Building facade design plays an essential role in enhancing energy efficiency and reducing environmental impact in high-performance building design. Balancing the conflicts among various building facade design variables to satisfy different optimization objectives constitutes a highly complex optimization problem. The rapidly increasing number of studies demonstrates a significant interest in implementing multi-objective optimization methods to tackle building facade optimization problems. This study conducts a systematic review of optimization methods for building facade optimization (BFO). The optimization objectives and design variables are categorized based on their characteristics. The efficiency and effectiveness of optimization algorithms in addressing BFO problems are compared. Building optimization techniques and tools are showcased, along with their functions and limitations. Key findings highlight the robust feasibility and effectiveness of optimization algorithms, methods, and techniques in resolving a diverse range of BFO challenges. The limitations, challenges, and future potential of these methods are summarized and proposed.

Incorporating Internet of Things (IoT) technology into the operation of buildings is expected to generate immense synergy, thereby saving energy and improving occupant comfort by overcoming the limitations of the existing system. Preventing operations in the absence of occupants can save energy, and the occupants’ preferred operating temperature should be used as the control set-point rather than the nominal temperature. In this study, IoT technology and image sensors are used to rapidly detect indoor environment changes, and a method is proposed to utilize air quality and thermal comfort as the control set-points. A real-time ventilation control algorithm is proposed based on the CO₂ concentration calculated according to the number of occupants. To check the thermal comfort level, the real-time operating temperature estimated from the surface temperature data of the infrared array sensor is reflected in the comfort zone defined by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). The deficiencies in indoor environment conditions caused by the temporal and spatial lag of sensors in the old system are minimized using IoT technology, which also facilitates wireless communications. The image sensors can be used for multiple purposes based on various interpretations of the image information obtained.

It has been identified that improving building energy efficiency is an effective method to reduce greenhouse gas (GHG) emissions. Although standards have been established to satisfy a building’s minimum energy demand while ensuring the comfort of its residents, they are difficult to implement in mixed-humid regions. This study proposes a hybrid ventilation strategy that can comprehensively reduce cooling, heating, and ventilation energy in mixed-humid climate regions to significantly decrease the primary energy demand and reduce the impact of buildings on the environment. This study evaluated the changes in energy saving potential and thermal comfort according to the extension of the natural ventilation period and passive strategies, such as decentralized ventilation. Changes in indoor air temperature, operative temperature, and PMV for each strategy were analyzed. As a result, extending the natural ventilation and the decentralized ventilation strategies can save 32% and 34% of the building’s energy, respectively. Considering that electricity is the main energy source for cooling in Korea, the extension of the natural ventilation period was judged to be the best approach from the perspective of primary energy demand. The results can be used to predict changes in building energy demand and thermal comfort and select an appropriate ventilation strategy based on occupant information obtained using Internet of Things.

Latitudo Borealis is a project that develops an innovative cold-climate wall assembly that combines new passive opaque building envelope technologies to absorb, store, and transfer solar energy into a building during winter, with exterior shading to mitigate overheating during summer. The research encompasses three domains of architectural research: the physical testing and optimization of high-performance envelope assemblies, the use of computational evolutionary algorithms in the design of highly tuned climate-informed shading configurations, and new tools and processes for precise robotic heat bending of wood. It is demonstrated that the assemblies are capable of successfully absorbing and redirecting heat into the building interior in winter to improve building performance. The application of the experimental envelope assembly is further explored through the design of an unbuilt test case pavilion.

This article describes recent research on the performative, formal and aesthetic potentials of multi-cellular pneumatic foil-based envelope systems for lightweight, responsive building skins able to control thermal insulation and air exchange with minimal amounts of energy and mechanical components. The prototype-based research involves the use of principles from biological examples of pneus, which inform the design of physical analogue models at an architectural scale. The process entails physical-computational feedback loops wherein physical performance findings are fed into computational design models for pneumatics and membranes, as well as modified energy models, in order to advance the predictive design capacities of simulation tools in designing such systems. In this process, material agency allies with computational agency to develop novel possibilities for dynamic pneumatic envelopes.