Elizabeth Papadopoulou

A Personal Smart Space approach to realising Ambient Ecologies

One of the main aims of research in the area of ubiquitous or pervasive computing is that of dealing with the rapidly growing number of sensors, devices and artefacts in the users environment, which have an increasing amount of intelligence built in and which can communicate via wireless technologies. To assist in this the concept of Ambient Ecologies has been proposed as a metaphor for modelling ubiquitous or pervasive applications based on fixed smart spaces, such as the Smart Home. This paper describes the notion of a Personal Smart Space (PSS) and how it can be used to realise Ambient Ecologies. It goes on to show how, using a PSS approach, one can handle more general situations in which an Ambient Ecology is formed dynamically when two or more PSSs come together wherever this may be. The idea of a PSS is fundamental to the prototype pervasive system that has been developed within the Persist project where it has been used to demonstrate a range of different pervasive applications. In particular this prototype has been used to demonstrate a futuristic situation in the smart home where the total environment is under user control. It is shown how the requisite Ambient Ecologies can be handled by PSSs. The paper concludes with an evaluation of the Persist prototype in which mobile PSSs are used to affect the behaviour of fixed PSSs in their environment.

Learning user preferences for adaptive pervasive environments: An incremental and temporal approach

Personalization mechanisms often employ behavior monitoring and machine learning techniques to aid the user in the creation and management of a preference set that is used to drive the adaptation of environments and resources in line with individual user needs. This article reviews several of the personalization solutions provided to date and proposes two hypotheses: (A) an incremental machine learning approach is better suited to the preference learning problem as opposed to the commonly employed batch learning techniques, (B) temporal data related to the duration that user context states and preference settings endure is a beneficial input to a preference learning solution. These two hypotheses are the cornerstones of the Dynamic Incremental Associative Neural NEtwork (DIANNE) developed as a tailored solution to preference learning in a pervasive environment. DIANNE has been evaluated in two ways: first, by applying it to benchmark datasets to test DIANNEs performance and scalability as a machine learning solution; second, by end-users in live trials to determine the validity of the proposed hypotheses and to evaluate DIANNEs utility as a preference learning solution.

Intelligent Systems that Combine Pervasive Computing and Social Networking

Despite the obvious importance of pervasive computing to help the user cope with the growing number of devices and services that surround her, thus far the take-up of developments emanating from research in this area has been somewhat limited. On the other hand Social Networking Systems have developed at an extraordinary rate with widespread take-up. By bringing together these two paradigms in an integrated and seamless way one can create a Pervasive Social Networking (PSN) system that can provide the benefits of both. To assist in developing pervasive systems the notion of a Personal Smart Space was introduced. This paper extends this notion to that of a Cooperating Smart Space and the accompanying Community Interaction Space which can be used as a basis for developing a PSN. The Societies project is currently using this to develop a PSN which will be evaluated in terms of its usefulness and effectiveness in a series of field trials with real users starting in the last quarter of 2012. The largest of these will involve a cohort of students and this paper also reports briefly on preparatory work leading to the implementation of the PSN system to be used in the student trials.

SOCIETIES: where pervasive meets social

Traditionally, pervasive systems are designed with a focus on the individual, offering services that take advantage of their physical environment and provide a context-aware, personalised user experience. On the other hand, social computing is centred around the notion of a community, leveraging the information about the users and their social relationships, connecting them together often using different criteria that can range from a users physical location and activity to personal interests and past experiences. The SOCIETIES Integrated Project attempts to bridge these different technologies in a unified platform allowing individuals to utilise pervasive services in a community sphere. SOCIETIES aims to use community driven context awareness, preference learning and privacy protection for intelligently connecting people, communities and things. Thus, the goal of SOCIETIES is to radically improve the utility of Future Internet services by combining the benefits of pervasive systems with these of social computing. This paper provides an overview of the vision, concepts, methodology, architecture and initial evaluation results towards the accomplishment of this goal.

Dynamic context-aware personalisation in a pervasive environment

In the development of ubiquitous and pervasive systems, it is understood that mechanisms are required to take adequate account of user preferences. This paper presents several key challenges for personalisation in pervasive environments and introduces the Daidalos solution developed as part of a European research project, Daidalos. The Daidalos personalisation system architecture goes beyond customary simplistic preference management to provide two aspects of dynamicity: first in the establishment of user preferences, where learning mechanisms are used to refine and update preferences when the need arises; second during the application of preferences whenever the context of the user changes. The paper discusses how this system meets the outlined challenges and details how the system has been evaluated.

