CN111259848A - Vehicle loss assessment method, vehicle loss assessment system, computer equipment and medium - Google Patents
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Abstract
The invention discloses a vehicle loss assessment method, a vehicle loss assessment system, a computer readable storage medium and computer equipment, wherein the vehicle loss assessment method comprises the following steps: receiving a vehicle video of an accident vehicle sent by a user terminal; recognizing the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle, and acquiring damage information of the accident vehicle; according to the vehicle information and the damage information, acquiring damage assessment accessories and associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data; and obtaining the loss assessment amount of the accident vehicle by utilizing a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated work hour information. The embodiment provided by the invention utilizes the artificial intelligence model and the historical data to evaluate the loss of the accident vehicle and realize artificial damage assessment, thereby reducing the labor cost and the operation cost of the insurance company.
Description
Technical Field
The invention relates to the technical field of vehicle insurance, in particular to a vehicle loss assessment method, a vehicle loss assessment system, a computer readable storage medium and computer equipment.
Background
According to statistics, 80% of vehicle owner report calls received by insurance companies every day are slight accidents, at present, many companies realize self-service claim settlement through APP or WeChat small programs, self-service photographing and uploading are carried out on lost vehicles through a mobile terminal, and finally subsequent claim settlement is carried out after manual review by insurance company claim settlement personnel. In the process, the APP or the WeChat applet reduces the labor cost of the insurance company and saves the operation cost to a certain extent through the artificial intelligence model, but the self-service claim settlement in the true sense cannot be realized.
Disclosure of Invention
In order to solve at least the above problems, a first embodiment of the present invention provides a vehicle damage assessment method applied to a server, including:
receiving a vehicle video of an accident vehicle sent by a user terminal;
recognizing the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle, and acquiring damage information of the accident vehicle;
according to the vehicle information and the damage information, acquiring damage assessment accessories and associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data;
and obtaining the loss assessment amount of the accident vehicle by utilizing a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated work hour information.
Further, before the identifying the vehicle video by using the first network in the preset artificial intelligence model, extracting the vehicle information of the accident vehicle, and obtaining the damage information of the accident vehicle, the method further includes:
judging whether the vehicle video meets a preset requirement or not, wherein the preset requirement comprises the following steps: and if the time length is more than or equal to the preset minimum time length, the time length comprises the vehicle overall appearance, the license plate number information and/or the frame number information and the damaged part from far to near, and if the time length is not more than the preset minimum time length, the prompt information for re-recording the vehicle video is sent to the user terminal.
Further, the recognizing the vehicle video and extracting the vehicle information of the accident vehicle and acquiring the damage information of the accident vehicle by using a first network in a preset artificial intelligence model further comprises:
recognizing and extracting license plate number information, frame number information and damaged parts of the accident vehicle by using a first network in an artificial intelligence model for deep learning;
inquiring the vehicle information of the accident vehicle according to the license plate number information and/or the frame number information; identifying damage information of the damaged part by using a first network in the artificial intelligence model, wherein the damage information comprises a damage position, a damage type, a damaged component proportion and a damaged component material;
or
The acquiring of the damage assessment accessory and the associated labor hour information of the accident vehicle by using the second network in the artificial intelligence model and the preset first historical data according to the vehicle information and the damage information further comprises:
matching the vehicle information and the damage information with preset first historical data by using a second network in the artificial intelligence model to obtain a damage assessment accessory of the accident vehicle;
matching the damage assessment accessory with preset first historical data by using a second network in the artificial intelligence model to calculate associated working hour information for repairing the accident vehicle; or
The obtaining of the loss assessment amount of the accident vehicle by using the second network in the artificial intelligence model and the preset second historical data according to the loss assessment accessory and the associated man-hour information further comprises:
and matching the damage assessment accessory and the associated labor hour information with preset second historical data by using a second network in the artificial intelligence model to obtain the damage assessment amount of the accident vehicle.
