Intelligent inspection method and device based on job progress

Abstract

This invention discloses an intelligent acceptance method and apparatus based on work progress. The method includes: acquiring installation effect data of a target installation project, including installation effect image data and / or installation effect video data; analyzing the installation effect data to obtain the real-time installation status of the target installation project; and determining whether the target installation project meets the installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project. If so, the target installation project is determined to be completed. Therefore, this invention can determine the real-time installation status of an installation project based on its installation effect data (such as image data and / or video data), thereby enabling installation acceptance without requiring on-site inspection by personnel. This improves the intelligence and digitalization of installation acceptance, thereby increasing the efficiency and convenience of determining the installation project acceptance results.

Description

Technical Field

[0001] This invention relates to the field of intelligent acceptance technology, and in particular to an intelligent acceptance method and device based on work progress. Background Technology

[0002] With economic development and people's pursuit of a technologically advanced lifestyle, the demand for professional equipment installation is increasing. In practice, after installation is completed, personnel responsible for verifying the installation results must be assigned to the site to inspect the installation. However, experience shows that current methods of manually verifying installation results on-site consume significant manpower and resources, and result in long waiting times for users, leading to low efficiency. Therefore, providing a technical solution to improve the efficiency of equipment installation verification is crucial. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an intelligent acceptance method and device based on the progress of the work, which can improve the acceptance efficiency of equipment installation.

[0004] To address the aforementioned technical problems, the first aspect of this invention discloses an intelligent acceptance method based on work progress, the method comprising:

[0005] Acquire installation effect data for the target installation project. The installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to represent the work progress of the target installation project.

[0006] Analyze the installation effect data to obtain the real-time installation status corresponding to the target installation project;

[0007] Based on the real-time installation status and the predicted installation status corresponding to the target installation item, it is determined whether the target installation item meets the preset installation completion conditions. When the determination result is yes, it is determined that the target installation item has been installed.

[0008] As an optional implementation, in the first aspect of the present invention, analyzing the installation effect data to obtain the real-time installation status corresponding to the target installation project includes:

[0009] Based on the installation effect data and the set installation subject determination conditions, determine the target installation subject corresponding to the target installation item in the installation effect data;

[0010] Determine the basic installation status corresponding to the target installation body, and based on the basic installation status, the installation effect data, and the set external installation analysis conditions, determine at least one installation difference point between the target installation body and the basic installation status.

[0011] Determine whether the number of all the installation differences is greater than or equal to a preset threshold for the number of differences;

[0012] When it is determined that the number of all the installation difference points is greater than or equal to the difference point number threshold, the basic installation status, the installation effect data, and all the installation difference points are analyzed to obtain the real-time installation status corresponding to the target installation project.

[0013] As an optional implementation, in the first aspect of the present invention, determining whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project includes:

[0014] Based on the real-time installation status and the predicted installation status corresponding to the set target installation item, the corresponding installation similarity is determined;

[0015] Determine whether the installation similarity is greater than or equal to a preset installation similarity threshold;

[0016] When it is determined that the installation similarity is greater than or equal to the installation similarity threshold, the target installation project is determined to meet the preset installation completion conditions;

[0017] When the installation similarity is determined to be less than the installation similarity threshold, it is determined that the target installation project does not meet the installation completion conditions.

[0018] As an optional implementation, in the first aspect of the present invention, after obtaining the installation effect data of the target installation project, the method further includes:

[0019] Determine whether the installation effect data meets the preset data validity conditions;

[0020] When it is determined that the installation effect data meets the data validity conditions, the operation of analyzing the installation effect data to obtain the real-time installation status corresponding to the target installation project is executed.

[0021] And, the determination of whether the installation effect data meets the preset data validity conditions includes:

[0022] When the data validity conditions include data subject attribute conditions, the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project are determined; it is determined whether the first installation subject and the second installation subject match. If it is determined that the first installation subject and the second installation subject do not match, it is determined that the installation effect data does not meet the data validity conditions; if it is determined that the first installation subject and the second installation subject match, the target identifier corresponding to the first installation subject is determined according to the installation effect data; it is determined whether the target identifier meets the preset identifier conditions corresponding to the target installation project. If it is determined that the target identifier meets the identifier conditions, it is determined that the installation effect data meets the data validity conditions; if it is determined that the target identifier does not meet the identifier conditions, it is determined that the installation effect data does not meet the data validity conditions.

[0023] When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is determined whether the subject visibility is greater than or equal to a preset subject visibility threshold. If the determination result is yes, it is determined that the installation effect data meets the data validity condition; if the determination result is no, it is determined that the installation effect data does not meet the data validity condition.

[0024] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0025] When the installation similarity is determined to be greater than or equal to the installation similarity threshold, the evaluation feedback information corresponding to the target installation project is obtained. The evaluation feedback information corresponding to the target installation project includes the evaluation feedback information of the installer corresponding to the target installation project and / or the evaluation feedback information of the installation customer corresponding to the target installation project. The information type corresponding to the evaluation feedback information includes text description type and / or voice description type.

[0026] Analyze the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project;

[0027] Determine whether the real-time installation status matches the installation feedback status. If the determination result is yes, execute the operation of determining that the target installation project meets the preset installation completion conditions.

[0028] As an optional implementation, in the first aspect of the present invention, analyzing the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project includes:

[0029] Based on the evaluation feedback information and the set evaluation type analysis conditions, at least one evaluation feedback type corresponding to the target installation project is determined, and all evaluation feedback types are analyzed to obtain the corresponding evaluation feedback situation.

[0030] When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types conflict, the operation data of the associated installation entities corresponding to the target installation entity and the target installation project are obtained, and the installation feedback corresponding to the target installation project is determined based on the operation data, the evaluation feedback information and all the evaluation feedback types.

[0031] When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types do not conflict, the installation feedback corresponding to the target installation project is determined based on the evaluation feedback information and all the evaluation feedback types.

