Urban Disaster Monitor: AI-powered computer vision app using YOLOv11 to detect and classify civilians, rescuers, and animals in urban disaster scenarios.

Gamified safety education platform for urban residents. Uses Toronto Police crime data and Street View to provide interactive neighborhood risk assessment. Helps users learn street smarts through competitive gameplay by turning safety education into data-driven gaming.

Cyclist safety risk assessment application for Austin using Random Forest classification with SMOTE for class balancing. Interactive Streamlit web app predicts cycling incident severity based on time, location, and environmental conditions to promote safer cycling practices.