TY  - JOUR
PY  - 2024//
TI  - Real-time drowsiness detection and health status system in agricultural vehicles using artificial intelligence
JO  - Lecture notes in networks and systems
A1  - Soares, Beatriz
A1  - Oliveira, Daniel
A1  - Lau, Nuno
A1  - Palaio, Helio
A1  - Contente, Olga
A1  - Albuquerque, Daniel
A1  - Marques, Daniel
A1  - Marques, Lino
A1  - Santos, Cristina
A1  - Lima, José Luís
A1  - Tardioli, Danilo
A1  - Ferre, Manuel
SP  - 336
EP  - 347
VL  - 978
IS  - 
N2  - Robot 2023: Sixth Iberian Robotics Conference    This study presents a real-time monitoring system for preventing accidents in agricultural vehicles by monitoring the farmer and driving conditions. The system employs vital signals monitoring, using a bracelet to assess the farmer's health status, and drowsiness detection, utilizing a camera and Artificial Intelligence to evaluate the level of drowsiness. In emergencies, the system communicates with a central station to identify the triggering factor. Driving conditions are monitored using inertial and GPS data. The focus of this paper is on the farmer's monitoring aspect. Health status is determined by analyzing Heart Rate and Oxygen Saturation values measured by the bracelet. While currently measuring two values, the system is designed to accommodate additional measurements. Multiple algorithms for driver drowsiness detection were tested, highlighting the need to consider different approaches in the final solution. This research proposes an integrated system to enhance safety and prevent accidents in agricultural vehicles, addressing the specific requirements of the farming industry.<p />  <p>Language: en</p>
LA  - en
SN  - 2367-3370
UR  - http://dx.doi.org/10.1007/978-3-031-59167-9_28
ID  - ref1
ER  -