CN112307335A - Vehicle service information pushing method, device and equipment and vehicle - Google Patents

Vehicle service information pushing method, device and equipment and vehicle Download PDF

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Publication number
CN112307335A
CN112307335A CN202011182497.5A CN202011182497A CN112307335A CN 112307335 A CN112307335 A CN 112307335A CN 202011182497 A CN202011182497 A CN 202011182497A CN 112307335 A CN112307335 A CN 112307335A
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data
service information
vehicle
processing
information
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Inventor
高洪伟
韩爽
吕贵林
孙玉洋
王文彬
李新超
娄泰
付雷
吴琼
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FAW Group Corp
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FAW Group Corp
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/211—Schema design and management
    • G06F16/212—Schema design and management with details for data modelling support
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/55—Push-based network services

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  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

The embodiment of the invention discloses a vehicle service information pushing method, a vehicle service information pushing device, vehicle service information pushing equipment and a vehicle. The method comprises the following steps: acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data; processing the multi-source data to obtain a processing result; determining scene information and event information of the current vehicle according to the processing result; determining service information according to the scene information, the event information and the user portrait data; and sending the service information to a terminal. The vehicle service information pushing method provided by the embodiment of the invention can intelligently push service information to a user according to the collected multi-source data, and provides personalized vehicle using experience for the user.

