 7 days. Then the average construction rate of construction project 1 is 3% of the daily completion progress. Each construction project corresponds to a preset simulation construction model, which is constructed based on the construction project and the corresponding construction personnel information. In addition to the personal information of each construction personnel, the construction personnel information also includes the ability score of each construction personnel. The preset simulation construction model constructed based on the construction personnel information has a high degree of adaptability to the actual construction situation, and is also convenient for improving the accuracy of the simulation results. In the process of simulated construction, it is only necessary to import the average construction rate of the construction project and the newly added construction content of each monitoring date into the preset simulation construction model, and the simulated newly added image corresponding to the construction project on each monitoring date can be obtained, and the simulated newly added image corresponds to the newly added construction content. Each preset simulation construction model is obtained after training with a large amount of sample data, and the sample data includes sample construction content and sample newly added images corresponding to each sample construction content.

[0077] By overlaying AR images, the simulated newly added construction images corresponding to each monitoring date are overlaid onto the latest project images to obtain the construction prediction images corresponding to each construction project on each monitoring date. The construction prediction images correspond to the degree of completion that needs to be achieved on the monitoring date. For example, when the monitoring date, August 18, needs to reach 45%, the construction project in the construction prediction image corresponding to August 18 is the project construction size corresponding to the degree of completion of 45%. The construction rate of the relevant construction personnel can be analyzed and determined through the construction progress within the first preset time period. In addition, the construction process corresponding to each monitoring date is simulated using the average construction rate and newly added construction content determined by the analysis of the first preset time period, and then the construction prediction images corresponding to each construction project on each monitoring date are determined based on the simulation results, so as to improve the accuracy of the construction prediction. Finally, by simulating the construction process of each construction project on each monitoring date, problems in the construction process can be discovered in advance and adjusted during the actual construction process, thereby improving the efficiency of construction supervision.

[0078] After construction prediction and image superposition, the construction prediction image corresponding to each construction project on each monitoring date can be obtained. In order to facilitate the management of multiple construction prediction images, the method provided in the embodiment of the present application also includes:

[0079] According to the monitoring date, multiple construction prediction images are classified, and according to the classification results and the preset data linked list, the image linked list corresponding to each monitoring date is obtained; the image linked list corresponding to each monitoring date is written into the preset time wheel to obtain the monitoring time wheel, which includes multiple time bins, and each time bin corresponds to a monitoring date; according to each monitoring date, the execution interval between the corresponding time bins is determined; according to the monitoring time wheel and the execution interval between each time bin in the monitoring time wheel, the execution time wheel is obtained.

[0080] Specifically, multiple construction prediction images are first distinguished according to the monitoring date to obtain multiple groups of construction prediction images, and each group of construction prediction images corresponds to the same monitoring date. The preset data linked table is used to store the construction prediction images, and each group corresponds to a preset data linked table. After each group of construction prediction images is written into the preset data linked table, the image linked table corresponding to each monitoring date can be obtained. The order of construction prediction images corresponding to different construction projects in different image linked tables can be consistent. For example, the arrangement order of each construction prediction image in the image linked table corresponding to the monitoring date August 18 is construction project 1, construction project 2, construction project 3, and construction project 4. The arrangement order of each construction prediction image in the image linked table corresponding to August 28 is also construction project 1, construction project 2, construction project 3, and construction project 4. By unifying the order of each construction prediction image in different image linked tables, it is convenient to improve the standardization of the image management process.

[0081] The preset time wheel pointer is a device used to record time. It usually consists of a disc and a pointer. The disc is divided into multiple time bins. Each time bin represents a specific time point. The pointer points to the current time bin, indicating the current time. There is a time interval between time bins. When the image list corresponding to each monitoring date is written into the preset time wheel, the binding relationship between the time bin and each monitoring date can be established, such as Figure 2 As shown, each time bin corresponds to a monitoring date and is connected to an image linked list. When the pointer of the preset time wheel points to a time bin, the image linked list corresponding to the time bin can be read. The execution interval between time bins is related to the monitoring date corresponding to the time bin. For example, the monitoring date corresponding to time bin 1 is August 18, and the monitoring date corresponding to time bin 2 is August 20. At this time, the execution interval between time bin 1 and time bin 2 is 2 days, that is, the execution time wheel will automatically read the image linked list corresponding to time bin 1 on August 18 for subsequent supervision. Similarly, it will automatically read the image linked list corresponding to time bin 2 on August 20 for subsequent supervision. In order to improve the utilization of storage space, the image linked list that has been called in the execution time wheel can be cleaned up regularly.

