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Greco E, Gaetano AS, De Spirt A, Semeraro S, Piscitelli P, Miani A, Mecca S, Karaj S, Trombin R, Hodgton R, Barbieri P. AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites. EPIDEMIOLOGIA 2024; 5:267-274. [PMID: 38920753 PMCID: PMC11203220 DOI: 10.3390/epidemiologia5020018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 05/29/2024] [Accepted: 06/03/2024] [Indexed: 06/27/2024] Open
Abstract
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.
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Affiliation(s)
- Enrico Greco
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy; (A.S.G.); (A.D.S.); (S.S.); (P.B.)
- Italian Society of Environmental Medicine (SIMA), Viale di Porta Vercellina, 9, 20123 Milan, Italy; (P.P.); (A.M.)
- National Interuniversity Consortium of Material Science and Technology (INSTM), Via G. Giusti, 9, 50121 Firenze, Italy
| | - Anastasia Serena Gaetano
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy; (A.S.G.); (A.D.S.); (S.S.); (P.B.)
| | - Alessia De Spirt
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy; (A.S.G.); (A.D.S.); (S.S.); (P.B.)
| | - Sabrina Semeraro
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy; (A.S.G.); (A.D.S.); (S.S.); (P.B.)
| | - Prisco Piscitelli
- Italian Society of Environmental Medicine (SIMA), Viale di Porta Vercellina, 9, 20123 Milan, Italy; (P.P.); (A.M.)
- Department of Experimental Medicine, University of Salento, Via Monteroni, 73100 Lecce, Italy
| | - Alessandro Miani
- Italian Society of Environmental Medicine (SIMA), Viale di Porta Vercellina, 9, 20123 Milan, Italy; (P.P.); (A.M.)
- Department of Environmental Science and Policy, University of Milan, Via Celoria 2, 20133 Milano, Italy
| | - Saverio Mecca
- Department of Architecture, University of Firenze, Via della Mattonaia 14, 50121 Firenze, Italy;
- Italian Academy of Biophilia (AIB), Lungadige Galtarossa 21, 37133 Verona, Italy;
| | - Stela Karaj
- Faculty of Social Sciences, European University of Tirana, Rruga Xhanfize Keko, 1000 Tirana, Albania;
| | - Rita Trombin
- Italian Academy of Biophilia (AIB), Lungadige Galtarossa 21, 37133 Verona, Italy;
| | - Rachel Hodgton
- International WELL Building Institute, New York, NY 10001, USA;
| | - Pierluigi Barbieri
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgieri 1, 34127 Trieste, Italy; (A.S.G.); (A.D.S.); (S.S.); (P.B.)
- Italian Society of Environmental Medicine (SIMA), Viale di Porta Vercellina, 9, 20123 Milan, Italy; (P.P.); (A.M.)
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A Novel Data Acquisition System for Obtaining Thermal Parameters of Building Envelopes. BUILDINGS 2022. [DOI: 10.3390/buildings12050670] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Owing to the high energy consumption in the building sector, appraising the thermal performance of building envelopes is an increasing concern. Recently, a few in situ methodologies to diagnose the thermal parameters of buildings have been considered. However, because of their limitations such as low accuracy, limited number of measurements, and the high cost of monitoring devices, researchers are seeking a new alternative. In this study, a novel hyper-efficient Arduino transmittance-meter was introduced to overcome these limitations and determine the thermal parameters of building envelopes. Unlike conventional methodologies, the proposed transmittance-meter is based on synchronized measurements of different parameters necessary to estimate the transmittance parameter. To verify the applicability of the transmittance-meter, an experimental study was conducted wherein a temperature-controlled box model was thermally monitored, and the outputs of the transmittance-meter employed were compared with those captured by a commercial device. The results revealed a high level of reduction in cost and a low range of difference compared with the latter, thereby validating the applicability of the proposed thermal monitoring system.
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A Method for Maximum Coverage of the Territory by Sensors with Minimization of Cost and Assessment of Survivability. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12063059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In the modern technological world, there are several key factors in the construction of sensor networks. These include maximizing the coverage and minimizing the cost of the network. Like any information system, the sensor network must also meet the conditions of survivability. This is why the development of a method for assessing the survivability of the sensor network is also a key factor. The purpose of this study is to develop a method to establish the maximum coverage of the territory of the sensor network at minimum cost with the ability to assess the survivability of the network. Coverage maximization while minimizing the network’s cost is achieved by finding the optimal pair of values of the coverage radius and the level of the intersection of coverage areas. These values are found by solving a nonlinear multicriteria optimization problem with the use of the genetic algorithm. The designed method for estimating the survivability of sensor networks takes into account not only the importance of network components but also the bandwidth of the network elements. The result of using the proposed methods is a set of Pareto optimal pairs of values of the radii of coverage and the value of the intersection of the coverage areas. In the case of network survivability assessment, the result, in addition to the percentage assessment, is a set of vulnerable sensors and network communication channels. The proposed network survivability estimation method improved the estimation accuracy by 18% compared to methods used in previous works.
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