Ubiquitous computing is a model of computing in which computer functions are integrated into everyday life, often in an invisible way. The model requires both small, inexpensive computers and wired and wireless ("dumb") devices connected to larger computers. A household controlled by ubiquitous computing might have remote-controlled lighting, automated sprinklers, a home entertainment center, devices to monitor the health of occupants, and a refrigerator that warns occupants about stale or spoiled food products.
The proponents of ubiquitous computing envision a progression in computing functionality from the primacy of desktop computing, with its focus on programming and publishing, to an age of "natural" computing, wherein computers are accepted and utilized in all aspects of work and leisure. Rapid changes in technology, combined with an increasingly mobile society, ensure that the average person is continually challenged to use unfamiliar electrical and mechanical devices. This requires that devices operate in accordance with the intuition of the user, and serving that intuition requires computing power. Ubiquitous computing is, therefore, (arguably) not a dream in need of pursuit, but a predictable outgrowth of technical solutions to societal trends.
Modern devices that may serve the ubiq...
Modern devices that may serve the ubiquitous computing model include mobile phones, digital audio players, radio-frequency identification tags and interactive whiteboards (Greenfield, 2006 & Hansmann, 2003).
Context aware computing is one of the main themes in ubiquitous computing. In practice, certain types of context, such as location, identity, time and activity are more important than others (Dey, 2000). Since the early 1990's much research effort has been
Focused on how to acquire, refine, and use location context information (Hightower, 2001). Traditional location-sensing systems rely on either explicit or implicit means of localization. In explicit localization, the user must wear or carry a device or tag which is used to locate them, while implicit localization systems do not require instrumenting the user. Most implicit localization systems use computer vision to track users. We are interested in the use of sound source localization, arguing that understanding the location of sound sources can be valuable for context aware computing. Sound events are often associated with human activities, but little effort in the ubiquitous computing community has tried to exploit this.
There are social concerns when sensing video and audio in the home environment.
When the actual information retrieved is not the rich signal that a human would see or
hear, there is potential for alleviating those concerns. We designed a sound source
localization (SSL) system which locates sound events in the environment using microphone arrays (Xuehai Bian and Gregory D. Abowd). The only information extracted in this case is solely the location of sound sources. Our system is based on a standard SSL algorithm which uses the time of delay method and PHAse Transform (PHAT) filtering in the