Chauffeur's Distraction and inattention recognition
Chauffer distraction and fatigue is the cause of many accidents and injuries. Many people lost their lives due to distracted driving. Majority of these accidents are caused because of the distraction of the driver. Lack of sleep or distractions like the phone call, talking with the passenger, eating
2025-06-28 16:30:47 - Adil Khan
Chauffeur's Distraction and inattention recognition
Project Area of Specialization RoboticsProject SummaryChauffer distraction and fatigue is the cause of many accidents and injuries. Many people lost their lives due to distracted driving. Majority of these accidents are caused because of the distraction of the driver. Lack of sleep or distractions like the phone call, talking with the passenger, eating food in the car, and drowsiness may lead to an accident. In this, we present a system for detecting states of distraction in chauffer during daylight hours using machine vision techniques, which is based on the image segmentation of the eyes as well as the mouth of a person, with a front face view camera. Segmentation states of motion of the mouth and head are established, thus allowing to infer the corresponding state of distraction. Images are extracted from short videos and image processing techniques.
Project ObjectivesOur proposed method is to design and develop a system, which is based on an embedded platform for chauffer distraction detection. The method combines eye movement, head movement, and mouth movement to detect the distraction. The objective is to overcome the problem related to the accidents and chauffer experiencing fatigue leads to need arises to design a system that keeps the chauffer focus on the road.
Project Implementation MethodPhase-I
First of all, we fix the front-facing camera on the dashboard of the car.
Phase-II
In the second phase, we capture a video by which the chauffer distractions states has been captured.
Phase-III
Convert the video in the frames in the form of images for getting a result more accurately.
Phase-IV
We classify the type of distractions of the chauffeur, collect them all and proceed to the next step.
Phase-V
If any type of distraction will be found then the alarm system will alert the chauffeur.
Phase-IV
If the driver does not respond on that alarm so the state of that driver will be captured and send it in the server where through the website all the data will be display.
The whole focus and concentration on accurately monitoring the open and closed state of the driver’s eye and detecting other distraction. To resolve the problem related to the cause of the accident due to drivers experiencing fatigue leads to needing arises to design a system that keeps the driver focus on the road.
Technical Details of Final DeliverableWe will use any classifier after detection the distraction, it can give warning/alarm to chauffer so that he can take some corrective measure.
we will need a system that analyzes the chauffer and his remedy.
Final Deliverable of the Project HW/SW integrated systemType of Industry IT Technologies RoboticsSustainable Development Goals Good Health and Well-Being for People, Life on LandRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 56300 | |||
| Dash-Cam | Equipment | 1 | 30000 | 30000 |
| Car alarm - speaker | Equipment | 1 | 5000 | 5000 |
| Raspberry pi 3 b+ | Equipment | 2 | 8000 | 16000 |
| Vibration Sensor | Equipment | 2 | 900 | 1800 |
| Wires/ Connectors | Equipment | 15 | 70 | 1050 |
| SRS | Miscellaneous | 5 | 120 | 600 |
| Reports | Miscellaneous | 4 | 100 | 400 |
| SDS | Miscellaneous | 5 | 120 | 600 |
| Other printings | Miscellaneous | 30 | 20 | 600 |
| Files | Miscellaneous | 10 | 25 | 250 |