Peripheral management device of ministry label host and data processing method

Abstract

The invention discloses a ministry label host peripheral management device and a data processing method, the ministry label host peripheral management device comprises a host and a slave, the host is used for receiving peripheral data from the slave, carrying out data processing and analysis, and sending a corresponding control instruction according to a processing result; the slave computer is used for collecting data of the peripheral equipment, performing data preprocessing and packaging, and transmitting the packaged data to the host computer in a wired mode; the slave is also used for executing corresponding actions according to the control instruction of the host; the host and the slave are connected in a wired mode and perform data transmission through a set communication protocol; wherein the communication protocol adopts a layered structure and comprises a physical layer, a data link layer and an application layer. According to the invention, a master-slave architecture is adopted, and efficient and stable peripheral management and data processing are realized by optimizing a communication protocol and a data transmission mode between the master and the slave.

Description

Technical Field

[0001] The present invention relates to the field of vehicle networking and automotive electronic technology, and in particular to a departmental standard host peripheral management device and a data processing method. Background Art

[0002] As the trend of intelligence and automation in the automotive industry becomes increasingly obvious, the functional requirements of the department-standard host (i.e., vehicle-mounted terminal equipment) are also constantly expanding. Traditional department-standard machines are mainly used for positioning, navigation, and data recording, but the requirements of modern vehicles for department-standard machines have far exceeded these basic functions. Modern department-standard machines need to integrate multiple functions such as data processing, peripheral management, entertainment systems, and vehicle control to achieve comprehensive intelligence and automation of vehicles. For example, in the transportation of valuable goods, department-standard machines need to monitor the safety of goods and realize intelligent anti-theft and anti-loss; in cold chain transportation, department-standard machines need to monitor temperature and humidity in real time to ensure the stability of the goods; in the field of taxis and online car-hailing, department-standard machines need to monitor driver behavior, vehicle driving status, vehicle location and surrounding environment to improve driving safety.

[0003] In order to meet the demand for functional expansion of the department-standard machine, the first method is to redevelop the department-standard machine with a chip that has higher performance and richer peripheral interfaces. This chip usually has powerful data processing capabilities and rich IO resources, and can easily handle complex peripheral management and data processing tasks. However, this redevelopment method using high-performance and peripheral-rich chips has the problem of high cost, that is, the price of high-performance chips is usually much higher than that of traditional chips, which will increase the manufacturing cost of the department-standard machine and is not conducive to the sales and promotion of manufacturers. Moreover, redevelopment also means that a lot of R&D time and resources need to be invested, which increases the overall cost of the project.

[0004] The second method is to use a wireless communication interface to achieve communication between the host and the peripherals, that is, to use a chip that meets the system resource requirements as the host, and communicate with the peripherals and sensors through a wireless communication interface (such as Wi-Fi, Bluetooth, etc.). This solution allows the host to receive data from peripherals and sensors through a wireless network and perform corresponding processing and management, but the cost of the wireless communication interface is relatively high, which will increase the overall cost of the standard machine, and the wireless network is susceptible to interference, which may cause unstable or lost data transmission. The wireless communication protocol and fault tolerance requirements are high, and additional R&D resources need to be invested to ensure the reliability and stability of communication; in addition, the host needs to process intelligent functions and peripheral data received by the wireless interface, which places high demands on the processing performance of the host, and may require the use of higher performance chips to meet the requirements, thereby further increasing costs.

[0005] Therefore, the prior art needs to be improved. Summary of the invention

[0006] The technical problem to be solved by the present invention is that, in view of the defects of the prior art, the present invention provides a departmental standard host peripheral management device and a data processing method to solve the problems of high cost and unstable data transmission of the existing departmental standard host.

[0007] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0008] In a first aspect, the present invention provides a method for optimizing the quality of a driving recorder trajectory data, comprising:

[0009] A host, which is used to receive peripheral data from the slave, process and analyze the data, and issue corresponding control instructions according to the processing results;

[0010] A slave, the slave is used to collect data from the peripheral device, perform data preprocessing and packaging, and transmit the packaged data to the host in a wired manner; the slave is also used to perform corresponding actions according to the control instructions of the host;

[0011] The host and the slave are connected by wire and perform data transmission through a set communication protocol; wherein the communication protocol adopts a layered structure, including a physical layer, a data link layer and an application layer.

[0012] In one implementation, the host includes: an intelligent chip, a data processing module, a task scheduling module, a communication control module and an AI algorithm module; the data processing module, the task scheduling module, the communication control module and the AI ​​algorithm module are respectively connected to the intelligent chip;

[0013] Among them, the intelligent chip is used to process core data processing tasks; the data processing module is used to process and analyze the received peripheral data; the task scheduling module is used to perform multi-task scheduling; the communication control module is used to control the communication module to realize the communication between the host and the slave; the AI ​​algorithm module is used to provide the corresponding deep learning algorithm to the data processing module.

[0014] In one implementation, the slave includes: a single-chip microcomputer, a peripheral interface module, a data acquisition module, a preliminary processing module and a communication module; the peripheral interface module, the data acquisition module, the preliminary processing module and the communication module are respectively connected to the single-chip microcomputer;

[0015] The single chip microcomputer is used to control the operation of other modules in the slave; the peripheral interface module is used to connect to the peripheral device; the data acquisition module is used to collect data from the peripheral device; the preliminary processing module is used to pre-process and encapsulate the collected data; and the communication module is used to transmit and communicate data with the host.

[0016] In a second aspect, the present invention provides a data processing method of a departmental standard host peripheral management device, comprising:

[0017] The slave collects raw data from the peripheral device through the peripheral interface module according to the preset sampling frequency and time interval, and after preprocessing and packaging the raw data, sends the packaged data to the host through the communication module, and waits for the host's response;

[0018] The host receives the data sent by the slave through the communication control module, performs data analysis and processing, makes decisions based on the analysis and processing results, and outputs corresponding results to generate corresponding reports, warning information or control instructions.

