CN115828112B

CN115828112B - Fault event response method and device, electronic equipment and storage medium

Info

Publication number: CN115828112B
Application number: CN202211540327.9A
Authority: CN
Inventors: 刘港
Original assignee: Delian Yikong Technology Beijing Co ltd
Current assignee: Delian Yikong Technology Beijing Co ltd
Priority date: 2022-12-02
Filing date: 2022-12-02
Publication date: 2023-08-18
Anticipated expiration: 2042-12-02
Also published as: CN115828112A

Abstract

The application is applicable to the technical field of data processing, and provides a response method and device of fault events, electronic equipment and a storage medium, wherein the method comprises the following steps: receiving event data of a fault event to be processed; generating a plurality of event tags associated with the fault event from event data and generating an object representation for the incident object based on the event tags; respectively calculating the portrait similarity of the object portrait and a plurality of historical portraits in an object database, and determining at least one historical fault event matched with an accident object based on the portrait similarity; and generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event. By adopting the method, the stability of the fault flow can be greatly improved, and under the condition of coping with a large number of fault events, the fault response report can be automatically generated in a mode of matching with the object database, so that the efficiency of generating the response fault report is greatly improved.

Description

Fault event response method and device, electronic equipment and storage medium

Technical Field

The application belongs to the technical field of vehicle management, and particularly relates to a response method and device of a fault event, electronic equipment and a storage medium.

Background

With the continuous promotion of socialization progress, social population is increasing. In daily life, unexpected fault events, such as traffic accidents, medical accidents and the like, can occur more or less, and when the fault events are handled, related personnel can specify corresponding response flows to handle the fault events, so that the loss of the fault events to people is reduced. Therefore, how to respond quickly to a fault event becomes a problem to be solved.

In the existing fault event response technology, workers are required to know the fault event on site, and corresponding response flows are designated according to processing experience. However, the quality of the corresponding response flow is also uneven due to the processing experience of different staff, and the staff determines that the response flow needs longer time and has lower response efficiency under the condition of more fault events. Therefore, the existing fault event response method has the problems of unstable generation quality of a response flow and lower response efficiency.

Disclosure of Invention

The embodiment of the application provides a response method, a device, electronic equipment and a storage medium for fault events, which can solve the problems of unstable generation quality and low response efficiency of the response flow in the existing response method for the fault events.

In a first aspect, an embodiment of the present application provides a method for responding to a fault event, including:

receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

generating a plurality of event tags associated with the fault event from event data and generating an object representation for the incident object based on the event tags;

respectively calculating the portrait similarity of the object portrait and a plurality of historical portraits in an object database, and determining at least one historical fault event matched with an accident object based on the portrait similarity; each history image corresponds to one history fault event;

and generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event.

In a possible implementation manner of the first aspect, the event tag includes: traffic scene tags and accident object tags; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag, and a scene location tag that are determined based on the accident scene information; the accident object tag includes: a professional tag and an age tag determined based on the accident object information;

The generating a plurality of event tags associated with the fault event according to event data and generating an object portrait about the accident object based on the event tags includes:

determining the contained tag keywords from the event data according to the tag keywords of a plurality of preset tag dimensions, and obtaining the event tag based on the contained tag keywords;

importing the event type label, the event reason label and the scene place label into a preset accident simulation model to construct a fault simulation scene corresponding to the fault event;

determining the road type associated with the fault event according to the scene location tag, and determining the vehicle speed of the fault vehicle at the moment of the fault event based on the rated speed interval associated with the road type;

calculating the safety coefficient of the failed vehicle based on the vehicle type tag;

constructing a corresponding vehicle model in the fault simulation scene through the safety coefficient of the fault vehicle and the vehicle speed;

controlling the vehicle model to move in the fault simulation scene, generating fault restoration data, and generating a collision dimension score of the accident object through the fault restoration data;

And generating an object portrait of the accident object according to the collision dimension score, the job tag and the age tag.

In a possible implementation manner of the first aspect, the generating the object representation of the accident object according to the collision dimension score, the job ticket, and the age ticket includes:

determining a body basis score for the accident subject from the job ticket and the age ticket;

determining the disease type associated with the job tag through the corresponding relation between the preset occupation and the common diseases, and determining the existing disease dimension score of the accident object based on the disease type;

receiving event description voice fed back by the accident object, and determining an emotion dimension score based on the event description language;

generating the representation of the subject based on the body basis score, the existing disease dimension score, the collision dimension score, and the emotion dimension score; the object representation is used for carrying out injury prediction on the accident object.

In a possible implementation manner of the first aspect, the receiving the event description voice fed back by the accident object and determining the emotion dimension score based on the event description language includes:

Extracting historical object voices associated with the accident object from an object voice library, and determining a basic decibel value through the historical voice amplitude of the historical object voices; the basic decibel value is used for determining the voice decibel of the accident object in the mood stabilization state;

determining a decibel characteristic parameter set according to the event description voice; the decibel characteristic parameter set comprises: decibel extremum, decibel mean and decibel mean square error;

obtaining at least one candidate emotion type based on the decibel characteristic parameter set and the basic decibel value;

matching the event description voice with standard voice waveforms of the candidate emotion types to determine a target emotion type;

and determining the emotion dimension score according to the target emotion type.

In a possible implementation manner of the first aspect, the event tag includes: traffic scene tags and accident object tags;

before said computing the portrait similarity of said object portrait with a plurality of historical portraits in an object database, respectively, and determining at least one historical fault event matching an accident object based on said portrait similarity, further comprising:

Invoking a plurality of first parallel threads associated with the number of first labels corresponding to the traffic scene labels, and extracting first object data corresponding to each traffic scene label from the object database; each first parallel path corresponds to one traffic scene tag;

performing data intersection recognition on all the first object data to obtain a first object group;

invoking a plurality of second parallel threads associated with a second number of tags corresponding to the accident object tags, and extracting second object data corresponding to each accident object tag from the object database; each second parallel thread corresponds to one accident object label;

performing data intersection recognition on all the second object data to obtain a second object group;

determining a candidate object group according to the first object group and the second object group;

constructing a multidimensional fusion vector related to the fault event according to all the traffic scene tags and the accident object tags;

extracting a target historical object matched with the multidimensional fusion vector from the candidate object group; the historical representation is generated based on historical fault events of the target historical object.

