Bringing context-aware access to the web through spoken interaction

The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology to hand-held devices. To optimize data access using these devices and provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. In addition, natural spoken conversation with handheld devices makes possible the use of these applications in environments in which the use of GUI interfaces is not effective, provides a more natural human-computer interaction, and facilitates access to the web for people with visual or motor disabilities, allowing their integration and the elimination of barriers to Internet access. In this paper, we present an architecture for the design of context-aware systems that use speech to access web services. Our contribution focuses specifically on the use of context information to improve the effectiveness of providing web services by using a spoken dialog system for the user-system interaction. We also describe an application of our proposal to develop a context-aware railway information system, and provide a detailed evaluation of the influence of the context information in the quality of the services that are supplied.     

Self-configuring agents for ambient assisted living applications

Ambient assisted living (AAL) is advocated as the technological solution that will enable the elderly population to maintain their independence for a longer period of time than would otherwise be the case. The inherently heterogeneous nature of AmI environments and special requirements of the elderly population pose new challenges for the design and implementation of AAL systems. Thus, the development of these systems demands a context-aware, open, scalable, and distributed software technology that incorporates both intelligent and autonomic reconfiguration techniques. In this contribution, we focus on the design and implementation challenges of an agent-based AAL system that incorporates self-configuring tasks, by means of applying autonomic computing to software agents’ internal architecture. We use an agent-based system for tracking elderly people’s activity using common commercially available electronic devices as case study. We have validated our approach focusing on response time (a main concern in AAL) using different tests and the results are satisfactory.     

The BehaviorScope framework for enabling ambient assisted living

The in-house monitoring of elders using intelligent sensors is a very desirable service that has the potential of increasing autonomy and independence while minimizing the risks of living alone. Because of this promise, the efforts of building such systems have been spanning for decades, but there is still a lot of room for improvement. Driven by the recent technology advances in many of the required components, in this article, we present a scalable framework for detailed behavior interpretation. Our framework supports in-house monitoring of elders using an intelligent gateway and a set of cheap commercially available sensors, in addition to more advanced camera-based human localization sensors and a client for GPS-enabled mobile phones that provides monitoring when outdoors. In this article, we report our experiences and present our current progress in three main components: sensors, middleware, and behavior interpretation mechanisms spanning from simple programmable rule-based alerts to algorithms for extracting the temporal routines of individuals.     

AnAbEL: towards empowering people living with dementia in ambient assisted living

Universal Access in the Information Society - Ambient assisted living aims to support the well-being of people with special needs by offering assistive solutions. Systems focused on dementia...     

Reactive,proactive, and extensible situation-awareness in ambient assisted living

Considering that the world population is aging, health-support issues are in evidence, and many dangerous situations concerning users in their living environment may arise. This paper presents an approach to allow Ambient Assisted Living (AAL) systems to identify and predict situations that may endanger users in their living environment. Elderly people generally have difficulties to perform daily activities as using some electronic device, cooking, dressing among others. This paper offers an alternative to acquire comprehension of a former person's behavioral providing this knowledge when cognitive impairments will occur. This is a significant improvement to traditional expert systems applied to AAL as the handling of the knowledge base is adapted to the failing users’ behavior. We consider the user profile dynamics where new and different situations not initially planned in the development of the systems may occur. This approach was developed considering the principles of reactive and proactive behavior and the extensibility capacity of the system. Systems developed following the above-described principles can react to the current situations and anticipate proactively a dangerous situation eliminating it or controlling its impact. The approach is evaluated and verified by a case study where unwanted, dangerous situations were created and subsequently detected. The case study is based on a simulated smart house fulfilled with sensors and appliances. An application was build based on the developed approach, and it was capable of choosing the most appropriate actions to solve the unwanted situations. The main contributions of the present work are the identification and prediction of situations in smart houses, an approach developed with the principles of reactive and proactive behavior validated with a case study and supported by a probabilistic ontology.     

