A fuzzy cognitive map-based algorithm for predicting water consumption in Spanish healthcare centres

• Published in: Building simulation Vol. 16; no. 11; pp. 2193 - 2205
• Main Authors: Sánchez-Barroso, Gonzalo, González-Domínguez, Jaime, Almeida-Fernandes, Joao Paulo, García-Sanz-Calcedo, Justo
• Format: Journal Article
• Language: English
• Published: Beijing Tsinghua University Press 01-11-2023; Springer Nature B.V
• Subjects: Algorithms; Atmospheric Protection/Air Quality Control/Air Pollution; Building Construction and Design; Cognitive maps; Cognitive models; Engineering; Engineering Thermodynamics; Health care facilities; Heat and Mass Transfer; Monitoring/Environmental Analysis; Prediction models; Profitability; Research Article; Software; System effectiveness; Water consumption; Fuzzy Cognitive Maps; water consumption; healthcare centres; water management; Healthcare Engineering
• ISSN: 1996-3599; 1996-8744
• DOI: 10.1007/s12273-023-1028-y

The management of water consumption in healthcare centres can have positive impacts on both the environmental performance and profitability of health systems. Computational tools assist in the decision-making process of managing the operation and maintenance of healthcare centres. This research aimed to integrate the empirical knowledge of experts in Healthcare Engineering and the historical data from 66 healthcare centres in a Fuzzy Cognitive Map. The outputs of the predictive model included water consumption, water cost, and CO
2
emissions in healthcare facilities, along with eleven variables to discover the causes and consequences of water consumption in healthcare centres. A healthcare centre with about 12 350 users, located in a city that experiences an average of 1100 heating degree days, whose facilities be moderately energy-efficient contributing over 50% with renewable energies is expected to consume 8.4 dam
3
of water with 32.1 k€ of cost, and contribute realising 30.8 ton CO
2
eq emissions. The use of Fuzzy Cognitive Maps for prediction can provide a high level of effectiveness in identifying the factors that contribute to water consumption and in designing key performance indicators to manage the environmental performance of healthcare buildings. This tool is extremely effective in enhancing the performance of the management division of health systems.