Real-Time Drowsiness Detection and Health Status System in Agricultural Vehicles Using Artificial Intelligence

Beatriz Soares, Daniel Oliveira, Nuno Lau, Hélio Palaio, Olga Contente, Daniel Filipe Albuquerque, Daniel Marques

Abstract: 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.