[0032] As an optional implementation, in the first aspect of the present invention, determining the installation feedback status corresponding to the target installation project based on the operating data, the evaluation feedback information, and all the evaluation feedback types includes:

[0033] Analyzing the operational data, the trend of stable usage changes corresponding to the target installation project is obtained;

[0034] Based on the trend of stable usage changes, determine the usage effect corresponding to the target installation project;

[0035] Based on the usage effect, at least one target evaluation feedback type is selected from all the evaluation feedback types, and target evaluation feedback information corresponding to all the target evaluation feedback types is selected from the evaluation feedback information;

[0036] Based on the usage effect and the target evaluation feedback information, determine the installation feedback status corresponding to the target installation project.

[0037] A second aspect of the present invention discloses an intelligent acceptance device based on work progress, the device comprising:

[0038] The acquisition module is used to acquire installation effect data of the target installation project. The installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to indicate the work progress of the target installation project.

[0039] The analysis module is used to analyze the installation effect data to obtain the real-time installation status corresponding to the target installation project;

[0040] The judgment module is used to determine whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project.

[0041] The determination module is used to determine that the target installation project is installed when the judgment module determines that the target installation project meets the installation completion conditions.

[0042] As an optional implementation, in the second aspect of the present invention, the method by which the analysis module analyzes the installation effect data to obtain the real-time installation status corresponding to the target installation project specifically includes:

[0043] Based on the installation effect data and the set installation subject determination conditions, determine the target installation subject corresponding to the target installation item in the installation effect data;

[0044] Determine the basic installation status corresponding to the target installation body, and based on the basic installation status, the installation effect data, and the set external installation analysis conditions, determine at least one installation difference point between the target installation body and the basic installation status.

[0045] Determine whether the number of all the installation differences is greater than or equal to a preset threshold for the number of differences;

[0046] When it is determined that the number of all the installation difference points is greater than or equal to the difference point number threshold, the basic installation status, the installation effect data, and all the installation difference points are analyzed to obtain the real-time installation status corresponding to the target installation project.

[0047] As an optional implementation, in a second aspect of the present invention, the method by which the determining module determines whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project specifically includes:

[0048] Based on the real-time installation status and the predicted installation status corresponding to the set target installation item, the corresponding installation similarity is determined;

[0049] Determine whether the installation similarity is greater than or equal to a preset installation similarity threshold;

[0050] When it is determined that the installation similarity is greater than or equal to the installation similarity threshold, the target installation project is determined to meet the preset installation completion conditions;

[0051] When it is determined that the installation similarity is less than the installation similarity threshold, it is determined that the target installation project does not meet the installation completion conditions.

[0052] As an optional implementation, in the second aspect of the present invention, the judgment module is further configured to, after the acquisition module acquires the installation effect data of the target installation project, determine whether the installation effect data meets the preset data validity conditions, and when the judgment result is yes, trigger the analysis module to perform the operation of analyzing the installation effect data to obtain the real-time installation status corresponding to the target installation project;

[0053] Furthermore, the specific methods by which the judgment module determines whether the installation effect data meets the preset data validity conditions include:

[0054] When the data validity conditions include data subject attribute conditions, the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project are determined; it is determined whether the first installation subject and the second installation subject match. If it is determined that the first installation subject and the second installation subject do not match, it is determined that the installation effect data does not meet the data validity conditions; if it is determined that the first installation subject and the second installation subject match, the target identifier corresponding to the first installation subject is determined according to the installation effect data; it is determined whether the target identifier meets the preset identifier conditions corresponding to the target installation project. If it is determined that the target identifier meets the identifier conditions, it is determined that the installation effect data meets the data validity conditions; if it is determined that the target identifier does not meet the identifier conditions, it is determined that the installation effect data does not meet the data validity conditions.

[0055] When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is then determined whether the subject visibility is greater than or equal to a preset subject visibility threshold. If the determination result is yes, the installation effect data is determined to meet the data validity condition; if the determination result is no, the installation effect data is determined not to meet the data validity condition.

[0056] As an optional implementation, in the second aspect of the present invention, the judgment module is further configured to, when it is determined that the installation similarity is greater than or equal to the installation similarity threshold, obtain evaluation feedback information corresponding to the target installation project, wherein the evaluation feedback information corresponding to the target installation project includes evaluation feedback information of the installer corresponding to the target installation project and / or evaluation feedback information of the installation customer corresponding to the target installation project; the information type corresponding to the evaluation feedback information includes text description type and / or voice description type; analyze the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project; determine whether the real-time installation status matches the installation feedback status, and when the determination result is yes, perform the operation of determining that the target installation project meets the preset installation completion conditions.

[0057] As an optional implementation, in the second aspect of the present invention, the method by which the judgment module analyzes the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project specifically includes:

[0058] Based on the evaluation feedback information and the set evaluation type analysis conditions, at least one evaluation feedback type corresponding to the target installation project is determined, and all evaluation feedback types are analyzed to obtain the corresponding evaluation feedback situation.

[0059] When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types conflict, the operation data of the associated installation entities corresponding to the target installation entity and the target installation project are obtained, and the installation feedback corresponding to the target installation project is determined based on the operation data, the evaluation feedback information and all the evaluation feedback types.

[0060] When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types do not conflict, the installation feedback corresponding to the target installation project is determined based on the evaluation feedback information and all the evaluation feedback types.

[0061] As an optional implementation, in a second aspect of the present invention, the method by which the determining module determines the installation feedback status corresponding to the target installation project based on the operating data, the evaluation feedback information, and all the evaluation feedback types specifically includes:

[0062] Analyzing the operational data, the trend of stable usage changes corresponding to the target installation project is obtained;

[0063] Based on the trend of stable usage changes, determine the usage effect corresponding to the target installation project;

[0064] Based on the usage effect, at least one target evaluation feedback type is selected from all the evaluation feedback types, and target evaluation feedback information corresponding to all the target evaluation feedback types is selected from the evaluation feedback information;

[0065] Based on the usage effect and the target evaluation feedback information, determine the installation feedback status corresponding to the target installation project.

