Urban Climate Intelligence Lab: Using Sensors, Maps, and AI to Understand How City Design Affects Heat

Cities heat unevenly because buildings, trees, roads, and open spaces affect heat, humidity, and airflow, creating microclimates that influence comfort and health. Study investigates the relationship between ambient air temperature and relative humidity to assess heat stress across diverse land-use types in Greensboro, NC using Wet-Bulb Temperature Formula. Using a mobile SMART-T sensor and a stationary HOBO logger, ground-level temperature and humidity data along chosen routes were collected over a ten-day period during late morning (11AM–12:00 PM) and evening (9:00 PM-10PM) intervals. The route spanned high-density urban zones, residential areas of varying income levels, and vegetated spaces. The sensors are calibrated using AI prediction to remove the noise from the variable driving velocity.  The AI based classification helps to explain the heat stress distribution pattern. The heat stress evaluation provides a straightforward suggestion for city development.