Modelling and Adapting to Context

One of the hardest points in context-aware applications is deciding what reactions a system has to a certain context. In this paper, we introduce an architecture used in two context-aware museum guides. We discuss how the context is modelled and we briefly present a rule-based mechanism to trigger system actions. A rule-based system offers the flexibility required to be context-sensitive in the broadest sense since many context features can be considered and evaluated at the same time. This architecture is very flexible and easily supports a fast prototyping approach.     

Building Distributed Context-Aware Applications

Context-aware applications gather information from sensors about their users and operating environment. Sensor handling is a complicated issue that makes it hard and time-consuming to develop context-aware applications. This paper shows how dynamic discovery protocols can be employed to deal with the physical distribution of sensors and the need to share sensors between many applications. We report on our experiences from building a position-aware application using the dynamic discovery protocol that is part of the Jini software infrastructure for distributed systems.     

A portable toolkit for supporting end-user personalization and control in context-aware applications

A context-aware application in the pervasive computing environment provides intuitive user centric services using implicit context cues. Personalization and control are important issues for this class of application as they enable end-users to understand and configure the behavior of an application. However most development efforts for building context-aware applications focus on the sensor fusion and machine learning algorithms to generate and distribute context cues that drive the application with little emphasis on user-centric issues. We argue that, to elevate user experiences with context-aware applications, it is very important to address these personalization and control issues at the system interface level in parallel to context centric design. Towards this direction, we present Persona, a toolkit that provides support for extending context-aware applications with end-user personalization and control features. Specifically, Persona exposes a few application programming interfaces that abstract end-user customization and control mechanisms and enables developers to integrate these user-centric aspects with rest of the application seamlessly. There are two primary advantages of Persona. First, it can be used with various existing middlewares as a ready-to-use plug-in to build customizable and controllable context-aware applications. Second, existing context-aware applications can easily be augmented to provide end-user personalization and control support. In this paper, we discuss the design and implementation of Persona and demonstrate its usefulness through the development and augmentation of a range of common context-aware applications.     

Accessing Context in Wearable Computers

We present an easy interaction technique for accessing location-based contextual data shown on a head-worn wearable computer display. Our technique, called Context Compass, is based on a regular compass metaphor. Each object belonging to the user’s current context is visualised on a linear compass shown on the screen. The object directly in front of the user is shown in the middle of the compass and can be activated. Whenever the user turns his or her head, the objects on the screen move accordingly. Therefore, an object can be selected by simply turning one’s head towards it. Context Compass consumes a minimal amount of screen space, making it ideal for usage with see-through head-worn displays. An initial pilot study, applying a newly developed usability method customised especially for Context Compass, revealed that Context Compass can be learned virtually immediately. Further, the method itself proved to be successful in evaluating techniques such as Context Compass.     

Exploring Context-aware Information Push

Despite much interest over recent years in the area of context-aware computing, there are still a number of significant gaps in our understanding of the HCI issues associated with such systems. One particular issue that remains relatively unexplored is how to design around the apparently conflicting goals of adapting to changes in context while at the same time adhering to the principle of predictability. In this paper, we describe our exploration into this issue through two alternative designs of an interactive context-aware tourist guide. One original design was based around information pull, i.e. the emphasis is on the user to decide when context-aware information is presented. Our second design incorporates the notion of information push whereby the actual presentation of context-aware information is triggered by contextual events, e.g. changes in the user’s location or changes to the opening times of attractions. Through the evaluation of these alternative designs we hope to gain a better understanding of the usability implications relating to push vs. pull in both this specific domain and in interactive context-aware systems in general.     

Metaphors and Context-Aware Information Access

Metaphors are often used to provide the user with a mental model to ease the use of computers. An example of such a metaphor is the commonly used “Desktop Metaphor”. Metaphors also can be used to ease context-aware information access for the users of mobile information systems. In this paper we present a taxonomy that allows the categorisation of such metaphors. Furthermore, we give an overview of existing metaphors and their implementations. After introducing some new metaphors we conclude our considerations with a classification of new and existing metaphors using our taxonomy.     

Modeling adaptive behaviors in Context UNITY

Context-aware computing refers to a paradigm in which applications sense aspects of the environment and use this information to adjust their behavior in response to changing circumstances. In this paper, we present a formal model and notation (Context UNITY) for expressing quintessential aspects of context-aware computations; existential quantification, for instance, proves to be highly effective in capturing the notion of discovery in open systems. Furthermore, Context UNITY treats context in a manner that is relative to the specific needs of an individual application and promotes an approach to context maintenance that is transparent to the application. In this paper, we construct the model from first principles, introduce its proof logic, and demonstrate how the model can be used as an effective abstraction tool for context-aware applications and middleware.     