[0066] A third aspect of the present invention discloses another intelligent acceptance device based on work progress, the device comprising:

[0067] Memory containing executable program code;

[0068] A processor coupled to the memory;

[0069] The processor calls the executable program code stored in the memory to execute the intelligent acceptance method based on work progress disclosed in the first aspect of the present invention.

[0070] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the intelligent acceptance method based on work progress disclosed in the first aspect of the present invention.

[0071] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0072] In this embodiment of the invention, installation effect data of a target installation project is acquired. This installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project, which represents the work progress of the target installation project. The installation effect data is analyzed to obtain the real-time installation status of the target installation project. Based on the real-time installation status and the predicted installation status corresponding to the target installation project, it is determined whether the target installation project meets the preset installation completion conditions. When the determination result is yes, the target installation project is determined to be completed. Therefore, this invention can determine the real-time installation status of an installation project based on its installation effect data (such as image data and / or video data), thereby enabling installation acceptance of the installation project. Acceptance personnel do not need to go to the site for acceptance, which is beneficial to improving the intelligence and electronic nature of installation acceptance, and thus improving the efficiency and convenience of determining the installation acceptance results, thereby improving the efficiency and convenience of installation project acceptance. Attached Figure Description

[0073] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0074] Figure 1 This is a flowchart illustrating an intelligent acceptance method based on work progress disclosed in an embodiment of the present invention;

[0075] Figure 2 This is a flowchart illustrating another intelligent acceptance method based on work progress disclosed in an embodiment of the present invention;

[0076] Figure 3 This is a schematic diagram of the structure of an intelligent acceptance device based on work progress disclosed in an embodiment of the present invention;

[0077] Figure 4 This is a schematic diagram of another intelligent acceptance device based on work progress disclosed in an embodiment of the present invention;

[0078] Figure 5 This is a schematic diagram of the structure of another intelligent acceptance device based on work progress disclosed in an embodiment of the present invention. Detailed Implementation

[0079] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0080] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0081] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0082] This invention discloses an intelligent acceptance method and device based on work progress. It can determine the real-time installation status of an installation project based on installation effect data (such as image data and / or video data), thereby enabling installation acceptance without requiring on-site personnel. This improves the intelligence and digitalization of installation acceptance, enhancing the efficiency and convenience of determining acceptance results. The following provides a detailed explanation.

[0083] Example 1

[0084] Please see Figure 1 , Figure 1This is a flowchart illustrating an intelligent acceptance method based on work progress disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to an intelligent acceptance device based on work progress. This device may include a server, which can be a local server or a cloud server; this embodiment of the invention is not limited to any particular server. Figure 1 As shown, this intelligent acceptance method based on work progress includes the following operations:

[0085] 101. Obtain the installation effect data of the target installation project. The installation effect data includes the installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to indicate the work progress of the target installation project.

[0086] Optionally, the installation effect data of the target installation project can be uploaded by the installation staff or by the installation customer; this embodiment of the invention does not impose any limitation.

[0087] 102. Analyze the installation effect data to obtain the real-time installation status of the target installation project.

[0088] 103. Based on the real-time installation status and the predicted installation status corresponding to the set target installation items, determine whether the target installation items meet the preset installation completion conditions.

[0089] Further optionally, when it is determined that the target installation project does not meet the installation completion conditions, an installation failure instruction is sent. This installation failure instruction is used to prompt the original installation personnel to reinstall the target installation project, or to prompt other installation personnel to install the target installation project, or to re-acquire and analyze the installation data to further verify whether the installation completion conditions are met. This embodiment of the invention is not limited to this.

[0090] Optionally, further verification can refer to personal attribute information that reflects the installation ability, such as the original installation staff's historical installation evaluations, historical installation records, personal installation level, and areas of expertise. It can also refer to personal attribute information that reflects the credibility of the installation customer's evaluation, such as the installation customer's historical installation needs data, information on the difference between historical installation evaluations and actual conditions, and the customer's installation attribute level. This embodiment of the invention does not limit this.

[0091] 104. When it is determined that the target installation item meets the installation completion conditions, the target installation item is confirmed to be installed.

[0092] As can be seen, the intelligent acceptance method based on work progress described in the embodiments of the present invention can determine the real-time installation status of the installation project based on the installation effect data (such as image data and / or video data), thereby realizing the installation acceptance of the installation project. The acceptance personnel do not need to go to the site for acceptance, which is conducive to improving the intelligence and electronic nature of the installation acceptance of the installation project, and thus improving the efficiency and convenience of determining the installation acceptance results of the installation project, thereby improving the acceptance efficiency and convenience of the installation project.

[0093] In an optional embodiment, the analysis of installation effect data to obtain the real-time installation status corresponding to the target installation project may include:

[0094] Based on the installation effect data and the set conditions for determining the installation subject, determine the target installation subject corresponding to the target installation item in the installation effect data;

[0095] Determine the basic installation conditions corresponding to the target installation body, and based on the basic installation conditions, installation effect data, and set external installation analysis conditions, determine at least one installation difference point between the target installation body and the basic installation conditions.

[0096] Determine whether the total number of all installation differences is greater than or equal to a preset threshold for the number of differences.

[0097] When it is determined that the number of all installation difference points is greater than or equal to the difference point number threshold, the basic installation status, installation effect data, and all installation difference points are analyzed to obtain the real-time installation status of the target installation project.

[0098] In the above optional embodiments, the method may further include the following operations:

[0099] When it is determined that the number of all installation difference points is less than the difference point number threshold, the functional information corresponding to all installation difference points is determined, and the functional importance of all installation difference points is determined based on the set installation key analysis conditions and the functional information corresponding to all installation difference points.

