Showing papers on "Context awareness published in 2008"

Activity Recognition for the Smart Hospital

Abstract: Although researchers have developed robust approaches for estimating, location, and user identity, estimating user activities has proven much more challenging. Human activities are so complex and dynamic that it's often unclear what information is even relevant for modeling activities. Robust approaches to recognize user activities requires identifying the relevant information to be sensed and the appropriate sensing technologies. In our effort to develop an approach for automatically estimating hospital-staff activities, we trained a discrete hidden Markov model (HMM) to map contextual information to a user activity. We trained the model and evaluated it using data captured from almost 200 hours of detailed observation and documentation of hospital workers. In this article, we discuss our approach, the results, and how activity recognition could empower our vision of the hospital as a smart environment.

Location and Context Awareness

Abstract: These proceedings contain the papers presented at the 2nd International Workshop on Location- and Context-Awareness in May of 2006. As computing moves increasingly into the everyday world, the importance of location and context knowledge grows. The range of contexts encountered while sitting at a desk working on a computer is very limited compared to the large variety of situations experienced away from the desktop. For computing to be relevant and useful in these situations, the computers must have knowledge of the user’s activity, resources, state of mind, and goals, i.e. the user’s context, of which location is an important indicator. This workshop is intended to present research aimed at sensing, inferring, and using location and context data in ways that help the user. Our call for papers resulted in 74 submissions, each of which was assigned to members of our program committee. After reviews and email discussion, we selected 18 papers for publication in these proceedings. Most of the accepted papers underwent a shepherding process by a reviewer or a member of the program committee to ensure that the reviewers’ comments were accounted for in the published version. We feel our selective review process and shepherding phase has resulted in a high quality set of published papers.

Modeling contextual security policies

Abstract: As computer infrastructures become more complex, security models must provide means to handle more flexible and dynamic requirements. In the Organization Based Access Control (OrBAC) model, it is possible to express such requirements using the notion of context. In OrBAC, each security rule (permission, prohibition, obligation or dispensation) only applies in a given context. A context is viewed as an extra condition that must be satisfied to activate a given security rule. In this paper, we present a taxonomy of different types of context and investigate the data the information system must manage in order to deal with these different contexts. We then explain how to model and evaluate them in the OrBAC model.

Toward a General Software Infrastructure for Ubiquitous Computing

Abstract: This general software architecture is designed to support ubiquitous computing's fundamental challenges, helping the community develop and assess middleware and frameworks for this area.

Toward interactive mobile synchronous learning environment with context-awareness service

Abstract: Mobile synchronous learning is a new challenge in the e-learning domain. While popular mobile communication devices, such as cell phones, cannot directly accommodate traditional synchronous content due to the major limitation of display size, other constraints also restrict convenient interactions while using mobile devices in a synchronous learning environment. These problems have motivated the authors of this study to design a context-awareness synchronous learning system and to develop a corresponding pedagogical framework. Different than existing synchronous learning strategies, the proposed system enhances the feedback mechanism and implements an enhanced model for achieving mobile interaction in a synchronous learning environment. The enhanced model is named Interactive Service Module, which enables interactions between teachers and students via short message delivery. In the proposed synchronous learning environment, different kinds of learning devices are used to access the same source of synchronous content simultaneously. To accommodate the diversity of devices, several content styles have been developed and an appropriate style can be selected to a learner via a decision mechanism. This mechanism is based on fuzzy weighted average technique to measure the average computational power for each device. Finally, questionnaires were used to evaluate the usability of the proposed synchronous learning environment, and the results indicate that our system can facilitate synchronous learning by enabling students to access lessons conveniently and efficiently from a wide variety of locations, using common mobile communication devices.

A comprehensive context modeling framework for pervasive computing systems

Abstract: Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.

An Autonomic Context Management System for Pervasive Computing

Abstract: Context-aware applications adapt to changing computing environments or changing user circumstances/tasks. Context information that supports such adaptations is provided by the underlying infrastructure, which gathers, pre-processes and provisions context information from a variety of context information sources. Such an infrastructure is prone to failures and disconnections that negatively impact on the ability of context-aware applications to adapt (and therefore dramatically impact on their usability). This paper describes a model-based autonomic context management system (ACoMS) that can dynamically configure and reconfigure its context information gathering and pre-processing functionality in order to provide fault tolerant provisioning of context information. The approach uses standards based descriptions of context information sources to increase openness, interoperability and scalability of context-aware systems.

