CN115131894A - Motor vehicle remote monitoring system based on block chain technology - Google Patents
Motor vehicle remote monitoring system based on block chain technology Download PDFInfo
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- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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Abstract
The invention provides a motor vehicle remote monitoring system based on a block chain technology, which comprises a data acquisition module, a data processing module, a wireless communication module, a block chain and a remote monitoring platform, wherein the data acquisition module is used for acquiring data; the data acquisition module is arranged on the motor vehicle and is used for acquiring vehicle operation data and driving state information of a driver in the operation process of the motor vehicle; the data processing module is used for preprocessing the vehicle operation data and the driving state information and packaging the preprocessed vehicle operation data and the driving state information into blocks; the wireless communication module uploads the block into a block chain; the remote monitoring platform acquires the blocks from the block chain, processes the blocks to acquire vehicle operation data and driving state information, analyzes the working state of the motor vehicle according to the vehicle operation data and the driving state information to obtain an analysis result, and sends an alarm signal to the motor vehicle and sends abnormal state information to the management terminal if the analysis result is in an abnormal state.
Description
Technical Field
The invention relates to the technical field of motor vehicle internet of things, in particular to a motor vehicle remote monitoring system based on a block chain technology.
Background
With the development of economy and the progress of society, the number and the popularity of motor vehicles are increasing day by day, and meanwhile, the traffic accident situation is becoming more severe. According to the statistical bulletin of national economy and social development in 2014, the method comprises the following steps: the quantity of civil motor vehicles in China at the bottom of 2014 in China reaches the historical new height, the number of the civil motor vehicles is 15447 thousands, the civil motor vehicles is increased by 12.4% compared with the number of the civil motor vehicles at the end of 2013, the number of the death people in traffic accidents in 2014 is 34292.34, the number of the death people is increased by 2688.04 compared with the death people 31604.3 in 2013, and the increase rate is 8.5%. Among them, traffic accidents caused by the carelessness of the driver's safety consciousness account for a considerable proportion, for example, traffic accidents caused by fatigue driving account for about 20% of the total number of traffic accidents, 40% of the total number of major traffic accidents, traffic accidents caused by overspeed driving account for 19% of the total number of traffic accidents, and traffic accidents caused by overload driving account for 10% of the total number of traffic accidents. In addition, traffic accidents can also occur due to the problem of equipment failure during the operation of the motor vehicle. Therefore, how to comprehensively and accurately monitor the running state of the motor vehicle and the working state of a driver in the running process of the motor vehicle and improve the running safety of the motor vehicle becomes a problem to be solved urgently.
Disclosure of Invention
The present invention is directed to a remote monitoring system for a motor vehicle based on a block chain technology, so as to solve the technical problems in the background art.
In order to achieve the above object, the present invention provides a motor vehicle remote monitoring system based on the block chain technology, which comprises a data acquisition module, a data processing module, a wireless communication module, a block chain and a remote monitoring platform, wherein,
the data acquisition module is arranged on a motor vehicle and is used for acquiring vehicle operation data and driving state information of a driver in the operation process of the motor vehicle;
the data processing module is used for preprocessing the vehicle operation data and the driving state information and packaging the preprocessed vehicle operation data and the driving state information into blocks;
the wireless communication module uploads the block into a block chain;
the remote monitoring platform acquires the block from the block chain, processes the block to acquire the vehicle operation data and the driving state information, analyzes the working state of the motor vehicle according to the vehicle operation data and the driving state information to obtain an analysis result, and sends an alarm signal to the motor vehicle and sends the abnormal state information to the management terminal if the analysis result is in an abnormal state.
Further, the data acquisition module comprises a tire pressure sensor, an engine sensor, an oil tank liquid level sensor, a water tank liquid level sensor, a storage battery voltage sensor, a speed sensor, a vehicle body collision sensor, a positioner and a camera.
Further, the camera is a camera with a night vision function;
the camera is adjustably mounted on a front windshield of the motor vehicle through a sucker, and is connected with the sucker through a spherical hinge seat.
Further, the data processing module preprocesses the vehicle operation data and the driving state information, and specifically includes:
performing data integration on the vehicle operation data and the driving state information to obtain vehicle data;
based on the time and the block size requirement of the block chain, slicing the vehicle data to obtain vehicle data segments;
and packaging the vehicle data fragments into blocks.
Further, the analyzing the working state of the motor vehicle according to the vehicle operation data and the driving state information to obtain an analysis result specifically includes:
analyzing the running state of the motor vehicle according to the vehicle running data to obtain a first analysis result;
analyzing the driving state of the driver according to the driving state information to obtain a second analysis result;
and obtaining a comprehensive analysis result according to the first analysis result and the second analysis result.
