Showing papers on "Context awareness published in 2005"

Activity recognition from accelerometer data

Abstract: Activity recognition fits within the bigger framework of context awareness. In this paper, we report on our efforts to recognize user activity from accelerometer data. Activity recognition is formulated as a classification problem. Performance of base-level classifiers and meta-level classifiers is compared. Plurality Voting is found to perform consistently well across different settings.

The java context awareness framework (JCAF) – a service infrastructure and programming framework for context-aware applications

Abstract: Context-awareness is a key concept in ubiquitous computing. But to avoid developing dedicated context-awareness sub-systems for specific application areas there is a need for more generic programming frameworks. Such frameworks can help the programmer develop and deploy context-aware applications faster. This paper describes the Java Context-Awareness Framework – JCAF, which is a Java-based context-awareness infrastructure and programming API for creating context-aware computer applications. The paper presents the design goals of JCAF, its runtime architecture, and its programming model. The paper presents some applications of using JCAF in three different applications and discusses lessons learned from using JCAF.

On location models for ubiquitous computing

Abstract: Common queries regarding information processing in ubiquitous computing are based on the location of physical objects. No matter whether it is the next printer, next restaurant, or a friend is searched for, a notion of distances between objects is required. A search for all objects in a certain geographic area requires the possibility to define spatial ranges and spatial inclusion of locations. In this paper, we discuss general properties of symbolic and geometric coordinates. Based on that, we present an overview of existing location models allowing for position, range, and nearest neighbor queries. The location models are classified according to their suitability with respect to the query processing and the involved modeling effort along with other requirements. Besides an overview of existing location models and approaches, the classification of location models with respect to application requirements can assist developers in their design decisions.

Where am i: recognizing on-body positions of wearable sensors

Abstract: The paper describes a method that allows us to derive the location of an acceleration sensor placed on the user's body solely based on the sensor's signal The approach described here constitutes a first step in our work towards the use of sensors integrated in standard appliances and accessories carried by the user for complex context recognition It is also motivated by the fact that device location is an important context (eg glasses being worn vs glasses in a jacket pocket) Our method uses a (sensor) location and orientation invariant algorithm to identify time periods where the user is walking and then leverages the specific characteristics of walking motion to determine the location of the body-worn sensor In the paper we outline the relevance of sensor location recognition for appliance based context awareness and then describe the details of the method Finally, we present the results of an experimental study with six subjects and 90 walking sections spread over several hours indicating that reliable recognition is feasible The results are in the low nineties for frame by frame recognition and reach 100% for the more relevant event based case

Supporting pervasive learning environments: adaptability and context awareness in mobile learning

Abstract: In the mobile learning context, it is helpful to consider context awareness and adaptivity as two sides of the same coin. The purpose of the adaptivity and context awareness is to better support a variety of learners, given that they may have very different skills and motivations to learn in varying contexts. The recent research on adaptivity and context awareness has turned towards supporting pervasive environments and this is coupled with the increasing trend in seeing learning environments from an informal learning perspective. In this paper are presented experiences of developing an adaptive and context aware mobile learning system, with examples of other systems underlining the development towards supporting pervasive learning environments. We then consider approaches for the future development of systems supporting pervasive learning environments.

WildCAT: a generic framework for context-aware applications

Abstract: We present WildCAT, an extensible Java framework to ease the creation of context-aware applications. WildCAT provides a simple yet powerful dynamic model to represent an application's execution context. The context information can be accessed by application programmers through two complimentary interfaces: synchronous requests (pull mode) and asynchronous notifications (push mode). Internally, WildCAT is designed as a framework supporting different levels of extensions, from the simple configuration of the default generic implementation to completely new implementations tailored to specific needs. A given application can mix different implementations for different aspects of its context while only depending on WildCAT's simple and unified API.

