A method for supervising construction quality in engineering supervision

Abstract

The application discloses a kind of engineering supervision construction quality's supervision method, it is related to engineering supervision technical field, to solve the problem that construction rectification instruction can be ignored or forgotten, rectification process lacks effective supervision.Its technical scheme points are as follows: including the following steps: S1, before starting according to design drawing, construction standard and acceptance specification, mobile supervision operation instruction book and the template of electronic inspection form embedded in application program are formulated;S2, when supervisory personnel carries the mobile terminal installed with the application program arrives preset checkpoint, application program generates construction scene based on geographic fence technology.The application converts scattered quality requirements into unified, executable digital instructions by electronic inspection form template and mobile terminal application.When on-site inspection, application program automatically compares data, forces to collect evidence, and synchronizes results in real time, ensures the standard, consistency and efficiency of inspection work from the source, greatly reduces human error and information delay.

Description

Technical Field

[0001] This invention relates to the field of engineering supervision technology, and more specifically, to a method for supervising construction quality in engineering supervision. Background Technology

[0002] In the field of construction engineering, construction quality supervision is a crucial link in ensuring that projects meet design requirements, construction standards, and safety regulations. Traditional quality supervision models primarily rely on supervisors carrying paper checklists to the construction site for manual inspection, measurement, and recording. Upon discovering problems, written supervisory notices are issued to require the construction company to rectify them, necessitating subsequent site visits for verification. Ultimately, quality assessment largely depends on summarized paper records and subjective judgment.

[0003] With the development of information technology, paperless inspection and recording methods using mobile applications have emerged in the industry, improving the efficiency of data entry and storage to some extent. However, most existing digital methods only achieve the electronic transfer of traditional processes. The issuance and execution of inspection tasks still rely on supervisors, making it impossible to effectively monitor whether they have completed the prescribed inspection items on time. This poses the risk of blind spots or perfunctory inspections. Furthermore, in the management of problem discovery, notification, rectification, and review, each link relies on manual promotion and offline communication. Rectification instructions may be ignored or forgotten, and the rectification process lacks effective supervision, leading to untimely reviews and quality problems.

[0004] Therefore, a new solution is needed to address this problem. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method for supervising construction quality in engineering supervision, which has the advantages of ensuring that the supervision work is standardized and efficient.

[0006] The above-mentioned technical objective of this invention is achieved through the following technical solution: a method for supervising construction quality in engineering supervision, comprising the following steps: S1. Before construction begins, develop mobile supervision operation instructions and electronic inspection form templates built into the application based on design drawings, construction standards and acceptance specifications. S2, when the supervisor arrives at the preset inspection point with a mobile terminal equipped with the application, the application generates a construction scene based on geofencing technology and generates a dynamic electronic inspection form corresponding to the construction scene based on the electronic inspection form template. S3, the supervisor completes the inspection according to the dynamic electronic inspection form, obtains the inspection data, and uploads it to the cloud supervision platform; S4. Based on the inspection data, the inspection results are reviewed and accepted. S5, a cloud-based supervision platform, aggregates data and generates a quality status view of the construction. Step S4 further includes: S4.1 When the inspection result is unqualified, the application triggers an alert, guides the supervisor to select the level of unqualified, and automatically generates a supervisor's notice containing the problem location and on-site data, which is then pushed to the construction party; S4.2 The construction party must submit rectification feedback through the client within the specified time limit. If no feedback is submitted within the time limit, the application will automatically upgrade the warning. S4.3 After receiving feedback, the supervisor must return to the site for verification. The application will force a comparison of images before and after rectification. After the supervisor confirms the acceptance result, the application will update the inspection result to qualified or return to step S4.2 to require the construction party to rectify again.

[0007] The present invention is further configured such that, in step S1, the electronic inspection form template includes: inspection location, inspection items, acceptance criteria, allowable deviation, inspection method, type and quantity of image data to be uploaded, and clear options for determining whether an item is qualified or unqualified.

