Elevator on-demand priority maintenance and effect evaluation method, device, equipment and system based on artificial intelligence

Abstract

The system comprises a data acquisition module, an operation and maintenance personnel qualification classification module, a fault category and grade division module, a fault and operation and maintenance personnel matching module, an operation and maintenance personnel identity verification module, a maintenance result uploading module and an effect evaluation module. The data acquisition module, the operation and maintenance personnel qualification classification module, the fault category and grade division module, the fault and operation and maintenance personnel matching module, the operation and maintenance personnel identity verification module, the maintenance result uploading module and the effect evaluation module are in communication connection in sequence; according to the elevator on-demand priority maintenance and effect evaluation method, device, equipment and system based on artificial intelligence, elevator fault data and operation and maintenance personnel data are collected, and classification, fault grade division and operation and maintenance personnel qualification division are performed on elevators, so that elevator faults can be quickly responded, and the operation and maintenance efficiency is improved. And the elevator maintenance process is more standard, and the elevator can be conveniently maintained.

Description

Technical Field

[0001] The present invention belongs to the technical field of elevator maintenance, and specifically relates to a method, device, equipment and system for on-demand priority maintenance and effect evaluation of elevators based on artificial intelligence. Background Art

[0002] As a vertical transportation tool, elevators play a vital role in people's daily life and work. However, the traditional elevator maintenance model has gradually exposed many problems and is unable to meet the growing demand.

[0003] When a problem occurs in an elevator, it is usually necessary to manually contact the operation and maintenance personnel to come for repair. This method not only cannot guarantee the efficiency of elevator maintenance, but also cannot guarantee that the maintenance personnel can quickly obtain the factors of the elevator failure. It also cannot guarantee that the operation and maintenance personnel who come for repair are qualified for maintenance. Operation and maintenance personnel without maintenance qualifications will increase the number of unexpected situations during the maintenance process of the elevator. Therefore, a method, device, equipment and system for on-demand priority maintenance and effect evaluation of elevators based on artificial intelligence are proposed. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a method, device, equipment and system for on-demand priority maintenance and effect evaluation of elevators based on artificial intelligence, so that elevator failures can be handled quickly and conveniently.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An on-demand priority maintenance and effect evaluation system for elevators based on artificial intelligence, comprising a data acquisition module, an operation and maintenance personnel qualification classification module, a fault category and level classification module, a fault and operation and maintenance personnel matching module, an operation and maintenance personnel identity authentication module, a maintenance result upload module, and an effect evaluation module, wherein the data acquisition module, the operation and maintenance personnel qualification classification module, the fault category and level classification module, the fault and operation and maintenance personnel matching module, the operation and maintenance personnel identity authentication module, the maintenance result upload module, and the effect evaluation module are sequentially connected in communication;

[0007] The data collection module is used to collect relevant data of operation and maintenance personnel and elevator fault data;

[0008] The fault category and level classification module is used to classify the collected elevator fault data into categories and levels;

[0009] The operation and maintenance personnel qualification classification module classifies the collected operation and maintenance personnel data by qualifications and experience;

[0010] The fault and operation and maintenance personnel matching module performs business matching based on the known elevator data and operation and maintenance personnel data;

[0011] The operator identity verification module is used to verify the operator identity information and ensure that the elevator is maintained by the assigned operator.

[0012] The maintenance result uploading module is used to receive the fault data and maintenance data uploaded by the operation and maintenance personnel;

[0013] The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effects of maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report.

[0014] Furthermore, the data collection module is used to collect relevant data of operation and maintenance personnel and elevator fault data processing process as follows:

[0015] The data collected about operation and maintenance personnel include the qualification information, identity information and location information of operation and maintenance personnel. The qualification information of operation and maintenance personnel includes professional certificates, training records and qualification certifications. The identity information of operation and maintenance personnel includes name, work number, contact information and department. The location information of operation and maintenance personnel is the location information of the current operation and maintenance personnel, and the location information is tracked through RFID technology.

[0016] When receiving information about elevator failure, the location information of the operation and maintenance personnel will be collected to facilitate quick retrieval of the nearest operation and maintenance personnel;

[0017] The collected elevator fault data include running speed, load condition, door opening and closing status, travel data, internal camera device data, historical operation data, and historical operation data including historical fault records.

