Electric vehicles are becoming a mode of transportation. Overall driver safety becomes a concern as traffic density rises and mishaps may occur due to causes such, as driving fatigue or falling asleep behind the wheel. This research introduces an ADAS tailored for electric vehicles incorporating smart seat belt detection real-time eye blink tracking to detect drowsiness and alcohol detection to prevent drunk driving. It can monitor the driver’s status. Limit vehicle control in critical situations while issuing warnings to both the driver and a remote monitoring station. Moreover it provides cloud-enabled data management for upkeep assessments of driver conduct and instantaneous monitoring. This enhances reaction accuracy by integrating safety protocols grounded in physiological aspects executed through AI-powered decision-making. IoT systems, instant alerts, cloud data handling and mobile enhancements would boost road safety by promoting driving effectiveness and supporting adherence, to regulations. This system will serve as a safety framework, for next-generation electric vehicles encouraging smart and accountable transportation characterized by greater automation and active safety measures.