Driver drowsiness remains one of the leading causes of traffic accidents, with early detection being critical to ensuring road safety. While EEG-based methods are effective at detecting cognitive fatigue, their practical use in vehicles is hindered by complexity and intrusiveness. In this presentation, we will explore the potential of Neumo’s Neuro-Bio Monitor (NBM)—a non-contact brain signal sensor—to detect driver drowsiness unobtrusively and in real-time. Neumo’s NBM running a drowsiness detection algorithm was evaluated in a driving simulator environment against established methods, including the eyelid closure ratio (PERCLOS) and the Karolinska Sleepiness Scale (KSS). Participants completed simulated night-driving sessions, with NBM signals recorded alongside conventional indicators. We will present the study highlights, showing the NBM’s ability to capture subtle cognitive changes associated with fatigue, offering the potential to identify drowsiness significantly earlier than camera-based perception systems. The findings underscore the promise of brain-signal sensing as a next-generation solution for proactive driver safety.