CN117408561A - Residential engineering construction supervision method and device and electronic equipment - Google Patents

Residential engineering construction supervision method and device and electronic equipment Download PDF

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CN117408561A
CN117408561A CN202311415890.8A CN202311415890A CN117408561A CN 117408561 A CN117408561 A CN 117408561A CN 202311415890 A CN202311415890 A CN 202311415890A CN 117408561 A CN117408561 A CN 117408561A
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杨超
魏贺
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Shenzhen Keyu Engineering Consulting Co ltd
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Abstract

The application provides a residential engineering construction supervision method, a device and electronic equipment, and relates to the field of data processing. In the method, a supervision data packet is acquired, wherein the supervision data packet is a supervision data packet for residential engineering construction; analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, wherein the preset supervision model is pre-stored with a preset project progress corresponding to a preset time node and a preset project cost corresponding to the preset time node; if the analysis result indicates that the supervision data packet is abnormal, acquiring the abnormal type of the supervision data packet; searching in a preset supervision database according to the abnormal type to obtain a supervision strategy, wherein the abnormal type comprises abnormal engineering progress and abnormal engineering cost, and the preset supervision database is pre-stored with the corresponding relation between the abnormal type and the supervision strategy so as to supervise the residential engineering construction according to the supervision strategy. By implementing the technical scheme provided by the application, the efficiency of supervising the residential engineering construction is improved conveniently.

Description

Residential engineering construction supervision method and device and electronic equipment
Technical Field
The application relates to the technical field of data processing, in particular to a residential engineering construction supervision method, a device and electronic equipment.
Background
In the process of residential engineering construction, supervision is a key link for ensuring engineering quality. And a supervisor can timely find and solve the problems existing in the construction process by comprehensively and carefully monitoring and analyzing the data in the engineering construction process so as to ensure that the engineering is successfully completed according to the preset quality standard.
However, with the expansion of the construction scale and the increase of the complexity of the residential engineering, the residential engineering is supervised by means of a single manual supervision mode, so that the workload of supervision personnel is easily caused to be large, and the experience of the supervision personnel is uneven, thereby resulting in lower efficiency of supervision on the residential engineering construction.
Therefore, there is an urgent need for a method, apparatus and electronic device for supervision of residential engineering construction.
Disclosure of Invention
The application provides a residential engineering construction supervision method, a device and electronic equipment, which are convenient for improving the efficiency of residential engineering construction supervision.
In a first aspect of the present application, there is provided a residential engineering construction supervision method, the method comprising: acquiring a supervision data packet, wherein the supervision data packet is a supervision data packet for residential engineering construction; analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, wherein the preset supervision model is pre-stored with a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node; if the analysis result indicates that the supervision data packet is abnormal, acquiring an abnormal type corresponding to the supervision data packet; and searching in a preset supervision database according to the abnormality type to obtain a supervision strategy, wherein the abnormality type comprises abnormal engineering progress and abnormal engineering cost, and the preset supervision database is pre-stored with a corresponding relation between the abnormality type and the supervision strategy so as to supervise the residential engineering construction according to the supervision strategy.
Through adopting above-mentioned technical scheme, through obtaining the supervision data package to adopt and predetermine the supervision model and carry out automatic analysis to the supervision data package, when supervision data package is unusual, obtain the unusual type of supervision data package, and according to unusual type generation supervision tactics, thereby be convenient for manage personnel and manage residential engineering construction according to supervision tactics. Compared with the prior art, the method has the advantages that manual supervision according to experience is not needed, the probability of low supervision efficiency caused by insufficient manual experience is reduced, and further the efficiency of supervision on residential engineering construction is improved.
Optionally, the acquiring the supervision packet specifically includes: receiving a supervision request sent by user equipment; acquiring various supervision data sent by the terminal equipment according to the supervision request; and preprocessing a plurality of supervision data to obtain the supervision data packet, wherein the preprocessing comprises data cleaning, data classification and normalization processing.
By adopting the technical scheme, invalid and erroneous data can be removed by data cleaning, and the accuracy and reliability of the data are ensured. The data classification can classify different types of supervision data, so that subsequent processing and analysis are facilitated. The normalization process may convert the proctorial data of different scales to a common scale such that the data is comparable and helps to eliminate effects caused by the difference in data source and scale. More accurate and reliable supervision data packets can be obtained through preprocessing, and powerful data support is provided for subsequent supervision work. Therefore, the pretreatment can improve the quality and the usability of the supervision data, and is beneficial to better performing supervision work of residential engineering construction.
Optionally, the supervision data packet includes an engineering progress, and the analysis is performed on the supervision data packet by using a preset supervision model to obtain an analysis result, which specifically includes: determining a preset project progress through the preset supervision model according to the project progress, wherein the preset project progress is a preset project progress corresponding to a current time node; comparing the engineering progress with the preset engineering progress; and if the engineering progress is smaller than the preset engineering progress, generating a first analysis result, wherein the first analysis result is used for indicating that the engineering progress is abnormal.
By adopting the technical scheme, the actual engineering progress is compared with the preset engineering progress, so that whether the problems of progress lag and the like exist can be rapidly detected, and corresponding measures are timely taken for intervention and adjustment. The first analysis result can be used as a basis for a supervision person to judge whether the engineering progress accords with the expectations or not, and can also be used as reference information formulated by a follow-up supervision strategy, so that the pertinence and the effectiveness of the supervision work are improved. By acquiring the engineering progress data, the analysis can be continuously performed, so that dynamic engineering progress monitoring is realized, problems are found and adjusted in time, and the smooth performance of engineering is ensured. Therefore, the efficiency and the accuracy of supervision work are improved conveniently, and the residential engineering construction is ensured to be carried out smoothly according to a plan.
Optionally, the supervision packet further includes engineering cost, and the analyzing the supervision packet by using a preset supervision model to obtain an analysis result specifically further includes: determining preset engineering cost according to the engineering cost through the preset supervision model, wherein the preset engineering cost is corresponding to the current time node; comparing the engineering cost with the preset engineering cost; and if the engineering cost is greater than the preset engineering cost, generating a second analysis result, wherein the second analysis result is used for indicating that the engineering cost is abnormal.
By adopting the technical scheme, whether the problems of cost hyperbranched and the like exist can be detected rapidly by comparing the actual engineering cost with the preset engineering cost, so that corresponding measures are taken in time for intervention and adjustment, and unnecessary losses are avoided. The second analysis result can be used as a basis for a supervisor to judge whether the engineering cost accords with the budget or not, and can also be used as reference information formulated by a follow-up supervision strategy, so that the pertinence and the effectiveness of the supervision work are improved. The analysis can be continuously carried out by periodically or real-time obtaining engineering cost data, so that dynamic engineering cost monitoring is realized, problems are found and adjusted in time, and the smooth operation of engineering is ensured. Therefore, the efficiency and the accuracy of supervision work are improved conveniently, and the residential engineering construction is guaranteed to be carried out smoothly within the budget range.
Optionally, the first analysis result includes an influence factor, and the method further includes: acquiring the influence factor; determining the number of influence days according to the influence factors; the days of influence are displayed.
By adopting the technical scheme, through showing the influence days, related personnel can know the influence degree of engineering progress abnormality on the construction period more clearly, so that more accurate decision and adjustment can be made. By displaying the influence days, the influence of progress delay can be found in time, and related personnel are prompted to take effective countermeasures so as to reduce the influence on the construction period. Communication and cooperation among all parties can be promoted by disclosing or sharing information affecting days, transparency of supervision work is improved, and smooth progress of engineering construction is ensured.
Optionally, analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, and training the preset supervision model; training the preset supervision model specifically comprises the following steps: acquiring training information, wherein the training information comprises the supervision data packet and the analysis result; inputting the training information into a self-adaptive feature fusion network for training to obtain a first training result; superposing and standardizing the first training result and the training information to obtain a second training result; inputting the second training result into the self-adaptive feature fusion network for processing to obtain a third training result; and superposing and standardizing the third training result and the second training result until the training information similarity matrix is output, wherein the training information similarity matrix meets a preset logistic regression condition.
By adopting the technical scheme, the training is performed through the self-adaptive feature fusion network, and the learning can be performed by utilizing a plurality of features of the supervision data packet and the analysis result, so that the accuracy and the adaptability of the model are improved. In the training process, multiple overlapping and standardization processing can be performed, and adjustment and optimization are performed according to actual conditions, so that the model is better suitable for different supervision scenes and data characteristics. By meeting the preset logistic regression condition, the output result of the model can be ensured to meet certain rules and constraints, and the reliability and the credibility of the supervision model are improved. The more accurate and reliable preset supervision model is obtained through training, so that the development of supervision work can be guided better, and the efficiency and accuracy of the supervision work are improved.
