<![CDATA[This research investigates how Artificial Intelligence (AI) can optimize environmental conditions in libraries to preserve paper longevity. Fluctuations in temperature, often caused by varying visitor numbers, can affect both humidity and the durability of paper materials. AI algorithms help predict and adjust these fluctuations by utilizing temperature and humidity sensors, which provide real-time data essential for maintaining optimal conditions. The method involves placing sensors in key areas of the library to collect environmental data over six months, covering seasonal changes and usage variations. AI algorithms then analyze the data to predict temperature shifts, and the system automatically adjusts controls to keep the environment stable. The results show that AI significantly improves temperature stability compared to conventional methods, reducing fluctuations that affect paper durability. Humidity sensors prevent mold growth, and energy efficiency is improved by up to 15% through more precise control. The discussion highlights the importance of maintaining stable temperatures to ensure long-term preservation of paper materials. AI not only enhances operational efficiency but also improves the visitor experience by ensuring a comfortable environment. In conclusion, AI proves to be effective in managing library conditions. The integration of sensors and predictive algorithms offers a sustainable solution for preserving materials and improving energy efficiency, laying the groundwork for future advancements.]]>
Copyrights © 2024