[0100] The system determines whether the importance of a function is greater than or equal to a preset threshold. If the determination is yes, it determines the real-time installation status of the target installation item based on the functional information, basic installation status, and installation effect data corresponding to all installation differences. If the determination is no, it determines the real-time installation status of the target installation item to indicate that the target installation item does not meet the installation completion conditions.

[0101] As can be seen, this optional embodiment can identify the installation differences between the installed and uninstalled states of the target installation project, and determine the real-time installation status of the target installation project based on these differences. This improves the comprehensiveness and rationality of the real-time installation status determination method, thereby enhancing the accuracy and reliability of the determined real-time installation status. Furthermore, the subsequent real-time installation status determination operation is only performed when the number of installation differences is greater than or equal to a threshold, which improves the efficiency, effectiveness, and applicability of the real-time installation status determination and reduces unnecessary resource waste. Additionally, it can provide a corresponding real-time installation status determination method for cases where the number of installation differences is less than a threshold. This method analyzes the functional status of the installation differences, and determines the real-time installation status based on a series of information when the functional importance is greater than or equal to a functional importance threshold. When the functional importance is less than the functional importance threshold, it directly determines that the target installation project does not meet the installation completion conditions. This improves the efficiency and convenience of determining the real-time installation status, thereby improving the efficiency and convenience of subsequent determinations of installation completion. Furthermore, it also improves the accuracy and reliability of the determined real-time installation status.

[0102] In another optional embodiment, the above-mentioned determination of whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the set target installation project may include:

[0103] Based on the real-time installation status and the predicted installation status corresponding to the set target installation items, the corresponding installation similarity is determined;

[0104] Determine whether the installation similarity is greater than or equal to the preset installation similarity threshold;

[0105] When the installation similarity is determined to be greater than or equal to the installation similarity threshold, the target installation project is determined to meet the preset installation completion conditions.

[0106] When the installation similarity is determined to be less than the installation similarity threshold, it is determined that the target installation project does not meet the installation completion conditions.

[0107] As can be seen, this optional embodiment can determine the installation similarity corresponding to the target installation project, and determine whether the target installation project meets the installation completion conditions based on the comparison between the installation similarity and the installation similarity threshold. This is beneficial to improving the rationality and comprehensiveness of the method for determining the installation completion conditions, thereby improving the accuracy and reliability of the determined installation completion condition satisfaction results, as well as improving the efficiency and convenience of determining the installation completion condition satisfaction results.

[0108] In yet another alternative embodiment, the method may further include the following operations:

[0109] When the installation similarity is determined to be greater than or equal to the installation similarity threshold, the evaluation feedback information corresponding to the target installation project is obtained. The evaluation feedback information corresponding to the target installation project includes the evaluation feedback information of the installer corresponding to the target installation project and / or the evaluation feedback information of the installation customer corresponding to the target installation project; the information type of the evaluation feedback information includes text description type and / or voice description type.

[0110] Analyze and evaluate the feedback information to obtain the installation feedback status corresponding to the target installation project;

[0111] Determine whether the real-time installation status matches the installation feedback status. If the determination result is yes, execute the above operation to determine whether the target installation item meets the preset installation completion conditions.

[0112] Alternatively, if it is determined that the real-time installation status does not match the installation feedback status, it can be determined that the target installation project does not meet the conditions for installation completion.

[0113] As can be seen, this optional embodiment can, for cases where the installation similarity is greater than or equal to the installation similarity threshold, further determine whether the real-time installation status matches the installation feedback status by combining the evaluation feedback information of the target installation project. If so, it will execute the subsequent operation of determining whether the target installation project meets the installation conditions. This provides an installation evaluation feedback function, enriches the factors to consider in determining the installation conditions, and helps to improve the comprehensiveness, rationality, and intelligence of the method for determining the installation conditions, thereby improving the reliability and accuracy of the determined installation conditions.

[0114] In another optional embodiment, the above analysis and evaluation of feedback information to obtain the installation feedback status corresponding to the target installation project may include:

[0115] Based on the evaluation feedback information and the set evaluation type analysis conditions, determine at least one evaluation feedback type corresponding to the target installation project, and analyze all evaluation feedback types to obtain the corresponding evaluation feedback situation.

[0116] When the evaluation feedback is used to indicate that the installation effect corresponding to all evaluation feedback types conflicts, the operation data of the associated installation entity corresponding to the target installation entity and the target installation project is obtained, and the installation feedback corresponding to the target installation project is determined based on the operation data, evaluation feedback information and all evaluation feedback types.

[0117] When the evaluation feedback is used to indicate that the installation effects corresponding to all evaluation feedback types do not conflict, the installation feedback corresponding to the target installation project is determined based on the evaluation feedback information and all evaluation feedback types.

[0118] Optionally, the above evaluation feedback is used to indicate conflicts in the installation effect corresponding to all evaluation feedback types. For example, the installation staff may report that the installation is secure while the customer reports that the installation is not secure. Examples are not listed here.

[0119] As can be seen, this optional embodiment can provide a corresponding method for determining installation feedback when the evaluation feedback indicates that all installation effects conflict or that all installation effects do not conflict. It introduces the operation data corresponding to the installation project to analyze the installation effect, which helps to improve the comprehensiveness, rationality and intelligence of the method for determining installation feedback. This, in turn, helps to improve the diversity and pertinence of the method for determining installation feedback, thereby improving the efficiency and convenience of determining installation feedback, as well as the accuracy and reliability of the determined installation feedback.

[0120] In yet another optional embodiment, determining the installation feedback status corresponding to the target installation project based on operational data, evaluation feedback information, and all evaluation feedback types may include:

[0121] Analyze the operational data to obtain the trend of stable usage changes for the target installation project;

[0122] Based on the trend of stable usage changes, determine the corresponding usage effect of the target installation project;

[0123] Based on the usage effect, at least one target evaluation feedback type is selected from all evaluation feedback types, and target evaluation feedback information corresponding to all target evaluation feedback types is selected from the evaluation feedback information.