Optionally, the method further comprises: and sending the supervision policy to the user equipment so that a user corresponding to the user equipment can learn the supervision policy, and conducting supervision on the residential engineering construction according to the supervision policy.
By adopting the technical scheme, after the supervision personnel obtain the supervision strategy, targeted supervision work can be carried out according to the requirements of the strategy, and the efficiency and the accuracy of the supervision work are improved. By sending the supervision strategy to the user equipment, the user can know the content and the requirement of the supervision work more, better information transmission and sharing can be realized, and the transparency and the utilization efficiency of the information are improved.
In a second aspect of the present application, a residential engineering construction supervision device is provided, where the residential engineering construction supervision device includes an acquisition module and a processing module, where the acquisition module is configured to acquire a supervision packet, where the supervision packet is a supervision packet for residential engineering construction; the processing module is used for analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, wherein the preset supervision model is pre-stored with a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node; the processing module is further configured to obtain an exception type corresponding to the supervision packet if the analysis result indicates that the supervision packet is abnormal; the processing module is further configured to search in a preset supervision database according to the anomaly type, to obtain a supervision policy, where the anomaly type includes an anomaly of an engineering progress and an anomaly of an engineering cost, and the preset supervision database stores in advance a correspondence between the anomaly type and the supervision policy, so as to perform supervision on the residential engineering construction according to the supervision policy.
In a third aspect of the present application, there is provided an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface, both for communicating to other devices, the processor being adapted to execute the instructions stored in the memory to cause the electronic device to perform the method as described above.
In a fourth aspect of the present application, there is provided a computer readable storage medium storing instructions that, when executed, perform a method as described above.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. the supervision data packet is obtained, and the preset supervision model is adopted to automatically analyze the supervision data packet, when the supervision data packet is abnormal, the abnormal type of the supervision data packet is obtained, and the supervision strategy is generated according to the abnormal type, so that supervision personnel can conveniently manage the residential engineering construction according to the supervision strategy. Compared with the related art, the method does not need to manually manage according to experience, reduces the probability of low management efficiency caused by insufficient manual experience, and is convenient for improving the efficiency of managing the residential engineering construction;
2. By comparing the actual engineering progress with the preset engineering progress, whether the problems of progress lag and the like exist or not can be detected rapidly, so that corresponding measures are taken in time for intervention and adjustment. The first analysis result can be used as a basis for a supervision person to judge whether the engineering progress accords with the expectations or not, and can also be used as reference information formulated by a follow-up supervision strategy, so that the pertinence and the effectiveness of the supervision work are improved. By acquiring the engineering progress data, the analysis can be continuously performed, so that dynamic engineering progress monitoring is realized, problems are found and adjusted in time, and the smooth performance of engineering is ensured. Therefore, the efficiency and the accuracy of supervision work are improved conveniently, and the residential engineering construction is ensured to be carried out smoothly according to a plan;
3. by sending the supervision strategy to the user equipment, the supervision personnel can know the content and the requirement of the supervision work more, so that better information transmission and sharing are realized, and the transparency and the utilization efficiency of the information are improved.
Drawings
Fig. 1 is a schematic flow chart of a residential engineering construction supervision method according to an embodiment of the present disclosure.
Fig. 2 is a schematic block diagram of a residential engineering construction supervision device according to an embodiment of the present disclosure.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 21. an acquisition module; 22. a processing module; 31. a processor; 32. a communication bus; 33. a user interface; 34. a network interface; 35. a memory.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.
In the description of embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "such as" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In the construction of residential projects, the role of supervision is of importance. They are the main defense lines for ensuring engineering quality, and perform comprehensive and detailed data monitoring and analysis on engineering construction, so as to discover and solve problems in time. By the mode, the supervision personnel can ensure that the engineering is successfully completed according to the preset quality standard, and subsequent maintenance and repair cost increase caused by quality problems is avoided.
However, with the continuous expansion of the construction scale of residential projects and the continuous increase of the complexity of projects, the conventional single-person supervision method has become more and more difficult to deal with. This kind of traditional supervision often leads to supervision personnel work burden too much, and because every person's experience is different, supervision effect is uneven too. This results in the supervision efficiency for residential engineering construction becoming very low, sometimes even possibly affecting the progress and quality of the engineering.
