Urban Heat Island. Machine Learning Models for Analysis and Maker Approach for Mitigation

The combination of expertise from academic and maker environments could generate new valuable skills and initiatives to counter the urban heat island (UHI) problem, exacerbated by climate change. This article starts with a description of an ongoing UHI analysis conducted within the University of Modena and Reggio Emilia for the Municipality of Carpi, a town of almost seventy-two thousand inhabitants located near Modena in the central Po Valley, Italy. The study adopts long short-term memory (LSTM) neural networks. Meanwhile, extending beyond academic boundaries, open local communities of machine learning developers are also forming in the same region. They are often connected to public fab labs, that are spaces for makers: people dedicated to digital-artisan fabrication and related education. Hence, a social involvement is envisaged in possible future UHI analysis and mitigation mini-initiatives. Expert analysis and engineering could be combined with participation of citizens in data collection, sensor fabrication, and architectural solutions prototyping. All these emerging activities can enrich the already worldwide spreading fab city movement.