Sarah Gallacher

VoxBox: A Tangible Machine that Gathers Opinions from the Public at Events

Gathering public opinions, such as surveys, at events typically requires approaching people in situ, but this can disrupt the positive experience they are having and can result in very low response rates. As an alternative approach, we present the design and implementation of VoxBox, a tangible system for gathering opinions on a range of topics in situ at an event through playful and engaging interaction. We discuss the design principles we employed in the creation of VoxBox and show how they encouraged wider participation, by grouping similar questions, encouraging completion, gathering answers to open and closed questions, and connecting answers and results. We evaluate these principles through observations from an initial deployment and discuss how successfully these were implemented in the design of VoxBox.

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.

Sens-Us: Designing Innovative Civic Technology for the Public Good

How can civic technology be designed to encourage more public engagement? What new methods of data collection and sharing can be used to engender a different relationship between citizens and the state? One approach has been to design physical systems that draw people in and which they can trust, leading them to give their views, opinions or other data. So far, they have been largely used to elicit feedback or votes for one or two questions about a given topic. Here, we describe a physical system, called Sens-Us, which was designed to ask a range of questions about personal and sensitive information, within the context of rethinking the UK Census. An in-the-wild study of its deployment in a city cultural center showed how a diversity of people approached, answered and compared the data that had been collected about themselves with others. We discuss the findings in relation to the pros and cons of using this kind of innovative technology when wanting to promote civic engagement or other forms of public engagement.

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.

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.

SmallTalk: Using Tangible Interactions to Gather Feedback from Children

Gathering opinions from young children is challenging and different methods have been explored. In this paper we investigated how tangible devices can be used to gather feedback from children in the context of a theater performance. We introduce SmallTalk, a tangible survey system designed for use within a theater space to capture what children, aged 4 to 9, thought of a live performance they had just seen. We describe how the system was designed to build on previous feedback methods that had been tried; while at the same time meeting the constraints of the challenging theater context. We present results from seven deployments of SmallTalk and based on these we briefly discuss its value as a method for evaluating the theater performance. We then look at how the results validated the system design and present several design implications that more generally relate to tangible feedback systems for children.

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.

Context-aware user preferences in systems for pervasive computing and social networking

Context-aware user preferences play an important role in adapting the behaviour of pervasive systems to satisfy the individual user in different contexts. Most of the pervasive system prototypes that have been developed, incorporate context-aware user preferences, capturing them in an appropriate form and using them to personalize the behaviour of the prototype. However, the rapid rise in use of social networking systems has created a new possibility – that of combining this type of system with pervasive systems to create a new type of system with the benefits of both. The challenge lies in finding how to integrate these two different paradigms in a seamless way to create such a system. This introduces new challenges for the context-dependent user preferences for both individuals and communities. This paper describes briefly some of the ideas, especially as they relate to context-aware user preferences.