This study presents a real-time driver safety system that integrates drowsiness detection, alcohol impairment prevention, and truck load monitoring. The system employs an Eye Aspect Ratio (EAR) algorithm to detect driver fatigue by analyzing eye movement patterns, triggering alerts when drowsiness is detected. Additionally, an alcohol sensor prevents vehicle ignition if alcohol is detected, and load cell sensors monitor truck weight to prevent overloading. A GSM-based alert mechanism enhances communication by sending real-time alerts. The system aims to reduce road accidents by integrating these technologies into an intelligent safety framework. Experimental results demonstrate the effectiveness of the system in enhancing road safety.