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Dey 4 defines context as any information characterising a situation related to the interaction between users, applications and the surrounding environment. Growing research activity within the realm of ubiquitous computing deals with the challenges of context awareness. The focus is mainly on understanding and handling context that can be sensed automatically in the physical environment and treated as implicit input to positively affect behaviour of an application.

A different view was introduced by Dey, 4 who proposed use of conceptual models and tools to support rapid development of context-aware applications that could better inform empirical investigation of interaction design and social implications of context-aware computing. This work attempted to enable a new phase of context-aware application development with the intention of helping applications developers understand what context is and what it can be used for, and to provide concepts and practical support for software design and construction of context-aware applications.

Different perspectives on how mobile applications can take advantage of context have been advanced. The watch is used both indoors and outdoors, in the dark as well as in sunlight, when running to catch a bus or when attending a boring lecture.

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A good user interface designer will create varied user interfaces for each situation. The context-aware computing approach enables one to create a context-aware watch, where all situation-optimised designs are combined in a single design. The watch is designed so that it can recognise each of the situations, and then reconfigure itself based on the recognised context.


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Figure 1 shows a design sketch for a context-aware watch. Understanding context. Schilit and Theimer 7 refer to context as comprising location, identities of neighbouring users and objects and changes to those objects.

Brown, Bovey and Chen 8 define context as location, identities of neighbouring users, time, and environment characteristics such as season and temperature. All of these definitions characterise context by examples, and as such their application is difficult.

Context-Aware System - an overview | ScienceDirect Topics

Furthermore, they define context to be subject to the constantly changing execution environment. Context-aware applications based on these environments are discussed later. Context information acquisition The goal of context information acquisition should be to determine what a user is trying to accomplish. Context awareness represents a generalised model of input both implicit and explicit , allowing almost any application to be considered more or less context aware insofar as it reacts to input and the environment.

However, there is divergent opinion as to whether context should only comprise automatically acquired information or also include manually acquired information. In an ideal setting context would be obtained automatically and there would be no need for manual acquisition. However, in the real world not all context information can be sensed automatically and applications must rely on the user to provide it manually. Dey 4 observed that designers lack conceptual tools and methods to account for the nature of context and context awareness.

As a result the choice of context information used in applications is very often driven by context-acquisition mechanisms available, typically hardware and software sensors. This entails a number of challenges: the choice of sensors may not be most appropriate or optimal; thus any shortcomings of sensors may be propagated up to application level and hinder flexibility of the interaction and further evolution of the application. Context-aware applications are often distributed because they acquire context information from a number of different sources.

Indeed, context awareness is most relevant when the environment is highly dynamic, such as when the user is mobile. Thus context-aware applications can be implemented on very diverse kinds of computing platforms, ranging from handheld devices to wearable computers to custom-built embedded systems. Some of the approaches for acquiring context information are outlined below. Direct sensing This is often used in applications with in-built local sensors. The client software gathers the desired information directly from these sensors, without an additional layer for gaining and processing data.

Drivers for the sensors are hardwired into the application. This is a distributed approach that extends the middleware-based architecture by introducing an access management component with sensor data gathering function moved to the so-called context server to facilitate concurrent multiple access.

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Winograd 13 describes three different context management models for coordinating multiple processes and components: widgets, networked services and blackboard models. The context of users may be a combination of various entities such as their identity, activity, location and mood; their social context may be the nature of their relationship with other persons e.

The context of a network may be its quality of service parameters, like round-trip time, and the context of a device may be its capabilities, display features or battery level. Identity refers to the ability to assign a unique identifier to an entity. Location is expanded to include orientation and elevation, as well as all information that can be used to deduce spatial relationships between entities, such as co-location, proximity, or containment.

Status or activity identifies intrinsic characteristics of the entity that can be sensed. Time helps characterise a situation, enabling us to leverage the richness and value of historical information. Application of context Nowadays ubiquity is fully embedded, with smart devices integrating intelligence for processing various kinds of data. In such an environment the interaction and management of the various devices that a user may hold is a tough task. Dey 4 propose three basic functions that should be implemented by any context-aware application: presentation of information and services, automatic execution of services and storage and retrieval of context information.

Presentation of information and services refers to functions that either present context information to the user, or use context to propose appropriate selections of actions to the user. In the third type of function, storage and retrieval of context information, applications tag captured data with relevant context information. For example, a zoology application may tag notes taken by the user with the location and time of a species observation; and a meeting capture system may provide an interface to access meeting notes based on who was there, when the meeting occurred and where it was located.

Context-aware systems can be implemented in many ways. The typical approach considers a number of special requirements and conditions, such as location of sensors local or remote , number of possible users, available resources such as high-end personal computers or small mobile devices , and extensibility of the system.

Service selection in mobile environments: considering multiple users and context-awareness

Context-awareness models A context-awareness model is needed to define and store context information in a machine- readable form. Strang and Linnhoff-Popien 18 summarised the most relevant context-modelling approaches based on data structures used for representing and exchanging contextual information in their respective systems. These are highlighted below.


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  • Key-value models These represent the simplest data structure for context modelling. They are frequently used in various service frameworks, where key-value pairs are used to describe the capabilities of a service. Service discovery is then applied with matching algorithms which use these key-value pairs.

    TEDxRyersonU - Hossein Rahnama - Ubiquitous Systems: Evolution of Context Aware Computing

    Mark-up models These use a hierarchical data structure comprising mark-up tags, attributes and content to create profiles which represent a typical mark-up scheme model. Graphical models A number of approaches have been proposed where contextual aspects are modelled using Unified Modelling Language. Existing approaches use various objects to represent different context information such as temperature, location, etc. Access to the context and context-processing logic is provided by well-defined interfaces like the hydrogen model. A logic-based system is used to manage the aforementioned terms and allows addition, updating or removal of new facts.

    The inference also called reasoning process is used to derive new facts based on existing rules in the systems. Contextual information is then represented in a formal way as facts. These models are very promising for modelling contextual information due to their high and formal expressiveness and possibilities for applying ontology reasoning techniques.

    As an example, a car navigation system works very well if one is in a new city; however, when using it around a familiar area one may sometimes be surprised at the route it tries to direct one to. The sensory perception e. In the new place you lack reference points, and the memory and experience parts in the model differ significantly. In the familiar environment you will have expectations about which route to take and which would be a good choice. In the unfamiliar environment you lack experience and reference points, and hence your expectation is simply that the system will guide you to your destination.

    The result is that a navigation system that successfully guides you to your destination with a non-optimal route will satisfy your expectations in an unfamiliar environment, but be frowned upon in a familiar environment. In the familiar environment we have a substantial awareness mismatch, whereas when navigating in new surroundings we have minimal awareness mismatch.

    Context-aware development frameworks. The architecture was aimed at supporting gathering of context information about devices and users. Dey, Abowd and Wood 4 identified important features of context and context-awareness and some of the difficulties in building context-aware applications. Three main agent-based components were proposed: device agents that maintain the status and capabilities of devices; user agents that maintain user preferences; and active maps that maintain location information of devices and users. The proposed architecture did not support or provide guidelines for acquisition of context.