Characterising Heating and Cooling Setpoint Dynamics in IoT-Enabled Smart Buildings

Smart buildings increasingly rely on thermostats to maintain indoor comfort temperature; however, the behavioural characteristics of heating and cooling setpoints remain underexplored in real-world deployments. This paper analyses zone-level thermostat setpoint data obtained from a real-world smart residential building. The study focuses on characterising comfort zone structure, setpoint variability, and temporal patterns in heating and cooling thresholds. Real-world thermostat data are analysed in combination with outdoor weather information using statistical visualisation and descriptive analysis. The results illustrate structured comfort control behaviour with variability across zones and time, reflecting occupant preferences and operational constraints. By exploring how comfort zones are configured in practice, this work helps clarify how smart thermostats operate in the real world to support tenant comfort using data-driven approaches.

کلیدواژه ها:

Smart Buildings ، Internet of Things (IoT) ، Thermal Comfort ، Thermostat Setpoints ، Comfort Zones ، Smart Cities