Data processing method, apparatus and system

Abstract

Disclosed in the present application are a data processing method, apparatus and system, which are applied to the technical field of vehicles. The method comprises: acquiring first data, wherein the first data comprises a plurality of sampled values, the plurality of sampled values are from at least one sensor, and the number of bits corresponding to each sampled value is a first number of bits; and sending second data, wherein the second data is obtained by compressing the first data. In the second data, a first sampled value among the plurality of sampled values is compressed into a first variation, the number of bits corresponding to the first variation is a second number of bits, and the first number of bits is greater than the second number of bits. The first variation is a variation of the first sampled value relative to a reference value of the first sampled value, and the reference value of the first sampled value is an adjacent sampled value of the first sampled value or a baseline sampled value of a sensor collecting the first sampled value. In this way, the bandwidth required to be consumed for transmitting sampled data of a sensor can be reduced without increasing hardware costs.

Description

A data processing method, apparatus and system Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a data processing method, apparatus and system. Background Technology

[0002] Vehicles are equipped with numerous sensors to monitor various physical quantities in the vehicle environment (such as collision-related quantities, temperature, humidity, etc.). The sensors are typically connected to the vehicle control center via a controller, which then transmits the sensor samples to the vehicle control center via an in-vehicle signal bus (such as CAN bus, LIN bus, etc.).

[0003] Sensors continuously collect data on changes in corresponding physical quantities over time. The amount of data sampled by a single sensor is large, and the amount of data sampled by multiple sensors is even larger. However, the bandwidth resources between the controller and the vehicle control center are limited. The transmission of data between the controller and the vehicle control center consumes a large proportion of the bandwidth resources, affecting system performance and potentially leading to data transmission failures. Summary of the Invention

[0004] This application discloses a data processing method, apparatus, and system that can reduce the bandwidth required to transmit sensor sampling data without increasing hardware costs, thereby improving system performance.

[0005] In a first aspect, this application provides a data processing method, comprising: firstly, acquiring first data, the first data including multiple sampled values, which are obtained from at least one sensor, each sampled value corresponding to a first number of bits; and then, sending second data, the second data being obtained by compressing the first data. Specifically, in the second data, the first sampled value among the multiple sampled values ​​is compressed into a first change, the first change being the change of the first sampled value relative to a reference value of the first sampled value, the reference value being an adjacent sampled value of the first sampled value or a reference sampled value of the sensor that acquired the first sampled value; the number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits.

[0006] Here, the sampled value is the digital data obtained by the first control device after performing analog-to-digital conversion on the output signal of the connected sensor. The number of bits corresponding to each sampled value is the first number of bits, which means that the number of bits required to encode each sampled value in binary form is the first number of bits.

[0007] For example, the at least one sensor includes a first sensor, the first sampled value is obtained by the first sensor in the i-th sampling, and the adjacent sampled value of the first sampled value is obtained by the first sensor in the (i-1)-th sampling, where i is an integer greater than 1. In some schemes, the adjacent sampled value of the sampled value may also be a sampled value collected by the same sensor at a certain sampling interval from the sampled value. For example, when i is greater than 2, the adjacent sampled value of sampled value 1 may be obtained by sensor 1 in the (i-2)-th sampling.

[0008] For example, the reference sample value is associated with the sensor, and the reference sample value may differ for different sensors. For instance, the reference sample value of a sensor can be the average noise floor of the sensor under no-excitation conditions. If the sensor is a collision sensor, the average noise floor of the collision sensor can be any sample value of the collision sensor without a collision signal input, or it can be the average of multiple sample values ​​of the collision sensor within a preset time period without a collision signal input. In this case, the applicable sensor could be a collision sensor, vibration sensor, etc. As another example, the reference sample value of a sensor can be the initial sample value of the sensor under no-abnormal monitoring conditions, or it can be the average of multiple sample values ​​of the sensor within a preset time period under no-abnormal monitoring conditions. In this case, the applicable sensor could be a temperature sensor, humidity sensor, etc.

[0009] In the above method, the sampled value in the first data is compressed into the change corresponding to that sampled value. The number of bits corresponding to the change is greater than the number of bits corresponding to the sampled value. Thus, the number of bits required to represent the compressed sampled value in binary form is less, reducing the number of bits required to transmit a single sampled value and also reducing the bandwidth consumed in transmitting the sensor's sampled data, which is beneficial for improving system performance. Furthermore, implementing this method requires no additional hardware, resulting in low hardware costs.

[0010] In one possible implementation of the first aspect, the plurality of sampled values ​​are derived from at least one sensor, including:

[0011] These multiple sample values ​​are obtained through multiple samplings from a single sensor;

[0012] These multiple sample values ​​are obtained through a single sampling from multiple sensors; or,

[0013] These multiple sample values ​​are obtained through multiple samplings from multiple sensors.

[0014] By implementing the above method, when these multiple sampled values ​​are obtained through a single sampling from multiple sensors or through multiple samplings from multiple sensors, it is convenient for the receiving end to analyze the sampled data from multiple sensors simultaneously. For example, if the sensor is a collision sensor, the receiving end can analyze whether a collision has occurred at multiple locations at the same time based on the sampled data from the collision sensor at different locations. When these multiple sampled values ​​are obtained through multiple samplings from a single sensor, it is convenient for the receiving end to perform a comprehensive analysis of the sampled data from that sensor.

[0015] In one possible implementation of the first aspect, the first sample value is at least a portion of the plurality of sample values.

[0016] By implementing the above method, at least some of the sampled values ​​in the first data are compressed. The number of bits corresponding to the compressed sampled values ​​is less than the number of bits corresponding to the uncompressed sampled values, which reduces the amount of data transmitted to a certain extent and also reduces the bandwidth required to transmit the sampled data of the sensor.

[0017] In one possible implementation of the first aspect, the number of bits corresponding to the first change is a second number of bits, including: indicating the sign of the first change by one bit of the second number of bits, and indicating the magnitude of the first change by the remaining bits of the second number of bits.

[0018] By implementing the above method, considering that the change can be positive or negative, the sign and magnitude of the change are encoded separately using different bits. This expands the range of data representation within a limited storage space, facilitates the representation of multiple data types, and helps computers process data efficiently.

[0019] In one possible implementation of the first aspect, the number of these multiple sampled values ​​is M, where M sampled values ​​are obtained from M sensors in the i-th sampling, and the j-th sampled value is obtained from the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; these M sampled values ​​include the first sampled value; in the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

[0020] By implementing the above method, each sample value in the first data is compressed into the change corresponding to the sample value. The number of bits corresponding to each change is less than the number of bits corresponding to the sample value, which minimizes the amount of data transmitted and greatly reduces the consumption of bandwidth resources.

[0021] In one possible implementation of the first aspect, sending the second data includes: sending a first data frame carrying the second data, the first data frame including the following information:

[0022] The first flag bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained by compression.

[0023] M second identifier bits, the j-th second identifier bit is used to indicate the sign of the j-th change; and,

[0024] The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

[0025] Implementing the above method, the first identifier enables the receiving end to know that the data in the first data frame needs to be decompressed, and the M second identifier bits and M groups of third identifier bits enable the receiving end to obtain each change.

[0026] In one possible implementation of the first aspect, before sending the second data, the data processing method further includes: sending third data, the third data including initial sampled values ​​corresponding to M sensors, the number of bits corresponding to the initial sampled values ​​being the first number of bits, and the initial sampled values ​​being used to decompress the second data into the first data.

[0027] For example, when the change is obtained based on adjacent sample values, the initial sample value corresponding to the sensor is the first sample value of the sensor during data transmission; when the change is obtained based on a reference sample value, the initial sample value corresponding to the sensor is the reference sample value of the sensor.

[0028] By implementing the above method, the transmission of the third data can help the receiving end to successfully restore the second data to the first data.

[0029] In one possible implementation of the first aspect, sending the third data includes: sending a second data frame carrying the third data, the second data frame including the following information:

[0030] The fourth flag bit indicates that the second data frame is an absolute data frame, and the data carried by an absolute data frame is uncompressed; and,

[0031] The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampled value corresponding to the j-th sensor.

[0032] Implementing the above method, the fourth identifier bit informs the receiver that decompression is unnecessary and the data in the second data frame can be used directly. The M groups of fifth identifier bits enable the receiver to obtain the initial sampled value corresponding to each sensor. As an absolute data frame, the second data frame allows the receiver to reconstruct the first data from the second data in the next data frame (i.e., the first data frame).

[0033] In one possible implementation of the first aspect, the data processing method further includes: sending a third data frame when any of the following conditions are met, wherein the third data frame is an absolute data frame, the third data frame carries fourth data, the sampled values ​​in the fourth data are obtained by sampling by M sensors after the first data, and the number of bits corresponding to each sampled value in the fourth data is the number of bits in the first data.

[0034] The time interval since the last transmission of an absolute data frame has reached the preset duration;

[0035] The number of compressed data frames sent since the last transmission of an absolute data frame has reached a preset value; or,

[0036] Receive frame loss indication information from the receiving end.

[0037] When the first data frame is sent as an absolute data frame, and subsequent data frames are sent as compressed data frames, if each change in the second data frame is obtained based on adjacent sample values, frame loss may occur during data transmission. For example, if a compressed data frame in the middle is lost, it will cause deviations when subsequent compressed data frames are restored. By implementing the above method, the first control device can actively (e.g., periodically or in the form of a quantitative compressed data frame) send a new absolute data frame to the second control device, or send a new absolute data frame to the second control device in response to a frame loss indication from the second control device, so as to correct the deviations that occur during the restoration of compressed data frames in a timely manner.

[0038] In one possible implementation of the first aspect, in the second data, the second sampled value among the plurality of sampled values ​​is compressed into a second change amount, which is the change amount of the second sampled value relative to a reference value of the second sampled value. The reference value of the second sampled value is an adjacent sampled value of the second sampled value or a reference sampled value of the sensor that acquires the second sampled value. The absolute value of the first change amount is less than or equal to a change threshold, the absolute value of the second change amount is greater than the change threshold, the number of bits corresponding to the second change amount is a third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

[0039] By implementing the above method, the change corresponding to each sample value is represented in bits according to its magnitude. The smaller the absolute value of the change, the smaller the number of bits corresponding to that change, which is equivalent to performing different degrees of compression. In this way, more data can be compressed using fewer bits, further improving the degree of data compression.

[0040] In one possible implementation of the first aspect, when the reference value of each of the plurality of sampled values ​​is represented in the form of a benchmark sampled value, the absolute value of the change obtained by compressing each of the plurality of sampled values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

[0041] By implementing the above method, a change threshold is used to classify and encode the sampled values. Smaller sampled values ​​are encoded with a smaller number of bits, thus compressing the data volume. For vibration sensors or collision sensors, the amplitude of the sampled data is relatively small (i.e., less than the change threshold) in most vehicle situations. Only when a collision occurs will the amplitude of the sampled data exceed the change threshold. Therefore, classifying and encoding the sampled values ​​based on their amplitude can reduce the amount of data transmitted in most time periods.

[0042] In one possible implementation of the first aspect, the plurality of sampled values ​​also includes a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information used to indicate that the third sampled value is represented by the fourth number of bits.

[0043] By implementing the above method, the sample value with the smaller absolute value among multiple sample values ​​can also be represented by a smaller number of bits to achieve compression. The smaller the absolute value of the sample value, the smaller the number of bits corresponding to that sample value, which can reduce the amount of data transmitted to a certain extent.

[0044] In one possible implementation of the first aspect, the sensor is a collision sensor, a vibration sensor, a temperature sensor, or a humidity sensor.

[0045] The above implementation method is suitable for scenarios where the sensor has a large number of time-series sensor signals to be transmitted.

[0046] Secondly, this application provides a data processing method, which includes: first, acquiring second data, which is obtained by compressing first data; and then, decompressing the second data to obtain the first data. The first data includes multiple sampled values, which are obtained from at least one sensor, and each sampled value corresponds to a first number of bits. In the second data, the first sampled value among these multiple sampled values ​​is compressed into a first change, which is the change of the first sampled value relative to a reference value of the first sampled value. The reference value of the first sampled value is an adjacent sampled value of the first sampled value or a reference sampled value of the sensor that acquired the first sampled value. The number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits.

