The integration of smart control systems in office buildings can be disruptive when individual preferences and expectations for control interfaces are overlooked. Understanding how human–building interaction influences environmental comfort and acceptance is essential for creating user-centered designs. This study aimed to evaluate the effectiveness of usability testing as an innovative method for assessing building system control interfaces and user interaction with automation. Specifically, we examined user preferences for shading and lighting controls in a controlled office laboratory, varying by “Type of Device” (analog vs. digital), “Position” (wall, desk, or split), and “System Cues” (information richness). In an experimental setting involving 20 participants, we investigated how these factors influence satisfaction and acceptance of automation. Using an adapted Post-Study System Usability Questionnaire (PSSUQ), we evaluated satisfaction with Ease of Use, Reachability, and Information. Findings show that while participants’ initial expectations favored simple analog controls, preferences shifted toward digital, information-rich systems after hands-on interaction. Ordered logistic regression confirmed that Reachability (β=2.317) and Ease of Use (β=1.831) were the strongest predictors of Overall Satisfaction (p<0.001), placing interface position as the primary design characteristic. However, preferences varied by office type: in shared offices, users preferred wall-mounted controls to facilitate shared access and visibility. These insights offer actionable guidance for designing smart control interfaces that enhance user satisfaction, support personal control, and promote greater acceptance of building automation.

In recent years, several studies have assessed the influence of automated façades on energy savings, IEQ, and occupant satisfaction. However, discrepancies exist between the expected advantages of automated façades predicted in research and the actual benefits observed in real-world tests. To assess how automated façade operation enhances building performance, in particular within office building contexts, this study reviews and analyzes current evidence on the influence of automated façades. In this review, 91 studies were identified presenting evidence of their performance. A total of 34 studies investigated performance in laboratory settings, 23 in real office buildings, and 34 in simulations. Only 13 laboratory studies and 17 real office building studies included human participants. Visual and thermal quality were the main indoor environmental domains investigated, with limited exploration of others. Existing studies show large variability in contextual factors (e.g., type of shading and control) or experimental designs (e.g., different benchmark scenarios), hindering the comparison of results. Consistent evidence shows the potential of automated façades for energy savings, particularly in lighting and cooling demands, which outperform manual control systems. Automated controls are more effective in reducing excessive daylight and glare, while evidence of the impact on thermal and air quality remains limited. Regarding occupant satisfaction, evidence is unclear since, in some cases, occupants prefer manually controlled façades and, in others, automated ones. Further research is suggested on human-centered studies in real office buildings to capture occupant behavior and preferences while exploring solutions that dynamically identify and integrate factors affecting occupant interaction with buildings.

The presence of sensor networks to monitor environmental conditions and the automation of blinds and lighting systems controls is now commonplace in buildings, especially public ones with a high number of occupants. However, implementing control algorithms that are sufficiently reactive to variable sky conditions and that actually meet occupants’ needs is still a challenge. In the present study, we investigate and compare advanced and simple control algorithms developed for a variable occupancy, open space, small sized conference venue. Operation and performance resulting from an optimized approach are assumed to be the benchmark strategy, and two other control algorithms of varying complexity are compared with it. Results show that the optimized control strategy performs best overall, but only marginally compared to the other two strategies. It performed especially well in meeting glare protection requirements, as a glare-related parameter was embedded into its objective function, but it also led to erratic movements of the blind slats’ tilt and it required significantly higher computation times than rule-based control strategies. These two factors make it impossible to implement such strategy as it is in the real building, and indicate that a practical control implementation can be more effective than an optimal one.

The adaptive control of sunlight through photochromic smart windows could have a huge impact on the energy efficiency and daylight comfort in buildings. However, the fabrication of inorganic nanoparticle and polymer composite photochromic films with a high contrast ratio and high transparency/low haze remains a challenge. Here, a solution method is presented for the in situ growth of copper-doped tungsten trioxide nanoparticles in polymethyl methacrylate, which allows a low-cost preparation of photochromic films with a high luminous transparency (luminous transmittance T_lum = 91%) and scalability (30 × 350 cm²). High modulation of visible light (ΔT_lum = 73%) and solar heat (modulation of solar transmittance ΔT_sol = 73%, modulation of solar heat gain coefficient ΔSHGC = 0.5) of the film improves the indoor daylight comfort and energy efficiency. Simulation results show that low-e windows with the photochromic film applied can greatly enhance the energy efficiency and daylight comfort. This photochromic film presents an attractive strategy for achieving more energy-efficient buildings and carbon neutrality to combat global climate change.

Optimizing the built environment via simulations of building models hinges on standardizing data acquisition. In this research, we put forward distinct levels of detail for geometry and material inputs, specifically tailored for indoor daylight applications. We primarily focus on understanding the uncertainties arising from imprecise estimations of material optical properties and incomplete geometrical inputs in climate-based indoor daylight simulations. Employing a Monte Carlo approach, we analyzed six office and teaching spaces, creating 20 variations for each by altering geometrical completeness and material accuracy. The technique of excluding non-permanent objects below certain sizes in four graduated steps was used to derive and test the impact of various geometrical levels of detail. Our findings reveal that different levels of geometrical completeness lead to errors ranging from 1.08% to 18.05%. Additionally, a twofold increase in simulation time was noted when geometrical detail was enhanced relative to the most basic model. Errors stemming from imprecise definitions of material optical properties showed a normal distribution. The uncertainty in simulation outcomes showed a linear rise with increasing input material uncertainty, lying between 10% to 30%, depending on space configurations. We observed heightened uncertainty near openings, attributed to window transmittance effects. The research underscores that daylight predictions are markedly more sensitive to transmittance uncertainties than to those in reflectance, regardless of the window-to-floor ratio. These insights may help to guide a more efficient data acquisition process of indoor spaces for daylight simulations.