Artificial intelligence's unique role in managing and enhancing the maintenance performance of museum works and collections

Effective maintenance and management of the museum is beyond cleaning and repairs. This requires a deep understanding of each artificial material, structure, and inherent vulnerability. From the delicate balance of humidity and temperature to the potential threats of pests and environmental pollutants, a vigilant approach is essential to reducing risks and preventing failure. Continuous monitoring and monitoring are also vital pillars of a maintenance program. Regular inspections allow operators and bodyguards to identify the early symptoms of deterioration and take timely action. The role of AI tools in replicating some human actions and implementing them as the main task of time and place is intriguing. These technologies have the potential to make the best decision based on the input parameters, offering a new perspective on museum management. The present study aims to evaluate computational artificial intelligence methods (machine learning) in managing and improving the performance of museum works and collections. The study formed a focus group of museum and artificial intelligence specialists and extracted high-potential applications in museum operations capable of using artificial intelligence. This study continued to analyze and evaluate the performance of each machine learning method in each application. The findings of this study can provide insight to researchers and policymakers in the field of museum management on how to equip artificial intelligence. This study has provided an extract of the experiences of experts in this field to researchers and other experts.

Keywords:

Artificial Intelligence , Management and Performance Improvement , Museum Works , Machine Learning , Monitoring , Diagnostics , Accounting Intelligence