[0047] In the above method, the second data is compressed data. The number of bits corresponding to the change in the second data is less than the number of bits corresponding to the change before compression (i.e., the sampled value), thus reducing the amount of data transmitted. After the receiving end obtains the second data, it can decompress it into the first data. In this way, without increasing hardware costs, bandwidth resource consumption is reduced during the transmission of sensor data, thereby improving system performance.

[0048] For the beneficial effects of features not described in the second aspect below, please refer to the description of the beneficial effects of the corresponding features in the first aspect, which will not be repeated here.

[0049] In one possible implementation of the second aspect, these multiple sampled values ​​originate from at least one sensor, including:

[0050] These multiple sample values ​​are obtained through multiple samplings from a single sensor;

[0051] These multiple sample values ​​are obtained through a single sampling from multiple sensors; or,

[0052] These multiple sample values ​​are obtained through multiple samplings from multiple sensors.

[0053] In one possible implementation of the second aspect, the first sample value is at least a portion of the plurality of sample values.

[0054] In one possible implementation of the second aspect, the number of these multiple sampled values ​​is M, where M sampled values ​​are obtained from M sensors in the i-th sampling, and the j-th sampled value is obtained from the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; the M sampled values ​​include the first sampled value; in the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

[0055] In one possible implementation of the second aspect, obtaining the second data includes: receiving a first data frame carrying the second data; and obtaining the second data from the first data frame; wherein the first data frame includes the following information:

[0056] The first flag bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained by compression.

[0057] M second identifier bits, the j-th second identifier bit is used to indicate the sign of the j-th change; and,

[0058] The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

[0059] In one possible implementation of the second aspect, the data processing method further includes: receiving third data, the third data including initial sampled values ​​corresponding to M sensors, the number of bits corresponding to the initial sampled values ​​being the first number of bits; the above-mentioned decompression of the second data to obtain the first data includes: decompressing the second data according to the third data to obtain the first data.

[0060] In one possible implementation of the second aspect, receiving the third data includes: receiving a second data frame carrying the third data, the second data frame including the following information:

[0061] The fourth flag bit indicates that the second data frame is an absolute data frame, and the data carried by an absolute data frame is uncompressed; and,

[0062] The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampled value corresponding to the j-th sensor.

[0063] In one possible implementation of the second aspect, the data processing method further includes: receiving a third data frame when any of the following conditions are met, wherein the third data frame is an absolute data frame, the third data frame carries fourth data, the sampled values ​​in the fourth data are obtained by sampling by M sensors after the first data, and the number of bits corresponding to each sampled value in the fourth data is the number of bits in the first data.

[0064] The time interval since the last received absolute data frame has reached the preset duration;

[0065] The number of compressed data frames received since the last reception of an absolute data frame has reached a preset value; or,

[0066] Send frame loss indication information to the sending end.

[0067] By implementing the above method, in the event of frame loss during data transmission, deviations occurring during the reconstruction of compressed data frames can be corrected promptly based on newly transmitted absolute data frames from the sending end. Alternatively, when frame loss is detected in the compressed data frames received from the receiving end, frame loss indication information can be proactively sent to the sending end to trigger the sending end to transmit new absolute data frames.

[0068] In one possible implementation of the second aspect, in the second data, the second sampled value among the multiple sampled values ​​is compressed into a second change amount, which is the change amount of the second sampled value relative to a reference value of the second sampled value. The reference value of the second sampled value is the adjacent sampled value of the second sampled value or the reference sampled value of the sensor that acquires the second sampled value. The absolute value of the first change amount is less than or equal to a change threshold, the absolute value of the second change amount is greater than the change threshold, the number of bits corresponding to the second change amount is a third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

[0069] In one possible implementation of the second aspect, when the reference value of each of the plurality of sampled values ​​is represented in the form of a benchmark sampled value, the absolute value of the change obtained by compressing each of the plurality of sampled values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

[0070] In one possible implementation of the second aspect, the plurality of sampled values ​​also include a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information, which is used to indicate that the third sampled value is represented by the fourth number of bits.

[0071] In one possible implementation of the second aspect, the data processing method further includes: receiving data collected by a target sensor; and performing scene detection based on the first data and the data collected by the target sensor, wherein the target sensor is a sensor other than at least one other sensor, and the scene detection includes at least one of the following:

[0072] Did a collision occur?

[0073] Are there any people near the vehicle?

[0074] Has anyone touched the vehicle body?

[0075] By implementing the above method, and combining the sampling data from at least one sensor with the data collected by the target sensor for comprehensive analysis of scene detection, not only is information fusion of multiple sensors achieved, but the accuracy and reliability of scene detection are also improved.

[0076] In one possible implementation of the second aspect, the data processing method further includes: receiving data collected by a target sensor, wherein the target sensor is a sensor other than at least one sensor; determining whether to reconstruct the first data based on the data collected by the target sensor; the above-mentioned decompression of the second data to obtain the first data includes: if it is determined that the first data has been reconstructed, decompressing the second data to obtain the first data.

[0077] By implementing the above method, the analysis of whether the physical quantity monitored by at least one sensor is abnormal is combined with the data collected by the target sensor. The decompression of the second data is only performed when an abnormality is determined to have occurred. Most of the time, the system is in a scenario where no abnormality is detected. Therefore, it is beneficial to avoid consuming the computing resources required to decompress the second data for most of the time.

[0078] In one possible implementation of the second aspect, the at least one sensor is a collision sensor, a vibration sensor, a temperature sensor, or a humidity sensor.

[0079] Thirdly, this application provides a data processing apparatus, which includes an acquisition unit for acquiring first data, the first data including multiple sampled values ​​from at least one sensor, each sampled value corresponding to a first number of bits; and a transmission unit for transmitting second data, the second data being obtained by compressing the first data through the processing unit in the data processing apparatus. In the second data, the first sampled value among the multiple sampled values ​​is compressed into a first change, the first change being the change of the first sampled value relative to a reference value of the first sampled value, the reference value being an adjacent sampled value of the first sampled value or a reference sampled value of the sensor acquiring the first sampled value; the number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits.

[0080] In one possible implementation of the third aspect, the aforementioned plurality of sampled values ​​originate from at least one sensor, including:

[0081] These multiple sample values ​​are obtained through multiple samplings from a single sensor;

[0082] These multiple sample values ​​are obtained through a single sampling from multiple sensors; or,

[0083] These multiple sample values ​​are obtained through multiple samplings from multiple sensors.

[0084] In one possible implementation of the third aspect, the first sample value is at least a portion of the plurality of sample values.

[0085] In one possible implementation of the third aspect, the number of bits corresponding to the first change is the second number of bits, including: indicating the sign of the first change by one bit of the second number of bits, and indicating the magnitude of the first change by the remaining bits of the second number of bits.

[0086] In one possible implementation of the third aspect, the number of these multiple sampled values ​​is M, where M sampled values ​​are obtained from M sensors in the i-th sampling, and the j-th sampled value is obtained from the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; these M sampled values ​​include the first sampled value; in the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

[0087] In one possible implementation of the third aspect, the sending unit is specifically configured to: send a first data frame, the first data frame carrying second data, the first data frame including the following information:

[0088] The first flag bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained by compression.

[0089] M second identifier bits, the j-th second identifier bit is used to indicate the sign of the j-th change; and,

[0090] The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

[0091] In one possible implementation of the third aspect, the transmitting unit is further configured to: transmit third data, the third data including initial sampled values ​​corresponding to M sensors, the number of bits corresponding to the initial sampled values ​​being the first number of bits, and the initial sampled values ​​being used to decompress the second data into the first data.

[0092] In one possible implementation of the third aspect, the sending unit is specifically configured to: send a second data frame, the second data frame carrying third data, the second data frame including the following information:

[0093] The fourth flag bit indicates that the second data frame is an absolute data frame, and the data carried by an absolute data frame is uncompressed; and,

[0094] The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampled value corresponding to the j-th sensor.

[0095] In one possible implementation of the third aspect, the transmitting unit is further configured to: transmit a third data frame when any of the following conditions are met, wherein the third data frame is an absolute data frame, the third data frame carries fourth data, the sampled values ​​in the fourth data are obtained by sampling from M sensors after the first data, and the number of bits corresponding to each sampled value in the fourth data is the number of bits in the first data.

[0096] The time interval since the last transmission of an absolute data frame has reached the preset duration;

[0097] The number of compressed data frames sent since the last transmission of an absolute data frame has reached a preset value; or,

[0098] The acquisition unit receives frame loss indication information from the receiving end.

[0099] In one possible implementation of the third aspect, in the second data, the second sampled value among the multiple sampled values ​​is compressed into a second change amount, which is the change amount of the second sampled value relative to a reference value of the second sampled value. The reference value of the second sampled value is the adjacent sampled value of the second sampled value or the reference sampled value of the sensor that acquires the second sampled value. The absolute value of the first change amount is less than or equal to a change threshold, the absolute value of the second change amount is greater than the change threshold, the number of bits corresponding to the second change amount is a third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

[0100] In one possible implementation of the third aspect, when the reference value of each of these multiple sample values ​​is represented in the form of a benchmark sample value, the absolute value of the change obtained by compressing each of the multiple sample values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

[0101] In one possible implementation of the third aspect, the plurality of sampled values ​​also includes a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information, which is used to indicate that the third sampled value is represented by the fourth number of bits.

[0102] In one possible implementation of the third aspect, the sensor is a collision sensor, vibration sensor, temperature sensor, or humidity sensor.

[0103] Fourthly, this application provides a data processing apparatus, which includes an acquisition unit for acquiring second data, which is obtained by compressing first data; and a processing unit for decompressing the second data to obtain the first data. The first data includes multiple sampled values, which are obtained from at least one sensor, and each sampled value corresponds to a first number of bits. In the second data, the first sampled value among the multiple sampled values ​​is compressed into a first change, which is the change of the first sampled value relative to a reference value of the first sampled value. The reference value of the first sampled value is an adjacent sampled value of the first sampled value or a reference sampled value of the sensor that acquired the first sampled value. The number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits.

[0104] In one possible implementation of the fourth aspect, these multiple sampled values ​​originate from at least one sensor, including:

[0105] These multiple sample values ​​are obtained through multiple samplings from a single sensor;

[0106] These multiple sample values ​​are obtained through a single sampling from multiple sensors; or,

[0107] These multiple sample values ​​are obtained through multiple samplings from multiple sensors.

[0108] In one possible implementation of the fourth aspect, the first sample value is at least a portion of the plurality of sample values.

[0109] In one possible implementation of the fourth aspect, the number of bits corresponding to the first change is the second number of bits, including: indicating the sign of the first change by one bit of the second number of bits, and indicating the magnitude of the first change by the remaining bits of the second number of bits.

[0110] In one possible implementation of the fourth aspect, the number of these multiple sampled values ​​is M, where M sampled values ​​are obtained from M sensors in the i-th sampling, and the j-th sampled value is obtained from the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; the M sampled values ​​include the first sampled value; in the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

[0111] In one possible implementation of the fourth aspect, the acquisition unit is specifically configured to: receive a first data frame, the first data frame carrying second data; and acquire the second data from the first data frame; wherein the first data frame includes the following information:

[0112] The first flag bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained by compression.

[0113] M second identifier bits, the j-th second identifier bit is used to indicate the sign of the j-th change; and,

[0114] The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

[0115] In one possible implementation of the fourth aspect, the acquisition unit is further configured to: receive third data, the third data including initial sampled values ​​corresponding to M sensors, the number of bits corresponding to the initial sampled values ​​being the first number of bits; the processing unit is specifically configured to: decompress the second data according to the third data to obtain the first data.

[0116] In one possible implementation of the fourth aspect, the acquisition unit is specifically configured to: receive a second data frame, the second data frame carrying third data, the second data frame including the following information:

[0117] The fourth flag bit indicates that the second data frame is an absolute data frame, and the data carried by an absolute data frame is uncompressed; and,

[0118] The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampled value corresponding to the j-th sensor.

