As global temperatures rise and cities race to meet aggressive energy-performance targets, adaptive building envelopes are rapidly shifting from experimental curiosities to essential components of climate-resilient architecture. In recent months, several high-profile research initiatives have accelerated this momentum, including new biomimetic kinetic facade prototypes capable of reducing solar heat gain by more than 40%, and Europe’s first AI-controlled facade assembly robots entering pilot projects. In the United States, where the Department of Energy is pushing for aggressive reductions in operational carbon and ASHRAE standards continue to evolve, robotics-enabled facades represent a critical pathway for improving building performance at scale.
Against this backdrop, we speak with an emerging leader in the field of adaptive architectural systems, Diana Salamaga. She holds dual training in Architecture and Mechatronics Engineering, presented her research on kinetic facades at the ASME International Mechanical Engineering Congress & Exposition in New Orleans and is currently working to expand this research, focusing on scalable kinetic facade modules and AI-driven control systems for high-performance buildings.
In the conversation ahead, Diana discusses not only the broader shift toward intelligent, sensor-driven building envelopes but also how her own research has evolved in response to rapid technological advances, and why the coming decade may redefine what a facade is expected to do.
— Diana, you presented your interdisciplinary research on kinetic facades at the American Society of Mechanical Engineers conference. How did this experience, combined with your dual background in Architecture and Mechatronics Engineering, shape your transition into robotics-integrated facade design?
— Preparing and presenting my paper in 2023 reinforced how naturally architecture and mechatronics intersect in the context of adaptive facades. Because I was trained in both fields, exploring the intersection of architecture and mechatronics has always felt natural. For me, it has always been a unified system where geometry, mechanical actuation, sensing, and control logic evolve together. My research began with studies on solar exposure, thermal performance, and environmental variability around buildings. There was a clear moment when it became obvious that meaningful adaptivity requires perception, interpretation, and decision-making, qualities we associate with robotics. Developing the prototype only confirmed this: a kinetic facade becomes effective only when all its architectural and mechatronic layers operate as one coherent organism.
— Diana, based on your research, how do you define a “robotics-enabled adaptive kinetic facade” within the broader smart-building ecosystem? What elevates a facade from simply movable to truly robotic?
— A facade becomes robotic when movement is no longer the primary attribute, but rather a consequence of continuous sensing, interpretation, and autonomous decision-making. In this sense, a robotics-enabled facade does not respond mechanically to pre-set schedules; it behaves as an intelligent subsystem embedded within the building’s control architecture. It observes environmental and occupancy conditions, processes data in real time, predicts changes when possible, and adjusts its configuration to optimize daylight, thermal loads, or resilience against wind. Such a facade is not performing a choreographed motion; it is executing purposeful actions based on data, which is why I consider it a robotic component rather than merely a kinetic one.
— Movement introduces wear, mechanical stress, and maintenance challenges. How do you address long-term reliability and robustness in your work with kinetic prototypes?
— Reliability emerges from the system’s architecture rather than from isolated components. When I design or evaluate a kinetic facade, I treat material durability, mechanical design, sensing, diagnostics, and control as interdependent. A system becomes reliable when its structure distributes loads predictably, when actuators operate within safe stress limits, when sensors continuously monitor performance, and when control logic can adapt or self-correct before issues escalate. Instead of treating maintenance as something external to the design, I consider it intrinsic to how the facade perceives its own state and responds to it. This integration of structural thinking, embedded intelligence, and operational awareness is what ensures long-term robustness.
— Skepticism often arises around cost justification. From your experience with prototypes and performance modeling, do adaptive robotic facades genuinely improve energy efficiency enough to justify their complexity?
— A kinetic facade only struggles to justify itself when it is treated as a standalone visual feature. Once it becomes part of a building’s active environmental strategy, the value becomes much clearer. Studies in the field consistently point to measurable reductions in cooling demand and notable improvements in daylight quality. In my own prototypes, responsive adjustments allowed us to maintain a stable indoor illumination target while mitigating heat-gain spikes, and the system reacted quickly enough to keep indoor conditions within comfortable thresholds. The true justification lies in cumulative performance: over months and years, adaptive control reduces energy consumption, enhances comfort, and aligns with the long-term operational goals of smart buildings, which ultimately offsets the initial investment.
— Despite rapid progress in research, robotics-enabled facades are still rare in commercial projects. What do you consider the main barriers to widespread adoption?
— The challenges stem from a combination of technical, economic, and regulatory factors. Most building codes were written for static envelopes, so adaptive systems often fall outside existing frameworks, which complicates approval processes. The lack of standardized modules or widely accepted design guidelines means each project becomes a bespoke engineering effort, increasing costs and time. At the same time, building-systems integration, especially with HVAC, lighting, and analytics, remains a hurdle for teams unfamiliar with complex controls. What the industry needs is accumulated evidence from real projects, modular solutions that simplify implementation, and clearer pathways for regulatory compliance. Once these elements converge, adoption will accelerate.
— Diana, your research emphasizes synchronous data and control. What types of data and algorithms are essential for a kinetic facade to function as a fully integrated element of a smart building?
— A kinetic facade becomes intelligent only when it has access to the right information and when its control logic can interpret that information meaningfully. It needs an understanding of solar exposure, indoor and outdoor temperature, wind conditions, daylight levels, and human occupancy patterns. With these inputs, algorithms can coordinate how the facade modulates light, heat, and airflow. In our prototype, this was demonstrated by the system maintaining an indoor illuminance target of around 300 lux and adjusting its configuration within 5–10 seconds in response to changing daylight conditions, as confirmed through real-time sensor logging, and by its ability to moderate emerging heat-gain spikes through temperature-informed actuation.
The core isn’t merely a choice between rule-based logic or predictive control; it is the relationship between real-time data and purposeful behavior. The most important principle is that sensing, prediction, and actuation must be conceived together from the start. When data and design evolve in parallel, the facade becomes an active participant in the building’s intelligence rather than an accessory to it.
— Given that your background place you at the intersection of design and engineering, how should architects, mechanical engineers, and robotics specialists collaborate on kinetic facade projects?
— Collaboration must begin at the conceptual stage. When architecture is developed independently from kinematic modeling or control architecture, the resulting conflicts are difficult and expensive to resolve later. In my research, the most productive insights came from iterative exchanges, adjusting the geometry because of actuator constraints, refining the control logic because of structural considerations, or adapting materials in response to kinematic behavior. A kinetic facade is too intertwined to be divided among disciplines. The most effective approach resembles a continuous design loop where each discipline informs the next, and decisions evolve collectively rather than in sequence.
— As AI becomes increasingly embedded in building systems, what role do you see for machine learning in the future of adaptive facade control?
— AI is a natural evolution for kinetic facade control. Rule-based logic can handle basic responsiveness, but machine learning can interpret patterns across time, anticipate environmental events, and optimize system behavior in ways that static algorithms cannot. For example, AI can anticipate glare or thermal peaks before they occur, refine actuation strategies based on historical performance, and detect subtle mechanical anomalies long before they manifest as failures. Although our last prototype did not yet employ machine learning, the architecture was designed with this progression in mind. I see AI as a transformative layer that will enable facades to operate not just reactively but proactively.