Description

Vehicle service information pushing method, device and equipment and vehicle
Technical Field
The embodiment of the invention relates to the technical field of intelligent vehicles, in particular to a method, a device and equipment for pushing vehicle service information and a vehicle.
Background
Automobile personalization is an innovative extension centered on customers, and with the continuous development of automobile intellectualization, consumers increasingly strongly demand personalized automobiles.
Disclosure of Invention
The embodiment of the invention provides a vehicle service information pushing method, device and equipment and a vehicle, and provides personalized vehicle using experience for a user.
In a first aspect, an embodiment of the present invention provides a method for pushing vehicle service information, including:
acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data;
processing the multi-source data to obtain a processing result;
determining scene information and event information of the current vehicle according to the processing result;
determining service information according to the scene information, the event information and the user portrait data;
and sending the service information to a terminal.
Further, processing the multi-source data to obtain a processing result, including:
filtering the multi-source data based on a set filtering table;
shunting the filtered data to different processing threads according to types;
each processing thread performs ETL processing on the shunted data in parallel; the ETL processing comprises: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
Furthermore, the user portrait data is acquired in the following manner:
acquiring offline multi-source data;
extracting, cleaning and standardizing the off-line multi-source data according to the requirements of a sliding model;
and performing data modeling analysis on the processed data, and obtaining a target data model and training result data through multiple rounds of iterative training and model optimization.
Further, determining scene information and event information of the current vehicle according to the processing result, including:
matching the processing result with a preset scene rule to obtain scene information;
and matching the processing result with a preset event rule to obtain event information.
Further, the sending the service information to the terminal includes:
determining a content template according to the service, and calculating parameters required by the template;
and loading the service information into the content template based on the parameters, and sending the loaded service information to a terminal.
Further, the sending the service information to the terminal includes:
and sending the service information to a terminal in a JSON character string mode. .
In a second aspect, an embodiment of the present invention further provides a vehicle service information pushing device, including:
the multi-source data acquisition module is used for acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data;
the data processing module is used for processing the multi-source data to obtain a processing result;
the scene and event information determining module is used for determining scene information and event information of the current vehicle according to the processing result;
the service information determining module is used for determining service information according to the scene information, the event information and the user portrait data;
and the service information sending module is used for sending the service information to the terminal.
Further, the data processing module is further configured to:
filtering the multi-source data based on a set filtering table;
shunting the filtered data to different processing threads according to types;
each processing thread performs ETL processing on the shunted data in parallel; the ETL processing comprises: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the pushing method of the vehicle service information according to the embodiment of the present invention when executing the program.
In a fourth aspect, the embodiment of the invention further provides a vehicle, which includes a vehicle service information pushing device, where the pushing of the vehicle service information is used to implement the vehicle service information pushing method according to the embodiment of the invention.
The embodiment of the invention discloses a vehicle service information pushing method, a vehicle service information pushing device, vehicle service information pushing equipment and a vehicle. Acquiring multi-source data; processing the multi-source data to obtain a processing result; determining scene information and event information of the current vehicle according to the processing result; determining service information according to the scene information, the event information and the user portrait data; and sending the service information to the terminal. The vehicle service information pushing method provided by the embodiment of the invention can intelligently push service information to a user according to the collected multi-source data, and provides personalized vehicle using experience for the user.
Drawings
Fig. 1 is a flowchart of a method for pushing vehicle service information according to a first embodiment of the present invention;
FIG. 2 is an exemplary diagram of processing multi-source data in accordance with one embodiment of the invention;
fig. 3 is an exemplary diagram of determining service information according to one embodiment of the present invention;
fig. 4 is an exemplary diagram of aggregated service information in a first embodiment of the present invention;
fig. 5 is a schematic structural diagram of a vehicle service information pushing device according to a second embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a computer device according to a third embodiment of the present invention;
fig. 7 is a schematic structural diagram of a vehicle according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for pushing vehicle service information according to an embodiment of the present invention, where the embodiment is applicable to a case where service information is intelligently pushed to a user, and the method may be executed by a device for pushing vehicle service information, as shown in fig. 1, where the method specifically includes the following steps:
the precondition of the invention is as follows: the vehicle TBOX SIM card is opened (namely, the vehicle can be used in a networking mode), the vehicle is powered on, a user logs in a vehicle account, and the vehicle can receive cloud push messages.
And step 110, acquiring multi-source data.
The multi-source data comprises user data, vehicle data, fault data and third-party ecological data. User data, vehicle data and fault data can be acquired by integrating a data acquisition tool in the equipment terminal, and are acquired in a periodic triggering or event triggering mode. The third-party ecological data comprises but is not limited to weather data, merchant data, map data and the like, and is obtained through an HTTP API (hyper text transport protocol API) interface between cloud platforms. According to the embodiment, the acquired multi-source data can be uploaded to a cloud service platform to be stored and processed, so that the data can be analyzed and processed in a later period.
And step 120, processing the multi-source data to obtain a processing result.
In this embodiment, the multi-source data is processed, and the process of obtaining the processing result may be: filtering the multi-source data based on a set filtering table; shunting the filtered data to different processing threads according to types; each processing thread performs ETL processing on the shunted data in parallel; the ETL treatment comprises the following steps: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
For example, fig. 2 is an exemplary diagram of processing multi-source data in the present embodiment. As shown in FIG. 2, the collected multi-source data is first sent to kafka, and the real-time task listens to kafka Topic and consumes the data in kafka. And then, according to a user behavior filtering table stored in the Redis table, data screening is carried out on data obtained by Kafka consumption, a data source required by the intelligent recommendation service is selected, and the program execution efficiency is improved. The filtered data has the problems of noise data, data loss and the like, for example, when a vehicle is flamed out in a garage, a flameout event is triggered, but flameout information cannot be reported in time due to reasons such as a vehicle network, and the like, at this time, the data needs to be repaired through a data compensation mechanism, so that ETL processing needs to be performed on the data, including operations of data extraction, conversion, missing value processing, noise data smoothing, outlier deletion, data inconsistency resolution and the like, and finally a target data index set required by the recommendation rule engine is obtained.
And step 130, determining scene information and event information of the current vehicle according to the processing result.
