Internet of vehicles data processing method and device, electronic equipment and storage medium

Abstract

The invention discloses an Internet of Vehicles data processing method and device, electronic equipment and a storage medium. The Internet of Vehicles data processing method is applied to a server, and comprises the following steps: acquiring to-be-processed vehicle data; obtaining a vehicle identifier from the to-be-processed vehicle data; processing the vehicle identifier according to a data processing node in the distributed system to obtain a storage identifier; sending the to-be-processed vehicle data to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the to-be-processed vehicle data; and storing the vehicle data of the same storage identifier into the same data processing node. According to the technical scheme of the embodiment of the invention, the processing of the Internet of Vehicles data is more efficient and orderly, the balance and order of the storage of the Internet of Vehicles data are realized, and the query efficiency of the Internet of Vehicles data is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, electronic device and storage medium for processing data of an Internet of Vehicles. Background Art

[0002] With the continuous development of intelligent connected car technology, a huge amount of connected vehicle data is generated. Efficient processing of connected vehicle data can provide support for safer, more efficient and intelligent traffic management and driving experience.

[0003] At present, a distributed big data technology is generally used to process massive amounts of Internet of Vehicles data.

[0004] However, when processing massive amounts of Internet of Vehicles data based on distributed big data technology, the data is unevenly distributed on each data processing node, and the Internet of Vehicles data is randomly distributed on different nodes, which brings inconvenience to subsequent data processing and query, and increases the complexity and delay of the system. Summary of the invention

[0005] The present invention provides a vehicle networking data processing method, device, electronic device and storage medium, which can improve the overall performance and efficiency of the system.

[0006] According to one aspect of the present invention, a method for processing Internet of Vehicles data is provided, which is applied to a server and includes:

[0007] Obtain vehicle data to be processed;

[0008] Obtaining a vehicle identification from vehicle data to be processed;

[0009] According to the data processing node in the distributed system, the vehicle identification is processed to obtain a storage identification;

[0010] Sending the vehicle data to be processed to the data processing node corresponding to the storage identifier so that the corresponding data processing node writes the vehicle data to be processed;

[0011] Vehicle data with the same storage identifier is stored in the same data processing node.

[0012] According to another aspect of the present invention, a vehicle networking data processing device is provided, comprising:

[0013] A data acquisition module, used to acquire vehicle data to be processed;

[0014] An identification extraction module, used for obtaining a vehicle identification from vehicle data to be processed;

[0015] An identification processing module, used to process the vehicle identification according to the data processing node in the distributed system to obtain a storage identification;

[0016] A data distribution module, used for sending the vehicle data to be processed to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the vehicle data to be processed;

[0017] The storage management module is used to store vehicle data with the same storage identifier in the same data processing node.

[0018] According to another aspect of the present invention, a vehicle networking data processing device is provided, comprising:

[0019] The data receiving and distributing module is used to receive the vehicle data to be processed sent by the server; the data processing node corresponds to the storage identifier of the vehicle data to be processed, and the storage identifier obtains the vehicle data to be processed through the server; obtains the vehicle identifier from the vehicle data to be processed; processes the vehicle identifier according to the data processing node in the distributed system; and stores the vehicle data with the same storage identifier in the same data processing node;

[0020] A data fusion module is used to fuse the vehicle data to be processed with the pre-collected vehicle data to obtain the vehicle data of each vehicle;

[0021] The data sorting and storage module is used to sort and store the vehicle data of each vehicle according to the vehicle identification and time stamp of the vehicle data of each vehicle.

[0022] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0023] at least one processor; and

[0024] a memory communicatively connected to at least one processor; wherein,

[0025] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the vehicle network data processing method of any embodiment of the present invention.

[0026] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle network data processing method of any embodiment of the present invention when executed.

[0027] The technical solution of the embodiment of the present invention processes the vehicle identification to obtain the storage identification, and sends the vehicle data to be processed to the data processing node corresponding to the storage identification, thereby ensuring that the vehicle data with the same storage identification are centrally stored on the same data processing node, ensuring the consistency and integrity of the vehicle data at the same data processing node, and reducing errors or conflicts caused by uneven vehicle data; by storing the vehicle data with the same storage identification in the same data processing node, the system can centrally store all data of the same vehicle in the same node, reducing the complexity brought by the decentralized data storage, making subsequent data processing and query more convenient and efficient, and improving the response speed and processing capability of the system.

[0028] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 is a flow chart of a method for processing Internet of Vehicles data provided according to Embodiment 1 of the present invention;

[0031] Figure 2 is a flow chart of a method for processing Internet of Vehicles data provided according to Embodiment 2 of the present invention;

[0032] Figure 3a is a flowchart of a method for processing Internet of Vehicles data provided according to Embodiment 3 of the present invention;

[0033] Figure 3b is a flowchart of a method for processing Internet of Vehicles data provided according to Embodiment 3 of the present invention;

[0034] Figure 4 It is a structural schematic diagram of a vehicle networking data processing device provided by a fourth embodiment of the present invention;

[0035] Figure 5 It is a structural schematic diagram of a vehicle networking data processing device provided by Embodiment 5 of the present invention;

[0036] Figure 6 It is a structural schematic diagram of an electronic device for implementing the vehicle networking data processing method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0039] Embodiment 1

[0040] Figure 1 This is a flow chart of a method for processing Internet of Vehicles data provided according to Embodiment 1 of the present invention. This embodiment is applicable to situations where large-scale Internet of Vehicles data needs to be efficiently processed, stored, and managed. The method can be executed by an Internet of Vehicles data processing device, which can be implemented in the form of hardware and / or software, and can be configured in a server device.

[0041] See also Figure 1 The vehicle networking data processing method shown includes:

[0042] S110: Obtain vehicle data to be processed.

[0043] Among them, vehicle data refers to various data generated by the vehicle during operation, including vehicle status data, engine operation data, sensor data, location information, speed information, driving behavior, fault codes and environmental information. Vehicle data is collected by internal sensors and external communication devices of the vehicle. The role of vehicle data is to realize real-time monitoring of the vehicle, driving behavior analysis, navigation location services, vehicle maintenance management, traffic management and various Internet of Vehicles services. For example, the engine operation data in the vehicle data includes engine speed, temperature and fuel consumption, which can be used to monitor the health of the engine, conduct fault warning and maintenance planning; the location information in the vehicle data refers to the GPS positioning of the vehicle, which is used for navigation and real-time traffic monitoring.

