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 th
2025-06-28 16:32:13 - Adil Khan
Drowsy State Prediction of Driver
Project Area of Specialization Artificial IntelligenceProject Summary| 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.
Project Objectives- Reducing Accident due to drowsiness
- Ensure safety and security of a driver
- Help maintain Law and order
- Safe and Secure traffic
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:
- Construct a database containing images of drowsiness, redness and Yawning
- Organize a USB camera to be adjusted at the frontal location of a driving seat
- Develop a sleep detection and recognition algorithms
- Develop a image matching algorithms
5. Test and deploy a final system
Benefits of the Project- Our proposed system will incorporate yawning feature along with the eye state analysis to determine the fatigue level of driver in real time. It is very important as it can be a life saving system.
- Moreover it can help maintain highway police officials to maintain law and order and ensure security and safety of a driver and other traffic during night and busy hours of the day.
- This system can help improve tourism and road trips within the country.
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.
- Initialized system.
- Capture video
- Extract frames
- Extract features
- Match from Database
- Generate Alarm
| 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 |