Engineering quality inspection and detection anti-counterfeiting method and system based on cloud platform

Abstract

The invention relates to the technical field of engineering anti-counterfeiting, and discloses an engineering quality inspection and detection anti-counterfeiting method and system based on a cloud platform, and the method comprises the steps: obtaining the data of a detection mechanism, carrying out the online analysis of the data of the detection mechanism, and carrying out the dynamic adjustment according to the performance of the detection mechanism, a personnel database with corresponding qualification requirements of a detection mechanism is established based on a cloud platform, dynamic score adjustment is performed according to the performance of inspection and detection personnel in a project, and detection behaviors and test block inspection and detection data in a construction site are monitored and collected in real time based on an unmanned aerial vehicle and a data sensor. And uploading the collected data to a cloud platform, judging the normalization of the detection behavior and the accuracy of the test block detection data, and generating a detection report. According to the invention, the authenticity of engineering quality inspection and detection is ensured, inspection and detection errors caused by human factors are reduced, and the whole process of engineering quality inspection and detection is supervised through a management function and a technical function.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering anti-counterfeiting, and in particular to a method and system for engineering quality inspection and detection anti-counterfeiting based on a cloud platform. Background Art

[0002] According to the Construction Law and other relevant regulations, in order to ensure the safety and construction quality of buildings, corresponding engineering quality inspections must be carried out during the construction process. Third-party inspection agencies play an important role in ensuring engineering quality. Their independence, objectivity and professionalism can effectively ensure the sustainable development of construction projects. However, due to objective reasons, there are still some non-standard inspection behaviors, and even problems with falsification of inspection and testing data. From a regulatory perspective, how to achieve effective supervision of inspection agencies is particularly important. Therefore, there is an urgent need for a method to comprehensively supervise inspection agencies and prevent fraud in all aspects. Summary of the invention

[0003] The purpose of the present invention is to overcome one or more of the above-mentioned existing technical problems and provide a cloud platform-based engineering quality inspection and detection anti-fraud method and system.

[0004] To achieve the above purpose, the present invention provides a cloud platform-based engineering quality inspection and detection anti-fraud method, comprising: Obtain the information of the testing agency, upload the information of the testing agency to the cloud platform, analyze the information of the testing agency online based on the cloud platform, and make dynamic adjustments based on the performance of the testing agency in the actual project; Based on the cloud platform, a personnel database with corresponding qualification requirements of the testing agency is established, personnel information is registered and recorded, and photos of the testing personnel are input. During the project testing process, designated testing personnel are set from the personnel database, and dynamic scoring is adjusted based on the performance of the testing personnel in the project; Based on drones and data sensors, real-time monitoring and collection of inspection behaviors and test block inspection data at the construction site are carried out, and the collected data are uploaded to the cloud platform; Clean and mine the data uploaded to the cloud platform, extract data features, mine and analyze the data through heuristic algorithms and deep learning algorithms, identify outliers and abnormal results in the data, and thus judge the standardization of the testing behavior and the accuracy of the test block inspection data; Based on the detection behavior and the test block inspection data, the corresponding relevant data is obtained and a test report is generated.

[0005] According to one aspect of the present invention, the online analysis of the data of the testing organization based on the cloud platform and the dynamic adjustment according to the performance of the testing organization in the actual project include: Based on the cloud platform, the data uploaded by testing institutions at all levels are obtained, and the uploaded data are reviewed and approved. The uploaded data are divided into ordinary files and important files. Ordinary files are management requirements files, quality control requirements files, credit system requirements files, risk prevention and control requirements files, sustainable development requirements files and agency award files. Important files are files related to violations. The scoring algorithm for the testing agency is set by weighted method, and the testing agency that has passed the data verification is evaluated based on the scoring algorithm. The comprehensive capability level of the testing agency is saved in the cloud platform, where the formula is,; ; in, Indicates the total score of the testing organization; Indicates the impact factor of important documents; Indicates the sum of 1-6 common files; Indicates the weight of the assessment index of common files; Indicates the score of the testing agency on the assessment indicators of general documents.