Ambient Intelligence: The MyCampus Experience

Abstract: : Over the past five years, the MyCampus group at Carnegie Mellon University has been developing and experimenting with Ambient Intelligence technologies aimed at enhancing everyday life. The project has drawn on multiple areas of expertise, combining the development of an open Semantic Web infrastructure for context-aware service provisioning with an emphasis on issues of privacy and usability. In this paper, we review key motivations behind the project, discuss the MyCampus Semantic Web infrastructure and report on our experience tailoring the architecture for different environments "e.g. everyday campus life applications, office applications, museum tour guide". This includes a discussion of Semantic e-Wallets aimed at reconciling user demands for context awareness and privacy as well as a description of different context-aware applications developed and evaluated during the course of the project. We also discuss our experience using Case-Based Reasoning "CBR" functionality developed to overcome usability issues associated with capturing complex, context-sensitive user preferences. The paper concludes with a summary of lessons learned so far and of challenges still to be addressed.

An approach to data fusion for context awareness

Abstract: We propose and develop an approach modeled with multi-attribute utility theory for sensor fusion in context-aware environments. Our approach is distinguished from existing general purpose fusion techniques by a number of factors including a general underlying context model it is built upon and a set of heuristics it covers. The technique is developed for context-aware applications and we argue that it provides various advantages for data fusion in context-aware scenarios. We experimentally evaluate our approach with actual use cases using real sensors.

Digital libraries' support for the user's 'information journey'

Abstract: The temporal elements of users' information requirements are a continually confounding aspect of digital library design. No sooner have users' needs been identified and supported than they change. This paper evaluates the changing information requirements of users through their 'information journey' in two different domains (health and academia). In-depth analysis of findings from interviews, focus groups and observations of 150 users have identified three stages to this journey: information initiation, facilitation (or gathering) and interpretation. The study shows that, although digital libraries are supporting aspects of users' information facilitation, there are still requirements for them to better support users' overall information work in context. Users are poorly supported in the initiation phase, as they recognize their information needs, especially with regard to resource awareness; in this context, interactive press-alerts are discussed. Some users (especially clinicians and patients) also require support in the interpretation of information, both satisfying themselves that the information is trustworthy and understanding what it means for a particular individual.

Context for ubiquitous data management

Abstract: In response to the advance of ubiquitous computing technologies, we believe that for computer systems to be ubiquitous, they must be context-aware. In this paper, we address the impact of context-awareness on ubiquitous data management. To do this, we overview different characteristics of context in order to develop a clear understanding of context, as well as its implications and requirements for context-aware data management. References to recent research activities and applicable techniques are also provided.

Just-for-us: a context-aware mobile information system facilitating sociality

Abstract: Mobile computer technologies are increasingly being appropriated and used to facilitate people's social life outside the work domain. Addressing this emerging domain of use, we present the design of a context-aware mobile information system prototype facilitating sociality in public places: Just-for-Us. The design of the prototype system was informed by two empirical studies: an architectural analysis of a recently built public space in Melbourne, Australia and a field study of small groups socialising there. We describe these two studies and illustrate how findings informed our prototype design. Finally, we outline an ongoing field study of the use of the Just-for-Us prototype.

Context for Personalized Web Services

Abstract: The paper discusses the way context is used for Web services personalization. A Web service is an accessible application that other applications and humans can discover and trigger to satisfy various needs such as car rental. Context is the information that characterizes the interactions between humans, applications, and the surrounding environment. Web services are personalized so that users' preferences can be accommodated. Preferences are of different types varying from when the execution of a Web service should start to where the outcome of this execution should be delivered. Besides users' preferences, this paper highlights that the resources on which the Web services are performed have an impact on Web services personalization.

Bridging the gap between knowledge management and e-learning with context-aware corporate learning

Abstract: Knowledge management and e-learning both address the same fundamental problem: facilitating learning in organizations. But they approach the problem with two different paradigms, resulting in two different types of system. This paper proposes context awareness with respect to the learner’s or employee’s context as a solution to bridge the gap. The project Learning in Process is illustrating a step into that direction.

Context-aware implementation based on CBR for smart home

Abstract: Context awareness is emphasized in order to provide automatic services in smart home. This paper uses case based reasoning as the reasoning method which solves the problem "in the first phase, we don't know exactly about the key processes and their interdependencies in smart home's context". The context's contents in smart home are described in this paper. Also, case representation, case storage and similarity calculation are discussed in smart home's context awareness. We propose a framework of context aware based on CBR, and discuss the case adaptation in detail.

