Explainable semi-supervised AI for green performance evaluation of airport buildings

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

“…Results from the review revealed that, impact of AI spans various facets of a building lifecycle (Table 4). Machine learning algorithms, a subset of AI, are instrumental in optimizing energy efficiency within buildings [63,64]. These algorithms continuously analyze real-time data from sensors embedded in building systems to understand patterns in energy consumption and environmental conditions.…”

“…Beyond the specific lifecycle stages, the review identified several overarching benefits of AI integration in promoting sustainability across the building lifecycle. Machine learning algorithms continuously analyze real-time data from sensors to understand patterns in energy consumption and environmental conditions, enabling dynamic adjustments to building systems for minimizing energy usage [63,64]. Predictive analytics algorithms forecast equipment failures by analyzing historical performance data, extending the lifespan of critical building systems [62,66].…”

“…One of the primary contributions of this review is the consolidation of current knowledge on the use of AI across the lifecycle of buildings, highlighting its potential to enhance sustainability [20,23,[31][32][33][36][37][38][40][41][42][43][44][45][46][47][48][62][63][64]69,71,72,86]. By compiling and analyzing findings from various studies, the review provides a comprehensive overview of the ways in which AI applications can optimize energy efficiency, predictive maintenance, lifecycle cost analysis, occupant comfort and productivity, waste reduction and recycling, carbon footprint reduction, and simulation and design optimization throughout the design, construction, and operation stages of buildings.…”

“…Furthermore, the review identified the potential advantages and challenges of integrating AI towards creating a sustainable building lifecycle [20,23,32,47,58,[62][63][64]66,69,70,72,73,83,86,[95][96][97][98][103][104][105][106][111][112][113][114][115][116][117][118][119][120][121][123][124][125]. While highlighting the benefits, such as energy efficiency optimization, predictive maintenance, and waste reduction, the review also addressed challenges like initial implementation costs, data security and privacy concerns, lack of standardization, skills gap, interoperability issues, ethical considerations, and regulatory compliance.…”