In a possible implementation manner of the first aspect, the receiving event data of a fault event to be processed includes:

receiving original event data fed back by a recorder of the fault event; the original event data is obtained based on natural language description of the recording personnel; the original event data comprises a plurality of degree parameters of event description dimensions;

extracting a degree correction algorithm associated with the personnel identification of the recording personnel from a correction algorithm library; the degree correction algorithm is generated after the difference information between the historic description language of the record personnel and the historic fault event is trained;

respectively importing the degree parameters corresponding to each event description dimension into the degree correction algorithm to obtain correction parameters of each event description dimension;

the event data is generated based on correction parameters for all of the event description dimensions.

In a possible implementation manner of the first aspect, the generating, based on the response flow report corresponding to the historical fault event, a fault response report corresponding to the fault event includes: respectively obtaining response flow reports corresponding to the historical fault events;

Performing flow clustering on all the response flow reports to obtain at least one flow group; the flow similarity between the response flow reports in each flow group is larger than a preset similarity threshold;

calculating the recommendation confidence corresponding to each flow group according to the portrait similarity of the accident object corresponding to each flow group;

determining the display priority of each flow group according to the order of the recommendation confidence level from large to small;

and generating the fault response report according to the display priority and the recommended response flow corresponding to the flow group.

In a second aspect, an embodiment of the present application provides a response device for a fault event, including:

an event data receiving unit for receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

an object representation generating unit for generating a plurality of event tags associated with the fault event based on event data, and generating an object representation about an accident object based on the event tags;

an object representation matching unit for calculating the representation similarity of the object representation and a plurality of history representations in an object database respectively, and determining at least one history fault event matched with the accident object based on the representation similarity; each history image corresponds to one history fault event;

And the fault response report generating unit is used for generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event.

In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the method according to any one of the first aspects when executing the computer program.

In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a method as in any of the first aspects above.

In a fifth aspect, an embodiment of the application provides a computer program product, which, when run on a server, causes the server to perform the method according to any of the first aspects described above.

Compared with the prior art, the embodiment of the application has the beneficial effects that: the method comprises the steps of receiving event data of a fault event to be processed, analyzing the event data to obtain a plurality of event labels related to the fault event, generating object images of accident objects related to the fault event according to the event labels, carrying out image similarity calculation on the object images and each history image in an object database, determining at least one history fault event matched with the object images through the image similarity, corresponding to an associated response flow because the history fault event is a processed event, and generating a fault response report corresponding to the fault event according to a response flow report which can be associated with the history fault event, thereby realizing the purpose of automatically generating the fault response report. Compared with the existing fault response technology, the embodiment of the application does not rely on the judgment of response flow by staff through experience, but multiplexes the response flow report of the history fault event by identifying the history fault event similar to the current fault event, thereby greatly improving the stability of the fault flow, and automatically generating the fault response report in a matching mode with the object database under the condition of dealing with a large number of fault events, and greatly improving the efficiency of generating the response fault report.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram illustrating an implementation of a method for responding to a fault event according to an embodiment of the present application;

FIG. 2 is a schematic diagram of an object representation provided by an embodiment of the present application;

FIG. 3 is a flowchart showing a specific implementation of a method S102 for responding to a fault event according to a second embodiment of the present application;

fig. 4 is a flowchart of a specific implementation of a method S1027 for responding to a fault event according to a third embodiment of the present application;

FIG. 5 is a flowchart showing a method for responding to a fault event according to a fourth embodiment of the present application;

FIG. 6 is a flowchart showing a method S101 for responding to a fault event according to a fifth embodiment of the present application;

FIG. 7 is a flowchart showing a method S104 for responding to a fault event according to a sixth embodiment of the present application;

FIG. 8 is a schematic structural diagram of a fault event responding device according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.

The fault event response method provided by the embodiment of the application can be applied to electronic equipment which can realize the generation of fault response reports corresponding to the fault event, such as intelligent mobile phones, servers, tablet computers, notebook computers, ultra-mobile personal computer (UMPC) and netbooks. The embodiment of the application does not limit the specific type of the electronic equipment.

In one possible implementation manner, the electronic device may be an intelligent terminal, such as a smart phone, used by a worker to whom event data of a fault event belongs, where the intelligent terminal may be installed with a corresponding client program, and through which event data corresponding to the fault event may be collected, so as to generate a corresponding fault response report.

In a possible implementation manner, the electronic device may also be a server deployed at a cloud end, in which case, a user may install a client program corresponding to the cloud end server in a local user terminal, and import corresponding event data in the client program, for example, a worker using the client program is a worker collecting event data at a fault event site, the worker records corresponding event data at the fault site, the user terminal may establish communication connection with the cloud end server through the client program, and upload the received event data to the cloud end server (i.e., an execution subject provided by the embodiment of the present application), and then the cloud end server may generate a fault response report corresponding to the fault event through a subsequent step, and feed back the fault response report to the user terminal used by the worker on site, so that the worker may respond to the fault event according to the fault response report.

Referring to fig. 1, fig. 1 shows an implementation schematic diagram of a fault event response method according to an embodiment of the present application, where the method includes the following steps:

in S101, event data of a fault event to be processed is received; the event data includes: accident object information and accident scene information.

In this embodiment, when a fault event occurs, event data corresponding to the fault event may be acquired according to a preset data acquisition module. The data acquisition template is internally recorded with a plurality of information dimensions for acquiring related information about the fault event under different dimensions, wherein the information dimensions comprise objects used for determining the action of the fault event, namely accident object dimensions, and scenes generated by the fault event, namely accident scene dimensions, and the corresponding accident object information and accident scene information can be obtained based on the two information dimensions, and the information of the two dimensions is packaged to obtain event data for describing the specific condition of the fault event.

For example, a traffic accident is taken as an example, and in the case of a traffic accident at a certain destination, there is a fault event corresponding to the traffic accident. The accident object is specifically a wounded person in the traffic accident, for example, a driver driving a vehicle in the traffic accident, a passenger in the vehicle, or the like, and of course, in some application scenarios, the accident object may also be an accident vehicle in the traffic accident. The accident scene may include information related to the scene where the traffic accident occurs, such as time, place, vehicle type, number of vehicles, etc., and the specific type of scene information to be collected may be selected according to the actual situation.