Secure Data Flow in a Calculus for Context Awareness

Abstract: We present a Mobile-Ambients-based process calculus to describe context-aware computing in an infrastructure-based Ubiquitous Computing setting. In our calculus, computing agents can provide and discover contextual information and are owners of security policies. Simple access control to contextual information is not sufficient to insure confidentiality in Global Computing, therefore our security policies regulate agents' rights to the provision and discovery of contextual information over distributed flows of actions. A type system enforcing security policies by a combination of static and dynamic checking of mobile agents is provided, together with its type soundness.

Using Annotation Services in a Ubiquitous Jigsaw Cooperative Learning Environment.

Abstract: This study describes the development of a ubiquitous cooperative learning environment using proposed annotation services, wireless communication devices, and the Jigsaw method of cooperative learning. The purpose of the study is to investigate the potential benefits of studying digital course materials with embedded annotations. The SQ3R study method is introduced during the individual study phase of a series of Jigsaw learning activities, enabling students to access and familiarize themselves with course content. In this phase, learners use the SQ3R method to enhance the quality of their annotations. It is noted that during this phase, individual students worked in separate locations. After the individual study phase, an expert group meeting process refines the annotations made by student experts and then the annotations discussed are provided to all members of the Jigsaw group during the group meeting phase. Importantly, annotations from different levels of literal meaning and connotation are assigned to different learners to help the group members develop a greater sense of context awareness of the different aspects of the topics under study. Analysis of data collected from questionnaires given to participants at the end of the study indicates that the proposed annotation services using handheld devices can enhance students' learning potential. The results also indicate the suitability and practicality of annotation services in an ubiquitous Jigsaw cooperative learning environment.

Issues in data fusion for healthcare monitoring

Abstract: Pervasive healthcare monitoring using body sensors and wireless sensor networks is a rapidly growing area in healthcare monitoring applications. Several issues arise in these systems, such as complex distributed data processing, data fusion, unreliable data communication, and uncertainty of data analysis in order to successfully monitor patients in real time. In this paper, we introduce some of the important issues in healthcare monitoring with focus on software problems such as reliability, network robustness, and context awareness. We describe related works in data filtering, data fusion, and data analysis then we suggest new architecture for handling data cleaning, data fusion, and context and knowledge generation using multi-tiered communication and a triadic hierarchical class analysis approach. The proposed architecture is called "Pervasive Healthcare Architecture" and we discuss how it can be applied to a particular monitoring scenario.

Location Systems: An Introduction to the Technology Behind Location Awareness

Abstract: Advances in electronic location technology and the coming of age of mobile computing have opened the door for location-aware applications to permeate all aspects of everyday life. Location is at the core of a large number of high-value applications ranging from the life-and-death context of emergency response to serendipitous social meet-ups. For example, the market for GPS products and services alone is expected to grow to US$200 billion by 2015. Unfortunately, there is no single location technology that is good for every situation and exhibits high accuracy, low cost, and universal coverage. In fact, high accuracy and good coverage seldom coexist, and when they do, it comes at an extreme cost. Instead, the modern localization landscape is a kaleidoscope of location systems based on a multitude of different technologies including satellite, mobile telephony, 802.11, ultrasound, and infrared among others. This lecture introduces researchers and developers to the most popular technolog es and systems for location estimation and the challenges and opportunities that accompany their use. For each technology, we discuss the history of its development, the various systems that are based on it, and their trade-offs and their effects on cost and performance. We also describe technology-independent algorithms that are commonly used to smooth streams of location estimates and improve the accuracy of object tracking. Finally, we provide an overview of the wide variety of application domains where location plays a key role, and discuss opportunities and new technologies on the horizon. Table of Contents: Introduction / The Global Positioning System / Infrared and Ultrasonic Systems / Location Esimation with 802.11 / Cellular-Based Systems / Other Approaches / Improving Localization Accuracy / Location-Based Applications and Services / Challenges and Opportunities / References

Activity-Based Computing

Abstract: The articles in this special issue focus on context-aware systems designed to recognize activities. They present underlying technologies for developing activity-aware systems and report on experiences with activity recognition in real-world applications.

Multiple-Agent Perspectives in Reasoning About Situations for Context-Aware Pervasive Computing Systems

Abstract: In open heterogeneous context-aware pervasive computing systems, suitable context models and reasoning approaches are necessary to enable collaboration and distributed reasoning among agents. This paper proposes, develops, and demonstrates the following: 1) a novel context model and reasoning approach developed with concepts from the state-space model, which describes context and situations as geometrical structures in a multidimensional space; and 2) a context algebra based on the model, which enables distributed reasoning by merging and partitioning context models that represent different perspectives of computing entities over the object of reasoning. We show how merging and reconciling different points of view over context enhances the outcomes of reasoning about the context. We develop and evaluate our proposed algebraic operators and reasoning approaches with cases using real sensors and with simulations. We embed agents and mobile agents with these modeling and reasoning capabilities, thus facilitating context-aware and adaptive mobile agents operating in open pervasive environments.