[0082] By storing the construction prediction images corresponding to each construction project on each monitoring date into the execution time wheel for preservation, it is convenient to improve the standardization of the retrieval process. That is, by selecting the corresponding time bin, all prediction images in the corresponding time bin can be read without reading multiple identifications and screenings from a large number of prediction images, thereby improving the speed and accuracy of the image reading process.

[0083] Step S140: Identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain the predicted overall construction image corresponding to the target monitoring date.

[0084] Specifically, the target monitoring date can be uploaded by relevant supervisors. The target monitoring date may be the date corresponding to the time bin pointed to by the pointer in the current execution time wheel, or it may not be the date. That is, the execution time wheel can automatically retrieve the image list according to the monitoring date corresponding to each time bin and the execution interval between the time bins for subsequent supervision and prediction work. The relevant supervisors can also specify to view the image list corresponding to a certain monitoring date according to actual needs. All construction prediction images in the image list corresponding to the target monitoring date are determined as target construction prediction images. Since each target construction prediction image is a construction project of the municipal construction site to be supervised, multiple target construction prediction images can be integrated into a predicted overall construction image through the features of the package in the image. The predicted overall construction image contains all target construction prediction images corresponding to the target monitoring date.

[0085] Furthermore, in order to improve the integration rate and the accuracy of the integration results, the target construction prediction image of each construction project corresponding to the target monitoring date is identified, and all the target construction prediction images are integrated, which may specifically include:

[0086] Get the time bin currently pointed to by the time wheel pointer, and determine whether the time bin currently pointed to is the target monitoring date; if so, retrieve the image list of the time bin currently pointed to, obtain multiple target construction prediction images corresponding to the target monitoring date, and identify the construction features contained in each target construction prediction image; integrate multiple target construction prediction images according to each construction feature.

[0087] Specifically, since the time wheel execution in the execution time wheel is always in a rotating state, it is necessary to first determine whether the monitoring date corresponding to the current execution time bin is the target monitoring date. If so, directly call the image linked list currently pointing to the time bin; if not, it is necessary to traverse from the execution time wheel, and then call the corresponding image linked list after locating the time bin corresponding to the target monitoring date.

[0088] The construction features contained in each target construction prediction image can be identified by a feature recognition algorithm. The specific feature recognition algorithm is not specifically limited in the embodiments of this application, as long as the construction features contained in each target construction prediction image can be identified. In addition to being able to characterize the features of the corresponding construction project, the construction features in the target construction prediction image must also include an area identifier that can ensure that each construction project corresponds to the construction area. Each target construction prediction image is spliced ​​based on the construction features in each target construction prediction image, and the predicted construction situation corresponding to the target monitoring date of the municipal construction site to be supervised can be determined.

[0089] Since the time wheel pointer can rotate according to the execution interval, when the time wheel pointer points to the corresponding time bin, the image integration operation in the corresponding time bin is executed, so that the construction progress can be checked at any time. However, the relevant supervisors can also check the construction progress by randomly selecting the viewing date, so as to improve the flexibility in checking the construction progress. In addition, multiple predicted images are integrated according to the construction characteristics of each construction project, so as to improve the integration rate and the accuracy of the integration results.

[0090] Step S150: Acquire the actual overall construction image corresponding to the target monitoring date, match the actual overall construction image with the predicted overall construction image, and generate monitoring feedback information according to the matching result.

[0091] Specifically, the actual overall construction image corresponding to the target monitoring date can be collected by the image acquisition device set up at the municipal construction site to be supervised and uploaded to the electronic device. The predicted overall construction image is obtained according to the actual construction status corresponding to the first time period and the preset construction plan, while the actual overall construction image is the current construction status actually collected on the target monitoring date. By matching the predicted overall construction image with the actual overall construction image, it is convenient to analyze whether the actual construction progress is in line with the construction plan. After the monitoring feedback information is generated, the monitoring feedback information can be forwarded to the terminal device of the relevant supervisor. The relevant supervisor can control the electronic device to regularly feedback the monitoring feedback information of the corresponding supervision date by setting the feedback time and frequency in advance, without the need to check each construction project based on the construction standards corresponding to each construction stage before checking or analyzing whether the construction progress is in line with the construction plan.