[0119] In one possible implementation of the fourth aspect, the acquisition unit is further configured to: receive a third data frame when any of the following conditions are met, wherein the third data frame is an absolute data frame, the third data frame carries fourth data, the sampled values ​​in the fourth data are obtained by sampling by M sensors after the first data, and the number of bits corresponding to each sampled value in the fourth data is the number of bits in the first data.

[0120] The time interval since the last received absolute data frame has reached the preset duration;

[0121] The number of compressed data frames received since the last reception of an absolute data frame has reached a preset value; or,

[0122] The data processing unit sends frame loss indication information to the sending end.

[0123] In one possible implementation of the fourth aspect, in the second data, the second sampled value among the multiple sampled values ​​is compressed into a second change amount, which is the change amount of the second sampled value relative to a reference value of the second sampled value. The reference value of the second sampled value is the adjacent sampled value of the second sampled value or the reference sampled value of the sensor that acquires the second sampled value. The absolute value of the first change amount is less than or equal to a change threshold, the absolute value of the second change amount is greater than the change threshold, the number of bits corresponding to the second change amount is a third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

[0124] In one possible implementation of the fourth aspect, when the reference value of each of the plurality of sampled values ​​is represented in the form of a benchmark sampled value, the absolute value of the change obtained by compressing each of the plurality of sampled values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

[0125] In one possible implementation of the fourth aspect, the plurality of sampled values ​​also include a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information, which is used to indicate that the third sampled value is represented by the fourth number of bits.

[0126] In one possible implementation of the fourth aspect, the acquisition unit is further configured to: receive data collected by the target sensor; the processing unit is further configured to perform scene detection based on the first data and the data collected by the target sensor, wherein the target sensor is a sensor other than at least one sensor, and the scene detection includes at least one of the following:

[0127] Did a collision occur?

[0128] Are there any people near the vehicle?

[0129] Has anyone touched the vehicle body?

[0130] In one possible implementation of the fourth aspect, the acquisition unit is further configured to: receive data collected by a target sensor, wherein the target sensor is a sensor other than at least one sensor; and the processing unit is further configured to: determine whether to reconstruct the first data based on the data collected by the target sensor, and if it is determined that the first data has been reconstructed, decompress the second data to obtain the first data.

[0131] In one possible implementation of the fourth aspect, at least one of the aforementioned sensors is a collision sensor, a vibration sensor, a temperature sensor, or a humidity sensor.

[0132] Fifthly, this application provides a data processing apparatus, which includes a processor and a memory, wherein the memory is used to store program instructions; the processor invokes the program instructions in the memory to cause the apparatus to execute the method in the first aspect or any possible implementation of the first aspect, or to execute the method in the second aspect or any possible implementation of the second aspect.

[0133] In a sixth aspect, this application provides a data processing system, which includes a data compression device and a data decompression device. The data compression device is used to execute the method in the first aspect or any possible implementation of the first aspect, and the data decompression device is used to execute the method in the second aspect or any possible implementation of the second aspect.

[0134] For example, the data compression apparatus may be an apparatus in the third aspect or any possible implementation of the third aspect, or an apparatus in the fifth aspect for implementing the method of the first aspect; the data decompression apparatus may be an apparatus in the fourth aspect or any possible implementation of the fourth aspect, or an apparatus in the fifth aspect for implementing the method of the second aspect.

[0135] In a seventh aspect, this application provides a vehicle that includes the apparatus as described in the third aspect or any possible implementation thereof, or includes the apparatus as described in the fourth aspect or any possible implementation thereof, or includes the apparatus described in the fifth aspect, or includes the data processing system described in the sixth aspect.

[0136] Eighthly, this application provides a computer-readable storage medium including computer instructions that, when executed by a processor, implement the method in the first aspect or any possible implementation of the first aspect, or implement the method in the second aspect or any possible embodiment of the second aspect.

[0137] Ninthly, this application provides a computer program product that, when executed by a processor, implements the method described in the first aspect or any possible embodiment of the first aspect, or implements the method described in the second aspect or any possible embodiment of the second aspect. Exemplarily, the computer program product may be a software installation package. Attached Figure Description

[0138] Figure 1 is a schematic diagram of the architecture of a data processing system provided in an embodiment of this application;

[0139] Figure 2 is a flowchart of a data processing method provided in an embodiment of this application;

[0140] Figure 3 is a schematic diagram of data compression provided in an embodiment of this application;

[0141] Figure 4A is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0142] Figure 4B is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0143] Figure 4C is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0144] Figure 4D is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0145] Figure 4E is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0146] Figure 4F is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0147] Figure 4G is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0148] Figure 4H is a schematic diagram of a first data and a second data provided in an embodiment of this application;

[0149] Figure 5A is a schematic diagram of the format of a first data frame provided in an embodiment of this application;

[0150] Figure 5B is a schematic diagram of the format of a first data frame provided in an embodiment of this application;

[0151] Figure 6 is a schematic diagram of the format of a second data frame provided in an embodiment of this application;

[0152] Figure 7 is a schematic diagram of the transmission of an absolute data frame provided in an embodiment of this application;

[0153] Figure 8 is a flowchart of another data compression method provided in an embodiment of this application;

[0154] Figure 9 is a schematic diagram of the structure of a data processing device provided in an embodiment of this application;

[0155] Figure 10 is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0156] In this scheme, prefixes such as "first" and "second" are used solely to distinguish different descriptive objects and do not impose any restrictions on the position, order, priority, quantity, or content of the described objects. For example, if the described object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the modified "fields" are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the described object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority of the "levels." Furthermore, the number of described objects is not limited by prefixes; it can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device," then "first device" and "second device" can be the same device, devices of the same type, or devices of different types. Similarly, if the object being described is "information," then "first information" and "second information" can be information with the same content or information with different content. In summary, the use of prefixes to distinguish the objects being described in the embodiments of this application does not constitute a limitation on the objects being described. The description of the objects being described is based on the claims or the context of the embodiments, and should not constitute an unnecessary limitation due to the use of such prefixes.

[0157] This solution provides a data processing system that, without increasing hardware costs, reduces the bandwidth required to transmit sensor sampling data by partially or completely compressing the sensor's sampling data, thereby improving system performance.

[0158] The composition of the data processing system is described in detail below with reference to Figure 1. Referring to Figure 1, Figure 1 is a schematic diagram of the architecture of a data processing system provided in an embodiment of this application. In Figure 1, the data processing system 10 includes a first control device, a second control device, and at least one sensor, wherein the at least one sensor is connected to the first control device in a wired and / or wireless manner, and the first control device is connected to the second control device in a wired or wireless manner.

[0159] For example, the data processing system 10 can be deployed on a terminal. The terminal can include mobile intelligent terminals or vehicles such as vehicles or robots. For example, vehicles can be vehicles (such as commercial vehicles, passenger cars, motorcycles, flying cars, etc.), industrial vehicles (such as forklifts, trailers, tractors, etc.), engineering vehicles, etc. As another example, robots can be automated guided vehicles (AGVs), walking conversational robots, service robots, etc.

[0160] As an example, when the data processing system 10 is deployed on a vehicle, the sensor is connected to the first control device via an analog cable, and the first control device is connected to the second control device via an in-vehicle wired signal bus. The in-vehicle wired signal bus can be one or more of the following: a controller area network (CAN) bus, a local interconnect network (LIN) bus, a FlexRay bus, or other signal buses used for transmitting monitoring data.

[0161] For example, the at least one sensor described above can be a collision sensor, a vibration sensor, a temperature sensor, or a humidity sensor. As an example, this at least one sensor is a sensor that measures the same physical parameter. It is understood that because the sensor periodically collects data, the data collected by the sensor generally has a temporal sequence. For example, the installation location of the collision sensor includes, but is not limited to, other locations on the vehicle such as the hood, front bumper, left front door, right front door, left rear door, right rear door, and rear bumper.

[0162] The first control device is a device with computing capabilities. The first control device can compress first data to obtain second data and transmit the second data to the second control device, wherein the first data originates from at least one of the aforementioned sensors. Exemplarily, the first control device can be a microcontroller unit (MCU) or other processing unit. For example, an MCU is also called a single-chip microcomputer.

[0163] For example, the first control device integrates an analog-to-digital converter (ADC), which is used to convert the output signal of the sensor connected to the first control device into a sampled value.

[0164] Here, the computing power of the second control device is greater than that of the first control device. For example, the second control device can be a system-on-chip (SOC), an artificial intelligence (AI) accelerator chip, etc. Alternatively, the second control device can also be a domain controller within the vehicle or a component within a domain controller; the component can be a chip, a control unit, etc. For example, the domain controller can be a hardware-software integrated platform supporting intelligent driving, i.e., a vehicle computing platform, such as a mobile data center (MDC); or it can be a hardware-software integrated platform supporting body control and chassis control, such as a vehicle domain controller (VDC). In some solutions, the domain controller can also be a controller that integrates the functions of multiple components from the VDC, MDC, and cockpit domain controller (CDC). Here, the CDC is an example of a hardware-software integrated platform for providing in-vehicle multimedia services. As an example, by integrating the VDC, MDC, and CDC, a domain controller capable of providing body control functions, autonomous driving control functions, and cockpit control functions is obtained; in this case, the domain controller can also be called a central computing unit.

[0165] For example, the second control device can decompress the second data into the first data. Furthermore, when the data processing system 10 is deployed on a vehicle, the second control device can also use the obtained first data as input information for multi-sensor information fusion to realize scene detection applications, wherein scene detection includes, but is not limited to, whether a collision has occurred, whether a person has touched the vehicle body, and whether a person has approached the vehicle.

[0166] In some possible embodiments, the data processing system 10 may further include a target sensor, which is connected to the second control device wirelessly and / or via a wired connection. In this case, the second control device can acquire data collected by the target sensor, which is then used by the second control device for multi-sensor information fusion applications.

[0167] Here, the target sensor is a sensor other than at least one of the aforementioned sensors. For example, the target sensor includes at least one of vehicle-mounted sensors such as a camera, LiDAR, millimeter-wave radar, ultrasonic sensor, wheel speed sensor, and pressure sensor.

[0168] The data processing system shown in Figure 1 can be applied to a variety of application scenarios, such as the following: mobile internet (MI), industrial control, self-driving, transportation safety, internet of things (IoT), smart city, or smart home.

[0169] The data processing system shown in Figure 1 can be applied to various network types, such as one or more of the following: SparkLink, Long Term Evolution (LTE) networks, 5th generation mobile communication technology (5G), wireless local area networks (e.g., Wi-Fi), Bluetooth (BT), Zigbee, or vehicular short-range wireless communication networks, etc.

[0170] Figure 1 is merely an exemplary architecture diagram of a data processing system. In some embodiments, the data processing system shown in Figure 1 may include more or fewer functional entities. For example, in Figure 1, the target sensor may also be connected to the second control device via other control devices (other than the first control device described above). Furthermore, the method provided in this embodiment can be applied to the data processing system shown in Figure 1.

[0171] Referring to Figure 2, which is a flowchart of a data processing method provided in an embodiment of this application, this method can be applied to the data processing system 10 shown in Figure 1, specifically between at least one sensor, a first control device, and a second control device. In some possible embodiments, the data processing system 10 further includes a target sensor. The method shown in the embodiment of Figure 1 includes, but is not limited to, the following steps S201-S206:

[0172] S201: The first control device acquires first data, which includes multiple sampled values, each sampled value having a corresponding number of bits as the first number of bits, and these multiple sampled values ​​come from at least one sensor.

[0173] Here, the sampled value is digital data obtained by the first control device after performing analog-to-digital conversion on the output signal of the connected sensor. Taking one of the sensors as an example, the sensor generally samples periodically (e.g., periodically), so the sensor will periodically output the sampling signal of that time to the first control device. The sampling signal is an analog signal, and the first control device performs analog-to-digital conversion on the sampling signal output by the sensor to obtain the sampled value of the sensor at that time.

