From Reactive to Predictive Smart Home Health Monitoring: Humidity Dynamics of Indoor Laundry Drying Under Contrasting Ventilation Strategies

Indoor humidity is a modifiable exposure relevant to respiratory morbidity, mould proliferation, and occupant comfort. Indoor laundry drying is common in energy-constrained homes and can generate multi-hour moisture loads that increase health risk when ventilation is limited. This paper compares humidity dynamics during laundry drying across three conditions in a controlled smart home: a closed non-ventilated room, reactive ventilation activated during drying, and predictive ventilation with scheduled window opening and dehumidifier operation before, during, and after the event. Results show that predictive ventilation suppresses peak humidity, shortens time at elevated levels, accelerates moisture decay, and prevents multi-cycle accumulation; relative to reactive or no ventilation, it maintains lower pre-event humidity and enables faster recovery, reducing cumulative exposure despite similar moisture loads. These empirical patterns support predictive control strategies that act before hazardous exposure rather than relying on post hoc threshold responses, with implications for respiratory symptom monitoring, household behaviour sensing, and scenario-based predictive intervention models in smart homes.