Further, after the obtaining of the damage amount of the accident vehicle by using the second network in the artificial intelligence model and the preset second historical data according to the damage accessories and the associated man-hour information, the vehicle damage method further includes:
sending the loss assessment accessory, the associated working hour information and the loss assessment amount to the user terminal;
and responding to the feedback of the user terminal, and sending the prompt information of uploading insurance policy information, identity information and selecting a maintenance place to the user terminal so as to finish the on-line claim settlement of the accident vehicle.
Further, after the sending the damage assessment accessory, the associated labor hour information, and the damage assessment amount to the user terminal, before sending, in response to a feedback prompt of the user terminal, prompt information for uploading policy information, identity information, and selecting a maintenance location to the user terminal to complete an online claim settlement of the accident vehicle, the vehicle damage assessment method further includes:
and calculating the next annual premium information of the accident vehicle according to the vehicle information and the loss assessment amount and sending the next annual premium information to the user terminal.
Further, the sending, in response to the feedback from the user terminal, the upload of policy information, identity information, and prompt information for selecting a maintenance location to complete the online settlement of the accident vehicle to the user terminal further includes:
if the user terminal responds to user operation to select on-line claim settlement, sending prompt information for uploading policy information of the accident vehicle to the user terminal and verifying the policy information according to the vehicle information;
if the policy information is verified to be correct, sending prompt information for uploading the identity information of the owner of the accident vehicle to the user terminal and verifying the identity information;
and if the identity information is verified to be correct, sending prompt information for selecting a maintenance place to the user terminal, and performing claim settlement payment according to the fed back maintenance place to finish online claim settlement.
A second embodiment of the present invention provides a vehicle damage assessment method applied to a user terminal, including:
sending a vehicle video of an accident vehicle to a server in response to a user operation, the vehicle video meeting preset requirements, the preset requirements including: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near;
receiving the loss assessment accessory, the associated labor hour information and the loss assessment amount sent by the server, responding to the selection of a user, carrying out online claims settlement and feeding back the results to the server, wherein the loss assessment accessory, the associated labor hour information and the loss assessment amount are obtained by the server according to the vehicle video by utilizing a first network, a second network, preset first historical data and preset second historical data in a preset artificial intelligence model;
and responding to the user operation to upload insurance policy information and identity information according to the prompt of the server, and selecting a maintenance shop to finish on-line claim settlement.
A third embodiment of the present invention provides a vehicle damage assessment system, comprising a server and a user terminal, wherein
The server comprises a first communication device, a loss assessment module and a processor, the user terminal comprises a second communication device, a video acquisition device and a controller, wherein
The controller responds to user operation and controls the video acquisition device to acquire vehicle videos of accident vehicles and sends the vehicle videos to the server through the second communication device, the vehicle videos meet preset requirements, and the preset requirements comprise: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near;
the processor controls the first communication device to receive the vehicle video, controls the damage assessment module to acquire vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle according to the vehicle video, and sends the vehicle information, the damage assessment accessories, the associated labor hour information and the damage assessment money to the user terminal through the first communication device, wherein the damage assessment module comprises a first network and a second network of a preset artificial intelligence model, and preset first historical data and second historical data;
the controller controls the second communication device to receive vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle, responds to the selection of a user to carry out online claim settlement and feeds back the result to the server through the second communication device;
the processor controls the first communication device to receive the feedback and sends prompt information for uploading policy information, identity information and selecting a maintenance place to the user terminal;
the controller responds to user operation to control the video acquisition device to acquire the policy information and the identity information, responds to user operation to select a maintenance place and sends the maintenance place to the server through the second communication device;
and the processor core realizes the policy information and the identity information and carries out claim settlement and claim payment according to the selected maintenance place so as to complete online claim settlement.
A fourth embodiment of the present invention provides a computer-readable storage medium, having a computer program stored thereon,
the program implementing the method of the first embodiment when executed by a processor;
or
Which when executed by a processor implements the method of the second embodiment.
A fifth embodiment of the invention provides a computer apparatus comprising a memory, a processor, and a computer program stored on the memory and executable on the processor,
the processor implements the method of the first embodiment when executing the program;
or
The processor, when executing the program, implements the method of the second embodiment.