An experimental characterization of reservoir computing in ambient assisted living applications

In this paper, we present an introduction and critical experimental evaluation of a reservoir computing (RC) approach for ambient assisted living (AAL) applications. Such an empirical analysis jointly addresses the issues of efficiency, by analyzing different system configurations toward the embedding into computationally constrained wireless sensor devices, and of efficacy, by analyzing the predictive performance on real-world applications. First, the approach is assessed on a validation scheme where training, validation and test data are sampled in homogeneous ambient conditions, i.e., from the same set of rooms. Then, it is introduced an external test set involving a new setting, i.e., a novel ambient, which was not available in the first phase of model training and validation. The specific test-bed considered in the paper allows us to investigate the capability of the RC approach to discriminate among user movement trajectories from received signal strength indicator sensor signals. This capability can be exploited in various AAL applications targeted at learning user indoor habits, such as in the proposed indoor movement forecasting task. Such a joint analysis of the efficiency/efficacy trade-off provides novel insight in the concrete successful exploitation of RC for AAL tasks and for their distributed implementation into wireless sensor networks.     

A security policy framework for context-aware and user preferences in e-services

In today’s dynamic and distributed markets a large spectrum of services is delivered through information and communication technologies. Emerging markets of e-services lie at the intersection of non-traditional user behaviour, and cyber-partnerships of enterprises to deliver innovative services. Current approaches to manage and control security demonstrate lacks in terms of security policy matching and integration in heterogeneous e-service environments. In this paper, we introduce a framework to support role-based access control for distributed services focusing on the integration of customer preferences. The framework aims to collect and generate policy-based security measures in cross-organisational scenarios. In addition to catering to specifications of security and business policies, the ability to integrate contextual information and user preferences make the role-based framework flexible and express a variety of access policies that provide a just-in-time permission activation.     

Modeling privacy control in context-aware systems

Significant complexity issues challenge designers of context-aware systems with privacy control. Information spaces provide a way to organize information, resources, and services around important privacy-relevant contextual factors. In this article, we describe a theoretical model for privacy control in context-aware systems based on a core abstraction of information spaces. We have previously focused on deriving socially based privacy objectives in pervasive computing environments. Building on Ravi Sandhu's four-layer OM-AM (objectives, models, architectures, and mechanisms) idea, we aim to use information spaces to construct a model for privacy control that supports our socially based privacy objectives. We also discuss how we can introduce decentralization, a desirable property for many pervasive computing systems, into our information space model, using unified privacy tagging.     

A multimedia social interaction service for inclusive community living: Initial user trials

The move from institution to community care has resulted in many people receiving care at home. For some, disability or frailty restricts their involvement in social activities outside the home, resulting in unacceptable social isolation. This problem is compounded if the person has a speech or language impairment. In this paper, we will describe a communication service designed to provide nonspeaking people with a means to interact socially when living independently, based on the sharing of stories using pictures and other media. Initial exploration on the usability of the system by a pair of representative users will be described. Published online: 6 November 2002     

Modeling user perception of 3D video based on ambient illumination context for enhanced user centric media access and consumption

For enjoying 3D video to its full extent, it is imperative that access and consumption of it is user centric, which in turn ensures improved 3D video perception. Several important factors including video characteristics, users’ preferences, contexts prevailing in various usage environments, etc have influences on 3D video perception. Thus, to assist efficient provision of user centric media, user perception of 3D video should be modeled considering the factors affecting perception. Considering ambient illumination context to model 3D video perception is an interesting research topic, which has not been particularly investigated in literature. This context is taken into account while modeling video quality and depth perception of 3D video in this paper. For the video quality perception model: motion and structural feature characteristics of color texture sequences; and for the depth perception model: luminance contrast of color texture and depth intensity of depth map sequences of 3D video are used as primary content related factors in the paper. Results derived using the video quality and depth perception models demonstrate that these models can efficiently predict user perception of 3D video considering the ambient illumination context in user centric media access and consumption environments.     