[0124] Based on the usage results and target evaluation feedback, determine the installation feedback for the target installation project.

[0125] As can be seen, this optional embodiment can analyze the operational data of the target installation project to obtain the usage effect of the target installation project, filter the target evaluation feedback information based on the usage effect, and then determine the final installation feedback situation. This helps to improve the comprehensiveness and rationality of the method for determining the installation feedback situation. In addition, by selectively filtering a large amount of evaluation feedback information based on the usage effect and using the filtered evaluation feedback information to determine the situation, the occurrence of malicious feedback on the installation situation is effectively reduced. This helps to improve the efficiency and convenience of determining the installation feedback situation, as well as the accuracy and reliability of the determined installation feedback situation.

[0126] Example 2

[0127] Please see Figure 2 , Figure 2 This is a flowchart illustrating another intelligent acceptance method based on work progress disclosed in an embodiment of the present invention. Figure 2 The described method can be applied to an intelligent acceptance device based on work progress. This device may include a server, which can be a local server or a cloud server; this embodiment of the invention is not limited to any particular server. Figure 2 As shown, this intelligent acceptance method based on work progress includes the following operations:

[0128] 201. Obtain the installation effect data of the target installation project. The installation effect data includes the installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to indicate the work progress of the target installation project.

[0129] 202. Determine whether the installation effect data meets the preset data validity conditions.

[0130] Optionally, when it is determined that the installation effect data does not meet the data validity conditions, new installation effect data corresponding to the target installation project is obtained according to the set data analysis conditions, and the installation effect data is updated; the operation of analyzing the installation effect data is performed to obtain the real-time installation status corresponding to the target installation project is executed.

[0131] Optionally, the above-mentioned updating of installation effect data may involve adding the new installation effect data to the installation effect data of the target installation project, or replacing the installation effect data of the target installation project with the new installation effect data. This embodiment of the invention does not limit the scope of the invention.

[0132] 203. When it is determined that the installation effect data meets the data validity conditions, analyze the installation effect data to obtain the real-time installation status corresponding to the target installation project.

[0133] 204. Based on the real-time installation status and the predicted installation status corresponding to the set target installation items, determine whether the target installation items meet the preset installation completion conditions.

[0134] 205. When it is determined that the target installation item meets the installation completion conditions, the target installation item is confirmed to be installed.

[0135] In this embodiment of the invention, for other descriptions of steps 201 and 203-205, please refer to the other detailed descriptions of steps 101-104 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0136] As can be seen, the embodiments of the present invention can determine the real-time installation status of an installation project based on installation effect data (such as image data and / or video data), thereby enabling installation acceptance without requiring on-site inspection personnel. This improves the intelligence and digitalization of installation acceptance, thereby increasing the efficiency and convenience of determining the installation acceptance results. Furthermore, the invention can also determine the compliance of the installation effect data in terms of form and content. Subsequent installation project acceptance operations based on the installation effect data are only performed when the data meets the data validity conditions. This provides a method for determining data compliance, enriches the intelligent functions, and improves the accuracy and reliability of the installation project acceptance results determined based on the installation effect data. It also improves the efficiency and convenience of determining the installation project acceptance results to a certain extent, thereby improving the accuracy and efficiency of the installation project acceptance.

[0137] In an optional embodiment, determining whether the installation effect data meets preset data validity conditions may include:

[0138] When the data validity conditions include data subject attribute conditions, determine the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project; determine whether the first installation subject and the second installation subject match; if the first installation subject and the second installation subject do not match, determine that the installation effect data does not meet the data validity conditions; if the first installation subject and the second installation subject match, determine the target identifier corresponding to the first installation subject based on the installation effect data; determine whether the target identifier meets the preset identifier conditions corresponding to the target installation project; if the target identifier meets the identifier conditions, determine that the installation effect data meets the data validity conditions; if the target identifier does not meet the identifier conditions, determine that the installation effect data does not meet the data validity conditions.

[0139] When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is then determined whether the subject visibility is greater than or equal to the preset subject visibility threshold. If the determination result is yes, the installation effect data is determined to meet the data validity condition; if the determination result is no, the installation effect data is determined not to meet the data validity condition.

[0140] Optionally, the data subject attribute condition can be understood as whether the installation object in the installation effect data matches the target object. For example, if the installation object in the installation effect data is a window, but the actual installation project object is a door, then the installation subjects do not match. The same applies to other installation subjects, and examples will not be given here.

[0141] Optionally, the subject visibility condition can be understood as whether the image or video has sufficiently high pixels, is blurry, or is sufficiently clear, etc., and this embodiment of the invention does not limit it.

[0142] As can be seen, this optional embodiment can provide corresponding methods for determining the data validity conditions for two situations, including data subject attribute conditions and / or subject visibility conditions. This is beneficial to improving the diversity and flexibility of the methods for determining the data validity conditions, as well as the comprehensiveness and rationality of the methods for determining the data validity conditions. In turn, it is beneficial to improve the accuracy, reliability, efficiency, and convenience of the determined results of the data validity condition determination.

[0143] Example 3

[0144] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an intelligent acceptance device based on work progress, as disclosed in an embodiment of the present invention. Figure 3 The described apparatus may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the intelligent acceptance device based on work progress may include:

[0145] The acquisition module 301 is used to acquire installation effect data of the target installation project. The installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to represent the work progress of the target installation project.

[0146] Analysis module 302 is used to analyze installation effect data and obtain the real-time installation status of the target installation project.

[0147] The judgment module 303 is used to determine whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the set target installation project.

[0148] The determination module 304 is used to determine that the target installation project is installed when the judgment module 303 determines that the target installation project meets the installation completion conditions.

[0149] It is evident that implementation Figure 3The intelligent acceptance device based on work progress described herein can determine the real-time installation status of an installation project based on installation effect data (such as image data and / or video data), thereby enabling the acceptance of the installation project without requiring on-site personnel. This improves the intelligence and digitalization of installation project acceptance, thereby increasing the efficiency and convenience of determining the installation project acceptance results.

