Smart home technologies hold promise for many aspects of daily life. Research and development of these systems has matured for elder care, energy efficiency, and home safety applications. The focus of most implementations has been on single living spaces for a small number of individuals. New low-power wireless systems, inexpensive computing power, and widely available network access has reached the point where large scale ubiquitous computing technologies have become much more feasible.

The smart environments research community has few projects to explore issues and techniques for deploying large scale ubiquitous systems. This work summarizes some of the existing works and introduces the Smart Home in a Box (SHiB) Project. The upcoming SHiB Project targets building 100 smart homes in several kinds of living spaces for gathering longitudinal data from a significant number of residents. The resulting data set will provide opportunities to answer open questions in the areas of transfer learning, active learning, digital asset migration, middleware architectures, activity detection and discovery, human factors, smart home installation, and others.