In order to solve the above technical problems, the present application provides a residential engineering construction supervision method, and referring to fig. 1, fig. 1 is a flow chart of a residential engineering construction supervision method provided in an embodiment of the present application. The residential engineering construction supervision method is applied to a server and comprises the following steps of S110 to S130:
S110, acquiring a supervision data packet, wherein the supervision data packet is a supervision data packet for residential engineering construction.
Specifically, when a manager needs to manage a certain residential engineering, the server will acquire a management data packet, where the management data packet includes various management data, such as a construction plan, an engineering progress, an engineering cost, a constructor, an engineering contract, and the like. The method for acquiring the supervision data packet by the server comprises, but is not limited to, acquiring by a construction site terminal, wherein supervision personnel can directly acquire various data including information on engineering progress, quality, safety and the like through the terminal on the construction site; relevant departments and units provide: the owners, design units, construction units and the like can provide relevant supervision data, such as design change orders, engineering measurement orders and the like; or related supervision data, such as industry standards, policies and regulations, etc., can be obtained through the internet, industry association and other approaches; the relevant proctoring data may also be provided by, for example, a proctoring company, a consultation company, etc. The embodiments of the present application are not limited, and are not described herein.
In one possible implementation manner, obtaining the supervision packet specifically includes: receiving a supervision request sent by user equipment; acquiring various supervision data sent by terminal equipment according to the supervision request; preprocessing various supervision data to obtain a supervision data packet, wherein the preprocessing comprises data cleaning, data classification and normalization processing.
Specifically, the proctoring personnel or the designated user equipment sends a proctoring request to the server, wherein the request contains relevant information of proctoring data to be acquired. And the server sends a data request to the related terminal equipment according to the received supervision request, and the terminal equipment provides the related supervision data according to the request. Such data may come from job sites, related departments and units, and other sources. And then, the server preprocesses various supervision data to obtain a supervision data packet. The preprocessing comprises the steps of data cleaning, data classification, normalization processing and the like, and aims to improve the accuracy and reliability of supervision data and provide better support for subsequent analysis and decision.
The following is an example illustrating the specific operation of the above steps: it is assumed that in a residential engineering project, a supervisor needs to acquire progress and cost data of the project. The user equipment (such as a mobile phone or a computer of a supervision person) sends a supervision request to the server, wherein the request contains relevant information of engineering progress and cost data to be acquired. And the server sends a data request to the terminal equipment of the construction site according to the request, and the terminal equipment is required to provide related engineering progress and cost data. The terminal equipment collects relevant data, such as engineering progress information, engineering cost information and the like of a construction site according to the request. The server performs preprocessing on the collected data, such as data cleaning, data classification, normalization processing and the like. For example, units of the amount of work done and the amount of work planned are unified, such as converting the units into percentages, classifying different types of data, such as classifying the cost of work as cost of labor and cost of materials, respectively, and normalizing data of different scales, such as converting all data into values between 0 and 1. The supervision data packet obtained through the steps can provide comprehensive residential engineering construction data for supervision personnel, and help the supervision personnel to make accurate decisions and effective supervision work.
The server is a server for managing the supervision data packets and is used for providing background service, and the server can be a server, a server cluster formed by a plurality of servers or a cloud computing service center. The user equipment is connected with the server in a wired or wireless manner, and the types of the user equipment include but are not limited to: android (Android) system equipment, mobile operating system (iOS) equipment developed by apple corporation, personal Computers (PCs), global area network (Web) equipment, virtual Reality (VR) equipment, augmented Reality (Augmented Reality, AR) equipment and the like. In the embodiment of the present application, the user equipment is a mobile phone.
S120, analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, wherein the preset supervision model is pre-stored with a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node.
Specifically, after obtaining the supervision data packet, the server analyzes the supervision data packet by adopting a preset supervision model, so as to obtain an analysis result. The preset supervision model is a decision tree model which is built and trained in advance, and different analysis results can be obtained through comparing supervision data with preset supervision data. The preset time node is a current time node. For example, when the supervision data shows that the actual engineering progress is 20% on 10 months 1 day, and the planned engineering progress of 10 months 1 day determined by the preset supervision data is 40%, an analysis result for indicating the abnormality of the engineering progress in the supervision data is generated.
S130, if the analysis result indicates that the supervision data packet is abnormal, acquiring the abnormal type of the supervision data packet.
