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[IEEE Research paper + Project] Real Time Road Accidents Detection System based on crash estimation; a computer vision techniques that detects road accidents and reports them in real-time as well as allowing the monitoring of accidents using a client server architecture and an interactive GUI.
The project aims at using quasi-experimental designs to estimate the impact of policy reducing speed limits in major cities, on the number of road accidents. It is based on Bayesian hierarchical modelling and Poisson regression
Interactive dashboard for exploring and analyzing road accident data in Poland. Built with Streamlit, PostgreSQL, and Python for dynamic SQL queries, visualizations, and insights.
The right emergency contact, in one tap, even with no signal. AI-prioritised location-aware PWA for road accidents — works offline across 200 countries. Built for the IIT Madras Road Safety Hackathon 2026.
Developed an interactive Road Accident Analysis Dashboard in Microsoft Excel using Pivot Tables, Pivot Charts, and Slicers to analyze 896K+ casualties by severity, vehicle type, road conditions, and yearly trends. Enabled dynamic filtering and year-over-year comparison to support data-driven decision-making.
An interactive Tableau dashboard project visualizing road accident data by vehicle type, weather, road conditions, and geography. Features year-over-year trends, fatalities by severity, and map-based insights for data-driven decision-making.