[0019] In one implementation, the slave collects raw data from the peripheral device through the peripheral interface module according to a preset sampling frequency and time interval, which includes:

[0020] The host obtains background parameter configuration, packages the parameter configuration into a communication format, and sends it to the slave via an RS485 bus;

[0021] The slave receives the control instruction of the host, parses the parameter configuration and the output state of the GPIO interface according to the protocol, executes corresponding actions and adjusts the configuration of the peripheral device according to the instruction, and saves the parameter configuration.

[0022] In one implementation, after the original data is preprocessed and packaged, the packaged data is sent to the host through the communication module, and a response from the host is waited for, including.

[0023] Check whether the raw data contains abnormal values, noise or erroneous data, mark or remove unreasonable data, convert the data formats provided by different peripheral devices into a standard format used inside the slave, and perform corresponding calibration processing on the data that needs to be calibrated;

[0024] Add accurate timestamps to each collected data, mark the source peripheral of the data in each data packet, and combine multiple pre-processed data items into one data packet;

[0025] The encapsulated data is sent to the host through the communication module, and a response from the host is waited for.

[0026] In one implementation, the host receives data sent by the slave through a communication control module, and performs data parsing and processing, including:

[0027] The host receives the encapsulated data sent by the slave through the RS485 bus, and performs a communication protocol check on the received data;

[0028] For data that has passed the communication protocol verification, extract each data item according to the structure of the data packet, and after screening, classification and format conversion, filter, denoise and smooth the duplicate data, invalid data and abnormal data, and convert the corresponding data units according to the requirements of the AI ​​algorithm;

[0029] Use AI algorithms to conduct comprehensive analysis on the converted data, make decisions based on the analysis results, output corresponding results, and generate corresponding reports, warning information or control instructions.

[0030] In one implementation, the comprehensive analysis of the converted data using an AI algorithm includes:

[0031] Classify the different types of parsed data and store them in corresponding databases or data structures;

[0032] Integrate data from different peripheral devices, video data, and GPS data, synchronize the timestamps of all data, extract key information using image recognition technology, and associate the extracted key information with non-video data.

[0033] In one implementation, the data of different peripheral devices include: driving assistance system data, driver monitoring system data, and direction sensing module data.

[0034] In one implementation, the comprehensive analysis of the converted data using an AI algorithm includes:

[0035] Performing feature extraction and fusion on the driving assistance system data, the driver monitoring system data, and the direction sensing module data;

[0036] For the driving assistance system data, analyzing the vehicle's surrounding environment information, determining whether there is a potential dangerous situation, and generating a corresponding warning signal;

[0037] Analyze the driver monitoring system data, detect the driver's status, use image recognition technology to analyze the driver's facial expression characteristics and eye status characteristics, determine the corresponding fatigue level, and issue a fatigue driving reminder;

[0038] For the direction sensing module data, the driving behavior data is analyzed, the frequency and severity of the driving behavior are counted, and a corresponding warning signal is generated.

[0039] The present invention adopts the above technical solution to achieve the following effects:

[0040] The present invention adopts a master-slave architecture, wherein a host is set to receive peripheral data from a slave, perform data processing and analysis, and issue corresponding control instructions according to the processing results; and a slave is set to collect data from peripheral devices, perform data preprocessing and packaging, and transmit the packaged data to the host in a wired manner; the slave is also used to perform corresponding actions according to the control instructions of the host; the host and the slave are connected in a wired manner, and data is transmitted through a set communication protocol. The present invention realizes efficient and stable peripheral management and data processing by optimizing the communication protocol and data transmission method between the master and the slave. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0042] Figure 1 It is a structural diagram of a department standard host peripheral management device in the present invention.

[0043] Figure 2 The invention discloses a flow chart of a data processing method of a department standard host peripheral management device.

[0044] Figure 3 It is a timing diagram of interaction between the host, slave and peripheral devices in the present invention.

[0045] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0047] Exemplary Devices

[0048] Among the existing functional expansion solutions for departmental standard machines, one method is to redevelop the departmental standard machine using a chip with higher performance and richer peripheral interfaces. This chip usually has powerful data processing capabilities and abundant IO resources, and can easily cope with complex peripheral management and data processing tasks. However, this method of redeveloping using high-performance and peripheral-rich chips has the problem of high cost. Another method is to use a wireless communication interface to achieve communication between the host and peripherals, that is, to use a chip that meets the system resource requirements as the host, and communicate with peripherals and sensors through a wireless communication interface (such as Wi-Fi, Bluetooth, etc.). This solution allows the host to receive data from peripherals and sensors through a wireless network and perform corresponding processing and management, but the cost of the wireless communication interface is relatively high, which will increase the overall cost of the departmental standard machine, and the wireless network is susceptible to interference, which may cause unstable or lost data transmission. The requirements for wireless communication protocols and fault tolerance are high, and additional R&D resources need to be invested to ensure the reliability and stability of communication.

[0049] In view of the above technical problems, an embodiment of the present invention provides a device for managing peripherals of a departmental standard host, wherein a host is configured to receive peripheral data from a slave, perform data processing and analysis, and issue corresponding control instructions according to the processing results; and a slave is configured to collect data from peripheral devices, perform data preprocessing and packaging, and transmit the packaged data to the host via a wired method; the slave is also configured to perform corresponding actions according to the control instructions of the host; the host and the slave are connected via a wired method, and data is transmitted via a set communication protocol. In the embodiment of the present invention, efficient and stable peripheral management and data processing are achieved by optimizing the communication protocol and data transmission method between the master and the slave.

[0050] like Figure 1 As shown, an embodiment of the present invention provides a device for managing peripherals of a departmental standard host, comprising: a host and a slave; wherein the host is used to receive peripheral data from the slave, perform data processing and analysis, and issue corresponding control instructions according to the processing results; the slave is used to collect data from peripheral devices, perform data preprocessing and packaging, and transmit the packaged data to the host in a wired manner; the slave is also used to perform corresponding actions according to the control instructions of the host; the host and the slave are connected in a wired manner, and data is transmitted through a set communication protocol, and the communication protocol adopts a layered structure, including a physical layer, a data link layer and an application layer.