And S140, searching in a preset supervision database according to the abnormal type to obtain a supervision strategy, wherein the abnormal type comprises abnormal engineering progress and abnormal engineering cost, and the preset supervision database is pre-stored with the corresponding relation between the abnormal type and the supervision strategy so as to supervise the residential engineering construction according to the supervision strategy.
Specifically, when the analysis result indicates that the supervision data packet is abnormal, the server acquires the abnormal type of the supervision data packet, and searches for the supervision policy in a preset supervision database according to the corresponding relationship between the abnormal type and the supervision policy. The preset supervision database is pre-stored with a corresponding relation between an abnormal type and a supervision policy, and one abnormal type corresponds to one supervision policy. For example, when the analysis result shows that the actual project progress is 20% on day 6 and 1, and the planned project progress is 40% on day 6 and 1 determined by the server, and the analysis result shows that the relevant responsible person Li Mou, the generated supervision policy is the responsible person Li Mou for suggesting investigation, and the supervision policy for performing accountability on Li Mou is adopted. When the analysis result shows that the supervision data packet is normal, the server keeps the continuous monitoring state of the supervision data packet.
In one possible implementation manner, the supervision data packet includes an engineering progress, and the supervision data packet is analyzed by adopting a preset supervision model to obtain an analysis result, which specifically includes: determining a preset engineering progress through a preset supervision model according to the engineering progress, wherein the preset engineering progress is the preset engineering progress corresponding to the current time node; comparing the engineering progress with a preset engineering progress; if the engineering progress is smaller than the preset engineering progress, a first analysis result is generated, and the first analysis result is used for indicating that the engineering progress is abnormal.
Specifically, the server determines a preset engineering progress through a preset supervision model according to the engineering progress: the preset supervision model is a model based on engineering progress, and can preset an engineering progress which accords with the actual condition of the engineering according to different characteristics and historical data of the engineering. The server matches a preset project progress through a preset supervision model according to the actual progress of the current project, compares the project progress with the preset project progress, compares the actual project progress with the preset project progress, and can find out whether a difference exists between the actual project progress and the preset project progress. If the actual project schedule is slower than the preset project schedule, i.e., the project schedule is less than the preset project schedule, a first analysis result is generated. The analysis result can be used for indicating the abnormal progress of the engineering and reminding a supervisor of paying attention to the hysteresis problem of the progress of the engineering.
The following is a specific example: assume that the current project progress of a residential project construction project is 60%, i.e., 60% of the completed project. The preset project schedule calculated by the server through the preset supervision model is 70%. And comparing the actual engineering progress with the preset engineering progress, and finding that the actual engineering progress is 10% slower than the preset engineering progress. At this time, the server generates a first analysis result, indicates that the engineering progress is abnormal, and reminds a supervisor to pay attention to the hysteresis problem of the engineering progress. Therefore, the supervision personnel can take measures in time to ensure that the engineering is smoothly carried out according to the plan.
In one possible implementation manner, the supervision data packet further includes engineering cost, and the analysis is performed on the supervision data packet by adopting a preset supervision model to obtain an analysis result, and specifically further includes: determining preset engineering cost according to the engineering cost through a preset supervision model, wherein the preset engineering cost is corresponding to the current time node; comparing the engineering cost with a preset engineering cost; if the engineering cost is greater than the preset engineering cost, a second analysis result is generated, and the second analysis result is used for indicating that the engineering cost is abnormal.
Specifically, the preset supervision model can calculate a preset engineering cost which accords with the actual engineering situation according to the historical cost data of the engineering and the related economic indexes. Next, the server compares the actual engineering cost with the preset engineering cost, and can find out whether there is a difference between the two. If the actual engineering cost is higher than the preset engineering cost, i.e. the engineering cost is greater than the preset engineering cost, a second analysis result is generated. This result can be used to indicate engineering cost anomalies, alerting the supervisor to the problem of engineering cost hyper-branches.
The following is a specific example: assuming that the engineering cost of a certain residential engineering project is 100 ten thousand yuan, the preset engineering cost calculated by a preset supervision model is 80 ten thousand yuan. The actual engineering cost is compared with the preset engineering cost, and the actual engineering cost is found to be 20 ten thousand yuan higher than the preset engineering cost. At this time, the system can generate a second analysis result, indicate that the engineering cost is abnormal, and remind a supervisor to pay attention to the problem of engineering cost hyperbranched. Thus, the supervision personnel can take measures in time to control engineering cost and avoid exceeding budget.
