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2018-12-11, Week 50
Program with Papers
Plenary Session
Tutorial Session

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Title : Driving behavior analysis by using smartphone sensors and its applications.
Time :
Speaker : Prof. Ha-Nam Nguyen, PhD. Vice president of ITI-VNU, Vietnam
Ha-Nam Nguyen has been a Vice president of Information Technology Institute (ITI), Vietnam national University in Hanoi (VNU) since 2017, an associate professor at Department of Information Systems in University of Engineering and Technology (VNU-UET) since 2011, a Senior Lecturer in Data Mining, Statistical Machine Learning, and Database at VNU-UET since 2007. He received his BSc in Information Technology from VNU-Hanoi University of Science and Technology (HUST) in 1998, MSc in Computer Science from Chungwoon University (CWU), Korea in 2003, and PhD in Software Applications from Korea Aerospace University (KAU), Korea in 2007. He interested in financial risk analysis, behavior analysis, developing information systems and maritime logistics/transport using techniques from data analysis, modelling, and software engineering. He has involve in several industrial projects collaborated with Hitachi, Panasonic and Samsung as well as international grants like Newton fund, Horizon 2020 – Research and Innovation Framework Programme

Abstract : Nowadays, driving assistance and road safety are critical issues in all countries around the world. According to the global status report on road safety 2015 by World health organization (WHO), road accidents are worldwide top ten causes of death, killing more than 1.2 million of people per year. The road traffic fatality rates are especially high in the low-income and middle-income countries. In fact, there are numerous factors possibly causing road accidents. Nonetheless, assisting and providing safety awareness for drivers during their trips is an effective approach to preventing such accidents. Furthermore, the document also shows that approximately a quarter of all road traffic deaths involve in motorcyclists. However, very few existing works provide driving assistance and safety awareness for motorcyclists. Nonetheless, there are certain limitations in such works. Recently, researchers have paid a lot of attention to study various methods of providing assistance and safety awareness to drivers. Indeed, such works primarily fall into the following categories: recognizing vehicle mode (car, bus, train, bike, walking...), identifying driving styles (normal, aggressive, drunken, fatigue, drowsy, inattentive...), detecting normal/abnormal driving events (moving, stopping, turning left, turning right, weaving, sudden braking, fast u-turn...), accident detection, estimating energy consumption and pollution, monitoring road and traffic condition. In this talk, we would like to present our study on developing a driving behavior detection system in order to automatically warn by sound, text message or call in emergency cases. We proposed an android application that can detect an abnormal behaviors based on analyzing the sequence of primitive activities of driver(i.e. stopping, going straight, turning left, turning right). Our proposed method was achieved promising results with onboard sensors of smartphone.

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