TY  - JOUR
PY  - 2023//
TI  - Non-intrusive drowsiness detection techniques and their application in detecting early dementia in older drivers
JO  - Lecture notes in networks and systems
A1  - Jan, Muhammad Tanveer
A1  - Hashemi, Ali
A1  - Jang, Jinwoo
A1  - Yang, Kwangsoo
A1  - Zhai, Jiannan
A1  - Newman, David
A1  - Tappen, Ruth
A1  - Furht, Borko
SP  - 776
EP  - 796
VL  - 560
IS  - V2
N2  - Proceedings of the Future Technologies Conference (FTC) 2022. Volume 2. Future Technologies Conference (7th : 2022 : Vancouver, B.C.; Online)    Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.<p />  <p>Language: en</p>
LA  - en
SN  - 2367-3370
UR  - http://dx.doi.org/10.1007/978-3-031-18458-1_53
ID  - ref1
ER  -