The overall goal of this project is to develop an intelligent daylighting system that can outperform today's commercially available systems. Specifically, we aim to increase user satisfaction while minimizing energy consumption and expense. We propose to achieve this through the use of several intelligent techniques including influence-diagram based decision-making, fuzzy-based sensor validation and fusion, and agency. The assumed underlying sensor technology is Smart Dust Motes, a wireless sensing and communications platform currently under development at U.C. Berkeley and various private companies.

News! Jessica Granderson, Yao-Jung Wen and Alice Agogino are featured in the December issue of Energy Notes, from the California Energy Institute. UC Berkeley researchers are exploring new combinations of commercial lighting systems controlled by "smart" wireless sensor technology that can customize a room’s lighting to meet a range of pre-established conditions, including the occupant’s personal preference.                    Jessica Granderson tests the demonstration system with a          remote control while Alice Agogino and Yao-Jung Wen watch. Read the full article:      Wireless Smart Lighting System: Saves energy, responds to human preferences (pdf)

Check the photo gallery for pictures of the system implementation.

GE Global Research

UC Energy Institute

PIER Program

VTT Finland