Today, cities face unprecedented challenges, including climate change, social inequality, housing shortages, and the energy transition. These challenges call for transformative solutions that are sustainable, inclusive, and informed by data. In this evolving landscape, integrating Environmental, Social, and Governance (ESG) criteria into urban planning and real estate valuation is essential, not optional. At the same time, the increasing accessibility of urban data and the rapid development of artificial intelligence (AI), machine learning (ML), and digital modeling tools are creating new opportunities to reimagine cities and the built environment. These technologies empower researchers and practitioners to capture complexity, simulate scenarios, and evaluate impacts at a level of depth and on a scale that was previously impossible. Against this backdrop, the time is ripe for cross-disciplinary dialogue exploring how tech-driven innovation can shape sustainable urban futures. This Research Topic aims to explore how such technologies can accelerate the ecological and digital transition of our cities, buildings, and infrastructures.
The aim of this Research Topic is to bring together visionary contributions that explore the fusion of AI-based methods and multidimensional assessment models in order to support ESG-oriented urban regeneration and real estate valuation. Although ESG frameworks are gaining global traction, many questions remain: How can AI and data analytics operationalize ESG indicators in urban and energy systems? How can we model the environmental and social impacts of regeneration strategies? What role can intelligent systems play in optimizing building retrofits, renewable energy deployment, or energy poverty mitigation?
We seek interdisciplinary research that blends technological innovation with social and environmental value creation. Contributions might focus on predictive models for urban change, AI tools for building energy performance simulation, integration of renewable energy data in urban planning, or new valuation metrics incorporating carbon footprint, climate risk, and social equity. We welcome theoretical and applied research, especially when grounded in real-world case studies or policy frameworks like the European Green Deal, the Renovation Wave, or national decarbonization strategies. Let’s shape a knowledge frontier where AI meets ESG, energy meets equity, and regeneration meets resilience.
We welcome original research articles, methodological papers, reviews, and case studies exploring the role of AI, machine learning (ML), and data-driven approaches in advancing environmental, social, and governance (ESG)-aligned urban regeneration, sustainable energy systems, and real estate valuation. Topics may include (but are not limited to):
• AI and ML for ESG-based valuation and risk models
• Energy-efficient urban regeneration and retrofitting strategies
• Smart energy systems, renewables, and data-driven transition planning
• Mapping energy poverty and social vulnerability
• Climate-risk modeling and resilience assessment
• Urban digital twins, the Internet of Things (IoT), and real-time energy data analytics
• Integrating EU Taxonomy, the Renovation Wave, and Net-Zero targets into planning
We encourage cross-sectoral approaches and diverse methodologies that bridge the fields of urban studies, real estate economics, energy engineering, data science, and environmental planning. Submissions that combine technical depth with policy relevance and social impact are especially welcome.
Keywords: AI, Artificial Intelligence, Machine Learning, Multidimensional Valuation, ESG, Urban Regeneration, Real Estate Valuation, Sustainable Design, Energy Efficiency, European Green Deal, Urban Data, Predictive Modelling, Governance, Resilient Decisions, Smart Cities, Urban Sustainability, Environmental Social Governance, Technology Integration, Complex Urban Contexts, Sustainable Development, Data-driven Decisions
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