The invention has the following beneficial effects:
aiming at the existing problems, the invention sets a vehicle damage assessment method, a vehicle damage assessment system, a computer readable storage medium and computer equipment, and evaluates the loss of the accident vehicle and realizes artificial damage assessment through an artificial intelligence model and historical data, thereby solving the problems in the prior art, effectively improving the efficiency of damage assessment and claim settlement of the accident vehicle and reducing the labor cost and the operation cost of an insurance company.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 illustrates a flow chart of a vehicle damage assessment method according to an embodiment of the present invention;
FIG. 2 shows a swim lane diagram of a vehicle impairment determination method according to an embodiment of the present invention;
FIG. 3 illustrates a flow chart of a vehicle damage assessment method according to another embodiment of the present invention;
FIG. 4 is a block diagram of a vehicle damage assessment system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device according to another embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the invention, the invention is further described below with reference to preferred embodiments and the accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. It is to be understood by persons skilled in the art that the following detailed description is illustrative and not restrictive, and is not to be taken as limiting the scope of the invention.
As shown in fig. 1, an embodiment of the present invention provides a vehicle damage assessment method, applied to a server, including: receiving a vehicle video of an accident vehicle sent by a user terminal; recognizing the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle, and acquiring damage information of the accident vehicle; according to the vehicle information and the damage information, acquiring damage assessment accessories and associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data; and obtaining the loss assessment amount of the accident vehicle by utilizing a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated work hour information.
In this embodiment, the server identifies the vehicle video through the artificial intelligence model according to the vehicle video sent by the user terminal, acquires the vehicle information of the accident vehicle and the damage information caused by the accident, and then carries out damage assessment on the accident vehicle according to the vehicle information and the damage information of the accident vehicle through the artificial intelligence model and a large amount of historical data so as to acquire the damage assessment accessory, the associated man-hour information and the damage assessment amount of the accident vehicle, so that the rapid and convenient artificial damage assessment and claim settlement is realized, the artificial claim settlement cost and the operation cost of an insurance company are greatly reduced, and the application prospect is wide.
In a specific example, as shown in fig. 2, the method specifically includes:
s1, the user terminal sends the vehicle video to a server.
In this embodiment, after an accident occurs, a vehicle owner of the accident vehicle shoots a vehicle video of the accident vehicle through a user terminal of an application installed on a mobile terminal, for example, a mobile device such as a smart phone or a tablet computer. The vehicle video needs to satisfy the following conditions: the time length of the vehicle video is greater than a preset minimum time length, the vehicle video comprises license plate number information or frame number information, or license plate number information and frame number information, the vehicle video comprises a surrounding vehicle video, a vehicle overall view and damage parts from far to near, and the user terminal sends the vehicle video to the server. The accident vehicle in the video can be proved to be the insurance vehicle through the vehicle-surrounding video containing the vehicle overall view and the injury part from far to near, so that the conditions of fraud and cheating insurance caused by only containing part of the video of the vehicle are effectively avoided.
And S2, identifying the vehicle video through an artificial intelligence model and extracting vehicle information and damage information.
In this embodiment, the server identifies the vehicle video according to a first network in a preset artificial intelligence model, extracts vehicle information of the accident vehicle, and obtains damage information of the accident vehicle. Specifically, the server inputs the vehicle video into a first network of an artificial intelligence model, and identifies the vehicle video through the first network of the artificial intelligence model, in an optional embodiment, the method specifically includes:
firstly, identifying and extracting license plate number information, frame number information and damaged parts of the accident vehicle by utilizing a first network in an artificial intelligence model for deep learning.
In this embodiment, the first network decomposes the vehicle video into a plurality of pictures, for example, extracts a picture including license plate information, frame number information, and a damaged portion from the vehicle video, i.e., decomposes the vehicle video into a plurality of frames of pictures, and extracts the license plate information, the frame number information, and the damaged portion from each picture.
And secondly, inquiring the vehicle information of the accident vehicle according to the license plate information and/or the frame number information.
In this embodiment, the first network obtains the vehicle information of the accident vehicle, for example, obtains information such as a brand and a vehicle model of the accident vehicle, according to the extracted license plate information or frame number information, or the license plate information and frame number information.