[0051] In this embodiment, the host part uses an intelligent chip that meets basic requirements. The chip has sufficient computing power to handle core data processing, task scheduling and communication control tasks. The host is responsible for receiving peripheral data from the slave, further processing and analysis, and issuing corresponding control instructions based on the processing results. The slave part uses a chip with interface performance suitable for single-chip microcomputer processing peripheral and sensor data.

[0052] Specifically, in one implementation of this embodiment, the host includes: an intelligent chip, a data processing module, a task scheduling module, a communication control module and an AI algorithm module; the data processing module, the task scheduling module, the communication control module and the AI ​​algorithm module are respectively connected to the intelligent chip; wherein the intelligent chip is used to process core data processing tasks; the data processing module is used to process and analyze received peripheral data; the task scheduling module is used to perform multi-task scheduling; the communication control module is used to control the communication module to realize communication between the host and the slave; the AI ​​algorithm module is used to provide the corresponding deep learning algorithm to the data processing module.

[0053] As an example, in this embodiment, the host chip selection is: a common intelligent chip with NPU function on the market can be selected as the core component of the host, such as ARM Cortex-M series (Rockchip RV1126), etc. These chips have powerful computing power and rich peripheral interfaces, which can meet the data processing and communication needs of the host.

[0054] In this embodiment, the slave is responsible for collecting data from peripherals (such as sensors, actuators, etc.), performing preliminary preprocessing and packaging, and then transmitting the data to the host via a wired manner. The slave can also perform corresponding actions according to the control instructions of the host.

[0055] Specifically, in one implementation of this embodiment, the slave includes: a single-chip microcomputer, a peripheral interface module, a data acquisition module, a preliminary processing module and a communication module; the peripheral interface module, the data acquisition module, the preliminary processing module and the communication module are respectively connected to the single-chip microcomputer; the single-chip microcomputer is used to control the operation of other modules in the slave; the peripheral interface module is used to connect to the peripheral device (such as a sensor, an actuator, etc.); the data acquisition module is used to collect data from the peripheral device; the preliminary processing module is used to preprocess and encapsulate the collected data; the communication module is used to transmit and communicate data with the host.

[0056] As an example, in this embodiment, the slave chip selection is: a low-cost, stable-performance single-chip microcomputer can be selected as the core component of the slave, such as the STM32F103 series (STM32F103RCT6), etc. These single-chip microcomputers have sufficient IO resources and computing power to complete the collection and preliminary processing of peripheral data.

[0057] Based on the above master-slave architecture, this embodiment achieves efficient and stable peripheral management and data processing by optimizing the communication protocol and data transmission mode; specifically, the communication protocol and data transmission between the host and the slave are:

[0058] Communication protocol: In this embodiment, an efficient and reliable communication protocol is designed for data transmission between the master and slave machines. The protocol adopts a layered structure, including: physical layer, data link layer and application layer. Among them, the physical layer is responsible for the physical transmission of data, the data link layer is responsible for the frame format, checksum and error handling of data, and the application layer is responsible for the encapsulation and parsing of data.

[0059] As an example, the physical layer design of the communication protocol in this embodiment is:

[0060] In order to improve the stability and reliability of data transmission, the wired communication RS485 mode (115200 baud rate, 8 data bits, 1 stop bit, no parity) is adopted in this embodiment to ensure the stability of data transmission and long-distance coverage.

[0061] As an example, the data link layer of the communication protocol in this embodiment is:

[0062] a. The frame format is:

[0063] Start flag: A specific byte used to mark the beginning of the frame 0xAA.

[0064] Protocol version number: one byte, used for distinction to facilitate future protocol expansion.

[0065] Serial number: A byte starts from 0 and increases by 1 each time it is sent. The initial value is 0xFF.

[0066] Check type: One byte, used to indicate the check type: no check, checksum, XOR check, crc8, crc16, etc.

[0067] Frame type: One byte used to indicate the frame type, such as control instruction frame, data reporting frame, slave upgrade frame, etc.

[0068] Data length: two bytes, used to indicate the length of the data part.

[0069] Data content: Different frame types contain different contents. For example, the control command frame contains specific control commands; the data reporting frame contains various types of data, such as serial port data, sensor data (temperature and humidity, door magnet, oil lever), CAN data, IO status (door, steering, high and low lights, brakes), battery voltage value, speed, slave time calibration (UNIX timestamp), etc.

[0070] Checksum: Zero to two bytes, used to check the frame content.

[0071] End flag: A specific byte used to mark the end of the frame 0x55.

[0072] b. Error handling method is: implement verification, timeout retransmission and error retry mechanism to deal with errors and packet loss in data transmission.

[0073] As an example, the application layer of the communication protocol in this embodiment is:

[0074] The application layer instructions include control type, heartbeat type, data reporting type and slave upgrade type instructions.

[0075] Specifically, when the host and the slave communicate through the above communication protocol, the host's control command transmission, the slave's heartbeat reporting, the host's response data transmission, and the slave's upgrade are as follows.

[0076] 1) The control instructions of the host are: the host sets the query heartbeat reporting interval, each serial port configuration (each serial port is generally fixed to a certain peripheral by default), CAN bus configuration, IO port output, system UNIX timestamp, each sensor configuration, etc. for the slave; query the slave version information.

[0077] A. The control instruction format is:

[0078] Command identifier: One byte, controls the command type.

[0079] Parameter address: one byte, parameter configuration starting virtual address (data reporting interval, serial port configuration, CAN bus parameters, IO output, sensor configuration, etc. are virtualized into one address).

[0080] Parameter address length: one byte, the length of the parameter address written starting from the parameter address. Supports simultaneous configuration of multiple consecutive parameter addresses.