[0006] According to one aspect of the present invention, the online analysis of the data of the testing organization based on the cloud platform and the dynamic adjustment according to the performance of the testing organization in the actual project also include: The testing agency in the cloud platform updates the certification information every month. If it fails to do so, the cloud platform will suspend the testing agency's inspection of the construction and notify the contact person of the testing agency to supplement the information in a timely manner; In response to the supplement and modification of the testing agency's information, the testing agency will be re-evaluated based on the scoring algorithm and the corresponding level will be changed in the cloud platform; For lower-level testing agencies, the cloud platform will promptly issue early warnings to the testing agencies and send copies to the relevant project responsible parties to remind them of relevant risks.

[0007] According to one aspect of the present invention, the personnel database of the testing organization is updated according to the latest adjustment of the testing personnel of the testing organization; During the inspection process, the camera uses the face recognition algorithm to identify the inspector in real time to confirm the inspector's authority; If the inspection personnel are detected to have performed operations beyond their authority, the cloud platform will automatically save the video of the inspection process, issue an early warning on the cloud platform, and notify the inspection agency, construction unit, and management unit; The level of the inspector is set as a suspicious person, the inspection task of the inspector is suspended, and the impact factor of the important files of the inspection agency is set to 0.

[0008] According to one aspect of the present invention, the real-time monitoring and collection of inspection behaviors and test block inspection data at the construction site based on drones and data sensors includes: Establish a video image management system for the testing process, and conduct real-time supervision and recording of testing behaviors by analyzing the image data of on-site testing; Use drones to film the inspection process of inspectors on site in real time, and record the location of inspection sampling according to the drone's positioning system. If the sampling location is inconsistent with the preset plan, the cloud platform automatically saves the illegal video and notifies the inspection agency, construction unit and management unit; The entire process of the specimen test is recorded using laboratory surveillance cameras and automatically saved on the cloud platform; The facial recognition system of the camera in the laboratory is used to monitor the authority of the inspectors. When the inspectors exceed their authority, the cloud platform automatically saves the video of the violation and notifies the inspection agency, construction unit and management unit.

[0009] According to one aspect of the present invention, the method for identifying outliers and abnormal results in data is: Mining and analyzing data through heuristic algorithms and deep learning algorithms to identify outliers and abnormal results in the data; The test value of the specimen is set to a. According to engineering experience, the test value of the specimen is b. According to the inspection and testing standards, the test value of the specimen is c. If satisfied and and and When , the test block inspection data is normal and can be included in the test value. Otherwise, the test value is an outlier and is an abnormal result. represents the j-th detection value, It represents the sum of all test values ​​of a parameter before the i-th test. Represents the i-th detection value.

[0010] To achieve the above purpose, the present invention provides a cloud platform-based engineering quality inspection and detection anti-fraud system, comprising: Testing agency data analysis module: obtain the testing agency data, upload the testing agency data to the cloud platform, analyze the testing agency data online based on the cloud platform, and make dynamic adjustments based on the testing agency's performance in actual projects; Personnel database establishment module: Based on the cloud platform, a personnel database with corresponding qualification requirements is established for the testing agency, personnel information is registered and recorded, and photos of the testing personnel are input. During the inspection and testing of the project, the designated testing personnel are set from the personnel database, and dynamic scoring is adjusted according to the performance of the testing personnel in the project; Inspection data acquisition module: Based on drones and data sensors, it monitors and collects inspection behaviors and test block inspection data at the construction site in real time, and uploads the collected data to the cloud platform; Test data analysis module: cleans and mines the data uploaded to the cloud platform, extracts data features, mines and analyzes the data through heuristic algorithms and deep learning algorithms, identifies outliers and abnormal results in the data, and thus determines the standardization of the test behavior and the accuracy of the test block inspection data; Test report generation module: based on the test behavior and test block inspection data, it obtains the corresponding relevant data and generates a test report.

[0011] To achieve the above-mentioned purpose, the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the above-mentioned anti-fraud method for engineering quality inspection and testing based on a cloud platform is implemented.

