1 Department Construction Science and Management, Lincoln School of Architecture and The Built Environment, University of Lincoln, UK.
2 Retrofit and Sustainability Coordinator, Infinity Energy Organization, London, UK.
3 Nigeria Atomic Energy Commission, Nigeria.
4 Federal University of Technology Akure, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 061-079
Received on 18 August 2024; revised on 28 September 2024; accepted on 30 September 2024
The decarbonization of buildings is a pivotal strategy in addressing global climate change, and artificial intelligence (AI) is increasingly recognized as a powerful tool in this process. This paper explores the application of AI in optimizing building energy consumption, focusing on predictive analytics, real-time energy monitoring, and smart energy systems. By leveraging machine learning algorithms, AI enhances energy efficiency through precise automation, particularly in heating, ventilation, and air conditioning (HVAC) systems. AI-powered demand response solutions dynamically adjust energy use based on factors like occupancy, weather patterns, and energy prices, further minimizing carbon footprints. Additionally, the integration of renewable energy sources such as solar and wind with AI-driven energy management systems enables smarter utilization of clean energy. The paper examines both new construction projects and the retrofitting of existing infrastructures, offering insights into AI’s role in reducing carbon emissions and improving energy sustainability. Case studies highlight successful implementations, underscoring AI’s ability to drive significant energy savings and carbon reduction. The study also discusses challenges such as data privacy, the high cost of AI technology, and the regulatory framework required for widespread adoption. The findings present AI as an essential component of the future of sustainable, carbon-neutral buildings.
AI-driven decarbonization; Predictive analytics; Smart HVAC systems; Energy optimization; Renewable energy integration; Building sustainability
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Feyisayo Ajayi, Osho Moses Ademola, Kafilat Funmilola Amuda and Bolape Alade. AI-driven decarbonization of buildings: Leveraging predictive analytics and automation for sustainable energy management. World Journal of Advanced Research and Reviews, 2024, 24(1), 061-079. Article DOI: https://doi.org/10.30574/wjarr.2024.24.1.2997