Bus real-time data acquisition method and system

Abstract

The invention relates to the technical field of data acquisition, in particular to a bus real-time data acquisition method and system, and the method comprises the following steps: collecting data from a plurality of sensors of a bus in real time; dividing the data into a plurality of categories according to the timeliness and importance of the data; multi-level dynamic compression algorithm selection based on data categories: adopting multi-level dynamic compression algorithms for different categories of data; during data transmission, a self-adaptive priority scheduling mechanism is adopted, and the uploading priority of different types of data is dynamically adjusted according to the current network bandwidth and the transmission delay; in a bus network, short-distance wireless communication is established among a plurality of buses, and data cached in one bus is shared to other surrounding vehicles through a bus-bus linkage mechanism; according to the invention, real-time sharing and temporary supplement of data are realized through short-distance wireless communication, the problem of data missing caused by network disconnection of a single vehicle in a traditional data acquisition system is solved, and the reliability of overall data is greatly enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection, and in particular to a method and system for collecting real-time data of a bus. Background Art

[0002] With the development of smart cities and intelligent transportation systems, buses, as an important part of urban public transportation, have gradually introduced various advanced sensors and information technologies to achieve data collection and real-time monitoring. The existing bus data collection system uses a variety of devices to collect data in order to monitor and optimize the bus operation status, passenger flow, and in-vehicle environment. These data are of great significance for optimizing bus operation scheduling, improving passenger experience, and reducing energy consumption and operating costs.

[0003] However, in practical applications, bus real-time data collection systems face many technical challenges, especially in the following aspects:

[0004] Network bandwidth limitation and data transmission delay: As buses run in different areas, they often face bandwidth limitations or unstable networks, which makes it difficult to transmit large amounts of real-time data. Especially when multiple sensors upload data at the same time, insufficient network bandwidth can lead to data congestion, or even data loss or delay, affecting the timeliness and accuracy of the data.

[0005] Data compression and transmission efficiency issues: Existing systems usually use simple data compression methods to reduce the amount of data transmission, but do not take into account the different requirements of different types of data for real-time and accuracy. For example, key data requires high accuracy and real-time transmission, while auxiliary data can appropriately reduce accuracy to improve transmission efficiency. Existing systems lack intelligent compression and transmission mechanisms that are adaptively adjusted based on data importance and network status.

[0006] Network interruption and data loss: In some areas with poor or interrupted network signals, buses often fail to upload collected data in a timely manner, resulting in incomplete data. Especially in large-scale bus networks, the loss of data from a particular bus may affect the dispatch and management of the entire system. Traditional systems usually rely on single-vehicle uploads, lack an effective data sharing and correction mechanism between vehicles and workshops, and cannot be effectively supplemented and repaired when network failures occur. Summary of the invention

[0007] The invention provides a bus real-time data collection method and system.

[0008] A bus real-time data collection method comprises the following steps:

[0009] S1, real-time data collection: collect data from multiple sensors on the bus in real time;

[0010] S2, according to the timeliness and importance of the data, the data is divided into multiple categories, including key data, auxiliary data, and background data;

[0011] S3, multi-level dynamic compression algorithm selection based on data category: multi-level dynamic compression algorithm is used for different categories of data: different compression ratios are used for key data, auxiliary data and background data;

[0012] S4, dynamic priority data transmission scheduling based on network status: During data transmission, an adaptive priority scheduling mechanism is adopted to dynamically adjust the upload priority of different types of data according to the current network bandwidth and transmission delay. For key data, low-latency transmission channels are preferentially used for uploading to ensure real-time data transmission; for auxiliary data, transmission channels are selected for intermittent uploading according to bandwidth conditions; background data is selected for batch uploading and is preferentially cached in the vehicle storage device and uploaded when bandwidth is sufficient;

[0013] S5, cross-vehicle data sharing and data correction mechanism: In the bus network, short-range wireless communication is established between multiple buses. Through the vehicle-to-vehicle linkage mechanism, the data cached in one vehicle is shared with other surrounding vehicles, especially in some environments with poor signals or network interruptions. At this time, the surrounding vehicles temporarily supplement the missing data by receiving shared data. If a bus fails to upload data in time due to network problems, it will obtain data corrections from other vehicles and supplement them to ensure data consistency and accuracy.