[0008] The present invention is further configured such that step S2 further includes: S2.1 The application matches the pre-set electronic fence with the positioning module of the mobile terminal and uses a computer vision model to identify the on-site construction status. After confirming the target scene by cross-verifying the positioning and visual information, the subsequent process is triggered. S2.2 The application calls the AI ​​engine to integrate BIM data, design parameters, process specifications, environmental data and multi-source historical records, and analyzes and evaluates compliance benchmarks and risk weights through machine learning models, thereby generating an information-enhanced composite scene view; S2.3 The application uses a pre-set electronic inspection form template and data mining algorithm to dynamically adjust inspection items according to specific processes and environmental parameters. It combines historical data and risk maps to identify and predict key points and upgrade critical inspection items, and finally generates and pushes dynamic electronic inspection forms.

[0009] The present invention is further configured such that, in step S3, the completion of the inspection specifically includes: For inspection items whose acceptance criteria are quantitative indicators, the supervisors directly enter the measured data, and the application program automatically compares it with the preset allowable deviation and gives a preliminary judgment result. For inspection items whose acceptance criteria are qualitatively described, the inspection can be completed by checking preset options or entering text descriptions. For inspection items marked as critical processes or hidden works, the application mandates that on-site images with time and geographic coordinate watermarks be taken and uploaded.

[0010] The present invention is further configured such that: in step S4.1, the selected non-compliance level includes three levels: general, serious, and major, and different levels are associated with different default handling time limits and notification scopes; The supervision notification form is a process in which the application automatically captures the location of the problem, the inspection items, the description of the non-compliance, the measured data and the on-site images, and fills them into a standardized electronic template; The generated supervision notice is pushed to the mobile terminal of the person in charge designated by the construction party in real time through application messages, SMS or to-do list according to preset rules, and is also copied to the internal management platform of the supervision party.

[0011] The present invention is further configured such that: in step S4.2, the rectification feedback submitted by the construction party shall at least include a brief description of the rectification measures and video materials proving the rectification process. For serious and major problems, a written rectification plan confirmed by the technical person in charge shall also be submitted.

[0012] The present invention is further configured such that, in step S4.2, the application will automatically upgrade the warning, specifically: if the construction party fails to submit feedback within the time limit specified for the corresponding non-compliance level, the application will automatically upgrade the warning level of the problem and send a reminder notice to the project management party and the supervisor at a higher level.

[0013] The present invention is further configured such that: in step S4.3, the return to the site for verification specifically means that: the supervisor must re-enter the geofence area where the original problem occurred in order to unlock the re-verification function in the application. During the re-verification, the application forces the taking of images after rectification and compares them with the images before rectification stored in the application on the same screen for the supervisor to confirm.

[0014] The present invention is further configured such that: in step S5, the quality status view is a general term for the multi-dimensional quality profile and spatial status map dynamically generated by the platform. The quality profile includes at least the first acceptance pass rate, the distribution of non-conformities, the timely response rate of rectification, and the closure rate. The spatial status map intuitively displays the status of each part in the form of a plan view or elevation view, and distinguishes the qualified closure, rectification in progress, and overdue unprocessed status with different colors.

[0015] In summary, the present invention has the following beneficial effects: 1. By using electronic inspection form templates and mobile terminal applications, scattered quality requirements are transformed into unified and executable digital instructions. During on-site inspections, the application automatically compares data, enforces evidence collection, and synchronizes results in real time, ensuring the standardization, consistency, and efficiency of inspection work from the source, and significantly reducing human error and information delays. Second, the application integrates BIM, environmental and historical data, generates information-enhanced composite scene views through an AI engine, and dynamically adjusts inspection items and identifies key points for prediction using data mining algorithms; this enables inspection work to focus on real-time risks, shifting from post-inspection to process pre-control, significantly improving the pertinence of problem discovery and early intervention capabilities. Third, non-conformities trigger automatic early warning and tiered supervision processes, and the authenticity and closed-loop of rectification are ensured by geofencing and mandatory image comparison. The cloud platform gathers data to generate quality profiles and spatial status maps, making the quality status, weak links and rectification performance clear at a glance. It provides managers with an intuitive and real-time data dashboard, driving the upgrade of quality management from statistics to intelligent decision-making. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating an application scenario of a construction quality supervision method in engineering supervision, based on some embodiments of this specification. Figure 2 This is a flowchart illustrating a construction quality supervision method in engineering supervision, based on some embodiments of this specification; Figure 3 The flowchart illustrates the inspection execution and data upload process according to some embodiments of this specification; Figure 4 This is a flowchart illustrating the composite acceptance closed-loop management according to some embodiments of this specification. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of this application can be combined with each other.