[0174] It is understandable that the sampling times of multiple sensors can be the same or different, but the error between the sampling times corresponding to the same acquisition is within the allowable time error range.

[0175] For example, the number of bits corresponding to each sample value is the first number of bits, meaning that the number of bits required to encode each sample value in binary form is the first number of bits. For any given sample value, the sample value does not exceed the data range indicated by the first number of bits.

[0176] Taking a first bit count of 12 bits as an example, if all sampled values ​​are positive, then the data range indicated by the first bit count is [0, 2]. 12 -1]; When the sampled value contains both positive and negative numbers, the highest bit in the first bit set is used to represent the sign of the sampled value, and the remaining bits in the first bit set are used to represent the magnitude of the sampled value. Therefore, the data range indicated by the remaining bits in the first bit set is [0, 2]. 11 -1], while the data range indicated by the first bit number is [-(2] 11 -1),2 11 -1].

[0177] As an example, multiple sampled values ​​come from at least one sensor, including any of the following cases:

[0178] Scenario 1: These multiple sample values ​​are obtained through multiple samplings from a single sensor;

[0179] Scenario 2: These multiple sample values ​​are obtained through a single sampling from multiple sensors; or,

[0180] Case 3: These multiple sample values ​​are obtained through multiple samplings from multiple sensors.

[0181] Regarding scenario 1 above, the first sensor is any one of the at least one sensors mentioned above. Assume that these multiple sampled values ​​are obtained through multiple samplings by the first sensor, where each sampling by the sensor yields one sampled value. These multiple sampled values ​​can be represented as {v2, ..., v...} N}, where v2 is obtained from the second sample of the first sensor, ..., v N This is obtained from the Nth sample taken by the first sensor.

[0182] Regarding scenario 2 above, assume that these multiple sampled values ​​are obtained through a single sampling (e.g., the i-th sampling, where i is an integer greater than 1) from M sensors, where M is an integer greater than 1. If each sensor sampling yields one sampled value, then the number of these multiple sampled values ​​is M, and these M sampled values ​​can be represented as {v 1i v 2i ,…,v Mi}, where v 1i v is obtained from the i-th sample of sensor 1. 2i v is obtained from the i-th sample of sensor 2, ..., v Mi This is obtained from the i-th sample of sensor M.

[0183] Regarding scenario 3 above, assume that these multiple sampled values ​​are obtained through two samplings (e.g., the i-th and i+1-th, where i is an integer greater than 1) from M sensors, where M is an integer greater than 1. If each sensor sampling yields one sampled value, then the total number of these multiple sampled values ​​is 2M. These 2M sampled values ​​can be represented as... in, This is obtained from the i-th sample taken by sensor 1. This is obtained from the (i+1)th sample taken by sensor 1. This is obtained from the i-th sample taken by sensor 2. This is obtained from the (i+1)th sample of sensor 2, ... This is obtained from the i-th sample of sensor M. This is obtained from the (i+1)th sample of sensor M. It can be understood that these multiple sample values ​​are obtained through multiple samplings from multiple sensors; "multiple" could mean three, four, or other times.

[0184] S202: The first control device compresses the first data to obtain the second data.

[0185] In this scheme, when the first control device compresses the first data, it can compress some or all of the sampled values ​​in the first data according to different compression methods and conditions, thereby reducing the bandwidth resources consumed for data transmission. It can be understood that when some of the sampled values ​​in the first data are compressed, the resulting second data contains two parts: the first part is the uncompressed sampled values ​​in the first data, and the second part is the data obtained after compression. When all the sampled values ​​in the first data are compressed, the resulting second data includes the compressed data of each sampled value in the first data. It can be understood that the uncompressed sampled values ​​are still represented by the first number of bits, and the data obtained after compression is represented by a number of bits less than the first number of bits.

[0186] In the first data, the number of bits corresponding to each sample value is the first number of bits. For example, in the second data, the number of bits corresponding to the data can have at least the following multiple cases, please refer to the descriptions of the first to third cases:

[0187] The first case: The number of bits corresponding to each data is the second number of bits, and the second number of bits is less than the first number of bits;

[0188] The second scenario: some data corresponds to the second number of bits, and the remaining data corresponds to the first number of bits, with the second number of bits being less than the first number of bits;

[0189] The third scenario: At least some of the data corresponds to multiple bit counts, where each of these multiple bit counts is less than the first bit count.

[0190] For the third case, taking the example of multiple bit numbers including at least the second bit number and the third bit number, the bit number corresponding to the above part of the data includes multiple bit numbers means that the bit number corresponding to one part of the data is the second bit number, and the bit number corresponding to another part of the data is the third bit number, wherein the second bit number is less than the third bit number, and the third bit number is less than the first bit number.

[0191] The compression methods for different scenarios are described below. For the first scenario: the number of bits corresponding to each data item is the second number of bits.

[0192] In one implementation, compressing the first data includes: for each sample value in the first data, compressing the sample value to the amount of change of the sample value relative to a reference value of that sample value, wherein the number of bits corresponding to each amount of change is a second number of bits, and the second number of bits is less than the first number of bits. That is, in the second data, each of the above plurality of sample values ​​is compressed to the amount of change of the sample value relative to a reference value of that sample value, and the number of bits corresponding to each amount of change is a second number of bits.

[0193] Here, the number of bits corresponding to the change is the second number of bits, which includes: one bit indicating the sign of the change, and the remaining bits representing the magnitude of the change. It can be understood that the absolute value of the change falls within the data range indicated by the remaining bits in the second number of bits. The data range indicated by the remaining bits in the second number of bits is similar to the data range indicated by the remaining bits in the first number of bits mentioned above, and will not be repeated here.

[0194] It can be understood that the description of "the change of the sampled value relative to the reference value of the sampled value" is equivalent to the description of "the difference between the sampled value and the reference value of the sampled value".

[0195] Here, the reference value for the sampled value can be a neighboring sampled value or a reference sampled value of the sensor that acquired the sampled value.

[0196] For example, sensor 1 is any one of the at least one sensors mentioned above, and sample value 1 is any one of the plurality of sample values ​​mentioned above. Assuming sample value 1 is obtained by sensor 1 in the i-th sampling, where i is an integer greater than 1, in this case, the adjacent sample value of sample value 1 can be obtained by sensor 1 in the (i-1)-th sampling. In some schemes, the adjacent sample value of a sample value can also be a sample value collected by the same sensor that is separated from that sample value by a certain number of sampling times. For example, when i is greater than 2, the adjacent sample value of sample value 1 can be obtained by sensor 1 in the (i-2)-th sampling.

[0197] Here, the reference sample value is associated with the sensor, and the reference sample value may be different for different sensors.

[0198] For example, the reference sample value of the sensor can be the average noise floor of the sensor under no-excitation conditions. If the sensor is a collision sensor, the average noise floor of the collision sensor can be any sample value of the collision sensor without a collision signal input, or it can be the average of multiple sample values ​​of the collision sensor within a preset time period without a collision signal input. In this case, the applicable sensor can be a collision sensor, vibration sensor, etc.

[0199] For example, the reference sampling value of the sensor can be the initial sampling value of the sensor under normal monitoring conditions, or it can be the average of multiple sampling values ​​of the sensor within a preset time period under normal monitoring conditions. In this case, the applicable sensor can be a temperature sensor, a humidity sensor, etc. For example, when the sensor is a collision sensor, normal monitoring means that no collision occurs; when the sensor is a temperature sensor, normal monitoring means that the monitored space environment is maintained at a constant temperature or within the allowable temperature range; when the sensor is a humidity sensor, normal monitoring means that the monitored space environment is maintained at a constant humidity or within the allowable humidity range.

[0200] Taking the above multiple sample values ​​obtained from a single sampling by multiple sensors as an example, assuming that the multiple sample values ​​are obtained by M sensors in the i-th sampling, and assuming that a single sampling by a sensor yields one sample value, then the number of multiple sample values ​​is also M, that is, M sample values ​​are obtained by M sensors in the i-th sampling, and the j-th sample value is obtained by the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; the above compression of the first data includes: compressing the j-th sample value in the first data into the j-th change, the j-th change being the change of the j-th sample value relative to the reference value of the j-th sample value, and the number of bits corresponding to the j-th change being the second number of bits mentioned above.

[0201] Referring to Figure 4A, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4A, taking the first data as an example, which includes 16 sample values, the number of bits corresponding to each sample value is 12 bits (an example of the first number of bits mentioned above); in the second data, each of the 16 sample values ​​is compressed into the change corresponding to that sample value, and the number of bits corresponding to each change is 6 bits (an example of the second number of bits mentioned above).

[0202] To make the compression effect easier to see more intuitively, the reference value of the sampled value is taken as the adjacent sampled value. The above multiple sampled values ​​are obtained by multiple samplings from a single sensor. Please refer to Figure 3 for the data representation of these multiple sampled values ​​before and after compression.

[0203] Referring to Figure 3, which is a schematic diagram of data compression provided in an embodiment of this application, it can be seen from Figure 3(1) that n samples from a sensor yield n sample values, with each sample corresponding to a sampling time. These n sample values ​​include v1, v2, ..., v n Where v1 is the sensor's sampled value at time t1, v2 is the sensor's sampled value at time t2, ..., v n The first data in Figure 3(1) refers to the sensor's sampled values ​​at time tn. The first data includes v2, v3, ..., v... n These multiple sample values ​​are compressed. Each sample value is compressed to the change relative to its adjacent sample values. Comparing Figure 3(1) and Figure 3(2), it can be seen that sample value v2 is compressed to the change d1, sample value v3 is compressed to the change d2, ..., sample value v n Compressed into a change d n-1 Where d1 = v2 - v1, d2 = v3 - v2, ..., d n-1 =v n -v n-1 That is, the second data includes d1, d2, ..., d n-1 These are multiple variables, and each of the sampled values ​​corresponds one-to-one with one of these variables.

[0204] As shown in Figure 3, after the sampled values ​​are compressed into variations, the length occupied by the variation on the vertical axis is less than the length occupied by the corresponding sampled value on the vertical axis. For example, the absolute value of the variation d1 is less than the absolute value of the sampled value v2. Therefore, the number of bits required to represent the variation d1 in binary form is less than the number of bits required to represent the sampled value v2 in binary form (i.e., the first number of bits mentioned above), thus achieving data compression. Furthermore, it can be seen that the amplitude of the sensor's sampled signal (i.e., the sampled value) does not change abruptly in the time domain. The amplitude variation between adjacent sampling points is often within a certain data range. Therefore, a uniform number of bits (i.e., the second number of bits mentioned above) can be used to achieve the binary representation of the variation, with the second number of bits being less than the first number of bits.

[0205] As an example, when the reference value of the sampled value is the baseline sampled value of the sensor that collects the sampled value, the compression method described above can be used to sequentially obtain the change amount of each sampled value after compression among the above multiple sampled values, and the number of bits corresponding to each change amount is the second number of bits mentioned above.

[0206] As another example, when the reference value of the sampled value is the reference sampled value of the sensor that acquired the sampled value, the above compression of the first data includes: for each sampled value in the first data, when it is determined that the absolute value of the change obtained by compressing each sampled value is less than or equal to the change threshold, compressing each sampled value to obtain the change corresponding to the sampled value, the change corresponding to the sampled value is the difference between the sampled value and the reference value of the sampled value, and the number of bits corresponding to each change is the second number of bits mentioned above, the second number of bits being associated with the change threshold.

[0207] For example, the association of the second bit number with the change threshold means that the maximum value of the data range indicated by the second bit number should be greater than or equal to the change threshold. Here, the data range indicated by the second bit number is described in the preceding relevant content and will not be repeated here.

[0208] Here, the absolute value of the change obtained by compressing each of the above sample values ​​is less than or equal to the change threshold, indicating that the sampling of the first data occurred in a scenario where no anomalies were detected. For a scenario where no anomalies were detected, please refer to the aforementioned description of a scenario where no anomalies were detected; it will not be repeated here.

[0209] In some schemes, if the reference value of the sampled value is the aforementioned benchmark sampled value, and if the absolute value of the change obtained by compressing the sampled value among the multiple sampled values ​​is greater than the change threshold, then only a portion of the sampled values ​​in the first data can be compressed. Please refer to the relevant description in "For the Third Case" below, which will not be repeated here.

