This Partnerships for Innovation:Building Innovation Capacity (PFI:BIC) project from the University of California-Merced provides support for an academic-industry partnership to focus on the development of a crowd-based temperature control system to manage both building energy expenses and building occupant comfort effectively and efficiently, adapting university-created technology to real business applications. Buildings represent an important context for complex service systems. Americans spend 90% of their time inside buildings. Buildings accounted for near 40% of U.S. energy consumption in 2011, 75% of which was electrical energy. The energy expenditure in the building market is huge: in 2011, more than $431B was spent on energy. The climate-change footprint of buildings is correspondingly large, and the energy performance of buildings is poor, as measured by occupant comfort surveys. The modest goal of building professionals "that 80% of occupants should be satisfied with the thermal, air quality, acoustic, and lighting environments" is almost never met in practice. Though reducing energy consumption is a strategic national policy issue, comfort should not be overlooked, and the relationship between comfort and energy use must be taken into account. This project relies on a crowd-based control system for gathering occupant comfort data and managing building systems.
ThermoVote is a platform technology for gathering and analyzing thermal comfort data from large numbers of building users and for controlling building heating, ventilation, and air conditioning (HVAC) systems in real-time. It provides a critical link in a complex service system to enable smart control of building infrastructure. This project uses ThermoVote as a crowd-based environment control system in new building environments to harden the platform technology, integrate it with new building systems, and develop service scenarios and related components to implement the ThermoVote approach on a large scale. From an engineering perspective, design of complex systems given large numbers of participants has rarely been studied. From a cognitive perspective, complex, distributed cognitive systems have rarely been studied. From an interdisciplinary perspective, design of engineering systems has rarely been done given deep knowledge of complex multiple feedback loops created by interactions of large numbers of people and technologies. There are several key innovations to the project: use of real buildings to show system benefits; investigation of both individual and group behavior to save energy by adjustable autonomy; and novel algorithms using multiple criteria optimization (e.g., energy consumption and preferences). And there are a number of open questions: How can we design effective learning systems that are controlled by large groups? How should a system portray its changing behavior? What are the best schemes for indirect or direct control? Many questions lie at the intersection of systems and people.
This project is led by faculty in the Electrical Engineering and Computer Science group of the School of Engineering at the University of California, Merced, with participation by faculty in Management and Cognitive Science at the University of California, Merced. The primary industrial partner is HP Labs (Palo Alto, California), the research arm of Hewlett Packard, a large U.S. business.