[0012] To achieve the above-mentioned purpose, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned anti-fraud method for engineering quality inspection and testing based on a cloud platform is implemented.

[0013] Based on this, the beneficial effects of the present invention are: supervising the collection, transmission, storage and use process of the detection data, ensuring the authenticity and security of the data, and achieving the traceability of the entire process of the detection data; Supervise the behavior of testers to ensure that the testing process is standardized, fair, scientific and legal. Establish a video image management system for the testing process. By analyzing the image data of on-site testing, conduct real-time supervision and record of testing behavior to ensure the fairness and authenticity of the testing process. Through the supervision of the above contents, fraud in project quality inspection and testing can be effectively avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of a method for preventing fraud in engineering quality inspection and detection based on a cloud platform according to an exemplary embodiment; Figure 2 It is a flow chart of a cloud platform-based engineering quality inspection and anti-fraud system according to an exemplary embodiment. DETAILED DESCRIPTION

[0015] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only for enabling those skilled in the art to better understand and thereby implement the present invention, rather than implying any limitation on the scope of the present invention.

[0016] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on,” and the terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0017] According to one embodiment of the present invention, Figure 1 is a flow chart of a method for preventing fraud in engineering quality inspection and detection based on a cloud platform according to an exemplary embodiment, such as Figure 1 As shown, in order to achieve the above purpose, the present invention provides a method for preventing fraud in engineering quality inspection and detection based on a cloud platform, comprising: Obtain the information of the testing agency, upload the information of the testing agency to the cloud platform, analyze the information of the testing agency online based on the cloud platform, and make dynamic adjustments based on the performance of the testing agency in the actual project; Based on the cloud platform, a personnel database with corresponding qualification requirements of the testing agency is established, personnel information is registered and recorded, and photos of the testing personnel are input. During the project testing process, designated testing personnel are set from the personnel database, and dynamic scoring is adjusted based on the performance of the testing personnel in the project; Based on drones and data sensors, real-time monitoring and collection of inspection behaviors and test block inspection data at the construction site are carried out, and the collected data are uploaded to the cloud platform; Clean and mine the data uploaded to the cloud platform, extract data features, mine and analyze the data through heuristic algorithms and deep learning algorithms, identify outliers and abnormal results in the data, and thus judge the standardization of the testing behavior and the accuracy of the test block inspection data; Based on the detection behavior and the test block inspection data, the corresponding relevant data is obtained and a test report is generated.

[0018] According to one embodiment of the present invention, online analysis of the data of the testing organization based on the cloud platform and dynamic adjustment based on the performance of the testing organization in the actual project include: Based on the cloud platform, the data uploaded by testing institutions at all levels are obtained, and the uploaded data are reviewed and approved. The uploaded data are divided into ordinary files and important files. Ordinary files are management requirements files, quality control requirements files, credit system requirements files, risk prevention and control requirements files, sustainable development requirements files and agency award files. Important files are files related to violations. The management requirements document includes qualifications, management system, information management, revenue, compliance with laws and regulations, social responsibility activities, and customer service management system; The quality control requirement documents include the qualifications of the testing agency personnel, the status of the instruments and equipment, the testing site and environmental management system, the inspection and testing contract management, the inspection and testing methods, the sample management, the inspection and testing process management, the original record management, the inspection and testing report template, the file management, the comparison test and the capability verification; The credit system requires documents to include organizational measures, target commitments, and credit culture construction; Risk prevention and control requirements include regular risk assessment mechanisms, special risk response plans, and risk control education records; The continuous development requirement document includes quality management maintenance measures and quality management improvement measures; The institution's award-winning documents include national awards, provincial and ministerial awards, municipal awards, patents, software works, and copyrights; The relevant documents of violation include statistics of current illegal testing management methods, testing agency qualification standards and other laws and regulations; The scoring algorithm for the testing agency is set by weighted method, and the testing agency that has passed the data verification is evaluated based on the scoring algorithm. The comprehensive capability level of the testing agency is saved in the cloud platform, where the formula is,; ; in, Indicates the total score of the testing organization; Indicates the impact factor of important documents; Indicates the sum of 1-6 common files; Indicates the weight of the assessment index of common files; Indicates the score of the testing agency on the assessment indicators of ordinary documents; When the testing agency has violations, the impact factor of important documents is 0, otherwise the impact factor of important documents is 1, the weight of the assessment indicators of management requirement documents is 0.39, the weight of the assessment indicators of quality control requirement documents is 0.27, the weight of the assessment indicators of credit system requirement documents is 0.06, the weight of the assessment indicators of risk prevention and control requirement documents is 0.07, the weight of the assessment indicators of sustainable development requirement documents is 0.06, and the weight of the assessment indicators of the agency's award-winning documents is 0.15. When the total score of the testing agency is ≥80, the testing agency is rated A; when 80 points> the total score of the testing agency is ≥70 points, the testing agency is rated B; when 70 points> the total score of the testing agency is ≥60 points, the testing agency is rated C; when 60 points> the total score of the testing agency, the testing agency is rated D.

