Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity). Since it was proposed about a decade ago, many researchers have studied this topic and built several context-aware applications to demonstrate the usefulness of this new technology. Context-aware applications (or the system infrastructure to support them), however, have never been widely available to everyday users. In this survey of research on context-aware systems and applications, we looked in depth at the types of context used and models of context information, at systems that support collecting and disseminating context, and at applications that adapt to the changing context. Through this survey, it is clear that context-aware research is an old but rich area for research. The difficulties and possible solutions we outline serve as guidance for researchers hoping to make context-aware computing a reality. 1.

We describe the Conference Assistant, a prototype mobile, context-aware application that assists conference attendees. We discuss the strong relationship between context-awareness and wearable computing and apply this relationship in the Conference Assistant. The application uses a wide variety of context and enhances user interactions with both the environment and other users. We describe how the application is used and the context-aware architecture on which it is based. 1. Introduction In human-human interaction, a great deal of information is conveyed without explicit communication, but rather by using cues. These shared cues, or context, help to facilitate grounding between participants in an interaction [3]. We define context to be any information that can be used to characterize the situation of an entity, where an entity can be a person, place, or physical or computational object. In human--computer interaction, there is very little shared context between the human and the co...

Pervasive computing applications are increasingly leveraging contextual information from several sources to provide users with behavior appropriate to the environment in which they reside. If these sources of contextual information are used and deployed in an ad hoc manner, however, they may provide overlapping functionality, fail to provide needed functionality, and require the use of inconsistent interfaces by applications. To overcome these problems, we introduce a Contextual Information Service that provides applications with contextual information via a virtual database. Unlike previous efforts, our service provides applications a consistent, lightweight, and powerful mechanism for obtaining contextual information, and includes explicit support for the on demand computation of contextual information. We show, via example applications and a Contextual Information Service prototype that we have implemented, how this approach can be used to allow proactive applications to adapt their behavior to match a user’s current environment.

Ubiquitous computing applications are increasingly leveraging contextual information from several sources to provide users with behavior appropriate to the environment in which they reside. If these sources of contextual information are used and deployed in an ad hoc manner, however, they may provide overlapping functionality, fail to provide needed functionality, and require the use of inconsistent interfaces by applications. To overcome these problems, we introduce a concise organization of services and a single service interface that provide applications with contextual information in a unified manner. We show, via example applications and services that we have implemented, how our service organization and interface can be used to allow proactive applications to adapt their behavior to match a user's current environment.

this paper, we present a process and a software mechanism that support context changes for plastic user interfaces. We propose to structure adaptation as a three-step process: recognition of the situation, computation of a reaction to cope with the situation, and execution of the reaction. Reactions are specified in an evolution model which, in turn, is executed by a context supervisor. This supervisor is notified of context changes by a software probe that automatically detects deviations from the current situation. When notified, the supervisor executes the evolution model, and, when possible, adapts the user interface to the new context of use. Keywords: human computer interaction, plasticity, adaptation, context of use, platform, environment. 1 Introduction Recent years have seen the introduction of many types of access devices including Personal Digital Assistants (PDAs) and mobile phones (cf. Figure 1). Systems like CyberGuide (Abowd et al., 19

Abstract. Today a variety of terms – like Ubiquitous Computing, Pervasive Computing, Invisible Computing, Ambient Intelligence, Sentient Computing, Post-PC Computing, etc. – refers to new challenges and paradigms for the interaction among users and mobile and embedded computing devices. Fertilized by a vast quantitative growth of the Internet over the past years and a growing availability of wireless communication technologies in the wide, local and personal area, a ubiquitous use of “embedded ” information technologies is evolving. Most of the services delivered through those new technologies are services adapted to context, particularly to the person, the time and the place of their use. The aim for seamless service provision to anyone (personalized services), at any place (location based services) and at any time (time dependent services) has brought the issues of software framework design and middleware to a new discussion: it is expected that context-aware services will evolve, enabled by wirelessly ad-hoc networked, autonomous special purpose computing devices (i.e. “smart appliances”), providing largely invisible

Abstract. Service discovery is a process of locating, or discovering, one or more documents, that describe a particular service. Most of the current service discovery approaches perform syntactic matching, that is, they retrieve services descriptions that contain particular keywords from the user’s query. This often leads to poor discovery results, because the keywords in the query can be semantically similar but syntactically different, or syntactically similar but semantically different from the terms in a service description. Another drawback of the existing service discovery mechanisms is that the query-service matching score is calculated taking into account only the keywords from the user’s query and the terms in the service descriptions. Thus, regardless of the context of the service user and the context of the services providers, the same list of results is returned in response to a particular query. This paper presents a novel approach for service discovery that uses ontologies to capture the semantics of the user’s query, of the services and of the contextual information that is considered relevant in the matching process. 1

It is widely accepted in the Pervasive Computing community that contextual interactions are the key to the delivery of truly calm technology. However, there is currently no easy way to incorporate contextual data into an application. If contextual data is used, it is generally in an ad hoc manner, which means that developers have to spend time on low-level details. There have been many projects investigating this area, however as yet none of them provide support for all of the key issues of dynamic composition and flexible representation of contextual information as well as the problems of scalability and adaptability to environmental changes. In this paper we present the Strathclyde Context Infrastructure (SCI), a middleware infrastructure for discovery, aggregation, and delivery of context information. 1.

Abstract. Inevitably, healthcare goes mobile. Recently developed mobile healthcare (i.e. m-health) services allow healthcare professionals to monitor mobile patient’s vital signs and provide feedback to this patient anywhere at any time. Due to the nature of current supporting mobile service platforms, mhealth services are delivered with a best-effort, i.e., there are no guarantees on the delivered quality of service (QoS). In this paper, we argue that the use of context information in an m-health service platform improves the delivered QoS. We give a first attempt to merge context information with a QoS-aware mobile service platform in the m-health services domain. We illustrate this with an epilepsy tele-monitoring scenario. 1

Events are real-world occurrences that unfold over space and time. Event mining from multimedia streams improves the access and reuse of large media collections, and it has been an active area of research with notable recent progress. This paper contains a survey on the problems and solutions in event mining, approached from three aspects: event description, event-modeling components, and current event mining systems. We present a general characterization of multimedia events, motivated by the maxim of five BW[s and one BH [ for reporting real-world events in journalism: when, where, who, what, why, and how. We discuss the causes for semantic variability in real-world descriptions, including multilevel