In one possible embodiment, the first analysis result includes an impact factor, the method further comprising: acquiring an influence factor; determining the number of influence days according to the influence factors; the days of influence are presented.
Specifically, after the server generates the supervision policy, the server acquires the influence factors, determines the influence days according to the influence factors, and finally displays the influence days. For example, the construction period of a residential project is 6 months to 8 months, the actual working progress of the residential project is 40% at 7 months and 1 day, and the planned project progress is not reached to 50%, the server will obtain the influence factor at 6 months and 1 day to 7 months and 1 day, and determine that the influence factor is unreasonable in the project scheduling. The server will display the unreasonable impact factors of the engineering shift to the supervisor, thereby reminding the supervisor to shift again.
In one possible implementation manner, the preset supervision model is trained by analyzing the supervision data packet to obtain an analysis result; training a preset supervision model, which specifically comprises the following steps: acquiring training information, wherein the training information comprises a supervision data packet and an analysis result; inputting training information into a self-adaptive feature fusion network for training to obtain a first training result; the first training result and the training information are overlapped and standardized to obtain a second training result; inputting the second training result into the self-adaptive feature fusion network for processing to obtain a third training result; and superposing and standardizing the third training result and the second training result until a training information similarity matrix is output, wherein the training information similarity matrix meets the preset logistic regression condition.
Specifically, the above-mentioned process is a training process of a preset supervision model. The server acquires training information and inputs the training information into the self-adaptive feature fusion network for training, so that a first training result is obtained. And then, the server performs superposition and standardization processing on the first training result and the training information to obtain a second training result. And secondly, the server inputs the second training result into the self-adaptive feature fusion network for processing, so that a third training result is obtained. And finally, the server performs superposition and standardization processing on the third training result and the second training result until a training information similarity matrix is output.
The preset logistic regression condition is preset by a manager of the server. Conventional feature cascading or feature fusion methods of each layer typically weight, select and fuse features based on weights and rules designed empirically or manually. In the embodiment of the application, the training information comprises a supervision data packet and an analysis result, and the adaptive feature fusion network is adopted to adaptively learn and optimize the model architecture and parameters through data, so that the adaptability of the model to complex and variant scenes is improved. Therefore, through the continuous training and processing process, the accuracy and stability of the model can be improved, so that the model can be better adapted to different data conditions and can be effectively analyzed.
In one possible embodiment, the method further comprises: and sending the supervision policy to the user equipment so that the user corresponding to the user equipment can acquire the supervision policy, and conducting supervision on the residential engineering construction according to the supervision policy.
Specifically, the server makes a supervision policy, such as supervision requirements and measures on engineering progress, quality, cost and the like, according to actual conditions of residential engineering construction and needs of supervision work. And sending the supervision policy to the user equipment, for example, by means of email, short message or application program. The user receives and checks the supervision policy through the user equipment and knows the requirements and measures of the supervision work. And the user manages the residential engineering construction according to the supervision strategy, for example, the user checks and supervises the construction site according to the strategy requirement.
The application also provides a residential engineering construction supervision device, and referring to fig. 2, fig. 2 is a schematic block diagram of the residential engineering construction supervision device provided in the embodiment of the application. The residential engineering construction supervision device is a server and comprises an acquisition module 21 and a processing module 22, wherein the acquisition module 21 is used for acquiring supervision data packets, and the supervision data packets are supervision data packets for residential engineering construction; the processing module 22 is configured to analyze the supervision packet by using a preset supervision model to obtain an analysis result, where a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node are pre-stored in the preset supervision model; the processing module 22 is further configured to obtain an exception type corresponding to the supervision packet if the analysis result indicates that the supervision packet is abnormal; the processing module 22 is further configured to search in a preset supervision database according to an anomaly type, to obtain a supervision policy, where the anomaly type includes an anomaly of an engineering progress and an anomaly of an engineering cost, and the preset supervision database stores a correspondence between the anomaly type and the supervision policy in advance, so as to perform supervision on residential engineering construction according to the supervision policy.
In one possible implementation, the obtaining module 21 obtains the supervision packet specifically includes: the acquisition module 21 receives a supervision request sent by user equipment; the acquisition module 21 acquires various supervision data sent by the terminal equipment according to the supervision request; the processing module 22 performs preprocessing on various supervision data to obtain supervision data packets, where the preprocessing includes data cleaning, data classification and normalization.