Illustratively, an equipment failure is taken as an example, and if a certain equipment fails, such as a laptop fails, or an automobile fails, a fault event is identified. The accident object is specifically a device with a fault, such as a computer or an automobile. The accident scenario may include location information, temperature information, related equipment operation parameters, etc. when the fault occurs, and the specific type of the scene information to be collected may be determined according to the type of the equipment, which is not limited herein.

In one possible implementation manner, the electronic device may be configured with a microphone module, and the microphone module is configured to obtain a description voice signal of the accident object for the fault event, perform voice recognition on the description voice signal, convert the description voice signal into corresponding description text data, extract keywords based on the description text data, and generate event data corresponding to the fault event.

In one possible implementation, a worker may collect raw data corresponding to a fault event. The raw data may be generated based on a natural language description of the staff member. After receiving the original data fed back by the staff, the electronic equipment can carry out data cleaning on the original data, carry out data division on the original data according to preset data dimensions defined in a preset data template to obtain sub-data associated with each data dimension, and then import each sub-data into a field corresponding to the associated data dimension, so as to generate the event data, and complete corresponding data cleaning. Optionally, to improve confidentiality of the event data, the electronic device may also encrypt and store the event data in the blockchain to improve confidentiality and reliability of the event data.

In S102, a plurality of event tags associated with the fault event are generated from event data, and an object representation for the incident object is generated based on the event tags.

In this embodiment, after obtaining event data of a fault event, the electronic device may perform tag extraction on the fault event to obtain a plurality of event tags for describing the fault event. Different event labels can correspond to different event description dimensions, so that a user can roughly know a fault event through the event labels, and extraction of key information is achieved.

The fault event is a traffic accident event. Such event tags include, but are not limited to: the traumatology, the traumatology place, the traumatology age, the traumatology sex, the accident type, the accident cause, the accident place, the traumatology, the collision azimuth, the traumatology place, the target vehicle type, the target vehicle body large class, the target vehicle year, the three vehicle types, the three vehicle body large class and the three vehicle year. Optionally, the electronic device may further process the generated event tags, classify the plurality of event tags to obtain a first tag group related to an accident object, a second tag group related to an accident vehicle, and a third tag group related to an accident environment, and process the event tags in each tag group to generate cluster tags to generate accident, wounded and vehicle tags.

In this embodiment, after determining the event tags corresponding to each different dimension, the electronic device may determine a dimension score corresponding to the dimension according to the content of the event tag corresponding to the dimension, and construct a corresponding object portrait according to the dimension scores corresponding to all the dimensions. Illustratively, FIG. 2 shows a schematic diagram of an object representation provided by an embodiment of the present application. Referring to fig. 2, the fault event is specifically a traffic accident, the object representation is used for determining the injury condition of the wounded in the traffic accident, wherein the object representation includes a vehicle speed dimension, a vehicle impact depth dimension, an injury degree dimension, a wounded physical condition dimension (before injury), a wounded mental state dimension and the like, and the different dimensions can determine corresponding dimension scores according to corresponding contents, so that the wounded condition after the traffic accident is constructed and determined.

In this embodiment, the electronic device stores an event tag score conversion function, the event tag conversion function is mutually bound with a corresponding dimension, the electronic device determines a dimension type corresponding to the event tag, extracts a conversion function associated with the dimension type from a database, imports the event tag into the associated conversion function, and can determine a dimension score corresponding to the event tag, so that an object representation of the accident object is generated based on the dimension scores of all the dimensions.

If the accident object includes a plurality of accident objects, that is, two or more accident objects exist in one fault event, the electronic device may establish a corresponding object representation for each accident object according to the number of accident objects, so as to determine an associated fault response report for different accident objects.

In S103, respectively calculating the portrait similarity of the object image and a plurality of history portraits in an object database, and determining at least one history fault event matched with an accident object based on the portrait similarity; each of the historical images corresponds to one of the historical fault events.

In this embodiment, the electronic device may store a response flow report corresponding to the historical fault event. Because of the fault events which are similar to the fault conditions, the response report which is processed once can be used for guiding how to respond to the fault event. In this case, the electronic device may extract, from the object database, a historical fault event having a high similarity to the current fault event by performing similarity calculation with the object image, so as to generate a fault response report of the current fault event based on the associated response flow report of the historical fault time.

In this embodiment, when each historical fault event is responded, the execution flow is consistent with the fault event occurring this time, and a corresponding historical portrait is also generated. The electronic device associates the historical images with the historical fault events and stores them in the object database. After the electronic device generates the object portrait corresponding to the fault event to be processed this time, the similarity calculation can be performed on the object portrait and the history portrait.

In one possible implementation manner, the manner of calculating the similarity between the object representation and the history representation may be: the electronic device may draw the object image and the history image in a predetermined coordinate system, thereby calculating the degree of coincidence between the two images, and perform a weighted calculation on the degree of coincidence according to the dimension weights corresponding to the respective dimensions, thereby calculating the weighted degree of coincidence as the degree of similarity. The higher the overlap ratio between the two images, the higher the corresponding similarity.

In this embodiment, the electronic device may determine, according to the similarity corresponding to each history image, a history image associated with the object image, and use a history fault event associated with the associated history image as a time-to-failure associated history fault event to be processed at this time. Alternatively, the electronic device may set a similarity threshold, and a historical representation having a similarity greater than the similarity threshold is identified as matching the object representation, thereby determining a historical failure event associated with the failure event.

In S104, a fault response report corresponding to the fault event is generated based on the response flow report corresponding to the historical fault event.

In this embodiment, a response flow report corresponding to each historical fault event may be stored in the object database of the electronic device. The response flow report is specifically a response flow that is actually performed when handling the historical failure event. Taking traffic accidents as an example for explanation, the response flow report is specifically used for the adjustment scheme and the optimal tracking time of the wounded, namely, for determining how to treat the illness state of the wounded according to the treatment flow of the wounded after the wounded, and can also be a claim flow for the wounded.