[0018] In the description of this invention, it should be noted that the terms upper, lower, inner, outer top / bottom, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0019] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms installation, setting, fitting / connecting, etc., should be interpreted broadly. For example, connection can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0020] In the field of construction engineering, construction quality supervision is a crucial link in ensuring that projects meet design requirements, construction standards, and safety regulations. Traditional quality supervision models primarily rely on supervisors carrying paper checklists to the construction site for manual inspection, measurement, and recording. Upon discovering problems, written supervisory notices are issued to require the construction company to rectify them, necessitating subsequent site visits for verification. Ultimately, quality assessment largely depends on summarized paper records and subjective judgment.

[0021] With the development of information technology, paperless inspection and recording methods using mobile applications have emerged in the industry, improving the efficiency of data entry and storage to some extent. However, most existing digital methods only achieve the electronic transfer of traditional processes. The issuance and execution of inspection tasks still rely on supervisors, making it impossible to effectively monitor whether they have completed the prescribed inspection items on time. This poses the risk of blind spots or perfunctory inspections. Furthermore, in the management of problem discovery, notification, rectification, and review, each link relies on manual promotion and offline communication. Rectification instructions may be ignored or forgotten, and the rectification process lacks effective supervision, leading to untimely reviews and quality problems.

[0022] In view of this, some embodiments of this specification provide a method for supervising construction quality in engineering supervision.

[0023] Figure 1 This is a schematic diagram illustrating an application scenario of a construction quality supervision method in engineering supervision, based on some embodiments of this specification. For example... Figure 1As shown, the system includes a mobile terminal 110, a dynamic electronic inspection form 120, supervisors 130, and inspection points 140. The mobile terminal 110 is the core interactive node and data acquisition hub for the entire supervision process. The mobile terminal 110 is equipped with a positioning module and can flexibly select GPS, Beidou satellite signals, or indoor Bluetooth beacon networks according to the construction site environment, ensuring accurate spatial positioning in any area. Furthermore, the mobile terminal 110 has pre-installed or online access to the project's BIM model or floor plan, defining electronic fences corresponding to each sub-item of the project, forming inspection trigger zones in the digital space. Simultaneously, the mobile terminal 110 utilizes its camera and computer vision module to enable it to see and understand the site. These modules do not operate in isolation but collaborate through an application. When the positioning module confirms that the mobile terminal 110 has entered the preset electronic fence, the computer vision module is activated, analyzing the site footage to verify the construction status.

[0024] The dynamic electronic inspection form 120 serves as a dynamic carrier and intelligent medium connecting standards and specifications with on-site execution. It is not a static document, but rather a dynamic task list instantly generated by the mobile terminal 110 based on the electronic inspection form template after the mobile terminal 110 arrives at the inspection point 140. Relying on the basic electronic inspection form template, the dynamic electronic inspection form 120 uses geofencing to determine macroscopic inspection locations, combined with computer vision-based microscopic construction activities, to lock onto the current scene. It integrates BIM design data, process specifications, real-time environmental parameters, and historical quality records for that location, and performs real-time analysis through an embedded machine learning model. Based on this analysis, the electronic inspection form template is dynamically adjusted to strengthen inspection requirements for high-risk items, hide irrelevant items according to process progress, and automatically identify predicted key areas such as frequently occurring historical problems.

