Global climate challenges often manifest as localized discomfort within buildings, including overheating, glare, and excessive energy consumption. Conventional solar control systems—such as large awnings or mechanical louvers—tend to be rigid, visually dominant, and disconnected from occupants’ experiences. This project proposes an alternative approach through a distributed system of small-scale shading devices composed of knitted textiles, 3D-printed scissor mechanisms, and Arduino-controlled servos.

Rather than relying on large monolithic interventions, the system operates through multiple modular shading units positioned across a window surface. Each unit combines the elasticity of knitted textiles with lightweight scissor mechanisms fabricated through additive manufacturing. The knitted membranes expand and contract seamlessly, while micro-controlled servos actuate the mechanisms in response to environmental sensors or user input. Together, these components enable dynamic adjustments to solar angles, local microclimates, and occupant preferences throughout the day.

Parametric design tools guide the development of textile patterns with localized elasticity, allowing the membranes to form volumetric geometries when deployed and collapse softly when retracted. This patterning produces shading elements that move beyond flat surfaces, introducing tactile and decorative qualities that contribute to the spatial experience of interior environments.

Within broader discussions of architecture’s role in climate action, this research explores how softness, adaptability, and distributed small-scale interventions can support environmental performance. By reducing reliance on mechanical cooling and encouraging passive solar control, the system promotes both thermal comfort and occupant agency. Its modular structure and accessible materials allow adaptation across diverse climates and building types.

By integrating textile craft, digital fabrication, and responsive technologies, the project demonstrates how small architectural devices can contribute to broader conversations on sustainability and climate-responsive design.

Buildings are often designed as static shelters; it’s time they became active participants in our everyday environment, responsive to climate, occupant needs, and real-time data. The built environment presents an opportunity for global decarbonization, yet approaches to building management lack proactive structures that allow AEC professionals to support climate adaptation. While architects and engineers have mastered comfort through mechanical control, the next age of design demands re-grounding design through awareness. Reyner Banham termed the “Well-Tempered Environment” to articulate how architects engage with the conditioning of built spaces. This research positions sensed data as an essential tool in this relationship, bridging between design intent, lived performance, and long-term climate goals. This investigation proposes a “Well-Sensed” framework: a system for integrating sensor networks, digital twins, and strategic system modelling into the lifecycle of existing buildings. The scheme enables continuous environmental feedback, turning building operational data into a dynamic tool for decision-making across maintenance, retrofit, and operational design. Establishing a network of awareness, the system supports AEC service providers in assessing and acting on live performance data through the accurate contextualization of degrading assets. Engaging with built typologies at live, contextualized and quantitative levels, this aims to enable design practitioners to develop individualized life cycle pathways to manage aging building stocks across diverse and complex design contexts. Contributing value-additive and intelligent investment tools, this framework engages with building owners and occupiers to quantify asset value and realize shifting potential through design intervention. This exploration contributes a conceptual and technical bridge between data, design, and behavior, redefining the architect's role in responsive and evidence-based design practices to maintain and promote stewardship and agency of the built environment. Transforming sensing into a tool for understanding rather than control, the Well-Sensed approach offers a scalable path toward more intelligent, adaptive, and climate-conscious building management.

This interdisciplinary research investigates the spatial relationship between Urban Heat Island (UHI) effects and the potential for photovoltaic (PV) solar energy generation on the North Carolina State University (NC State) campus in Raleigh, North Carolina. As urban campuses face rising energy demands and climate challenges, understanding where to integrate renewable infrastructure is critical (Santamouris,2015). This project combines geospatial analysis, remote sensing, and energy simulation to identify locations with elevated surface temperatures and high solar potential,key indicators for PV deployment.

Satellite-derived thermal imagery and land surface temperature (LST) data were used in ArcGIS Pro to map UHI intensity and locate urban "hotspots" (Voogt&Oke, 2003). These were overlaid with solar irradiance maps generated using NREL’s PVWatts Calculator (Dobos,2014) to model PV energy potential on rooftops and open spaces. Cooling degree days and building-level energy consumption were integrated to assess the link between thermal stress and energy demands, especially for buildings in high-UHI zones.

Results show strong spatial correlations between high surface temperature areas and high solar irradiance, highlighting optimal zones for PV installation. Buildings most affected by UHI also exhibited elevated cooling loads during peak summer months, emphasizing the need for renewable energy offsets. Comparative analysis between denser, developed areas and more vegetated or open zones demonstrated that urban buildings experience stronger UHI effects while offering greater solar energy capture potential due to reduced shading and higher irradiance.

This study contributes to campus sustainability by providing a replicable, data-driven framework for evaluating UHI intensity and identifying solar-ready zones through integrated geospatial and energy modeling (Zhou et al.,2011). Findings support NC State University’s sustainability and climate resilience initiatives by guiding strategic investment in renewable infrastructure and demonstrating how co-analysis of environmental stressors and energy potential can inform equitable, integrated campus planning.

This research was supported by the Sustainable Futures Fellowship at NC StateUniversity.