For example, if the fault event is a device fault event, the response flow report may be a fault diagnosis for the device and a corresponding actual maintenance flow. In this case, the actual repair procedure may include a repair method in the repair process for the faulty device, and tools required for repair, such as a software tool and a hardware tool.

In this embodiment, the electronic device may cluster and sort the response flow reports corresponding to the fault events, so as to generate a fault response report having guiding significance for the fault events, so that a staff may respond to the fault events according to the fault response report.

It can be seen from the foregoing that, in the response method of the fault event provided by the embodiment of the present application, by receiving the event data about the fault event to be processed, analyzing the event data to obtain a plurality of event labels related to the fault event, generating object portraits of accident objects related to the fault event according to the plurality of event labels, performing portraits similarity calculation on the object portraits and each historical portraits in the object database, and determining at least one historical fault event matched with the object portraits through the portraits similarity, because the historical fault event is an event that has been processed, the corresponding response flow corresponds to the historical fault event, and generating a fault response report corresponding to the fault event according to a response flow report that can be associated with the historical fault event, thereby achieving the purpose of automatically generating the fault response report. Compared with the existing fault response technology, the embodiment of the application does not rely on the judgment of response flow by staff through experience, but multiplexes the response flow report of the history fault event by identifying the history fault event similar to the current fault event, thereby greatly improving the stability of the fault flow, and automatically generating the fault response report in a matching mode with the object database under the condition of dealing with a large number of fault events, and greatly improving the efficiency of generating the response fault report.

Fig. 3 is a flowchart showing a specific implementation of a fault event response method S102 according to a second embodiment of the present invention. Referring to fig. 3, with respect to the embodiment described in fig. 1, in a response method of a fault event provided in this embodiment, S102 includes: s1021 to S1027 are described in detail as follows:

further, the event tag includes: traffic scene tags and accident object tags; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag, and a scene location tag that are determined based on the accident scene information; the accident object tag includes: a professional tag and an age tag determined based on the accident object information;

in S1021, according to the preset tag keywords of the plurality of tag dimensions, determining the tag keywords contained in the event data, and obtaining the event tag based on the contained tag keywords.

In this embodiment, the fault event is specifically a traffic accident, so it is necessary to determine the corresponding related event label from two aspects. The labels are respectively related to the traffic scene and the accident object related to the current traffic accident. The two types of labels further comprise corresponding sub-labels, and traffic accidents can be restored according to the sub-labels of different types.

In this embodiment, after obtaining the event data, the electronic device may perform event tag extraction on the event data. The extraction process specifically includes matching event data with tag keywords of each tag dimension, so as to obtain tag content corresponding to the fault event in the corresponding tag dimension. Wherein different tag dimensions may correspond to one or more tag keywords. Taking scene location tags as an example, the tag keywords include, but are not limited to: mountain roads, urban roads, highways, etc. to distinguish corresponding scene locations under different geographic environments. The electronic device detects the tag keywords contained in the event data, so that specific tag content corresponding to the fault event in the corresponding tag dimension can be determined, and the tag keywords contained in the event data are used as event tags corresponding to the tag dimension, so that identification of the event tags is realized.

Wherein the identified event tag includes: the event type tag, the event reason tag, the vehicle type tag and the scene place tag which are determined based on the accident scene information also comprise a professional tag and an age tag which are determined based on the accident object information.

In S1022, the event type tag, the event reason tag, and the scene location tag are imported into a preset accident simulation model, and a fault simulation scene corresponding to the fault event is constructed.

In this embodiment, the electronic device may restore the accident situation by using the event type tag and the event cause tag, and determine the physical scene situation when the accident occurs by using the scene location tag, for example, determine that the accident occurs in a corresponding city, country, expressway, mountain area, etc., so that the electronic device may import the three types of event tags into a preset accident simulation model, thereby being able to construct an accident simulation scene corresponding to the traffic accident.

In S1023, a road type associated with the fault event is determined according to the scene location tag, and a vehicle speed of the fault vehicle at the time of the fault event is determined based on a rated speed section associated with the road type.

In this embodiment, the electronic device may determine, according to the scene location tag, a road type corresponding to the occurrence of the fault event, and since different roads have corresponding rated speed intervals, after a traffic accident occurs, the vehicle is often in a damaged state, and the corresponding driving record may not be directly acquired or may take a long time to recover. Thus, the electronic device may determine the corresponding road type through the scene location tag, for example: urban roads, rural roads, internal roads, urban expressways, mountain-turning roads and the like, and respectively determine rated speed intervals associated with different road types, and predict the speed of the fault vehicle according to the rated speed intervals, for example, the upper limit of the intervals of the rated speed intervals is taken as the vehicle speed, corresponding vehicle speeds can be obtained by calculating the overspeed coefficient and the rated speed intervals based on preset, and the specific calculation mode can be set according to actual conditions.

In S1024, the safety coefficient of the failed vehicle is calculated based on the vehicle type tag.

In this embodiment, when a traffic accident occurs, the electronic device has a strong relationship with the structure of the vehicle itself in addition to the relationship with the vehicle speed, so that in order to more accurately simulate the traffic accident, the electronic device may determine the safety coefficient corresponding to the faulty vehicle in which the traffic accident occurs through the vehicle type tag. Specifically, the manner of determining the safety coefficient may be: the vehicle type tag may be used to determine: the information of the target vehicle type, the target vehicle service year and the like can be used for determining the vehicle safety coefficient of the vehicle through the information of the type.

In S1025, a corresponding vehicle model within the fault simulation scenario is constructed from the safety factor of the faulty vehicle and the vehicle speed.

In this embodiment, after obtaining the safety coefficient of the fault vehicle and the vehicle speed, the electronic device may construct a vehicle model corresponding to the fault vehicle in the fault simulation scene, where the appearance of the vehicle model may be determined according to the vehicle type tag, the rigidity of the vehicle model may be determined according to the safety coefficient, and the motion track of the vehicle simulation in the fault simulation scene may be restored according to the vehicle speed, so that the simulation of the fault event may be completed when video data of the fault vehicle in the occurrence time cannot be quickly obtained or when a blind spot is monitored.