[0025] exist Figure 1 In the illustrated application scenario, the role of the supervisor 130 has shifted from relying primarily on personal experience and paper records in the traditional model to evolving into a human-machine collaborative, data-driven intelligent inspector and final decision-maker. At inspection point 140, the supervisor 130's main interface is a dynamic electronic inspection form 120 presented on a mobile terminal 110. Inspections are conducted according to the standardized guidelines of the dynamic electronic inspection form 120, reducing the burden on the supervisor 130 of memorizing complex specifications, manual calculations and comparisons, and subjective descriptions of the situation, thus lowering the risk of human error. In one embodiment, the core value of the supervisor 130 lies more in making final decisions on complex situations, professionally verifying AI-generated prompts, and crucially confirming the effectiveness of rectification within the closed-loop process.

[0026] exist Figure 1In the illustrated application scenario, checkpoint 140 is no longer a vague geographical concept of the construction site, but rather a smart spatial anchor point that is precisely defined in the digital space, possesses rich attribute information, and can interact with the physical world in real time. Each checkpoint 140 is digitally defined in the project's BIM model or floor plan using electronic fence technology, and its scope strictly corresponds to a specific construction location. In one embodiment, the construction scope may include a wall, equipment, or a section of a construction component. This digital definition gives checkpoint 140 an identity ID and spatial boundaries that can be automatically recognized by the program.

[0027] like Figure 2 As shown in Figure S1, before construction begins, a mobile supervision operation guide and an electronic inspection form template built into the application are prepared in accordance with the design drawings, construction standards and acceptance specifications.

[0028] In some embodiments, S1 is the cornerstone of the entire digital and standardized supervision work. The supervision operation manual clarifies the mobile inspection process and responsibilities of the supervisors 130 at each construction stage and for different sub-items. The electronic inspection form template is the operational carrier of this process. The electronic inspection form template includes: inspection location, inspection item, acceptance standard, allowable deviation, and inspection method. The inspection method includes, but is not limited to, measurement, observation, and testing. It also mandates the types and minimum quantity requirements of the on-site image data to be uploaded. For example, multi-angle photos with spatiotemporal watermarks must be taken for key processes or concealed works. Most importantly, the form has pre-set clear pass and fail options. For quantifiable indicators, the application will automatically compare the entered data with the allowable deviation. For qualitative descriptions, standardized checkboxes are provided. Through this deep customization in advance, the quality requirements scattered in various documents are transformed into a unified set. The executable and easily collected digital inspection instructions by the mobile terminal 110 and processed in the cloud ensure the standardization, consistency, and efficiency of the supervision and inspection work from the source.

[0029] In some embodiments, such as Figure 2 and Figure 3 As shown in step S2, when the supervisor 130 arrives at the preset inspection point 140 with a mobile terminal 110 equipped with the application, the application generates a construction scene based on geofencing technology and generates a dynamic electronic inspection form 120 corresponding to the construction scene based on the electronic inspection form template. This process changes the traditional inspection mode that relies on paper forms and manual judgment. Based on geofencing technology, it ensures the accurate alignment of inspection instructions with on-site conditions, laying the foundation for high-quality data collection.

[0030] S2.1 The application matches the pre-set electronic fence with the positioning module of the mobile terminal 110, and uses a computer vision model to identify the on-site construction status. After confirming the target scene by cross-verifying the positioning and visual information, the application triggers the subsequent process.

[0031] The positioning module of mobile terminal 110 can use GPS, Beidou positioning, or indoor Bluetooth beacons. The application uses the positioning module to match the pre-set electronic fences in the engineering BIM model or floor plan in real time. At the same time, it calls the camera of mobile terminal 110 and uses its embedded computer vision module to analyze the images or videos captured on site in real time to identify the ongoing construction activities, main materials, and equipment. By cross-validating and judging the confidence level through positioning information and visual information, the application can confirm the current location and target construction scene, rather than just arriving at some abstract geographical coordinates. This dual verification mechanism reduces the problem of errors or inappropriate timing in checking geographical location from the source, ensuring that all subsequent operations are triggered based on some verified real scene.

