CN111476464A

CN111476464A - Method, device and equipment for scheduling survey resources based on grids and readable medium

Info

Publication number: CN111476464A
Application number: CN202010203311.3A
Authority: CN
Inventors: 王记红
Original assignee: China Auto Service Technology Service Co ltd
Current assignee: China Auto Service Technology Service Co ltd
Priority date: 2020-03-20
Filing date: 2020-03-20
Publication date: 2020-07-31
Anticipated expiration: 2040-03-20
Also published as: CN111476464B

Abstract

The embodiment of the invention discloses a method, a device, equipment and a readable medium for scheduling exploration resources based on grids, wherein the method comprises the following steps: receiving a survey request, and determining target grids and resource demand information corresponding to the survey request; determining at least one survey resource as a candidate resource according to the target grid and the resource demand information; acquiring resource characteristic data of the candidate resources, and determining available resources from the candidate resources according to the resource characteristic data; and sending the survey request to the available resources, acquiring service available information returned by the available resources within a preset time length, and determining target resources from the available resources according to the service available information so that the target survey resources process the survey request. The invention improves the efficiency of surveying resource scheduling, thereby improving the surveying user experience.

Description

Method, device and equipment for scheduling survey resources based on grids and readable medium

Technical Field

The invention relates to the field of computer data processing, in particular to a method, a device, equipment and a readable medium for surveying resource scheduling based on grids.

Background

Since the available resources for scheduling are limited, more and more insurance companies utilize the shared resources for surveying, such as third-party personnel around a consignment accident who have the survey qualification to go forward to work.

In the prior art, scheduling or a method of nearby simple scheduling based on a voluntary principle is generally adopted for scheduling and using survey resources, and due to the characteristics of wide distribution of shared resources, unfixed quantity of each region and large mobility of the survey resources, the two survey resource calling methods are not suitable for calling the shared survey resources, so that the problems of low survey efficiency, high cost and poor user experience based on shared resource scheduling are caused.

Disclosure of Invention

In view of the foregoing, there is a need to provide a method, an apparatus, a computer device and a readable medium for scheduling a resource based on a grid.

A method for scheduling a resource based on a grid, the method comprising:

receiving a survey request, and determining target grids and resource demand information corresponding to the survey request;

determining at least one survey resource as a candidate resource according to the target grid and the resource demand information;

acquiring resource characteristic data of the candidate resources, and determining available resources from the candidate resources according to the resource characteristic data;

and sending the survey request to the available resources, acquiring service available information returned by the available resources within a preset time length, and determining target resources from the available resources according to the service available information so that the target survey resources process the survey request.

An apparatus for scheduling a grid-based survey resource, the apparatus comprising:

a receiving unit: the system comprises a data processing module, a data processing module and a resource management module, wherein the data processing module is used for receiving a survey request and determining a target grid and resource demand information corresponding to the survey request;

a first determination unit: the resource demand information is used for determining at least one survey resource as a candidate resource according to the target grid and the resource demand information;

a second determination unit: the resource characteristic data is used for acquiring the resource characteristic data of the candidate resources, and available resources are determined from the candidate resources according to the resource characteristic data;

a response unit: the resource allocation method is used for sending the survey request to the available resources, acquiring service available information returned by the available resources within a preset time length, and determining target resources from the available resources according to the service available information so that the target survey resources process the survey request.

A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of:

A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:

In the embodiment of the invention, firstly, a survey request is received, and target grids and resource demand information corresponding to the survey request are determined;

Compared with the prior art that fixed personnel shift or nearby arrangement is adopted when the survey resources are scheduled, the survey efficiency is low and the user experience is poor due to the fact that the distribution of the shared survey resources is not matched with the case requests when the survey resources are shared.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Wherein:

FIG. 1 illustrates a flow diagram of a method for grid-based exploration resource scheduling in one embodiment;

FIG. 2 illustrates a process diagram for determining associated survey resources for various grids in one embodiment;

FIG. 3 shows a flow diagram of the determination of the candidate resource in one embodiment;

FIG. 4 illustrates a flow diagram for determining the quality of service score in one embodiment;

FIG. 5 illustrates a flow diagram for determining age evaluation information in one embodiment;

FIG. 6 illustrates a flow diagram for determining available resources from the candidate resources in one embodiment;

FIG. 7 is a block diagram that illustrates an apparatus for grid-based exploration resource scheduling in one embodiment;

FIG. 8 is a diagram illustrating an internal structure of a computer device in one embodiment.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention provides a method for scheduling survey resources based on grids.

Referring to fig. 1, an embodiment of the present invention provides a method for scheduling a resource based on a grid.

