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could also be used, though this style is not preferred since the speed at which braille is read is often to slow for the rate at which objects are encountered in the environment. Also, only a very small proportion of the blind community actually read Braille.

Some research has looked into combining different output technologies. Ross and Blasch (2000), for instance, found that the most effective interface combined tactile cues using a tapping interface with improved speech output. More research and studies, however, are required to identify different preferences for communication styles.

7.4 Principles of Mobile Context-aware Computing

In the last section, examples of current technologies to support distant navigation for visually impaired people were described. Here, the principles of context-aware computing, where the notion of ‘context-awareness’ concerns the ability of a computing system to recognise a user’s context and respond to it in a way that is useful to the user, are discussed. This ability is achieved by integrating information acquired from both multiple sensing technologies and other contextual resources, such as web-based servers and personal diaries/calendars. By integrating and then interpreting this information, the application becomes more aware of the user’s environment and is able to provide more useful information and services in line with the user’s task, location, and situation. Context-awareness could therefore support independent mobility of visually impaired people as it would augment their perception and understanding of the environment (Helal et al. 2001).

Adapting or personalising information to the individual user is also at the heart of context-aware computing. So, for instance, unique cognitive mapping strategies used for encoding spatial information could be accounted for by having more customised feedback. Using the example of people with different visual impairments (discussed in Section 7.2.1), it is vital that feedback is structured in such a way in order to allow people with different requirements to learn and experience the environment rather than become dependent on verbose and generic application feedback.

The capabilities of context-awareness become even more prominent when one considers the current trend towards ubiquitous or pervasive computing. This is an ideology originally propounded by Wesier (1991) who envisaged a world where computers are embedded in everyday objects allowing contextual information to be exchanged in an interconnected environmental infrastructure. As sensors become cheaper and smaller, this notion becomes a closer reality, allowing many new services to be available to the user. However, such advancements need to be investigated alongside the human and social implications of acquiring more information about the user, particularly privacy and security issues.

The remainder of this section will be discussed under five headings: (i) adding context to user computer interaction, (ii) acquiring useful contextual information, (iii) capabilities of context-awareness, (iv) application of context-aware principles, and (v) technological and usability issues.

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last issue is particular relevant to visually impaired people, who would wish to focus their attention on hazard identification and environmental learning and experience, rather than frequent interaction with the device.

Context-aware computing therefore completely redefines the basic notions of interface and interaction (Moran and Dourish 2001), and ‘by improving the computer’s access to context, we increase the richness of communication’ (Dey and Abowd 2000a). Examples of useful contextual information and the processes with which information could be acquired will be described in the next section.

7.4.2 Acquiring Useful Contextual Information

Before useful contextual information can be identified, it is important to firstly specify what is meant by the notion of context. This is a ‘powerful, and longstanding, concept in human-computer interaction’ (Moran and Dourish 2001), which provides an insight into how people behave, make decisions, select goals, and interact with other people and objects within their environmental context. Context is a complex and multidimensional term that has received many contrasting definitions and categorisations over the years. Typical dimensions of context are described in Table 7.1.

In other examples, Dey and Abowd (2000a) define context as ‘any information that can be used to characterize the situation of an entity—an entity is a person, place, object that is considered relevant to the interaction between a user and

Table 7.1. Dimensions of context

an application, including the user and application themselves’. So, here, a blind person’s guide dog may be considered a relevant entity to the interaction between the user and the GPS-based navigation device, since the activities supported by the guide dog would not need to be supported by the device.

Some researchers have also proposed a multidisciplinary approach to contextaware design. Selker and Burleson (2000) describe how cognitive science needs to be integrated, while Bradley and Dunlop (2003) combine theories of context within linguistics, computer science and psychology. In the latter case, it is argued that adding contextual theories within (i) linguistics provide a useful insight into how contextual detail might be altered for different contexts and situations (Bunt 1997), (ii) psychology provides a invaluable insight into the cognitive processes that underpin a user’s decisions and behaviour, such as cognitive mapping strategies (as discussed before), decisions regarding meaningful vs incidental aspects of the environment (Smith 1988).

Thus, an understanding of context will enable application designers to identify which dimensions are useful for both inferring a user’s activity/intentions and providing more relevant context-specific feedback. Useful contextual information, all of which has been used by context researchers at some point, may include:

•User’s profile. Preferences/dislikes, e.g. customised speech output settings.

•Physical environment. Location and nearby objects, e.g. in bus station and ticket machine nearby.

•User’s activity. Orientation and speed, e.g. asleep or awake, on a bus or walking.

•Temporal. Time of day, week, or season, e.g. just finished work and a winter’s day.

•Environmental parameters. Temperature, light, noise, and weather conditions, e.g. cold, dark, and icy.

•Social environment. People nearby, e.g. streets busy prior to a football match.

•Resources. Nearby and available, e.g. train and bus timetables.

•Physiological. Blood pressure, heart rate, and tone of voice, e.g. heart rate indicating level of anxiety/stress.

Contextual information can be acquired using various sensing technologies and contextual resources. Sensing technologies include GPS and Active Badge to identify user’s location; ultrasonic transducers and Bluetooth to detect objects in the local environment; temperature sensors; physiological sensors to measure, for instance, heart rate to give an indication of anxiety levels; and camera technology and image processing for face recognition. Contextual resources, such as weather forecasts, can be acquired by connecting to web-based servers, while a user’s diary and personal settings can be used to identify a user’s planned social or business arrangements, holidays, activities, etc. While these sensing technologies can be used to better understand the user’s context, the human implications of their design and use need to fully investigated, such as the intrusiveness of physiological sensors.