[0044] Among them, obtaining the vehicle data to be processed may refer to the fact that in the vehicle networking data processing method, first, the vehicle-related data to be processed needs to be collected or received from various sources. The data acquisition methods include capturing by internal vehicle sensors, uploading by vehicle-mounted devices, and transmitting through wireless communication networks; these data include vehicle status data, engine operation data, sensor data, location information, speed information, driving behavior, fault codes, and environmental information. For example, during the driving process of the vehicle, the on-board diagnostic system collects the engine's operating status data in real time, such as engine speed, vehicle speed, and fuel consumption, and uploads it to the cloud server through the on-board 4G module.

[0045] By acquiring the vehicle data to be processed, vehicle data can be obtained in advance, which can lay a good foundation for subsequent data processing and analysis, and avoid inefficiency caused by data missing or delays during the data processing process; by acquiring vehicle data in real time, the integrity and real-time nature of the data can be guaranteed, which helps to promptly discover and deal with problems; by acquiring and processing vehicle data in real time, abnormal situations in vehicle operation can be promptly discovered and dealt with, enhancing the reliability and safety of the system.

[0046] Optionally, obtaining the vehicle data to be processed includes obtaining vehicle data of at least one vehicle; randomly distributing and storing the vehicle data collected from each vehicle on at least one storage node; and reading the vehicle data to be processed from each storage node.

[0047] Among them, a storage node refers to an independent unit used to store and manage data in a distributed system. Each storage node has its own storage resources and processing capabilities, and can independently store data and respond to data access requests. The role of a storage node is to store data in a distributed system and manage the data, including operations such as reading, writing, backing up, and restoring data. For example, in a vehicle networking system, a large amount of vehicle data generated by vehicles needs to be effectively stored and managed, such as the real-time location, speed, and direction of the vehicle, and the system distributes this data on multiple storage nodes.

[0048] Acquiring vehicle data of at least one vehicle may refer to collecting and acquiring vehicle data generated by one or more vehicles. This step is the starting point of the entire data processing process, ensuring that the system has sufficient raw data for subsequent processing. Exemplarily, in the Internet of Vehicles system, each vehicle is equipped with multiple sensors for real-time monitoring of vehicle operating status and other information. The Internet of Vehicles system acquires multiple vehicle data from vehicle A. At the same time, the Internet of Vehicles system also acquires similar vehicle data from vehicles B and C, etc. These vehicle data will be used as data to be processed and input into the system for subsequent processing and analysis.

[0049] Randomly distributing and storing the vehicle data collected from each vehicle on at least one storage node may mean that in a distributed system, in order to avoid load imbalance and performance bottlenecks caused by the centralized storage of vehicle data, the system will randomly distribute and store the data collected from each vehicle on more than one storage node to achieve load balancing and improve the overall performance and reliability of the system. Exemplarily, the Internet of Vehicles system has three storage nodes A, B, and C, and collects corresponding vehicle data from vehicle 1, vehicle 2, and vehicle 3, wherein the data of vehicle 1 may be distributed to storage nodes A and C, the data of vehicle 2 may be distributed to storage nodes B and A, and the data of vehicle 3 may be distributed to storage nodes C and B. The specific distribution depends on the random distribution algorithm of the system.

[0050] Reading the vehicle data to be processed from each storage node can mean that in a distributed system, when vehicle data needs to be processed, the system will read the vehicle data to be processed from each storage node that previously stored the data. Since the vehicle data is distributed and stored, it is necessary to collect the vehicle data from multiple storage nodes for unified processing and analysis. For example, the data of vehicle 1 is distributed on storage nodes A and C, and the system will read the relevant parts of the data from storage nodes A and C respectively, and then process them; similarly, if the data of vehicle 2 and vehicle 3 are distributed on multiple storage nodes, the data will also be read from the corresponding storage nodes respectively, and then processed.

[0051] By acquiring vehicle data of at least one vehicle; randomly distributing and storing the vehicle data collected by each vehicle on at least one storage node; and reading the vehicle data to be processed from each storage node, the flexibility and adaptability of the Internet of Vehicles system are improved, and it is able to process vehicle data from different quantities and types according to actual needs and adapt to Internet of Vehicles environments of different sizes; it avoids the concentrated storage of vehicle data in one or a few nodes, prevents node overload, and improves the overall performance of the system; through parallel reading, the time for data reading is reduced, the efficiency of data processing is improved, and when a node fails, data can be read from other nodes to ensure the continuity of data processing and the high availability of the system; as the amount of vehicle data increases, the capacity and performance of the system can be expanded by adding storage nodes to meet large-scale data processing needs; the Internet of Vehicles system can flexibly adjust the number and configuration of storage nodes to adapt to changing data processing needs.

[0052] Optionally, obtaining vehicle data of at least one vehicle includes obtaining, from a message queue, vehicle data uploaded by at least one vehicle within a target time period, where the target time period is determined based on performance of the server.

[0053] Among them, a message queue refers to a data structure used to pass messages in a distributed system, allowing applications to communicate asynchronously, that is, the message sender sends the message to the queue, and the receiver reads the message from the queue. Message queues usually support features such as persistence, order guarantee, load balancing, and high fault tolerance. The role of a message queue is to decouple the components that send and receive messages, so that the sender and the receiver do not need to run synchronously, reducing the dependency between system components; through the message queue, the system can dynamically allocate tasks according to processing power, thereby balancing the load and avoiding overloading of a single component; the message queue supports message persistence and retry mechanisms to ensure that messages are not lost and improve the reliability of the system; the message queue can expand or shrink without affecting other parts of the system, improving the flexibility and scalability of the system. Exemplary, the message subscription and publishing system can be Kafka.

[0054] Wherein, obtaining the vehicle data of at least one vehicle includes obtaining the vehicle data uploaded by at least one vehicle within the target duration from the message queue. The target duration is determined according to the performance of the server and may refer to the system reading data from the message queue. The vehicle data uploaded by the vehicle is first placed in the message queue to ensure that the read data contains at least one vehicle data. According to the processing capacity of the server (such as CPU and memory, etc.), the time range for reading the vehicle data is dynamically determined to ensure that the server is not overloaded when processing the vehicle data. Exemplarily, a vehicle networking system has a message queue for receiving real-time vehicle data uploaded by vehicles. A vehicle uploads multiple vehicle data within 10 seconds. These vehicle data will be placed in the message queue. The system reads all vehicle data within these 10 seconds from the message queue for processing to ensure the timeliness of the data and the stability of the system.