FIG. 1 shows a flow diagram of a method for grid-based exploration resource scheduling in one embodiment. The method for scheduling resources based on grid-based exploration includes at least steps S1022 to S1028 shown in fig. 1, which are described in detail as follows:

in step S1022, a survey request is received, and the target grid and the resource requirement information corresponding to the survey request are determined.

First, the survey request may be sent manually by the vehicle insurance user who has an accident or the customer service staff for insurance claims, and specifically may be performed through a preset application program (e.g., a preset vehicle insurance APP).

It will be readily appreciated that in view of the needs of the on-site survey operation being conducted, in one particular embodiment, the survey request may include at least two of insurance policy information, insurance order number, customer name, contact address, accident location and/or accident type.

For example, in one embodiment, after an accident occurs in a road section in the area B, a certain owner a fills in relevant information of a survey request in a survey request applet of a vehicle insurance claim and sends the relevant information to a background, so that insurance department information, an insurance order number, a client name, a contact address, an accident site and/or an accident type at this place can be filled in by a user and respectively identified as C insurance company, X102738, a, 13800000000, a D street 15 number in the area B, and a vehicle collision.

Furthermore, the qualification requirements (i.e. resource requirement information) for survey operators (i.e. survey resources) are correspondingly extracted from the survey request information, for example, only a certain type of survey personnel has the expertise to perform a survey for a certain type of accident, or due to regional limitations, a survey site and a survey time are also the most basic key information for the scheduling of survey resources, and thus, the resource requirement information may at least include at least two items of security information, an accident site, an accident time and an accident type.

With reference to the above examples, the insurance company C, the D street number 15 in the B area, the 1/2019, the 20:00:39 in the 1/2019, and the vehicle collision are determined as the insurance information, the accident location, the accident time, and the accident type.

Correspondingly, the process of determining the target grid corresponding to the survey request may be to determine the corresponding grid as the target grid according to the accident location.

Before determining the target mesh, the definition and determination process of the mesh herein needs to be explained first.

First, it is readily understood that shared survey resources or other third party resources have greater mobility and distributed non-organisational properties, since the availability of survey resources, particularly shared survey resources, is uncertain in their spatio-temporal distribution, that is, distinguished from fixedly organised survey personnel that may be present in the vicinity of a fixed area (i.e. must be available) at a fixed time.

Therefore, when performing survey scheduling based on shared resources, the service area may be first divided into sub-areas (i.e. grids) of appropriate size by using the distribution of the shared resources and the dynamic variability in availability, and data prediction is performed on each grid according to the historical case of the area, so as to achieve efficient utilization of the survey resources.

The process of the partitioning of a particular grid to determine a match of its associated survey resources may include steps S1032-S10310 as shown in fig. 2. FIG. 2 illustrates a process diagram for determining the associated survey resources for various grids in one embodiment.

In step S1032, historical case data is acquired, which includes at least two of historical case time, historical case location, historical accident type, and historical accident toast information.

First, the object of the history case data here may be a fixed area for a boundary of interest (e.g., a city or a street). The characteristics of historical case occurrence, such as the number of cases occurring in each time period of a day, the difference between the type of the case occurring and the corresponding demand for exploration resources, are used as references to predict the demand trend of exploration resources in the future time period, so that the historical case data of the historical case time, the historical case location, the historical accident type, the historical accident insurance information and the like at the place needs to be acquired.

In step S1034, a number of predetermined grids are determined according to the historical case data.

In an alternative embodiment, the aforementioned region of interest may be divided into a plurality of preset grids according to a preset area size. Such as dividing a city into 5 km squares on average.

But furthermore, the case occurrence density of cases with different time and space corresponding to the two areas with the same area size is considered to be greatly different. For example, due to differences in road conditions, traffic density, etc., some streets or geographic locations may be accident-prone locations, i.e., locations where survey cases are often found, while areas with relatively little traffic or motor vehicle travel may have relatively few case occurrences and survey requests.

Therefore, the grids can be reasonably divided according to the occurrence density of the historical cases in the region (instead of the sizes of all grids being consistent), so that the historical case requests of the grids are relatively balanced (not too large or too small), and the resource allocation of later exploration is more convenient.

In addition, in an optional embodiment, for more intuitive display, the case thermal indexes can be calculated according to historical case data in the grid, and different colors are displayed on a preset device (such as a workbench of a survey call manager) according to different case thermal indexes, so that the distribution condition and trend of cases in each grid can be more intuitively acquired, and the efficiency of survey resource scheduling can be further improved.

In step S1036, predicted case distribution data of each of the preset grids is determined according to a preset time sequence estimation model and the historical case data.

