Toward Utilizing IoT Open Data Set to Identify the Room Thermal Comfort

Building sectors are responsible for 33% of global energy consumption and a one-third CO2 emission as buildings expected to experience high performance in order mee occupnt requirments such lightng, coling, heting, ventiltion systm. Internet Things (IoT) one the leading developments digital technologies led establishment devices improving living style occupants. To date, stdies on intgrating mechnisms IoT identify room thrmal cmfort very sarce. Therefore, this study discussed thermal comfort with respect temperature relative humidity. Three activities i.e. read, write, sit were adopted. The value air sped, metablic rate, clohing inslation was assumed constant. anlysis condcted according Fanger method ASHRAE standard 55. Center Built Environment (CBE) Thermal Comfort Tool usd calculate Predicted Mean Vote (PMV) vales. Results showed average PMV values each activity -2.3 (read), -2.0 (write), -1.4 (sit). Compared climate data set, sitting performed closest scale neutral. It means light lower metabolic rate should be conducted higher