[0092] For the embodiment of the present application, the construction conditions corresponding to each monitoring date in the future are predicted based on the actual construction conditions, so as to improve the adaptability between the prediction results and the corresponding construction conditions in the future, and by distinguishing the prediction results corresponding to each monitoring date, it is convenient for relevant supervisors to flexibly call and view the construction progress corresponding to each monitoring date. In addition, through the newly added construction content of each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date can be predicted, so as to facilitate the intuitive display of the prediction results corresponding to each construction project on each monitoring date, so as to facilitate the relevant supervisors to view the prediction results. Finally, by matching the actual overall construction image corresponding to the target monitoring date with the predicted overall construction image, it is convenient to timely discover possible problems in the construction process, and generate monitoring feedback information based on the matching results. By collecting construction images and predicting based on the collected content, the construction process is visualized, without the need for relevant supervisors to check each construction project based on the construction standards corresponding to each construction stage, thereby reducing the workload of relevant supervisors in the supervision process and improving the supervision accuracy.

[0093] Furthermore, in order to improve the effectiveness of the monitoring feedback information, the actual overall construction image is matched with the predicted overall construction image, and the monitoring feedback information is generated according to the matching result, which may specifically include:

[0094] The actual overall construction image is matched with the predicted overall construction image, and the abnormal area is determined, wherein the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area is lower than the preset matching value; the abnormal construction projects contained in the abnormal area are identified, and the actual construction image and the simulated image of each abnormal construction project within a third preset time period are retrieved to determine the abnormal starting time and the abnormal tracing image frame corresponding to the abnormal starting time; monitoring feedback information is generated based on the abnormal construction projects, the abnormal starting time and the abnormal tracing image frame corresponding to the abnormal starting time.

[0095] Specifically, when matching the actual overall construction image with the predicted overall construction image, the actual overall construction image and the predicted overall construction image can be firstly cut according to the preset division rules to obtain multiple groups of segmented images, and the construction sites contained in each group of segmented images are consistent. Each group of segmented images is matched to determine whether there are distinguishing points in each group of segmented images, and the image segmentation area containing the distinguishing points is determined as an abnormal area. Therefore, the number of abnormal areas is not specifically limited in the embodiment of the present application, and there can be 1 or more. The preset matching value can be 98%, or 95%. The specific value is not specifically limited in the embodiment of the present application. The higher the preset matching value, the higher the corresponding abnormal judgment accuracy. Since the abnormal area is not divided according to the construction project, multiple construction projects may be contained in the same abnormal area. The construction projects contained in the abnormal area are identified according to the feature recognition algorithm, and the identified construction projects are determined as abnormal construction projects.

[0096] The third preset time period is the time period between the last non-abnormal monitoring date and the current monitoring date. For example, the current monitoring date is August 28, the last monitoring date is August 18, and no abnormal situation occurred during the monitoring on the last monitoring date. At this time, the time period between August 18 and August 28 can be determined as the third preset time period. Since no abnormal situation was detected on the last monitoring date, the abnormal situation has a high probability of occurring within the third preset time period. By analyzing the actual construction images within the third preset time period, it is convenient to trace the abnormal situation.

[0097] The third preset time period is divided into multiple comparison time periods. By comparing the actual construction image and the simulation image in each comparison time period, the comparison time period without abnormal conditions is eliminated to narrow the comparison range. For example, the third preset time period corresponds to 10 days. At this time, the third preset time period can be divided into 5 comparison time periods, each of which corresponds to 2 days. By comparing whether there is a difference between the actual construction image and the simulation image in each comparison time period, it is determined that there is no difference between the first comparison time period and the second comparison time period, and there is a difference in the third comparison time period. The third comparison time period is then compared frame by frame to determine the abnormal starting time, that is, the starting time when the actual construction image and the simulation image have a difference. By dividing the third preset time period and then determining the abnormal starting time, rather than performing frame comparison on all the third preset time periods, it is convenient to reduce the processing amount of the electronic device, thereby improving the processing rate of the electronic device.

[0098] The abnormality tracing image frame is the image frame corresponding to the start time of the abnormality, which can be captured from the actual construction image corresponding to the comparison time period based on the start time of the abnormality. The generated monitoring feedback information includes the abnormal construction project, the start time of the abnormality and the abnormality tracing image frame. In order to facilitate the relevant supervisory personnel to view it intuitively, the abnormality tracing image frame can also be superimposed on the corresponding position of the actual overall construction image, so that the relevant supervisory personnel can respond to and resolve abnormal situations in the construction process in a timely manner.