[0055] By obtaining the vehicle data uploaded by at least one vehicle within the target time from the message queue, the target time is determined according to the performance of the server to ensure reliable data transmission and processing, avoid data loss and processing delays; the system can flexibly adjust the target time according to actual needs and server performance to improve the system's adaptability and scalability.

[0056] S120: Obtain a vehicle identification from the vehicle data to be processed.

[0057] Among them, the vehicle identification is used to uniquely identify each vehicle. In the Internet of Vehicles data processing method, the vehicle identification can be a unique name, string or digital sequence used to identify a specific vehicle. The role of the vehicle identification is to ensure that each vehicle has a unique identity in the Internet of Vehicles system, which facilitates the accurate tracking and processing of the data of each vehicle. Through the vehicle identification, specific vehicle data can be quickly located and queried to avoid traversing all vehicle data. Exemplarily, the vehicle identification can be a vehicle identification number (VIN), a license plate number, or other unique identifiers.

[0058] Wherein, obtaining the vehicle identification from the vehicle data to be processed may refer to first collecting vehicle data from vehicle sensors, vehicle systems or other sources, and the data contains various information, such as the vehicle's operating status, location data and sensor readings, etc.; parsing the collected vehicle data and finding the vehicle identification contained therein. Exemplarily, when parsing information from the vehicle data to be processed, a field containing VIN is found, and a set of vehicle data contains multiple fields, one of which is VIN, such as "1HGCM82633A123456", and the field is used as the vehicle identification.

[0059] By obtaining the vehicle identification from the vehicle data to be processed, the vehicle identification is extracted to ensure that each data record can uniquely correspond to a specific vehicle, avoiding data confusion and repeated processing; the vehicle identification can quickly locate and associate vehicle data, improve the efficiency of data processing, and in distributed systems, help with efficient distribution and management of data; the unique vehicle identification allows the system to accurately manage and track different vehicle data, which is helpful for subsequent data analysis, troubleshooting and performance optimization; it improves data management capabilities and supports more refined and intelligent Internet of Vehicles applications.

[0060] S130. Process the vehicle identification according to the data processing node in the distributed system to obtain a storage identification.

[0061] Among them, a distributed system refers to a system in which multiple computing nodes work together through a network connection to complete tasks. These nodes process and store data independently and in parallel, and work in a coordinated manner through a communication mechanism, thereby achieving efficient processing of large-scale data and complex computing tasks. The role of a distributed system is to integrate the computing resources and storage resources of multiple nodes to process more data and more complex tasks. The distributed system improves the speed and efficiency of task processing through parallel processing of multiple nodes. Exemplarily, the distributed system can be Hadoop, which is a common distributed system used in the field of Internet of Vehicles data processing technology. Hadoop includes components such as a distributed file system (Hadoop Distributed File System, HDFS) and a distributed computing framework to store and process large-scale data.

[0062] Data processing nodes refer to the basic computing units in a distributed system, which are responsible for receiving, processing and storing data. Each node has independent computing resources and storage resources and can independently perform data processing tasks. The role of data processing nodes is to store data and ensure the persistence and accessibility of data; data processing nodes can perform data processing tasks such as data cleaning, calculation and analysis; data processing nodes transmit data through the network to achieve data sharing and task coordination; by assigning tasks to different nodes, the system load is balanced to avoid overloading of a single node. Exemplarily, in the Hadoop system, data nodes are responsible for storing data blocks and responding to data read and write requests from clients.

[0063] Storage identification refers to an identifier used to identify the location of data storage. In a distributed system, the storage identification is generated or calculated by the data processing node to determine which node the data should be stored on. The role of the storage identification is to help the system quickly determine the data storage location and improve data access efficiency; through consistent storage identification rules, ensure that the same data is stored in the same node to avoid data redundancy and inconsistency; storage identification helps balance the system load and distribute data to different nodes to avoid performance bottlenecks; quickly locate data through storage identification to reduce query time. Exemplarily, the hash is calculated based on the vehicle identification, and then modulo is taken to obtain a file ID, that is, the storage identification, where the selection of the modulus in the modulo is based on factors such as the number of vehicle data, the number of data processing nodes, and the balance of data distribution; file ID refers to an identifier used to uniquely identify a file or data block. In a distributed system, the file ID is used to accurately map data to the corresponding storage node; the role of the file ID is to quickly determine the storage location of the data. By quickly locating the file ID, the system can reduce query time and improve overall query efficiency.

[0064] Among them, according to the data processing node in the distributed system, the vehicle identification is processed to obtain the storage identification, which may mean that each vehicle data has a vehicle identification, such as VIN, etc. The distributed system is composed of multiple data processing nodes, and each data processing node independently processes the vehicle identification to obtain the storage identification, which is used to determine which data processing node to store the vehicle. Exemplarily, there are vehicle identifications VIN1 "1HGCM82633A004352" and VIN2 "1HGCM82633A004353", and there are 4 data processing nodes in the distributed system. First, VIN1 is hashed to obtain a hash value H1, and the hash value H1 is modulo (the modulus is 4, the number of nodes) to obtain a storage identification S1. Assuming that the result of H1 modulo 4 is 2, the storage identification S1 is 2; secondly, the same hashing is performed on VIN2 to obtain a hash value H2, and the hash value H2 is modulo 4 to obtain a storage identification S2. Assuming that the result of H2 modulo 4 is 3, the storage identification S2 is 3; finally, according to the storage identification, the data corresponding to VIN is stored in node 2, and the data corresponding to VIN2 is stored in node 3.

[0065] By processing the vehicle identification according to the data processing node in the distributed system to obtain the storage identification, the storage and management problems in large-scale vehicle data processing are effectively solved; through operations such as hash processing and modulus operation, the vehicle data can be evenly distributed on each data processing node to avoid overload of a single data processing node; the storage identification clearly specifies the storage location, which can quickly locate the vehicle data, improve query efficiency, and avoid traversing all vehicle data; uniform data distribution and load balancing reduce the possibility of single point failure and improve the reliability and fault tolerance of the system.