In this embodiment, the scene information may include a car-using scene and a car-using scene. Wherein, with big scene of car includes: commuting to work, traveling and daily; the scene with the car includes: getting on, on the way, near the destination and before leaving the car after parking. The permutation and combination of the large vehicle-using scene and the sub-vehicle-using scene are 16 scenes in total, the whole vehicle-using scene of a user can be covered, and only one scene meets the condition at the same time, and the scenes are mutually exclusive.
Specifically, the method for determining the scene information and the event information of the current vehicle according to the processing result may be: matching the processing result with a preset scene rule to obtain scene information; and matching the processing result with a preset event rule to obtain event information.
The scenes are divided into a large scene and a small scene, the large scene comprises a commuting on-duty scene, a commuting off-duty scene, a travel scene and a daily scene, the small scene comprises an getting-on scene, a passing scene, a scene near a destination and a scene before a vehicle leaves after parking, the scene ID is the large scene ID + the sub-scene ID, for example, the large scene ID is 1001, and the small scene ID is 1002, then the scene ID is 10011002.
The event is a trigger condition of intelligent recommendation, and when the event trigger condition is met, the required recommendation service is judged based on the current scene. The events include but are not limited to insufficient fuel, insufficient power, fatigue driving, rain, snow and the like, for example, the judgment condition of insufficient fuel is that the fuel is less than 10% or 20%, the specific value depends on the scene, for the travel scene, the condition of insufficient fuel is met when the fuel is less than 20%, the recommended gas station is triggered, and the condition of insufficient fuel is met when the fuel is less than 10% in the rest scenes.
Step 140, determining service information according to the scene information, the event information and the user portrait data.
The user portrait data acquisition mode is as follows: acquiring offline multi-source data; extracting, cleaning and standardizing the off-line multi-source data according to the requirements of the sliding model; and performing data modeling analysis on the processed data, and obtaining a target data model and training result data through multiple rounds of iterative training and model optimization.
Specifically, multi-source data in the HDFS system is read and stored into a Redis cache. The method comprises the following steps of extracting, cleaning, standardizing and the like multi-source data, and extracting specified offline data according to the requirements of an image model, for example: acquiring food information (food retrieval information, food classification information and the like) in the buried point data aiming at the food preference; according to the vehicle data, the starting point and the end point of the user track are identified according to the driving state in the data, data in the Hive table are extracted, the user driving track data are obtained, dirty data such as invalid data and missing data are filtered, the data are subjected to standardization processing, and the data are stored in the Hive table. And then: and (3) performing data modeling analysis on the preprocessed preference data by combining with actual business requirements, and obtaining a target data model and training result data through multiple rounds of iterative training and model optimization, wherein the model comprises but is not limited to a home position, a company position, working hours, working routes, delicates, scenic spot preferences, hotel preferences, oil product preferences, entertainment preferences and the like. And finally, providing a user portrait query interface according to the service requirement definition, packaging the REST API for data release, supporting a request in an http post mode, carrying out logic analysis and judgment on the obtained result after the release module receives the request, and returning the result.
In this embodiment, the service information may be determined based on a recommendation rule engine. The recommendation rule engine is a component embedded in an application program, and the rule engine performs rule matching on a data set obtained by real-time data processing by reading drl recommendation rule files, and judges a matching result, so that recommended services are determined.
Exemplarily, fig. 3 is an exemplary diagram of determining service information in this embodiment. As shown in FIG. 3, when context information and event information are known, recommended service information is triggered in conjunction with user profile data. For example, in a commute work scene, an oil shortage event occurs, and a recommended gas station is triggered. Recommended services include, but are not limited to, gas stations, charging piles, gouges, attractions, hotels, music, radio stations, etc.
Step 150, the service information is sent to the terminal.
Specifically, the manner of sending the service information to the terminal may be: determining a content template according to the service, and calculating parameters required by the template; and loading the service information into the content template based on the parameters, and sending the loaded service information to the terminal.
In this embodiment, the service information may be aggregated by using a content aggregation module. Fig. 4 is an exemplary diagram of aggregated service information in the present embodiment. As shown in fig. 4, according to the recommendation service, a corresponding content template is selected, parameters required by the template are calculated, and the message content is assembled and sent to the message channel. For example, when a gas station is recommended, the message content is "is fuel low, is the nearest a gas station B kilometers away, is you going to navigate how to refuel in the past? ", where A is the gas station classification obtained according to the user's oil preference, and B is the straight-line distance calculated according to the latitude and longitude of the nearest gas station and the user's current location.
Optionally, the service information may be sent to the terminal in a JSON string manner. After receiving the service information, the terminal analyzes the message content sent by the cloud, identifies the message display modes including but not limited to popup windows/cards/voice and the like, finally displays the message to the user and interacts with the user.
According to the technical scheme, multi-source data are processed to obtain a processing result; determining scene information and event information of the current vehicle according to the processing result; determining service information according to the scene information, the event information and the user portrait data; and sending the service information to the terminal. The vehicle service information pushing method provided by the embodiment of the invention can intelligently push service information to a user according to the collected multi-source data, and provides personalized vehicle using experience for the user.
Example two
Fig. 5 is a schematic structural diagram of a vehicle service information pushing device according to a second embodiment of the present invention, and as shown in fig. 5, the device includes: the system comprises a multi-source data acquisition module 210, a data processing module 220, a scene and event information determination module 230, a service information determination module 240 and a service information sending module 250.
A multi-source data obtaining module 210 for obtaining multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data;
the data processing module 220 is configured to process multi-source data to obtain a processing result;
a scene and event information determining module 230, configured to determine scene information and event information of the current vehicle according to the processing result;
a service information determining module 240 for determining service information according to the scene information, the event information, and the user portrait data;
a service information sending module 250, configured to send the service information to the terminal.
Optionally, the data processing module 220 is further configured to:
filtering the multi-source data based on a set filtering table;
shunting the filtered data to different processing threads according to types;
each processing thread performs ETL processing on the shunted data in parallel; the ETL treatment comprises the following steps: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
Optionally, the user portrait data is obtained in the following manner:
acquiring offline multi-source data;
extracting, cleaning and standardizing the off-line multi-source data according to the requirements of the sliding model;
and performing data modeling analysis on the processed data, and obtaining a target data model and training result data through multiple rounds of iterative training and model optimization.