Bluetooth-based indoor proximity sensing for nursing context awareness

Abstract: This paper proposes a Bluetooth-based indoor proximity detection method for nursing context awareness. We exploit proximity between Bluetooth devices attached to people and objects for estimating 1) room-level proximity of people and objects, and 2) mutual proximity between moving people and objects. We show that the proximity information exchanged between several devices can be updated at a rate of more than 1 Hz by effectively choosing the timing parameters of Bluetooth inquiry mechanism. Empirical results of evaluating the receiver signal strength indicator (RSSI) at various distances between devices are also shown.

NAMA: a context-aware multi-agent based web service approach to proactive need identification for personalized reminder systems

Abstract: Developing a personalized, user-centric system is one of today's challenging issues in ubiquitous network-based systems, especially personalized reminder systems. Such a personalized reminder system has to identify the user's current needs dynamically and proactively based on the user's current context, such as location and current activity. However, need identification methodologies and their feasible architectures for personalized reminder systems have so far been rare. Hence, this paper aims to propose a proactive need identification mechanism by applying agent and semantic web technologies for a personalized reminder system, which is one of the supporting systems for a robust ubiquitous service support environment. We revisit associationism in order to understand a buyer's need identification process, and we adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have shown how an agent-based semantic web service system can be used to realize a personalized reminder system which identifies a buyer's need autonomously. We have created a prototype system, NAMA (Need Aware Multi-Agent), to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper. NAMA embeds a Bluetooth-based location-tracking module and identifies what users are currently looking at through their mobile devices. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services to discover the user's current needs and then link the user to a set of services, which are implemented as web services.

Context aware session management for services in ad hoc networks

Abstract: The increasing ubiquity of wireless mobile devices is promoting unprecedented levels of electronic collaboration among devices interoperating to achieve a common goal. Issues related to host interoperability are addressed partially by the service-oriented computing paradigm. However, certain technical concerns relating to reliable interactions among hosts in ad hoc networks have not yet received much attention. We introduce follow-me sessions, where interactions occur between a client and a service, rather than a specific provider or server. We allow the client to switch service providers, if needed. We exploit strategies involving the use of contextual information, strong process migration, context-sensitive binding, and location-agnostic communication protocols. We show how follow-me sessions mitigate issues related to proxy-based service-oriented architectures in ad hoc networks.

An adaptive middleware framework for context-aware applications

Abstract: We describe a middleware framework for the adaptive delivery of context information to context-aware applications. The framework abstracts the applications from the sensors that provide context. Further applications define utility functions on the quality of context attributes that describe the context providers. Then, given multiple alternatives for providing the same type of context, the middleware applies the utility function to each alternative and choose the one with maximum utility. By allowing applications to delegate the selection of context source to the middleware, our middleware can implement autonomic properties, such as self-configuration when new context providers appear and resilience to failures of context providers.

Classifying user environment for mobile applications using linear autoencoding of ambient audio

Abstract: Many mobile devices and applications can act in context-sensitive ways, but rely on explicit human action for context awareness. It would be preferable if our devices were able to attain context awareness without human intervention. One important aspect of user context is environment. We present a novel method for classifying environment types based on acoustic signals. This method makes use of linear autoencoding neural networks, and is motivated by the observation that biological coding systems seem to be heavily influenced by the statistics of their environments. We show that the autoencoder method achieved a lower error rate than a standard Gaussian mixture model on a representative sample task, and that a linear combination of autoencoders and GMMs yielded better performance than either alone.

Context-awareness in mobile tourist information systems: challenges for user interaction

Abstract: Context in mobile tourist information systems is typically captured as the current location of the user. Few systems consider the user’s interests or wider context of the sights. This paper explores ideas of how to model, observe, evaluate, and exploit a richer notion of context in this application area. We discuss the influence of such a richer context model on the user interaction for both the capturing of context and the context-aware user/device interactions.