Uncertain inference control in privacy protection

Context management is the key enabler for emerging context-aware applications, and it includes context acquisition, understanding and exchanging. Context exchanging should be made privacy-conscious. We can specify privacy preferences to limit the disclosure of sensitive contexts, but the sensitive contexts could still be derived from those insensitive. To date, there have been very few inference control mechanisms for context management, especially when the environments are uncertain. In this paper, we present an inference control method for private context protection in uncertain environments.     

2PSM: an efficient framework for searching video information in a limited-bandwidth environment

We present a novel technique, called 2-Phase Service Model, for streaming videos to home users in a limited-bandwidth environment. This scheme first delivers some number of non-adjacent data fragments to the client in Phase 1. The missing fragments are then transmitted in Phase 2 as the client is playing back the video. This approach offers many benefits. The isochronous bandwidth required for Phase 2 can be controlled within the capability of the transport medium. The data fragments received during Phase 1 can be used to provide an excellent preview of the video. They can also be used to facilitate VCR-style operations such as fast-forward and fast-reverse. Systems designed based on this method are less expensive because the fast-forward and fast-reverse versions of the video files are no longer needed. Eliminating these files also improves system performance because mapping between the regular files and their fast-forward and fast-reverse versions is no longer part of the VCR operations. Furthermore, since each client machine handles its own VCR-style interaction, this technique is very scalable. We provide simulation results to show that 2-Phase Service Model is able to handle VCR functions efficiently. We also implement a video player called {\em FRVplayer}. With this prototype, we are able to judge that the visual quality of the previews and VCR-style operations is excellent. These features are essential to many important applications. We discuss the application of FRVplayer in the design of a video management system, called VideoCenter. This system is intended for Internet applications such as digital video libraries.     

The ALIVE system: wireless, full-body interaction with autonomous agents

The cumbersome nature of wired interfaces often limits the range of application of virtual environments. In this paper, we discuss the design and implementation of a novel system, called ALIVE, which allows unencumbered full-body interaction between a human participant and a rich graphical world inhabited by autonomous agents. Based on results obtained with thousands of users, the paper argues that this kind of system can provide more complex and very different experiences than traditional virtual reality systems. The ALIVE system significantly broadens the range of potential applications of virtual reality systems; in particular, the paper discusses novel applications in the area of training and teaching, entertainment, and digital assistants or interface agents. We give an overview of the methods used in the implementation of the existing ALIVE systems.     

Modelling both the Context and the User

Research into context-aware computing risks losing sight of the user. This paper discusses how different types of information about a user, ranging from information about the current context to information about the user’s long-term properties, can simultaneously be relevant to a given adaptation decision. Pointers are given to two areas of research that can help with the integration of a broader range of information into context-aware systems: research on user-adaptive systems and on decision-theoretic methods.     

Context data management: an architectural framework for context-aware services

Mobile devices are equipped with increasing processing power and sensing capabilities, and mobile services can benefit from these features to provide a more personalized and context-aware experience to final users. To efficiently collect and deliver context information, a proper architecture is required, where heterogeneous context information can be processed to provide higher-level context information, context data are represented uniformly, and applications can process context data with high-level queries. This paper fulfils this goal of interoperability and domain independence by defining a framework for context data management relying on open standards (XMPP and REST), acting as an enabler for third-party context-aware applications; other main novelties of our work are the definition of a ContextML for standard context data representation, and a Context Query Language (CQL) to access context information based on high-level data filtering.     

Context-aware Retrieval: Exploring a New Environment for Information Retrieval and Information Filtering

The opportunities for context-aware computing are fast expanding. Computing systems can be made aware of their environment by monitoring attributes such as their current location, the current time, the weather, or nearby equipment and users. Context-aware computing often involves retrieval of information: it introduces a new aspect to technologies for information delivery; currently these technologies are based mainly on contemporary approaches to information retrieval and information filtering. In this paper, we consider how the closely related, but distinct, topics of information retrieval and information filtering relate to context-aware retrieval. Our thesis is that context-aware retrieval is as yet a sparsely researched and sparsely understood area, and we aim in this paper to make a start towards remedying this.     

Toward an OSGi-based infrastructure for context-aware applications

Applications and services must adapt to changing contexts in dynamic environments. However, building context-aware applications is still complex and time-consuming due to inadequate infrastructure support. We propose a context-aware infrastructure for building and rapidly prototyping such applications in a smart-home environment. This OSGi-based infrastructure manages context-aware services reliably and securely and efficiently supports context acquisition, discovery, and reasoning. A formal, ontology-based context model enables semantic context representation, reasoning, and knowledge sharing. We propose an ontology-based context model that leverages Semantic Web technology and OWL (Web Ontology Language). OWL is an ontology markup language that enables context sharing and context reasoning. Based on our context model, we also propose a service-oriented context-aware middleware (SOCAM) architecture, including a set of independent services that perform context discovery, acquisition, and interpretation.     