[0032] S2.2 The application calls the AI ​​engine to integrate BIM data, design parameters, process specifications, environmental data and multi-source historical records. Through machine learning models, it analyzes and evaluates compliance benchmarks and risk weights, thereby generating an information-enhanced composite scene view.

[0033] The core capabilities of the application's AI engine are rooted in a series of specially trained machine learning models. These models first rely on building structured training datasets derived from massive amounts of inspection records from historical projects, verified and accepted by all parties. Each record includes design parameters for specific parts, process specifications, measured data, and clear labels for pass / fail. Machine learning models can employ techniques such as random forests, gradient boosting decision trees, or deep neural networks, which effectively handle complex nonlinear relationships. Through learning from these samples, these models gradually establish a nonlinear mapping relationship between design parameters, process requirements, and actual quality performance, internalizing the quantitative and qualitative standards of various acceptance specifications. When new data is input from the field, the machine learning models can not only quickly compare measured values ​​with allowable deviations but also comprehensively judge the compliance level of the current state based on the distribution of historical compliance samples under similar working conditions. This generates dynamic, probabilistic compliance benchmarks, rather than rigid thresholds.

[0034] Meanwhile, the training of models used to assess risk weights focuses more on in-depth mining of temporal patterns and association rules, typically employing deep learning networks and ensemble learning methods. For example, deep learning networks can use Long Short-Term Memory networks or temporal convolutional networks to process environmental and process data with time-series characteristics; ensemble learning methods can use decision tree-based ensemble frameworks such as extreme gradient boosting or lightweight gradient boosters to fuse multi-source features and improve the accuracy of risk pattern recognition. This includes, but is not limited to, environmental data sequences from different stages, process connection logs, and historical quality issues from databases of this project (if any) and similar engineering projects, including the occurrence time, location, handling process, and final impact. By processing this data, the model learns to identify precursory patterns and multi-factor coupled risks leading to quality defects. In real-time applications, the model integrates currently captured environmental data, ongoing processes, and past quality history of the relevant area, calling upon learned risk patterns for matching and deduction, thereby outputting quantitative risk warning weights for specific quality issues. Ultimately, the probabilistic judgments provided by the compliance benchmark model and the early warning signals generated by the risk weight model are fused and overlaid by the AI ​​engine onto the 3D scene or real-world imagery provided by BIM, generating augmented reality scene views. In this view, supervisors can not only see the basic information of the components, but also intuitively obtain confidence level prompts and highlighted risk warnings, realizing a shift from passive inspection to proactive risk prevention and control.

[0035] S2.3, the application dynamically adjusts inspection items based on pre-set electronic inspection form templates and data mining algorithms, according to specific processes and environmental parameters. It combines historical data and risk maps to identify and predict key areas and upgrade critical inspection items, ultimately generating and pushing a dynamic electronic inspection form 120. Specifically, the dynamic adjustment follows these rules: For strengthening high-risk items, based on the quantified risk value output by the model that assesses risk weights in step S2.2, when the risk value corresponding to a certain inspection item exceeds a preset threshold, the application marks that inspection item as a critical mandatory inspection item in the dynamic electronic inspection form 120, increases its detailed inspection items, and raises the required quantity or clarity requirements of uploaded image data. For hiding irrelevant items, based on the currently identified specific process stage and environmental parameters, the application collapses or hides inspection items in the electronic inspection form template that are irrelevant to that stage or minimally affected by the current environmental parameters, in order to focus on the current core inspection content.