[0081] Parameter data: parameter configuration of each parameter address.

[0082] B. The slave response mechanism is: the slave sets the success or failure flag, error code and data feedback in response to the control command.

[0083] 2) The heartbeat reporting method of the slave is as follows: the slave heartbeat reports the collected values ​​of each sensor, IO port status, battery IO voltage value and vehicle speed according to the interval configured by the host.

[0084] A. The format of the heartbeat reporting instruction is:

[0085] Command identifier: one byte, heartbeat command type.

[0086] Timestamp: 4 bytes, system UNIX timestamp.

[0087] Data length: two bytes, heartbeat content data length.

[0088] Heartbeat content: collected values ​​of various sensors, IO port status, battery IO voltage value, vehicle speed, etc.

[0089] B. The host response mechanism is: the host responds to the heartbeat.

[0090] 3) The data transmission mode of the host response is:

[0091] A. The command format of the host response is:

[0092] Command identifier: One byte, controls the command type.

[0093] Timestamp: 4 bytes, system UNIX timestamp.

[0094] Data type: One byte.

[0095] Data length: two bytes.

[0096] Data content: various serial port and CAN bus data.

[0097] B. The priority of the host response is:

[0098] Design a priority processing mechanism based on the urgency and importance of the data to ensure timely transmission of critical data.

[0099] 4) The slave upgrade method is:

[0100] A. The instruction format for upgrading the slave is:

[0101] Command identifier: one byte, upgrade command type, including the start of upgrade package information sending, upgrade package transmission, and upgrade package sending end.

[0102] Data type: One byte.

[0103] Data packet sequence number: one byte, sent only when the command identifier is an upgrade packet transmission.

[0104] Data length: two bytes.

[0105] Data content: When the instruction is to start upgrading, the upgrade package version information, upgrade package file size and upgrade package verification are sent; when the instruction is to transfer the upgrade package, it is the upgrade package data content; when the upgrade package is sent, there is no content.

[0106] B. The process of upgrading the slave is as follows:

[0107] The slave upgrade process includes: receiving upgrade package information, accepting upgrade package, verifying upgrade package, and feedback of upgrade result. The important data in the heartbeat and data will be sent immediately before the upgrade.

[0108] C. The error handling method for slave machine upgrade is: abnormal situations such as upgrade package verification failure and power failure during upgrade can ensure that the slave machine can run the old version program normally.

[0109] As an example, in some application scenarios of this embodiment, based on the above transmission protocol between the host and the slave, the data processing process of the department standard host peripheral management device includes the following steps:

[0110] A. After the host is running, it pulls relevant parameter configurations from the background (including host system configuration, peripheral configuration, master and slave background version information, peripheral data reporting frequency, etc.), and obtains the slave version information. If the slave version is lower than the background slave version, the upgrade process is performed; the host sends the peripheral and slave-related configuration parameters obtained from the background to the slave (if the host fails to send, the error handling process is performed to resend).

[0111] B. The slave obtains peripheral data regularly according to the reporting frequency. If there is data on the serial port or CAN, the serial port, CAN bus received data, and peripheral data are packaged and inserted into the slave send buffer according to the data priority (key data is sent immediately). The serial port and CAN bus are designed to receive and send queues to avoid data loss.

[0112] C. The slave sends data to the host according to the data priority in the send buffer. (If the slave fails to send, it will perform error handling and resend).

[0113] D. The host receives the data sent by the slave and performs data analysis and processing. The host combines the peripheral data with video data, GPS data, and six-axis data for comprehensive analysis and performs relevant AI algorithm analysis.

[0114] For example, by identifying goods through videos or pictures, combining temperature and humidity with goods, and training with regression algorithms in machine learning, such as linear regression algorithms or support vector regression algorithms, these algorithms can be trained based on historical sensor data (including data in normal and abnormal states); through these regression algorithm training, the relationship between environmental factors such as temperature and humidity and the state of goods can be learned. When new data is input, it can accurately predict whether the state of the goods is normal, and issue an alarm when it is abnormal.

[0115] For example, the truck doors detected by door magnets and infrared cameras can be combined with the smart camera-AI image recognition system, and trained using the target detection algorithm and image classification algorithm in deep learning, such as Faster R-CNN (regional convolutional neural network) or ResNet (residual network). After being trained with a large number of images labeled with normal cargo status and abnormal cargo status (such as cargo loss, packaging damage, etc.), these algorithms can accurately identify the status changes of cargo in real-time monitoring images.

[0116] It is worth mentioning that the present embodiment can be modified and improved in any of the following ways:

[0117] 1) Expand the types of peripherals: You can add more types and quantities of peripherals according to actual needs, such as adding pressure sensors, gas sensors, etc., to enrich the functions and performance of the system. When adding peripherals, you need to ensure that the interface and processing power of the slave can meet the needs of the new peripherals, and update the communication protocol to support data transmission of the new peripherals.

[0118] 2) Communication interface design: You can choose a suitable communication interface for data transmission according to actual needs. For example, for wired communication, you can choose CAN bus, Ethernet and other interfaces; for wireless communication, you can choose low-power Bluetooth, Zigbee and other interfaces. When selecting a communication interface, you need to consider factors such as data transmission rate, transmission distance, power consumption and cost. At the same time, you also need to design the corresponding communication protocol and data transmission format to ensure the accuracy and reliability of data transmission.

[0119] 3) The functions of the slave can be expanded, for example, adding data storage function, temporarily storing the collected data in the slave, and transmitting it when the host needs it. This can reduce the burden on the host and improve the response speed of the system.

[0120] 4) Optimize communication protocols: The communication protocols can be optimized and improved according to actual needs, such as adding data compression functions, increasing data transmission rates, etc., to further improve the performance and efficiency of the system.

[0121] 5) Integration of other functional modules: Other functional modules, such as audio processing modules, can be integrated into the system to achieve richer functions and application scenarios. These functional modules can communicate and exchange data with the host or slave to jointly complete the tasks and goals of the system.