[0099] Furthermore, in order to avoid the aggravation of the situation in the abnormal construction area, the method provided in the embodiment of the present application further includes:

[0100] Identify the abnormal time bin corresponding to the abnormal construction project from the execution time wheel, and wake up the hidden time bin corresponding to the abnormal time bin, and the observation date corresponding to the hidden time bin is the date between the abnormal time bin and the next time bin; determine the observation frequency corresponding to the hidden time bin according to the matching degree and preset mapping relationship between the actual overall construction image and the predicted overall construction image in the abnormal area, and the preset mapping relationship is the corresponding relationship between the matching degree and the observation frequency; start the hidden time bin based on the observation frequency, obtain the observation result corresponding to each observation date, and feedback each observation result.

[0101] Specifically, the hidden time bin is a hidden part in the execution time wheel. When there is no abnormal time bin, the hidden time bin is always in a hidden state. Each abnormal time bin corresponds to a hidden time bin. The hidden time bin is located between the abnormal time bin and the next time bin. The execution time wheel may contain multiple hidden time bins. The observation frequency of the hidden time bin is related to the degree of abnormality, that is, the observation frequency is related to the matching degree between the actual overall construction image and the predicted overall construction image. The lower the matching degree, the greater the difference between the actual overall construction image and the predicted overall construction image, and the higher the abnormality of the corresponding construction project. Therefore, it is necessary to supervise the abnormal situation through a higher observation frequency. The preset mapping relationship contains observation frequencies corresponding to different matching degrees. The higher the matching degree, the lower the corresponding observation frequency. For example, when the matching degree is 82%, the corresponding observation frequency is to generate and feedback an observation result once every 2 days; when the matching degree is 62%, the corresponding observation frequency is to generate and feedback an observation result once every 0.5 days. The specific content is not specifically limited in the embodiments of this application and can be set by relevant technical personnel. The method of determining the observation result corresponding to the observation date can refer to the method of generating monitoring feedback information in the above embodiment, which will not be described in detail here.

[0102] By starting the hidden time bin after an abnormality occurs, the progress of the abnormal construction project can be monitored instead of waiting until the monitoring date to view it. By increasing the supervision frequency, it is easier to analyze and view the changes in the abnormal construction area to determine whether the abnormal construction area has been corrected in time, thereby avoiding the situation in the abnormal construction area from worsening.

[0103] The above embodiment introduces a method for visualizing image monitoring of engineering progress from the perspective of method flow, and the following embodiment introduces a device for visualizing image monitoring of engineering progress from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0104] The present application embodiment provides a project progress visualization image monitoring device, such as Figure 3 As shown, the device may specifically include a construction image acquisition module 310, a construction progress identification module 320, a construction prediction image determination module 330, an image integration module 340, and a monitoring feedback information generation module 350, wherein:

[0105] The construction image acquisition module 310 is used to acquire a construction image within a first preset time period and a preset construction plan corresponding to each construction project included in the construction image at each monitoring date, wherein the construction image includes at least one construction project and each monitoring date is a date within a second preset time period;

[0106] The construction progress identification module 320 is used to identify the completed construction progress and the latest project image of each construction project within a first preset time period according to the construction image;

[0107] The construction prediction image determination module 330 is used to determine the newly added construction content corresponding to each construction project on each monitoring date according to the preset construction plan and the completed construction progress corresponding to each construction project on each monitoring date, and determine the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image;

[0108] An image integration module 340 is used to identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain a predicted overall construction image corresponding to the target monitoring date;

[0109] The monitoring feedback information generating module 350 is used to obtain the actual overall construction image corresponding to the target monitoring date, match the actual overall construction image with the predicted overall construction image, and generate monitoring feedback information according to the matching result.

[0110] In a possible implementation, when determining the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content and the corresponding latest project image of each construction project on each monitoring date, the construction prediction image determining module 330 is specifically used to:

[0111] Determine an average construction rate for each construction project based on the completion progress of each construction project within the first preset time period;

[0112] According to the average construction rate of each construction project, the newly added construction content on each monitoring date and the corresponding preset simulation construction model, the construction process of each construction project when the corresponding newly added construction content is completed on each monitoring date is simulated to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date;

[0113] The simulated newly added construction images corresponding to each construction project on each date are superimposed on the latest project images corresponding to each construction project to obtain the construction prediction images corresponding to each construction project on each monitoring date.