[0036] In this step, the application transforms the static checklist into adaptive decision-making tools. This process begins with the invocation of pre-set electronic inspection form templates. Based on this framework, the application's built-in data mining algorithm analyzes the results from step S2.2 in real time, including specific process stages, real-time environmental parameters, and the overall risk weight of that location. For example, when it identifies the current process as concrete pouring for a floor slab in high-temperature weather, the data mining algorithm immediately correlates the composite scene view and dynamically adjusts the form, such as automatically enhancing checks like concrete placement temperature monitoring. This adjustment is based on matching environmental and process coupling rule bases, ensuring that the inspection focus is synchronized with the most volatile quality factors.

[0037] Furthermore, it can combine historical inspection data from similar projects already generated in this project and imported from external sources, along with a global quality risk map. By continuously analyzing the defect incidence, severity, and causes of all similar processes, the application not only retrieves standard engineering inspection items when supervisor 130 inspects similar areas, but also proactively identifies predicted key points and upgrades them to critical inspection items. These are emphasized in the form through highlighting, strong prompts, or increasing the number of required images. Ultimately, this dynamic electronic inspection form 120, which integrates real-time context, historical lessons, and risk prediction, is pushed to supervisor 130. The dynamic electronic inspection form 120 improves the targeting of inspections and the efficiency of problem discovery, guiding supervisor 130 to conduct an efficient, accurate, and targeted quality inspection.

[0038] S3, the supervisor 130 completes the inspection according to the dynamic electronic inspection form 120, obtains the inspection data, and uploads it to the cloud supervision platform. The inspection includes: for inspection items with quantitative indicators as acceptance standards, such as rebar spacing, concrete strength, wall verticality, etc., the supervisor 130 only needs to use the mobile terminal 110 to directly input or connect to professional measurement tools via Bluetooth to automatically input the measured data. The application randomly calls the built-in acceptance algorithm to compare the measured values ​​with the preset allowable deviation range in the dynamic electronic inspection form 120 in real time and automatically, reducing the errors and delays that may be caused by manual calculation and judgment.

[0039] For inspection items whose acceptance criteria are qualitative, such as uniform coating, no drips, and smooth construction joint treatment, the application guides supervisors to make objective and consistent descriptive judgments by providing preset standardized options or supplementing them with brief text description input boxes, effectively avoiding ambiguity in understanding caused by differences in individual expressions.

[0040] In some embodiments, for inspection items marked as critical processes or concealed works, the application initiates a mandatory evidence solidification process. The interface clearly prompts and locks the next step, mandating that the supervisor 130 take and upload a fixed number of images and videos at specific angles on-site. These photos or short videos are automatically embedded with an immutable timestamp and geographic coordinate watermark by the application at the moment of capture, forming digital evidence uniquely bound to the inspection point 140 and the inspection time. All inspection data, whether automatically determined results, selected options, entered text, or watermarked images, are automatically integrated and uploaded to the cloud supervision platform in real time when the inspection is submitted, achieving seamless synchronization from the site to the data center. This ensures the timeliness, authenticity, and non-repudiation of the inspection records, laying a solid and credible data foundation for subsequent closed-loop rectification and quality traceability.

[0041] like Figure 4 As shown, S4, based on the inspection data, the inspection results are reviewed and accepted; S4.1 When the inspection result is unqualified, the application triggers an alert, guiding the supervisor 130 to select the unqualified level. The unqualified level can be divided into three levels: general, serious, and major. Different levels are associated with different default handling time limits and notification scopes. The application automatically generates a supervisor notification form containing the problem location and on-site data. The supervisor notification form is generated by the application automatically capturing the location of the problem, inspection items, unqualified description, measured data, and on-site images, and filling them into a standardized electronic template. The generated supervisor notification form is pushed to the mobile terminal 110 of the person in charge designated by the construction party in real time through application messages, SMS, or to-do list according to preset rules, and is also copied to the internal management platform of the supervisor.

[0042] S4.2 The construction party must submit rectification feedback through the client within the specified time limit. The feedback must include at least a brief description of the rectification measures and video evidence of the rectification process. For serious and major issues, a written rectification plan confirmed by the technical supervisor must also be submitted. If no feedback is submitted within the specified time, the application will automatically escalate the warning. Specifically, if the construction party fails to submit feedback within the time limit specified for the corresponding non-compliance level, the application will automatically raise the warning level for that issue and send reminder notices to the project management and supervision personnel at higher levels.