[0018] Furthermore, the fault category and level classification module performs the following classification and level classification processing on the collected elevator fault data:

[0019] According to the collected elevator data, the elevator categories are divided into traction elevators, hydraulic elevators, machine room-less elevators, and home elevators;

[0020] When an elevator breaks down, accurate classification can help match the corresponding professional operation and maintenance personnel and also make it easier for subsequent operation and maintenance personnel to quickly determine the cause of the failure.

[0021] Process the collected running speed, load condition, door opening and closing status, and camera device data to determine the elevator fault level;

[0022] Perform image processing on the data collected by the camera device to determine the situation of people inside the elevator. When it is identified that there are trapped people inside the elevator, the fault is directly classified as a high fault level;

[0023] The collected running speed, load condition, and door opening and closing status data are calculated, and the fault index threshold range is preset. The fault level is determined based on the specific value obtained. The specific formula is:

[0024] T1+T2=T3;

[0025]

[0026] T3∈T4, T3=0;

[0027] Among them, T1 is the door opening time, T2 is the door closing time, T3 is the total door opening and closing time, and T4 is the normal door opening and closing time range. When T3 exceeds T4, the value of T3 is 1, and when T3 belongs to T4, the value of T3 is 0;

[0028] F=a·V1+b·W1+c·T3;

[0029] Among them, F is the calculated abnormal value, V1 is the abnormal speed, W1 is the abnormal load data, and a, b, and c are weight coefficients. The abnormal threshold range is set to Q. When F is less than the lowest range of Q, it is judged as a low fault level. When F∈Q, it is judged as a medium fault level. When F is greater than the highest range of Q, it is judged as a high fault level.

[0030] Furthermore, the operation and maintenance personnel qualification classification module performs qualification classification and experience classification on the collected operation and maintenance personnel data as follows:

[0031] Receive elevator classification data, organize the collected data into a structured format, assign elevator classification labels to operation and maintenance personnel, and classify operation and maintenance personnel with 0-2 years of experience as primary qualifications, those with 3-5 years of experience as intermediate qualifications, and those with more than 5 years of experience as senior qualifications.

[0032] Operation and maintenance personnel with different qualification levels can be reasonably assigned to different projects and tasks according to their abilities and experience. The classified personnel qualification information will be stored for quick matching next time. At the same time, the operation and maintenance personnel information will be updated regularly to ensure that the elevator maintenance service is accurate and keeps pace with the times.

[0033] Furthermore, the fault and operation and maintenance personnel matching module performs business matching processing based on the known elevator data and operation and maintenance personnel data as follows:

[0034] The operation and maintenance personnel are screened based on the known elevator types. After the screening is completed, the elevator fault level is matched with the operation and maintenance personnel's qualifications. First, high fault levels will be matched first; secondly, high fault levels will be matched with senior qualified operation and maintenance personnel first, medium fault levels will be matched with intermediate qualified operation and maintenance personnel first, and low fault levels will be matched with junior qualified operation and maintenance personnel first;

[0035] The elevator fault level will be matched with the qualifications of the operation and maintenance personnel. When a high-level fault cannot be matched with a highly qualified operation and maintenance personnel, it will be matched with the operation and maintenance personnel in order of level from high to low, so as to facilitate rapid fault matching and response.

[0036] After the qualification matching is completed, the specific location information of the operation and maintenance personnel is further collected, and the fault is matched with the operation and maintenance personnel who are closest to the fault.

[0037] Furthermore, the operation and maintenance personnel identity authentication module is used to verify the identity information of the operation and maintenance personnel to ensure that the elevator is maintained by the assigned operation and maintenance personnel. The process is as follows:

[0038] After the task assignment is completed, the gesture punch-in posture is randomly assigned;

[0039] After the operation and maintenance personnel arrive at the maintenance destination, they take a selfie with their mobile phone according to the assigned punch-in posture. The selfie needs to be attached with real-time location information. After the shooting is completed, the operation and maintenance personnel upload the image data to the background. The system will automatically verify the identity of the operation and maintenance personnel through image processing technology. After the verification is successful, the operation and maintenance personnel will start the elevator maintenance.

[0040] This method can first ensure that the operation and maintenance personnel have the qualifications for elevator maintenance, thereby preventing the maintenance personnel from being temporarily replaced for the specific business assigned to them.