In one possible implementation, the supervision data packet includes an engineering progress, and the processing module 22 analyzes the supervision data packet by using a preset supervision model to obtain an analysis result, which specifically includes: the processing module 22 determines a preset project progress through a preset supervision model according to the project progress, wherein the preset project progress is a preset project progress corresponding to the current time node; the processing module 22 compares the project schedule with a preset project schedule; if the project progress is less than the preset project progress, the processing module 22 generates a first analysis result, where the first analysis result is used to indicate that the project progress is abnormal.
In one possible implementation manner, the supervision packet further includes engineering cost, and the processing module 22 analyzes the supervision packet by using a preset supervision model to obtain an analysis result, and specifically further includes: the processing module 22 determines a preset engineering cost according to the engineering cost through a preset supervision model, wherein the preset engineering cost is the preset engineering cost corresponding to the current time node; the processing module 22 compares the engineering cost with a preset engineering cost; if the engineering cost is greater than the preset engineering cost, the processing module 22 generates a second analysis result, where the second analysis result is used to indicate that the engineering cost is abnormal.
In one possible implementation, the first analysis result includes an impact factor, and the obtaining module 21 obtains the impact factor; the processing module 22 determines the number of days of influence based on the influence factor; the processing module 22 displays the days of influence.
In one possible implementation, the processing module 22 uses a preset supervision model to analyze the supervision data packet to obtain an analysis result, and trains the preset supervision model; the processing module 22 trains a preset supervision model, specifically including: the acquisition module 21 acquires training information, wherein the training information comprises a supervision data packet and an analysis result; the processing module 22 inputs the training information into the self-adaptive feature fusion network for training to obtain a first training result; the processing module 22 performs superposition and standardization processing on the first training result and the training information to obtain a second training result; the processing module 22 inputs the second training result into the adaptive feature fusion network to be processed, so as to obtain a third training result; the processing module 22 performs superposition and standardization processing on the third training result and the second training result until a training information similarity matrix is output, where the training information similarity matrix meets a preset logistic regression condition.
In one possible implementation, the processing module 22 sends the supervision policy to the user device, so that the user corresponding to the user device knows the supervision policy, so as to perform supervision on the residential engineering construction according to the supervision policy.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application further provides an electronic device, and referring to fig. 3, fig. 3 is a schematic structural diagram of the electronic device provided in the embodiment of the application. The electronic device may include: at least one processor 31, at least one network interface 34, a user interface 33, a memory 35, at least one communication bus 32.
Wherein the communication bus 32 is used to enable connected communication between these components.
The user interface 33 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 33 may further include a standard wired interface and a standard wireless interface.
The network interface 34 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 31 may comprise one or more processing cores. The processor 31 connects various parts within the overall server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 35, and invoking data stored in the memory 35. Alternatively, the processor 31 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 31 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 31 and may be implemented by a single chip.
The Memory 35 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 35 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 35 may be used to store instructions, programs, code sets, or instruction sets. The memory 35 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 35 may alternatively be at least one memory device located remotely from the aforementioned processor 31. As shown in fig. 3, an operating system, a network communication module, a user interface module, and an application program of a residential engineering construction supervision method may be included in the memory 35 as a computer storage medium.
In the electronic device shown in fig. 3, the user interface 33 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 31 may be configured to invoke an application program in the memory 35 that stores a residential engineering construction supervision method, which when executed by one or more processors, causes the electronic device to perform the method as in one or more of the embodiments described above.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
The present application also provides a computer-readable storage medium having instructions stored thereon. When executed by one or more processors, cause an electronic device to perform the method as described in one or more of the embodiments above.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims (10)

1. A method of supervision of residential engineering construction, the method comprising:
acquiring a supervision data packet, wherein the supervision data packet is a supervision data packet for residential engineering construction;
analyzing the supervision data packet by adopting a preset supervision model to obtain an analysis result, wherein the preset supervision model is pre-stored with a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node;
If the analysis result indicates that the supervision data packet is abnormal, acquiring an abnormal type corresponding to the supervision data packet;
and searching in a preset supervision database according to the abnormality type to obtain a supervision strategy, wherein the abnormality type comprises abnormal engineering progress and abnormal engineering cost, and the preset supervision database is pre-stored with a corresponding relation between the abnormality type and the supervision strategy so as to supervise the residential engineering construction according to the supervision strategy.
