CN210428777U - Anti-fatigue driving detection system - Google Patents
Anti-fatigue driving detection system Download PDFInfo
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- CN210428777U CN210428777U CN201921678334.9U CN201921678334U CN210428777U CN 210428777 U CN210428777 U CN 210428777U CN 201921678334 U CN201921678334 U CN 201921678334U CN 210428777 U CN210428777 U CN 210428777U
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Abstract
The utility model discloses a fatigue driving prevention detection system, which comprises a main control module, a power supply module, a detection module, a human-computer interaction module and an alarm module; the detection module acquires image information of a driver in real time and processes and judges whether the driver is in fatigue driving, when the driver is in fatigue driving, the detection module sends a fatigue driving signal to the main control module through serial port communication, the main control module converts the fatigue driving signal into an alarm signal and sends the alarm signal to the alarm module and controls the alarm module to give an alarm, and meanwhile, the main control module sends the fatigue driving signal and the image to the human-computer interaction module through serial port communication to display. The utility model discloses a prevent driver fatigue detecting system, system architecture is simple, and alarm range is big, disturbs for a short time, and real-time and the degree of accuracy are high, effectively avoids the serious consequence that driver fatigue probably brought.
Description
Technical Field
The utility model relates to a car driving technical field, in particular to prevent driver fatigue detecting system.
Background
At present, the domestic mature products for preventing fatigue driving comprise: when the user wears the alarm on the ear, the function is very simple, and the alarm can be given when the user lowers the head. The disadvantages of this product are: doze off and do not always need to lower head, wait for the head to alarm and estimate it is late; the watch type and the glasses type, the watch type estimates whether people are tired by using pulse beating, has no scientific basis of power and cannot solve the problem of sudden sleep, the glasses type forces a piece of thick glasses to judge the blinking frequency, basically, many people are not suitable, and the blinking frequency and the fatigue have no direct relation; the fatigue driving early warning system is a driving auxiliary early warning system based on a machine vision technology, can detect fatigue and distraction states of a driver in real time, and provides alarm information; there are also coffee drinks or stimulants that are given to the mouth, but this method has only a short duration of effect and is more tiring once time has elapsed. The detection system or the product has poor effect, or the detection effect is not ideal, or the cost is too high to obtain wide application. And for the more common anti-theft device, an alarm mode is adopted, the alarm range is smaller, and the noise of the alarm disturbs the public.
Disclosure of Invention
An object of the utility model is to provide a prevent driver fatigue detecting system, the system architecture is simple, and alarm range is big, disturbs for a short time, and the real-time and the degree of accuracy are high, effectively avoids the serious consequence that driver fatigue probably brought.
In order to achieve the purpose, the utility model provides a fatigue driving prevention detection system, which comprises a main control module, a power supply module, a detection module, a human-computer interaction module and an alarm module; the output end of the power supply module is electrically connected with the power supply input ends of the main control module, the detection module, the human-computer interaction module and the alarm module; the detection module acquires image information of a driver in real time and processes and judges whether the driver is in fatigue driving, when the driver is in fatigue driving, the detection module sends a fatigue driving signal to the main control module through serial port communication, the main control module converts the fatigue driving signal into an alarm signal and sends the alarm signal to the alarm module and controls the alarm module to give an alarm, and meanwhile, the main control module sends the fatigue driving signal and the image to the human-computer interaction module through serial port communication to display.
Preferably, in the above technical solution, the power supply module provides 5V direct current to the main control module, the detection module and the human-computer interaction module, respectively.
Preferably, in the above technical solution, the main control module is a microcontroller of which model is STM32F103C8T 6.
Preferably, in the above technical solution, the detection module includes a raspberry pi 3B, a camera module, and an OpenCV library; the camera module shoots images in real time and transmits the images to the raspberry pi 3B, the raspberry pi 3B is transplanted into an OpenCV image library based on a Linux operating system to complete processing of video images acquired by the camera module, and all processed information is output to the main control module to be converted and a control signal is sent.
Preferably, in the above technical solution, the camera module is an OV5647 camera.
Preferably, in the above technical solution, the human-computer interaction module is a USART HMI intelligent serial port screen module.
Preferably, in the above technical scheme, the alarm module is composed of an audible and visual alarm and a voice alarm, wherein a buzzer and an alarm lamp are arranged in the audible and visual alarm, and the voice alarm is a BY8301 voice module.
Compared with the prior art, the utility model discloses following beneficial effect has:
1. the utility model discloses a detection module adopts the raspberry group 3B + camera + OpenCV storehouse to carry out the detection of eyes and people's face, because the raspberry group 3B and OpenCV execution speed are very fast, and the analysis accuracy makes this system high to driver fatigue's detection reliability.
2. In the detection mode of the system, the eyes are detected on the basis of the detection of the face, fatigue driving can be judged if the face is detected but the eyes cannot be detected within 2S, dangerous driving can be judged if the face is not detected within 2S, normal driving can be judged only if the eyes are detected while the face is detected, and the detection method is scientific compared with other methods.