[0014] Optionally, the sensor in S1 includes:

[0015] GPS positioning unit: obtain the location information of the bus in real time;

[0016] Speed ​​sensor: obtain bus speed data in real time, including instantaneous speed and average speed;

[0017] Passenger flow detection sensor: real-time monitoring of the number of passengers in the car, especially the flow fluctuations when entering and leaving the station, to obtain information on the passenger capacity in the car;

[0018] Temperature and humidity sensor: collects temperature and humidity inside the car;

[0019] Noise sensor: obtains noise level data inside the car;

[0020] In S2: the key data includes location information and speed data; the auxiliary data includes the number of passengers and the temperature and humidity in the vehicle; and the background data includes environmental noise.

[0021] Optionally, the S3 specifically includes:

[0022] Key data: Use a lossless compression algorithm with a low compression ratio to ensure that no information is lost during the compression process, maintain data integrity and real-time performance, and meet high timeliness requirements;

[0023] Auxiliary data: A lossy compression algorithm with a medium compression ratio is used to balance data compression rate and accuracy through moderate lossy compression while ensuring the compression rate, so as to optimize bandwidth occupancy and transmission efficiency;

[0024] Background data: Use a lossy compression algorithm with a high compression ratio to reduce bandwidth usage, meet the needs of low-priority data transmission, and reduce system burden.

[0025] Optionally, in S4, an adaptive priority scheduling mechanism is used to schedule the network bandwidth B according to the real-time network bandwidth B. net , transmission delay T key , dynamically adjust the upload priority of different types of data, the key data is uploaded preferentially through low-latency transmission channels, ensuring the real-time and integrity of key data. When the network bandwidth is low, the low-latency channels with less bandwidth requirements are automatically selected for uploading to ensure the immediacy of data. The transmission delay T key Real-time requirements must be met: Among them, S key is the size of the key data, B key is the available bandwidth of the low-latency channel, T key Less than the maximum delay threshold T set by the system maxx .

[0026] Optionally, the auxiliary data is based on the real-time network bandwidth B net In the case of intermittent upload, the transmission channel is selected. If the bandwidth is sufficient, the auxiliary data will be transmitted continuously. If the bandwidth is tight, interval upload is selected, and part of the data is uploaded during each transmission period. The upload frequency of auxiliary data is f aux Dynamic adjustment based on bandwidth conditions:

[0027] Among them, f aux is the frequency of auxiliary data upload, S aux is the size of the auxiliary data, B net It is the current network bandwidth. According to the network conditions, the system will adjust the upload frequency appropriately to ensure that data transmission does not affect other network usage requirements.

[0028] Optionally, the background data has the lowest priority, so batch upload can be selected. It is first cached to the vehicle storage device. When the network bandwidth is sufficient, the batch upload process is started to upload the cached data to the cloud or other target server. At this time, the upload rate of background data v bg Automatically adjust based on bandwidth conditions: Among them, v bg is the background data upload rate, S bg is the size of the background data, T bg is the transmission time of background data. When the network bandwidth is B net When available, choose the maximum bandwidth to transmit background data to minimize upload latency.

[0029] Optionally, the S5 specifically includes:

[0030] S51, in a bus network, a vehicle-to-vehicle network connection is established between multiple buses through short-range wireless communications (such as WiFi-Direct, Bluetooth, V2X communication, etc.), allowing efficient data transmission between vehicles and realizing sharing and synchronization of vehicle-mounted data;

[0031] S52, when the data of a bus cannot be uploaded due to network interruption or poor signal, the vehicle-to-vehicle linkage mechanism is activated to share the cached data in the bus with surrounding vehicles. The shared data includes all temporarily stored real-time data (such as GPS positioning, vehicle speed, temperature and humidity, etc.), expressed as:

