VISIONGUARD- Object Detection in Adverse Weather Conditions with Health Monitoring

Driving in bad weather like rain, fog, or low light often makes it hard for traditional vehicle detection systems to work effectively. To tackle this, we introduce VisionGuard—a smart solution that combines advanced object detection with real-time driver health and drowsiness monitoring. Powered by YOLOv8 and trained with the ACDC dataset, it’s built to handle tough visual conditions. It also uses ultrasonic and infrared sensors to improve how it sees the environment. On the inside, it tracks vital signs like heart rate, oxygen levels, and body temperature through wearable sensors, while keeping an eye on signs of fatigue using facial landmarks and blink detection. With over 95% detection accuracy, VisionGuard brings together deep learning, sensor fusion, and health monitoring into one system—making roads safer by looking out for both what’s outside the vehicle and how the driver is doing. Keywords— Autonomous Vehicles, Object Detection, YOLOv8, Deep Learning, Health Monitoring, Drowsiness Detection, Sensor Fusion, Adverse Weather.