Mathematical and Data-Driven Modeling for Intelligent, Healthy, and Sustainable Indoor Built Environments

The goal of this Research Topic is to advance the state of the art in mathematical and data-driven modeling approaches applied to indoor built environments, with a focus on methods that improve occupant health, comfort, safety, and energy efficiency while supporting the transition toward sustainable, nearly zero-carbon buildings. We aim to address current challenges in predicting and optimizing thermal comfort, indoor air quality, ventilation, and HVAC system performance, including the integration of physics-informed machine learning, hybrid simulation-data approaches, and digital twins for real-time monitoring and control. The Research Topic will also welcome contributions on explainable and interpretable AI models, uncertainty and sensitivity analysis, and multi-criteria decision-support systems for building performance assessment, as recent advances in these areas offer significant potential to bridge the gap between data-driven predictive accuracy and the practical, transparent decision-making required by building designers, engineers, and facility managers.We invite Original Research, Review, Mini Review, Perspective, and Methods articles addressing, but not limited to, the following themes: - mathematical and computational modeling of indoor environmental quality; - predictive modeling of thermal comfort, ventilation, air quality, and energy consumption; - optimization of HVAC systems and building operation; - explainable AI and interpretable models for sustainable and healthy buildings; - physics-informed machine learning and hybrid simulation-data approaches; - digital twins for smart indoor environments; - multi-criteria decision-making in building performance assessment; - uncertainty, sensitivity, and reliability analysis of indoor environment models. We particularly encourage submissions that combine artificial intelligence and machine learning with structural, environmental, or energy-related engineering perspectives, and welcome contributions from researchers across different institutions, countries, and career stages, in keeping with the interdisciplinary and international spirit of this collection. Topic editors: Miljan Kovacevic, Ercan Işık, Marijana Hadzima-Nyarko, Borko Bulajic Source: https://www.frontiersin.org/research-topics/84130/mathematical-and-data-driven-modeling-for-intelligent-healthy-and-sustainable-indoor-built-environments