TY - JOUR
T1 - Sensor-Based Fuzzy Inference of COVID-19 Transmission Risk in Cruise Ships
AU - Triantafyllou, Georgios
AU - Sovatzidi, Georgia
AU - Dimas, George
AU - Kalozoumis, Panagiotis G.
AU - Drikakis, Dimitris
AU - Kokkinakis, Ioannis W.
AU - Markakis, Ioannis A.
AU - Golna, Christina
AU - Iakovidis, Dimitris
PY - 2024/8/22
Y1 - 2024/8/22
N2 - Cruise ships are densely populated ecosystems where infectious diseases can spread rapidly. Hence, early detection of infected individuals and risk assessment (RA) of the disease transmissibility are critical. Recent studies have investigated the long-term assessment of transmission risk on cruise ships; however, short-term approaches are limited by data unavailability. To this end, this work proposes a novel short-term knowledge-based method for RA of disease transmission based on fuzzy rules. These rules are constructed using knowledge elicited from domain experts. In contrast to previous approaches, the proposed method considers data captured by several sensors and the ship information system, according to a recently proposed smart ship design. Evaluation with agent-based simulations confirms the effectiveness of the proposed method across various cases.
AB - Cruise ships are densely populated ecosystems where infectious diseases can spread rapidly. Hence, early detection of infected individuals and risk assessment (RA) of the disease transmissibility are critical. Recent studies have investigated the long-term assessment of transmission risk on cruise ships; however, short-term approaches are limited by data unavailability. To this end, this work proposes a novel short-term knowledge-based method for RA of disease transmission based on fuzzy rules. These rules are constructed using knowledge elicited from domain experts. In contrast to previous approaches, the proposed method considers data captured by several sensors and the ship information system, according to a recently proposed smart ship design. Evaluation with agent-based simulations confirms the effectiveness of the proposed method across various cases.
KW - agent-based simulation
KW - Airborne transmission
KW - cruise ships
KW - fuzzy logic
KW - fuzzy rules
UR - http://www.scopus.com/inward/record.url?scp=85202002356&partnerID=8YFLogxK
U2 - 10.3233/SHTI240784
DO - 10.3233/SHTI240784
M3 - Article
C2 - 39176844
AN - SCOPUS:85202002356
SN - 0926-9630
VL - 316
SP - 1817
EP - 1821
JO - Studies in health technology and informatics
JF - Studies in health technology and informatics
ER -