[0210] In some possible embodiments, the first control device can periodically acquire sensor sampling values. The aforementioned first data may be the result of a single acquisition by the first control device. If the reference value for the sampling values ​​is the aforementioned benchmark sampling value, and if the absolute value of the change obtained by compressing any of the multiple sampling values ​​is greater than the aforementioned change threshold, the first control device may not compress the first data for that instance and directly send the acquired first data to the second control device. Please refer to the description of the embodiment in Figure 8 below for this implementation. Thus, since most data monitoring scenarios are normal, the acquired first data can be compressed in most cases. From the perspective of the entire sensor monitoring process, compared to the prior art where the first control device directly transmits each acquired first data to the second control device, this method reduces the bandwidth required to transmit the sensor's sampling data to a certain extent, which is beneficial for improving system performance.

[0211] The second scenario: some data corresponds to the second number of bits, while the remaining data corresponds to the first number of bits.

[0212] Here, some data types include the amount of change of a sampled value relative to a reference value of that sampled value (hereinafter referred to as the change corresponding to the sampled value), or the sampled value and the change corresponding to the sampled value, while the remaining data types include the sampled value and / or the change corresponding to the sampled value, wherein the reference value of the sampled value involved is the aforementioned benchmark sampled value.

[0213] For example, the second scenario may be: when the reference value of the sampled value is the above-mentioned benchmark sampled value, it is possible that the absolute value of the change obtained by compressing the first part of the sampled values ​​is less than or equal to the above-mentioned change threshold, but the absolute value of the change obtained by compressing the second part of the sampled values ​​is greater than or equal to the above-mentioned change threshold. In this case, please refer to the following implementation method A1 and implementation method A2.

[0214] Implementation method A1: The first data is compressed, including: compressing each sample value in the first part of the sampled values ​​to obtain the change corresponding to the sample value, and the number of bits corresponding to each change is the second number of bits; each sample value in the second part of the sampled values ​​is not compressed, and each sample value is still represented by the first number of bits. Thus, the second data contains data types including sample values ​​and the changes corresponding to the sample values, wherein the number of bits corresponding to each sample value is the first number of bits, and the number of bits corresponding to each change is the second number of bits.

[0215] Referring to Figure 4B, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4B, taking the first data as an example, which includes 16 sample values, the number of bits corresponding to each sample value is 12 bits (an example of the first number of bits mentioned above); in the second data, some of the 16 sample values ​​are compressed into the change amount corresponding to that sample value, and the number of bits corresponding to each change amount is 6 bits (an example of the second number of bits mentioned above), while the number of bits corresponding to the remaining sample values ​​among the 16 sample values ​​is still 12 bits.

[0216] Implementation method A2: The data type in the second data can be unified as the change amount corresponding to the sampled value. Then, in the second data, for each sampled value in the first part of the sampled values, the number of bits corresponding to its change amount is the second number of bits, and for each sampled value in the second part of the sampled values, the number of bits corresponding to its change amount is the first number of bits.

[0217] Referring to Figure 4C, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4C, taking the first data as an example, which includes 16 sample values, each sample value corresponds to 12 bits (an example of the first bit number mentioned above); the second data includes the change amount corresponding to each of the 16 sample values, wherein some of the change amounts correspond to 6 bits (an example of the second bit number mentioned above), and the other part of the change amounts still corresponds to 12 bits (an example of the first bit number mentioned above).

[0218] For example, the second scenario can also be: when the reference value of the sampled value is the above-mentioned benchmark sampled value, among the above-mentioned multiple sampled values, there may be a first part of the sampled value whose absolute value is less than or equal to the above-mentioned change threshold, a second part of the sampled value whose absolute value of the change obtained after compression is less than or equal to the above-mentioned change threshold, but a third part of the sampled value whose absolute value of the change obtained after compression is greater than or equal to the above-mentioned change threshold. In this case, please refer to the following implementation methods A3 and A4.

[0219] Implementation method A3: The data types in the second data include sampled values ​​and the changes corresponding to the sampled values. In the second data, the number of bits corresponding to each sampled value in the first part of the sampled values ​​is the second number of bits; for each sampled value in the second part of the sampled values, the number of bits corresponding to its change is the second number of bits; and the number of bits corresponding to each sampled value in the third part of the sampled values ​​is the first number of bits.

[0220] Referring to Figure 4D, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4D, taking the first data as an example, which includes 16 sample values, each sample value corresponds to 12 bits (an example of the first bit number mentioned above); the second data includes the change amount corresponding to a portion of the 16 sample values ​​and the remaining sample values ​​among the 16 sample values, wherein the number of bits corresponding to the change amount is 6 bits (an example of the second bit number mentioned above), the number of bits corresponding to a portion of the remaining sample values ​​is 6 bits (an example of the second bit number mentioned above), and the number of bits corresponding to another portion of the remaining sample values ​​is 12 bits (an example of the first bit number mentioned above).

[0221] Implementation method A4: The difference from implementation method A3 is that in the second data, for each sample value in the above third part of the sample values, the number of bits corresponding to its change is the first number of bits.

[0222] Referring to Figure 4E, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4E, taking the first data as an example, which includes 16 sample values, each sample value corresponds to 12 bits (an example of the first bit number mentioned above); the second data includes the changes corresponding to a portion of the 16 sample values ​​and the remaining sample values ​​among the 16 sample values, wherein the remaining sample values ​​correspond to 6 bits (an example of the second bit number mentioned above), a portion of the changes correspond to 6 bits (an example of the second bit number mentioned above), and another portion of the changes correspond to 12 bits (an example of the first bit number mentioned above).

[0223] In some possible embodiments, the data type of the second data may also be only sample values. In this case, the number of bits corresponding to a portion of the sample values ​​is the second number of bits, and the number of bits corresponding to another portion of the sample values ​​is also the second number of bits, which is less than the first number of bits. This implementation scenario is that most of the sample values ​​are small, and they can be represented by fewer bits than the first number of bits, thus achieving data compression. In another approach, the data type of the second data may also be only sample values. In this case, the multiple sample values ​​can be represented hierarchically based on their size, with larger sample values ​​indicating a larger number of bits, and the maximum number of bits corresponding to a sample value being the first number of bits. This also achieves data compression to a certain extent.

[0224] The third scenario: At least some of the data corresponds to multiple bit counts, each of which is less than the first bit count.

[0225] Here, some data types include the amount of change of a sampled value relative to a reference value of that sampled value (hereinafter referred to as the amount of change corresponding to the sampled value), or a sampled value and the amount of change corresponding to the sampled value, wherein the reference value of the sampled value involved is the aforementioned benchmark sampled value.

[0226] For example, the third scenario is applicable when, after obtaining the change corresponding to each of the multiple sample values, the change corresponding to each sample value can be represented in bits according to the magnitude of the change, which is equivalent to performing compression at different degrees. This allows for the use of fewer bits, further improving the data compression. For implementation in this case, please refer to implementation method B1 below.

[0227] Implementation Method B1: The data type in the second data is only the change amount corresponding to the sampled value. Multiple bit counts are included, including second and third bit counts. Taking change amount 1 and change amount 2 in the second data as examples, change amount 1 is obtained by performing the above compression on sample value 1 from the multiple sampled values, and change amount 2 is obtained by performing the above compression on sample value 2 from the multiple sampled values. The absolute value of change amount 1 is less than or equal to the first change threshold, and the absolute value of change amount 2 is greater than the first change threshold but less than or equal to the second change threshold. The second change threshold is greater than the first change threshold. The number of bits corresponding to change amount 1 is the second bit count, and the number of bits corresponding to change amount 2 is the third bit count. The second bit count is less than the third bit count, and the third bit count is less than the first bit count. The second bit count is associated with the first change threshold, and the third bit count is associated with the second change threshold. Here, only two levels of bit count (i.e., second and third bit counts) are used as an example. In practical applications, more levels of bit count representation can also be implemented, such as three-level bit counts, four-level bit counts, etc., which will not be elaborated here.

[0228] Referring to Figure 4F, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4F, taking the first data as an example, which includes 16 sample values, the number of bits corresponding to each sample value is 12 bits (an example of the first number of bits mentioned above); the second data includes the change amount corresponding to each of the 16 sample values, wherein the number of bits corresponding to some of the change amounts is 6 bits (an example of the second number of bits mentioned above), the number of bits corresponding to some of the change amounts is 8 bits (an example of the third number of bits mentioned above), and the number of bits corresponding to the remaining change amounts is 12 bits (an example of the first number of bits mentioned above).

[0229] For example, the third scenario may be applicable when some of the sampled values ​​have small absolute values ​​and some sampled values ​​have small or large changes after compression. In this case, please refer to the implementation methods B2 and B3 below.

[0230] Implementation Method B2: The second data contains data types including sampled values ​​and their corresponding changes. Multiple bit counts are included, including second and fourth bit counts. Taking a second data set including change 1 (for sampled value 1), change 2 (for sampled value 2), and sampled value 3 as an example, the absolute values ​​of change 1 and change 2 are both less than a first change threshold. The bit count corresponding to change 1 and change 2 is the second bit count, which is associated with the first change threshold. Sampled value 3 is less than a third change threshold. The bit count corresponding to sampled value 3 is the fourth bit count, which is less than the first bit count and is associated with the third change threshold. The fourth bit count is different from the second bit count. For example, the fourth bit count may be less than or greater than the second bit count.

[0231] Referring to Figure 4G, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4G, taking the first data as an example, which includes 16 sample values, each sample value corresponds to 12 bits (an example of the first bit number mentioned above); the second data includes the change amount corresponding to a portion of the 16 sample values ​​and the remaining sample values ​​among the 16 sample values, wherein the remaining sample values ​​correspond to 6 bits (an example of the fourth bit number mentioned above), and the change amount corresponds to 8 bits (an example of the second bit number mentioned above).

[0232] Implementation Method B3: The difference from Implementation Method B2 is that the change corresponding to the sampled value can be represented in a hierarchical manner based on the magnitude of the change. For example, multiple bit counts can be used, including second, third, and fourth bit counts. Taking the second data, which includes change 1 corresponding to sampled value 1, change 2 corresponding to sampled value 2, and sampled value 3, as an example, the number of bits corresponding to change 1 is the second bit count, the number of bits corresponding to change 2 is the third bit count, and the number of bits corresponding to sampled value 3 is the fourth bit count. The second bit count is less than the third bit count, the third bit count is less than the first bit count, and the fourth bit count is less than the first bit count. Here, please refer to the description of change 1 and change 2 in Implementation Method B2, which will not be repeated here.

[0233] Referring to Figure 4H, which is a schematic diagram of a first data and a second data provided in an embodiment of this application. In Figure 4H, taking the first data as an example, which includes 16 sample values, each sample value corresponds to 12 bits (an example of the first bit number mentioned above); the second data includes the change amount corresponding to a portion of the 16 sample values ​​and the remaining sample values ​​among the 16 sample values, wherein the remaining sample values ​​correspond to 6 bits (an example of the fourth bit number mentioned above), a portion of the change amount corresponds to 8 bits (an example of the second bit number mentioned above), and another portion of the change amount corresponds to 10 bits (an example of the third bit number mentioned above).

[0234] In the third scenario, in some schemes, if only some data in the second data includes multiple bit counts, then the remaining data is the first bit count, and the types of the remaining data include sampled values ​​and / or the changes corresponding to the sampled values.

[0235] S203: The first control device sends second data to the second control device. Correspondingly, the second control device receives the second data from the first control device.

[0236] For example, the second data is transmitted in the form of a data frame, wherein the data frame carries the second data. Based on the description in S202, the format of the data frame may also be different depending on the compression method selected.

[0237] In one implementation, when the data type in the second data is the change amount corresponding to the sampled value, the data frame used to carry the second data is a compressed data frame, wherein the compressed data frame indicates that the carried data has been compressed.