[0041] Furthermore, the effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of the maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report. The processing process is as follows:

[0042] Clean the uploaded data, remove duplicate and invalid information, and ensure the accuracy and completeness of the data;

[0043] Extract key performance indicators from the cleaned data, such as operating speed, failure rate, energy consumption, etc., as the basis for evaluation;

[0044] Compare and analyze the performance indicators before and after maintenance, use statistical methods or machine learning algorithms to evaluate the effectiveness of maintenance measures, identify the trends and influencing factors of performance changes, and generate detailed reports based on the analysis results.

[0045] An on-demand priority maintenance and effect evaluation device for elevators based on artificial intelligence, comprising a data analysis module, a priority evaluation module, an effect evaluation module, and a user interface module;

[0046] The data analysis module is used to collect, organize and analyze various data during the operation of the elevator and the data of the operation and maintenance personnel;

[0047] The priority evaluation module is used to prioritize elevator faults, with high-level faults being matched first, and high-level faults being matched first to senior qualified operation and maintenance personnel.

[0048] The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of the maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report;

[0049] The user interface module is used to display fault data, operation and maintenance personnel data, operation and maintenance personnel matching data and evaluation data.

[0050] The evaluation device can integrate the overall data and evaluate the final maintenance effect.

[0051] An on-demand priority maintenance and effect evaluation method for elevators based on artificial intelligence.

[0052] S1. Collect elevator fault data and operation and maintenance personnel related data;

[0053] S2. Classify the elevators and divide the fault levels;

[0054] S3. Assign elevator category labels to operation and maintenance personnel according to elevator categories, and classify the qualifications of operation and maintenance personnel according to their years of experience;

[0055] S4. Matching the corresponding operation and maintenance personnel based on the known elevator type and fault type, and further matching based on the distance of the operation and maintenance personnel after the matching is completed;

[0056] S5. Randomly generate a punch-in gesture. After the operation and maintenance personnel arrive at the maintenance site, they will undergo identity verification. After passing the verification, they can start the maintenance work.

[0057] S6. The operation and maintenance personnel upload the specific fault information and maintenance information, and the system automatically integrates and processes the data and generates an evaluation report.

[0058] An electronic device, comprising:

[0059] A processor and a memory, the memory being used to store executable instructions of the processor;

[0060] The processor is configured to perform any of the above steps by executing executable instructions.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] By setting up a fault level classification module, the faulty elevators can be quickly classified according to the preset elevator classification standards. After the classification is completed, the fault level can be determined by calculating the running speed, load condition, door opening and closing status, and camera device data, so as to quickly understand the severity of the fault and facilitate subsequent matching with operation and maintenance personnel;

[0063] By setting up the operation and maintenance personnel qualification classification module, the qualifications of different operation and maintenance personnel can be classified to facilitate matching with elevators of different categories and grades;

[0064] By setting up a fault and maintenance personnel matching module, maintenance personnel can respond to faults quickly. During matching, they will be matched quickly based on known elevator types, fault levels, maintenance personnel qualifications, and real-time distance of maintenance personnel, so that the faulty elevator can be quickly matched with the most suitable maintenance personnel.

[0065] By setting up the identity verification module for the operation and maintenance personnel, it can ensure that the operation and maintenance personnel who arrive at the destination have the actual maintenance qualifications, which improves the standardization and safety of the maintenance work. At the same time, the random clocking-in posture can also avoid the possibility of false attendance by the operation and maintenance personnel, and improve the overall elevator maintenance standardization process;

[0066] The present invention has the functions of elevator classification, fault level classification, operation and maintenance personnel qualification classification, operation and maintenance personnel quick matching and operation and maintenance personnel identity verification, so that elevator faults can be responded to quickly, and high-level faults will be matched and processed first, so as to facilitate the priority elimination of major hidden dangers. At the same time, it can also effectively standardize the elevator maintenance process and further improve the professionalism and reliability of elevator maintenance work. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 This is a block diagram of an on-demand priority maintenance and effect evaluation system for elevators based on artificial intelligence of the present invention;

[0068] Figure 2 The present invention is a flow chart of an on-demand priority maintenance and effect evaluation method for elevators based on artificial intelligence. DETAILED DESCRIPTION