And finally, identifying the damage information of the damaged part by using a first network in the artificial intelligence model, wherein the damage information comprises a damaged position, a damaged type, a damaged component proportion and a damaged component material.
In this embodiment, the vehicle information is acquired and the damage information of the accident vehicle, such as the damage information including the damage location, the damage type, the damaged component ratio, the damaged component material, etc. of the accident vehicle is identified through the first network.
Meanwhile, in order to ensure that the vehicle video is a valid video and facilitate the identification of the artificial intelligence model, in an optional embodiment, before identifying the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle and acquiring damage information of the accident vehicle, the method further includes: judging whether the vehicle video meets a preset requirement or not, wherein the preset requirement comprises the following steps: and if the time length is more than or equal to the preset minimum time length, the time length comprises the vehicle overall appearance, the license plate number information and/or the frame number information and the damaged part from far to near, and if the time length is not more than the preset minimum time length, the prompt information for re-recording the vehicle video is sent to the user terminal.
In this embodiment, after receiving the vehicle video, the server checks the vehicle video, if the vehicle video meets a preset requirement, the vehicle video is determined to be an effective video for further identification, otherwise, prompt information for re-recording the vehicle video is sent to the user terminal, so that the user terminal re-records and sends the vehicle video meeting the preset requirement for damage settlement.
And S3, acquiring damage assessment accessories and associated working hour information of the accident vehicle through the artificial intelligence model and historical data.
In this embodiment, the server obtains the damage assessment accessory and the associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data according to the vehicle information and the damage information. And inputting the vehicle information and the damage information into the second network, and acquiring the damage assessment accessories and the associated working hour information of the accident vehicle by the second network according to the vehicle information and the damage information and a large amount of pre-stored first historical data. In an optional embodiment, the method specifically includes:
and matching the vehicle information and the damage information with preset first historical data by utilizing a second network in the artificial intelligence model to obtain a damage assessment accessory of the accident vehicle.
In this embodiment, the second network is used to query and screen the timing damage assessment data matched with the accident vehicle from preset first historical data, so as to obtain the damage assessment accessories of the accident vehicle, where the first historical data includes a large amount of historical data of manually audited damage assessment accessories.
And matching the damage assessment accessory with preset first historical data by using a second network in the artificial intelligence model to calculate associated working hour information for repairing the accident vehicle.
In this embodiment, data matched with the accident vehicle is queried and screened from preset first historical data through the second network according to the damage assessment accessory, so as to calculate associated labor hour information required for repairing the accident vehicle, where the first historical data further includes historical data of a large amount of associated labor hour information related to the manually checked damage assessment accessory.
And S4, obtaining the loss assessment amount of the accident vehicle through the artificial intelligence model and the historical data.
In the embodiment, the loss assessment amount of the accident vehicle is obtained by using a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated labor hour information. In an optional embodiment, the method specifically includes:
and matching the damage assessment accessory and the associated labor hour information with preset second historical data by using a second network in the artificial intelligence model to obtain the damage assessment amount of the accident vehicle.
In this embodiment, the data matched with the accident vehicle is searched and screened from preset second historical data through the second network according to the damage assessment accessory and the associated man-hour information, so that the damage assessment amount of the accident vehicle required to be settled in the current accident is calculated. The second historical data comprises a large amount of historical data of the claim settlement amount after manual review, so the loss settlement amount is highly matched with the manual loss settlement amount of loss settlement personnel with abundant loss settlement experiences.
Therefore, the server can realize self-service damage assessment of the accident according to the vehicle video of the accident vehicle sent by the user terminal through the pre-stored artificial intelligence model and the historical data, so that the damage assessment efficiency is effectively improved, a user can obtain damage assessment help quickly and timely, and meanwhile the labor cost of an insurance company is greatly reduced.
To further implement self-service damage assessment, in an optional embodiment, the vehicle damage assessment method further includes: sending the loss assessment accessory, the associated working hour information and the loss assessment amount to the user terminal; and responding to the feedback of the user terminal, and sending the prompt information of uploading insurance policy information, identity information and selecting a maintenance place to the user terminal so as to finish the on-line claim settlement of the accident vehicle.
