Ubiquitous sensing for smart and aware environments

s computing technology increasingly becomes part of our daily activities, we are required to consider what is the future of computing and how will it change our lives? To address this question, we are interested in developing technologies that would allow for ubiquitous sensing and recognition of daily activities in an environment. Such environments will be aware of the activities performed within it and will be capable of supporting these activities without increasing the cognitive load on the users in the space. Toward this end, we are prototyping different types of smart and aware spaces, each supporting a different part of our daily life and each varying in function and detail. Our most significant effort in this direction is the building of the “Aware Home” at Georgia Tech. In this article, we outline the research issues we are pursuing toward the building of such smart and aware environments, and especially the Aware Home. We are interested in developing an infrastructure for ubiquitous sensing and recognition of activities in environments. Such sensing will be transparent to everyday activities, while providing the embedded computing infrastructure with an awareness of what is happening in a space. We expect such a ubiquitous sensing infrastructure to support different environments, with varying needs and complexities. These sensors can be mobile or static, configuring their sensing to suit the task at hand while sharing relevant information with other available sensors. This configurable sensor-net will provide high-end sensory data about the status of the environment, its inhabitants, and the ongoing activities in the environment. To achieve this contextual knowledge of the space that is being sensed and to model the environment and the people within it requires methods for both low-level and high-level signal processing and interpretation. We are also building such signal-understanding methods to process the sensory data captured from these sensors and to model and recognize the space and activities in them.