Specifically, the timing estimation Model may be ARIMA (Autoregressive Integrated moving average Model), and the working principle and the application process of the ARIMA Model are described below.

First, an ARIMA model, i.e., an autoregressive moving average model, also referred to as ARIMA (p, d, q), is the most common statistical model for time series prediction. As the name implies, the time sequence is a sequence formed by arranging the values of the same statistical index according to the time sequence of occurrence, and in a specific embodiment, the training process of the ARIMA timing model may be as follows:

firstly, acquiring historical case occurrence data, and converting the historical case occurrence data into time sequence data (namely case data occurring at each time point in a historical time period according to a time sequence);

and (3) carrying out standardization processing on the time sequence data to obtain a training sample, inputting the training sample into a preset ARIMA model to train the training sample to obtain a case prediction model for predicting the future case occurrence condition of each grid contained in the whole area.

In step S1038, preset survey resource distribution data is obtained, and a matching degree between the survey resource distribution data and the predicted case distribution data of each target grid is determined.

First, the preset survey resource may be a survey resource of a third party service provider who has entered into a cooperative agreement with the insurance company, and the third party service provider may enter into a cooperative agreement with a plurality of different insurance companies, so that there are characteristics of freedom, dispersion, high mobility, and uncertain availability in using the shared resource.

It is therefore desirable to predict the occurrence of a case at a future time to ensure that available survey resources are selected at the time of the future occurrence of the case.

The specific determination process of the matching degree between the survey resource distribution data and the predicted case distribution data of each target grid may be as follows:

matching the available location and the corresponding available time of each survey resource in the preset survey resources with the number of survey resources required by each location at each time point in the future in each grid, for example: for grid X, it is determined from the output of ARIMA that 50 cases may occur in the future 24, 10 of which are on a street S1 in grid X, 6-11 am. And the coverage (i.e., the job capability) of the existing survey resource corresponding to grid X is 45, and more specifically, the coverage thereof is 5 in 6-11 am of street S1. So that the preset resources and matching degree are present.

In an optional embodiment, each grid area on the scheduling working device can be displayed in different colors according to different matching degrees (which can be understood as the reasonable degree of resource scheduling and the resource shortage degree), so that resource side and background scheduling personnel can intuitively feel the resource supply satisfaction condition.

In step S10310, the associated survey resources corresponding to each preset grid are determined according to the matching degree.

It is easy to understand that as the case happens continuously, the historical case data of each grid is updated continuously in real time, so the possible future case prediction distribution corresponding to each region also changes, i.e. the amount of resources required by each site and the like will change in the future time. If, as is possible with the construction of urban municipalities, certain roads are repaired in a closed manner, the case occurrence for a certain grid is significantly reduced, whereby correspondingly also in the future the exploration resources can be distributed into the grid less (that is to say less exploration resources are associated therewith).

In step S1024, at least one survey resource is determined as a candidate resource according to the target grid and the resource demand information.

It is easy to understand that after the user a has an accident in a certain grid (here, the target grid) and submits the survey request, it needs to find a suitable resource in the survey resources associated with the target grid according to the resource requirement information corresponding to the survey request to perform the final survey operation.

The specific step S1024 may thus comprise steps S1042-S1044 as shown in fig. 3. FIG. 3 shows a flow diagram of the determination of candidate resources in one embodiment.

In step S1042, the association mapping resource information corresponding to the target grid is obtained, and the resource requirement information is matched with the association mapping resource information.

In contrast to the foregoing steps, in determining the associated surveyed resources of each grid, the surveyed resources allocated (i.e., associated) to each grid are reallocated (i.e., scheduled) according to the predicted situation of the future case, where the matching refers to obtaining the relevant resource characteristics (e.g., the location of the resource, the type of accident that the resource can handle, etc.) of the information of the associated surveyed resources, and matching the resource characteristics with the resource requirements.

In step S1044, in case of successful matching, determining the candidate resource according to the matched associated surveyed resource information.

In step S1026, resource feature data of the candidate resource is obtained, and an available resource is determined from the candidate resource according to the resource feature data.

That is, in the case where there are multiple exploration resources that can be scheduled to the grid where the current user is located and can be simultaneously surveyed for a case, further optimization of the determination of the exploration resources is needed, that is, further selection is performed among multiple selectable candidate resources according to parameters that are very relevant to the user experience, such as resource quality, time that the resources can reach, resource cost, and the like.

Thus, in a particular embodiment, the resource characteristic data may include at least two of a quality of service score, a distance from a venue, and service price information.