[0150] In an optional embodiment, the analysis module 302 analyzes the installation effect data to obtain the real-time installation status corresponding to the target installation project, specifically including the following methods:

[0151] Based on the installation effect data and the set conditions for determining the installation subject, determine the target installation subject corresponding to the target installation item in the installation effect data;

[0152] Determine the basic installation conditions corresponding to the target installation body, and based on the basic installation conditions, installation effect data, and set external installation analysis conditions, determine at least one installation difference point between the target installation body and the basic installation conditions.

[0153] Determine whether the total number of all installation differences is greater than or equal to a preset threshold for the number of differences.

[0154] When it is determined that the number of all installation difference points is greater than or equal to the difference point number threshold, the basic installation status, installation effect data, and all installation difference points are analyzed to obtain the real-time installation status of the target installation project.

[0155] It is evident that implementation Figure 4 The described device can determine the installation differences between the installed state and the pending state of a target installation item, and determine the real-time installation status of the target installation item based on the installation differences. This helps to improve the comprehensiveness and rationality of the real-time installation status determination method, thereby improving the accuracy and reliability of the determined real-time installation status. In addition, the subsequent real-time installation status determination operation is only performed when the number of installation differences is greater than or equal to a threshold, which helps to improve the efficiency, effectiveness and applicability of the real-time installation status determination, and reduce unnecessary waste of resources.

[0156] In another optional embodiment, the determination module 303 determines whether the target installation item meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the set target installation item. The specific methods include:

[0157] Based on the real-time installation status and the predicted installation status corresponding to the set target installation items, the corresponding installation similarity is determined;

[0158] Determine whether the installation similarity is greater than or equal to the preset installation similarity threshold;

[0159] When the installation similarity is determined to be greater than or equal to the installation similarity threshold, the target installation project is determined to meet the preset installation completion conditions.

[0160] When the installation similarity is determined to be less than the installation similarity threshold, it is determined that the target installation project does not meet the installation completion conditions.

[0161] It is evident that implementation Figure 4 The described device can also determine the installation similarity corresponding to the target installation project, and determine whether the target installation project meets the installation completion conditions based on the comparison between the installation similarity and the installation similarity threshold. This helps to improve the rationality and comprehensiveness of the method for determining the installation completion conditions, thereby improving the accuracy and reliability of the determined installation completion condition satisfaction results, as well as improving the efficiency and convenience of determining the installation completion condition satisfaction results.

[0162] In another optional embodiment, the judgment module 303 is further configured to determine whether the installation effect data meets the preset data validity conditions after the acquisition module 301 acquires the installation effect data of the target installation project. When the judgment result is yes, the analysis module 302 is triggered to perform the above-mentioned analysis of the installation effect data to obtain the real-time installation status corresponding to the target installation project.

[0163] Furthermore, the specific methods by which the judgment module 303 determines whether the installation effect data meets the preset data validity conditions include:

[0164] When the data validity conditions include data subject attribute conditions, determine the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project; determine whether the first installation subject and the second installation subject match; if the first installation subject and the second installation subject do not match, determine that the installation effect data does not meet the data validity conditions; if the first installation subject and the second installation subject match, determine the target identifier corresponding to the first installation subject based on the installation effect data; determine whether the target identifier meets the preset identifier conditions corresponding to the target installation project; if the target identifier meets the identifier conditions, determine that the installation effect data meets the data validity conditions; if the target identifier does not meet the identifier conditions, determine that the installation effect data does not meet the data validity conditions.

[0165] When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is then determined whether the subject visibility is greater than or equal to the preset subject visibility threshold. If the determination result is yes, the installation effect data is determined to meet the data validity condition; if the determination result is no, the installation effect data is determined not to meet the data validity condition.

[0166] It is evident that implementation Figure 4 The described device can also determine the compliance of installation effect data in terms of both form and content. Only when the installation effect data meets the data validity conditions will subsequent installation project acceptance operations based on the installation effect data be performed. This provides a method for determining data compliance, enriches intelligent functions, and helps improve the accuracy and reliability of installation project acceptance results determined based on installation effect data. It also helps improve the efficiency and convenience of determining installation project acceptance results to a certain extent, thereby improving the accuracy and efficiency of installation project acceptance. Furthermore, it can provide corresponding methods for determining compliance with data validity conditions, including data subject attribute conditions and / or subject visibility conditions. This helps improve the diversity and flexibility of methods for determining compliance with data validity conditions, as well as their comprehensiveness and rationality, thereby improving the accuracy, reliability, efficiency, and convenience of the determined data validity condition results.

[0167] In another optional embodiment, the judgment module 303 is further configured to, when the installation similarity is determined to be greater than or equal to the installation similarity threshold, obtain the evaluation feedback information corresponding to the target installation project, the evaluation feedback information corresponding to the target installation project includes the evaluation feedback information of the installer corresponding to the target installation project and / or the evaluation feedback information of the installation customer corresponding to the target installation project; the information type corresponding to the evaluation feedback information includes text description type and / or voice description type; analyze the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project; determine whether the real-time installation status matches the installation feedback status, and when the determination result is yes, perform the above-mentioned operation of determining that the target installation project meets the preset installation completion conditions.

[0168] It is evident that implementation Figure 4 The described device can also, for cases where the installation similarity is greater than or equal to the installation similarity threshold, further determine whether the real-time installation status matches the installation feedback status by combining the evaluation feedback information of the target installation project. If so, it will execute the subsequent operation of determining whether the target installation project meets the installation conditions. This provides an installation evaluation feedback function, enriches the factors to consider in determining the installation conditions, and helps to improve the comprehensiveness, rationality, and intelligence of the method for determining the installation conditions, thereby improving the reliability and accuracy of the determined installation conditions.

