The Role of Social Media in Maternal Health: Balancing Awareness, Misinformation, and Commercial Interests - Abu Halka, Mohamad; Nasereddin, Sara (International Journal of Computational and Experimental Science and Engineering, 2025)
The implementation of AI parametric façade design counters business in an unprecedented manner, accommodating building flexibility, energy efficiency, and user comfort. This study investigates: the performance of AI-driven parametric façades in enhancing adaptive architectural performance through real-time optimization of energy efficiency and thermal comfort. The façade is AI-driven, using a combination of genetic algorithms and artificial neural networks, to dynamically respond to environmental conditions and minimize HVAC and lighting energy use while improving indoor climate stability. The testing through simulation demonstrates that façades AI-optimized outperform static systems by far, with higher energy savings, reduced indoor temperature swings, and improved comfort of the occupants. Sensitivity analysis also corroborated that AI-based façades could be responsive under different climate scenarios, thus assuring lasting sustainability and resilience. The conclusions drawn are align with existing intelligent façade control system literature and thereby position the data-driven architecture as a pathway to net-zero energy buildings (NZEBs). Future directions of research will involve hybrid AI approaches with smart BMS integration and real-life application, thereby enhancing façade performance. Through AI adaptive façade design, architects and engineers can facilitate the construction of energy-efficient, climate-sensitive, and sustainable built environments.