Urban Sustainability Monitoring through Automatic Insights using LLM AI Agents

Urbanisation and climate change are accelerating environmental degradation, making cities critical battlegrounds for sustainability. While vast amounts of environmental data (e.g., CO₂ emissions, energy use, air quality, weather, etc.) are collected, extracting actionable insights remains a challenge due to data complexity, real-time processing demands, extensive human/expert involvement, and the need for predictive analytics.  This project aims to develop AI-powered Large Language Model (LLM) agents that autonomously interpret urban environmental data, detect anomalies, forecast trends, and provide decision-support for sustainable urban management.