[0069] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] like Figure 1-Figure 2As shown, an on-demand priority maintenance and effect evaluation system for elevators based on artificial intelligence includes: a data acquisition module, an operation and maintenance personnel qualification classification module, a fault category and level classification module, a fault and operation and maintenance personnel matching module, an operation and maintenance personnel identity authentication module, a maintenance result upload module, and an effect evaluation module, wherein the data acquisition module, the operation and maintenance personnel qualification classification module, the fault category and level classification module, the fault and operation and maintenance personnel matching module, the operation and maintenance personnel identity authentication module, the maintenance result upload module, and the effect evaluation module are sequentially connected in communication;

[0071] Data collection module, used to collect relevant data of operation and maintenance personnel and elevator fault data;

[0072] In this embodiment, the data collection module is used to collect the relevant data of the operation and maintenance personnel and the elevator fault data processing process is as follows:

[0073] The data collected about operation and maintenance personnel include the qualification information, identity information and location information of operation and maintenance personnel. The qualification information of operation and maintenance personnel includes professional certificates, training records and qualification certifications. The identity information of operation and maintenance personnel includes name, work number, contact information and department. The location information of operation and maintenance personnel is the location information of the current operation and maintenance personnel, and the location information is tracked through RFID technology.

[0074] The collected elevator fault data include running speed, load condition, door opening and closing status, travel data, internal camera device data, historical operation data, and historical operation data including historical fault records.

[0075] It should be noted that the elevator running speed is monitored by a speed sensor, the load condition is monitored by a load sensor, and the door opening and closing status is monitored by a magnetic sensor; the travel data and historical operation data are collected. The historical operation data including historical fault records can provide a strong basis for subsequent fault analysis.

[0076] Fault category and level classification module, which classifies the collected elevator fault data into categories and levels;

[0077] In this embodiment, the fault category and level classification module performs the following classification and level classification process on the collected elevator fault data:

[0078] According to the collected elevator data, the elevator categories are divided into traction elevators, hydraulic elevators, machine room-less elevators, and home elevators;

[0079] Process the collected running speed, load condition, door opening and closing status, and camera device data to determine the elevator fault level;

[0080] Perform image processing on the data collected by the camera device to determine the situation of people inside the elevator. When it is identified that there are trapped people inside the elevator, the fault is directly classified as a high fault level;

[0081] The collected running speed, load condition, and door opening and closing status data are calculated, and the fault index threshold range is preset. The fault level is determined based on the specific value obtained. The specific formula is:

[0082] T1+T2=T3;

[0083]

[0084] T3∈T4, T3=0;

[0085] Among them, T1 is the door opening time, T2 is the door closing time, T3 is the total door opening and closing time, and T4 is the normal door opening and closing time range. When T3 exceeds T4, the value of T3 is 1, and when T3 belongs to T4, the value of T3 is 0;

[0086] F=a·V1+b·W1+c·T3;

[0087] Among them, F is the calculated abnormal value, V1 is the abnormal speed, W1 is the abnormal load data, and a, b, and c are weight coefficients. The abnormal threshold range is set to Q. When F is less than the lowest range of Q, it is judged as a low fault level. When F∈Q, it is judged as a medium fault level. When F is greater than the highest range of Q, it is judged as a high fault level.

[0088] It should be noted that accurately judging the fault level of an elevator will help improve the safety management level of the elevator. Since different faults may have different manifestations in terms of running speed, load conditions, and door opening and closing status, the specific location and cause of the elevator fault can be more accurately located through comprehensive calculation of multi-dimensional data.

[0089] The operation and maintenance personnel qualification classification module classifies the collected operation and maintenance personnel data by qualifications and experience;

[0090] In this embodiment, the operation and maintenance personnel qualification classification module performs qualification classification and experience classification on the collected operation and maintenance personnel data as follows:

[0091] Receive elevator classification data, organize the collected data into a structured format, assign elevator classification labels to operation and maintenance personnel, and classify operation and maintenance personnel with 0-2 years of experience as primary qualifications, those with 3-5 years of experience as intermediate qualifications, and those with more than 5 years of experience as senior qualifications.

[0092] It should be noted that the specific steps for assigning elevator classification labels to operation and maintenance personnel are as follows:

[0093] Summarize the information of the operation and maintenance personnel to determine whether they are capable of repairing this type of elevator. If the operation and maintenance personnel are found to have the repair qualifications for this type of elevator, they will be directly given such labels so that the elevator can receive more professional repairs.

