Smart Healthcare Engineering: A Data-Driven Educational Framework for Psychrometric Analysis and Air Handling Systems in Hospitals

This paper presents a data-driven educational framework for teaching psychrometry and air quality control in hospitals, developed within an international pilot project involving universities and hospitals in Spain, Romania, and Turkey. The objective of this pilot study is to examine a multidisciplinary framework that equips engineering students with essential technical skills for managing hospital infrastructure, particularly in critical areas like operating rooms and intensive care units. The methodology integrates theoretical instruction, analogue instruments, and digital technologies, including Arduino-based sensing and AI tools, to facilitate data interpretation and critical thinking. By bridging manual measurements with digital monitoring, the framework aims to equalize proficiency among students from diverse engineering backgrounds. Quantitative results from 23 participants provide preliminary evidence of academic growth, consistent with the hypothesis that this integrated approach may facilitate conceptual mastery. This work offers preliminary insights into the advancement of data-driven modelling in engineering education, emphasizing the significance of multidisciplinary training and international collaboration in preparing future professionals for the oversight, operational management, and maintenance of modern healthcare facilities.