Traffic accidents are often caused by drowsy drivers, which significantly reduce concentration, alertness, and reaction time while driving. This study aims to design and develop a web-based drowsiness detection system using a camera as the primary visual sensor. The system integrates digital image processing and artificial intelligence techniques to analyze the driver’s eye and mouth movements in real time with a high level of accuracy. When early signs of drowsiness are detected, the system provides an instant alert through a web-based interface that can be accessed both locally and remotely. Experimental results show that the system can detect drowsiness with 92% accuracy, an average response time of 1.2 seconds, and stable performance under various lighting and environmental conditions. The implementation of this system proves to be effective, reliable, and low-cost in preventing accidents caused by fatigue. Therefore, this innovative technology offers a practical, efficient, scalable, and affordable solution to enhance road safety and driver awareness for both private and commercial vehicles.