[0122] This embodiment achieves the following technical effects through the above technical solution:

[0123] This embodiment realizes efficient peripheral management and data processing through the division of labor and cooperation of the master-slave architecture and the optimized communication protocol and data transmission method. The host can process a large amount of peripheral data in a timely manner and issue corresponding control instructions according to the processing results, thereby improving the overall performance of the system. Moreover, the stability and reliability of data transmission are improved by combining wired communication with optimized wireless communication. Even in harsh communication environments, the system can ensure the continuity and accuracy of data transmission; and the use of relatively low-cost intelligent chips and single-chip microcomputers as the core components of the host and slave significantly reduces the manufacturing cost of the system. At the same time, the optimized communication protocol and data transmission method also reduce the operating cost and maintenance cost of the system.

[0124] Exemplary Methods

[0125] Based on the above embodiments, an embodiment of the present invention further provides a data processing method for a device for managing peripherals of a host computer.

[0126] like Figure 2 As shown, an embodiment of the present invention provides a data processing method of a department standard host peripheral management device, comprising the following steps:

[0127] In step S100, the slave collects raw data from the peripheral device through the peripheral interface module according to a preset sampling frequency and time interval, pre-processes and packages the raw data, and then sends the packaged data to the host through the communication module, while waiting for a response from the host.

[0128] In this embodiment, the slave is responsible for collecting data from peripherals (such as sensors, actuators, etc.), performing preliminary preprocessing and packaging, and then transmitting the data to the host via a wired manner. The slave can also perform corresponding actions according to the control instructions of the host.

[0129] Specifically, in one implementation of this embodiment, the slave includes: a single-chip microcomputer, a peripheral interface module, a data acquisition module, a preliminary processing module and a communication module; the peripheral interface module, the data acquisition module, the preliminary processing module and the communication module are respectively connected to the single-chip microcomputer; the single-chip microcomputer is used to control the operation of other modules in the slave; the peripheral interface module is used to connect to the peripheral device (such as a sensor, an actuator, etc.); the data acquisition module is used to collect data from the peripheral device; the preliminary processing module is used to preprocess and encapsulate the collected data; the communication module is used to transmit and communicate data with the host.

[0130] As an example, in this embodiment, the slave chip selection is: a low-cost, stable-performance single-chip microcomputer can be selected as the core component of the slave, such as the STM32F103 series (STM32F103RCT6), etc. These single-chip microcomputers have sufficient IO resources and computing power to complete the collection and preliminary processing of peripheral data.

[0131] In this embodiment, before the slave uploads peripheral data to the host, the slave and peripheral devices need to be configured by the host, that is, after the host is running, it pulls relevant parameter configurations from the background (including host system configuration, peripheral configuration, master-slave background version information, peripheral data reporting frequency, etc.), and the host obtains the slave version information. If the slave version is lower than the background slave version, the upgrade process is performed; the host sends the peripheral and slave-related configuration parameters obtained from the background to the slave (if the host fails to send, the error handling process is performed for resending).

[0132] Specifically, in an implementation of this embodiment, the following steps are included before step S100:

[0133] Step S101a, the host obtains background parameter configuration, packages the parameter configuration into a communication format, and sends it to the slave via the RS485 bus;

[0134] Step S101b, the slave receives the control instruction of the host, parses the parameter configuration and the output state of the GPIO interface according to the protocol, executes corresponding actions and adjusts the configuration of the peripheral device according to the instruction, and saves the parameter configuration.

[0135] As an example, in this embodiment, the timing of data transmission between the master and slave devices includes the following stages:

[0136] a. Host control command sending stage: The host obtains the background parameter configuration (including heartbeat frequency, data collection frequency, serial port baud rate, CAN bus parameter configuration, GPIO output, etc.), packages the parameter configuration into a communication format, and then sends it to the slave through the RS485 bus (if a sending error occurs, a sending error is processed).

[0137] b. Slave execution control instruction stage: The slave receives the control instruction from the host, parses the parameter configuration and GPIO port output status according to the protocol, and then performs corresponding actions and adjusts the configuration of peripherals according to the instruction (for example, setting the serial port, CAN bus and other peripheral configurations; adjusting the sampling frequency of sensors, power supply voltage, vehicle speed, GPIO input, etc.; adjusting the heartbeat reporting frequency), and saves the parameters.

[0138] In this embodiment, after the host configures the slave and peripheral devices, the slave can obtain peripheral data regularly according to the reporting frequency. If the serial port and CAN have data, the serial port and CAN bus receive data and the peripheral data are packaged and inserted into the slave sending buffer according to the data priority (wherein important key data is sent immediately). Among them, the serial port and CAN bus are designed to receive and send queues to avoid data loss. Moreover, the slave sends the data to the host according to the data priority in the sending buffer. If the slave fails to send, the error handling process is performed for retransmission.

[0139] Specifically, in an implementation of this embodiment, step S100 includes the following steps:

[0140] Step S101, checking whether the original data contains abnormal values, noise or erroneous data, marking or removing unreasonable data, converting the data formats provided by different peripheral devices into a standard format used inside the slave, and performing corresponding calibration processing on the data that needs to be calibrated;

[0141] Step S102, adding an accurate timestamp to each collected data, marking the source peripheral of the data in each data packet, and combining the preprocessed multiple data items into one data packet;

[0142] Step S103, sending the encapsulated data to the host through the communication module, and waiting for the response of the host.

[0143] As an example, in this embodiment, the timing of data transmission between the master and slave devices also includes the following stages:

[0144] c. Slave data collection stage:

[0145] 1. Data acquisition: The slave collects raw data from external devices (such as sensors, actuators, etc.) through peripheral interface modules (such as ADC, UART, CAN, SPI, IIC, etc.) according to the preset sampling frequency and time interval. These data may include temperature, pressure, humidity, speed and other physical quantities.

