Computational Sustainability as a Framework for a Bioelectromagnetically-Conscious Urban Microenvironment

The concept of computational sustainability in urban environments emphasizes integrating data engineering, artificial intelligence (AI), and computational techniques to harmonize environmental, social, and economic needs while advancing the United Nations (UN) Sustainable Development Goals (SDGs). A bioelectromagnetically-conscious microenvironment represents an architectural and spatial design approach that incorporates various advanced disciplines to align with natural biological rhythms and regulate electromagnetic (EM) fields, ultimately fostering a balance between human health and environmental well-being. As cities and high-density urban regions are increasingly saturated with EM fields from various sources, the integration of computational sustainability and bioelectromagnetics becomes essential to enhance the occupant experience when interacting with buildings and spaces. This study addresses this EM anthropocene influence by presenting an EM exposure mapping (EMEM) that involves a data acquisition (DAQ), interpolation heatmaps, and machine learning (ML) algorithms for validation and prediction. A case study is conducted on a microenvironment that comprises three buildings on the University of Ottawa campus in Canada. The above correlation between techniques serves as a robust pathway for architects, engineers, and policymakers for promoting designs that are mindful of visualization and management of EM ambient influences. The outcomes serve not only scientific and educational purposes but also bolster adaptive urban design, compliance with safety standards, and building certification systems. All the above aim at fostering smarter and more livable communities and establishing a pathway for advancing EM sustainability.