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A Mobile-Based Fatigue Driving Detection & Alarm System

DEPARTMENT:

Department of Computer Science

PRODUCER:

CHEUNG, Yiu-ming

PROJECT YEAR:

2016

LENGTH:

4 Minutes

VIDEO TYPE:

Other Videos

According to the statistics from the US Government's report in 2014, 31% of fatal traffic accidents are due to fatigue driving. However, unlike drink driving, there are no laws regulating driver fatigue. In view of this, Prof Cheung Yiu-ming of the Department of Computer Science and his team have developed a highly reliable and efficient system, which requires only a smart phone to operate.

Professor Cheung says, "This invention only requires a smart mobile device and a device holder to fix the smart phone in the car. Once the smart phone is fixed and open our application installed in the phone, and make sure that the driver's face can be seen from the front camera with the angle falling between ±30 degrees while driving, the system will make real-time tracking for fatigue-driving detection and the alarm will be raised as soon as fatigue driving is detected. There are two ways to turn off the alarm by either voice command or screen-touch by the driver whereby waking the driver up."

Using an eye-tracking technology, our system analyses driver's facial expression in real-time by the smart phone's camera. The alarm will automatically set off to alert the driver when symptoms of drowsiness manifest themselves.

A Mobile-Based Fatigue Driving Detection & Alarm System

部門:

計算機科學系

影片提供:

CHEUNG, Yiu-ming

項目年份:

2016

影片長度:

4 分鐘

影片類型:

其他影片

According to the statistics from the US Government's report in 2014, 31% of fatal traffic accidents are due to fatigue driving. However, unlike drink driving, there are no laws regulating driver fatigue. In view of this, Prof Cheung Yiu-ming of the Department of Computer Science and his team have developed a highly reliable and efficient system, which requires only a smart phone to operate.

Professor Cheung says, "This invention only requires a smart mobile device and a device holder to fix the smart phone in the car. Once the smart phone is fixed and open our application installed in the phone, and make sure that the driver's face can be seen from the front camera with the angle falling between ±30 degrees while driving, the system will make real-time tracking for fatigue-driving detection and the alarm will be raised as soon as fatigue driving is detected. There are two ways to turn off the alarm by either voice command or screen-touch by the driver whereby waking the driver up."

Using an eye-tracking technology, our system analyses driver's facial expression in real-time by the smart phone's camera. The alarm will automatically set off to alert the driver when symptoms of drowsiness manifest themselves.

A Mobile-Based Fatigue Driving Detection & Alarm System

部门:

计算机科学系

影片提供:

CHEUNG, Yiu-ming

项目年份:

2016

影片长度:

4 分钟

影片类型:

其他影片

According to the statistics from the US Government's report in 2014, 31% of fatal traffic accidents are due to fatigue driving. However, unlike drink driving, there are no laws regulating driver fatigue. In view of this, Prof Cheung Yiu-ming of the Department of Computer Science and his team have developed a highly reliable and efficient system, which requires only a smart phone to operate.

Professor Cheung says, "This invention only requires a smart mobile device and a device holder to fix the smart phone in the car. Once the smart phone is fixed and open our application installed in the phone, and make sure that the driver's face can be seen from the front camera with the angle falling between ±30 degrees while driving, the system will make real-time tracking for fatigue-driving detection and the alarm will be raised as soon as fatigue driving is detected. There are two ways to turn off the alarm by either voice command or screen-touch by the driver whereby waking the driver up."

Using an eye-tracking technology, our system analyses driver's facial expression in real-time by the smart phone's camera. The alarm will automatically set off to alert the driver when symptoms of drowsiness manifest themselves.

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