[0066] S140, sending the vehicle data to be processed to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the vehicle data to be processed; the vehicle data with the same storage identifier are stored in the same data processing node.

[0067] Among them, sending the vehicle data to be processed to the data processing node corresponding to the storage identifier so that the corresponding data processing node writes the vehicle data to be processed can mean that according to the obtained storage identifier, the system determines which data processing node will store specific vehicle data, and the system sends the vehicle data to be processed to the corresponding processing node. Exemplarily, there are 4 data processing nodes in the system, which are divided into 0, 1, 2 and 3, and the storage identifier is determined for the vehicle data. The storage identifier of vehicle data A is 2, and the storage identifier of vehicle data B is 3; the system confirms that vehicle data A needs to be stored in node 2, and the system writes vehicle data A to data processing node 2. The system confirms that vehicle data B needs to be stored in node 3, and the system writes vehicle data B to data processing node 3.

[0068] The vehicle data with the same storage identifier is stored in the same data processing node, which means that each vehicle data is assigned a storage identifier, and the system allocates the data to a specific data processing node according to the storage identifier, and all vehicle data with the same storage identifier are stored on the same node. For example, assuming that there is a storage identifier of vehicle data A in the system of 1, a storage identifier of vehicle data B of 1, and a storage identifier of vehicle data C of 2, according to the storage identifier, the system stores the vehicle data on the corresponding data processing node, the storage identifiers of vehicle data A and vehicle data B are both 1, so they are both stored on the same data processing node, and the storage identifier of vehicle data C is 2, so it will be stored on another data processing node.

[0069] Exemplarily, the vehicle data to be processed is sent to the data processing node corresponding to the storage identifier so that the corresponding data processing node writes the vehicle data to be processed; the vehicle data with the same storage identifier is stored in the same data processing node. This process can be achieved by data bucketing. Data bucketing can refer to dividing vehicle data into different buckets. First, different buckets need to be divided in advance to store vehicle data with the same storage identifier. Different buckets can refer to different data processing nodes. Corresponding storage identifiers are attached to different buckets. Vehicle data with the same storage identifier is stored in the same bucket. Each vehicle data is divided into different buckets according to certain rules.

[0070] By sending the vehicle data to be processed to the data processing node corresponding to the storage identifier so that the corresponding data processing node writes the vehicle data to be processed, efficient data transmission and storage are achieved, and the data processing mode of the distributed system is optimized; by sending the data directly to the corresponding processing node, the centralization of vehicle data processing is avoided, and the overall processing efficiency is improved; by determining the storage identifier, it can be ensured that the vehicle data with the same storage identifier is stored in the same data processing node, avoiding data redundancy and inconsistency; by evenly distributing the vehicle data to different data processing nodes, it is helpful to evenly distribute the system load and avoid overloading of some data processing nodes. By storing the vehicle data with the same storage identifier in the same data processing node, the consistency and efficiency of the vehicle data are ensured, the query efficiency and overall performance of the system are improved, the data management and maintenance work are simplified, and the inconsistency problem caused by the dispersion of vehicle data is avoided; the centralized storage of data with the same identifier can significantly improve the query efficiency of the data; the management and maintenance of the data are simplified, and the problem of data asynchrony and incoordination caused by cross-nodes is avoided; by centrally storing related data, network transmission can be reduced and the overall performance of the system can be improved.

[0071] The technical solution of the embodiment of the present invention ensures the consistency of data by storing the vehicle data with the same storage identifier in the same data processing node, avoids the inconsistency problem that may be caused by data being scattered on different nodes, and ensures the integrity and accuracy of data during storage and processing; since each data processing node only processes vehicle data with a specific storage identifier, the system can process and query data more effectively, and the centralized storage of data with the same identifier simplifies the data retrieval process and improves the query speed and efficiency; the centralized storage strategy simplifies data management and maintenance work, and managers only need to maintain data at specific nodes without having to synchronize and coordinate data across multiple nodes; by reasonably allocating and processing vehicle data, the system can effectively utilize computing resources, reduce data transmission in the network, reduce latency, and improve overall system performance. The load balancing strategy can also be better implemented, avoiding overload of certain nodes; the above beneficial effects make the technical solution of the embodiment of the present invention have significant advantages in processing massive Internet of Vehicles data.

[0072] Embodiment 2

[0073] Figure 2 It is a flow chart of a method for processing vehicle network data provided according to the second embodiment of the present invention. This embodiment is further supplemented on the basis of the above embodiment as "receiving a vehicle data query request; extracting a key identifier from the vehicle data query request; processing the key identifier according to the data processing node in the distributed system to obtain a query identifier; according to the vehicle data query request, obtaining the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier". It should be noted that for the parts not described in detail in the embodiments of the present invention, please refer to the description of other embodiments.

[0074] See also Figure 2 The vehicle networking data processing method shown includes:

[0075] S210: Obtain vehicle data to be processed.

[0076] S220: Obtain a vehicle identification from the vehicle data to be processed.

[0077] S230: Process the vehicle identification according to the data processing node in the distributed system to obtain a storage identification.

[0078] S240, sending the vehicle data to be processed to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the vehicle data to be processed; the vehicle data with the same storage identifier are stored in the same data processing node.

[0079] S250: Receive a vehicle data query request.

[0080] Among them, a query request refers to a request sent by a client to a server to retrieve specific data. In the Internet of Vehicles system, after receiving the query request, the server searches and returns the corresponding vehicle data based on these key identifiers. The purpose of the query request is to obtain specific vehicle data from the system to meet different business needs, such as real-time monitoring and historical data analysis. For example, to view the driving record of a vehicle in a specific time period, a query request is issued. After receiving the request, the server retrieves the corresponding data from the storage and returns the result.

[0081] Receiving the vehicle data query request may be that the server receives the query request from the client, which means that the client sends the request in some way.

[0082] By receiving vehicle data query requests, the Internet of Vehicles system can quickly locate and retrieve the required vehicle data, ensuring the accuracy and efficiency of data queries.

[0083] S260: Extract a key identifier from the vehicle data query request.