In S1026, the vehicle model is controlled to move within the fault simulation scenario, fault restoration data is generated, and a collision dimension score of the accident object is generated through the fault restoration data.

In this embodiment, the electronic device may control the vehicle model to move along the motion track in the fault simulation scene according to the determined motion track, so as to obtain collision data during a collision, determine relevant information such as a corresponding collision depth, a corresponding collision direction, a corresponding collision force and the like during the current traffic accident, and determine a corresponding collision dimension score. Because of the high degree of collision, there is a direct strong correlation with the degree of injury to the accident object, and in order to be able to improve the accuracy of recognition of subsequent object representations, it is necessary to determine a corresponding collision dimension score.

In S1027, a target representation of the accident target is generated based on the collision dimension score, the job ticket, and the age ticket.

In this embodiment, the electronic device may determine the body basis score of the accident object according to the occupation tag and the age tag of the accident object, so as to generate the object representation of the accident object based on the collision dimension score and the body basis score.

In the embodiment of the application, the fault event is restored through the event labels, so that the corresponding collision dimension score can be obtained, the fault response method can be suitable for larger scenes, the event restoration can be completed without relying on the acquisition of the traffic video of three parties, the waiting time of the fault response report is reduced, and the fault response efficiency is greatly improved.

Fig. 4 is a flowchart showing a specific implementation of a fault event response method S1027 according to the third embodiment of the present application. Referring to fig. 4, with respect to the embodiment described in fig. 3, in a response method of a fault event provided in this embodiment, S1027 includes: s401 to S404 are specifically described below:

in S401, a body basis score of the accident object is determined from the job ticket and the age ticket.

In this embodiment, the electronic device may predict the exercise situation of the user in the daily life according to the professional tag corresponding to the accident object, for example, if the accident object is a physical teacher or a fitness trainer, a certain exercise may be kept in the working and living process, based on which the corresponding physical quality is higher; on the contrary, if the accident object is a programmer or a game developer, the working intensity is high, the exercise is less, and the corresponding physical quality can be lower. Of course, the physical quality of the accident subject is also age-related, so that the physical basis score of the accident subject can be determined based on the two tags described above.

In one possible implementation manner, different professional labels may correspond to one score weighted value, different age ranges may also correspond to one score basic value, the electronic device may determine the score weighted value of the accident object according to the professional label, determine the score basic value corresponding to the range according to the age label, and superimpose the score weighted value on the score basic value, so as to calculate the body basic score.

In S402, a disease type associated with the job tag is determined according to a preset correspondence between occupation and common diseases, and an existing disease dimension score of the accident object is determined based on the disease type.

In this embodiment, the electronic device stores a correspondence between occupation and common diseases, and after determining the occupation label of the accident object, the electronic device can predict the possible occupation diseases of the accident object through the correspondence, so as to determine the disease type associated with the occupation label, and determine to obtain a corresponding dimension score of the existing diseases.

In S403, event description speech fed back by the accident object is received, and an emotion dimension score is determined based on the event description speech.

In this embodiment, during the process of acquiring event data, a worker may collect event description voice corresponding to the current fault event by the accident object at the same time. Since the real situation of the fault event is the most known accident object, in order to improve the understanding degree of the fault event situation, the electronic device may collect event description voices, and cannot generate corresponding event data based on the event description voices.

In this embodiment, since the voice can describe the situation of the fault event, the voice signal can also embody other information besides the text, that is, the emotion information of the accident object, the electronic device can extract the voice voiceprint corresponding to the event description voice, and analyze the voice voiceprint to determine the emotion dimension score corresponding to the accident object.

Further, as another embodiment of the present application, the above manner of determining the emotion dimension score may employ the following steps:

step 1: determining a decibel characteristic parameter set according to the event description voice; the decibel characteristic parameter set comprises: decibel extremum, decibel mean, and decibel mean square error.

Step 2: and obtaining at least one candidate emotion type based on the decibel characteristic parameter set and the basic decibel value.

Step 3: and matching the event description voice with standard voice waveforms of the candidate emotion types, and determining a target emotion type.

Step 4: and determining the emotion dimension score according to the target emotion type.

In this embodiment, the electronic device may perform signal analysis on the event description voice to generate a signal waveform corresponding to the event description voice, where the signal waveform is the signal waveform in the time domain, so that the corresponding signal amplitude is a decibel value of the voice signal, and then the set of decibel feature parameters may be determined according to the signal waveform. The decibel characteristic parameter set specifically comprises a decibel extremum, a decibel mean value and a decibel mean square error. The electronic equipment can store a corresponding basic decibel value in a calm state, and can compare the decibel characteristic parameter with the basic decibel value, and because people have corresponding characteristics in different emotions, the electronic equipment can compare the basic decibel value with the calm state, and can determine at least one candidate emotion type, namely, can carry out primary evaluation on the emotion of an accident object.

In one possible implementation, the basic db value may be used to enable a worker to contact an accident object before the accident occurs, and to collect the data collected by the user during the daily process during the contact. I.e. there is a difference in the base decibel values corresponding to different users.

In this embodiment, the electronic device may obtain standard speech waveforms corresponding to each candidate emotion type, and calculate similarity between the voiceprint signal of each event description speech and the standard speech waveform, so as to calculate a matching degree corresponding to each candidate emotion type, and select a candidate emotion type with the highest matching degree as a target emotion type corresponding to the accident object. The electronic device may determine a corresponding emotion dimension score from the target emotion type.

According to the embodiment of the application, the event description voice of the accident object is collected and analyzed, so that the corresponding target emotion type can be accurately determined, the emotion dimension score is obtained, and the accuracy of the emotion dimension score is improved.

In S404, generating the subject representation from the body basis score, the existing disease dimension score, the collision dimension score, and the emotion dimension score; the object representation is used for carrying out injury prediction on the accident object.

In this embodiment, the object representation of the accident object may be generated according to the body base score, the existing disease dimension score, the collision dimension score, and the emotion dimension score of the accident object, so that the injury caused by the fault event by the object representation may be predicted.

In the embodiment of the application, the physical condition of the user is predicted through the accident object label, so that a plurality of dimension scores related to the accident object can be obtained, the corresponding object portrait can be determined, and the accuracy of the object portrait is improved.