[0114] In a possible implementation, the device further includes:

[0115] An image classification module is used to classify multiple construction prediction images according to the monitoring date, and obtain an image chain table corresponding to each monitoring date according to the classification result and the preset data chain table;

[0116] Determine a monitoring time wheel module, which is used to write the image chain list corresponding to each monitoring date into a preset time wheel to obtain a monitoring time wheel, wherein the monitoring time wheel includes multiple time bins, each time bin corresponding to a monitoring date;

[0117] An execution interval determination module is used to determine the execution interval between corresponding time bins according to each monitoring date;

[0118] The execution time wheel determination module is used to obtain the execution time wheel according to the monitoring time wheel and the execution interval between each time bin in the monitoring time wheel.

[0119] In a possible implementation, the image integration module 340 is specifically used to:

[0120] Get the time bin currently pointed to by the time wheel pointer, and determine whether the current time bin is the target monitoring date;

[0121] If so, the image linked list currently pointing to the time bin is retrieved to obtain multiple target construction prediction images corresponding to the target monitoring date, and the construction features contained in each target construction prediction image are identified;

[0122] Multiple target construction prediction images are integrated according to each construction feature.

[0123] In a possible implementation, when the monitoring feedback information generating module 350 matches the actual overall construction image with the predicted overall construction image and generates the monitoring feedback information according to the matching result, it is specifically used to:

[0124] Matching the actual overall construction image with the predicted overall construction image, and determining an abnormal area, where the degree of matching between the actual overall construction image and the predicted overall construction image is lower than a preset matching value;

[0125] Identify abnormal construction projects contained in the abnormal area, and retrieve actual construction images and simulated images of each abnormal construction project within a third preset time period to determine the abnormal starting time and the abnormal tracing image frame corresponding to the abnormal starting time;

[0126] Monitoring feedback information is generated based on the abnormal construction project, the abnormal starting time and the abnormal tracing image frame corresponding to the abnormal starting time.

[0127] In a possible implementation, the device further includes:

[0128] A hidden time bin awakening module is used to identify the abnormal time bin corresponding to the abnormal construction project from the execution time round, and awaken the hidden time bin corresponding to the abnormal time bin, and the observation date corresponding to the hidden time bin is the date between the abnormal time bin and the next time bin;

[0129] An observation frequency determination module is used to determine the observation frequency corresponding to the hidden time bin according to the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area and a preset mapping relationship, wherein the preset mapping relationship is the corresponding relationship between the matching degree and the observation frequency;

[0130] The observation feedback module is used to start the hidden time bin based on the observation frequency, obtain the observation result corresponding to each observation date, and feedback each observation result.

[0131] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0132] An electronic device is provided in an embodiment of the present application, such as Figure 4 As shown, Figure 4The electronic device 400 shown includes: a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, such as through a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that in actual applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 does not constitute a limitation on the embodiments of the present application.

[0133] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0134] The bus 402 may include a path to transmit information between the above components. The bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The fact that only one line is used in the diagram does not mean that there is only one bus or only one type of bus.

[0135] The memory 403 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0136] The memory 403 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the contents shown in the above method embodiment.