In one particular example, this includes:
and S5, the server sends the loss assessment accessories, the associated working hour information and the loss assessment amount to the user terminal.
And S6, the user terminal sends a claim confirmation to the server.
In this embodiment, the server sends the damage assessment accessories, the associated labor hour information and the damage assessment amount obtained through the artificial intelligence model and the historical data to the user terminal, and provides specific damage assessment information for a user using the user terminal, so that the user can determine whether to use the online claims. And if the user determines the on-line claim settlement, continuing to finish the claim settlement step, otherwise, not performing subsequent operation.
In view of the fact that insurance claims using an insurance company may affect the insurance cost of the accident vehicle in the next year, in an alternative embodiment, the vehicle damage assessment method further comprises: and calculating the next annual premium information of the accident vehicle according to the vehicle information and the loss assessment amount and sending the next annual premium information to the user terminal.
In this embodiment, the server calculates the influence of the insurance claim on the insurance fee of the vehicle in the next year of the accident according to the vehicle model of the vehicle and the loss settlement amount of the accident, specifically, calculates the premium information of the vehicle in the next year of the accident, and sends the premium information to the user terminal, so that the user can determine whether to use the online claim or select another mode to process the accident.
And S7, the server sends prompt information for uploading policy information, identity information and selecting a maintenance place to the user terminal so as to complete the on-line claim settlement of the accident vehicle.
In this embodiment, after the user determines to use the online claim settlement, the server starts an auditing stage of the online claim settlement, for example, auditing policy information of the accident vehicle, identity information of the vehicle owner, and the like, which specifically includes:
and if the user terminal responds to the user operation and selects on-line claim settlement, sending prompt information for uploading policy information of the accident vehicle to the user terminal and verifying the policy information according to the vehicle information.
In this embodiment, first, the insurance policy information of the accident vehicle is checked, for example, whether the insurance policy is the insurance policy of the accident vehicle, the insurance time of the insurance policy, the specific insurance items in the insurance policy, and the insurance amount selected by the insurance policy, etc. are checked.
And if the policy information is verified to be correct, sending prompt information for uploading the identity information of the owner of the accident vehicle to the user terminal and verifying the identity information.
In this embodiment, if the policy information is approved, the identity information of the owner is continuously approved, for example, a prompt message is sent to the user terminal to prompt the user to upload the identity information of the owner, for example, to upload the identity information of the owner, such as an identity card or a driver's license. And if the policy audit is not passed, prompting to upload the effective policy information again.
And if the identity information is verified to be correct, sending prompt information for selecting a maintenance place to the user terminal, and performing claim settlement payment according to the fed back maintenance place to finish online claim settlement.
In this embodiment, if the identity information of the owner is verified, the user terminal sends the selection information of the maintenance location, for example, the maintenance information of the nearby 4S store or the maintenance information of the nearby maintenance point, so that the user can select the information. Meanwhile, according to the maintenance place fed back by the user terminal, the maintenance personnel are contacted and the claim settlement money is paid, so that the on-line claim settlement service is conveniently and quickly completed. According to the vehicle damage assessment method provided by the embodiment, the damage assessment data and the online self-service claims of the accident vehicle are calculated by using the artificial intelligent model and the historical data, so that the workload of claim settlement personnel of an insurance company can be effectively reduced, and the labor cost and the operation cost of the insurance company are greatly reduced.
Corresponding to the above vehicle damage assessment method applied to the server, as shown in fig. 3, an embodiment of the present application further provides a vehicle damage assessment method applied to a user terminal, including: sending a vehicle video of an accident vehicle to a server in response to a user operation, the vehicle video meeting preset requirements, the preset requirements including: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near; receiving the loss assessment accessory, the associated labor hour information and the loss assessment amount sent by the server, responding to the selection of a user, carrying out online claims settlement and feeding back the results to the server, wherein the loss assessment accessory, the associated labor hour information and the loss assessment amount are obtained by the server according to the vehicle video by utilizing a first network, a second network, preset first historical data and preset second historical data in a preset artificial intelligence model; and responding to the user operation to upload insurance policy information and identity information according to the prompt of the server, and selecting a maintenance shop to finish on-line claim settlement.