Further, the vehicle operation data comprises tire pressure data, engine working data, oil tank liquid level data, water tank liquid level data, battery voltage data, vehicle speed data, collision state data and vehicle positioning data.
Further, the analyzing the operation state of the motor vehicle according to the vehicle operation data to obtain a first analysis result specifically includes:
and if at least one of the tire pressure data, the engine working data, the oil tank liquid level data, the water tank liquid level data, the battery voltage data, the vehicle speed data or the collision state data is not in the corresponding set threshold value interval, judging that the motor vehicle is in an abnormal operation state.
Further, the driving state information includes a driver face video image;
the analyzing the driving state of the driver according to the driving state information to obtain a second analysis result specifically includes:
carrying out image recognition on a video image of the face of a driver to obtain a recognition result, wherein the recognition result comprises the blinking frequency, the eye closing interval time, the eye closing duration of each time and whether a yawning state occurs or not of the driver;
performing fatigue evaluation analysis according to the identification result, and outputting a second analysis result;
the second analysis conclusion includes three driver states of wakefulness, fatigue and extreme fatigue.
Further, carrying out image recognition on the video image of the face of the driver by adopting a fatigue recognition model;
the fatigue recognition model adopts a convolutional neural network algorithm, and is obtained by training a plurality of samples.
Further, the data processing module is an arm microprocessor; the wireless communication module is a 4G module, a 5G module and/or a WiFi module.
According to the motor vehicle remote monitoring system based on the block chain technology, the vehicle operation data of the motor vehicle and the driving state information of the driver are analyzed, the driver is reminded by sending the alarm signal to the motor vehicle when the vehicle state and the driving state of the driver are abnormal, and the abnormal state information is sent to the management terminal, so that the management terminal can conveniently remotely monitor the motor vehicle.
And the vehicle running data and the driving state information of the driver in the running process of the motor vehicle, which are collected by the data collection module, can be stored in the block chain, so that the possibility of tampering the driving data by a management background is avoided, and the driving data of the motor vehicle cannot be lost and is real and effective.
Drawings
Fig. 1 is a schematic structural diagram of a motor vehicle remote monitoring system based on a block chain technology according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a camera of a motor vehicle remote monitoring system based on a block chain technology according to an embodiment of the present invention.
Detailed Description
The following describes in more detail embodiments of the present invention with reference to the schematic drawings. The advantages and features of the present invention will become more apparent from the following description. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is provided for the purpose of facilitating and clearly illustrating embodiments of the present invention.
As shown in fig. 1, the present invention provides a motor vehicle remote monitoring system based on the block chain technology, which includes a data acquisition module 100, a data processing module 200, a wireless communication module 300, a block chain 400, and a remote monitoring platform 500.
The data acquisition module 100 is disposed on a motor vehicle and is configured to acquire vehicle operation data and driving state information of a driver during operation of the motor vehicle.
Specifically, in this embodiment, the data acquisition module 100 includes a tire pressure sensor, an engine sensor, an oil tank liquid level sensor, a water tank liquid level sensor, a battery voltage sensor, a speed sensor, a vehicle body collision sensor, a locator, and a camera 101.
The engine sensor is used for collecting engine vibration data, engine rotating speed data, engine temperature data and engine water temperature data. The vehicle body collision sensor is used for acquiring whether the vehicle body collides. The locator adopts big dipper locator or GPS locator for gather the geographical position data of motor vehicle. The camera 101 is used to capture a video image of the face of the driver.
In order to ensure that a clear video image of the face of the driver can be captured at night, in this embodiment, the camera 101 is a camera with night vision function. As shown in fig. 2, the camera 101 is adjustably mounted on a front windshield of the motor vehicle through a suction cup 102, and the camera 101 is connected with the suction cup 102 through a ball hinge seat 103, so that the shooting angle of the camera can be finely adjusted conveniently, and the whole face of a driver can be shot. The installation is convenient and fast through the sucker 102.
The data processing module 200 is configured to pre-process the vehicle operation data and the driving state information, and package the pre-processed vehicle operation data and the driving state information into blocks. In this embodiment, the data processing module 200 is an arm microprocessor.