Fig. 5 is a flowchart of a specific implementation of a method for responding to a fault event according to a fourth embodiment of the present application. Referring to fig. 5, with respect to the embodiment described in fig. 1, the response method of a fault event provided in this embodiment further includes, before S103: s501 to S507 are specifically described as follows:

further, the event tag includes: traffic scene tags and accident object tags;

in S501, invoking a plurality of first parallel threads associated with a first number of tags corresponding to the traffic scene tags, and extracting first object data corresponding to each traffic scene tag from the object database; each first parallel path corresponds to one traffic scene tag;

In S502, data intersection recognition is performed on all the first object data, so as to obtain a first object group.

In this embodiment, in order to reduce unnecessary matching operations of object images, the electronic device may extract a target history object with a greater correlation of fault events. Because the data in the object database is more, the electronic equipment can perform multi-thread synchronous search through parallel threads in order to improve the search efficiency. The traffic scene tags and the accident object tags are mutually independent, so that the search task of the accident object tags can be executed while searching based on the traffic scene tags. The electronic device will thus create two parallel thread groups, one being a first parallel thread for searching traffic scene tags and the other being a second parallel thread for searching accident object tags.

In this embodiment, a corresponding history tag may be associated with the history object data in the object database, where the history tag may be used as index information of the history object data, so as to improve efficiency of subsequent searching, without reading the content of the history object data, and may be capable of quickly searching for the associated history object data by matching with the tag. Therefore, the rate of tag matching by the electronic device through the thread is larger than the rate of content matching after data analysis, so that the efficiency of target historical object recognition can be improved.

In this embodiment, the electronic device creates a plurality of first parallel lines associated with the number of first tags, where each first parallel line is used to extract, from the object database, historical object data of a traffic scene tag including a certain tag dimension, i.e. the first object data. For example, a traffic scenario tag for a certain failure event includes: if the electronic device can call three first parallel lines, the first object data of the label of the vehicle type A, the first object data of the label of the vehicle type 4 years and the first object data of the label of the urban road are searched in the object database respectively. Then, the electronic device may perform intersection recognition on the three first object data, extract first object data that includes the three traffic scene tags at the same time, and obtain a first object group.

In S503, invoking a plurality of second parallel threads associated with a second number of tags corresponding to the accident object tags, and extracting second object data corresponding to each accident object tag from the object database; each of the second parallel threads corresponds to one of the incident object tags.

In S504, data intersection recognition is performed on all the second object data, so as to obtain a second object group.

In this embodiment, similar to searching the first object group related to the traffic scene tag, the electronic device may also call a plurality of second parallel threads when determining the second object group, where each second parallel thread is used to search the historical object data of the accident object tag that includes any tag dimension, so as to obtain second object data corresponding to the accident object tag, and then perform intersection recognition on all the second object data to obtain the second object group.

In S505, a candidate object set is determined according to the first object set and the second object set.

In this embodiment, after determining the object groups corresponding to the two dimensions, that is, the first object group and the second object group, the electronic device may also perform intersection recognition, so as to determine the candidate object group that includes the same event tag as the fault event.

In S506, a multidimensional fusion vector related to the fault event is constructed according to all the traffic scene tags and the accident object tags.

In this embodiment, the electronic device may perform vectorization processing on the traffic scene tag and the accident object tag, so as to construct a corresponding multidimensional fusion vector of the fault event. The multidimensional fusion vector is specifically used for determining the key event content of the fault event, namely, the vector obtained after feature extraction of event data.

In S507, extracting a target history object matched with the multidimensional fusion vector from the candidate object group; the historical representation is generated based on historical fault events of the target historical object.

In this embodiment, the electronic device may perform content matching on the multidimensional fusion vector and the historical object data recorded in the candidate object group, calculate the content association degree, and identify that the historical object data in the candidate object group is the target historical object matched by the fault event if the content association degree is greater than a preset association threshold. Because the time for calculating the content association is longer than that of tag matching, the extraction efficiency of the target historical object can be improved by determining the candidate object group and then calculating the content association.

Fig. 6 shows a flowchart of a specific implementation of a fault event response method S101 according to a fifth embodiment of the present invention. Referring to fig. 6, with respect to the embodiments described in any of fig. 1 to 5, in a response method of a fault event provided in this embodiment, S101 includes: s1011 to S1014, the details are as follows:

in S1011, receiving raw event data fed back by a recorder of the fault event; the original event data is obtained based on natural language description of the recording personnel; the original event data comprises a plurality of degree parameters of event description dimensions.

In S1012, extracting a degree correction algorithm associated with the person identification of the recording person from a correction algorithm library; the degree correction algorithm is generated after training through difference information between the historic description language of the record personnel and the historic fault events.

In S1013, the degree parameters corresponding to the respective event description dimensions are respectively imported into the degree correction algorithm to obtain correction parameters of the respective event description dimensions.

In this embodiment, different recording personnel may have certain differences in description of the same event, so that in order to improve accuracy of event data, the electronic device may perform data cleaning on original event data fed back by the recording personnel, so as to reduce influence of subjective factors on the event data. Based on the description habits of different recording personnel, the electronic equipment can construct a corresponding program correction algorithm. The description habit of the recording personnel can be determined according to the history description language obtained by the recording personnel in the history time and the degree of difference between the history fault events determined according to the actual situation.

For example, if the fault event is a traffic accident event, and if a certain event description dimension is the impact depth of the vehicle, in the present fault event, the impact depth is 0.5m, a description of a certain recorder is "deeper" for the impact depth, and a description of another recorder is "shallower" for the impact depth, so that there may be a difference between descriptions of different recorders for the same phenomenon, and based on this, the electronic device may perform data correction through a degree correction algorithm.

In this embodiment, the electronic device may introduce each degree parameter into the degree correction algorithm, so as to perform a de-subjectiveization process on each degree parameter to obtain a corresponding correction parameter.

In S1014, the event data is generated based on correction parameters of all the event description dimensions.

In this embodiment, the electronic device may encapsulate all correction parameters to obtain corresponding event data, so that accuracy of the subsequently generated event tag may be improved.