[0043] S4.3 After receiving feedback, the supervisor 130 must return to the site for verification. They must re-enter the geofence where the original problem occurred in order to unlock the re-inspection function in the application. During the re-inspection, the application will require the taking of images after rectification and comparing them with the images before rectification stored in the application on the same screen for the supervisor 130 to confirm. After confirming the acceptance result, the application will update the inspection result to qualified or return to step S4.2 to require the construction party to rectify again.

[0044] The S5 cloud-based supervision platform continuously aggregates and integrates real-time inspection data, rectification process data, and external environment data uploaded from all mobile terminals. Through a data analysis engine, it generates an intuitive and multi-dimensional construction quality status view, transforming massive amounts of on-site information into an actionable state. The quality status view is a collective term for the multi-dimensional quality profile and spatial status map dynamically generated by the platform. The quality profile includes at least the first-time acceptance pass rate, non-conformity distribution, rectification response timeliness rate, and closure rate. The first-time acceptance pass rate measures the accuracy and workmanship of the construction team's first operation. The non-conformity distribution statistics can be analyzed from multiple dimensions by responsible unit, problem type, and location, clearly revealing weak links in quality. The rectification response timeliness rate and rectification closure rate can track the efficiency and effectiveness from problem discovery to complete resolution, serving as a benchmark for measuring management execution and problem resolution capabilities. These indicators can be updated in real time with each new data entry and trend analysis can be performed to warn of quality decline risks.

[0045] Meanwhile, the spatial status diagram directly links abstract data with specific engineering entities. Using the project's BIM model, floor plan, or elevation as a base map, it visually renders each inspection area with different colors based on its latest processing status. For example, green represents a qualified and closed-loop system, yellow represents rectification in progress, and red indicates overdue and unprocessed issues. Managers only need to view this spatial status diagram to grasp the quality status of the entire construction project, improving the intuitiveness and responsiveness of management decisions. This allows quality control to move from post-event statistics to a real-time, visible, and predictable intelligent management stage.

[0046] How to use: First, the supervisor 130, based on the work instructions, triggers an intelligent inspection process on the mobile terminal 110 using geofencing and visual verification. Then, based on the dynamic electronic inspection form 120 generated by the application, the supervisor completes standardized inspection and data collection, which is automatically uploaded to the cloud platform. If any non-conformities are found, a closed-loop process including early warning, notification, rectification feedback, and mandatory on-site image comparison and verification is initiated through the application. Finally, all data is integrated into the cloud supervision platform, dynamically generating a multi-dimensional quality profile and spatial status map.

[0047] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for supervising construction quality in engineering supervision, characterized in that, Includes the following steps: S1. Before construction begins, develop mobile supervision operation instructions and electronic inspection form templates built into the application based on design drawings, construction standards and acceptance specifications. S2, when the supervisor arrives at the preset inspection point with a mobile terminal equipped with the application, the application generates a construction scene based on geofencing technology and generates a dynamic electronic inspection form corresponding to the construction scene based on the electronic inspection form template. S3, the supervisor completes the inspection according to the dynamic electronic inspection form, obtains the inspection data, and uploads it to the cloud supervision platform; S4. Based on the inspection data, the inspection results are reviewed and accepted. S5, a cloud-based supervision platform, aggregates data and generates a quality status view of the construction. Step S4 further includes: S4.1 When the inspection result is unqualified, the application triggers an alert, guides the supervisor to select the level of unqualified, and automatically generates a supervisor's notice containing the problem location and on-site data, which is then pushed to the construction party; S4.2 The construction party must submit rectification feedback through the client within the specified time limit. If no feedback is submitted within the time limit, the application will automatically upgrade the warning. S4.3 After receiving feedback, the supervisor must return to the site for verification. The application will force a comparison of images before and after rectification. After the supervisor confirms the acceptance result, the application will update the inspection result to qualified or return to step S4.2 to require the construction party to rectify again.