Optionally, the scene and event information determining module 230 is further configured to:
matching the processing result with a preset scene rule to obtain scene information;
and matching the processing result with a preset event rule to obtain event information.
Optionally, the service information sending module 250 is further configured to:
determining a content template according to the service, and calculating parameters required by the template;
and loading the service information into the content template based on the parameters, and sending the loaded service information to the terminal.
Optionally, the service information sending module 250 is further configured to:
and sending the service information to the terminal in a JSON character string mode.
The device can execute the methods provided by all the embodiments of the invention, and has corresponding functional modules and beneficial effects for executing the methods. For details not described in detail in this embodiment, reference may be made to the methods provided in all the foregoing embodiments of the present invention.
EXAMPLE III
Fig. 6 is a schematic structural diagram of a computer device according to a third embodiment of the present invention. FIG. 6 illustrates a block diagram of a computer device 312 suitable for use in implementing embodiments of the present invention. The computer device 312 shown in FIG. 6 is only an example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention. The device 312 is a typical push-enabled computing device for vehicle service information.
As shown in FIG. 6, computer device 312 is in the form of a general purpose computing device. The components of computer device 312 may include, but are not limited to: one or more processors 316, a storage device 328, and a bus 318 that couples the various system components including the storage device 328 and the processors 316.
Bus 318 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.
Computer device 312 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer device 312 and includes both volatile and nonvolatile media, removable and non-removable media.
Storage 328 may include computer system readable media in the form of volatile Memory, such as Random Access Memory (RAM) 330 and/or cache Memory 332. The computer device 312 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 334 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard drive"). Although not shown in FIG. 6, 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 Compact disk-Read Only Memory (CD-ROM), a Digital Video disk (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 318 by one or more data media interfaces. Storage 328 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.
Program 336 having a set (at least one) of program modules 326 may be stored, for example, in storage 328, such program modules 326 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which may comprise an implementation of a network environment, or some combination thereof. Program modules 326 generally carry out the functions and/or methodologies of embodiments of the invention as described herein.
The computer device 312 may also communicate with one or more external devices 314 (e.g., keyboard, pointing device, camera, display 324, etc.), with one or more devices that enable a user to interact with the computer device 312, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 312 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 322. Also, computer device 312 may communicate with one or more networks (e.g., a Local Area Network (LAN), Wide Area Network (WAN), etc.) and/or a public Network, such as the internet, via Network adapter 320. As shown, network adapter 320 communicates with the other modules of computer device 312 via bus 318. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the computer device 312, including but not limited to: microcode, device drivers, Redundant processing units, external disk drive Arrays, disk array (RAID) systems, tape drives, and data backup storage systems, to name a few.
The processor 316 executes various functional applications and data processing by executing programs stored in the storage device 328, for example, implementing the push method of vehicle service information provided by the above-described embodiment of the present invention.
Example four
Fig. 7 is a schematic structural diagram of a vehicle according to an embodiment of the present invention, and as shown in fig. 7, the vehicle includes a vehicle service information push device according to an embodiment of the present invention, the device includes: the multi-source data acquisition module is used for acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data; the data processing module is used for processing the multi-source data to obtain a processing result; the scene and event information determining module is used for determining scene information and event information of the current vehicle according to the processing result; the service information determining module is used for determining service information according to the scene information, the event information and the user portrait data; and the service information sending module is used for sending the service information to the terminal.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A method for pushing vehicle service information is characterized by comprising the following steps:
acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data;
processing the multi-source data to obtain a processing result;
determining scene information and event information of the current vehicle according to the processing result;
determining service information according to the scene information, the event information and the user portrait data;
and sending the service information to a terminal.
2. The method of claim 1, wherein processing the multi-source data to obtain a processing result comprises:
filtering the multi-source data based on a set filtering table;
shunting the filtered data to different processing threads according to types;
each processing thread performs ETL processing on the shunted data in parallel; the ETL processing comprises: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
3. The method of claim 1, wherein the user representation data is obtained by:
acquiring offline multi-source data;
extracting, cleaning and standardizing the off-line multi-source data according to the requirements of a sliding model;
and performing data modeling analysis on the processed data, and obtaining a target data model and training result data through multiple rounds of iterative training and model optimization.
4. The method of claim 1, wherein determining scene information and event information of the current vehicle according to the processing result comprises:
matching the processing result with a preset scene rule to obtain scene information;
and matching the processing result with a preset event rule to obtain event information.
5. The method of claim 1, wherein sending the service information to a terminal comprises:
determining a content template according to the service, and calculating parameters required by the template;
and loading the service information into the content template based on the parameters, and sending the loaded service information to a terminal.
6. The method of claim 1, wherein sending the service information to a terminal comprises:
and sending the service information to a terminal in a JSON character string mode.
7. A vehicle service information pushing device is characterized by comprising:
the multi-source data acquisition module is used for acquiring multi-source data; the multi-source data comprises user data, vehicle data, fault data and third-party ecological data;
the data processing module is used for processing the multi-source data to obtain a processing result;
the scene and event information determining module is used for determining scene information and event information of the current vehicle according to the processing result;
the service information determining module is used for determining service information according to the scene information, the event information and the user portrait data;
and the service information sending module is used for sending the service information to the terminal.
8. The apparatus of claim 7, wherein the data processing module is further configured to:
filtering the multi-source data based on a set filtering table;
shunting the filtered data to different processing threads according to types;
each processing thread performs ETL processing on the shunted data in parallel; the ETL processing comprises: data extraction, conversion, missing value processing, noise data smoothing, outlier deletion and data inconsistency resolution.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method for pushing vehicle service information according to any one of claims 1 to 6.
10. A vehicle, characterized by comprising a vehicle service information pushing device, wherein the pushing of the vehicle service information is used for realizing the vehicle service information pushing method according to any one of claims 1-6.
CN202011182497.5A 2020-10-29 2020-10-29 Vehicle service information pushing method, device and equipment and vehicle Pending CN112307335A (en)