[0032] Among them, D shared is the total size of the shared dataset, For the data cached in the i-th bus, the cached data is transmitted to the surrounding vehicles through short-range wireless communication to ensure that the data is effectively transmitted between multiple vehicles;

[0033] S53, if a bus fails to upload data in time due to network problems, the surrounding vehicles receive the shared data and make corrections and supplements to the data. When supplementing the data, the missing data is updated through the correction algorithm:

[0034] D corrected =D missing ∪D shared and if networkStatus=failed,D vehicle =D corrected ; Among them, D missing For the missing data set, D shared D is the data obtained through car-to-car sharing. corrected is the corrected data set, networkStatus is the current network connection status (such as network failure, network recovery). When a bus cannot upload data through the network, it will obtain data from other vehicles for correction;

[0035] S54, during the data correction process, a data priority scheduling algorithm is used to give priority to selecting high-timeliness and high-priority data for supplementation. The data priority scheduling formula is as follows:

[0036] P data =f(T data ,R data ,D priority ), where P data is the data priority, T data is the timeliness of the data, R data For data integrity requirements, D priority The data category priority.

[0037] Optionally, the S51 further includes network connection status detection, which is expressed as:

[0038] Among them, Conn link SignalStrength is the quality of the network connection between vehicles. i is the signal strength between the i-th bus and the target vehicle, ConnectionStatus i The system dynamically determines whether to establish a short-range network connection by calculating the signal strength and connection status of multiple vehicles (such as successful connection, failed connection, etc.).

[0039] Optionally, the data priority scheduling algorithm specifically includes:

[0040] Timeliness of data data : Indicates the real-time requirement of data. The higher the timeliness, the higher the priority;

[0041] Data integrity requirements data : Indicates the weight of the data on integrity requirements, with a value range of 0≤R data ≤1, the higher the value, the more important the integrity is;

[0042] Data Category Priority D priority : According to the basic priority preset by data type, among which, key data: D priority =1.0; auxiliary data: D priority =0.5; Background data: D priority =0.2;

[0043] The priority is calculated as: Among them, P data It is the priority of the current data. The higher the value, the higher the priority of data transmission or processing. data is the timeliness of the data. The smaller the value, the higher the timeliness requirement. data is the integrity weight, the larger the value, the more important the integrity is. priority It is the preset basic priority, determined according to the data category.

[0044] A bus real-time data collection system, used to implement the above-mentioned bus real-time data collection method, includes the following modules:

[0045] Data acquisition module: used to collect data in real time from multiple sensors of the bus, including GPS positioning module, vehicle speed sensor, accelerometer, passenger flow detection sensor, and in-vehicle environment sensor;

[0046] Data classification module: according to the timeliness and importance of the collected data, the data is divided into multiple categories, including key data, auxiliary data and background data;

[0047] Data compression module: selects the corresponding compression ratio calculation based on the data category, and performs multi-level dynamic compression on different types of data to ensure data integrity and transmission efficiency;

[0048] Priority scheduling module: dynamically adjusts the upload priority of different types of data according to the current network bandwidth and transmission delay, ensuring that key data is transmitted first, auxiliary data is uploaded intermittently, and background data is uploaded in batches;

[0049] On-board storage module: used to cache and store data, temporarily store low-priority data when network bandwidth is insufficient, and upload it when bandwidth is sufficient;

[0050] Vehicle-to-vehicle linkage module: Shares the cached data in one vehicle with other surrounding vehicles through short-range wireless communication, helping to temporarily supplement the missing data in a network interruption environment;

[0051] Data upload module: responsible for uploading high-priority data to the server through a low-latency transmission channel.

[0052] Beneficial effects of the present invention:

[0053] The present invention adopts different compression algorithms according to data categories (key data, auxiliary data, background data), combined with dynamic adjustment of network bandwidth and vehicle-mounted storage, and can significantly improve data transmission efficiency while ensuring data quality. A lossless compression algorithm is used for key data to ensure its integrity and real-time performance; a lossy algorithm with a medium compression ratio is used for auxiliary data to balance compression rate and accuracy; a lossy algorithm with a high compression ratio is used for background data to reduce bandwidth occupancy. This multi-level compression mechanism ensures the optimal data transmission effect under different network environments and reduces the waste of bandwidth resources.

