Sustainable Cities and Society · 2026
Automated Urban Energy Assessment: From Thermal Flyover to AI-Driven Retrofit Prioritization for Sustainable Cities.
Uses Thermal-SAM to segment mid-wave infrared flyovers into building patches, pairs ring and context thermal features with EPC-derived EUI benchmarks, and shows thermal data is most useful for triaging anomalous high-EUI or EPC-inconsistent buildings for follow-up audits rather than routine direct EUI regression.
DOI
Hongshan Guo, Sebastiano Anselmo, Maria Ferrara, Shuai Niu, Binlin Chi, Xuchen Wang
energyclimate
Building and Environment · 2026
From Seven Points to Probabilities: Ordinal Learning for Risk-Aware Thermal Comfort Prediction.
Reframes thermal sensation prediction as an ordinal learning problem with calibrated probabilities for risk-aware comfort decisions. The model yields confidence-aware outputs that are more useful for control and design decisions under uncertainty than a flat seven-point label alone.
DOI
Hongshan Guo, Dorit Aviv
thermal comfortcontrol
Energy and AI · 2026
Toward Smarter HVAC Control: Machine Learning Reveals Hidden Drivers in Thermal Comfort Databases.
Shows how missing-data policy reshapes feature sensitivity rankings and supports MRT-aware, occupant-centric HVAC control. The paper makes clear that preprocessing decisions materially affect what machine-learning models appear to learn from thermal comfort databases.
DOI
Hongshan Guo, Ilaria Pigliautile, Yu Chang, Qingyao Qiao, Yichun Li
thermal comfortcontrolenergy