[0146] 2. Preliminary pretreatment:

[0147] Data cleaning: Check the collected data for outliers, noise, or erroneous data. Mark or remove obviously unreasonable data to ensure data quality. For example, if sensor data has abnormal fluctuations, it needs to be cleaned.

[0148] Data format conversion: Convert the various data formats provided by different peripherals into a standard format used inside the slave. This facilitates subsequent processing and packaging, as well as data exchange with other systems. For example, the numerical formats of different sensors are unified into a standardized digital format.

[0149] Data calibration: For some peripheral data that need to be calibrated, corresponding calibration processing is performed. For example, temperature compensation and zero point calibration are performed on the sensor's measurement value to improve the accuracy of the data.

[0150] 3. Data encapsulation:

[0151] Add timestamp: Add an accurate timestamp to each collected data so that the time sequence and timeliness of the data can be determined during subsequent analysis.

[0152] Mark the data source: Mark the source peripheral of the data in the data packet so that in subsequent processing, data from different peripherals can be distinguished and targeted analysis and processing can be performed.

[0153] Data Packaging: Combine multiple pre-processed data items into a data packet for transmission and storage. Packaging is done in a protocol-defined format to ensure data integrity and identifiability.

[0154] d. Slave data transmission stage: The slave sends the packaged data to the host through the communication module and waits for the host's response. During the process of data transmission and waiting for response, if an abnormal situation occurs (for example, communication failure, data loss, timeout, etc.), retransmission is performed.

[0155] like Figure 2 As shown, an embodiment of the present invention provides a data processing method of a department standard host peripheral management device, comprising the following steps:

[0156] In step S200, the host receives the data sent by the slave through the communication control module, performs data analysis and processing, makes a decision based on the analysis and processing results, and outputs the corresponding results to generate corresponding reports, warning information or control instructions.

[0157] In this embodiment, the host part uses an intelligent chip that meets basic requirements. The chip has sufficient computing power to handle core data processing, task scheduling and communication control tasks. The host is responsible for receiving peripheral data from the slave, further processing and analysis, and issuing corresponding control instructions based on the processing results. The slave part uses a chip with interface performance suitable for single-chip microcomputer processing peripheral and sensor data.

[0158] Specifically, in one implementation of this embodiment, the host includes: an intelligent chip, a data processing module, a task scheduling module, a communication control module and an AI algorithm module; the data processing module, the task scheduling module, the communication control module and the AI ​​algorithm module are respectively connected to the intelligent chip; wherein the intelligent chip is used to process core data processing tasks; the data processing module is used to process and analyze received peripheral data; the task scheduling module is used to perform multi-task scheduling; the communication control module is used to control the communication module to realize communication between the host and the slave; the AI ​​algorithm module is used to provide the corresponding deep learning algorithm to the data processing module.

[0159] As an example, in this embodiment, the host chip selection is: a common intelligent chip with NPU function on the market can be selected as the core component of the host, such as ARM Cortex-M series (Rockchip RV1126), etc. These chips have powerful computing power and rich peripheral interfaces, which can meet the data processing and communication needs of the host.

[0160] In this embodiment, after the slave sends the packaged data to the host through the communication module, the host performs a communication protocol check on the data sent by the slave, and then performs data analysis and processing, and makes decisions based on the analysis and processing results of the AI ​​algorithm, outputs corresponding results, and generates corresponding reports, warning information or control instructions to control the safety of the vehicle.

[0161] Specifically, in an implementation of this embodiment, step S200 includes the following steps:

[0162] Step S201, the host receives the encapsulated data sent by the slave through the RS485 bus, and performs a communication protocol check on the received data;

[0163] Step S202: extract the data items from the data that have passed the communication protocol verification according to the structure of the data packet, filter and classify them, convert the format, filter, denoise and smooth the duplicate data, invalid data and abnormal data, and convert the corresponding data into units according to the requirements of the AI ​​algorithm;

[0164] Step S203, using AI algorithm to conduct comprehensive analysis on the converted data, make decisions based on the analysis results and output corresponding results, and generate corresponding reports, warning information or control instructions.

[0165] In this embodiment, after receiving the data sent by the slave, the host parses and processes the data. The host combines the peripheral data and video data, GPS data, and six-axis data for comprehensive analysis and performs relevant AI algorithm analysis.

[0166] For example, by identifying goods through videos or pictures, combining temperature and humidity with goods, and training with regression algorithms in machine learning, such as linear regression algorithms or support vector regression algorithms, these algorithms can be trained based on historical sensor data (including data in normal and abnormal states); through these regression algorithm training, the relationship between environmental factors such as temperature and humidity and the state of goods can be learned. When new data is input, it can accurately predict whether the state of the goods is normal, and issue an alarm when it is abnormal.

[0167] For example, the truck doors detected by door magnets and infrared cameras can be combined with the smart camera-AI image recognition system, and trained using the target detection algorithm and image classification algorithm in deep learning, such as Faster R-CNN (regional convolutional neural network) or ResNet (residual network). After being trained with a large number of images labeled with normal cargo status and abnormal cargo status (such as cargo loss, packaging damage, etc.), these algorithms can accurately identify the status changes of cargo in real-time monitoring images.

[0168] Specifically, in one implementation of this embodiment, the AI ​​algorithm is used to perform a comprehensive analysis on the converted data, which includes: classifying the different types of parsed data and storing them in corresponding databases or data structures; integrating data from different peripheral devices, video data, and GPS data, synchronizing the timestamps of all data, extracting key information using image recognition technology, and associating the extracted key information with non-video data. The data from different peripheral devices include: driving assistance system data, driver monitoring system data, and direction sensing module data.