[0054] The present invention realizes data sharing and correction through the vehicle-to-vehicle linkage mechanism when the network is unstable or interrupted. When a bus fails to upload data in time due to network problems, the surrounding vehicles can receive and supplement the data to ensure the integrity and consistency of the data. Especially in an environment with poor signal or network interruption, real-time sharing and temporary supplement of data can be realized through short-range wireless communication. This mechanism effectively solves the problem of data loss caused by single vehicle disconnection in traditional data collection systems, and greatly enhances the reliability of the overall data.

[0055] The priority scheduling mechanism of the present invention improves the real-time performance and accuracy of key data transmission: a dynamic priority scheduling algorithm based on data timeliness, integrity requirements and priority categories is adopted to ensure that key data is transmitted first, while auxiliary data and background data are scheduled according to real-time network bandwidth and on-board storage conditions. This scheduling algorithm dynamically adjusts the order of data transmission by calculating the priority of each data and sorting it, ensuring that high-timeliness and important data are processed first. This not only improves the data processing capability of the system when bandwidth is limited, but also ensures that the core data in bus operation can be transmitted accurately and timely, improving the response speed and operating efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0059] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0060] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0061] like Figure 1 As shown, a method for collecting real-time data of a bus comprises the following steps:

[0062] S1, real-time data collection: collect data from multiple sensors on the bus in real time;

[0063] S2, according to the timeliness and importance of the data, the data is divided into multiple categories, including key data (such as location, speed, passenger volume, etc., which have high timeliness requirements), auxiliary data (temperature and humidity, in-vehicle noise), and background data (environmental noise);

[0064] S3, multi-level dynamic compression algorithm selection based on data category: multi-level dynamic compression algorithm is used for different categories of data: different compression ratios are used for key data, auxiliary data and background data;

[0065] S4, dynamic priority data transmission scheduling based on network status: During data transmission, an adaptive priority scheduling mechanism is adopted to dynamically adjust the upload priority of different types of data according to the current network bandwidth and transmission delay. For key data, low-latency transmission channels are preferentially used for uploading to ensure real-time data transmission; for auxiliary data, transmission channels are selected for intermittent uploading according to bandwidth conditions; background data is selected for batch uploading and is preferentially cached in the vehicle storage device and uploaded when bandwidth is sufficient;

[0066] S5, cross-vehicle data sharing and data correction mechanism: In the bus network, short-range wireless communication is established between multiple buses. Through the vehicle-to-vehicle linkage mechanism, the data cached in one vehicle is shared with other surrounding vehicles, especially in some environments with poor signals or network interruptions. At this time, the surrounding vehicles temporarily supplement the missing data by receiving shared data. If a bus fails to upload data in time due to network problems, it will obtain data corrections from other vehicles and supplement them to ensure data consistency and accuracy.

[0067] The sensors in the S1 include:

[0068] GPS positioning unit: obtain the location information of the bus in real time;

[0069] Speed ​​sensor: obtain bus speed data in real time, including instantaneous speed and average speed;

[0070] Passenger flow detection sensor: real-time monitoring of the number of passengers in the car, especially the flow fluctuations when entering and leaving the station, to obtain information on the passenger capacity in the car;

[0071] Temperature and humidity sensor: collects temperature and humidity inside the car;

[0072] Noise sensor: obtains noise level data inside the car;

[0073] In S2: key data include location information and speed data; auxiliary data include the number of passengers and the temperature and humidity in the car; background data include environmental noise.

[0074] S3 specifically includes:

[0075] Key data: Use a lossless compression algorithm with a low compression ratio to ensure that no information is lost during the compression process, maintain data integrity and real-time performance, and meet high timeliness requirements;

[0076] Auxiliary data: A lossy compression algorithm with a medium compression ratio is used to balance data compression rate and accuracy through moderate lossy compression while ensuring the compression rate, so as to optimize bandwidth occupancy and transmission efficiency;

[0077] Background data: Use a lossy compression algorithm with a high compression ratio to reduce bandwidth usage, meet the needs of low-priority data transmission, and reduce system burden.