Personalisation in a System Combining Pervasiveness and Social Networking

One of the key objectives of a pervasive computing system is to provide appropriate support to enable the user to manage the increasingly complex environment surrounding her. This includes managing the ever-increasing number of devices which can be accessed wirelessly as well as the vast range of services at her disposal. The aim of the Persist project was to develop a pervasive system that would bridge the gap between fixed smart spaces (e.g. smart homes) and systems created for mobile users. Using the concept of Personal Smart Spaces the Persist project has built a prototype system to demonstrate some of the capabilities that this can provide. The Societies project is currently building on these ideas to develop a new type of system that combines pervasive with social networking functionality. Personalisation is an essential feature of any pervasive system and plays a key role in the prototype implemented in Persist. This will also play a key role in the new platform being developed in the Societies project. This paper describes how personalisation is handled within the Persist system and some ideas for the new platform.

Personal Smart Spaces as a Basis for Identifying Users in Pervasive Systems

The notion of a Personal Smart Space (PSS) offers a new and flexible solution to the problem of implementing pervasive systems. Its attractiveness lies not only in the way in which it bridges the gap between conventional fixed smart spaces and mobile ubiquitous systems, but also in the new functionality it can provide to enhance the user experience. The use of PSSs to realize pervasive systems is currently being investigated in the Persist project, which has developed a pervasive system platform through which these ideas are being explored. This paper considers one of the features of PSSs, namely that of identifying users through the interaction of their respective PSSs, and the problems that arise when dealing with multiple Personal Smart Spaces. Some scenarios are presented to illustrate how this might be utilized in novel services. The problems surrounding implementation are discussed and a solution based on the Persist architecture is presented.

Implicit Adaptation of User Preferences in Pervasive Systems

User preferences have an essential role to play in decision making in pervasive systems. However, building up and maintaining a set of user preferences for an individual user is a nontrivial exercise. Relying on the user to input preferences has been found not to work and the use of different forms of machine learning are being investigated. This paper is concerned with the problem of updating a set of preferences when a new aspect of an existing preference is discovered. A basic algorithm (with variants) is given for handling this situation. This has been developed for the Daidalos and Persist pervasive systems. Some research issues are also discussed.

Smartening Up the Student Learning Experience with Ubiquitous Media

This article describes how an experimental platform for social, mobile and ubiquitous computing has been used in a wide-ranging longitudinal “in the wild” case study of the platform with a set of third-party services. The article outlines some of the relevant aspects of the platform, including built-in support for community formation, for context sensitivity, automated learning and adaptation to the user, and for management of privacy and trust relationships. The platform architecture is based on the notion of Cooperating Smart Spaces (CSSs), where a CSS is a partition of the platform corresponding to a single user and distributed over the devices belonging to that user. Three of the case study services were intended for use in a physical environment specifically created to support ubiquitous intelligence; they were highly interactive and used shared screens, voice input and gestural interaction. Another three ubiquitous services were available throughout the university environment as mobile and desktop services. The case study exploited this architectures ability to integrate multiple novel applications and interface devices and to deliver them flexibly in these different environments. The platform proved to be stable and reliable and the study shows that treating a provider of services and resources (the University) as a CSS is instrumental in enabling the platform to provide this range of services across differing environments.

Linking Privacy and User Preferences in the Identity Management for a Pervasive System

Two important concepts in developing ubiquitous or pervasive computing technologies that are acceptable to the end user are personalization and privacy. On the one hand it is essential to take account of user needs and preferences to personalize decision making within such a system, on the other hand it is equally important to protect user privacy. One approach to handling user privacy is through the use of virtual identities. This has the advantage that it can also benefit the handling of user preferences. In particular, virtual identities can be used as a substitute for roles. On the other hand user preferences can be used in identity management to assist in selecting a virtual identity to hide the real identity of the user, thereby improving user-friendliness of the system. This paper describes this symbiosis and how it is implemented in the Daidalos pervasive system.