[0084] Among them, the key identifier refers to an identifier used to uniquely identify a specific data item in data processing. In the Internet of Vehicles data processing, the key identifier is usually the vehicle identifier, which is used to accurately locate and retrieve the required data. The role of the key identifier is to ensure that specific vehicle data can be accurately located during the data processing process to avoid confusion and errors; through the key identifier, the corresponding data can be quickly retrieved and accessed to improve the efficiency of system queries; help the system establish associations between different data items, making data processing more efficient and accurate. Exemplarily, in the Internet of Vehicles system, the vehicle identification code VIN can be used as a key identifier to uniquely identify each vehicle.

[0085] Extracting the key identifier from the vehicle data query request may refer to a received query request, the request including specific data requested for query, and identifying and extracting an identifier for uniquely identifying the data from the query request. Exemplarily, in the vehicle data query request, a vehicle identification code VIN is extracted as the key identifier.

[0086] By extracting key identifiers from vehicle data query requests, the system can accurately locate and retrieve corresponding data to avoid data confusion and errors; making the data query process more efficient and reducing the system's query time and resource consumption; the method of extracting key identifiers can adapt to different types of query requests, improving the flexibility and adaptability of the system.

[0087] Optionally, extracting a key identifier from the vehicle data query request includes, when the vehicle data query request is a single vehicle data query request, extracting a key identifier from the single vehicle data query request.

[0088] Among them, when the vehicle data query request is a single vehicle data query request, a key identifier from the single vehicle data query request may refer to that when processing the vehicle data query request, the system will extract an important identification information, namely the key identifier, from the query request. When the query request is for data of a single vehicle, this key identifier is usually a unique identifier of the vehicle. Exemplarily, the system receives a vehicle data query request, determines whether the query request is for a single vehicle or multiple vehicles, and if it is a single vehicle data query request, extracts the unique identifier VIN of the vehicle from the request as the key identifier.

[0089] By using a key identifier in a single vehicle data query request when the vehicle data query request is a single vehicle data query request, the key identifier can be efficiently and accurately extracted and used for data positioning and retrieval, thereby improving the query efficiency and data processing accuracy; by extracting the key identifier in the single vehicle data query request, the system can quickly respond to query requirements.

[0090] Optionally, extracting a key identifier from the vehicle data query request includes, when the vehicle data query request is a multi-vehicle data query request, extracting multiple key identifiers from the multi-vehicle data query.

[0091] Wherein, when the vehicle data query request is a multi-vehicle data query request, extracting multiple key identifiers from the multi-vehicle data query may mean that when the system receives a data query request for multiple vehicles, the system extracts multiple vehicle identifiers from the query request, and these identifiers are used to locate the corresponding data processing nodes so as to retrieve the vehicle data of each vehicle. Exemplarily, the VINs of three vehicles are extracted from the vehicle data query request as the key, and the data processing nodes storing the vehicle data are located according to the extracted key identifiers, and the vehicle data of the three vehicles are retrieved and returned from the corresponding data processing nodes.

[0092] By extracting multiple key identifiers from a multi-vehicle data query when the vehicle data query request is a multi-vehicle data query request, the system can efficiently and accurately process data query requests for multiple vehicles; this improves query efficiency, optimizes the use of system resources, and provides comprehensive vehicle data support, thereby improving the overall performance and user experience of the Internet of Vehicles system.

[0093] S270. Process the key identifier according to the data processing node in the distributed system to obtain a query identifier.

[0094] Among them, the query identifier refers to an identifier used to locate and retrieve data during the data query process. In the Internet of Vehicles data processing, the query identifier is generated by the key identifier through a certain processing method, which is used to determine the data storage location to facilitate efficient query and acquisition of data. The role of the query identifier is to help the system quickly determine the storage location of the data, thereby improving the speed and efficiency of data retrieval; through consistent query identification rules, ensure that the same query request points to the same data, and avoid data inconsistency and redundancy. Exemplarily, the system receives a vehicle data query request, extracts the vehicle identification code VIN as the key identifier, and obtains the query identifier after processing, such as calculating the hash and then taking the modulus, so as to obtain a file ID, and uses the file ID as the query identifier to locate the specific data storage location of the vehicle.

[0095] According to the data processing nodes in the distributed system, the key identifier is processed to obtain the query identifier, which can refer to multiple data processing units in the system, which are responsible for data storage and processing tasks, and perform specific calculations, conversions or mappings on the extracted key identifiers, which refers to generating identifiers for data queries by processing key identifiers.

[0096] By processing key identifiers according to data processing nodes in the distributed system to obtain query identifiers, data storage locations can be quickly located to improve query speed; ensure that query requests can consistently point to the same data to avoid data redundancy and inconsistency; and balance system load and improve overall system performance through reasonable query identifier allocation.

[0097] S280. According to the vehicle data query request, obtain vehicle data corresponding to the vehicle data query request from a data processing node corresponding to the query identifier.

[0098] Among them, according to the vehicle data query request, obtaining the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier can mean that after receiving the vehicle data query request, the system can quickly locate the data processing node storing the relevant data through the previously generated query identifier, and extract the vehicle data that meets the query request conditions from the located data processing node. Exemplarily, after receiving the vehicle data query request, the VIN field "1HGCM82633A004352" is extracted as the key identifier, and a file ID is generated as the query identifier through hash operation and modulus operation, and the query identifier is used to locate the data processing node, and all vehicle data corresponding to the vehicle identification code VIN "1HGCM82633A004352" are extracted.

[0099] By obtaining the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier based on the vehicle data query request, it is ensured that the system can respond to the vehicle data query request efficiently and accurately, significantly improving the query speed and system performance, while ensuring the consistency and reliability of the data; through the combination of reasonable query identifier generation and distributed systems, efficient data management and query processing are achieved.

[0100] Optionally, extracting a key identifier from a vehicle data query request includes, based on the vehicle data query request, obtaining vehicle data corresponding to the vehicle data query request from a data processing node corresponding to the query identifier, including, based on a single vehicle data query request, obtaining vehicle data corresponding to the single vehicle data query request from a data processing node corresponding to the query identifier.