There is more to context than location

Context is a key issue in interaction between human and computer, describing the surrounding facts that add meaning. In mobile computing location is usually used to approximate context and to implement context-aware applications. We propose that ultra-mobile computing, characterized by devices that are operational and operated while on the move (e.g. PDAs, mobile phones, wearable computers), can significantly benefit from a wider notion of context. To structure the field we introduce a working model for context, discuss mechanisms to acquire context beyond location, and application of context-awareness in ultra-mobile computing. We investigate the utility of sensors for context-awareness and present two prototypical implementations — a light-sensitive display and an orientation-aware PDA interface. The concept is then extended to a model for sensor fusion to enable more sophisticated context recognition. Based on an implementation of the model an experiment is described and the feasibility of the approach is demonstrated. Further, we explore fusion of sensors for acquisition of information on more sophisticated contexts.     

TRIP: A Low-Cost Vision-Based Location System for Ubiquitous Computing

Sentient Computing provides computers with perception so that they can react and provide assistance to user activities. Physical spaces are made sentient when they are wired with networks of sensors capturing context data, which is communicated to computing devices spread through the environment. These devices interpret the information provided and react by performing the actions expected by the user. Among the types of context information provided by sensors, location has proven to be especially useful. Since location is an important context that changes whenever the user moves, a reliable location-tracking system is critical to many sentient applications. However, the sensor technologies used in indoor location tracking are expensive and complex to deploy, configure and maintain. These factors have prevented a wider adoption of Sentient Computing in our living and working spaces. This paper presents TRIP, a low-cost and easily deployable vision-based sensor technology addressing these issues. TRIP employs off-the-shelf hardware (low-cost CCD cameras and PCs) and printable 2-D circular markers for entity identification and location. The usability of TRIP is illustrated through the implementation of several sentient applications.     

An experimental analysis of digital video library servers

Much work on video servers has concentrated on movies on demand, in which a relatively small number of titles are viewed and users are given basic VCR-style controls. This paper concentrates on analyzing video server performance for non-linear access applications. In particular, we study two non-linear video applications: video libraries, in which users select from a large collection of videos and may be interested in viewing only a small part of the title; and video walk-throughs, in which users can move through an image-mapped representation of a space. We present a characterization of the workloads of these applications. Our simulation studies show that video server architectures developed for movies on demand can be adapted to video library usage, though caching is less effective and the server can support a smaller user population for non-linear video applications. We also show that video walk-throughs require extremely large amounts of RAM buffering to provide adequate performance for even a small number of users.     

Integrating ontologies and thesauri for RDF schema creation and metadata querying

In this paper we present a new approach for building metadata schemas by integrating existing ontologies and structured vocabularies (thesauri). This integration is based on the specification of inclusion relationships between thesaurus terms and ontology concepts and results in application-specific metadata schemas incorporating the structural views of ontologies and the deep classification schemes provided by thesauri. We will also show how the result of this integration can be used for RDF schema creation and metadata querying. In our context, (metadata) queries exploit the inclusion semantics of term relationships, which introduces some recursion. We will present a fairly simple database-oriented solution for querying such metadata which avoids a (recursive) tree traversal and is based on a linear encoding of thesaurus hierarchies. Published online: 22 September 2000     

Database indexing for large DNA and protein sequence collections

Our aim is to develop new database technologies for the approximate matching of unstructured string data using indexes. We explore the potential of the suffix tree data structure in this context. We present a new method of building suffix trees, allowing us to build trees in excess of RAM size, which has hitherto not been possible. We show that this method performs in practice as well as the O(n) method of Ukkonen [70]. Using this method we build indexes for 200 Mb of protein and 300 Mbp of DNA, whose disk-image exceeds the available RAM. We show experimentally that suffix trees can be effectively used in approximate string matching with biological data. For a range of query lengths and error bounds the suffix tree reduces the size of the unoptimised O(mn) dynamic programming calculation required in the evaluation of string similarity, and the gain from indexing increases with index size. In the indexes we built this reduction is significant, and less than 0.3% of the expected matrix is evaluated. We detail the requirements for further database and algorithmic research to support efficient use of large suffix indexes in biological applications. Received: November 1, 2001 / Accepted: March 2, 2002 Published online: September 25, 2002