Coco: Heat Minimizer
Project Overview
About
Pedestrians face dangerously high street temperatures during heatwaves, yet conventional navigation apps ignore heat exposure. CoCo combines satellite temperature data with information about buildings, tree cover, shade and weather conditions, to identify cooler routes at street level. Users can compare heat exposure, distance and travel efficiency before choosing a route. Developed and tested in New York City, the tool protects vulnerable pedestrians while helping authorities target tree planting, reflective surfaces and other heat-reduction measures.
Team
Lenny Metlitsky
I'm Lenny, and I'm an environmental engineering student at Cornell University who is focusing on using climate modeling techniques to help people across the world. My work with Dr. Norouzi first began at the NASA Climate Change Research Initiative, where I worked to develop a machine learning model to predict Harmful Algal Blooms. This project started when Dr. Norouzi and I began to explore extreme heat while building a satellite temperature downscaling model. At Cornell, I'm researching to better understand Mercury cycling within ecosystems, and I'm also leading Cornell GeoData, a group that builds low-cost sensors to assess environmental trends.