In this embodiment, the user terminal responds to the operation of the user, and after the accident vehicle has an accident, the user terminal starts the online vehicle damage assessment to determine damage assessment accessories, associated working hour information and damage assessment amount, and meanwhile, the user terminal responds to the operation of the user to select insurance policy information and identity information of the vehicle owner of the accident vehicle after the online claims settlement, and selects a maintenance place, so that the server contacts maintenance personnel and pays the claims settlement according to the maintenance place selected by the user, and the online self-service claims settlement is conveniently and quickly completed. The detailed implementation of this embodiment is similar to the previous embodiment, and those skilled in the art can refer to the previous embodiment, which is not described herein again.
In correspondence with the vehicle damage assessment method provided in the foregoing embodiment, an embodiment of the present application further provides a vehicle damage assessment system, and since the vehicle damage assessment system provided in the embodiment of the present application corresponds to the vehicle damage assessment methods provided in the foregoing several embodiments, the foregoing embodiment is also applicable to the vehicle damage assessment system provided in the present embodiment, and detailed description is not given in this embodiment.
As shown in fig. 4, an embodiment of the present application further provides a vehicle damage assessment system, which includes a server and a user terminal, wherein the server includes a first communication device, a damage assessment module and a processor, the user terminal includes a second communication device, a video capture device and a controller, wherein the controller controls the video capture device to capture a vehicle video of an accident vehicle in response to a user operation and sends the vehicle video to the server through the second communication device, the vehicle video meets a preset requirement, and the preset requirement includes: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near; the processor controls the first communication device to receive the vehicle video, controls the damage assessment module to acquire vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle according to the vehicle video, and sends the vehicle information, the damage assessment accessories, the associated labor hour information and the damage assessment money to the user terminal through the first communication device, wherein the damage assessment module comprises a first network and a second network of a preset artificial intelligence model, and preset first historical data and second historical data; the controller controls the second communication device to receive vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle, responds to the selection of a user to carry out online claim settlement and feeds back the result to the server through the second communication device; the processor controls the first communication device to receive the feedback and sends prompt information for uploading policy information, identity information and selecting a maintenance place to the user terminal; the controller responds to user operation to control the video acquisition device to acquire the policy information and the identity information, responds to user operation to select a maintenance place and sends the maintenance place to the server through the second communication device; and the processor core realizes the policy information and the identity information and carries out claim settlement and claim payment according to the selected maintenance place so as to complete online claim settlement.
In this embodiment, can realize the self-service claim of claim to the online of accident vehicle through the vehicle system of definding with server and user terminal convenient and fast, not only save user's time, be convenient for road traffic's normal passage, can also reduce insurance company's cost of labor and operation cost, have extensive application prospect. The specific implementation of this embodiment is similar to the previous embodiments, and is not described herein again.
Another embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements: receiving a vehicle video of an accident vehicle sent by a user terminal; recognizing the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle, and acquiring damage information of the accident vehicle; according to the vehicle information and the damage information, acquiring damage assessment accessories and associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data; and obtaining the loss assessment amount of the accident vehicle by utilizing a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated work hour information.
Another embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements: sending a vehicle video of an accident vehicle to a server in response to a user operation, the vehicle video meeting preset requirements, the preset requirements including: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near; receiving the loss assessment accessory, the associated labor hour information and the loss assessment amount sent by the server, responding to the selection of a user, carrying out online claims settlement and feeding back the results to the server, wherein the loss assessment accessory, the associated labor hour information and the loss assessment amount are obtained by the server according to the vehicle video by utilizing a first network, a second network, preset first historical data and preset second historical data in a preset artificial intelligence model; and responding to the user operation to upload insurance policy information and identity information according to the prompt of the server, and selecting a maintenance shop to finish on-line claim settlement.