[0078] A lossless compression algorithm is used for key data to ensure data integrity, so the compression ratio R key The calculation is as follows: Among them, S original is the original data size, S compressed is the compressed data size, R key is the compression ratio, ranging from 0.1 to 0.3 (lossless compression);

[0079] Auxiliary data compression ratio R aux The calculation is as follows: And 0.4≤R aux ≤0.7, where R aux is the compression ratio of the auxiliary data. The selection of this compression ratio takes into account the balance between compression rate and data accuracy.

[0080] Compression ratio R of background data bg The calculation is as follows: And 0.6≤R bg ≤0.9, the compression ratio is relatively high to reduce bandwidth usage. Background data can withstand greater compression loss due to its lower timeliness.

[0081] In S4, an adaptive priority scheduling mechanism is used to schedule the network based on the real-time network bandwidth B. net , transmission delay T key , dynamically adjust the upload priority of different types of data, prioritize the use of low-latency transmission channels for uploading key data, ensure the real-time and integrity of key data, and automatically prioritize the use of low-latency channels with less bandwidth requirements for uploading when the network bandwidth is low, ensure the immediacy of data, and the transmission delay T key Real-time requirements must be met: Among them, S key is the size of the key data, B key is the available bandwidth of the low-latency channel, T key Less than the maximum delay threshold T set by the system maxx .

[0082] Auxiliary data is based on the real-time network bandwidth B net In the case of intermittent upload, the transmission channel is selected. If the bandwidth is sufficient, the auxiliary data will be transmitted continuously. If the bandwidth is tight, interval upload is selected, and part of the data is uploaded during each transmission period. The upload frequency of auxiliary data is f aux Dynamic adjustment based on bandwidth conditions:

[0083] Among them, f aux is the frequency of auxiliary data upload, S aux is the size of the auxiliary data, B net It is the current network bandwidth. According to the network conditions, the system will adjust the upload frequency appropriately to ensure that data transmission does not affect other network usage requirements.

[0084] Background data has the lowest priority, so it can be uploaded in batches. It is first cached to the vehicle storage device. When the network bandwidth is sufficient, the batch upload process is started to upload the cached data to the cloud or other target servers. At this time, the upload rate of background data is v bg Automatically adjust based on bandwidth conditions: Among them, v bg is the background data upload rate, S bg is the size of the background data, T bg is the transmission time of background data. When the network bandwidth is B net When available, choose the maximum bandwidth to transmit background data to minimize the upload delay;

[0085] During the transmission process, the system adjusts the transmission priority of various types of data according to real-time conditions such as network bandwidth and transmission delay to ensure:

[0086] Key data is transmitted in real time and is not affected by bandwidth limitations;

[0087] Assists in balancing data upload frequency and dynamically adjusts it based on bandwidth;

[0088] Background data is uploaded in batches and cached in the vehicle storage first, and then transmitted in batches when there is sufficient bandwidth.

[0089] S5 specifically includes:

[0090] S51, in a bus network, a vehicle-to-vehicle network connection is established between multiple buses through short-range wireless communications (such as WiFi-Direct, Bluetooth, V2X communication, etc.), allowing efficient data transmission between vehicles and realizing sharing and synchronization of vehicle-mounted data;

[0091] S52, when the data of a bus cannot be uploaded due to network interruption or poor signal, the vehicle-to-vehicle linkage mechanism is activated to share the cached data in the bus with surrounding vehicles. The shared data includes all temporarily stored real-time data (such as GPS positioning, vehicle speed, temperature and humidity, etc.), expressed as:

[0092] Among them, D shared is the total size of the shared dataset, For the data cached in the i-th bus, the cached data is transmitted to the surrounding vehicles through short-range wireless communication to ensure that the data is effectively transmitted between multiple vehicles;

[0093] S53, if a bus fails to upload data in time due to network problems, the surrounding vehicles receive the shared data and make corrections and supplements to the data. When supplementing the data, the missing data is updated through the correction algorithm:

[0094] D corrected =D missing ∪D shared and if networkStatus=failed,D vehicle =D corrected ; Among them, D missing For the missing data set, D shared D is the data obtained through car-to-car sharing. corrected is the corrected data set, networkStatus is the current network connection status (such as network failure, network recovery). When a bus cannot upload data through the network, it will obtain data from other vehicles for correction;

[0095] S54, during the data correction process, a data priority scheduling algorithm is used to give priority to selecting high-timeliness and high-priority data for supplementation. The data priority scheduling formula is as follows:

[0096] P data=f(T data ,R data ,D priority ), where P data is the data priority, T data is the timeliness of the data, R data For data integrity requirements, D priority Prioritize data categories and schedule them according to their priority to ensure that data with high real-time requirements (such as GPS, vehicle speed, etc.) are corrected first.

[0097] S51 also includes network connection status detection, which is expressed as:

[0098] Among them, Conn link SignalStrength is the quality of the network connection between vehicles. i is the signal strength between the i-th bus and the target vehicle, ConnectionStatus i The system dynamically determines whether to establish a short-range network connection by calculating the signal strength and connection status of multiple vehicles (such as successful connection, failed connection, etc.).

[0099] The data priority scheduling algorithm specifically includes:

[0100] Timeliness of data data : Indicates the real-time requirement of data. The higher the timeliness, the higher the priority;

[0101] Data integrity requirements data : Indicates the weight of the data on integrity requirements, with a value range of 0≤R data ≤1, the higher the value, the more important the integrity is;

[0102] Data Category Priority D priority : According to the basic priority preset by data type, among which, key data: D priority =1.0; auxiliary data: D priority =0.5; Background data: D priority =0.2;

[0103] The priority is calculated as: Among them, P data It is the priority of the current data. The higher the value, the higher the priority of data transmission or processing. data is the timeliness of the data. The smaller the value, the higher the timeliness requirement. data is the integrity weight, the larger the value, the more important the integrity is. priority It is the preset basic priority, determined according to the data category.

[0104] The specific explanation is as follows:

[0105] 1. Initialize the data list: The data received by the system is a set {D1, D2, ..., D n}, each piece of data D i Contains the following information: Timeliness T data , integrity requirement R data and category priority D priority ;

[0106] 2. Priority calculation: For each piece of data D i , calculate its priority according to the above formula:

[0107] 3. Sort data: by priority P data Sort all data from high to low to get a sorted queue {D1′,D2′,...,D n '},in

[0108] 4. Dynamic resource allocation:

[0109] According to the network bandwidth B net and storage capacity C storage Transmit or modify the data in the sort queue one by one:

[0110] If bandwidth is limited, only high-priority data is transmitted or modified, and low-priority data is ignored;

[0111] If there is sufficient bandwidth, all data will be transmitted in order of priority.

[0112] A bus real-time data collection system, used to implement the above-mentioned bus real-time data collection method, includes the following modules:

[0113] Data acquisition module: used to collect data from multiple sensors of the bus in real time, including GPS positioning module, vehicle speed sensor, accelerometer, passenger flow detection sensor, and in-vehicle environment sensor;

[0114] Data classification module: according to the timeliness and importance of the collected data, the data is divided into multiple categories, including key data, auxiliary data and background data;

[0115] Data compression module: selects the corresponding compression ratio calculation based on the data category, and performs multi-level dynamic compression on different types of data to ensure data integrity and transmission efficiency;

[0116] Priority scheduling module: dynamically adjusts the upload priority of different types of data according to the current network bandwidth and transmission delay, ensuring that key data is transmitted first, auxiliary data is uploaded intermittently, and background data is uploaded in batches;

[0117] On-board storage module: used to cache and store data, temporarily store low-priority data when network bandwidth is insufficient, and upload it when bandwidth is sufficient;

[0118] Vehicle-to-vehicle linkage module: Shares the cached data in one vehicle with other surrounding vehicles through short-range wireless communication, helping to temporarily supplement the missing data in a network interruption environment;

[0119] Data upload module: responsible for uploading high-priority data to the server through a low-latency transmission channel to ensure real-time and accuracy.

