Composition-first analytics for daily screen time. Computes the Digital Balance Index (DBI) using normalized entropy, plus dominance, tiers, and a “high-load & skewed” flag. Exports scored rows, segment summaries, daily trends, and figures, and ships a Streamlit dashboard to explore patterns by age group, primary device, and internet type.

Digital habits → wellbeing risk (binary): calibrated risk scoring + cost-aware thresholding with deployable artifacts (LogReg/RF/XGBoost).

The goal of this project is to develop a predictive model that analyzes children's physical activity and fitness data to identify early signs of problematic internet use. Identifying these patterns can help trigger interventions to encourage healthier digital habits.

Parasocial Reflection is an experimental tool for exploring human–AI interaction patterns. It highlights linguistic and behavioral signals in conversations to encourage self-reflection and balanced engagement with conversational AI.

📊 Analyze children's activity data to predict and address problematic internet use, fostering healthier digital habits through early intervention.