Developed CrowdVision, an AI-powered real-time crowd monitoring system using YOLOv8 and OpenCV. Achieved 95%+ accuracy at 30+ FPS with zone-based alerts. Built a Flask dashboard with live feeds, heatmaps, and Firebase integration for authentication, data sync, and user management.

Created a real-time driver drowsiness detection system with ESP32, IR eye-blink sensors, and an accelerometer. Integrated Firebase for live storage, multi-driver monitoring, and remote authority access. Added automated email alerts for prolonged drowsiness to enhance road safety and proactive accident prevention.

Implemented an HR analytics platform using Python, ML models, and Streamlit dashboards to analyze employee data, visualize attrition trends, and predict churn. Helps organizations identify at-risk employees and improve retention strategies through actionable, data-driven insights.

Built an Android application in Java for real-time school bus tracking. Integrated Firebase Realtime Database for live updates accessible to parents and administrators. Designed a user-friendly map interface showing bus location, route details, and estimated arrival times.