Proactive Fuzzy Control and Adaptation Methods for Smart Homes

Abstract: Proactive, context-aware computing isn't new. In 2000, David Tennenhouse called for a change in the boundary between the physical and virtual worlds. He identified proactive computing as an alternative to interactive computing and defined how future systems should become more involved with the real world. He also considered context-aware control systems with online adaptation especially promising. Today, ambient-intelligence researchers show increasing interest in both proactive applications and context-aware applications. Using different context-recognition methods, researchers can easily gather application-specific information from the environment and enable context-triggered actions. According to Hee Eon Byun and Keith Cheverst, a context-aware home can serve its inhabitants more flexibly and adaptively than an ordinary home. They also claim that proactive systems can be built using machine-learning algorithms with context recognition. In addition to context recognition, adaptivity is essential in intelligent environments. In terms of computing systems, the environment can adjust itself using adaptation mechanisms to comply with user preferences; it can become unobtrusive and better support user activities. A home adapting to its inhabitants' living style is much more convenient than a user adapting to the home's behavior. In this article, we show how to develop a proactive, adaptive, fuzzy home-control system, present the algorithm we used for adaptation, and evaluate the test results we obtained.

Model-based fault detection in context-aware adaptive applications

Abstract: Applications running on mobile devices are heavily context-aware and adaptive, leading to new analysis and testing challenges as streams of context values drive these applications to undesired configurations that are not easily exposed by existing validation techniques. We address this challenge by employing a finite-state model of adaptive behavior to enable the detection of faults caused by (1) erroneous adaptation logic, and (2) asynchronous updating of context information, which leads to inconsistencies between the external physical context and its internal representation within an application. We identify a number of adaptation fault patterns, each describing a class of faulty behaviors that we detect automatically by analyzing the system's adaptation model. We illustrate our approach on a simple but realistic application in which a cellphone's configuration profile is changed automatically based on the user's location, speed and surrounding environment.

A context aware handheld wayfinding system for individuals with cognitive impairments

Abstract: A challenge to individuals with cognitive impairments in wayfinding is how to remain oriented, recall routines, and travel in unfamiliar areas in a way relying on limited cognitive capacity. According to psychological model of spatial navigation and the requirements of rehabilitation professionals, a novel wayfinding system is presented with an aim to increase workplace and life independence for people suffering from diseases such as traumatic brain injury, cerebral palsy, mental retardation, schizophrenia, Down syndromes, and Alzheimer's disease. This paper describes an approach to providing distributed cognition support of travel guidance for persons with cognitive disabilities. The unique strength of the system is the ability to provide unique-to-the-user prompts that are triggered by context. As this population is very sensitive to issues of abstraction (e.g. icons) and presents the designer with the need to tailor prompts to a 'universe-of-one' the use of images specific to each user and context is implemented. The key to the approach is to spread the context awareness across the system, with the context being flagged by the QR-code tags and the appropriate response being evoked by displaying the appropriate path guidance images indexed by the intersection of specific end-user and context ID embedded in the tags. By separating the context trigger from the pictorial response, responses can be updated independently of the rest of the installed system, and a single QR-code tag can trigger multiple responses in the PDA depending on the end-user and their specific path. A prototype is built and tested in field experiments with real patients. The experimental results show the human-computer interface is friendly and the capabilities of wayfinding are reliable.

Adaptation in Context-Aware Pervasive Information Systems: The SECAS Project

Abstract: Purpose – The simple environment for context aware systems (SECAS) Project deals with the adaptation of applications to the context (user preferences and environment, terminal, etc.). The authors aim to develop a platform which makes the services, data and the user interface of applications adaptable to different context situations.Design/methodology/approach – Previous research has concentrated on how to capture context data and how to carry it to the application. The present work focuses on the impact of context on the application core. A case study in the medical field is also analysed.Findings – The paper illustrates a new definition of the context which separates the application data from the parameters of the context. This definition helps to establish a complete study on how to adapt applications on their three dimensions (services, content and presentation) to the context.Originality/value – The paper presents the SECAS platform, one that ensures the deployment of adaptive context‐aware applications.

Context Integration for Smart Workflows

Abstract: The usage of workflow technology to model and execute business processes is widespread in many enterprises and within the software industry. With the growing maturity of sensors, wireless communication, and distributed computing environments, we can enhance this approach to enable smart workflows, which are business processes crossing the boundary to the physical world. Applications for such processes can be found in many application domains, like logistics or in smart factory environments. To realize smart workflows, workflow engines can be coupled with existing context provisioning systems. However, there is a gap between the rather low- level provisioning of context (e.g., sensor data and stock information) and the concepts needed in smart workflows (e.g., "is a spare tool available?"). The main contribution of this paper is to bridge this gap: we show how integration processes can be used to provide context information at different semantical levels for smart workflows.