[0137] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0138] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0139] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0140] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for visualizing an image of a project progress, characterized in that: include: Acquire a construction image within a first preset time period, and a preset construction plan corresponding to each construction project included in the construction image on each monitoring date, wherein the construction image includes at least one construction project, and each monitoring date is a date within a second preset time period, wherein the first preset time period is adjacent to the second preset time period, and the duration corresponding to the first preset time period is shorter than the duration corresponding to the second preset time period; According to the construction images, identifying the completed construction progress and the latest project images of each construction project within the first preset time period; According to the preset construction plan and completed construction progress corresponding to each construction project on each monitoring date, the newly added construction content corresponding to each construction project on each monitoring date is determined, and based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date is determined, wherein the newly added construction content is the construction content that needs to be completed between the last moment of the first preset time period and each monitoring date, and there is a corresponding relationship between the completed construction progress corresponding to the first preset time period and the latest project image of each construction project. According to the corresponding relationship and the newly added construction content corresponding to each monitoring date, the corresponding project image is obtained, and the construction prediction image corresponding to each construction project on each monitoring date is obtained based on the image overlay technology; Identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain the predicted overall construction image corresponding to the target monitoring date; Acquire an actual overall construction image corresponding to the target monitoring date, match the actual overall construction image with the predicted overall construction image, and generate monitoring feedback information according to the matching result; Wherein, based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image, the construction prediction image corresponding to each construction project on each monitoring date is determined, including: determining the average construction rate of each construction project according to the completion progress of each construction project within the first preset time period; simulating the construction process of each construction project when the corresponding newly added construction content is completed on each monitoring date according to the average construction rate of each construction project, the newly added construction content on each monitoring date and the corresponding preset simulation construction model, to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date; superimposing the simulated newly added construction image corresponding to each construction project on each date onto the latest project image corresponding to each construction project, to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date. The construction prediction image corresponding to each monitoring date; wherein, the average construction rate of the construction project can be calculated according to the completion progress of the construction and the duration corresponding to the first preset time period, and each construction project corresponds to a preset simulation construction model, which is constructed according to the construction project and the corresponding construction personnel information. In addition to the personal information of each construction personnel, the construction personnel information also includes the ability score of each construction personnel. The preset simulation construction model constructed based on the construction personnel information has a high degree of adaptability to the actual construction situation. In the process of simulated construction, the average construction rate of the construction project and the newly added construction content on each monitoring date are imported into the preset simulation construction model to obtain the simulated newly added image corresponding to the construction project on each monitoring date, and the simulated newly added image corresponds to the newly added construction content; After determining the construction prediction image corresponding to each construction project on each monitoring date, the method further includes: Classify multiple construction prediction images according to the monitoring date, and obtain an image link list corresponding to each monitoring date according to the classification result and the preset data link list; Writing the image chain list corresponding to each monitoring date into a preset time wheel to obtain a monitoring time wheel, wherein the monitoring time wheel includes multiple time bins, each time bin corresponding to a monitoring date; Determine the execution interval between corresponding time bins based on each monitoring date; Obtaining an execution time wheel according to the monitoring time wheel and the execution interval between each time bin in the monitoring time wheel; The step of identifying the target construction prediction image of each construction project corresponding to the target monitoring date and integrating all the target construction prediction images includes: Obtain the current time bin pointed by the time wheel pointer, and determine whether the current time bin is the target monitoring date; if so, retrieve the image linked list of the current time bin, obtain multiple target construction prediction images corresponding to the target monitoring date, and identify the construction features contained in each target construction prediction image; integrate the multiple target construction prediction images according to each construction feature; The matching of the actual overall construction image with the predicted overall construction image and generating monitoring feedback information according to the matching result includes: The actual overall construction image is matched with the predicted overall construction image, and an abnormal area is determined, wherein the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area is lower than a preset matching value; abnormal construction projects contained in the abnormal area are identified, and the actual construction image and the simulated image of each abnormal construction project within a third preset time period are retrieved to determine the abnormal starting moment and the abnormal tracing image frame corresponding to the abnormal starting moment; monitoring feedback information is generated based on the abnormal construction project, the abnormal starting moment and the abnormal tracing image frame corresponding to the abnormal starting moment.

2. A method for visualizing project progress according to claim 1, characterized in that: Also includes: Identify the abnormal time bin corresponding to the abnormal construction project from the execution time wheel, and wake up the hidden time bin corresponding to the abnormal time bin, where the observation date corresponding to the hidden time bin is the date between the abnormal time bin and the next time bin; Determine the observation frequency corresponding to the hidden time bin according to the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area and a preset mapping relationship, wherein the preset mapping relationship is a corresponding relationship between the matching degree and the observation frequency; The hidden time bin is started based on the observation frequency, an observation result corresponding to each observation date is obtained, and each observation result is fed back.