It is readily understood that there may be two evaluation indicators for the determination of the quality of service score here, one being the evaluation of the relevant behavior of the insurance company for the field work of the surveyor, and on the other hand the evaluation of the services of the surveyor by a user, such as a car owner, directly reflects the user experience.

Thus, the determination of the quality of service score in the resource characterization data may include S1052-S1054 shown in fig. 4. Figure 4 illustrates a flow diagram for determining the quality of service score in one embodiment.

In S1052, service processing information returned by the candidate resource is acquired, and the aging evaluation information of the candidate resource is determined according to the service processing information.

In an alternative embodiment, the service processing information may be, for example, a picture of a survey scene, a card punching time of a survey place, a total survey time, and the like uploaded by each candidate resource through a preset program in each historical survey operation, that is, how time efficiency of each candidate resource is evaluated according to historical operation data of each candidate resource.

More specifically, the determination process of the aging evaluation information herein may include steps S1062-S1064 shown in fig. 5. FIG. 5 illustrates a flow diagram for determining age evaluation information in one embodiment.

In step S1062, the scheduling time, the survey time, and the job time of the candidate resource are determined based on the service processing information.

In step S1064, determining aging evaluation information of the candidate resource according to a preset weight value and according to the scheduling time, the survey time, and the job time.

The above two steps are described by way of example, the average historical scheduling time (i.e., the time from the request to the request acceptance), the time to the survey (i.e., the time from the request acceptance to the case site arrival), and the work time (i.e., the total time from the time to the site arrival to the survey completion) of a survey person K may be 2 minutes, 10 minutes, and 20 minutes, respectively.

Considering that the user is sensitive to the time of the survey, the weighting values corresponding to the scheduling time, the surveying time, and the job time may be 0.1, 0.5, and 0.4, respectively. Thereby correspondingly calculating the time efficiency score of the investigation operation of the investigation personnel K.

In step S1054, service evaluation information corresponding to the candidate resource is acquired, and a service quality score corresponding to the candidate resource is determined according to the service evaluation information and the age evaluation information.

The service evaluation information here may be evaluation information for survey staff, such as a service evaluation score (e.g., 4 stars or 1 star), which is submitted by a user in a preset program.

Similarly, the service quality score corresponding to the candidate resource determined according to the service evaluation information and the aging evaluation information may also be a certain weighted value, which is more critical in consideration of the experience and experience of the user, so that the weighted value of the service evaluation information may be set to be larger when calculating the service quality score.

And finally determining available resources from the candidate resources according to the service characteristic data may include steps S1072-S1074 as shown in fig. 6, where fig. 6 shows a flowchart of determining available resources from the candidate resources in one embodiment.

In step S1072, a competitive score of each of the candidate resources is determined according to a preset weight value and the resource feature data.

That is, the higher the service quality score (representing the higher survey quality), the closer the distance to the site of the risk (representing the faster the resource can arrive at the site), and the more the service price information conforms to the interval selected by the user (the more sensitive and relevant resource characteristics of the user), i.e., the higher the competitive score representing the candidate resource, the more the best survey experience is likely to be brought to the user.

In step S1074, a candidate resource having a competitive score higher than a preset score threshold is determined as the available resource.

In step S1028, the survey request is sent to the available resource, service availability information returned from the available resource within a preset duration is obtained, and a target resource is determined from the available resource according to the service availability information, so that the target survey resource processes the survey request.

It should be noted that, since the freely shared survey personnel may be engaged in other tasks because they are not fully occupied, after determining the available resources corresponding to the suitable current grid (step S1074), further confirmation is needed to determine whether these available resources are in a condition that can accept the survey request.

Thus, similar to the assignment of tasks by the outsiders of the take-away market and the processing of real-time vehicle requests by the taxi-taking software, a preemption action may be initiated within a certain time period (e.g., 5 or 10 minutes) to send a target survey request message to the available resources, i.e., to ask the available resources whether the request can be accepted (i.e., order pickup). In an alternative embodiment, when the survey request is more crowded or the available resources are less, the order taking confirmation time can be prolonged or preset reward information can be sent to the relevant available resources, so that the order dispatching success rate is increased.

After the available resources return the information for confirming order taking or the information for failing to take the order taking, the available and simultaneously suitable exploration resources can be finally determined from the available resources for field operation according to the information whether the current service returned by each available resource is available.

Fig. 7 is a block diagram of an apparatus for grid-based exploration resource scheduling in one embodiment.

Referring to fig. 7, a resource scheduling apparatus 1080 based on grid survey according to an embodiment of the present invention includes: receiving section 1082, first determining section 1084, second determining section 1086, and responding section 1088.