Using activity theory to model context awareness

Abstract: One of the cornerstones of any intelligent entity is the ability to understand how occurrences in the surrounding world influence its own behaviour. Different states, or situations, in its environment should be taken into account when reasoning or acting. When dealing with different situations, context is the key element used to infer possible actions and information needs. The activities of the perceiving agent and other entities are arguably one of the most important features of a situation; this is equally true whether the agent is artificial or not. This work proposes the use of Activity Theory to first model context and further on populate the model for assessing situations in a pervasive computing environment. Through the socio-technical perspective given by Activity Theory, the knowledge intensive context model, utilised in our ambient intelligent system, is designed.

Loosely coupling ontological reasoning with an efficient middleware for context-awareness

Abstract: Context-awareness in mobile and ubiquitous computing requires the acquisition, representation and processing of information which goes beyond the device features, network status, and user location, to include semantically rich data, like user interests and user current activity. On the other hand, when services have to be provided on-the-fly to many mobile users, the efficiency of reasoning with these data becomes a relevant issue. Experimental evidence has lead us to consider currently impractical a tight integration of ontological reasoning with rule based reasoning at the time of request. This paper illustrates a hybrid approach where ontological reasoning is loosely coupled with the efficient rule-based reasoning of a middleware architecture for service adaptation. While rule-based reasoning is performed at the time of service request to evaluate adaptation policies and reconcile possibly conflicting context information, ontological reasoning is mostly performed asynchronously by local context providers to derive non-shallow context information. A limited form of ontological reasoning is activated at the time of request only when essential for service provisioning.

SAFE-RD (secure, adaptive, fault tolerant, and efficient resource discovery) in pervasive computing environments

Abstract: To facilitate thousands of hand held device users' lookup for services anywhere anytime, the importance of a resource discovery scheme in pervasive computing environments cannot be overlooked. The incorporation of security, adaptability, fault tolerance, and efficiency features is the quest for long but there is no existing resource discovery scheme that can be claimed as "the solution". In this paper, we propose the design of such a discovery mechanism named SAFE-RD, which is an integral part of our on-going research project MARKS (Adaptive Middleware for Resource discovery, Knowledge usability and Self-healing) with illustrative examples.

A location aware mobile tourist guide selecting and interpreting sights and services by context matching

Abstract: Most tourists exploring a destination either join a guided tour or walk on their own using maps. Neither are their individual preferences nor the actual situation considered. These tours are strongly inflexible. The ideal is an intelligent guide taking care of the whole tour organisation and execution in time. This is the main objective of the dynamic tour guide (DTG). The DTG is a mobile agent that selects attractions, plans an individual tour, provides navigational guidance and offers location based interpretation. This kind of ambient intelligence is based on the analysis of all available context information to support the tourist in any possible way with the help of a mobile device.

Designing a configurable services platform for mobile context‐aware applications

Abstract: Context-aware services platforms aim at supporting the handling of contextual information in order to provide better user-tailored services. This paper proposes a novel services platform architecture to support mobile context-aware applications, giving emphasis to the configurability of the platform’s generic functionality. The paper introduces concepts and a language to cope with configurability aspects. The paper also reports on the implementation of a prototype, which implements a Web services-based context-aware services platform that runs on top of 3G networks

Innovative Media in Support of Distributed Intelligence and Lifelong Learning

Abstract: Individual, unaided human abilities are constrained. Media have helped us to transcend boundaries in thinking, working, learning, and collaborating by supporting distributed intelligence. Wireless and mobile technologies provide new opportunities for empowering humans, but not without potential pitfalls. We explore these opportunities and pitfalls from a lifelong-learning perspective and discuss how wireless and mobile technologies can influence and change conceptual frameworks such as the relationship between planning and situated action, context awareness, human attention, distances in collaborative design activities, and the trade-off between tools for living and tools for learning. The impact of wireless and mobile technologies is illustrated with our research projects, which focus on moving "computing off the desktop" by "going small, large, and everywhere." Specific examples include human-centered public transportation systems, collaborative design, and information sharing with smart physical objects.