[0019] According to one embodiment of the present invention, online analysis of the data of the testing organization based on the cloud platform and dynamic adjustment based on the performance of the testing organization in the actual project also includes: The testing agency in the cloud platform updates the certification information every month. If it fails to do so, the cloud platform will suspend the testing agency's inspection of the construction and notify the contact person of the testing agency to supplement the information in a timely manner; In response to the supplement and modification of the testing agency's information, the testing agency will be re-evaluated based on the scoring algorithm and the corresponding level will be changed in the cloud platform; For lower-level testing agencies, the cloud platform will promptly issue early warnings to the testing agencies and send copies to the relevant project responsible parties to remind them of relevant risks.

[0020] According to one aspect of the present invention, the personnel database of the testing organization is updated according to the latest adjustment of the testing personnel of the testing organization; During the inspection process, the camera uses the face recognition algorithm to identify the inspector in real time to confirm the inspector's authority; If the inspection personnel are detected to have performed operations beyond their authority, the cloud platform will automatically save the video of the inspection process, issue an early warning on the cloud platform, and notify the inspection agency, construction unit, and management unit; The level of the inspector is set as a suspicious person, the inspection task of the inspector is suspended, and the impact factor of the important files of the inspection agency is set to 0.

[0021] According to one embodiment of the present invention, real-time monitoring and collection of inspection behaviors and test block inspection data at a construction site based on drones and data sensors include: Establish a video image management system for the testing process, and conduct real-time supervision and recording of testing behaviors by analyzing the image data of on-site testing; Use drones to film the inspection process of inspectors on site in real time, and record the location of inspection sampling according to the drone's positioning system. If the sampling location is inconsistent with the preset plan, the cloud platform automatically saves the illegal video and notifies the inspection agency, construction unit and management unit; The entire process of the specimen test is recorded using laboratory surveillance cameras and automatically saved on the cloud platform; The facial recognition system of the camera in the laboratory is used to monitor the authority of the inspectors. When the inspectors exceed their authority, the cloud platform automatically saves the video of the violation and notifies the inspection agency, construction unit and management unit.

[0022] According to one embodiment of the present invention, a method for identifying outliers and abnormal results in data is as follows: Mining and analyzing data through heuristic algorithms and deep learning algorithms to identify outliers and abnormal results in the data; The test value of the specimen is set to a. According to engineering experience, the test value of the specimen is b. According to the inspection and testing standards, the test value of the specimen is c. If satisfied and and and When , the test block inspection data is normal and can be included in the test value. Otherwise, the test value is an outlier and is an abnormal result. represents the j-th detection value, It represents the sum of all test values ​​of a parameter before the i-th test. Represents the i-th detection value.

[0023] According to one embodiment of the present invention, it also includes automatic report generation. Based on the data collected on the cloud platform, parameters such as concrete strength, tensile strength of steel bar joints, concrete density and other information corresponding to the data, environmental parameters, project overview and other information, a test report is automatically generated with one click to avoid the influence of human factors.