[0120] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0121] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A bus real-time data collection method, characterized in that: The following steps are involved: S1, real-time data collection: collect data from multiple sensors on the bus in real time; S2, according to the timeliness and importance of the data, the data is divided into multiple categories, including key data, auxiliary data, and background data; S3, multi-level dynamic compression algorithm selection based on data category: multi-level dynamic compression algorithm is used for different categories of data: different compression ratios are used for key data, auxiliary data and background data; S4, dynamic priority data transmission scheduling based on network status: During data transmission, an adaptive priority scheduling mechanism is adopted to dynamically adjust the upload priority of different types of data according to the current network bandwidth and transmission delay. For key data, low-latency transmission channels are preferentially used for uploading to ensure real-time data transmission; for auxiliary data, transmission channels are selected for intermittent uploading according to bandwidth conditions; background data is selected for batch uploading and is preferentially cached in the vehicle storage device and uploaded when bandwidth is sufficient; S5, cross-vehicle linkage data sharing and data correction mechanism: In the bus network, short-range wireless communication is established between multiple buses. Through the vehicle-to-vehicle linkage mechanism, the data cached in one vehicle is shared with other surrounding vehicles. The surrounding vehicles temporarily supplement the missing data by receiving the shared data. If a bus fails to upload data in time due to network problems, it will obtain data corrections from other vehicles and supplement them to ensure data consistency and accuracy.

2. A bus real-time data collection method according to claim 1, characterized in that: The sensors in S1 include: GPS positioning unit: obtain the location information of the bus in real time; Speed ​​sensor: obtain bus speed data in real time, including instantaneous speed and average speed; Passenger flow detection sensor: real-time monitoring of the number of passengers in the car; Temperature and humidity sensor: collects temperature and humidity inside the car; Noise sensor: obtains noise level data inside the vehicle; In S2: the key data includes location information and speed data; the auxiliary data includes the number of passengers and the temperature and humidity in the vehicle; and the background data includes environmental noise.

3. A bus real-time data collection method according to claim 1, characterized in that: The S3 specifically includes: Key data: Use a lossless compression algorithm with a low compression ratio to ensure that no information is lost during the compression process; Auxiliary data: A lossy compression algorithm with a medium compression ratio is used to balance data compression rate and accuracy through moderate lossy compression while ensuring the compression rate; Background data: Use a lossy compression algorithm with a high compression ratio to reduce bandwidth usage and meet the needs of low-priority data transmission.

4. A bus real-time data collection method according to claim 1, characterized in that: In S4, an adaptive priority scheduling mechanism is adopted to schedule the network according to the real-time network bandwidth B. net , transmission delay T key , dynamically adjust the upload priority of different types of data, the key data is uploaded using low-latency transmission channels first, to ensure the real-time and integrity of key data, when the network bandwidth is low, automatically give priority to uploading low-latency channels with less bandwidth requirements, to ensure the immediacy of data, transmission delay T key Real-time requirements must be met: Among them, S key is the size of the key data, B key is the available bandwidth of the low-latency channel, T key Less than the maximum delay threshold T set by the system maxx .

5. A bus real-time data collection method according to claim 4, characterized in that: The auxiliary data is based on the real-time network bandwidth B net In the case of intermittent upload, the transmission channel is selected. If the bandwidth is sufficient, the auxiliary data will be transmitted continuously. If the bandwidth is tight, interval upload is selected, and part of the data is uploaded during each transmission period. The upload frequency of auxiliary data is f aux Dynamic adjustment based on bandwidth conditions: Among them, f aux is the frequency of auxiliary data upload, S aux is the size of the auxiliary data, B net is the current network bandwidth.

6. A bus real-time data collection method according to claim 5, characterized in that: The background data is first cached in the vehicle storage device. When the network bandwidth is sufficient, the batch upload process is started to upload the cached data to the cloud or other target servers. At this time, the upload rate of the background data is v bg Automatically adjust based on bandwidth conditions: Among them, v bg is the background data upload rate, S bg is the size of the background data, T bg The transmission duration of background data.