Wherein, receiving unit 1082: the system comprises a data processing module, a data processing module and a resource management module, wherein the data processing module is used for receiving a survey request and determining a target grid and resource demand information corresponding to the survey request;

the first determination unit 1084: the resource demand information is used for determining at least one survey resource as a candidate resource according to the target grid and the resource demand information;

second determination unit 1086: the resource characteristic data is used for acquiring the resource characteristic data of the candidate resources, and available resources are determined from the candidate resources according to the resource characteristic data;

the answering unit 1088: the resource allocation method is used for sending the survey request to the available resources, acquiring service available information returned by the available resources within a preset time length, and determining target resources from the available resources according to the service available information so that the target survey resources process the survey request.

FIG. 8 is a diagram illustrating an internal structure of a computer device in one embodiment. The computer device may specifically be a terminal, and may also be a server. As shown in fig. 8, the computer device includes a processor, a memory and acquisition module, a processing module, a communication module connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may further store a computer program, which, when executed by the processor, causes the processor to implement the present grid-based exploration resource scheduling method. The internal memory may also have stored therein a computer program that, when executed by the processor, causes the processor to perform the method for scheduling resources for a grid-based survey. Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is proposed, comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:

In one embodiment, a computer-readable storage medium is proposed, in which a computer program is stored which, when executed by a processor, causes the processor to carry out the steps of:

Those skilled in the art will appreciate that all or a portion of the processes in the methods of the embodiments described above may be implemented by computer programs that may be stored in a non-volatile computer-readable storage medium, which when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, non-volatile memory may include read-only memory (ROM), programmable ROM (prom), electrically programmable ROM (eprom), electrically erasable programmable ROM (eeprom), or flash memory, volatile memory may include Random Access Memory (RAM) or external cache memory, RAM is available in a variety of forms, such as static RAM (sram), Dynamic RAM (DRAM), synchronous sdram (sdram), double data rate sdram (ddr sdram), enhanced sdram (sdram), synchronous link (sdram), dynamic RAM (rdram) (rdram L), direct dynamic RAM (rdram), and the like, and/or external cache memory.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for scheduling a resource based on a grid, the method comprising:

2. The grid-based survey resource scheduling method of claim 1, wherein the survey request comprises at least two of insurance department information, insurance order number, customer name, contact details, accident location and/or accident type;

the resource demand information comprises at least two items of insurance department information, the accident site, the accident time and the accident type;

the process of determining the target grid corresponding to the survey request comprises:

and determining a corresponding grid as the target grid according to the accident site.

3. The grid-based survey resource scheduling method of claim 1, wherein prior to receiving a survey request, determining a target grid to which said survey request corresponds, further comprising:

acquiring historical case data, wherein the historical case data comprises at least two items of historical case time, historical case location, historical accident type and historical accident safety information;

determining a plurality of preset grids according to the historical case data;

determining predicted case distribution data of each preset grid according to a preset time sequence estimation model and the historical case data;

acquiring preset survey resource distribution data, and determining the matching degree of the survey resource distribution data and the predicted case distribution data of each target grid;

and determining the associated survey resources corresponding to each preset grid according to the matching degree.

4. The grid-based exploration resource scheduling method of claim 3, wherein said process of determining at least one exploration resource as a candidate resource from said target grid and resource demand information comprises:

acquiring associated survey resource information corresponding to the target grid, and matching the resource demand information with the associated survey resource information;

and under the condition that the matching is successful, determining the candidate resource according to the matched associated survey resource information.

5. The grid-based exploration resource scheduling method of claim 1, wherein said resource characteristic data comprises at least two of quality of service score, distance to a place of venture, service price information, and said process of determining available resources from said candidate resources based on said service characteristic data comprises:

determining the competitive power score of each candidate resource according to a preset weight value and the resource characteristic data;

determining candidate resources with a competitive score higher than a preset score threshold as the available resources.

6. The grid-based exploration resource scheduling method of claim 5, wherein said quality of service score determination process comprises:

acquiring service processing information returned by the candidate resource, and determining the time efficiency evaluation information of the candidate resource according to the service processing information;

and acquiring service evaluation information corresponding to the candidate resources, and determining the service quality scores corresponding to the candidate resources according to the service evaluation information and the time efficiency evaluation information.

7. The grid-based exploration resource scheduling method of claim 6, wherein said process of determining aging evaluation information of said candidate resource from said service processing information comprises:

determining the scheduling time, the prospecting time and the operation time of the candidate resources according to the service processing information;

and according to a preset weight value, determining the time efficiency evaluation information of the candidate resource according to the scheduling time, the exploration time and the job time.

8. An apparatus for scheduling a grid-based survey resource, the apparatus comprising:

9. A readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method according to any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 7.