In the embodiment of the application, corresponding degree correction algorithms are created for different recording personnel, and the original event data collected by the recording personnel can be subjected to data cleaning through the degree correction algorithms, so that the event data with reduced subjective factors can be obtained, and the accuracy of subsequent processing is improved.

Fig. 7 is a flowchart showing a specific implementation of a fault event response method S104 according to a sixth embodiment of the present application. Referring to fig. 7, with respect to the embodiments described in any of fig. 1 to 5, in a response method of a fault event provided in this embodiment, S104 includes: s1041 to S1045 are specifically described below:

in S1041, a response flow report corresponding to each of the historical fault events is obtained respectively;

In S1042, performing flow clustering on all the response flow reports to obtain at least one flow group; the flow similarity between the response flow reports in each flow group is larger than a preset similarity threshold;

in S1043, calculating a recommendation confidence corresponding to the flow group according to the image similarity of the accident object corresponding to each flow group;

in S1044, determining a display priority of each of the flow groups according to an order of the recommendation confidence levels from high to low;

in S1045, the fault response report is generated according to the display priority and the recommended response procedure corresponding to the procedure group.

In this embodiment, in order to improve the readability of the fault response report, the electronic device may perform clustering processing on the response flow report associated with the historical fault event, and encapsulate the response flow report with higher flow similarity in the same flow group, so that packet processing can be performed on all the response flow reports. Then, the electronic device can determine the recommendation confidence corresponding to the response flow report corresponding to each flow group according to the association degree of the flow group and the fault event. The recommendation confidence is related to the portrait similarity corresponding to the flow group, and the higher the portrait similarity to the accident object, namely the more similar to the fault event, the higher the corresponding recommendation confidence. The electronic equipment can be used as the display priority corresponding to the response flow report according to the order of the recommended confidence level, so that the user can conveniently check the response flow report corresponding to the flow group with higher correlation, and the checking efficiency of the user is improved.

Fig. 8 is a block diagram of a fault event responding device according to an embodiment of the present invention, where each unit included in the fault event responding device is configured to perform each step implemented by the encryption device in the corresponding embodiment of fig. 1. Please refer to fig. 1 and the related description of the embodiment corresponding to fig. 1. For convenience of explanation, only the portions related to the present embodiment are shown.

Referring to fig. 8, the response device for the fault event includes:

an event data receiving unit 81 for receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

an object representation generating unit 82 for generating a plurality of event tags associated with the fault event from event data and generating an object representation about the accident object based on the event tags;

an object representation matching unit 83 for calculating representation similarity of the object representation with a plurality of history representations in an object database, respectively, and determining at least one history fault event matched with the accident object based on the representation similarity; each history image corresponds to one history fault event;

the fault response report generating unit 84 is configured to generate a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event.

Optionally, the event tag includes: traffic scene tags and accident object tags; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag, and a scene location tag that are determined based on the accident scene information; the accident object tag includes: a professional tag and an age tag determined based on the accident object information;

the object representation generating unit 82 includes:

a tag keyword extraction unit, configured to determine a tag keyword that is included from the event data according to a tag keyword of a plurality of preset tag dimensions, and obtain the event tag based on the tag keyword that is included;

the fault simulation scene construction unit is used for importing the event type label, the event reason label and the scene place label into a preset accident simulation model to construct a fault simulation scene corresponding to the fault event;

the vehicle speed determining unit is used for determining the road type associated with the fault event according to the scene location tag and determining the vehicle speed of the fault vehicle at the moment of the fault event based on the rated speed interval associated with the road type;

A safety coefficient determining unit for calculating a safety coefficient of a failed vehicle based on the vehicle type tag;

a vehicle model construction unit, configured to construct a vehicle model corresponding to the fault simulation scene according to the safety coefficient of the fault vehicle and the vehicle speed;

a collision dimension score determining unit, configured to control the vehicle model to move in the fault simulation scene, generate fault restoration data, and generate a collision dimension score of the accident object according to the fault restoration data;

and a first portrait construction unit configured to generate an object portrait of the accident object based on the collision dimension score, the job ticket, and the age ticket.

Optionally, the first portrait construction unit includes:

a body basis score determining unit for determining a body basis score of the accident subject from the job ticket and the age ticket;

the disease dimension score determining unit is used for determining the disease type associated with the job label through the corresponding relation between the preset occupation and the common diseases, and determining the existing disease dimension score of the accident object based on the disease type;

The emotion dimension score determining unit is used for receiving event description voice fed back by the accident object and determining emotion dimension scores based on the event description voice;

a second representation construction unit for generating the subject representation based on the body basis score, the existing disease dimension score, the collision dimension score, and the emotion dimension score; the object representation is used for carrying out injury prediction on the accident object.

Optionally, the emotion dimension score determination unit includes:

a basic decibel value determining unit, configured to extract a history object voice associated with the accident object from an object voice library, and determine a basic decibel value according to a history voice amplitude of the history object voice; the basic decibel value is used for determining the voice decibel of the accident object in the mood stabilization state;

the characteristic parameter set determining unit is used for determining a decibel characteristic parameter set according to the event description voice; the decibel characteristic parameter set comprises: decibel extremum, decibel mean and decibel mean square error;

a candidate emotion type determining unit, configured to obtain at least one candidate emotion type based on the db characteristic parameter set and the base db value;

The target emotion type determining unit is used for matching the event description voice with standard voice waveforms of the candidate emotion types and determining a target emotion type;

and the emotion dimension score determining unit is used for determining the emotion dimension score according to the target emotion type.

Optionally, the event tag includes: traffic scene tags and accident object tags; the response device further includes:

the first parallel unit is used for calling a plurality of first parallel threads related to the number of the first labels corresponding to the traffic scene labels, and extracting first object data corresponding to each traffic scene label from the object database; each first parallel path corresponds to one traffic scene tag;

the first object group determining unit is used for carrying out data intersection recognition on all the first object data to obtain a first object group;

a second parallel unit, configured to invoke a plurality of second parallel threads associated with a second number of tags corresponding to the incident object tags, and extract second object data corresponding to each of the incident object tags from the object database; each second parallel thread corresponds to one accident object label;

The second object group determining unit is used for carrying out data intersection recognition on all the second object data to obtain a second object group;

a candidate object group determining unit configured to determine a candidate object group according to the first object group and the second object group;

the multidimensional fusion vector generation unit is used for constructing multidimensional fusion vectors related to the fault event according to all the traffic scene labels and the accident object labels;

a target history object determining unit, configured to extract a target history object matched with the multidimensional fusion vector from the candidate object group; the historical representation is generated based on historical fault events of the target historical object.

