CS8501: Smart Buildings -- Fall, 2011


Buildings are the basis of our social and economic infrastructure. We spend 90 percent of our time indoors and the indoor environment affects our physical and mental health and our productivity. In the US, buildings are responsible for 71 percent of electricity consumption and 39 percent of total energy use, 38 percent of carbon dioxide emissions, 12 percent of water consumption, and 40 percent of non-industrial waste. Despite the clear societal impact, the design and operation of buildings has largely been left behind by the technological revolution that has improved so many other aspects of life.

In this seminar, we will explore the computational structure of buildings, and technological approaches to exploit and/or improve that structure for improved building performance. We will focus on energy and water efficiency, but other building performance metrics will also be discussed. Students will become familiar with the state of the art in the field and will learn about core challenges and principles of smart building design, including topics in:
  • sensing and control
  • wireless networking
  • low-power and low-energy computer systems
  • distributed programming
  • embedded systems
The course will include a project component that teaches experimental design and the scientific method. The outcome of the project will be a proposal that, if executed, could result in a wokshop-quality publication. Execution of the proposed experiment is encouraged, but not required for the class. For the projects, we will leverage data sets streaming live from actual smart buildings.

Students will also learn to critique scientific papers in this research area.


Mechanical Engineering Bldg 214
Tue-Thur: 12:30-1:45

Instructor: Kamin Whitehouse
Office Hours: Tue-Thurs 1:45-3:00


The full course schedule and topics will be maintained on the course Wiki. More information about the course can be found by enrolling in the course and visiting the course website through Collab.itc.virginia.edu.

Grading for the course will be:
  1. 25% two paper critiques and presentations
  2. 50% project
  3. 25% participation