[0238] Taking the number of sampled values ​​as M as an example, where M is an integer greater than 1, in the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to its reference value. The number of bits corresponding to the j-th change is the second number of bits, where j is an integer less than or equal to M. Here, the reference value of the j-th sampled value is described in the previous section on the reference value of sampled values, and will not be repeated here. In this case, sending the second data includes: sending a first data frame, the first data frame carrying the second data, wherein the first data frame includes the following information:

[0239] The first flag bit is used to indicate that the first data frame belongs to a compressed data frame.

[0240] M second identifier bits, the j-th second identifier bit is used to indicate the sign of the j-th change; and,

[0241] The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

[0242] Optionally, the first data frame may also include frame count information, which indicates the sequence number of the first data frame, facilitating the receiving end to sort the received data frames, detect data loss, etc. The frame count information can be represented by multiple bits.

[0243] Referring to Figure 5A, which is a schematic diagram of the format of a first data frame provided in an embodiment of this application. In Figure 5A, taking M=16 and the second bit number=6 bits as an example, where j is a positive integer less than or equal to 16, the second data carried by the first data frame shown in Figure 5A is the second data in Figure 4A. In Figure 5A, for example, the first flag bit is set to "0", indicating that the first data frame is a compressed data frame; the j-th second flag bit is used to indicate the sign of the j-th change as "positive (+)" or "negative (-)", and one second flag bit is 1 bit; the j-th group of third flag bits is used to indicate the magnitude of the j-th change, and one group of third flag bits is 5 bits, so that the number of bits corresponding to each change is 6 bits. Optionally, the first data frame may also include frame count information, which can be represented by multiple bits. It is understood that Figure 5A is only an example of a frame format when the first data frame carries the second data shown in Figure 4A. In some schemes, the placement of each flag bit in the data frame can also be seen as shown in Figure 5B. Comparing with Figure 5A, it can be seen that the 16 second flag bits and 16 groups of third flag bits in Figure 5A are combined into 16 groups of flag bits in Figure 5B. Each group of flag bits is 6 bits. The j-th group of flag bits is used to represent the j-th change. The highest bit in the j-th group of flag bits is used to indicate the sign of the j-th change, and the remaining bits in the j-th group of flag bits are used to indicate the magnitude of the j-th change.

[0244] Furthermore, when each data point in the second data is of the type of a variable, in order to facilitate the receiving end to reconstruct the first data from the second data, the first control device also sends third data to the second control device before sending the second data. The third data includes the initial sampling value corresponding to at least one of the above-mentioned sensors, and the number of bits corresponding to each initial sampling value is the first number of bits. The initial sampling value is used to decompress the second data into the first data.

[0245] For example, the third data includes the initial sampled value corresponding to at least one of the sensors, including: if the multiple sampled values ​​come from one sensor (e.g., the first sensor), then the third data includes the initial sampled value corresponding to the first sensor; if the multiple sampled values ​​come from multiple sensors, then the third data includes the initial sampled value corresponding to each of the multiple sensors.

[0246] For example, when the change is obtained based on adjacent sample values, the initial sample value corresponding to the sensor is the first sample value of the sensor during data transmission; when the change is obtained based on a reference sample value, the initial sample value corresponding to the sensor is the reference sample value of the sensor.

[0247] Referring to Figure 3, if the change is obtained based on adjacent sampled values, the aforementioned sampled values ​​include v2, v3, ..., v in (1) of Figure 3. n Therefore, the first sample value of the sensor during the data transmission process is the sample value v1 in Figure 3(1), so the third data is the sample value v1, and the second data includes d1, d2, ..., d n-1 .

[0248] In one implementation, the third data is transmitted in the form of data frames. These data frames are absolute data frames, indicating that the data is uncompressed. In this case, during data transmission, the first data frame transmitted by the first control device is an absolute data frame, and subsequent data frames may, for example, be compressed data frames.

[0249] For example, sending the third data includes: sending a second data frame, the second data frame carrying the third data, the second data frame including the following information:

[0250] The fourth flag bit, used to indicate that the second data frame belongs to an absolute data frame; and,

[0251] The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampled value corresponding to the j-th sensor.

[0252] Optionally, the second data frame may also include frame count information, which indicates the sequence number of the second data frame, facilitating the receiving end to sort the received data frames, detect data loss, etc. The frame count information can be represented by multiple bits.

[0253] Referring to Figure 6, which is a schematic diagram of the format of a second data frame provided in an embodiment of this application. Taking the number of sensors M=16 as an example, the first data comes from 16 sensors. In Figure 6, for example, the fourth identifier bit is set to "1", which indicates that the second data frame is an absolute data frame; the fifth identifier bit of the j-th group is used to indicate the initial sampling value corresponding to the j-th sensor, and each group of fifth identifier bits is 12 bits (i.e., an example of the first bit number). Optionally, the second data frame may also include frame count information, which is used to indicate the sequence number of the second data frame, and the frame count information can be represented by multiple bits.

[0254] In some schemes, when any of the following conditions are met, the first control device also sends a third data frame to the second control device. The third data frame is an absolute data frame. The third data frame carries fourth data. The sampled values ​​in the fourth data are obtained by the at least one sensor after the first data. The number of bits corresponding to each sampled value in the fourth data is the number of bits in the first data.

[0255] The time interval since the last transmission of an absolute data frame has reached the preset duration;

[0256] The number of compressed data frames sent since the last transmission of an absolute data frame has reached a preset value; or,

[0257] Receive frame loss indication information from the receiving end.

[0258] It is understandable that when the first data frame is sent as an absolute data frame and subsequent data frames are sent as compressed data frames, if the data types in the second data frame are all variable quantities and these variable quantities are obtained based on adjacent sample values, frame loss may occur during data transmission. For example, if a compressed data frame in the middle is lost, it will cause a deviation when subsequent compressed data frames are restored. By implementing the above method, the first control device promptly sends a new absolute data frame to the second control device to correct this deviation. The new absolute data frame can be actively sent by the first control device through timing or by quantitative compression of data frames, or it can be sent by the first control device in response to the frame loss indication information from the second control device. The second control device can determine whether frame loss has occurred by using the frame count information in the received data frames.

[0259] Referring to Figure 7, which is a schematic diagram of a first control device periodically transmitting absolute data frames according to an embodiment of this application, the first control device transmits an absolute data frame every preset time interval T, so that the receiving end can accurately reconstruct the corresponding data from the compressed data frame in a timely manner when frame loss occurs. For example, the first control device sequentially transmits absolute data frame 1, compressed data frame 2, compressed data frame 3, ..., compressed data frame a, where a is an integer greater than 2, and a represents the sequence number of the data frame. Absolute data frame 1 is the first data frame. Assuming the time interval between the transmission time of absolute data frame 1 and the transmission time of compressed data frame a is a preset time interval T, the next data frame after compressed data frame a should be absolute data frame a+1. After absolute data frame a+1, the first control device then sequentially transmits compressed data frame a+2, compressed data frame a+3, ..., and so on. Here, Figure 7 is only an example of the first control device periodically transmitting absolute data frames and does not limit the transmission method of absolute data frames.

[0260] In some possible embodiments, where the data types involved in the second data are all variables, and the number of bits corresponding to the variables can be multiple, such as the second data shown in Figures 4C and 4F above, the first data frame carrying the second data also includes multiple identification information, with each identification information corresponding to a variable in the second data. For example, the j-th identification information is used to indicate the number of bits corresponding to the j-th variable. As an example, if the number of bits corresponding to the variable includes a second number of bits and a third number of bits, then each identification information can also be 1 bit. When the j-th identification information is "1", it indicates that the number of bits corresponding to the j-th variable is the second number of bits; when the j-th identification information is "0", it indicates that the number of bits corresponding to the j-th variable is the third number of bits.

[0261] In some possible embodiments, the data types involved in the second data include sampled values ​​and changes. For example, the second data shown in Figures 4B, 4D, 4E, 4G, and 4H may have multiple numbers of bits corresponding to sampled values ​​and / or multiple numbers of bits corresponding to changes, and the number of bits corresponding to sampled values ​​and changes may be different. In this case, the first data frame carrying the second data also includes multiple first identification information and multiple second identification information. The first identification information is used to indicate that the data type is a sampled value or a change, and the second identification information is used to indicate the number of bits corresponding to the data. For example, the j-th first identification information is used to indicate the type of the j-th data in the second data, and the j-th first identification information is used to indicate the number of bits corresponding to the j-th data. In this case, since the data types involved in the second data include sampled values ​​and changes, although the first data frame belongs to the above-mentioned compressed data frame, if each sampled value in the first data can be restored from the second data carried by the first data frame, the first control device does not need to send the above-mentioned second data frame; if each sampled value in the first data cannot be restored from the second data carried by the first data frame, the first control device still needs to send the above-mentioned second data frame.

[0262] In some schemes, when the data types involved in the second data are all sample values, the first data frame carrying the second data also includes multiple identification information, with each identification information corresponding to a sample value in the second data. For example, the j-th identification information is used to indicate the number of bits corresponding to the j-th sample value. In this case, although the first data frame belongs to the aforementioned compressed data frame, since the type of each data in the second data is a sample value, the first control device does not need to send the aforementioned second data frame (i.e., absolute data frame).

[0263] In some possible embodiments, multiple different data frame formats may be provided for the second data based on the above situation. An additional identification information can be added to indicate the format type of the data frame. Each time the first control device acquires the second data, it can determine which data frame format to use based on the second data. The data frame format selected for different acquisitions of the second data can be the same or different.

[0264] S204: The second control device decompresses the second data to obtain the first data.

[0265] In one implementation, when the second control device receives third data from the first control device, the second control device decompresses the second data to obtain first data, including: the second control device decompresses the second data based on the third data to obtain the first data. This implementation is applicable to scenarios where the data types involved in the second data are all quantities of change, and where the data types present in the second data include quantities of change.

[0266] The process of decompressing the second data to obtain the first data based on the third data is illustrated in Figure 3 above. As can be seen from the above, the third data is the sampled value v1, and the second data includes d1, d2, ..., d... n-1 These multiple changes, specifically, are decompressed from sampled value v1 and change d1 to obtain sampled value v2, from sampled value v2 and change d2 to obtain sampled value v3, ..., from sampled value v n-1 and change d n-1 Decompress the sampled value v n Thus, the first set of data obtained includes v2, v3, ..., v n .

[0267] It is understandable that the premise for the second control device to successfully restore the data from the compressed data frame is that the data frame previously received by the second control device is an absolute data frame, or that the second control device has already restored the previously received compressed data frame.

[0268] In one implementation, since the second data is carried in the first data frame, the second control device first parses the first data frame to obtain the second data before decompressing the second data.

[0269] In some schemes, the second control device can also directly decompress the second data to obtain the first data. For example, for the second data shown in Figures 4G and 4H above, assuming that the 16 sampled values ​​included in the first data are obtained through multiple acquisitions by the same sensor, and that these 16 sampled values ​​are adjacent to each other in terms of sampling time, the second control device can restore the first data based solely on the second data.

[0270] In one implementation, before decompressing the second data, the second control device may first execute the following S205 to obtain the data collected by the target sensor. The second control device determines whether to restore the first data based on the data collected by the target sensor. The second control device decompresses the second data to obtain the first data, including: if the second control device determines that the first data can be restored, it decompresses the second data to obtain the first data.

[0271] Here, the target sensor is a sensor other than at least one of the aforementioned sensors. For example, the target sensor includes at least one of vehicle-mounted sensors such as a camera, LiDAR, millimeter-wave radar, ultrasonic sensor, wheel speed sensor, and pressure sensor.

[0272] For example, the first data and the data collected by the target sensor can be collected within the same time range (e.g., the first time range). Taking at least one of the above-mentioned sensors as a collision sensor as an example, the target sensor can monitor the surrounding environment of the vehicle. The data collected by the target sensor includes at least one of the following: image / video data containing surrounding environment information collected by a camera, point cloud data containing surrounding environment information collected by a lidar, distance data collected by an ultrasonic sensor, distance to the target object collected by a millimeter-wave radar, and speed data of the target object. It can be understood that the sampling value of the collision sensor is mainly used for collision detection. The second control device can first detect whether there are people or vehicles approaching the vehicle within the first time range based on the data collected by the target sensor. When it is determined that there are no people or vehicles approaching the vehicle within the first time range, it means that it can be determined with a high probability or complete certainty that the vehicle has not collided. In this case, the second control device does not need to decompress the second data to obtain the first data, thus avoiding the consumption of computing resources required to decompress the second data.

