Application of Occupancy-Based Control in Building Energy Saving and Indoor Thermal Comfort

Abstract

Research on smart energy saving is becoming famous globally in different sectors. The current research is
anticipated to lower energy demand and consumption in the building industry, which has already reached 49% globally
and is projected to rise by 2% yearly, incurring significant monthly costs. One prevalent problem nowadays is striking
a balance between energy efficiency and. Most research has concentrated on energy efficiency without taking into
account occupant thermal comfort, which might pose health risks to both young and old occupants. The proposed
model is capable of setting the ideal temperature set point to achieve healthy comfort. Although our proposal lacked
an experimental evaluation a different machine learning technique can be integrated alongside fuzzy logic algorithms
to enable significant energy saving as well as maintained thermal satisfaction of occupants.