Related papers: Virtual Breathalyzer
Alcohol-impaired driving remains a major yet preventable cause of road traffic injury and death, with many drivers underestimating their level of intoxication. Compared to in-vehicle systems, mobile drunk-driving detection using consumer…
Excess alcohol consumption leads to serious health risks and severe consequences for both individuals and their communities. To advocate for healthier drinking habits, we introduce a groundbreaking mobile smartwatch application approach to…
About 30% of all traffic crash fatalities in the United States involve drunk drivers, making the prevention of drunk driving paramount to vehicle safety in the US and other locations which have a high prevalence of driving while under the…
Excessive alcohol consumption causes disability and death. Digital interventions are promising means to promote behavioral change and thus prevent alcohol-related harm, especially in critical moments such as driving. This requires real-time…
The paper proposes a novel approach towards identification of alcohol and drug induced people, through the use of a wearable bracelet.As alcohol and drug induced human people are in an unconscious state of mind, they need external help from…
This paper presents a unique driving dataset collected in Nigeria via mobile phone sensors to support a machine learning model for detecting alcohol-influenced driving behaviours, with the long-term aim of integrating this model into a…
Integrating driver, in-cabin, and outside environment's contextual cues into the vehicle's decision making is the centerpiece of semi-automated vehicle safety. Multiple systems have been developed for providing context to the vehicle, which…
In this paper we propose a new algorithm for detecting if a person is under the influence of alcohol. This algorithm is based on number of pauses the speaker makes by judging that if the number of pauses compared to the previous recordings…
Phone sensors could be useful in assessing changes in gait that occur with alcohol consumption. This study determined (1) feasibility of collecting gait-related data during drinking occasions in the natural environment, and (2) how…
Numerous studies have established the necessity for developing safety equipment to detect drowsiness among vehicle drivers. However, for reliable implementations, such systems must employ dependable sources of stimuli; through…
The main objective of this work is to detect early if a driver shows symptoms of sleepiness that indicate that he/she is falling asleep and, in that case, generate an alert to wake him/her up. To solve this problem, an application has been…
The last decade's market has been characterized by wearable devices, mainly smartwatches, edge, and cloud computing. A possible application of these technologies is to improve the safety of dangerous activities, especially driving motor…
Since the number of cars has grown rapidly in recent years, driving safety draws more and more public attention. Drowsy driving is one of the biggest threatens to driving safety. Therefore, a simple but robust system that can detect drowsy…
A sleepy driver is arguably much more dangerous on the road than the one who is speeding as he is a victim of microsleeps. Automotive researchers and manufacturers are trying to curb this problem with several technological solutions that…
Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of "just-in-time" injury prevention interventions. We aimed to identify the salient features of gait that could be used for…
The increasing number of accidents caused by alcohol-impaired driving has prompted the development of integrated safety systems in vehicles to monitor driver behavior and prevent crashes. This paper explores how drivers perceive these…
Driver drowsiness has caused a large number of serious injuries and deaths on public roads and incurred billions of taxpayer dollars in costs. Hence, monitoring of drowsiness is critical to reduce this burden on society. This paper surveys…
Road crashes and related forms of accidents are a common cause of injury and death among the human population. According to 2015 data from the World Health Organization, road traffic injuries resulted in approximately 1.25 million deaths…
Automatic detection and tracking of emotional states has the potential for helping individuals with various mental health conditions. While previous studies have captured physiological signals using wearable devices in laboratory settings,…
Despite recent advances in automated driving technology, impaired driving continues to incur a high cost to society. In this paper, we present a driving dataset designed to support the study of two common forms of driver impairment: alcohol…