[0101] Among them, according to the single-vehicle data query request, obtaining the vehicle data corresponding to the single-vehicle data query request from the data processing node corresponding to the query identifier can mean that the system receives a data query request for a certain vehicle, uses the query identifier extracted and processed previously, locates the corresponding data processing node, and finally retrieves the vehicle data related to the request from the located data processing node. Exemplarily, the system receives a single-vehicle query request, identifies the vehicle VIN as "1HGCM82633A004352", extracts the vehicle ID as a key identifier, processes it to obtain a query identifier, uses the query identifier to locate the data processing node that stores the vehicle data of "1HGCM82633A004352", and obtains the vehicle data of the vehicle on the node.

[0102] By obtaining the vehicle data corresponding to the single-vehicle data query request from the data processing node corresponding to the query identifier based on the single-vehicle data query request, it is ensured that when the system receives the single-vehicle data query request, it can efficiently and accurately locate and retrieve the corresponding vehicle data through the query identifier, thereby improving the efficiency and accuracy of data processing and query; accurately locate the data storage location according to the query identifier to ensure that the retrieved data is up-to-date and accurate; reduce manual intervention and improve the automation level of the system.

[0103] Optionally, extracting a key identifier from a vehicle data query request includes, based on the vehicle data query request, obtaining vehicle data corresponding to the vehicle data query request from a data processing node corresponding to the query identifier, including, for each query identifier, obtaining the vehicle data corresponding to the query identifier from the data processing node corresponding to the query identifier; and fusing the vehicle data corresponding to each query identifier to obtain vehicle data corresponding to multiple vehicle data query requests.

[0104] Among them, for each query identifier, the vehicle data corresponding to the query identifier is obtained from the data processing node corresponding to the query identifier; the vehicle data corresponding to each query identifier is merged to obtain the vehicle data corresponding to the multi-vehicle data query request, which can mean that the system has extracted multiple vehicle identifiers from the multi-vehicle data query request, and each identifier corresponds to a vehicle. The system locates the specific data processing node that stores the vehicle data according to the identifier of each vehicle, and obtains the corresponding vehicle data from these nodes, and merges the obtained data of multiple vehicles to obtain a comprehensive result to meet the needs of multi-vehicle data query requests.

[0105] By targeting each query identifier, obtaining the vehicle data corresponding to the query identifier from the data processing node corresponding to the query identifier; fusing the vehicle data corresponding to each query identifier to obtain the vehicle data corresponding to the multi-vehicle data query request, that is, performing statistical query based on querying multiple single-vehicle data, therefore, it also has the beneficial effects of all single-vehicle queries. The system can efficiently process multi-vehicle data query requests, provide comprehensive vehicle status information, and improve query efficiency and system performance.

[0106] Embodiment 3

[0107] Figure 3a 1 is a flow chart of a vehicle network data processing method provided according to Embodiment 3 of the present invention. Based on the above embodiment, the embodiment of the present invention applies it to a data processing node. It should be noted that for the parts not described in detail in the embodiment of the present invention, reference can be made to the description of other embodiments.

[0108] See also Figure 3a The vehicle networking data processing method shown includes:

[0109] S310, receiving the vehicle data to be processed sent by the server; the data processing node corresponds to the storage identifier of the vehicle data to be processed, and the storage identifier obtains the vehicle data to be processed through the server; obtains the vehicle identifier from the vehicle data to be processed; according to the data processing node in the distributed system, the vehicle identifier is processed to obtain; the vehicle data with the same storage identifier is stored in the same data processing node.

[0110] Among them, receiving the vehicle data to be processed sent by the server means that the data processing nodes in the system will receive the vehicle data sent from the server, and these vehicle data are waiting for further processing. The data processing node corresponds to the storage identifier of the vehicle data to be processed. The storage identifier obtains the vehicle data to be processed through the server, which means that each data processing node is responsible for processing the vehicle data corresponding to a specific storage identifier, and the server will send the data to the corresponding data processing node according to the storage identifier. Obtaining the vehicle identification from the vehicle data to be processed means that after receiving the data, the data processing node will extract the unique identifier related to the vehicle from it. According to the data processing node in the distributed system, processing the vehicle identification means that the system processes the extracted vehicle identification to determine how the data should be stored or further processed. Storing vehicle data with the same storage identifier in the same data processing node means that vehicle data with the same storage identifier will be stored in the same data processing node, which can ensure the centralized management and processing of related data.

[0111] By receiving the vehicle data to be processed sent by the server; the data processing node corresponds to the storage identifier of the vehicle data to be processed, and the storage identifier obtains the vehicle data to be processed through the server; the vehicle identifier is obtained from the vehicle data to be processed; according to the data processing node in the distributed system, the vehicle identifier is processed to obtain; the vehicle data with the same storage identifier is stored in the same data processing node, so that the data storage and management are more centralized and efficient, the efficiency of querying and processing data is improved, and the reliability and scalability of the system are enhanced; by centrally storing the data with the same storage identifier in the same data processing node, the system can manage and process related data more effectively and reduce the query efficiency caused by data dispersion; through the processing of the distributed system, the system can evenly distribute the data to each node according to the storage identifier, avoid the overload problem of a single node, and optimize the utilization of system resources.

[0112] S320: Fusing the vehicle data to be processed with the pre-collected vehicle data to obtain vehicle data of each vehicle.

[0113] Among them, fusing the to-be-processed vehicle data with the pre-collected vehicle data to obtain the vehicle data of each vehicle may refer to integrating the newly received to-be-processed vehicle data with the historically collected vehicle data already in the system to generate a more complete vehicle data record. Exemplarily, the system currently receives the to-be-processed vehicle data of a vehicle, and the system has stored the pre-collected vehicle data of the vehicle, and the system fuses the currently received to-be-processed vehicle data with the pre-collected vehicle data of the vehicle.

[0114] By fusing the vehicle data to be processed with the vehicle data collected in advance to obtain the vehicle data of each vehicle, the vehicle data to be processed is merged with the vehicle data collected in advance to generate a more comprehensive vehicle information record, which is helpful for comprehensive analysis and evaluation of the vehicle; the system can make more accurate predictions and decisions based on the comprehensive data.

[0115] S330. Sort and store the vehicle data of each vehicle according to the vehicle identification and timestamp of the vehicle data of each vehicle.

[0116] Wherein, sorting and storing the vehicle data of each vehicle according to the vehicle identification and timestamp of the vehicle data of each vehicle may refer to sorting and storing the vehicle data according to the vehicle identification code VIN and the timestamp. Exemplarily, wherein, each vehicle data of different vehicles is sorted and stored according to the VIN code, and each vehicle data of the same vehicle is sequentially stored according to the timestamp.