[0169] Specifically, in one implementation of this embodiment, the AI ​​algorithm is used to perform a comprehensive analysis on the converted data, including: extracting and fusing features of the driving assistance system data, the driver monitoring system data, and the direction sensing module data; for the driving assistance system data, analyzing the vehicle's surrounding environment information to determine whether there is a potential dangerous situation, and generating a corresponding warning signal; analyzing the driver monitoring system data, detecting the driver's status, using image recognition technology to analyze the driver's facial expression characteristics and eye status characteristics, determining the corresponding degree of fatigue, and providing fatigue driving reminders; for the direction sensing module data, analyzing the driving behavior data, counting the frequency and severity of driving behavior, and generating a corresponding warning signal.

[0170] As an example, in this embodiment, the timing of data transmission between the master and slave devices also includes the following stages:

[0171] e. Host data receiving stage: The host receives the data sent by the slave through the communication control module, and performs data analysis and processing.

[0172] 1. Data reception: The host receives slave data via RS485 and performs communication protocol verification on the data. If the verification passes, the data field is parsed.

[0173] 2. Data analysis: According to the structure of the data packet, extract each data item and first filter and classify each data. Then convert the data from binary format or specific encoding format to a format that can be processed inside the host. For example, convert digital codes such as power supply voltage, temperature, and vehicle speed into actual values. Then filter, denoise, and smooth the data for duplicate data, invalid data, and abnormal data. Finally, convert the corresponding data into units according to the requirements of the AI ​​algorithm.

[0174] 3. Data processing:

[0175] The parsed data of different types are classified and stored in corresponding databases or data structures. For example, ADAS data (i.e. driving assistance system data), DMS data (i.e. driver monitoring system data), GPS data (Gsensor module data, i.e. direction sensing module data), etc. are stored in different tables or arrays.

[0176] Integrate data from different peripherals (such as ADAS, DMS, Gsensor modules, etc.) as well as video data, GPS data and other related data. Ensure the synchronization of timestamps of various data, and use image recognition technology to extract key information, such as objects around the vehicle, road signs, driver's facial features, etc.; associate this information with other data, such as comparing and verifying the vehicle position detected in the video with the vehicle position in the GPS data.

[0177] Extract valuable features from peripheral data for feature extraction and fusion. For example, extract features such as the distance between the vehicle and surrounding objects and the relative speed from ADAS data; extract features such as the driver's fatigue level and attention status from DMS data; extract features such as the vehicle's acceleration and tilt angle from Gsensor module data. Fuse these features with features in video data and GPS data. For example, combine the road conditions detected in the video with the location information in the GPS data to determine whether the vehicle is driving in a complex road area; combine the driver's facial features with the vehicle's driving status to analyze the impact of the driver's emotions on driving behavior.

[0178] Use AI algorithms to conduct a comprehensive analysis of the fused features. For example, for ADAS system data, analyze the vehicle's surrounding environment information, such as the distance to the vehicle in front, lane deviation, etc. Use algorithms to determine whether there are potential dangerous situations, such as an impending collision, lane deviation without timely correction, etc., and generate corresponding warning signals. Analyze DMS system data to detect the driver's status, such as whether he is driving fatigued and whether his attention is focused. Use image recognition technology to analyze the driver's facial expressions, eye conditions and other features to determine his fatigue level and issue reminders when necessary. Analyze driving behavior data, such as sudden acceleration, sudden deceleration, sharp turns, speeding, etc. Count the frequency and severity of these behaviors to provide a basis for evaluating the driver's driving habits.

[0179] Make decisions based on the analysis results and output corresponding results to generate corresponding reports, warning information or control instructions. If a dangerous situation is detected, such as an impending collision or driver fatigue, the AI ​​algorithm module can output a warning signal to remind the driver to take appropriate measures. In some cases, it is also possible to automatically avoid danger by controlling certain systems of the vehicle, such as automatic braking, adjusting the speed, etc.

[0180] The GPS module data is processed, combined with map information to determine the vehicle's location, and the vehicle's driving trajectory is analyzed. The future driving route can be predicted based on historical trajectory data to provide support for intelligent navigation.

[0181] The following uses actual application scenarios as examples to illustrate the method in this embodiment:

[0182] like Figure 3 As shown, in an actual application scenario of this embodiment, the timing of data transmission between the master and slave machines includes the following steps:

[0183] 1. The host sends reporting interval, peripheral configuration, and time synchronization parameters to the slave;

[0184] 2. The slave sets the configuration parameters sent by the host to the peripheral;

[0185] 3. The peripheral returns the setting result to the slave;

[0186] 4. The slave integrates the setting results and sends them to the master;

[0187] 5. If a parameter setting fails or the slave machine responds with a timeout, resend the setting to the slave machine;

[0188] 6. The slave device periodically obtains data such as peripheral IO, vehicle speed, battery voltage, etc.;

[0189] 7. The peripheral returns the corresponding data to the slave;

[0190] 8. When the peripheral has CAN bus or serial port data, the slave will pack the peripheral data, serial port data and CAN data according to the protocol, and then insert them into the sending queue according to the priority;

[0191] 9. The slave sends the data in the transmission queue to the host; the host parses and processes the received peripheral data, and then performs intelligent AI algorithm analysis based on video, GPS, six-axis and other data;

[0192] 10. If the slave fails to send or times out, resend.

[0193] This embodiment achieves the following technical effects through the above technical solution:

[0194] This embodiment achieves efficient peripheral management and data processing through the division of labor and cooperation of the master-slave architecture and optimized communication protocols and data transmission methods. The host can process a large amount of peripheral data in a timely manner and issue corresponding control instructions based on the processing results, thereby improving the overall performance of the system. In addition, the AI ​​algorithm is used to conduct a comprehensive analysis of the peripheral data, make decisions based on the analysis results and output corresponding results, generate corresponding reports, warning information or control instructions, so that during the driving process of the vehicle, there will be no data transmission interruption or error due to wireless network interference, and the vehicle can be controlled according to the actual situation of the road, ensuring the safe driving of the vehicle.

[0195] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and volatile memory.