Specifically, the data processing module 200 performs data integration on the vehicle operation data and the driving state information to obtain vehicle data. And integrating the vehicle operation data and the driving state information based on time to enable the vehicle operation data and the driving state information at a certain moment to be in one-to-one correspondence. And then, based on the block size requirements of time and a block chain, slicing the vehicle data to obtain vehicle data segments. And finally, packaging the vehicle data fragments into blocks. Because the block chain has a requirement on the size of the block file, vehicle data needs to be sliced to obtain vehicle data fragments, and the vehicle data fragments are packaged into blocks so as to meet the requirement of the block chain on the size of the block file.
The wireless communication module 300 uploads the blocks into a block chain. In this embodiment, the wireless communication module 300 may be a 4G module, a 5G module, and/or a WiFi module, and the wireless communication module 300 is disposed in a vehicle.
The remote monitoring platform 500 obtains the block from the block chain, processes the block to obtain the vehicle operation data and the driving state information, analyzes the working state of the motor vehicle according to the vehicle operation data and the driving state information to obtain an analysis result, and sends an alarm signal to the motor vehicle and sends abnormal state information to the management terminal if the analysis result is in an abnormal state.
Specifically, the vehicle operation data includes tire pressure data, engine operating data, oil tank liquid level data, water tank liquid level data, battery voltage data, vehicle speed data, collision state data, and vehicle positioning data. The driving state information includes a video image of the driver's face.
After the remote monitoring platform 500 is authorized, the blocks are downloaded from the block chain, and the vehicle operation data and the driving state information are acquired after decryption calculation processing.
And then, analyzing the running state of the motor vehicle according to the vehicle running data to obtain a first analysis result. The analysis process specifically comprises:
and if at least one of the tire pressure data, the engine working data, the oil tank liquid level data, the water tank liquid level data, the battery voltage data, the vehicle speed data or the collision state data is not in the corresponding set threshold value interval, judging that the motor vehicle is in an abnormal operation state.
And analyzing the driving state of the driver according to the driving state information to obtain a second analysis result. The analysis process specifically comprises:
carrying out image recognition on a video image of the face of a driver to obtain a recognition result, wherein the recognition result comprises the blinking frequency of the driver, the eye closing interval time, the eye closing time of each time and whether a yawning state occurs or not;
performing fatigue evaluation analysis according to the identification result, and outputting a second analysis result;
the second analysis conclusion includes three driver states, awake, tired and very tired.
In the embodiment, a fatigue identification model is adopted to carry out image identification on the video image of the face of the driver; the fatigue recognition model adopts a convolutional neural network algorithm, and is obtained by training a plurality of samples.
The blinking frequency, the eye closing interval time and the eye closing time of each time of a driver in different fatigue states are different, and people feel yawned when tired. When a driver is awake, the blinking frequency is low, the eye closing interval is long, the eye closing time of each time is short, and yawning is generally avoided or rarely avoided; when a driver is tired, the blinking frequency is high, the eye closing interval time is long, the eye closing time is long each time, the face is fatigued, and the phenomenon of yawning is easy to occur; when the driver is very tired, the blinking frequency is higher, the eye closing interval is longer, the eye closing time is longer each time, and the yawning frequency is higher. Therefore, the driving state of the driver can be obtained by acquiring the video image of the driver and analyzing the video image through image recognition.
In this embodiment, a comprehensive analysis result is obtained according to the first analysis result and the second analysis result. The analysis result comprises a normal state and an abnormal state, and the analysis result is in the normal state only when the motor vehicle is in the normal running state and the driver is in the waking state. If the motor vehicle is in an abnormal operation state or the driver is in a fatigue or very fatigue state, the abnormal states are all abnormal states.
If the analysis result is abnormal, the remote monitoring platform 500 sends an alarm signal to the motor vehicle, the motor vehicle is provided with an alarm device, the alarm device starts alarming after receiving the alarm signal, the alarm device comprises a display, a buzzer or an alarm lamp, the display is used for displaying abnormal state information, a driver can conveniently confirm the abnormality in time, and the buzzer or the alarm lamp reminds the driver of paying attention to the abnormality.
In addition, the remote monitoring platform 500 sends the abnormal state information to the management terminal. The driver fatigue state or the vehicle running state can be monitored by the manager conveniently, the vehicle running state can be monitored, the driver can be reminded through voice conversation, and the vehicle running state can be controlled before a safety accident happens.
In summary, in the motor vehicle remote monitoring system based on the block chain technology provided by the invention, by analyzing the vehicle operation data of the motor vehicle and the driving state information of the driver, when the vehicle state and the driving state of the driver are abnormal, the driver is reminded by sending an alarm signal to the motor vehicle, and the abnormal state information is sent to the management terminal, so that the management terminal can conveniently remotely monitor the motor vehicle.
