Abstract
This study is devoted to the design, implementation and evaluation of an Artificial Intelligence (AI)-based hotel energy management optimization system (EMOS), aiming at improving energy efficiency, reducing operating costs and providing scientific and intelligent solutions for the sustainable development of the hotel industry. The system integrates machine learning, data analysis and intelligent control technology. Through real-time monitoring, forecasting and adjustment, energy consumption can be more intelligent and flexible to adapt to different operating conditions. In the aspect of experimental deployment, this study selected an actual hotel as a pilot, deployed the hotel EMOS based on AI, and conducted comparative experiments in different time periods. The results show that the system significantly improves the energy efficiency of the hotel. Through the machine learning algorithm, the system established an accurate energy forecasting model, and realized the accurate prediction of future energy demand. Compared with the traditional baseline system, the intelligent system shows higher energy efficiency in each time period, which provides substantial economic benefits for the hotel. EMOS, an AI-based hotel, shows excellent performance in improving energy efficiency and reducing operating costs.