Group Interaction Analysis in Dynamic Context $^{\ast}$

Abstract: Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.

Hybrid Approach to Collaborative Context-Aware Service Platform for Pervasive Computing

Abstract: The behavior of pervasive applications depend not only on their internal state and user interactions but also on contexts sensed during their execution. In this work, we present a collaborative context-aware service platform based on hybrid context management model (enhanced CoCA). It performs reasoning and decisions based on context data, context semantics, and related rules and policies. Such data is organized into a hybrid context management model (HCoM). The platform also introduces a neighborhood collaboration mechanism to facilitate peer collaboration in order to share their resources. We have developed an initial prototype of the platform. Our preliminary test shows that the platform is a promising data independent development environment for pervasive context-aware applications and it possesses good standard of scalability.

Context-awareness and mobile devices

Abstract: Context-awareness is a maturing area within the field of ubiquitous computing. It is particularly relevant to the growing sub-field of mobile computing as a user’s context changes more rapidly when a user is mobile, and interacts with more devices and people in a greater number of locations. In this chapter, we present a definition of context and context-awareness and describe its importance to human-computer interaction and mobile computing. We describe some of the difficulties in building context-aware applications and the solutions that have arisen to address these. Despite these solutions, users have difficulties in using and adopting mobile context-aware applications. We discuss these difficulties and present a set of eight design guidelines that can aid application designers in producing more usable and useful mobile context-aware applications.

Implementing a low-cost, personalized and location based service for delivering advertisements to mobile users

Abstract: Context aware, personalized services can give users equipped with mobile devices targeted and timely information in a seamless way. This paper presents the design and implementation of a low cost, personalized and location based shopping advertisement service for mobile users. The service is intended to run over WiFi connections between an AP located in a shopping center or mall and on-board or hand-held mobile devices. We describe an Ontology based formulation of user and advertised products profiles and the process followed by an Ontology reasoner to select ads that will interest a particular user with high probability. Dynamic parameters such as the time of day and user location are also taken into account in the selection. A prototype service implementation using the OSGi platform is also discussed. The OSGi technology made our implementation portable enough to run on a great variety of clients and servers. Finally, user privacy issues and computational and communication resource constraints are playing an important role in our design.

A Pluggable and Reconfigurable Architecture for a Context-Aware Enabling Middleware System

Abstract: Context awareness is a core feature of modern mobile and ubiquitous computing systems. Although it has not reached its full potential yet, one can already observe significant activity in the area of software engineering for supporting the development of context-aware applications. An example of such an activity is the MUSIC project, which proposes a middleware featuring a generic and reusable context management system. This paper describes the pluggable architecture of this system, and explains how it advances the state of the art through its support for context heterogeneity and better resource utilization. The former is achieved with the use of a novel architecture, which enables the separation of low-level, platform-specific context plug-ins from higher-level application-specific ones. The improved resource utilization is achieved through intelligent activation and deactivation of context plug-ins based on the needs of the active applications. The proposed approach has been experimentally evaluated and the results indicate that it significantly improves the resource utilization in context-aware applications, especially when deployed on lightweight mobile devices.

Heuristics-Based Strategies for Resolving Context Inconsistencies in Pervasive Computing Applications

Abstract: Context-awareness allows pervasive applications to adapt to changeable computing environments. Contexts, the pieces of information that capture the characteristics of environments, are often error-prone and inconsistent due to noises. Various strategies have been proposed to enable automatic context inconsistency resolution. They are formulated on different assumptions that may not hold in practice. This causes applications to be less context-aware to different extents. In this paper, we investigate such impacts and propose our new resolution strategy. We conducted experiments to compare our work with major existing strategies. The results showed that our strategy is both effective in resolving context inconsistencies and promising in its support of applications using contexts.

Development of context aware system based on Bayesian network driven context reasoning method and ontology context modeling

Abstract: Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Network for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Towards Context-Aware Workflow Management for Ubiquitous Computing

Abstract: Ubiquitous computing is a user-centric distributed computing paradigm, allowing users to access to their preferred services even while moving around. To make such a vision a reality, context-aware workflow management is one of key issues because the context of ubiquitous applications is highly varying. In this paper, we propose a context model for intelligent campus navigation applications, then present a context-adaptive workflow management algorithm which can dynamically adjust workflow execution policies in terms of current context information. Moreover, we model the workflow management algorithm in Petri nets. Our context model and workflow management algorithm may be easily extended to other ubiquitous applications with a little change on context structure.