Citation

Hossen, Md. Ismail and Goh, Michael Kah Ong and Lau, Siong Hoe and Bari, Ahsanul and Connie, Tee (2019) Smartphone-Based Drivers Context Recognition. In: Intelligent Decision Technologies 2019. Smartphone-Based Drivers Context Recognition, 142 . Springer, Smart Innovation, Systems and Technologies, pp. 239-249. ISBN 978-981-13-8311-3

Text 274.pdf - Published Version Restricted to Repository staff only Download (10MB)

Abstract

Various embedded sensors such as accelerometer and gyroscope have opened a new horizon in the scientific studies. One of the most prevailing areas of research is context recognition which can be adopted for smartphone-based parking, road condition detection and sports. To the best of our knowledge, the existing context recognition research covers human’s basic contexts such as walking, jogging and are position dependent that require tightening sensors in fixed position of the body. Furthermore, none of the work has seen to be more specific to detect the contexts of driver. Therefore, to be more specific, in this study, we have constructed a position-independent approach to recognize driver’s contexts that occurs while a driver parks car or leaves from parking place. The support vector machine, random forest and decision tree are employed and the accuracies of 83.38, 93.71 and 98.41% are obtained, respectively.

Item Type:	Book Section
Uncontrolled Keywords:	Machine learning
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	20 Sep 2021 02:29
Last Modified:	20 Sep 2021 02:29
URII:	http://shdl.mmu.edu.my/id/eprint/8988

Downloads

Edit (login required)