Abstract More than 60 percentage of fatal accidents while riding a bicycle is caused by elderly people over 65 years old. The main cause is the detection delay of approaching vehicle caused by the decrease of cognitive function due to aging. In this paper, we propose an approaching vehicle detection method using a smartphone aiming to support bicycle operation to prevent elderly people from fatal accidents while riding a bicycle vehicle. Among various sensors embedded in a smartphone, we focus on microphone as the most suitable sensor for detecting an approaching vehicle. We collected sound data in a real environment and created an approaching vehicle detection model by using machine learning. Finally, as a result of accuracy evaluation wit...
Deaf cyclists do not receive acoustic warnings of motor vehicles approaching from behind. This can b...
The project aims to detect rear approaching vehicles for cycslist with a low power consumption. Stud...
Every day around the world, a large percentage of people die from traffic accident injuries. An effe...
Cycling is an efficient mode of travel widely used for transport, recreation and sport all over the ...
The increase of smartphones over the past decade has contributed to distraction in traffic. However,...
When a cyclist is cycling on a suburban road, it’s a problem to notice fast rear approaching vehicle...
Detecting users' transportation state based on wearable sensors in general and smartphones in partic...
The manner in which people use bicycles has changed very little since their invention in 1817. In th...
Thanks to the development in recent years, the placement of miniaturized sensors such as acceleromet...
It is estimated that over half of bicycle crashes are not reported. There are various reasons for th...
The purpose of this study was to determine the effect of a device called the Bicycle Safety Device (...
Elderly activity detection is one of the significant applications in machine learning. A supportive ...
This final year project report presents two separate Human Activity Recognition (HAR) systems for mo...
Smartphones are everywhere, and they are a very attractive platform to perform unobtrusive monitori...
Abstract—Due to safety reasons, using mobile phones while driving is prohibited in many countries. R...
Deaf cyclists do not receive acoustic warnings of motor vehicles approaching from behind. This can b...
The project aims to detect rear approaching vehicles for cycslist with a low power consumption. Stud...
Every day around the world, a large percentage of people die from traffic accident injuries. An effe...
Cycling is an efficient mode of travel widely used for transport, recreation and sport all over the ...
The increase of smartphones over the past decade has contributed to distraction in traffic. However,...
When a cyclist is cycling on a suburban road, it’s a problem to notice fast rear approaching vehicle...
Detecting users' transportation state based on wearable sensors in general and smartphones in partic...
The manner in which people use bicycles has changed very little since their invention in 1817. In th...
Thanks to the development in recent years, the placement of miniaturized sensors such as acceleromet...
It is estimated that over half of bicycle crashes are not reported. There are various reasons for th...
The purpose of this study was to determine the effect of a device called the Bicycle Safety Device (...
Elderly activity detection is one of the significant applications in machine learning. A supportive ...
This final year project report presents two separate Human Activity Recognition (HAR) systems for mo...
Smartphones are everywhere, and they are a very attractive platform to perform unobtrusive monitori...
Abstract—Due to safety reasons, using mobile phones while driving is prohibited in many countries. R...
Deaf cyclists do not receive acoustic warnings of motor vehicles approaching from behind. This can b...
The project aims to detect rear approaching vehicles for cycslist with a low power consumption. Stud...
Every day around the world, a large percentage of people die from traffic accident injuries. An effe...