7. A bus real-time data collection method according to claim 1, characterized in that: The S5 specifically includes: S51, in a bus network, establishing a vehicle-to-vehicle network connection between multiple buses through short-range wireless communication, allowing efficient data transmission between vehicles and realizing sharing and synchronization of vehicle-mounted data; S52, when the data of a bus cannot be uploaded due to network interruption or poor signal, the vehicle-to-vehicle linkage mechanism is activated to share the cached data in the bus with surrounding vehicles. The shared data includes all temporarily stored real-time data, which is expressed as: Among them, D shared is the total size of the shared dataset, The cached data in the i-th bus is transmitted to surrounding vehicles via short-range wireless communication; S53, if a bus fails to upload data in time due to network problems, the surrounding vehicles receive the shared data and make corrections and supplements to the data. When supplementing the data, the missing data is updated through the correction algorithm: D corrected =D missing ∪D shared and if networkStatus=failed,D vehicle =D corrected ; Among them, D missing For missing data sets, D is the data obtained through car-to-car sharing. corrected is the corrected data set, networkStatus is the current network connection status. When a bus cannot upload data through the network, it will obtain data from other vehicles for correction; S54, during the data correction process, a data priority scheduling algorithm is used to give priority to selecting high-timeliness and high-priority data for supplementation. The data priority scheduling formula is as follows: P data =f(T data ,R data ,D priority ), where P data is the data priority, T data is the timeliness of the data, R data For data integrity requirements, D priority The data category priority.

8. A bus real-time data collection method according to claim 7, characterized in that: The S51 also includes network connection status detection, which is expressed as: Among them, Conn link SignalStrength is the quality of the network connection between vehicles. i is the signal strength between the i-th bus and the target vehicle, ConnectionStatus i The system dynamically determines whether to establish a short-range network connection by calculating the signal strength and connection status of multiple vehicles.

9. A bus real-time data collection method according to claim 8, characterized in that: The data priority scheduling algorithm specifically includes: Timeliness of data data : Indicates the real-time requirement of data. The higher the timeliness, the higher the priority; Data integrity requirements data : Indicates the weight of the data on integrity requirements, with a value range of 0≤R data ≤1, the higher the value, the more important the integrity is; Data Category Priority D priority : According to the basic priority preset by data type, among which, key data: D priority =1.0; auxiliary data: D priority =0.5; Background data: D priority =0.2; The priority is calculated as: Among them, P data It is the priority of the current data. The higher the value, the higher the priority of data transmission or processing. data is the timeliness of the data. The smaller the value, the higher the timeliness requirement. data is the integrity weight, the larger the value, the more important the integrity is. priority It is the preset basic priority, determined according to the data category.

10. A bus real-time data collection system, used to implement a bus real-time data collection method as claimed in any one of claims 1 to 9, characterized in that: Includes the following modules: Data acquisition module: used to collect data in real time from multiple sensors of the bus, including GPS positioning module, vehicle speed sensor, accelerometer, passenger flow detection sensor, and in-vehicle environment sensor; Data classification module: according to the timeliness and importance of the collected data, the data is divided into multiple categories, including key data, auxiliary data and background data; Data compression module: selects the corresponding compression ratio calculation based on the data category, and performs multi-level dynamic compression on different types of data to ensure data integrity and transmission efficiency; Priority scheduling module: dynamically adjusts the upload priority of different types of data according to the current network bandwidth and transmission delay, ensuring that key data is transmitted first, auxiliary data is uploaded intermittently, and background data is uploaded in batches; On-board storage module: used to cache and store data, temporarily store low-priority data when network bandwidth is insufficient, and upload it when bandwidth is sufficient; Vehicle-to-vehicle linkage module: Shares the cached data in one vehicle with other surrounding vehicles through short-range wireless communication, helping to temporarily supplement the missing data in a network interruption environment; Data upload module: responsible for uploading high-priority data to the server through a low-latency transmission channel.

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