[0117] By sorting and storing the vehicle data of each vehicle according to the vehicle identification and timestamp of the vehicle data of each vehicle, the data is sorted and stored according to the vehicle identification and timestamp, so that all data of the same vehicle are stored together and arranged in chronological order, which is convenient for subsequent reading, analysis and processing; this sorting and storage method enables the system to quickly locate the vehicle data of a certain vehicle at a specific time, which is particularly suitable for scenarios that require historical trajectory tracing or analysis of the vehicle; storing vehicle data in sequence helps to reduce file fragmentation and optimize the utilization efficiency of storage space; because the vehicle data has been arranged in order according to the vehicle identification and timestamp, batch processing can be performed directly when reading files sequentially, reducing the computing load of the system.

[0118] Optionally, in the target file, the vehicle data of each vehicle is sorted and stored, and the storage identifier corresponds to the target file.

[0119] Among them, the target file refers to an actual physical file or logical file used for data storage. The role of the target file is to help the system store and block the processed vehicle data in an orderly manner. By sorting and storing the vehicle data according to the vehicle identification and timestamp, the structure and consistency of the vehicle data are ensured; the target file makes the access of vehicle data more efficient, reduces the access time, and improves the reading efficiency. Exemplarily, the vehicle data A and vehicle data B are processed according to the storage identification, the vehicle identification and timestamp are extracted from the vehicle data to be processed, these data are merged with the pre-collected data, and the merged vehicle data are sorted according to the vehicle identification and timestamp. A target file is created on the data processing node, such as "vehicle data_node1.dat", and the sorted data is stored in the "vehicle data_node1.dat" file. When specific vehicle data needs to be queried, the corresponding data can be quickly located on the target file "vehicle data_node1.dat" to query.

[0120] Among them, in the target file, the vehicle data of each vehicle is sorted and stored, and the correspondence between the storage identifier and the target file can mean that in a data storage unit or file specifically used to store processed vehicle data, the vehicle data is sorted according to specific rules (such as vehicle identification and timestamp, etc.), and the sorted data is written into the target file, wherein the storage identifier determines the creation and management of the target file.

[0121] By sorting and storing the vehicle data of each vehicle in the target file and corresponding the storage identifier to the target file, the structural consistency of the vehicle data can be ensured, making data management more orderly and efficient; the clear identification of the target file makes data retrieval and access more direct, avoiding complex searches between multiple files or nodes; the storage identifier helps the system quickly determine the location of the target file, thereby reducing the time for data access and retrieval and improving the overall performance of the system.

[0122] In an example of a specific implementation of a vehicle networking data processing method, the overall process is as follows Figure 3b As shown, the specific steps include:

[0123] S410, the Internet of Vehicles data collected by the vehicle is uploaded to the cloud Kafka via the wireless network.

[0124] S420, subscribe to kafka through the spark program, read the vehicle data and store it in HDFS. At this time, the vehicle data is randomly distributed on all nodes in HDFS.

[0125] S430, start another distributed data processing task, read all vehicle data, calculate the hash according to the unique identification VIN of the vehicle, and then take the modulus to obtain the file ID.

[0126] S440, collecting data with the same file ID to the same data processing node via network transmission;

[0127] S450, each data processing node is responsible for merging the collected vehicle data, sorting them by VIN and timestamp, and then writing them into the same file;

[0128] S460, when querying single vehicle data, by calculating the hash code of the VIN in advance, then taking the film, obtaining the file ID, and quickly locating the file, avoiding traversal of all data;

[0129] S470: When performing statistical analysis on group data, each task is responsible for the statistics of one file. There is no need for data interaction or network transmission between tasks, which greatly improves performance.

[0130] Through the above steps, the vehicle data is processed by writing once and reading multiple times. By calculating the hash of the unique identifier VIN of the vehicle data and then taking the modulus to obtain the file ID, the data of the same vehicle are all in the same file, thus avoiding a large amount of network transmission for data processing. At the same time, the query of a single vehicle will only need to read one file, which greatly improves the system performance and reduces resource consumption.

[0131] Embodiment 4

[0132] Figure 4 1 is a schematic diagram of the structure of a vehicle networking data processing device provided in Embodiment 4 of the present invention. The device can execute the vehicle networking data processing method, the device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device that carries the vehicle networking data processing function.

[0133] See also Figure 4 The vehicle networking data processing device shown includes:

[0134] A data acquisition module 510 is used to acquire vehicle data to be processed;

[0135] The identification extraction module 520 is used to obtain the vehicle identification from the vehicle data to be processed;

[0136] The identification processing module 530 is used to process the vehicle identification according to the data processing node in the distributed system to obtain a storage identification;

[0137] The data distribution module 540 is used to send the vehicle data to be processed to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the vehicle data to be processed; the vehicle data with the same storage identifier is stored in the same data processing node.

[0138] Optionally, the data acquisition module 510 includes:

[0139] A data acquisition unit, configured to acquire vehicle data of at least one vehicle;

[0140] A data distribution unit, used for randomly distributing and storing the vehicle data collected by each vehicle on at least one storage node;

[0141] The data reading unit is used to read the vehicle data to be processed from each storage node.

[0142] Optionally, the data acquisition unit includes:

[0143] The data acquisition subunit is used to obtain vehicle data uploaded by at least one vehicle within a target time period from the message queue, and the target time period is determined according to the performance of the server.

[0144] Optionally, a vehicle networking data processing device further includes:

[0145] A query request receiving module 550, for receiving a vehicle data query request;

[0146] A key identifier extraction module 560, used to extract a key identifier from a vehicle data query request;

[0147] A query identifier processing module 570 is used to process the key identifier according to the data processing node in the distributed system to obtain a query identifier;

[0148] The data query acquisition module 580 is used to acquire the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier according to the vehicle data query request.

