
doi: 10.1109/98.944006
handle: 11858/00-001M-0000-0027-7D0B-D
In this article smart appliances are characterized as devices that are attentive to their environment. We introduce a terminology for situation, sensor data, context, and context-aware applications because it is important to gain a thorough understanding of these concepts to successfully build such artifacts. In the article the relation between a real-world situation and the data read by sensors is discussed; furthermore, an analysis of available sensing technology is given. Then we introduce an architecture that supports the transformation from sensor data to cues then to contexts as a foundation to make context-aware applications. The article suggests a method to build context-aware devices; the method starts from situation analysis, offers a structured way for selection of sensors, and finally suggests steps to determine recognition and abstraction methods. In the final part of the article the question of how this influences the applications is raised and the areas of user interfaces, communication, and proactive application scheduling are identified. We conclude with the description of a case study where a mobile phone was made aware of its environment using different sensors. The profile settings of the phone (ringing mode etc.) are automatically selected according to the real world situation the phone is used in.
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| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 146 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