2. The method for supervising construction quality in engineering supervision according to claim 1, characterized in that, In step S1, the electronic inspection form template includes: inspection location, inspection items, acceptance criteria, allowable deviation, inspection method, type and quantity of image data to be uploaded, and clear options for determining whether an item is qualified or unqualified.

3. The method for supervising construction quality in engineering supervision according to claim 1, characterized in that, Step S2 further includes: S2.1 The application matches the pre-set electronic fence with the positioning module of the mobile terminal and uses a computer vision model to identify the on-site construction status. After confirming the target scene by cross-verifying the positioning and visual information, the subsequent process is triggered. S2.2 The application calls the AI ​​engine to integrate BIM data, design parameters, process specifications, environmental data and multi-source historical records, and analyzes and evaluates compliance benchmarks and risk weights through machine learning models, thereby generating an information-enhanced composite scene view; S2.3 The application uses a pre-set electronic inspection form template and data mining algorithm to dynamically adjust inspection items according to specific processes and environmental parameters. It combines historical data and risk maps to identify and predict key points and upgrade critical inspection items, and finally generates and pushes dynamic electronic inspection forms.

4. The method for supervising construction quality in engineering supervision according to claim 1, characterized in that, In step S3, the completion of the inspection specifically includes: For inspection items whose acceptance criteria are quantitative indicators, the supervisors directly enter the measured data, and the application program automatically compares it with the preset allowable deviation and gives a preliminary judgment result. For inspection items whose acceptance criteria are qualitatively described, the inspection can be completed by checking preset options or entering text descriptions. For inspection items marked as critical processes or hidden works, the application mandates that on-site images with time and geographic coordinate watermarks be taken and uploaded.

5. The method for supervising construction quality in engineering supervision according to claim 1, characterized in that, In step S4.1, the selected non-compliance level includes three levels: general, serious, and major. Different levels are associated with different default handling time limits and notification scopes. The supervision notification form is a process in which the application automatically captures the location of the problem, the inspection items, the description of the non-compliance, the measured data and the on-site images, and fills them into a standardized electronic template; The generated supervision notice is pushed to the mobile terminal of the person in charge designated by the construction party in real time through application messages, SMS or to-do list according to preset rules, and is also copied to the internal management platform of the supervision party.

6. The method for supervising construction quality in engineering supervision according to claim 1, characterized in that, In step S4.2, the rectification feedback submitted by the construction party shall include at least a brief description of the rectification measures and video materials proving the rectification process. For serious and major issues, a written rectification plan confirmed by the technical supervisor shall also be submitted.

7. A method for supervising construction quality in engineering supervision according to claim 6, characterized in that, In step S4.2, the application will automatically escalate the warning as follows: if the construction party fails to submit feedback within the time limit specified for the corresponding non-compliance level, the application will automatically escalate the warning level of the problem and send a reminder notice to the project management party and the supervisor at a higher level.

8. A method for supervising construction quality in engineering supervision according to claim 6, characterized in that, In step S4.3, the re-site verification specifically means that the supervisor must re-enter the geofence area where the original problem occurred in order to unlock the re-verification function in the application. During the re-verification, the application will require the shooting of the image after rectification and compare it with the image before rectification stored in the application on the same screen for the supervisor to confirm.

9. A method for supervising construction quality in engineering supervision according to claim 1, characterized in that, In step S5, the quality status view is a collective term for the multi-dimensional quality profile and spatial status map dynamically generated by the platform. The quality profile includes at least the first acceptance pass rate, the distribution of non-conformities, the timely response rate of rectification, and the closure rate. The spatial status map visually displays the status of each part in the form of a plan view or elevation view, and uses different colors to distinguish between qualified closure, rectification in progress, and overdue unprocessed situations.

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