3. A visual image monitoring device for project progress, characterized in that: include: A construction image acquisition module is used to acquire a construction image within a first preset time period, and a preset construction plan corresponding to each construction project contained in the construction image on each monitoring date, wherein the construction image contains at least one construction project, and each monitoring date is a date within a second preset time period, wherein the first preset time period is adjacent to the second preset time period, and the duration corresponding to the first preset time period is shorter than the duration corresponding to the second preset time period; A construction progress identification module, used to identify the completed construction progress and the latest project image of each construction project within the first preset time period according to the construction image; A construction prediction image determination module is used to determine the newly added construction content corresponding to each construction project on each monitoring date according to the preset construction plan and completed construction progress corresponding to each construction project on each monitoring date, and determine the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content corresponding to each construction project on each monitoring date and the corresponding latest project image, wherein the newly added construction content is the construction content that needs to be completed between the last moment of the first preset time period and each monitoring date, and there is a corresponding relationship between the completed construction progress corresponding to the first preset time period and the latest project image of each construction project, and the corresponding project image is obtained according to the corresponding relationship and the newly added construction content corresponding to each monitoring date, and the construction prediction image corresponding to each construction project on each monitoring date is obtained based on the image superposition technology; An image integration module is used to identify the target construction prediction image of each construction project corresponding to the target monitoring date, and integrate all the target construction prediction images to obtain the predicted overall construction image corresponding to the target monitoring date; A monitoring feedback information generation module is used to obtain an actual overall construction image corresponding to the target monitoring date, match the actual overall construction image with the predicted overall construction image, and generate monitoring feedback information according to the matching result; The construction prediction image determination module is specifically used to determine the construction prediction image corresponding to each construction project on each monitoring date based on the newly added construction content and the corresponding latest project image of each construction project on each monitoring date: Determine the average construction rate of each construction project according to the completion progress of each construction project within the first preset time period; According to the average construction rate of each construction project, the newly added construction content on each monitoring date and the corresponding preset simulation construction model, the construction process of each construction project when the corresponding newly added construction content is completed on each monitoring date is simulated to obtain the simulated newly added construction image corresponding to each construction project on each monitoring date; The simulated newly added construction images corresponding to each construction project on each date are superimposed on the latest project images corresponding to each construction project, so as to obtain the construction prediction images corresponding to each construction project on each monitoring date; wherein, the average construction rate of the construction project can be calculated according to the completion progress of the construction and the duration corresponding to the first preset time period, and each construction project corresponds to a preset simulated construction model, which is constructed according to the construction project and the corresponding construction personnel information. In addition to the personal information of each construction personnel, the construction personnel information also includes the ability score of each construction personnel. The preset simulated construction model constructed based on the construction personnel information has a high degree of adaptability to the actual construction situation. In the process of simulated construction, the average construction rate of the construction project and the newly added construction content on each monitoring date are imported into the preset simulated construction model, so as to obtain the simulated newly added images corresponding to the construction project on each monitoring date, and the simulated newly added images correspond to the newly added construction content; The device further comprises: An image classification module is used to classify multiple construction prediction images according to the monitoring date, and obtain an image chain table corresponding to each monitoring date according to the classification result and the preset data chain table; Determine a monitoring time wheel module, which is used to write the image chain list corresponding to each monitoring date into a preset time wheel to obtain a monitoring time wheel, wherein the monitoring time wheel includes multiple time bins, each time bin corresponds to a monitoring date; An execution interval determination module is used to determine the execution interval between corresponding time bins according to each monitoring date; An execution time wheel determination module is used to obtain an execution time wheel according to the monitoring time wheel and the execution interval between each time bin in the monitoring time wheel; The image integration module is specifically used to identify the target construction prediction image of each construction project corresponding to the target monitoring date and integrate all the target construction prediction images: Obtain the current time bin pointed by the time wheel pointer, and determine whether the current time bin is the target monitoring date; if so, retrieve the image linked list of the current time bin, obtain multiple target construction prediction images corresponding to the target monitoring date, and identify the construction features contained in each target construction prediction image; integrate the multiple target construction prediction images according to each construction feature; Wherein, when the module for generating monitoring feedback information matches the actual overall construction image with the predicted overall construction image and generates monitoring feedback information according to the matching result, it is specifically used for: The actual overall construction image is matched with the predicted overall construction image, and an abnormal area is determined, wherein the matching degree between the actual overall construction image and the predicted overall construction image in the abnormal area is lower than a preset matching value; abnormal construction projects contained in the abnormal area are identified, and the actual construction image and the simulated image of each abnormal construction project within a third preset time period are retrieved to determine the abnormal starting moment and the abnormal tracing image frame corresponding to the abnormal starting moment; monitoring feedback information is generated based on the abnormal construction project, the abnormal starting moment and the abnormal tracing image frame corresponding to the abnormal starting moment.

4. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a method for visualizing an engineering progress according to any one of claims 1-2.

5. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and execute a method for visualizing and supervising a project progress as claimed in any one of claims 1 to 2.

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