Exploring the Role of Artificial Intelligence in Advancing Net Zero Energy Buildings: A Comprehensive Literature Review
Keywords:
AI systems, AI technologies, Data analytics, HVAC systems, Machine learning, Net Zero Energy Buildings (NZEBs)Abstract
The review integrates current literature on net Zero Energy Buildings (NZEBs), and AI applications in building construction and energy management, and determines gaps to warrant the scope of the project. The overall analysis is organized to furnish a concise description of the state of the field. To start with, the review explores the ground rules of NZEBs, which aim to generate as much energy as they use within one year. The idea is becoming ever more important in light of international initiatives to fight climate change and minimize carbon emissions. The literature describes several approaches used for designing and managing NZEBs, such as the utilization of renewable energy technologies, energy-efficient systems, and green materials. Nevertheless, even though great strides have been taken, the inclusion of AI in these systems is something that is still very much up for discovery. The review also discusses the existing applications of AI in building design and energy management. In industries like fashion and energy, machine learning, data analytics, and IoT have started to change the way buildings are designed, constructed, and operated. AI systems, for instance, can make optimized decisions for HVAC systems, lighting control, and building efficiency after monitoring the real-time data or perhaps shift the system configuration upon the changes. Yet, according to the literature, most present studies put emphasis on the stand-alone use of AI rather than an integrated approach within the NZEB concept. This highlights a need for a stronger framework that integrates various AI technologies to extract maximum benefits in net zero energy solutions.
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