2. The residential engineering construction supervision method according to claim 1, wherein the obtaining the supervision packet specifically comprises:
receiving a supervision request sent by user equipment;
acquiring various supervision data sent by the terminal equipment according to the supervision request;
and preprocessing a plurality of supervision data to obtain the supervision data packet, wherein the preprocessing comprises data cleaning, data classification and normalization processing.
3. The residential engineering construction supervision method according to claim 1, wherein the supervision data packet includes an engineering progress, and the analysis is performed on the supervision data packet by using a preset supervision model to obtain an analysis result, specifically including:
Determining a preset project progress through the preset supervision model according to the project progress, wherein the preset project progress is a preset project progress corresponding to a current time node;
comparing the engineering progress with the preset engineering progress;
and if the engineering progress is smaller than the preset engineering progress, generating a first analysis result, wherein the first analysis result is used for indicating that the engineering progress is abnormal.
4. The residential engineering construction supervision method according to claim 3, wherein the supervision data packet further comprises engineering cost, the supervision data packet is analyzed by a preset supervision model to obtain an analysis result, and the method specifically further comprises:
determining preset engineering cost according to the engineering cost through the preset supervision model, wherein the preset engineering cost is corresponding to the current time node;
comparing the engineering cost with the preset engineering cost;
and if the engineering cost is greater than the preset engineering cost, generating a second analysis result, wherein the second analysis result is used for indicating that the engineering cost is abnormal.
5. A residential engineering construction supervision method according to claim 3, wherein the first analysis result comprises an impact factor, the method further comprising:
Acquiring the influence factor;
determining the number of influence days according to the influence factors;
the days of influence are displayed.
6. The residential engineering construction supervision method according to claim 1, wherein the supervision data packet is analyzed by a preset supervision model to obtain an analysis result, and the preset supervision model is trained; training the preset supervision model specifically comprises the following steps:
acquiring training information, wherein the training information comprises the supervision data packet and the analysis result;
inputting the training information into a self-adaptive feature fusion network for training to obtain a first training result;
superposing and standardizing the first training result and the training information to obtain a second training result;
inputting the second training result into the self-adaptive feature fusion network for processing to obtain a third training result;
and superposing and standardizing the third training result and the second training result until the training information similarity matrix is output, wherein the training information similarity matrix meets a preset logistic regression condition.
7. The residential engineering construction supervision method according to claim 2, further comprising:
And sending the supervision policy to the user equipment so that a user corresponding to the user equipment can learn the supervision policy, and conducting supervision on the residential engineering construction according to the supervision policy.
8. A residential engineering construction supervision device is characterized in that the residential engineering construction supervision device comprises an acquisition module (21) and a processing module (22), wherein,
the acquisition module (21) is used for acquiring a supervision data packet, wherein the supervision data packet is a supervision data packet for residential engineering construction;
the processing module (22) is configured to analyze the supervision data packet by using a preset supervision model, so as to obtain an analysis result, where a preset engineering progress corresponding to a preset time node and a preset engineering cost corresponding to the preset time node are stored in the preset supervision model in advance;
the processing module (22) is further configured to obtain an exception type corresponding to the supervision packet if the analysis result indicates that the supervision packet is abnormal;
the processing module (22) is further configured to search in a preset supervision database according to the anomaly type, to obtain a supervision policy, where the anomaly type includes an anomaly of an engineering progress and an anomaly of an engineering cost, and the preset supervision database stores in advance a correspondence between the anomaly type and the supervision policy, so as to perform supervision on the residential engineering construction according to the supervision policy.
9. An electronic device, characterized in that the electronic device comprises a processor (31), a memory (35), a user interface (33) and a network interface (34), the memory (35) being adapted to store instructions, the user interface (33) and the network interface (34) being adapted to communicate to other devices, the processor (31) being adapted to execute the instructions stored in the memory (35) to cause the electronic device to perform the method according to any one of claims 1 to 7.
10. A computer readable storage medium storing instructions which, when executed, perform the method of any one of claims 1 to 7.
CN202311415890.8A 2023-10-30 2023-10-30 Residential engineering construction supervision method and device and electronic equipment Pending CN117408561A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117875797A (en) * 2024-03-12 2024-04-12 广东华宸建设工程质量检测有限公司 Collaborative supervision method and system for construction engineering

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117875797A (en) * 2024-03-12 2024-04-12 广东华宸建设工程质量检测有限公司 Collaborative supervision method and system for construction engineering

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