%0 Journal Article
%T Predictive Maintenance for Sustainability: Implementing AI and ML to Predict Equipment Failures and Maintenance Needs in Hotels, Ensuring Energy-Efficient Operation and Minimizing Carbon Emissions
%A Samiha Guetal
%J Open Access Library Journal
%V 12
%N 9
%P 1-5
%@ 2333-9721
%D 2025
%I Open Access Library
%R 10.4236/oalib.1113484
%X This study explores the use of artificial intelligence (AI) and machine learning (ML) in predicting maintenance requirements to support sustainability in the tourism and hospitality sector. The investigation addresses how different AI and ML techniques are used to forecast the possibility of malfunctions in equipment and maintenance needs, with a focus on the way these advancements impact the operations of hotels by reducing emissions of carbon and increasing energy conservation. The findings draw attention to the impact that these developments have on a range of hotel activities and highlight the potential for ML and AI implementation to support the environmental sustainability of hospitality businesses, as evidenced by the significant reduction in carbon emissions and improvements in energy utilization.<br />
%K Hospitality
%K Artificial Intelligence
%K Data Science
%K Machine Learning
%K Sustainability
%U http://www.oalib.com/paper/6860239