Conference Name: Korean Institute of Communications and Information Sciences (KICS Winter 2024) Conference
Abstract: Worldwide, road accidents are a significant issue,
primarily affecting Middle and Lower-Middle-Class countries,
where human errors are responsible for approximately 90% of
these accidents. This research focuses on training a lightweight
Mobilenet version 2 architecture variant known as Faster Object
More Object (FOMO) for truck driver monitoring system that
utilizes a camera to capture the driver unsafe driving behaviours
while driving. Mobilenet V2 model variant (FOMO) has been
trained and tested on a publicly available image driver dataset
from Kaggle and so far has recorded an accuracy of 91.4% and
has been embedded into ESP32 AI Thinker in form of Arduino
code.
Status: Accepted
Conference Type: Domestic
Cite: Odinachi Udemezuo Nwankwo, Dong Seong Kim and Jae-Min Lee,"ESP32-Based Distracted Truck Driver Monitoring System using FOMO", KICS 2024 Winter Conference, Yong Pyong Resort, Pyeongchang, January 31-February 2, 2024