[0024] According to one embodiment of the present invention, any information changes in the cloud platform, including sample numbers, original data, original records, test reports, etc., can be retrieved by authorized personnel at any time. The information includes information such as the test standards and methods used in the test process, which standardizes the test process while also achieving traceability of the test work.

[0025] According to one embodiment of the present invention, the equipment model corresponding to the detection parameters in the inspection and testing process is selected on the cloud platform, and a remote networking function is established to realize functions such as setting up the detection equipment, collecting data, and preliminary storage of data.

[0026] According to one embodiment of the present invention, the anti-counterfeiting detection method for concrete test blocks is to input the test block image before the experiment and the test block image after the experiment into the first convolution module to obtain the first convolution module feature before the experiment and the first convolution module feature after the experiment, wherein the formula is, ; ; in, represents the image of the test block before the experiment; Represents the image of the test block after the test; Represents a 3×3 convolution kernel; represents the first convolutional module; Represents the features of the first convolutional module before the experiment; Represents the features of the first convolutional module after the experiment; The features of the first convolution module before the experiment and the features of the second convolution module after the experiment are input into the second convolution module to obtain the initial convolution features before the experiment and the initial convolution features after the experiment, where the formula is, ; ; in, represents the second convolutional module; Represents the initial convolution features before the experiment; Represents the initial convolution features after the experiment.

[0027] The initial convolution features before the experiment and the initial convolution features after the experiment are input into the first repeated convolution module to obtain the first repeated convolution module features before the experiment and the first repeated convolution module features after the experiment, where the formula is, ; ; in, represents the first repeated convolution module; Represents a 1×1 convolution kernel; Indicates that the convolution kernel is 4×4 depth separation convolution; Represents the features of the first repeated convolution module before the experiment; Represents the features of the first repeated convolution module after the experiment; The features of the first repeated convolution module before the experiment and the features of the first repeated convolution module after the experiment are input into the second repeated convolution module to obtain the deepening convolution features before the experiment and the deepening convolution features after the experiment, where the formula is, ; ; in, represents the second repeated convolution module; Indicates deepening of convolution features before the experiment; Indicates deepening of convolution features after the experiment.

[0028] The deepening convolution features before the experiment and the deepening convolution features after the experiment are input into the first integration module to obtain the first integration module features before the experiment and the first integration module features after the experiment, where the formula is, ; ; in, represents the first integration module; FFN stands for Feed-Forward Neural Network; Represents repeated associative attention mechanisms; represents the first integrated module characteristics before the experiment; It represents the first integrated module characteristics after the experiment; The features of the first integration module before the experiment and the features of the first integration module after the experiment are input into the second integration module to obtain the high-level convolution features before the experiment and the high-level convolution features after the experiment, where the formula is, ; ; in, represents the second integration module; Represents the high-level convolution features before the experiment; Represents high-level convolutional features after experiments.

[0029] Based on the FPN strategy, the deeper features are gradually integrated into the shallow features to obtain the initial shallow features before the experiment and the initial shallow features after the experiment, where the formula is: ; ; in, Indicates feature fusion; Represents the list of features before the experiment; Represents the feature list after the experiment; represents the initial shallow characteristics before the experiment; Represents the initial shallow features after the experiment.

[0030] The initial shallow features before the experiment and the initial shallow features after the experiment are applied with adaptive average pooling to obtain the compressed features before the experiment and the compressed features after the experiment, where the formula is, ; ; in, Indicates feature fusion; Represents the list of features before the experiment; Represents the feature list after the experiment; Apply the fully connected layer to the pre-experimental compressed features and the post-experimental compressed features to obtain the pre-experimental feature vector and the post-experimental feature vector, where the formula is, ; ; in, represents a fully connected layer; represents the feature vector before the experiment; represents the post-experimental feature vector.

[0031] The similarity is calculated based on the eigenvector before and after the experiment. If the two are similar, the concrete specimen is the same before and after the experiment.