And the vehicle running data and the driving state information of the driver in the running process of the motor vehicle, which are collected by the data collection module, can be stored in the block chain, so that the possibility of tampering the driving data by a management background is avoided, and the driving data of the motor vehicle cannot be lost and is real and effective.
The above description is only a preferred embodiment of the present invention, and does not limit the present invention in any way. It will be understood by those skilled in the art that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A motor vehicle remote monitoring system based on block chain technology is characterized in that: comprises a data acquisition module, a data processing module, a wireless communication module, a block chain and a remote monitoring platform, wherein,
the data acquisition module is arranged on a motor vehicle and is used for acquiring vehicle operation data and driving state information of a driver in the operation process of the motor vehicle;
the data processing module is used for preprocessing the vehicle operation data and the driving state information and packaging the preprocessed vehicle operation data and the driving state information into blocks;
the wireless communication module uploads the block into a block chain;
the remote monitoring platform acquires the block from the block chain, processes the block to acquire the vehicle operation data and the driving state information, analyzes the working state of the motor vehicle according to the vehicle operation data and the driving state information to obtain an analysis result, and sends an alarm signal to the motor vehicle and sends the abnormal state information to the management terminal if the analysis result is in an abnormal state.
2. A remote monitoring system for motor vehicles based on block chain technology as claimed in claim 1, wherein: the data acquisition module comprises a tire pressure sensor, an engine sensor, an oil tank liquid level sensor, a water tank liquid level sensor, a storage battery voltage sensor, a speed sensor, a vehicle body collision sensor, a positioner and a camera.
3. A remote monitoring system for motor vehicles based on block chain technology as claimed in claim 1, wherein: the camera is a camera with a night vision function;
the camera is adjustably mounted on a front windshield of the motor vehicle through a sucker, and is connected with the sucker through a spherical hinge seat.
4. The system according to claim 1, wherein the data processing module preprocesses the vehicle operation data and the driving state information, and specifically comprises:
performing data integration on the vehicle operation data and the driving state information to obtain vehicle data;
slicing the vehicle data based on the time and the block size requirement of the block chain to obtain a vehicle data fragment;
and packaging the vehicle data fragments into blocks.
5. The system according to claim 1, wherein the analyzing the operating status of the vehicle according to the vehicle operation data and the driving status information to obtain an analysis result comprises:
analyzing the running state of the motor vehicle according to the vehicle running data to obtain a first analysis result;
analyzing the driving state of the driver according to the driving state information to obtain a second analysis result;
and obtaining a comprehensive analysis result according to the first analysis result and the second analysis result.
6. The system of claim 5, wherein the vehicle operating data comprises tire pressure data, engine operating data, fuel tank level data, water tank level data, battery voltage data, vehicle speed data, crash state data, and vehicle positioning data.
7. The system according to claim 5, wherein the analyzing the operating status of the vehicle according to the vehicle operating data to obtain a first analysis result comprises:
and if at least one of the tire pressure data, the engine working data, the oil tank liquid level data, the water tank liquid level data, the battery voltage data, the vehicle speed data or the collision state data is not in the corresponding set threshold value interval, judging that the motor vehicle is in an abnormal operation state.
8. The remote monitoring system for motor vehicles based on blockchain technology as claimed in claim 5, wherein the driving status information includes a video image of the driver's face;
the analyzing the driving state of the driver according to the driving state information to obtain a second analysis result specifically includes:
carrying out image recognition on a video image of the face of a driver to obtain a recognition result, wherein the recognition result comprises the blinking frequency, the eye closing interval time, the eye closing duration of each time and whether a yawning state occurs or not of the driver;
performing fatigue evaluation analysis according to the identification result, and outputting a second analysis result;
the second analysis conclusion includes three driver states, awake, tired and very tired.
9. The remote monitoring system for motor vehicle based on blockchain technology as claimed in claim 8, wherein the image recognition of the video image of the driver's face is performed by using a fatigue recognition model;
the fatigue recognition model adopts a convolutional neural network algorithm, and is obtained by training a plurality of samples.
10. The remote monitoring system for motor vehicle based on block chain technology as claimed in claim 1, wherein the data processing module is an arm microprocessor; the wireless communication module is a 4G module, a 5G module and/or a WiFi module.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115802119A (en) * | 2022-11-15 | 2023-03-14 | 上海菱动信息科技有限公司 | Safety monitoring system based on block chain |
| CN117334066A (en) * | 2023-09-20 | 2024-01-02 | 广州亿胜鑫网络科技有限公司 | Risk analysis method, system, terminal and storage medium based on vehicle data |
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Application publication date: 20220930 |