Since people spend most of their time in indoor environments, they are continuously exposed to various contaminants that threaten human health. The air quality in these settings is therefore a crucial factor in maintaining health safety. In order to reduce the concentration of indoor air pollutants and improve air quality, photocatalytic oxidation has drawn the attention of researchers. This study aims to provide a comprehensive view of the nanomaterials used in the photocatalytic oxidation of the most common pollutants in indoor environments. The effects of various parameters like humidity, airflow, deposition time, and light intensity were also evaluated, as they can significantly influence photocatalytic reactions. The most common nanomaterials used in photocatalysis are TiO₂-based and, in this study, they were classified and examined based on their morphology. TiO₂ doping with metals and non-metals has demonstrated an enhancement of its adsorption properties and photocatalytic efficiency for the removal of several pollutants. The role of carbon-based nanomaterials in photocatalysis was also evaluated due to their adsorption capabilities towards various pollutants. In addition, other less common photocatalysts such as ZnO, MnO₂, WO₃, CeO₂, and CdS also exhibited high photocatalytic activity for pollutant degradation. Applications of these photocatalysts in air purifiers, paints, and building materials e.g., concrete, glass, and wallpapers, lead to efficient reduction of pollutants in indoor settings.

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.