[0094] The fault and maintenance personnel matching module performs business matching based on the known elevator data and maintenance personnel data;

[0095] In this embodiment, the fault and operation and maintenance personnel matching module performs business matching processing based on the known elevator data and operation and maintenance personnel data as follows:

[0096] The operation and maintenance personnel are screened based on the known elevator types. After the screening is completed, the elevator fault level is matched with the operation and maintenance personnel's qualifications. First, high fault levels will be matched first; secondly, high fault levels will be matched with senior qualified operation and maintenance personnel first, medium fault levels will be matched with intermediate qualified operation and maintenance personnel first, and low fault levels will be matched with junior qualified operation and maintenance personnel first;

[0097] After the qualification matching is completed, the specific location information of the operation and maintenance personnel is further collected, and the fault is matched with the operation and maintenance personnel who are closest to the fault.

[0098] It should be noted that prioritizing the matching of this fault with the nearest operation and maintenance personnel can greatly shorten the fault response time, allowing the operation and maintenance personnel to quickly carry out fault detection and repair work, and reduce the elevator downtime.

[0099] The operator identity verification module is used to verify the operator identity information and ensure that the elevator is maintained by the assigned operator.

[0100] In this embodiment, the operation and maintenance personnel identity authentication module is used to verify the identity information of the operation and maintenance personnel to ensure that the elevator is maintained by the assigned operation and maintenance personnel. The process is as follows:

[0101] After the task assignment is completed, the gesture punch-in posture is randomly assigned;

[0102] After the operation and maintenance personnel arrive at the maintenance destination, they take a selfie with their mobile phone according to the assigned punch-in posture. The selfie needs to be attached with real-time location information. After the shooting is completed, the operation and maintenance personnel upload the image data to the background. The system will automatically verify the identity of the operation and maintenance personnel through image processing technology. After the verification is successful, the operation and maintenance personnel will start the elevator maintenance.

[0103] It should be noted that by verifying the identity of operation and maintenance personnel, the standardization and safety of maintenance work are improved. Maintenance can only be started after successful verification, which prompts operation and maintenance personnel to strictly abide by the work process and enhance their sense of responsibility. At the same time, the system's automatic image processing technology verifies identity, improving the accuracy and efficiency of verification.

[0104] The maintenance result upload module is used to receive the fault data and maintenance data uploaded by the operation and maintenance personnel;

[0105] The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of maintenance measures, analyzes the changes in elevator performance after maintenance, and generates reports.

[0106] In this embodiment, the effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of the maintenance measures, analyzes the performance changes of the elevator after maintenance, and generates a report. The processing process is as follows:

[0107] Clean the uploaded data, remove duplicate and invalid information, and ensure the accuracy and completeness of the data;

[0108] Extract key performance indicators from the cleaned data, such as operating speed, failure rate, energy consumption, etc., as the basis for evaluation;

[0109] Compare and analyze the performance indicators before and after maintenance, use statistical methods or machine learning algorithms to evaluate the effectiveness of maintenance measures, identify the trends and influencing factors of performance changes, and generate detailed reports based on the analysis results;

[0110] An on-demand priority maintenance and effect evaluation device for elevators based on artificial intelligence, comprising a data analysis module, a priority evaluation module, an effect evaluation module, and a user interface module;

[0111] Data analysis module, used to collect, organize and analyze various data during elevator operation and operation and maintenance personnel data;

[0112] Priority evaluation module, used to prioritize elevator faults, with high-level faults given priority and high-level qualified operation and maintenance personnel given priority;

[0113] The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of maintenance measures, analyzes the changes in elevator performance after maintenance, and generates reports;

[0114] The user interface module is used to display fault data, operation and maintenance personnel data, operation and maintenance personnel matching data and evaluation data.

[0115] An on-demand priority maintenance and effect evaluation method for elevators based on artificial intelligence, comprising:

[0116] S1. Collect elevator fault data and operation and maintenance personnel related data;

[0117] S2. Classify the elevators and divide the fault levels;

[0118] S3. Assign elevator category labels to operation and maintenance personnel according to elevator categories, and classify the qualifications of operation and maintenance personnel according to their years of experience;

[0119] S4. Matching the corresponding operation and maintenance personnel based on the known elevator type and fault type, and further matching based on the distance of the operation and maintenance personnel after the matching is completed;

[0120] S5. Randomly generate a punch-in gesture. After the operation and maintenance personnel arrive at the maintenance site, they will undergo identity verification. After passing the verification, they can start the maintenance work.