[0149] Optionally, the key identifier extraction module 560 includes:

[0150] A single vehicle key identifier extraction unit, used for extracting a key identifier from the single vehicle data query request when the vehicle data query request is a single vehicle data query request;

[0151] A multi-vehicle key identifier extraction unit, used to extract multiple key identifiers from the multi-vehicle data query when the vehicle data query request is a multi-vehicle data query request;

[0152] Optionally, the data acquisition module 580 includes:

[0153] A single vehicle data acquisition unit, used to acquire vehicle data corresponding to the single vehicle data query request from a data processing node corresponding to the query identifier according to the single vehicle data query request;

[0154] A multi-vehicle data acquisition unit, for acquiring, for each query identifier, vehicle data corresponding to the query identifier from a data processing node corresponding to the query identifier;

[0155] The data fusion unit is used to fuse the vehicle data corresponding to each query identifier to obtain the vehicle data corresponding to the multi-vehicle data query request.

[0156] The Internet of Vehicles data processing device provided in the embodiment of the present invention can execute the Internet of Vehicles data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0157] Embodiment 5

[0158] Figure 5 1 is a schematic diagram of the structure of a vehicle networking data processing device provided in Embodiment 5 of the present invention. The device can execute the vehicle networking data processing method, the device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device that carries the vehicle networking data processing function.

[0159] See also Figure 5 The vehicle networking data processing device shown includes:

[0160] The data receiving and distributing module 510 is used to receive the vehicle data to be processed sent by the server; the data processing node corresponds to the storage identifier of the vehicle data to be processed, and the storage identifier obtains the vehicle data to be processed through the server; obtains the vehicle identifier from the vehicle data to be processed; processes the vehicle identifier according to the data processing node in the distributed system; and stores the vehicle data with the same storage identifier in the same data processing node;

[0161] The data fusion module 520 is used to fuse the vehicle data to be processed with the pre-collected vehicle data to obtain the vehicle data of each vehicle;

[0162] The data sorting and storage module 530 is used to sort and store the vehicle data of each vehicle according to the vehicle identification and timestamp of the vehicle data of each vehicle.

[0163] Optionally, the data sorting storage module 530 includes:

[0164] The target file sorting storage unit is used to sort and store the vehicle data of each vehicle in the target file, and the storage identifier corresponds to the target file.

[0165] The Internet of Vehicles data processing device provided in the embodiment of the present invention can execute the Internet of Vehicles data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0166] Embodiment 6

[0167] Figure 6: is a schematic diagram of the structure of an electronic device of a vehicle networking data processing method according to an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0168] like Figure 6 As shown, the electronic device 600 includes at least one processor 601, and a memory connected to the at least one processor 601, such as a read-only memory (ROM) 602, a random access memory (RAM) 603, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 601 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 602 or the computer program loaded from the storage unit 608 to the random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 can also be stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 606 is also connected to the bus 604.

[0169] Multiple components in the electronic device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0170] The processor 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 601 executes the various methods and processes described above, such as the Internet of Vehicles data processing method.

[0171] In some embodiments, the vehicle networking data processing method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the processor 601, one or more steps of the vehicle networking data processing method described above may be performed. Alternatively, in other embodiments, the processor 601 may be configured to execute the vehicle networking data processing method in any other appropriate manner (e.g., by means of firmware).

[0172] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0173] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0174] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0175] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0176] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0177] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0178] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0179] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing Internet of Vehicles data, characterized in that: Applied in a server, the method comprises: Obtain vehicle data to be processed; Acquire a vehicle identification from the vehicle data to be processed; According to the data processing node in the distributed system, the vehicle identification is processed to obtain a storage identification; The vehicle data to be processed is sent to the data processing node corresponding to the storage identifier, so that the corresponding data processing node writes the vehicle data to be processed; the vehicle data with the same storage identifier is stored in the same data processing node.

2. The method according to claim 1, characterized in that Obtaining vehicle data to be processed includes: obtaining vehicle data of at least one vehicle; Randomly distributing and storing the vehicle data collected by each of the vehicles on at least one storage node; The vehicle data to be processed is read from each of the storage nodes.

3. The method according to claim 2, characterized in that The acquiring vehicle data of at least one vehicle comprises: The vehicle data uploaded by at least one vehicle within a target duration is obtained from the message queue, where the target duration is determined according to the performance of the server.

4. The method according to claim 1, characterized in that: Also includes: Receiving vehicle data query request; Extracting a key identifier from the vehicle data query request; Processing the key identifier according to the data processing node in the distributed system to obtain a query identifier; According to the vehicle data query request, the vehicle data corresponding to the vehicle data query request is acquired from the data processing node corresponding to the query identifier.

5. The method according to claim 4, characterized in that The extracting a key identifier from the vehicle data query request includes: When the vehicle data query request is a single vehicle data query request, a key identifier from the single vehicle data query request; The acquiring, according to the vehicle data query request, the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier comprises: According to the single vehicle data query request, vehicle data corresponding to the single vehicle data query request is obtained from a data processing node corresponding to the query identifier.

6. The method according to claim 4, characterized in that The extracting a key identifier from the vehicle data query request includes: When the vehicle data query request is a multi-vehicle data query request, extracting multiple key identifiers from the multi-vehicle data query; The acquiring, according to the vehicle data query request, the vehicle data corresponding to the vehicle data query request from the data processing node corresponding to the query identifier comprises: For each query identifier, obtaining the vehicle data corresponding to the query identifier from the data processing node corresponding to the query identifier; The vehicle data corresponding to each of the query identifiers are merged to obtain the vehicle data corresponding to the multi-vehicle data query request.

7. A method for processing Internet of Vehicles data, characterized in that: Applied in a data processing node, the method comprises: Receiving the vehicle data to be processed sent by the server; the data processing node corresponds to the storage identifier of the vehicle data to be processed, and the storage identifier obtains the vehicle data to be processed through the server; obtaining the vehicle identifier from the vehicle data to be processed; processing the vehicle identifier according to the data processing node in the distributed system; storing the vehicle data with the same storage identifier in the same data processing node; Merging the vehicle data to be processed with the pre-collected vehicle data to obtain vehicle data of each of the vehicles; The vehicle data of each of the vehicles are sorted and stored according to the vehicle identification and timestamp of the vehicle data of each of the vehicles.

8. The method according to claim 7, characterized in that The step of sorting and storing the vehicle data of each of the vehicles comprises: In the target file, the vehicle data of each of the vehicles is sorted and stored, and the storage identifier corresponds to the target file.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle network data processing method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle network data processing method according to any one of claims 1 to 7 when executed.

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