| Autor: |
Greco, Enrico, Gaetano, Anastasia Serena, De Spirt, Alessia, Semeraro, Sabrina, Piscitelli, Prisco, Miani, Alessandro, Mecca, Saverio, Karaj, Stela, Trombin, Rita, Hodgton, Rachel, Barbieri, Pierluigi |
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| Zdroj: |
Epidemiologia; Jun2024, Vol. 5 Issue 2, p267-274, 8p |
| Abstrakt: |
In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI's role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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