Conference Agenda

Overcast skies are defined by diffuse illumination and low luminance contrast, often producing visually flat and uninspiring interior environments in northern climates. This study investigates whether small, low-cost optical components can be retrofitted onto existing windows to enhance the perceptual quality of daylight in north-facing rooms of multi-story buildings. The research examines how reflective, refractive, and diffractive elements—concave mirrors, plano-convex lenses, Fresnel lenses, and hologram sheets—modify diffused daylight to introduce spatial contrast or color under overcast sky conditions.A 1:8 physical model was used to test thirty-eight iterations using these devices, with each configuration assessed under real overcast daylight. Eighteen iterations demonstrating the strongest effects were selected for detailed analysis. Results indicate that concave mirrors clearly outperform lenses in concentrating diffuse light: they produced sharper light patches, cast defined shadows, and generated contrast. Transparent hologram sheets created strong color dispersion but often oversaturated the interior due to transmitted refracted light. Opaque-backed hologram sheets successfully mitigated this issue by eliminating transmission while preserving desirable reflective and diffractive qualities. Together, these findings reveal two distinct pathways for qualitative daylight enhancement in overcast climates: contrast-based strategies using direct reflections, and color-based strategies using controlled diffraction.Building on these insights, the study proposes nine retrofit design solutions that integrate optical elements as adjustable, user-controlled components within existing window assemblies. These add-on systems offer a practical, non-invasive, and cost-effective approach to improving visual interest, occupant experience, and perceived daylight quality in buildings located in predominantly overcast regions.

In terms of Indoor Environmental Quality (IEQ), providing sufficient daylight and access to outdoor views is important for occupants’ health and productivity. Consequently, contemporary architectural design increasingly adopts high Window-to-Wall Ratios (WWR) to maximize daylight penetration and visual connectivity. However, high WWR, particularly in office perimeter zones, often results in excessive direct solar penetration and severe glare conditions. Conventional static shading systems exhibit limited capacity to consistently balance daylight admission and glare mitigation under dynamically changing solar conditions. Although dynamic shading systems allow more responsive control strategies, single-axis systems remain insufficient in addressing the simultaneous variations of solar azimuth and altitude angles, while multi-axis kinetic facades often encounter practical limitations due to mechanical complexity and implementation constraints. Within this context, a dual-axis dynamic shading system capable of independently responding to both solar azimuth and altitude angles is proposed as a practical solution to simultaneously enhance daylight regulation and glare control. This study evaluates the proposed dual-axis dynamic system on a room-scale south-facing facade located in Phoenix, Arizona, where high solar radiation and exterior illuminance levels necessitate carefully optimized shading strategies. To comprehensively assess visual environmental performance, an integrated metric Mutual Satisfied Area (MSA) was introduced, combining useful daylight, glare probability, and unobstructed view ratio into a unified performance index. The results indicate that, compared to a conventional static horizontal louver system, both grid-based array scenarios (7×7 and 14×14) achieved higher MSA values. Furthermore, correlation analysis revealed that the most influential design parameters affecting MSA were the shading panel width and height, which determine the inter-panel spacing within the grid configuration, whereas the distance between the facade and the shading system exhibited relatively minor impact on overall performance.

In contemporary cities, tensions persist between legitimized and illegitimized urban art, limiting public participation and artistic freedom. While murals are widely celebrated, graffiti is frequently criminalized, yet few studies examine the design elements shaping this distinction. This gap challenges the democratic urban ideals described by Jane Jacobs and Henri Lefebvre, who emphasized vibrant and inclusive public spaces. Most existing research focuses on controlling graffiti through surveillance or machine learning rather than exploring how street art—both sanctioned and unsanctioned—can function as a participatory civic medium. This study proposes an augmented reality (AR) street art platform designed to democratize urban expression and expand community participation in creating and evaluating urban art. In the first experimental phase, machine learning and electroencephalography (EEG) measure cognitive and emotional responses to 200 images of sanctioned murals and unsanctioned graffiti collected from Manhattan and the Bronx. Participants view these images in a virtual reality (VR) environment while neural activity is recorded. Verbal feedback is analyzed using the BERT algorithm to evaluate semantic relevance and sentiment. These neural and linguistic datasets are integrated into engagement scores used to classify artworks and identify patterns in public perception. Results show that legitimized murals generate higher engagement scores than illegitimized graffiti based on neural and linguistic analysis. Natural Language Processing (NLP) further indicates murals align more closely with public policy priorities and collective aesthetic preferences. The analysis identifies key design features—including color, composition, and subject matter—that influence public acceptance. Building on these findings, the AR platform integrates AI-assisted creation tools (txt2pix and pix2pix) to generate interactive AR street art. Users can visualize, comment on, navigate, and vote on artworks in urban space, enabling participatory curation. By combining VR evaluation, EEG engagement metrics, and AI-assisted generation, this research reframes urban art as a democratic digital-physical medium supporting civic dialogue and cultural expression.