[0169] In another optional embodiment, the method by which the judgment module 303 analyzes and evaluates the feedback information to obtain the installation feedback status corresponding to the target installation project specifically includes:

[0170] Based on the evaluation feedback information and the set evaluation type analysis conditions, determine at least one evaluation feedback type corresponding to the target installation project, and analyze all evaluation feedback types to obtain the corresponding evaluation feedback situation.

[0171] When the evaluation feedback is used to indicate that the installation effect corresponding to all evaluation feedback types conflicts, the operation data of the associated installation entity corresponding to the target installation entity and the target installation project is obtained, and the installation feedback corresponding to the target installation project is determined based on the operation data, evaluation feedback information and all evaluation feedback types.

[0172] When the evaluation feedback is used to indicate that the installation effects corresponding to all evaluation feedback types do not conflict, the installation feedback corresponding to the target installation project is determined based on the evaluation feedback information and all evaluation feedback types.

[0173] It is evident that implementation Figure 4 The described device can also provide a corresponding method for determining installation feedback in cases where all installation effects conflict or do not conflict. It introduces operational data corresponding to the installation project to analyze the installation effect, which helps to improve the comprehensiveness, rationality and intelligence of the method for determining installation feedback. This, in turn, helps to improve the diversity and pertinence of the method for determining installation feedback, thereby improving the efficiency and convenience of determining installation feedback, as well as the accuracy and reliability of the determined installation feedback.

[0174] In another optional embodiment, the determination module 303 determines the installation feedback status corresponding to the target installation project based on the running data, evaluation feedback information, and all evaluation feedback types in the following specific ways:

[0175] Analyze the operational data to obtain the trend of stable usage changes for the target installation project;

[0176] Based on the trend of stable usage changes, determine the corresponding usage effect of the target installation project;

[0177] Based on the usage effect, at least one target evaluation feedback type is selected from all evaluation feedback types, and target evaluation feedback information corresponding to all target evaluation feedback types is selected from the evaluation feedback information.

[0178] Based on the usage results and target evaluation feedback, determine the installation feedback for the target installation project.

[0179] It is evident that implementation Figure 4The described device can also analyze the operational data of the target installation project to obtain the usage effect of the target installation project, filter the target evaluation feedback information based on the usage effect, and then determine the final installation feedback status. This helps to improve the comprehensiveness and rationality of the method for determining the installation feedback status. In addition, by selectively filtering a large amount of evaluation feedback information based on the usage effect and using the filtered evaluation feedback information to determine the status, the occurrence of malicious feedback on the installation status is effectively reduced. This helps to improve the efficiency and convenience of determining the installation feedback status, as well as the accuracy and reliability of the determined installation feedback status.

[0180] Example 4

[0181] Please see Figure 5 , Figure 5 This is a structural schematic diagram of another intelligent acceptance device based on work progress disclosed in an embodiment of the present invention. Figure 5 The described apparatus may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 5 As shown, the device may include:

[0182] Memory 401 storing executable program code;

[0183] Processor 402 coupled to memory 401;

[0184] Furthermore, it may also include an input interface 403 coupled to the processor 402 and an output interface 404;

[0185] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the intelligent acceptance method based on the work progress described in Embodiment 1 or Embodiment 2.

[0186] Example 5

[0187] This invention discloses a computer storage medium that stores a computer program for electronic data interchange, wherein the computer program causes a computer to execute the steps in the intelligent acceptance method based on work progress described in Embodiment 1 or Embodiment 2.

[0188] Example 6

[0189] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the intelligent acceptance method based on work progress described in Embodiment 1 or Embodiment 2.

[0190] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0191] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0192] Finally, it should be noted that the intelligent acceptance method and device based on work progress disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent acceptance method based on work progress, characterized in that, The method includes: Acquire installation effect data for the target installation project. The installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to indicate the work progress of the target installation project. The installation effect data is uploaded by installation staff and / or installation customers. Determine whether the installation effect data meets the preset data validity conditions; When it is determined that the installation effect data meets the data validity conditions, the installation effect data is analyzed to obtain the real-time installation status corresponding to the target installation project. Based on the real-time installation status and the predicted installation status corresponding to the target installation item, determine whether the target installation item meets the preset installation completion conditions; When it is determined that the target installation item meets the installation completion conditions, the target installation item is determined to be installed successfully. When it is determined that the target installation project does not meet the installation completion conditions, an installation failure instruction is sent. This instruction is used to reacquire and analyze installation data to further verify the fulfillment of the installation completion conditions. This further verification specifically includes verification through one or more of the following: the original installation worker's historical installation evaluation, historical installation status, personal installation level, personal areas of expertise, and other personal attribute information that can reflect installation capabilities; and / or verification through one or more of the installation customer's historical installation demand data, information on the difference between historical installation evaluations and actual conditions, customer installation attribute level, and other personal attribute information that can reflect the credibility of the installation customer's evaluation. And, the determination of whether the installation effect data meets the preset data validity conditions includes: When the data validity conditions include data subject attribute conditions, determine the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project; determine whether the first installation subject and the second installation subject match; when it is determined that the first installation subject and the second installation subject match, determine the target identifier corresponding to the first installation subject based on the installation effect data; determine whether the target identifier meets the preset identifier conditions corresponding to the target installation project; when it is determined that the target identifier meets the identifier conditions, determine that the installation effect data meets the data validity conditions. When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is determined whether the subject visibility is greater than or equal to a preset subject visibility threshold; when it is determined that the subject visibility is greater than or equal to the subject visibility threshold, it is determined that the installation effect data meets the data validity condition.

2. The intelligent acceptance method based on work progress according to claim 1, characterized in that, The analysis of the installation effect data yields the real-time installation status corresponding to the target installation project, including: Based on the installation effect data and the set installation subject determination conditions, determine the target installation subject corresponding to the target installation item in the installation effect data; Determine the basic installation status corresponding to the target installation body, and based on the basic installation status, the installation effect data, and the set external installation analysis conditions, determine at least one installation difference point between the target installation body and the basic installation status. Determine whether the number of all the installation differences is greater than or equal to a preset threshold for the number of differences; When it is determined that the number of all the installation difference points is greater than or equal to the difference point number threshold, the basic installation status, the installation effect data, and all the installation difference points are analyzed to obtain the real-time installation status corresponding to the target installation project.

