Ubiquitous Computing and Awareness

Ubiquitous computing (also referred to as ubicomp) came about from Weiser’s (1991) work into novel user interfaces and interaction in the 1980s. The basic idea of ubiquitous computing is that computing technology will be- come more advanced and more integrated into our lives so that we will use it without explicitly thinking about how or what we are doing; computing technology will become second nature.

2.7. ACTIVE FIELDS themselves into the fabric of everyday life until they are indistinguish- able from it.”

Weiser (1991, p.3)

The dream of ubiquitous computing is to have systems that are invisible and with which we interact without even thinking about them. Related to, and seen as an important component of ubiquitous computing systems, is calm computing. Calm computing is the concept that technology should be passive and undemanding of a person’s time and attention, technology

that“is informing without overburdening”(Weiser and Brown 1996, p.76).

An interesting issue here is that in order to do this the systems need to have an understanding of the context of an action. That is the informa- tion and current situation that is used to help inform the action. Without such an understanding, any information generated or actions performed may well not be appropriate, causing the user to intervene and destroy- ing the illusion of the technology hiding in the background. Therefore a definition of context needs to exist. This is an issue with which computing researchers have struggled for some time, Every researcher, when talking about context, tends to create their own definition of context. These defi- nitions often are just synonyms for context (Dey 2001, p.7). This research uses the following definition of context for the remainder of the work:

“Context is any information that can be used to characterise the situa- tion of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.”

Dey (2001)

A major component powering ubiquitous computing is awareness sys- tems. These are computing devices and software which provide an in-

sight into the behaviours, actions, and context of another person or the participant themself (Dourish and Bellotti 1992, Schilit et al. 1994, Chen and Kotz 2000, Dey 2001). As with most computing research, this general idea of having an insight into the context of a person is not precise enough. Awareness systems are therefore generally broken up into three different categories:

• Location awareness: Systems which use location as the primary context

source.

• Context awareness: A general catch-all for any system which uses con-

text sources.

• Social awareness: Systems which are designed to give a person an in-

sight into people other than themself.

Of these three categories location awareness is the most explored, most likely due to the relative ease of determining location via technological means. All three categories heavily overlap and it is mostly up to the re- searcher to decide into which category they feel their work falls. These three categories essentially just differentiate the goal and sources of con- text used to provide the awareness. Awareness systems are also broken up into what they do with any appropriate context they determine or are provided.

Schilit et al. (1994) decomposed the possible features an aware device could take into two dimensions: whether the task is getting information or running a command, and whether the the task should be performed manually (by the user of the system) or automatically by the system itself.

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Table 2.1: The awareness task breakdown. Reproduction from Schilit et al. (1994)

Manual

Automatic

Information

Command

Proximate

Selection

Automatic

Configuration

Contextual

Commands

Context triggered_Actions

Proximate selection relates to the idea that contextuallycloseitems and actions are emphasised more in the system interface than others, making it easier to perform these actions (Schilit et al. 1994). Automatic config- uration is where the system connects and changes what the system can do depending on the context, such as connecting to other machines to use their resources instead of slowing down the user’s work (Schilit et al. 1994). Contextual commands exploit the concept that many possible actions can be predicted by a person’s context and then make these options available in that context, an example is defaulting to the printer in a user’s room when they print a document (Schilit et al. 1994). Finally, context triggered actions are actions that the system will automatically trigger and perform once the correct contextual position occurs (Schilit et al. 1994).

Dey (2001) on the other hand split awareness features into three cate- gories:

• Presentation: Systems which present information and services to the

user.

• Automatic execution: Systems which automatically perform actions

for the user.

• Tagging: Systems which tag context information for later retrieval.

This work, however, considers the work of Chen and Kotz (2000) to be the most apt and useful: activesystems, those systems which automat- ically adapt and change based on the context, and passivesystems, those that record and present updated context information letting the user de- cide what they wish to do. This work prefers this definition over the others because it is immediately understandable: there are some systems which show context and others that perform actions based upon it. This is not to say that the definitions by Schilit et al. (1994) and Dey (2001) are defi- cient, just that this work prefers Chen and Kotz’s (2000). The active and passive breakdown is also remarkably similar to that created by one of the earlier works to look at awareness by Dourish and Bellotti (1992) where they defined the types asexplicitly generatedandpassively collected.

For a truly ubiquitous computing future we will require both active and passive systems, however, this research takes the approach that for the immediate time-being passive systems will provide better results than active. The reasons for this are simple: people are complicated and for a system always to perform the correct action it needs to have a through understanding of the context of its user. A passive system allows for the user to determine what to do based on the context, allowing researchers

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and developers to exploit the innate intelligence of a person instead of try- ing to guess their intent correctly. The trick is providing the contextual information in a way that is meaningful to a person.