Peoples daily lives and experiences often contain memories and information that they may want to recall again at a later time. Human memory, however, has its limitations and many times it alone may not be sufficient. People sometimes have difficulty recalling salient information and can forget important details over time. To complement what they can remember naturally, people must expend much time and manual effort to record desired content from their lives for future retrieval. Unfortunately, manual methods for capturing information are far from ideal.
Over the years, ubiquitous computing researchers have constructed devices and applications to support the automated capture of live experiences and access to those records. At Georgia Tech, we have also investigated the benefits of automated capture and access in over half a dozen projects since 1995. As we encountered challenges in developing these systems, we began to understand how the difficulty of building capture and access systems can prevent exploration of the hard issues intertwined with understanding how capture impacts our everyday lives. These challenges illustrate the need for support structures in building this class of ubiquitous computing systems.
This dissertation presents a set of abstractions for a conceptual framework and a focused design process that encourages designers to decompose the design of capture and access applications into a set of concerns that will be easier to develop and to manage. In addition, an implementation of the framework called the INCA Toolkit is discussed, along with a number of capture and access applications that have been built with it. These applications illustrate how the toolkit is used in practice and supports explorations of the capture and access design space.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7167 |
| Date | 13 July 2005 |
| Creators | Truong, Khai Nhut |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 6341164 bytes, application/pdf |
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