Optionally, the event data receiving unit 81 includes:

the original event data receiving unit is used for receiving original event data fed back by a recorder of the fault event; the original event data is obtained based on natural language description of the recording personnel; the original event data comprises a plurality of degree parameters of event description dimensions;

a correction algorithm determining unit for extracting a degree correction algorithm associated with the person identification of the recording person from a correction algorithm library; the degree correction algorithm is generated after the difference information between the historic description language of the record personnel and the historic fault event is trained;

The correction unit is used for respectively importing the degree parameters corresponding to the event description dimensions into the degree correction algorithm to obtain the correction parameters of the event description dimensions;

and the correction parameter packaging unit is used for generating the event data based on correction parameters of all the event description dimensions.

Optionally, the fault response report generating unit 84 includes: the response flow report determining unit is used for respectively acquiring response flow reports corresponding to the historical fault events;

the flow group dividing unit is used for carrying out flow clustering on all the response flow reports to obtain at least one flow group; the flow similarity between the response flow reports in each flow group is larger than a preset similarity threshold;

a recommendation confidence determining unit, configured to calculate a recommendation confidence corresponding to each flow group according to the portrait similarity of the accident object corresponding to each flow group;

a display priority determining unit, configured to determine a display priority of each of the flow groups according to an order of the recommendation confidence levels from large to small;

and generating a report, namely generating the fault response report according to the display priority and the recommended response flow corresponding to the flow group.

Therefore, the response device of the fault event provided by the embodiment of the application can also analyze the event data by receiving the event data about the fault event to be processed to obtain a plurality of event labels related to the fault event, generate object portraits of accident objects related to the fault event according to the event labels, calculate the portraits of the object portraits and each history portraits in an object database, determine at least one history fault event matched with the object portraits according to the portraits of the portraits, and correspond to the associated response flow because the history fault event is the processed event, and generate the fault response report corresponding to the fault time according to the response flow report which can be associated with the history fault event, thereby realizing the purpose of automatically generating the fault response report. Compared with the existing fault response technology, the embodiment of the application does not rely on the judgment of response flow by staff through experience, but multiplexes the response flow report of the history fault event by identifying the history fault event similar to the current fault event, thereby greatly improving the stability of the fault flow, and automatically generating the fault response report in a matching mode with the object database under the condition of dealing with a large number of fault events, and greatly improving the efficiency of generating the response fault report.

It should be understood that, in the block diagram of the response device for a fault event shown in fig. 8, each module is configured to perform each step in the embodiment corresponding to fig. 1 to 7, and each step in the embodiment corresponding to fig. 1 to 7 has been explained in detail in the foregoing embodiment, and specific reference is made to fig. 1 to 7 and related descriptions in the embodiment corresponding to fig. 1 to 7, which are not repeated herein.

Fig. 9 is a block diagram of an electronic device according to another embodiment of the present application. As shown in fig. 9, the electronic device 900 of this embodiment includes: a processor 910, a memory 920, and a computer program 930 stored in the memory 920 and executable on the processor 910, such as a program of a response method to a fault event. The processor 910, when executing the computer program 930, implements the steps in the embodiments of the response method of each fault event described above, such as S101 to S104 shown in fig. 1. Alternatively, the processor 910 may implement the functions of the modules in the embodiment corresponding to fig. 8, for example, the functions of the units 81 to 84 shown in fig. 8, when executing the computer program 930, and refer to the related description in the embodiment corresponding to fig. 8.

By way of example, the computer program 930 may be partitioned into one or more modules, with one or more modules stored in the memory 920 and executed by the processor 910 to perform the present application. One or more of the modules may be a series of computer program instruction segments capable of performing particular functions to describe the execution of the computer program 930 in the electronic device 900. For example, the computer program 930 may be divided into individual unit modules, each of which functions specifically as above.

Electronic device 900 may include, but is not limited to, processor 910, memory 920. It will be appreciated by those skilled in the art that fig. 9 is merely an example of an electronic device 900 and is not intended to limit the electronic device 900, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., an electronic device may also include an input-output device, a network access device, a bus, etc.

The processor 910 may be a central processing unit, or may be another general purpose processor, digital signal processor, application specific integrated circuit, off-the-shelf programmable gate array, or other programmable logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or any conventional processor or the like.

The memory 920 may be an internal storage unit of the electronic device 900, such as a hard disk or a memory of the electronic device 900. The memory 920 may also be an external storage device of the electronic device 900, such as a plug-in hard disk, a smart memory card, a flash memory card, etc. provided on the electronic device 900. Further, the memory 920 may also include both internal storage units and external storage devices of the electronic device 900.

The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. A method of responding to a fault event, comprising:

Generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event;

the event tag includes: traffic scene tags and accident object tags; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag, and a scene location tag that are determined based on the accident scene information; the accident object tag includes: a professional tag and an age tag determined based on the accident object information;

2. The response method of claim 1, wherein the generating the object representation of the accident object based on the collision dimension score, the job tag, and the age tag comprises:

3. The response method of claim 2, wherein the receiving the event description speech of the incident object feedback and determining the emotion dimension score based on the event description language comprises:

4. The response method of claim 1, further comprising, prior to said separately computing representation similarities for said object representation and a plurality of historical representations in an object database, and determining at least one historical failure event matching an accident object based on said representation similarities:

5. The response method according to any one of claims 1-4, wherein the receiving event data of a fault event to be processed comprises:

6. The response method according to any one of claims 1-4, wherein generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event comprises: respectively obtaining response flow reports corresponding to the historical fault events;

7. A fault event generating device, comprising:

the fault response report generating unit is used for generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event;

the object representation generating unit includes:

8. An electronic device comprising a memory, a processor and a computer program stored in the memory and running on the processor, characterized in that the processor implements the method according to any of claims 1 to 6 when executing the computer program.

9. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the method according to any one of claims 1 to 6.