TY - GEN
T1 - Risk Assessment of COVID-19 Transmission on Cruise Ships Using Fuzzy Rules
AU - Sovatzidi, Georgia
AU - Triantafyllou, Georgios
AU - Dimas, George
AU - Kalozoumis, Panagiotis G.
AU - Drikakis, Dimitris
AU - Kokkinakis, Ioannis W.
AU - Markakis, Ioannis A.
AU - Golna, Christina
AU - Iakovidis, Dimitris K.
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2024.
PY - 2024
Y1 - 2024
N2 - Cruise ships constitute a popular means of vacationing for millions of people each year. However, due to the on-board conditions, e.g., densely populated areas, highly transmissible respiratory diseases, such as COVID-19, are a common cause of outbreaks. Hence, accurate assessment of the transmission risk (TR) is crucial. Recent approaches focus on long-term forecasting of such events; however, the limited availability and inconsistency of relevant data poses a challenge for developing short-term and data-driven methods. To this end, this work proposes a novel short-term knowledge-based method implemented through fuzzy rules for assessing the TR in cruise ships. The use of fuzzy rules, developed by domain experts and information extracted from the literature, assists in dealing with the data limitations. In contrast to previous approaches, the proposed method considers information deriving from various sensors and the ship information system in accord with a recently proposed smart ship design. Moreover, the fuzzy TR assessment estimates the confidence of an inferred decision, quantifying the uncertainty regarding its results. Evaluation via agent-based simulations demonstrates the effectiveness of the proposed method across different scenarios.
AB - Cruise ships constitute a popular means of vacationing for millions of people each year. However, due to the on-board conditions, e.g., densely populated areas, highly transmissible respiratory diseases, such as COVID-19, are a common cause of outbreaks. Hence, accurate assessment of the transmission risk (TR) is crucial. Recent approaches focus on long-term forecasting of such events; however, the limited availability and inconsistency of relevant data poses a challenge for developing short-term and data-driven methods. To this end, this work proposes a novel short-term knowledge-based method implemented through fuzzy rules for assessing the TR in cruise ships. The use of fuzzy rules, developed by domain experts and information extracted from the literature, assists in dealing with the data limitations. In contrast to previous approaches, the proposed method considers information deriving from various sensors and the ship information system in accord with a recently proposed smart ship design. Moreover, the fuzzy TR assessment estimates the confidence of an inferred decision, quantifying the uncertainty regarding its results. Evaluation via agent-based simulations demonstrates the effectiveness of the proposed method across different scenarios.
KW - Airborne Disease Transmission
KW - Cruise Ship
KW - Fuzzy Logic
KW - Fuzzy Rules
KW - Knowledge-based System
UR - http://www.scopus.com/inward/record.url?scp=85199197767&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-63219-8_25
DO - 10.1007/978-3-031-63219-8_25
M3 - Conference contribution
AN - SCOPUS:85199197767
SN - 9783031632181
T3 - IFIP Advances in Information and Communication Technology
SP - 336
EP - 348
BT - Artificial Intelligence Applications and Innovations - 20th IFIP WG 12.5 International Conference, AIAI 2024, Proceedings
A2 - Maglogiannis, Ilias
A2 - Iliadis, Lazaros
A2 - Macintyre, John
A2 - Avlonitis, Markos
A2 - Papaleonidas, Antonios
PB - Springer Science and Business Media Deutschland GmbH
T2 - 20th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2024
Y2 - 27 June 2024 through 30 June 2024
ER -