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Cited By (5)

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Publication number Priority date Publication date Assignee Title
CN113010773A (en) * 2021-02-22 2021-06-22 东风小康汽车有限公司重庆分公司 Information pushing method and equipment
CN113194442A (en) * 2021-05-09 2021-07-30 深圳市迈鸿车联网服务有限公司 Internet of vehicles interactive platform of wisdom car
CN113536065A (en) * 2021-07-15 2021-10-22 江苏小牛电动科技有限公司 Method, device and system for determining state of vehicle event and storage medium
CN114407652A (en) * 2022-01-19 2022-04-29 亿咖通(湖北)技术有限公司 Information display method, device and equipment
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Publication number Priority date Publication date Assignee Title
CN113010773A (en) * 2021-02-22 2021-06-22 东风小康汽车有限公司重庆分公司 Information pushing method and equipment
CN113194442A (en) * 2021-05-09 2021-07-30 深圳市迈鸿车联网服务有限公司 Internet of vehicles interactive platform of wisdom car
CN113536065A (en) * 2021-07-15 2021-10-22 江苏小牛电动科技有限公司 Method, device and system for determining state of vehicle event and storage medium
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CN114407652A (en) * 2022-01-19 2022-04-29 亿咖通(湖北)技术有限公司 Information display method, device and equipment
CN114407652B (en) * 2022-01-19 2024-04-12 亿咖通(湖北)技术有限公司 Information display method, device and equipment
WO2023241388A1 (en) * 2022-06-14 2023-12-21 中国第一汽车股份有限公司 Model training method and apparatus, energy replenishment intention recognition method and apparatus, device, and medium

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Application publication date: 20210202