[0196] In summary, the present invention provides a device for managing peripherals of a departmental standard host and a data processing method, including: a host and a slave, the host is used to receive peripheral data from the slave, perform data processing and analysis, and issue corresponding control instructions according to the processing results; the slave is used to collect data from peripheral devices, perform data preprocessing and packaging, and transmit the packaged data to the host by wired means; the slave is also used to perform corresponding actions according to the control instructions of the host; the host and the slave are connected by wired means, and data is transmitted through a set communication protocol; wherein the communication protocol adopts a layered structure, including a physical layer, a data link layer, and an application layer. The present invention adopts a master-slave architecture, and realizes efficient and stable peripheral management and data processing by optimizing the communication protocol and data transmission method between the master and the slave.

[0197] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A departmental standard host peripheral management device, characterized in that: include: A host, which is used to receive peripheral data from the slave, process and analyze the data, and issue corresponding control instructions according to the processing results; A slave, the slave is used to collect data from the peripheral device, perform data preprocessing and packaging, and transmit the packaged data to the host in a wired manner; the slave is also used to perform corresponding actions according to the control instructions of the host; The host and the slave are connected by wire and perform data transmission through a set communication protocol; wherein the communication protocol adopts a layered structure, including a physical layer, a data link layer and an application layer.

2. The device for managing peripherals of a departmental standard host according to claim 1, characterized in that: The host comprises: an intelligent chip, a data processing module, a task scheduling module, a communication control module and an AI algorithm module; the data processing module, the task scheduling module, the communication control module and the AI ​​algorithm module are respectively connected to the intelligent chip; Among them, the intelligent chip is used to process core data processing tasks; the data processing module is used to process and analyze the received peripheral data; the task scheduling module is used to perform multi-task scheduling; the communication control module is used to control the communication module to realize the communication between the host and the slave; the AI ​​algorithm module is used to provide the corresponding deep learning algorithm to the data processing module.

3. The device for managing peripherals of a departmental standard host according to claim 1, characterized in that: The slave includes: a single-chip microcomputer, a peripheral interface module, a data acquisition module, a preliminary processing module and a communication module; the peripheral interface module, the data acquisition module, the preliminary processing module and the communication module are respectively connected to the single-chip microcomputer; The single chip microcomputer is used to control the operation of other modules in the slave; the peripheral interface module is used to connect to the peripheral device; the data acquisition module is used to collect data from the peripheral device; the preliminary processing module is used to pre-process and encapsulate the collected data; and the communication module is used to transmit and communicate data with the host.

4. A data processing method for a departmental standard host peripheral management device, characterized in that: include: The slave collects raw data from the peripheral device through the peripheral interface module according to the preset sampling frequency and time interval, and after preprocessing and packaging the raw data, sends the packaged data to the host through the communication module, and waits for the host's response; The host receives the data sent by the slave through the communication control module, performs data analysis and processing, makes decisions based on the analysis and processing results, and outputs corresponding results to generate corresponding reports, warning information or control instructions.

5. The data processing method of the department standard host peripheral management device according to claim 4 is characterized in that: The slave collects raw data from the peripheral device through the peripheral interface module according to a preset sampling frequency and time interval, which includes: The host obtains background parameter configuration, packages the parameter configuration into a communication format, and sends it to the slave via an RS485 bus; The slave receives the control instruction of the host, parses the parameter configuration and the output state of the GPIO interface according to the protocol, executes corresponding actions and adjusts the configuration of the peripheral device according to the instruction, and saves the parameter configuration.

6. The data processing method of the department standard host peripheral management device according to claim 4 is characterized in that: After the original data is preprocessed and packaged, the packaged data is sent to the host through the communication module, and a response from the host is waited for, including. Check whether the raw data contains abnormal values, noise or erroneous data, mark or remove unreasonable data, convert the data formats provided by different peripheral devices into a standard format used inside the slave, and perform corresponding calibration processing on the data that needs to be calibrated; Add accurate timestamps to each collected data, mark the source peripheral of the data in each data packet, and combine multiple pre-processed data items into one data packet; The encapsulated data is sent to the host through the communication module, and a response from the host is waited for.

7. The data processing method of the department standard host peripheral management device according to claim 4 is characterized in that: The host receives the data sent by the slave through the communication control module, and performs data analysis and processing, including: The host receives the encapsulated data sent by the slave through the RS485 bus, and performs a communication protocol check on the received data; For data that has passed the communication protocol verification, extract each data item according to the structure of the data packet, and after screening, classification and format conversion, filter, denoise and smooth the duplicate data, invalid data and abnormal data, and convert the corresponding data units according to the requirements of the AI ​​algorithm; Use AI algorithms to conduct comprehensive analysis on the converted data, make decisions based on the analysis results, output corresponding results, and generate corresponding reports, warning information or control instructions.

8. The data processing method of the department standard host peripheral management device according to claim 7 is characterized in that: The use of AI algorithms to conduct a comprehensive analysis of the converted data previously included: Classify the different types of parsed data and store them in corresponding databases or data structures; Integrate data from different peripheral devices, video data, and GPS data, synchronize the timestamps of all data, extract key information using image recognition technology, and associate the extracted key information with non-video data.

9. The data processing method of the department standard host peripheral management device according to claim 8, characterized in that: The data of different peripheral devices include: driving assistance system data, driver monitoring system data, and direction sensing module data.

10. The data processing method of the department standard host peripheral management device according to claim 9, characterized in that: The AI ​​algorithm is used to conduct a comprehensive analysis of the converted data, including: Performing feature extraction and fusion on the driving assistance system data, the driver monitoring system data, and the direction sensing module data; For the driving assistance system data, analyzing the vehicle's surrounding environment information, determining whether there is a potential dangerous situation, and generating a corresponding warning signal; Analyze the driver monitoring system data, detect the driver's status, use image recognition technology to analyze the driver's facial expression characteristics and eye status characteristics, determine the corresponding fatigue level, and issue a fatigue driving reminder; For the direction sensing module data, the driving behavior data is analyzed, the frequency and severity of the driving behavior are counted, and a corresponding warning signal is generated.

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