An IoT-enabled predictive maintenance framework for hospital HVAC systems: implications for facilities management and sustainability

Purpose Hospital buildings are highly energy-intensive, with HVAC systems critical to reliability, energy use and indoor environmental quality. Despite the potential of predictive maintenance (PdM), its adoption in hospital facilities management remains limited. This study aims to develop an IoT-enabled PdM framework to support HVAC maintenance decision-making while aligning maintenance practice with sustainability objectives. Design/methodology/approach An explanatory sequential mixed-methods design was adopted, comprising a survey of hospital HVAC maintenance practices and digital readiness, followed by expert interviews to contextualise feasibility, workflow integration and organisational constraints. Findings from both phases informed development of a layered PdM framework. Findings Results reveal uneven organisational readiness, marked by high HVAC criticality but limited digital infrastructure, skills and data integration. Preventive maintenance remains dominant, although PdM is viewed favourably when compatible with existing workflows. These drivers informed a phased, system-agnostic framework integrating sensing, analytics, decision-support and performance feedback. Practical implications The framework provides a structured pathway for phased PdM adoption, supporting improved maintenance planning, HVAC reliability and alignment between maintenance practice and sustainability goals. Originality/value This study contributes an empirically grounded PdM framework that links HVAC maintenance decision-making with energy performance and sustainability outcomes, bridging technical PdM research and facilities management practice in hospital environments.