3. The main control module of the system selects a 32-bit processor (STM 32F103ZE chip) of an ARM framework core and a raspberry Pi 3B + module, the processing of images is faster, the number of frames is higher, the data processing speed returned by the sensor is faster, the efficiency is higher, and the power consumption is smaller.
4. When fatigue driving occurs in the system, the alarming information can be transmitted to surrounding vehicles through the technology of the Internet of things, the alarming range is large, and danger and noise interference are reduced to the minimum.
Drawings
FIG. 1 is a block diagram of a detection system according to the present invention;
FIG. 2 is a flow chart of a detection system according to the present invention;
fig. 3 is an alarm flow diagram of a detection system according to the present invention.
Description of the main reference numerals:
100-a main control module, 101-a power supply module, 102-a detection module, 103-a man-machine interaction module, 104-an alarm module and 105-surrounding vehicles.
Detailed Description
The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited by the following detailed description.
In order to make the technical problem, technical solution and advantageous effects to be solved by the present invention more clearly understood, the following description is given in conjunction with the accompanying drawings and embodiments to illustrate the present invention in further detail. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the invention.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meaning of the above terms in the present invention can be understood according to specific situations by those skilled in the art.
As shown in fig. 1, the fatigue driving prevention detection system of the present invention comprises a main control module 100, a power module 101, a detection module 102, a human-computer interaction module 103, and an alarm module 104; the output end of the power supply module 101 is electrically connected with the power supply input ends of the main control module 100, the detection module 102, the human-computer interaction module 103 and the alarm module 104, and is used for supplying 5V direct current to the main control module 100, the detection module 102 and the human-computer interaction module 103 and supplying 5V and 3.3V direct current to the alarm module 104 by the power supply module 101; more specifically, the power supply module 101 supplies 3.3V to the BY8301 voice module portion (buzzer) in the alarm module 104, and supplies 5V of direct current to the audible and visual alarm portion (alarm lamp). The detection module 102 acquires image information of a driver in real time, processes and judges whether the driver is in fatigue driving, sends a fatigue driving signal to the main control module 100 through serial port communication when the driver is in fatigue driving, the main control module 100 converts the fatigue driving signal into an alarm signal and sends the alarm signal to the alarm module 104 and controls the alarm module 104 to give an alarm, meanwhile, the main control module 100 sends the fatigue driving signal and the image to the human-computer interaction module 103 through serial port communication to be displayed, and an alarm signal mark is generated and displayed on the human-computer interaction module 103. In the present embodiment, both the control technology and the signal conversion technology of the main control module 100 are implemented by using common-knowledge technology.
Further, in this embodiment, the main control module 100 is a microcontroller of the model STM32F103C8T6, and is configured to process information sent back by the detection module and communicate with the human-computer interaction module 103 and the alarm module 104. Preferably, the main control module 100, the detection module 102 and the human-computer interaction module 103 are connected in a serial communication manner by signal transmission.
Further, in this embodiment, the raspberry pi 3B + module selected by the detection module 102 is an OV5647 camera that additionally adds a raspberry pi original package to a raspberry pi by using a raspberry pi 3B + system, and then introduces an OpenCV library through python to realize detection of a human face and closed eyes. More specifically, the camera shoots images in real time and transmits the images to the raspberry pi 3B + module; the raspberry pi 3B + mainly performs image processing, wherein the processed image information includes extracted face features, eye opening and closing angle features, mouth opening and closing frequency features, and the like of a face, and is transplanted into an OpenCV image library based on a Linux operating system, so that basic preprocessing of the acquired video image is completed, driving information features are extracted, and all processed information is output to the main control module 100 to be converted and send control signals.
Further, in this embodiment, the human-computer interaction module 103 is a USART HMI intelligent serial screen module, which is used to implement some operations of the system by the driver and display the current state of the system.
Further, in this embodiment, the alarm module 104 is composed of an audible and visual alarm and a voice alarm, wherein a buzzer and an alarm lamp are provided in the audible and visual alarm, and a BY8301 voice module is adopted in the voice alarm, so that the two alarms can play a better warning and prompting role, and meanwhile, the alarm information can be transmitted to the surrounding vehicles 105 through the internet of things communication technology.
The utility model discloses the flow of work is shown as fig. 2 and fig. 3, specifically as follows:
1. when the automobile is started, initializing each module;
2. the method comprises the following steps that an automobile starts to run, a camera captures (acquires) a facial image of a driver, and a detection module processes the image and judges whether fatigue driving occurs or not;
3. when fatigue driving is judged, an alarm signal is sent to the main control module through serial port communication, the main control module converts the signal and transmits the signal to the buzzer and the alarm lamp of the alarm module, the buzzer and the alarm lamp are controlled to give an alarm, and the signal is transmitted to surrounding vehicles 105 through the Internet of things to remind neighboring vehicles of reasonably avoiding fatigue driving vehicles; meanwhile, the main control module is in serial port communication and sends fatigue driving image information and warning marks to the man-machine interaction module, and the driver and the passengers are reminded by utilizing voice and video images.