3. The intelligent acceptance method based on work progress according to claim 2, characterized in that, The step of determining whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project includes: Based on the real-time installation status and the predicted installation status corresponding to the set target installation item, the corresponding installation similarity is determined; Determine whether the installation similarity is greater than or equal to a preset installation similarity threshold; When it is determined that the installation similarity is greater than or equal to the installation similarity threshold, the target installation project is determined to meet the preset installation completion conditions; When the installation similarity is determined to be less than the installation similarity threshold, it is determined that the target installation project does not meet the installation completion conditions.

4. The intelligent acceptance method based on work progress according to claim 3, characterized in that, The method further includes: When it is determined that the first installation body and the second installation body are not compatible, it is determined that the installation effect data does not meet the data validity conditions; When it is determined that the target identifier does not meet the identifier condition, it is determined that the installation effect data does not meet the data validity condition; When it is determined that the visibility of the subject is less than the subject visibility threshold, it is determined that the installation effect data does not meet the data validity condition.

5. The intelligent acceptance method based on work progress according to claim 4, characterized in that, The method further includes: When the installation similarity is determined to be greater than or equal to the installation similarity threshold, the evaluation feedback information corresponding to the target installation project is obtained. The evaluation feedback information corresponding to the target installation project includes the evaluation feedback information of the installer corresponding to the target installation project and / or the evaluation feedback information of the installation customer corresponding to the target installation project. The information type corresponding to the evaluation feedback information includes text description type and / or voice description type. Analyze the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project; Determine whether the real-time installation status matches the installation feedback status. If the determination result is yes, execute the operation of determining that the target installation project meets the preset installation completion conditions.

6. The intelligent acceptance method based on work progress according to claim 5, characterized in that, The analysis of the evaluation feedback information to obtain the installation feedback status corresponding to the target installation project includes: Based on the evaluation feedback information and the set evaluation type analysis conditions, at least one evaluation feedback type corresponding to the target installation project is determined, and all evaluation feedback types are analyzed to obtain the corresponding evaluation feedback situation. When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types conflict, the operation data of the associated installation entities corresponding to the target installation entity and the target installation project are obtained, and the installation feedback corresponding to the target installation project is determined based on the operation data, the evaluation feedback information and all the evaluation feedback types. When the evaluation feedback indicates that the installation effects corresponding to all the evaluation feedback types do not conflict, the installation feedback corresponding to the target installation project is determined based on the evaluation feedback information and all the evaluation feedback types.

7. The intelligent acceptance method based on work progress according to claim 6, characterized in that, The step of determining the installation feedback status corresponding to the target installation project based on the operational data, the evaluation feedback information, and all the evaluation feedback types includes: Analyzing the operational data, the trend of stable usage changes corresponding to the target installation project is obtained; Based on the trend of stable usage changes, determine the usage effect corresponding to the target installation project; Based on the usage effect, at least one target evaluation feedback type is selected from all the evaluation feedback types, and target evaluation feedback information corresponding to all the target evaluation feedback types is selected from the evaluation feedback information; Based on the usage effect and the target evaluation feedback information, determine the installation feedback status corresponding to the target installation project.

8. An intelligent acceptance device based on work progress, characterized in that, The device includes: The acquisition module is used to acquire installation effect data of the target installation project. The installation effect data includes installation effect image data and / or installation effect video data corresponding to the target installation project. The installation effect data is used to indicate the work progress of the target installation project. The installation effect data is uploaded by installation staff and / or installation customers. The judgment module is used to determine whether the installation effect data meets the preset data validity conditions; The analysis module is used to analyze the installation effect data and obtain the real-time installation status corresponding to the target installation project when the judgment module determines that the installation effect data meets the data validity conditions. The judgment module is also used to determine whether the target installation project meets the preset installation completion conditions based on the real-time installation status and the predicted installation status corresponding to the target installation project. The determining module is used to determine that the target installation project is installed when the judging module determines that the target installation project meets the installation completion conditions; The determining module is further configured to send an installation failure instruction when the judging module determines that the target installation project does not meet the installation completion conditions. This installation failure instruction is used to re-acquire and analyze the installation data to further verify the fulfillment of the installation completion conditions. The further verification specifically includes verification through one or more of the following: the original installation staff's historical installation evaluation, historical installation status, personal installation level, personal areas of expertise, and other personal attribute information that can reflect installation capabilities; and / or verification through one or more of the installation customer's historical installation demand data, historical installation evaluation and actual situation difference information, customer installation attribute level, and other personal attribute information that can reflect the credibility of the installation customer's evaluation. Furthermore, the specific methods by which the judgment module determines whether the installation effect data meets the preset data validity conditions include: When the data validity conditions include data subject attribute conditions, determine the first installation subject corresponding to the installation effect data and the second installation subject corresponding to the target installation project; determine whether the first installation subject and the second installation subject match; when it is determined that the first installation subject and the second installation subject match, determine the target identifier corresponding to the first installation subject based on the installation effect data; determine whether the target identifier meets the preset identifier conditions corresponding to the target installation project; when it is determined that the target identifier meets the identifier conditions, determine that the installation effect data meets the data validity conditions. When the data validity condition includes the subject visibility condition, the corresponding subject visibility is determined based on the installation effect data; it is determined whether the subject visibility is greater than or equal to a preset subject visibility threshold; when it is determined that the subject visibility is greater than or equal to the subject visibility threshold, it is determined that the installation effect data meets the data validity condition.

9. An intelligent acceptance device based on work progress, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent acceptance method based on the work progress as described in any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the intelligent acceptance method based on work progress as described in any one of claims 1-7.

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