Estimation of driver alertness using low-cost wearable devices

Abstract

Operator tiredness and fatigue pose significant safety risks in industries such as mining, trucking, aviation and air traffic control. Fatigue is a major factor behind on-the-job accidents, absenteeism and lowered productivity. The detection and prediction of fatigue is a technical challenge, confounded by the practical constraints of the working environment. This paper presents a mathematical fatigue model using low cost wearable biosensors, customized for each individual participant. The circadian rhythm mathematical model is the major part of fatigue model core. Heart rate and skin temperature, which are known circadian pacemakers, are used to build the proposed mathematical model. The customization and adaptation of the circadian is expected to improve the fatigue model and make it more accurate in the context of individuality and adaptation to the time of day and the activity at hand. Using low-cost, non-intrusive and portable biosensors allows the model to be tested in real working conditions with minimal impact on the operators. In addition to presenting a mathematical model for the customized circadian, this paper presents some preliminary results from a limited experiment, with some promising results.