The fatigue-related accident is increasing due to long work hours, medical reasons, and age that decrease response time in a moment of hazard. One of drowsiness and fatigue visual indicators is excessive yawning, redness of eyes and blinking of eyes. In this project we are using a dash cam th
Drowsy State Prediction of Driver
| The fatigue-related accident is increasing due to long work hours, medical reasons, and age that decrease response time in a moment of hazard. One of drowsiness and fatigue visual indicators is excessive yawning, redness of eyes and blinking of eyes. In this project we are using a dash cam that is used to record driving scenarios and imitates real-life driving situations. We are using image processing and machine learning techniques to detect drowsiness using three parameters yawning, redness of eye and blinking pattern. Also using enhancing, the frames by using different filters in MATLAB. . We can classify the drivers' fatigue into three levels, alert, early fatigue and fatigue based on the judgment of the number of yawns and other parameters. Alert level means when the driver is not yawning, while, early fatigue is when the driver yawns once in a minute, or have slightly red eyes. Fatigued is when the driver yawns more than once in a minute, eyes are red or slow blinking. An overall decision is made by analyzing the source score and the condition of the driver's fatigue state. |
The fatigue-related accident is increasing due to long work hours, medical reasons, and age that decrease response time in a moment of hazard. One of drowsiness and fatigue visual indicators is excessive yawning, redness of eyes and blinking of eyes.
In this project we are using a dash cam that is used to record driving scenarios and imitates real-life driving situations. We are using image processing and machine learning techniques to detect drowsiness using three parameters yawning, redness of eye and blinking pattern. Also using enhancing, the frames by using different filters in MATLAB.
. We can classify the drivers' fatigue into three levels, alert, early fatigue and fatigue based on the judgment of the number of yawns and other parameters. Alert level means when the driver is not yawning, while, early fatigue is when the driver yawns once in a minute, or have slightly red eyes. Fatigued is when the driver yawns more than once in a minute, eyes are red or slow blinking. An overall decision is made by analyzing the source score and the condition of the driver's fatigue state.
We have done a vast survey of traffic conditions and streamlined our project around drivers who usually due to sleep and drowsiness get themselves into fatal accident. We have decided to follow the following steps into completion of our project:
5. Test and deploy a final system
Our proposed system will use includes camera placed and attached on front of driving seat, when driver will activate the camera, it will start capturing video. Frames will be extracted from the video. Then system will extract feature and assess threat based on certain parameters like driver's yawn, continuous eye blinking and eye redness, on detecting all the parameters the system will generate an alarm sending an alert to the driver. We
These are the function of the system.
| Elapsed time in (days or weeks or month or quarter) since start of the project | Milestone | Deliverable |
|---|---|---|
| Month 1 | Project Idea | Presentation |
| Month 2 | Feasibility study | Research and documentation |
| Month 3 | Meeting with Supervisor | Progress Report |
| Month 4 | Proposal Submission and Defense | Documentation and Presentation |
| Month 5 | SRS Document | Documentation |
| Month 6 | Designing | Design Document |
| Month 7 | Implementation | Working System and Demo |
| Month 8 | FYP submission | Final Presentation and Documentation |
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