Design of a System for Driver Drowsiness Detection and Seat Belt Monitoring Using Raspberry Pi 4 and Arduino Nano.

This research explores the design of a system for monitoring driver drowsiness and supervising seat belt usage in interprovincial buses. In Peru, road accidents involving long-distance bus transportation amounted to 5449 in 2022, and the human factor plays a significant role. It is essential to understand how the use of non-invasive sensors for monitoring and supervising passengers and drivers can enhance safety in interprovincial transportation. The objective of this research is to develop a system using a Raspberry Pi 4 and Arduino Nano that allows for the storage of monitoring data. To achieve this, a conventional camera and MediaPipe were used for driver drowsiness detection, while passenger supervision was carried out using a combination of commercially available sensors as well as custom-built sensors. RS485 communication was utilized to store data related to both the driver and passengers. The simulations conducted demonstrate a high level of reliability in detecting driver drowsiness under specific conditions and the correct operation of the sensors for passenger supervision. Therefore, the proposed system is feasible and can be implemented for real-world testing. The implications of this research suggest that the system's cost is not a barrier to its implementation, thus contributing to improved safety in interprovincial transportation. [ABSTRACT FROM AUTHOR]