[0273] Optionally, in some possible embodiments, steps S205-S206 may also be performed.

[0274] S205: The second control device acquires the data collected by the target sensor.

[0275] Here, the execution order of S205 and S204 is not limited. S205 can be executed before S204, after S204, or simultaneously. When S205 is executed before S204, the second control device can determine whether to execute S204 based on the data collected by the target sensor. Please refer to the description of the corresponding content in S204; it will not be repeated here.

[0276] S206: The second control device performs scene detection based on the first data and the data collected by the target sensor.

[0277] For example, when applied to vehicles, scene detection includes at least one of the following:

[0278] Did a collision occur?

[0279] Are there any people near the vehicle?

[0280] Has anyone touched the vehicle body?

[0281] Taking collision detection as an example, the second control device obtains physical quantities such as acceleration and impact force based on the first data. For instance, the acceleration sensor will detect a peak acceleration far exceeding that during normal driving at the moment of collision. When the sensor's measurement exceeds the acceleration threshold, it is preliminarily determined that a collision may have occurred. The second control device combines the data collected by the target sensors for comprehensive analysis. For example, it may obtain analysis results such as the airbag sensors being triggered at the same time, abnormal data display from the tire pressure sensor, data collected by the ultrasonic sensor indicating a nearby object, and video stream data collected by the camera detecting a target object contacting the vehicle, further confirming that a collision has occurred. Furthermore, when there are multiple collision sensors, it can further detect the collision type, collision intensity, and collision location.

[0282] Based on the description of the entire embodiment in Figure 2, it can be seen that in the second data, the first sample value among the plurality of sample values ​​is compressed into a first change, and the number of bits corresponding to the first change is the second number of bits, wherein the first number of bits is greater than the second number of bits. For example, the first sample value is at least a portion of these plurality of sample values. The first change is the change of the first sample value relative to a reference value of the first sample value, where the reference value is an adjacent sample value of the first sample value or a reference sample value of the sensor that acquired the first sample value.

[0283] In the embodiment shown in Figure 2, at least a portion of the sampled values ​​in the first data are compressed into the amount of change of the sampled value relative to a reference value. The number of bits corresponding to the amount of change is less than the number of bits corresponding to the sampled value. Thus, fewer bits are required to represent the compressed sampled value in binary form, thereby reducing the number of bits required to transmit a single sampled value and also reducing the bandwidth consumed in transmitting the sensor's sampled data. Especially when transmitting sampled data from multiple sensors, the amount of data transmitted using this method is significantly reduced, and the hardware cost is also low.

[0284] The embodiment shown in Figure 2 above compresses the first data once to obtain the second data. In some possible embodiments, the first data can also be compressed multiple times to obtain the second data. Taking the second compression in multiple compression as an example, the specific process of the second compression is explained with reference to Figure 3. Please refer to steps 1-3 below.

[0285] Step 1: In Figure 3, the first data includes v2, v3, ..., v n These multiple sampled values, the number of bits corresponding to the sampled values ​​in the first data is the first number of bits. Here, the sampled value v1 in (1) of Figure 3 is the initial sampled value.

[0286] Step 2: Compress these multiple sample values ​​once to obtain the first compression result.

[0287] The first compression result includes d1, d2, ..., d n-1 These n-1 variables, where variable d1 corresponds to sampled value v2, variable d2 corresponds to sampled value v3, ..., variable d... n-1 With sampled value v n Correspondingly, the number of bits corresponding to each change in the first compression result is the second number of bits, where the second number of bits is less than the first number of bits.

[0288] As can be seen, in the first compression result, each of these multiple sample values ​​is compressed to the amount of change of that sample value relative to the reference value of the sample value, where the reference value of the sample value is the adjacent sample value of that sample value.

[0289] Step 3: Further compress the first compression result to obtain the second data.

[0290] In the first compression result, the change d2 is compressed to d 21 =d2-d1, the change d3 in the first compression result is compressed to d 32 =d3-d2, ..., the change d in the first compression result n-1 It is compressed into d(n-1)(n-2)=d n-1 -d n-2 That is, the second data includes d 21 d 32 There are n-2 variables, d(n-1)(n-2), where the variable d... 21 Corresponding to the change d2, the change d 32 Corresponding to the change d3, ..., the changes d(n-1)(n-2) and the changes d n-1 Correspondingly, the number of bits corresponding to each change in the second data is the number of the third bits, where the number of the third bits is less than the number of the second bits.

[0291] In this case, the third data sent by the first control device includes the change d1 and the sampled value v1. Thus, after receiving the second and third data, the second control device first decompresses the second data based on the change d1 to obtain the other changes in the first compression result besides d1, namely d2, ..., d... n-1 The first compression result was obtained; then the first compression result was decompressed according to the sampled value v1 to obtain the first data.

[0292] By implementing the above method, the first data is compressed multiple times, and each compression reduces the amount of data, which is equivalent to improving the data compression effect. This greatly reduces the bandwidth required to transmit the sensor's sampling data, and the hardware cost is also low.

[0293] Referring to Figure 8, which is a flowchart of another data compression method provided in an embodiment of this application, the method shown in Figure 8 is applied to the first control device described above. The method shown in Figure 8 includes, but is not limited to, the following steps S801-S805.

[0294] S801: Obtain first data, which includes multiple sampled values. Please refer to the description of S201 in the aforementioned embodiment of Figure 2 for this step, which will not be repeated here.

[0295] S802: Determine whether the absolute value of each sampled value is less than or equal to the change threshold.

[0296] Here, the change threshold is either preset by the developers or set by the factory default.

[0297] For example, if it is determined that the absolute value of each sample value is less than or equal to the change threshold, the following S803 and S804 are executed; if it is determined that the absolute value of one of the multiple sample values ​​is greater than the change threshold, the following S805 is executed.

[0298] S803: Compress the first data to obtain the second data. Please refer to the description of S202 in the embodiment shown in Figure 2 above for this step, which will not be repeated here.

[0299] S804: Send the second data to the second control device. Please refer to the description of S203 in the embodiment shown in Figure 2 above for this step, and it will not be repeated here.

[0300] S805: Send the first data to the second control device. The first data frame is sent in the form of an absolute data frame.

[0301] The embodiment shown in Figure 8 uses a changing threshold to classify and encode the sampled values. Smaller sampled values ​​are encoded with a smaller number of bits, thus compressing the data volume. For vibration sensors or collision sensors, the amplitude of the sampled data is relatively small (i.e., less than the changing threshold) in most vehicle situations. Only when a collision occurs will the amplitude of the sampled data exceed the changing threshold. Therefore, classifying and encoding the sampled values ​​based on their amplitude can reduce the amount of data transmitted in most time periods.

[0302] Referring to Figure 9, which is a schematic diagram of a data processing device according to an embodiment of this application, the data processing device 30 includes an acquisition unit 310 and a processing unit 312. In some embodiments, the data processing device 30 further includes a sending unit 314. Here, the acquisition unit 310 and the sending unit 314 can also be collectively referred to as a communication unit. The data processing device 30 can be implemented by hardware, software, or a combination of hardware and software. Exemplarily, the data processing device 30 can be the aforementioned first control device or second control device.

[0303] In one implementation, when the data processing device 30 is the aforementioned first control device, the acquisition unit 310 is used to acquire first data, which includes multiple sampled values ​​from at least one sensor, and the number of bits corresponding to each sampled value is a first number of bits; the processing unit 312 is used to compress the first data to obtain second data, in which the first sampled value among the multiple sampled values ​​is compressed into a first change, the first change being the change of the first sampled value relative to a reference value of the first sampled value, the reference value of the first sampled value being an adjacent sampled value of the first sampled value or a reference sampled value of the sensor that acquired the first sampled value; the number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits; the sending unit 314 is used to send the second data.

[0304] In this case, the data processing device 30 can be used to implement the method on the first control device side described in the embodiment of FIG2. In the embodiment of FIG2, the acquisition unit 310 is used to execute S201, the processing unit 312 is used to execute S203, and the sending unit 314 is used to execute S203. In some embodiments, the data processing device 30 can be used to implement the method described in the embodiment of FIG8, which will not be repeated here.

[0305] In another implementation, when the data processing device 30 is the aforementioned second control device, the acquisition unit 310 is used to acquire second data, which is obtained by compressing the first data; the processing unit 312 is used to decompress the second data to obtain the first data. For explanations of the first and second data, please refer to the preceding descriptions; they will not be repeated here.

[0306] In this case, the data processing device 30 can be used to implement the method on the second control device side described in the embodiment of FIG2. In the embodiment of FIG2, the acquisition unit 310 is used to execute S203 and S205, and the processing unit 312 is used to execute S204 and S206.

[0307] It should be understood that the division of the units in the data processing device 30 described above is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units in the device can be implemented by a processor calling software; for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each unit in the device. The processor can be, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units in the device can be implemented as hardware circuits. The functionality of some or all units can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the above units is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through a configuration file, thereby achieving the functionality of some or all of the above units. All units of the above device can be implemented entirely through processor-invoked software, entirely through hardware circuits, or partially through processor-invoked software with the remaining parts implemented through hardware circuits.

[0308] In this application embodiment, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a type of microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. These logical relationships of hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as a type of ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0309] As can be seen, each unit in the above device can be one or more processors (or processing circuits) configured to implement the above methods, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0310] Furthermore, the units in the above devices can be integrated in whole or in part, or they can be implemented independently. In one implementation, these units are integrated together as a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of the units in the device. The at least one processor may be of different types, such as CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0311] Referring to Figure 10, which is a schematic diagram of the structure of a computing device according to an embodiment of this application, the computing device 40 includes a processor 401, a communication interface 402, a memory 403, and a bus 404. The processor 401, the memory 403, and the communication interface 402 communicate with each other via the bus 404. It should be understood that this application does not limit the number of processors and memories in the computing device 40.

[0312] In one implementation, the computing device 40 can be the first control device or a component within the first control device, or the second control device or a component within the second control device. Components may include, for example, chips or control modules. For a description of the first and second control devices, please refer to the foregoing descriptions; further details will not be repeated here.

[0313] Bus 404 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one line is used in Figure 10, but this does not imply that there is only one bus or one type of bus. Bus 404 can include pathways for transmitting information between various components of computing device 40 (e.g., memory 403, processor 401, communication interface 402).

[0314] The processor 401 can be referred to the relevant description of the processor in the above embodiments, and will not be repeated here.

[0315] Memory 403 provides storage space, which can store data such as the operating system and computer programs. Memory 403 can be one or a combination of several of the following: random access memory (RAM), erasable programmable read-only memory (EPROM), read-only memory (ROM), or compact disc read memory (CD-ROM). Memory 403 can exist alone or be integrated into processor 401.

[0316] The communication interface 402 can be used to provide information input or output to the processor 401. Alternatively, the communication interface 402 can be used to receive and / or send data to externally transmitted data, and can be a wired link interface including an Ethernet cable, or a wireless link interface (such as Wi-Fi, Bluetooth, general wireless transmission, etc.). Alternatively, the communication interface 402 may also include a transmitter (such as an RF transmitter, antenna, etc.) or a receiver coupled to the interface.

[0317] The processor 401 in the computing device 40 is used to read the computer program stored in the memory 403 to execute the aforementioned method, such as the method described in FIG2 or FIG8.

[0318] In one possible design, computing device 40 may be one or more modules in an execution entity (e.g., a first control device) that performs the method shown in FIG2, and processor 401 may be used to read one or more computer programs stored in memory for performing the following operations:

[0319] First data is acquired by acquisition unit 310. The first data includes multiple sampled values, which come from at least one sensor. The number of bits corresponding to each sampled value is the first number of bits.