[0121] S6. The operation and maintenance personnel upload the specific fault information and maintenance information, and the system automatically integrates and processes the data and generates an evaluation report.

[0122] It should be noted that the entire method and process are standardized, which can not only ensure that fault inspection and maintenance personnel have maintenance qualifications, but also quickly match operation and maintenance personnel so that elevator faults can be responded to quickly.

[0123] An electronic device, comprising:

[0124] A processor and a memory, the memory being used to store executable instructions of the processor;

[0125] The processor is configured to perform any of the above steps by executing executable instructions.

[0126] It should be noted that the processor is used for the steps of classifying the qualifications of operation and maintenance personnel, classifying elevator categories, fault diagnosis, matching faults with operation and maintenance personnel, identity verification of operation and maintenance personnel, and evaluation of operation and maintenance effects, and the memory is used to store data information of each step.

[0127] In the embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules is only a logical function division, and there may be other division methods in actual implementation; the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of this embodiment.

[0128] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An on-demand priority maintenance and effect evaluation system for elevators based on artificial intelligence, characterized by: Including data collection module, operation and maintenance personnel qualification classification module, fault category and level classification module, Fault and operation and maintenance personnel matching module, operation and maintenance personnel identity authentication module, maintenance result upload module, The effect evaluation module, the data acquisition module, the operation and maintenance personnel qualification classification module, the fault category and level classification module, the fault and operation and maintenance personnel matching module, the operation and maintenance personnel identity authentication module, the maintenance result upload module, and the effect evaluation module are sequentially connected in communication; The data collection module is used to collect relevant data of operation and maintenance personnel and elevator fault data; The fault category and level classification module is used to classify the collected elevator fault data into categories and levels; The operation and maintenance personnel qualification classification module classifies the collected operation and maintenance personnel data by qualifications and experience; The fault and operation and maintenance personnel matching module performs business matching based on the known elevator data and operation and maintenance personnel data; The operator identity verification module is used to verify the operator identity information and ensure that the elevator is maintained by the assigned operator. The maintenance result uploading module is used to receive the fault data and maintenance data uploaded by the operation and maintenance personnel; The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effects of maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report.

2. According to claim 1, an artificial intelligence-based elevator on-demand priority maintenance and effect evaluation system is characterized by: The data collection module is used to collect the relevant data of the operation and maintenance personnel and the elevator fault data processing process is as follows: The data collected about operation and maintenance personnel include the qualification information, identity information and location information of operation and maintenance personnel. The qualification information of operation and maintenance personnel includes professional certificates, training records and qualification certifications. The identity information of operation and maintenance personnel includes name, work number, contact information and department. The location information of operation and maintenance personnel is the location information of the current operation and maintenance personnel, and the location information is tracked through RFID technology. The collected elevator fault data include running speed, load condition, door opening and closing status, travel data, internal camera device data, historical operation data, and historical operation data including historical fault records.

3. The artificial intelligence-based elevator on-demand priority maintenance and effect evaluation system according to claim 1 is characterized in that: The fault classification and level classification module performs classification and level classification processing on the collected elevator fault data as follows: According to the collected elevator data, the elevator categories are divided into traction elevators, hydraulic elevators, machine room-less elevators, and home elevators; Process the collected running speed, load condition, door opening and closing status, and camera device data to determine the elevator fault level; Perform image processing on the data collected by the camera device to determine the situation of people inside the elevator. When it is identified that there are trapped people inside the elevator, the fault is directly classified as a high fault level; The collected running speed, load condition, and door opening and closing status data are calculated, and the fault index threshold range is preset. The fault level is determined based on the specific value obtained. The specific formula is: T1+T2=T3; T3＝1； T3∈T4, T3=0; Among them, T1 is the door opening time, T2 is the door closing time, T3 is the total door opening and closing time, and T4 is the normal door opening and closing time range. When T3 exceeds T4, the value of T3 is 1, and when T3 belongs to T4, the value of T3 is 0; F=a·V1+b·W1+c·T3; Among them, F is the calculated abnormal value, V1 is the abnormal speed, W1 is the abnormal load data, and a, b, and c are weight coefficients. The abnormal threshold range is set to Q. When F is less than the lowest range of Q, it is judged as a low fault level. When F∈Q, it is judged as a medium fault level. When F is greater than the highest range of Q, it is judged as a high fault level.

