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

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.

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Publication Details

Journal
OALib
Published
2025-01-01
DOI
https://doi.org/10.4236/oalib.1113484
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Samiha Guetal
OALib
Occupational Health and Safety Research
article

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

Samiha Guetal
article en

Abstract

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.

OALibVol. 12(09)
Alliant International University (US)
Openalex Percentile: Top 65%
Occupational Health and Safety Research
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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 — Samiha Guetal · OALib (2025) | TGRS Research Map | TGRS