Human-in-the-loop: Occupants as integral drivers of indoor climate controls

Occupant thermal comfort and ventilation drive the operation of HVAC (heating, ventilation, and air conditioning) systems in buildings, which consume a large portion of their energy use. “Human-in-the-loop” (HITL), a term borrowed from machine learning referring to a synergy between humans and machines, is a data-driven approach that aims to enable human-based controls of the HVAC system. This participatory approach integrates environmental data and recurrent occupant feedback in the HVAC control loop to tune comfort predictions and determine set points. The goal of this project is to apply it to an educational setting, to attempt to optimize educational building environments for teaching and learning, while minimizing energy use.
Following a machine-leaning based approach, this research aims to develop a pilot testbed project in the BCIT campus to explore the application of human-in-the-loop principles in an educational setting. The objective of the project is to design an experiment in a classroom or a group of classrooms linking a comfort App in the students’ and faculty phones, with enhanced room environmental sensors to provide real time feedback to the HVAC building management system (BMS) controls.

Faculty Supervisor:

Sirine Maalej

Student:

Partner:

École Centrale de Lille

Discipline:

Engineering

Sector:

Energy and Utilities; Artificial Intelligence; Achieving Net Zero

University:

British Columbia Institute of Technology

Program: