I am designing a Machine Learning (ML) powered module for personalized thermal comfort and air quality in office buildings based on occupant feedback.
It is evident that people spend more and more time indoors. Thus, a lot of energy is consumed by buildings, and especially office buildings although with not the desirable results. Occupant satisfaction in terms of building conditioning is less than 80%, while they do not have any control over the conditions of their workplace. Both, energy consumption and occupant comfort, can be addressed by ML-powered personalized comfort systems (PCS), that can learn from the occupants behavior and adjust the conditioning according to their needs.
I have decided to join the SBC program as an EngD (former PDEng) trainee in order to get a more hands-on experience in working with the industry. The program provides great opportunities for personal and professional development that broaden engineers’ knowledge and perspective.