In practice, the computer-readable storage medium may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present embodiment, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
As shown in fig. 5, another embodiment of the present invention provides a schematic structural diagram of a computer device. The computer device 12 shown in FIG. 5 is only an example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 5, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processor unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, to implement a vehicle damage assessment method provided by the embodiment of the present invention.
Aiming at the existing problems, the invention sets a vehicle damage assessment method, a vehicle damage assessment system, a computer readable storage medium and computer equipment, and evaluates the loss of the accident vehicle and realizes artificial damage assessment through an artificial intelligence model and historical data, thereby solving the problems in the prior art, effectively improving the efficiency of damage assessment and claim settlement of the accident vehicle and reducing the labor cost and the operation cost of an insurance company.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.
Claims (10)
1. A vehicle damage assessment method is applied to a server and is characterized by comprising the following steps:
receiving a vehicle video of an accident vehicle sent by a user terminal;
recognizing the vehicle video by using a first network in a preset artificial intelligence model, extracting vehicle information of the accident vehicle, and acquiring damage information of the accident vehicle;
according to the vehicle information and the damage information, acquiring damage assessment accessories and associated labor hour information of the accident vehicle by using a second network in the artificial intelligence model and preset first historical data;
and obtaining the loss assessment amount of the accident vehicle by utilizing a second network in the artificial intelligence model and preset second historical data according to the loss assessment accessory and the associated work hour information.
2. The vehicle damage assessment method according to claim 1, wherein before said recognizing the vehicle video and extracting the vehicle information of the accident vehicle and obtaining the damage information of the accident vehicle by using the first network in the preset artificial intelligence model, the method further comprises:
judging whether the vehicle video meets a preset requirement or not, wherein the preset requirement comprises the following steps: and if the time length is more than or equal to the preset minimum time length, the time length comprises the vehicle overall appearance, the license plate number information and/or the frame number information and the damaged part from far to near, and if the time length is not more than the preset minimum time length, the prompt information for re-recording the vehicle video is sent to the user terminal.
3. The vehicle damage assessment method according to claim 1,
the recognizing the vehicle video and extracting the vehicle information of the accident vehicle and obtaining the damage information of the accident vehicle by using a first network in a preset artificial intelligence model further comprises:
recognizing and extracting license plate number information, frame number information and damaged parts of the accident vehicle by using a first network in an artificial intelligence model for deep learning;
inquiring the vehicle information of the accident vehicle according to the license plate number information and/or the frame number information;
identifying damage information of the damaged part by using a first network in the artificial intelligence model, wherein the damage information comprises a damage position, a damage type, a damaged component proportion and a damaged component material;
or
The acquiring of the damage assessment accessory and the associated labor hour information of the accident vehicle by using the second network in the artificial intelligence model and the preset first historical data according to the vehicle information and the damage information further comprises:
matching the vehicle information and the damage information with preset first historical data by using a second network in the artificial intelligence model to obtain a damage assessment accessory of the accident vehicle;
matching the damage assessment accessory with preset first historical data by using a second network in the artificial intelligence model to calculate associated working hour information for repairing the accident vehicle; or
The obtaining of the loss assessment amount of the accident vehicle by using the second network in the artificial intelligence model and the preset second historical data according to the loss assessment accessory and the associated man-hour information further comprises:
and matching the damage assessment accessory and the associated labor hour information with preset second historical data by using a second network in the artificial intelligence model to obtain the damage assessment amount of the accident vehicle.
4. The vehicle damage assessment method according to claim 1, wherein after said obtaining of the damage amount of the accident vehicle using a second network in the artificial intelligence model and a second history data preset according to the damage accessories and the associated man-hour information, the vehicle damage assessment method further comprises:
sending the loss assessment accessory, the associated working hour information and the loss assessment amount to the user terminal;
and responding to the feedback of the user terminal, and sending the prompt information of uploading insurance policy information, identity information and selecting a maintenance place to the user terminal so as to finish the on-line claim settlement of the accident vehicle.