[0032] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a cloud platform-based engineering quality inspection and anti-fraud system. Figure 2 is a flowchart of a cloud platform-based engineering quality inspection and anti-fraud system according to an exemplary embodiment. Figure 2 As shown, a cloud platform-based engineering quality inspection and anti-fraud system in the present invention includes: Testing agency data analysis module: obtain the testing agency data, upload the testing agency data to the cloud platform, analyze the testing agency data online based on the cloud platform, and make dynamic adjustments based on the testing agency's performance in actual projects; Personnel database establishment module: Based on the cloud platform, a personnel database with corresponding qualification requirements is established for the testing agency, personnel information is registered and recorded, and photos of the testing personnel are input. During the inspection and testing of the project, the designated testing personnel are set from the personnel database, and dynamic scoring is adjusted according to the performance of the testing personnel in the project; Inspection data acquisition module: Based on drones and data sensors, it monitors and collects inspection behaviors and test block inspection data at the construction site in real time, and uploads the collected data to the cloud platform; Test data analysis module: cleans and mines the data uploaded to the cloud platform, extracts data features, mines and analyzes the data through heuristic algorithms and deep learning algorithms, identifies outliers and abnormal results in the data, and thus determines the standardization of the test behavior and the accuracy of the test block inspection data; Test report generation module: based on the test behavior and test block inspection data, it obtains the corresponding relevant data and generates a test report.

[0033] In order to achieve the above-mentioned purpose of the invention, the present invention also provides an electronic device, which includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the above-mentioned cloud platform-based engineering quality inspection and anti-fraud method is implemented.

[0034] In order to achieve the above-mentioned purpose of the invention, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned cloud platform-based engineering quality inspection and anti-fraud method is implemented.

[0035] Those of ordinary skill in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0036] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0037] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0038] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0039] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0040] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0041] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

[0042] It should be understood that the size of the serial numbers of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Claims

1. A cloud platform-based engineering quality inspection and detection anti-fraud method, characterized in that: include: Obtain the information of the testing agency, upload the information of the testing agency to the cloud platform, analyze the information of the testing agency online based on the cloud platform, and make dynamic adjustments based on the performance of the testing agency in the actual project; Based on the cloud platform, a personnel database with corresponding qualification requirements of the testing agency is established, personnel information is registered and recorded, and photos of the testing personnel are input. During the project testing process, designated testing personnel are set from the personnel database, and dynamic scoring is adjusted based on the performance of the testing personnel in the project; Based on drones and data sensors, real-time monitoring and collection of inspection behaviors and test block inspection data at the construction site are carried out, and the collected data are uploaded to the cloud platform; Clean and mine the data uploaded to the cloud platform, extract data features, mine and analyze the data through heuristic algorithms and deep learning algorithms, identify outliers and abnormal results in the data, and thus judge the standardization of the testing behavior and the accuracy of the test block inspection data; Based on the detection behavior and the test block inspection data, the corresponding relevant data is obtained and a test report is generated.

2. A cloud platform-based engineering quality inspection and detection anti-fraud method as claimed in claim 1, characterized in that: The online analysis of the data of the testing agency based on the cloud platform and the dynamic adjustment based on the performance of the testing agency in the actual project include: Based on the cloud platform, the data uploaded by testing institutions at all levels are obtained, and the uploaded data are reviewed and approved. The uploaded data are divided into ordinary files and important files. Ordinary files are management requirements files, quality control requirements files, credit system requirements files, risk prevention and control requirements files, sustainable development requirements files and agency award files. Important files are files related to violations. The scoring algorithm for the testing agency is set by weighted method, and the testing agency that has passed the data verification is evaluated based on the scoring algorithm. The comprehensive capability level of the testing agency is saved in the cloud platform, where the formula is,; ； in, Indicates the total score of the testing organization; Indicates the impact factor of important documents; Indicates the sum of 1-6 common files; Indicates the weight of the assessment index of common files; Indicates the score of the testing agency on the assessment indicators of general documents.