Redundant positioning architecture

Abstract: Positioning has been a driving factor in the development of ubiquitous computing applications throughout the past two decades. Numerous devices and techniques have been developed-few of them are actually used commercially. The precision is limited to specific applications, the availability limited to the provider of specific services. Occasionally, few methods have been combined to recalibrate each other by means of data fusion. We present a novel architecture for processing the vast amount of data from pervasive devices penetrating everyday objects to the cheapest level. Location information can be inferred from infrastructure deployed for different purposes, only partly designed for positioning in the first place. The massive redundancy of such nodes and the synergetic heterogeneity of completely different recognition principles allows to tailor the perceived positioning probability to the specific requirements of the target application. A self-learning and self-healing approach to misleading, wrong and outdated pieces of information provides a new quality of interworking position and context aware systems.

A Privacy Service for Context-aware Mobile Computing

Abstract: Privacy issues related to the access of context information are becoming increasingly important as we move toward ubiquitous and mobile computing environments. In this article, we describe the design and implementation of a privacy service, called Context Privacy Service (CoPS), to control how, when and to whom disclose a user’s context information. Based on the results of an end-user survey and experience reported by other research groups, we identified the main service requirements and designed CoPS aiming flexibility, generality, simplicity and fine-grained privacy control. CoPS is an optional service of our context-provisioning middleware MoCA and allows users of context- and location-aware applications to define and manage their privacy policies regarding disclosure of their context information. The main features supported by CoPS are group-based access control, pessimistic and optimistic approaches for access control, hierarchical privacy rules, mixed-initiative interaction, and rule specificity analysis.

Blackboard-based software framework and tool for mobile device context awareness

Abstract: The usage needs of a mobile device vary according to context. Mobile context awareness research aims at providing the device user with a way of usage that suits the situation. Interaction based on context requires acquiring, abstracting and delivering information from multiple sources, such as sensors, to the application or application control. A generic software framework and tool for facilitating the rapid development of mobile device context-aware applications were developed in this work. The blackboard-based framework supports all tasks that are required for context-based application control, where contexts can be any events that are relevant to user interaction with the application, including explicit inputs. The core component of the framework, Context Manager, provides a publish and subscribe mechanism and a database for the applications and application control. The framework provides an application programming interface (API) for developers. As a higher abstraction-level programming interface, a customization tool enables easy end-user development of contextaware features into existing applications without changing them. An extensible ontology is used as a uniform context representation within the framework. The purpose of the ontology, together with the API, is to enable easy access, use and reuse of human-understandable context information. Context information sources, such as sensors, often produce a continuous stream of low abstraction-level data. The framework supports the transformation of a continuous data stream into abstracted context events, described in the ontology. Context information is delivered to applications or application control as abstracted events. The main result of the dissertation is a software framework, ontology and tool, which facilitate the customization of sensor-based humancomputer interaction in mobile devices. The practical applicability, scope, and computational efficiency of the implemented framework and customization tool are evaluated with performance measurements and multiple applications implemented in a mobile phone with real sensor sources.

Towards situation-awareness and ubiquitous data mining for road safety: rationale and architecture for a compelling application

Abstract: Road crashes cost Australia $15 billion a year and 95% of these are attributed to drivers' errors. Risk assessment is at the core of the road safety problem. This paper presents an Advanced Driving Assistance System (ADAS), called SAWUR, that analyses situational driver behaviour and proposes real-time countermeasures to minimise fatalities/ casualties. The system is based on Ubiquitous Data Mining (UDM) concepts. It fuses and analyses different types of information from crash data and physiological sensors to diagnose driving risks in real-time. The novelty of our approach consists of augmenting the diagnosis through UDM with associated countermeasures based on a context awareness mechanism. In other words, our system diagnoses and chooses a countermeasure by taking into account the contextual situation of the driver and the road conditions. The types of context we exploit include vehicle dynamics, drivers' physiological condition, driver's profile and environmental conditions. The rationale for exploiting contextual information is to increase the accuracy of the diagnosis (90%) and to reduce false alarm rates (below 1%). The ultimate goal is to decrease driver's exposure to risks.