[0320] The first data is compressed to obtain the second data; in the second data, the first sample value among the multiple sample values ​​is compressed into a first change, which is the change of the first sample value relative to the reference value of the first sample value. The reference value of the first sample value is the adjacent sample value of the first sample value or the reference sample value of the sensor that acquires the first sample value.

[0321] The second data is transmitted via the transmitting unit 314.

[0322] In another possible design, computing device 40 may be one or more modules in an execution entity (e.g., a second control device) that performs the method shown in FIG2, wherein processor 401 may be used to read one or more computer programs stored in memory for performing the following operations:

[0323] The second data is obtained by the acquisition unit 310, wherein the second data is obtained by compressing the first data. The first data includes multiple sample values, which come from at least one sensor, and the number of bits corresponding to each sample value is the first number of bits. In the second data, the first sample value among the multiple sample values ​​is compressed into a first change amount, which is the change amount of the first sample value relative to the reference value of the first sample value. The reference value of the first sample value is the adjacent sample value of the first sample value or the reference sample value of the sensor that acquires the first sample value.

[0324] The second data is decompressed to obtain the first data.

[0325] In the embodiments described above, each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant descriptions in other embodiments. Furthermore, in the embodiments of this application, unless otherwise specified or logically conflicting, the terminology and / or descriptions between the embodiments are consistent and can be mutually referenced. Technical features from different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0326] It should be noted that those skilled in the art will recognize that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0327] The technical solution of this application, in essence, or the part that makes the contribution, or all or part of the technical solution, can be embodied in the form of a software product. The computer program product is stored in a storage medium and includes several instructions to cause a device (which may be a personal computer, server, network device, robot, microcontroller, chip, robot, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

Claims

1. A data processing method, characterized in that, The method includes: Acquire first data, which includes multiple sampled values, the multiple sampled values ​​being from at least one sensor, and the number of bits corresponding to each sampled value being the first number of bits; Send the second data, which is obtained by compressing the first data; In the second data, the first sample value among the plurality of sample values ​​is compressed into a first change amount, which is the change amount of the first sample value relative to a reference value of the first sample value. The reference value of the first sample value is an adjacent sample value of the first sample value or a reference sample value of the sensor that collects the first sample value. The number of bits corresponding to the first change amount is a second number of bits, and the first number of bits is greater than the second number of bits.

2. The method according to claim 1, characterized in that, The plurality of sampled values ​​come from at least one sensor, including: The multiple sampled values ​​are obtained through multiple samplings by a single sensor; The multiple sampled values ​​are obtained through a single sampling by multiple sensors; or, The multiple sample values ​​are obtained through multiple samplings from multiple sensors.

3. The method according to claim 1 or 2, characterized in that, The first sample value is at least a portion of the plurality of sample values.

4. The method according to any one of claims 1-3, characterized in that, The number of bits corresponding to the first change is the second number of bits, including: The sign of the first change is indicated by one bit in the second bit set, and the magnitude of the first change is indicated by the remaining bits in the second bit set.

5. The method according to any one of claims 1-4, characterized in that, The number of the plurality of sampled values ​​is M, where the M sampled values ​​are obtained by the M sensors in the i-th sampling, and the j-th sampled value is obtained by the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; the M sampled values ​​include the first sampled value; In the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

6. The method according to claim 5, characterized in that, The sending of the second data includes: A first data frame is sent, the first data frame carrying the second data, and the first data frame includes the following information: The first identifier bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained through compression. M second identifier bits, the j-th second identifier bit being used to indicate the sign of the j-th change; and, The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

7. The method according to claim 5 or 6, characterized in that, Before sending the second data, the method further includes: Send third data, which includes initial sampling values ​​corresponding to the M sensors, wherein the number of bits corresponding to the initial sampling values ​​is the first number of bits, and the initial sampling values ​​are used to decompress the second data into the first data.

8. The method according to claim 7, characterized in that, The transmission of the third data includes: A second data frame is sent, the second data frame carrying the third data, the second data frame including the following information: The fourth identifier bit indicates that the second data frame is an absolute data frame, and the data carried in the absolute data frame is uncompressed; and, The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampling value corresponding to the j-th sensor.

9. The method according to claim 8, characterized in that, The method further includes: A third data frame is sent when any of the following conditions are met: the third data frame belongs to the absolute data frame; the third data frame carries fourth data; the sampled values ​​in the fourth data are obtained by the M sensors after the first data; and the number of bits corresponding to each sampled value in the fourth data is the same as the number of bits in the first data. The time interval since the last transmission of an absolute data frame has reached the preset duration; The number of compressed data frames sent since the last transmission of an absolute data frame has reached a preset value; or, Receive frame loss indication information from the receiving end.

10. The method according to any one of claims 1-4, characterized in that, In the second data, the second sample value among the plurality of sample values ​​is compressed into a second change amount, which is the change amount of the second sample value relative to a reference value of the second sample value. The reference value of the second sample value is an adjacent sample value of the second sample value or a reference sample value of the sensor that acquires the second sample value. Wherein, the absolute value of the first change is less than or equal to the change threshold, the absolute value of the second change is greater than the change threshold, the number of bits corresponding to the second change is the third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

11. The method according to any one of claims 1-4, characterized in that, When the reference value of each of the plurality of sampled values ​​is represented in the form of a baseline sampled value, the absolute value of the change obtained by the compression of each of the plurality of sampled values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

12. The method according to any one of claims 1-4, 10 and 11, characterized in that, The plurality of sampled values ​​also includes a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information, the identification information being used to indicate that the third sampled value is represented by the fourth number of bits.

13. The method according to any one of claims 1-12, characterized in that, The sensor is a collision sensor, vibration sensor, temperature sensor, or humidity sensor.

14. A data processing method, characterized in that, Obtain the second data, which is obtained by compressing the first data; The second data is decompressed to obtain the first data; The first data includes multiple sampled values, which are obtained from at least one sensor, and the number of bits corresponding to each sampled value is a first number of bits. In the second data, the first sampled value among the multiple sampled values ​​is compressed into a first change, which is the change of the first sampled value relative to a reference value of the first sampled value. The reference value of the first sampled value is an adjacent sampled value of the first sampled value or a reference sampled value of the sensor that acquired the first sampled value. The number of bits corresponding to the first change is a second number of bits, and the first number of bits is greater than the second number of bits.

15. The method according to claim 14, characterized in that, The plurality of sampled values ​​come from at least one sensor, including: The multiple sampled values ​​are obtained through multiple samplings by a single sensor; The multiple sampled values ​​are obtained through a single sampling by multiple sensors; or, The multiple sample values ​​are obtained through multiple samplings from multiple sensors.

16. The method according to claim 14 or 15, characterized in that, The first sample value is at least a portion of the plurality of sample values.

17. The method according to any one of claims 14-16, characterized in that, The number of the plurality of sampled values ​​is M, where the M sampled values ​​are obtained by the M sensors in the i-th sampling, and the j-th sampled value is obtained by the j-th sensor in the i-th sampling, where i is an integer greater than 1, M is an integer greater than 1, and j is an integer less than or equal to M; the M sampled values ​​include the first sampled value; In the second data, the j-th sampled value is compressed into the j-th change, which is the change of the j-th sampled value relative to the reference value of the j-th sampled value, and the number of bits corresponding to the j-th change is the second number of bits.

18. The method according to claim 17, characterized in that, The acquisition of the second data includes: Receive a first data frame, the first data frame carrying the second data; The second data is obtained from the first data frame; wherein the first data frame includes the following information: The first identifier bit is used to indicate that the first data frame belongs to a compressed data frame, and the data carried by the compressed data frame is obtained through compression. M second identifier bits, the j-th second identifier bit being used to indicate the sign of the j-th change; and, The third identifier bit of group M, the third identifier bit of group j is used to indicate the magnitude of the j-th change.

19. The method according to claim 17 or 18, characterized in that, The method further includes: Receive third data, the third data including the initial sampled values ​​corresponding to the M sensors, the number of bits corresponding to the initial sampled values ​​being the first number of bits; The step of decompressing the second data to obtain the first data includes: The second data is decompressed based on the third data to obtain the first data.

20. The method according to claim 19, characterized in that, The receiving of third data includes: Receive a second data frame, the second data frame carrying the third data, the second data frame including the following information: The fourth identifier bit indicates that the second data frame is an absolute data frame, and the data carried in the absolute data frame is uncompressed; and, The fifth identifier bit of group M, the fifth identifier bit of group j is used to indicate the initial sampling value corresponding to the j-th sensor.

21. The method according to claim 20, characterized in that, The method further includes: A third data frame is received when any of the following conditions are met: the third data frame belongs to the absolute data frame; the third data frame carries fourth data; the sampled values ​​in the fourth data are obtained by the M sensors after the first data; and the number of bits corresponding to each sampled value in the fourth data is the same as the number of bits in the first data. The time interval since the last received absolute data frame has reached the preset duration; The number of compressed data frames received since the last reception of an absolute data frame has reached a preset value; or, Send frame loss indication information to the sending end.

22. The method according to any one of claims 14-16, characterized in that, In the second data, the second sample value among the plurality of sample values ​​is compressed into a second change amount, which is the change amount of the second sample value relative to a reference value of the second sample value. The reference value of the second sample value is an adjacent sample value of the second sample value or a reference sample value of the sensor that acquires the second sample value. Wherein, the absolute value of the first change is less than or equal to the change threshold, the absolute value of the second change is greater than the change threshold, the number of bits corresponding to the second change is the third number of bits, the third number of bits is greater than the second number of bits and less than or equal to the first number of bits, and the second number of bits is associated with the change threshold.

23. The method according to any one of claims 14-16, characterized in that, When the reference value of each of the plurality of sampled values ​​is represented in the form of a baseline sampled value, the absolute value of the change obtained by the compression of each of the plurality of sampled values ​​is less than or equal to the change threshold, and the second number of bits is associated with the change threshold.

24. The method according to any one of claims 14-16, 22 and 23, characterized in that, The plurality of sampled values ​​also includes a third sampled value, wherein the number of bits corresponding to the third sampled value in the second data is a fourth number of bits, the fourth number of bits being less than the first number of bits, and the second data also includes identification information, the identification information being used to indicate that the third sampled value is represented by the fourth number of bits.

25. The method according to any one of claims 14-24, characterized in that, The method further includes: Receive data collected by the target sensor; Based on the first data and the data collected by the target sensor, scene detection is performed, wherein the target sensor is a sensor other than the at least one sensor, and the scene detection includes at least one of the following: Did a collision occur? Are there any people near the vehicle? Has anyone touched the vehicle body? 26. The method according to any one of claims 14-25, characterized in that, The method further includes: Receive data collected by a target sensor, wherein the target sensor is a sensor other than the at least one sensor; Determine whether to reconstruct the first data based on the data collected by the target sensor; The step of decompressing the second data to obtain the first data includes: If the first data is determined to be restored, the second data is decompressed to obtain the first data.

27. The method according to any one of claims 14-26, characterized in that, The sensor is a collision sensor, vibration sensor, temperature sensor, or humidity sensor.

28. An apparatus for data processing, characterized in that, The device includes a communication unit and a processing unit, and is configured to perform the method as described in any one of claims 1-13, or the method as described in any one of claims 14-27.

29. An apparatus for data processing, characterized in that, The device includes a memory and a processor, the memory storing computer program instructions, and the processor executing the computer program instructions to cause the device to perform the method as claimed in any one of claims 1-13, or to perform the method as claimed in any one of claims 14-27.

30. A data processing system, characterized in that, The data processing system includes a first device and a second device, wherein the first device is used to implement the method as described in any one of claims 1-13, and the second device is used to implement the method as described in any one of claims 14-27.

31. A vehicle, characterized in that, The vehicle includes the apparatus as described in claim 28 or 29, or the data processing system as described in claim 30.

32. A computer-readable storage medium containing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the method as described in any one of claims 1-13, or the method as described in any one of claims 14-27.

33. A computer program product containing instructions, characterized in that, When the instructions are executed by the computing device, the computing device performs the method as described in any one of claims 1-13, or performs the method as described in any one of claims 14-27.

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