5. The vehicle damage assessment method according to claim 4, wherein after said transmitting said damage assessment accessories, associated man-hour information and damage assessment amount to said user terminal, before said transmitting to said user terminal, in response to a feedback prompt of said user terminal, prompt information for uploading policy information, identity information, selecting a repair location to complete an online claim settlement of said accident vehicle, said vehicle damage assessment method further comprises:
and calculating the next annual premium information of the accident vehicle according to the vehicle information and the loss assessment amount and sending the next annual premium information to the user terminal.
6. The vehicle damage assessment method according to claim 4,
the sending, in response to the feedback of the user terminal, to the user terminal prompt information for uploading policy information, identity information, and selecting a maintenance location to complete the online settlement of the accident vehicle further comprises:
if the user terminal responds to user operation to select on-line claim settlement, sending prompt information for uploading policy information of the accident vehicle to the user terminal and verifying the policy information according to the vehicle information;
if the policy information is verified to be correct, sending prompt information for uploading the identity information of the owner of the accident vehicle to the user terminal and verifying the identity information;
and if the identity information is verified to be correct, sending prompt information for selecting a maintenance place to the user terminal, and performing claim settlement payment according to the fed back maintenance place to finish online claim settlement.
7. A vehicle damage assessment method is applied to a user terminal and is characterized by comprising the following steps:
sending a vehicle video of an accident vehicle to a server in response to a user operation, the vehicle video meeting preset requirements, the preset requirements including: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near;
receiving the loss assessment accessory, the associated labor hour information and the loss assessment amount sent by the server, responding to the selection of a user, carrying out online claims settlement and feeding back the results to the server, wherein the loss assessment accessory, the associated labor hour information and the loss assessment amount are obtained by the server according to the vehicle video by utilizing a first network, a second network, preset first historical data and preset second historical data in a preset artificial intelligence model;
and responding to the user operation to upload insurance policy information and identity information according to the prompt of the server, and selecting a maintenance shop to finish on-line claim settlement.
8. A vehicle damage assessment system is characterized by comprising a server and a user terminal, wherein
The server comprises a first communication device, a loss assessment module and a processor, the user terminal comprises a second communication device, a video acquisition device and a controller, wherein
The controller responds to user operation and controls the video acquisition device to acquire vehicle videos of accident vehicles and sends the vehicle videos to the server through the second communication device, the vehicle videos meet preset requirements, and the preset requirements comprise: the time length is more than or equal to the preset minimum time length, and the time length comprises the overall appearance of the vehicle, license plate number information and/or frame number information and the damaged part from far to near;
the processor controls the first communication device to receive the vehicle video, controls the damage assessment module to acquire vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle according to the vehicle video, and sends the vehicle information, the damage assessment accessories, the associated labor hour information and the damage assessment money to the user terminal through the first communication device, wherein the damage assessment module comprises a first network and a second network of a preset artificial intelligence model, and preset first historical data and second historical data;
the controller controls the second communication device to receive vehicle information, damage assessment accessories, associated labor hour information and damage assessment money of the accident vehicle, responds to the selection of a user to carry out online claim settlement and feeds back the result to the server through the second communication device;
the processor controls the first communication device to receive the feedback and sends prompt information for uploading policy information, identity information and selecting a maintenance place to the user terminal;
the controller responds to user operation to control the video acquisition device to acquire the policy information and the identity information, responds to user operation to select a maintenance place and sends the maintenance place to the server through the second communication device;
and the processor core realizes the policy information and the identity information and carries out claim settlement and claim payment according to the selected maintenance place so as to complete online claim settlement.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that,
the program when executed by a processor implementing the method of any one of claims 1-6;
or
Which program, when being executed by a processor, carries out the method of claim 7.
10. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor,
the processor, when executing the program, implementing the method of any one of claims 1-6;
or
The processor, when executing the program, implements the method of claim 7.
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| CN202010074589.5A CN111259848A (en) | 2020-01-22 | 2020-01-22 | Vehicle loss assessment method, vehicle loss assessment system, computer equipment and medium |
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| CN202010074589.5A CN111259848A (en) | 2020-01-22 | 2020-01-22 | Vehicle loss assessment method, vehicle loss assessment system, computer equipment and medium |
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