In the embodiment, the camera captures (acquires) a facial image of the driver, and the detection module processes the image to judge whether fatigue driving occurs; the method specifically comprises the steps of detecting and processing human eyes and human faces by using a raspberry pi 3B + a camera + an OpenCV library, and judging whether fatigue driving is caused, for example, fatigue driving can be judged if the human faces are detected but the eyes cannot be detected within 2S; if the human face is not detected within 2S, dangerous driving can be judged, eyes are detected while the human face is detected, and normal driving can be judged at the moment.
To sum up, the utility model discloses a detection module adopts raspberry group 3B + camera + OpenCV storehouse to carry out the detection of eyes and people's face, because raspberry group 3B and OpenCV execution speed are very fast, and the analysis is accurate makes this system high to driver fatigue's detection reliability. In the detection mode of the system, the eyes are detected on the basis of the detection of the face, fatigue driving can be judged if the face is detected but the eyes cannot be detected within 2S, dangerous driving can be judged if the face is not detected within 2S, normal driving can be judged only if the eyes are detected while the face is detected, and the detection method is scientific compared with other methods. In addition, the main control module adopts a 32-bit processor (STM 32F103ZE chip) of an ARM framework core and a raspberry Pi 3B + module, so that the image is processed more quickly, the frame number is higher, the data returned by the sensor is processed more quickly, the efficiency is higher, and the power consumption is lower. And when the vehicle is in fatigue driving, alarm information can be transmitted to surrounding vehicles through the technology of the Internet of things, so that the danger is reduced to the minimum.
The component types, structures, shapes, connection relationships, operation principles and control principles (control software and detection software) which are not described in the specification are all realized by the prior art, and belong to the common general knowledge.
The foregoing descriptions of specific exemplary embodiments of the present invention have been presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the invention and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the invention and various alternatives and modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.
Claims (7)
1. A fatigue driving prevention detection system is characterized by comprising a main control module, a power supply module, a detection module, a human-computer interaction module and an alarm module;
the output end of the power supply module is electrically connected with the power supply input ends of the main control module, the detection module, the human-computer interaction module and the alarm module;
the detection module acquires image information of a driver in real time and processes and judges whether the driver is in fatigue driving, when the driver is in fatigue driving, the detection module sends a fatigue driving signal to the main control module through serial port communication, the main control module converts the fatigue driving signal into an alarm signal and sends the alarm signal to the alarm module and controls the alarm module to give an alarm, and the main control module sends the fatigue driving signal and the image to the human-computer interaction module through serial port communication to display.
2. The fatigue driving prevention detection system of claim 1, wherein the power module provides 5V dc to the main control module, the detection module, and the human-computer interaction module, respectively.
3. The anti-fatigue driving detection system of claim 1, wherein the master control module is a microcontroller of type STM32F103C8T 6.
4. The fatigue driving prevention detection system of claim 1, wherein the detection module comprises a raspberry pi 3B, a camera module, and an OpenCV library;
the camera module shoots images in real time and transmits the images to the raspberry pi 3B, the raspberry pi 3B is transplanted into an OpenCV image library based on a Linux operating system to complete processing of video images acquired by the camera module, and all processed information is output to the main control module to be converted and a control signal is sent.
5. The anti-fatigue driving detection system of claim 4, wherein the camera module is an OV5647 camera.
6. The fatigue driving prevention detection system of claim 1, wherein the human-computer interaction module is a USART HMI smart serial screen module.
7. The fatigue driving prevention detection system according to claim 1, wherein the alarm module is composed of an audible and visual alarm in which a buzzer and an alarm lamp are disposed, and a voice alarm is a BY8301 voice module.
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| CN201921678334.9U CN210428777U (en) | 2019-10-09 | 2019-10-09 | Anti-fatigue driving detection system |
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| CN201921678334.9U CN210428777U (en) | 2019-10-09 | 2019-10-09 | Anti-fatigue driving detection system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113421402A (en) * | 2021-06-07 | 2021-09-21 | 上海大学 | Passenger body temperature and fatigue driving behavior detection system and method based on infrared camera |
| CN116030595A (en) * | 2021-10-26 | 2023-04-28 | 上海擎感智能科技有限公司 | Fatigue driving warning method, device and system |
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2019
- 2019-10-09 CN CN201921678334.9U patent/CN210428777U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113421402A (en) * | 2021-06-07 | 2021-09-21 | 上海大学 | Passenger body temperature and fatigue driving behavior detection system and method based on infrared camera |
| CN116030595A (en) * | 2021-10-26 | 2023-04-28 | 上海擎感智能科技有限公司 | Fatigue driving warning method, device and system |
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Granted publication date: 20200428 Termination date: 20201009 |