3. A cloud platform-based engineering quality inspection and detection anti-fraud method as claimed in claim 2, characterized in that: The online analysis of the data of the testing agency based on the cloud platform and the dynamic adjustment based on the performance of the testing agency in the actual project also include: The testing agency in the cloud platform updates the certification information every month. If it fails to do so, the cloud platform will suspend the testing agency's inspection of the construction and notify the contact person of the testing agency to supplement the information in a timely manner; In response to the supplement and modification of the testing agency's information, the testing agency will be re-evaluated based on the scoring algorithm and the corresponding level will be changed in the cloud platform; For lower-level testing agencies, the cloud platform will promptly issue early warnings to the testing agencies and send copies to the relevant project responsible parties to remind them of relevant risks.

4. A cloud platform-based engineering quality inspection and detection anti-fraud method as claimed in claim 3, characterized in that: Update the personnel database of the testing agency according to the latest adjustment of the testing personnel of the testing agency; During the inspection process, the camera uses the face recognition algorithm to identify the inspector in real time to confirm the inspector's authority; If the inspection personnel are detected to have performed operations beyond their authority, the cloud platform will automatically save the video of the inspection process, issue an early warning on the cloud platform, and notify the inspection agency, construction unit, and management unit; The level of the inspector is set as a suspicious person, the inspection task of the inspector is suspended, and the impact factor of the important files of the inspection agency is set to 0.

5. A cloud platform-based engineering quality inspection and detection anti-fraud method as claimed in claim 4, characterized in that: The real-time monitoring and collection of inspection behaviors and test block inspection data at the construction site based on drones and data sensors includes: Establish a video image management system for the testing process, and conduct real-time supervision and recording of testing behaviors by analyzing the image data of on-site testing; Use drones to film the inspection process of inspectors on site in real time, and record the location of inspection sampling according to the drone's positioning system. If the sampling location is inconsistent with the preset plan, the cloud platform automatically saves the illegal video and notifies the inspection agency, construction unit and management unit; The entire process of the specimen test is recorded using laboratory surveillance cameras and automatically saved on the cloud platform; The facial recognition system of the camera in the laboratory is used to monitor the authority of the inspectors. When the inspectors exceed their authority, the cloud platform automatically saves the video of the violation and notifies the inspection agency, construction unit and management unit.

6. A cloud platform-based engineering quality inspection and detection anti-fraud method as claimed in claim 5, characterized in that: The method for identifying outliers and abnormal results in data is: Mining and analyzing data through heuristic algorithms and deep learning algorithms to identify outliers and abnormal results in the data; The test value of the specimen is set to a. According to engineering experience, the test value of the specimen is b. According to the inspection and testing standards, the test value of the specimen is c. If satisfied and and and When , the test block inspection data is normal and can be included in the test value. Otherwise, the test value is an outlier and is an abnormal result. represents the j-th detection value, It represents the sum of all test values ​​of a parameter before the i-th test. Represents the i-th detection value.

7. A cloud platform-based engineering quality inspection and anti-fraud system, characterized in that: include: Testing agency data analysis module: obtain the testing agency data, upload the testing agency data to the cloud platform, analyze the testing agency data online based on the cloud platform, and make dynamic adjustments based on the testing agency's performance in actual projects; Personnel database establishment module: Based on the cloud platform, a personnel database with corresponding qualification requirements is established for the testing agency, personnel information is registered and recorded, and photos of the testing personnel are input. During the inspection and testing of the project, the designated testing personnel are set from the personnel database, and dynamic scoring is adjusted according to the performance of the testing personnel in the project; Inspection data acquisition module: Based on drones and data sensors, it monitors and collects inspection behaviors and test block inspection data at the construction site in real time, and uploads the collected data to the cloud platform; Test data analysis module: cleans and mines the data uploaded to the cloud platform, extracts data features, mines and analyzes the data through heuristic algorithms and deep learning algorithms, identifies outliers and abnormal results in the data, and thus determines the standardization of the test behavior and the accuracy of the test block inspection data; Test report generation module: based on the test behavior and test block inspection data, it obtains the corresponding relevant data and generates a test report.

8. An electronic device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements a cloud platform-based engineering quality inspection and anti-fraud method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements a cloud platform-based engineering quality inspection and anti-fraud method as described in any one of claims 1 to 6.

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