4. The artificial intelligence-based elevator on-demand priority maintenance and effect evaluation system according to claim 1 is characterized in that: The operation and maintenance personnel qualification classification module performs qualification classification and experience classification on the collected operation and maintenance personnel data as follows: Receive elevator classification data, organize the collected data into a structured format, assign elevator classification labels to operation and maintenance personnel, and classify operation and maintenance personnel with 0-2 years of experience as primary qualifications, 3-5 years of experience as intermediate qualifications, and more than 5 years of experience as senior qualifications.

5. According to claim 1, an artificial intelligence-based elevator on-demand priority maintenance and effect evaluation system is characterized by: The fault and operation and maintenance personnel matching module performs business matching processing based on the known elevator data and operation and maintenance personnel data as follows: The operation and maintenance personnel are screened based on the known elevator types. After the screening is completed, the elevator fault level is matched with the operation and maintenance personnel's qualifications. First, high fault levels will be matched first; secondly, high fault levels will be matched with senior qualified operation and maintenance personnel first, medium fault levels will be matched with intermediate qualified operation and maintenance personnel first, and low fault levels will be matched with junior qualified operation and maintenance personnel first; After the qualification matching is completed, the specific location information of the operation and maintenance personnel is further collected, and the fault is matched with the operation and maintenance personnel who are closest to the fault.

6. The artificial intelligence-based elevator on-demand priority maintenance and effect evaluation system according to claim 1 is characterized by: The operator identity verification module is used to verify the operator identity information to ensure that the elevator is maintained by the assigned operator. The maintenance process is as follows: After the task assignment is completed, the gesture punch-in posture is randomly assigned; After the operation and maintenance personnel arrive at the maintenance destination, they take a selfie with their mobile phone according to the assigned punch-in posture. The selfie needs to be attached with real-time location information. After the shooting is completed, the operation and maintenance personnel upload the image data to the background. The system will automatically verify the identity of the operation and maintenance personnel through image processing technology. After the verification is successful, the operation and maintenance personnel will start the elevator maintenance.

7. The artificial intelligence-based elevator on-demand priority maintenance and effect system according to claim 1 is characterized by: The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of the maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report. The processing process is as follows: Clean the uploaded data, remove duplicate and invalid information, and ensure the accuracy and completeness of the data; Extract key performance indicators from the cleaned data, such as operating speed, failure rate, energy consumption, etc., as the basis for evaluation; Compare and analyze the performance indicators before and after maintenance, use statistical methods or machine learning algorithms to evaluate the effectiveness of maintenance measures, identify the trends and influencing factors of performance changes, and generate detailed reports based on the analysis results.

8. An on-demand priority maintenance and effect evaluation device for elevators based on artificial intelligence, characterized in that: Including data analysis module, priority assessment module, effect assessment module, and user interface module; The data analysis module is used to collect, organize and analyze various data during the operation of the elevator and the data of the operation and maintenance personnel; The priority evaluation module is used to prioritize elevator faults, with high-level faults being matched first, and high-level faults being matched first with senior qualified operation and maintenance personnel; The effect evaluation module processes the data uploaded by the operation and maintenance personnel, evaluates the effect of the maintenance measures, analyzes the changes in elevator performance after maintenance, and generates a report; The user interface module is used to display fault data, operation and maintenance personnel data, operation and maintenance personnel matching data and evaluation data.

9. An on-demand priority maintenance and effect evaluation method for elevators based on artificial intelligence, characterized in that: S1. Collect elevator fault data and operation and maintenance personnel related data; S2. Classify the elevators and divide the fault levels; S3. Assign elevator category labels to operation and maintenance personnel according to elevator categories, and classify the qualifications of operation and maintenance personnel according to their years of experience; S4. Matching the corresponding operation and maintenance personnel based on the known elevator type and fault type, and further matching based on the distance of the operation and maintenance personnel after the matching is completed; S5. Randomly generate a punch-in gesture. After the operation and maintenance personnel arrive at the maintenance site, they will undergo identity verification. After passing the verification, they can start the maintenance work. S6. The operation and maintenance personnel upload the specific fault information and maintenance information, and the system automatically integrates and processes the data and generates an evaluation report.

10. An electronic device, characterized in that: include: A processor and a memory, the memory being used to store executable instructions of the processor; The processor is configured to perform the steps of any one of claims 1-7 by executing the executable instructions.

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