video1.0<iframe src="https://www.loom.com/embed/a9643feae8ef4773965ca95992db03d5" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/a9643feae8ef4773965ca95992db03d5-d0caa013facd6537.gif121.025In this video, we present our HackNZ project focused on high-resolution gridded air temperature and relative humidity data from the Environmental Lab in the School of Data Science and Society. We created an interactive map that overlays a heat map onto geographic data for the Durham area, allowing users to explore local conditions and engage with our AI model, Climate Coach, for insights and solutions. We also suggest considering the integration of socio-economic data to better understand the links between income and heat vulnerability. I encourage viewers to think about how we can expand our project to include a wider range of demographic groups for deeper analysis. Your feedback and ideas would be greatly appreciated!