Data-driven user simulation for automated evaluation of spoken dialog systems

This paper proposes a novel integrated dialog simulation technique for evaluating spoken dialog systems. A data-driven user simulation technique for simulating user intention and utterance is introduced. A novel user intention modeling and generating method is proposed that uses a linear-chain conditional random field, and a two-phase data-driven domain-specific user utterance simulation method and a linguistic knowledge-based ASR channel simulation method are also presented. Evaluation metrics are introduced to measure the quality of user simulation at intention and utterance. Experiments using these techniques were carried out to evaluate the performance and behavior of dialog systems designed for car navigation dialogs and a building guide robot, and it turned out that our approach was easy to set up and showed similar tendencies to real human users.     

Evaluating the impact of proactivity in the user experience of a context-aware restaurant recommender for Android smartphones

Proactivity has recently gained much attention in the area of cyber physical systems as sensing the users’ real world environment is needed to achieve it. Proactive recommenders are a good example because they push recommendations to the user when the current situation seems appropriate, without explicit user request. Evaluating whether users would accept proactive recommendations, how to properly notify them and how to present recommended items are important research questions. In this article, we present the scenario related to a context-aware restaurant recommender for Android smartphones. Two options to achieve proactivity have been designed: a widget- and a notification-based solution. In addition, our mobile user interface includes a visualization of recommended items and allows for user feedback. The approach was evaluated in a survey among users with good results regarding usefulness and effectiveness. The results also showed that test users preferred the widget-based solution in terms of user experience.     

RecAm: a collaborative context-aware framework for multimedia recommendations in an ambient intelligence environment

With an ever-increasing accessibility to different multimedia contents in real-time, it is difficult for users to identify the proper resources from such a vast number of choices. By utilizing the user’s context while consuming diverse multimedia contents, we can identify different personal preferences and settings. However, there is a need to reinforce the recommendation process in a systematic way, with context-adaptive information. The contributions of this paper are twofold. First, we propose a framework, called RecAm, which enables the collection of contextual information and the delivery of resulted recommendation by adapting the user’s environment using Ambient Intelligent (AmI) Interfaces. Second, we propose a recommendation model that establishes a bridge between the multimedia resources, user joint preferences, and the detected contextual information. Hence, we obtain a comprehensive view of the user’s context, as well as provide a personalized environment to deliver the feedback. We demonstrate the feasibility of RecAm with two prototypes applications that use contextual information for recommendations. The offline experiment conducted shows the improvement of delivering personalized recommendations based on the user’s context on two real-world datasets.     

Enhanced interaction styles for user interfaces

Seven precompetitive research projects on user interfaces in Europe are described. The projects considered are Hufit, the Comett I Project, the Elusive Office Project, the Euroworkstation Project, Acord, MMI², and Xtra. The integration of user interface technologies into new application tasks and the integration of new techniques and artifacts into toolkits are stressed. Also addressed are spreading human factors awareness, adding intelligence to the integration, and the interaction of graphics and natural languages     

Mobile manipulators for assisted living in residential settings

We describe a methodology for creating new technologies for assisted living in residential environments. The number of eldercare clients is expected to grow dramatically over the next decade as the baby boom generation approaches 65 years of age. The UMass/Smith ASSIST framework aims to alleviate the strain on centralized medical providers and community services as their clientele grow, reduce the delays in service, support independent living, and therefore, improve the quality of life for the up-coming elder population. We propose a closed loop methodology wherein innovative technical systems are field tested in assisted care facilities and analyzed by social scientists to create and refine residential systems for independent living. Our goal is to create technology that is embraced by clients, supports efficient delivery of support services, and facilitates social interactions with family and friends. We introduce a series of technologies that are currently under evaluation based on a distributed sensor network and a unique mobile manipulator (MM) concept. The mobile manipulator provides client services and serves as an embodied interface for remote service providers. As a result, a wide range of cost-effective eldercare applications can be devised, several of which are introduced in this paper. We illustrate tools for social interfaces, interfaces for community service and medical providers, and the capacity for autonomous assistance in the activities of daily living. These projects and others are being considered for field testing in the next cycle of ASSIST technology development.

Characterization of privacy based on context sensitivity and user preference for multimedia context-aware on IoT

Multimedia Tools and Applications - In an IoT environment, building a Context-Aware system is mandatory and can provide a suitable and timely (just-in-time) service suited to the context of the...