MATRIX > Mental HeAlth Diagnostics Through Real time Unified Intelligent X-AI Reasoning and SNOMED-CT Attribution

The increasing impact of carbon emissions from automobiles on public health and climate necessitates accessible tools to inform individuals and policymakers. This research project introduces an AI-driven system called NEXUS that predicts tailpipe emissions using carbon emission data from various cars and contextualizes these predictions within the appropriate regulatory framework. The system integrates a robust retrievalaugmented generation (RAG) model, which retrieves relevant regulatory information from government PDF documents and combines it with emission predictions to generate informed, context-aware responses. By providing tailored insights on the climate effects of car-buying choices, the system aims to raise public awareness about the environmental and health consequences of carbon footprints. Furthermore, it offers actionable intelligence to support policy decisions, promoting sustainable practices and improving air quality. Experimental evaluations demonstrate the system’s effectiveness in delivering accurate, contextual, and actionable information, underscoring its potential to drive both individual and collective climate-conscious decision-making.