Catálogo de publicaciones - libros

In this paper we present a framework for attaching information to physical objects in a way that can be interactively browsed and searched in a hands-free, multi-modal, and personalized manner that leverages users’ natural looking, pointing and reaching behaviors. The system uses small infrared transponders on objects in the environment and worn by the user to achieve dense, on-object visual feedback usually possible only in augmented reality systems, while improving on interaction style and requirements for wearable gear. We discuss two applications that have been implemented, a tutorial about the parts of an automobile engine and a personalized supermarket assistant. The paper continues with a user study investigating browsing and searching behaviors in the supermarket scenario, and concludes with a discussion of findings and future work.

We investigate the use of 2 tagging technologies: Near Field Communication (NFC) and 2-dimensional barcodes. Our investigation combined a field trial and interview based study with an experimental evaluation. The field trial focused on users’ experience of the usability of NFC for a range of trial services, users’ perceptions of NFC use in their daily life context, and users’ suggestions for potential applications of NFC. The tags were embedded in a variety of postcards, table-top signs and posters. The experimental evaluation compared the ease of use of NFC and 2D barcodes, operationalised in terms of time taken to read a specified sequence of tags on posters. We found that for untrained users the 2D barcodes were quicker to use than the NFC tags but that training significantly improved users’ performance with the NFC tags while having no effect on their performance with the barcodes.

We present a large-scale pervasive game called Manhattan Story Mashup that combines the Web, camera phones, and a large public display. The game introduces a new form of interactive storytelling which lets an unlimited number of players author stories in the Web while a large number of players illustrate the stories with camera phones. This paper presents the first deployment of the game and a detailed analysis of its quantitative and qualitative results. We present details on the game implementation and game set up including practical lessons learnt about this large-scale experiment involving over 300 players in total. The analysis shows how the game succeeds in fostering players’ creativity by exploiting ambiguity and how the players were engaged in a fast-paced competition which resulted in 115 stories and 3142 photos in 1.5 hours.

PersonisAD, is a framework for building context-aware, ubiquitous applications: its defining foundation is a consistent mechanism for scrutable modelling of people, sensors, devices and places. This paper describes the PersonisAD features for supporting distributed models with active elements which can trigger when relevant events occur. This framework makes it possible to quickly create new context-aware applications. We demonstrate the power of the framework by describing how it has been used to create two context aware applications: MusicMix which plays music based on the preferences of the people in the room; MyPlace, which informs people of relevant details of the current environment. Major contributions of this work are: the PersonisAD framework which provides a powerful and consistent means to respond to significant changes in the models of people, sensors, devices and places; support for distributed models and associated resource discovery; two applications that illustrate the power of PersonisAD.

Targeted advertising benefits consumers by delivering them only the messages that match their interests, and also helps advertisers by identifying only the consumers interested in their messages. Although targeting mechanisms for online advertising are well established, pervasive computing environments lack analogous approaches. This paper explores the application of activity inferencing to targeted advertising. We present two mechanisms that link activity descriptions with ad content: direct keyword matching using an online advertising service, and “human computation” matching, which enhances keyword matching with help from online workers. The direct keyword approach is easier to engineer and responds more quickly, whereas the human computation approach has the potential to target more effectively.

This paper introduces a user-centered design process and case study evaluation of a novel wearable visualization system for team sports, coined . TeamAwear consists of three basketball jerseys that are equipped with electroluminescent wires and surfaces. Each jersey can be wirelessly controlled to represent game-related information on the player in real-time, such as the amount of individual fouls, scores and time alerts. A participatory user-centered approach guided the development process towards a more meaningful, ethically and ergonomically valid design. The system aims to enhance the awareness and understanding of game-related public information for all stakeholders, including players, referees, coaches and audience members. We initially hypothesized that such increased awareness would positively influence in-game decisions by players, resulting in a more interesting and enjoyable game play experience for all participants. Instead, the case study evaluation demonstrated TeamAwear’s perceived usefulness particularly for non-playing stakeholders, such as the audience, referees and coaches, supporting more accurate coaching assessments, better understanding of in-game situations and increased enjoyment for spectators. The high amount of game-related cognitive load on the players during game-play seems to hinder its influence on in-game decisions.

In evaluating and analysing a pervasive computing system, it is common to log system use and to create video recordings of users. A lot of data will often be generated, representing potentially long periods of user activity. We present a procedure to identify sections of such data that are salient given the current context of analysis; for example analysing the activity of a particular person among many trial participants recorded by multiple cameras. By augmenting the cameras used to capture a mobile experiment, we are able to establish both a location and heading for each camera, and thus model the field of view for each camera over time. Locations of trial participants are also recorded and compared against camera views, to determine which periods of user activity are likely to have been recorded in detail. Additionally the stability of a camera can be tracked and video can be subsequently filtered to exclude footage of unacceptable quality. These techniques are implemented in an extension to : a software toolkit for use in the development cycle of mobile applications. A report of initial testing is given, whereby the technique’s use is demonstrated on a representative mobile application.

Although the privacy threats and countermeasures associated with location data are well known, there has not been a thorough experiment to assess the effectiveness of either. We examine location data gathered from volunteer subjects to quantify how well four different algorithms can identify the subjects’ home locations and then their identities using a freely available, programmable Web search engine. Our procedure can identify at least a small fraction of the subjects and a larger fraction of their home addresses. We then apply three different obscuration countermeasures designed to foil the privacy attacks: spatial cloaking, noise, and rounding. We show how much obscuration is necessary to maintain the privacy of all the subjects.

Small, mobile devices without user interfaces, such as Bluetooth headsets, often need to communicate securely over wireless networks. Active attacks can only be prevented by authenticating wireless communication, which is problematic when devices do not have any a priori information about each other. We introduce a new method for device-to-device authentication by shaking devices together. This paper describes two protocols for combining cryptographic authentication techniques with known methods of accelerometer data analysis to the effect of generating authenticated, secret keys. The protocols differ in their design, one being more conservative from a security point of view, while the other allows more dynamic interactions. Three experiments are used to optimize and validate our proposed authentication method.

As pervasive environments become more commonplace, the privacy of users is placed at increased risk. The numerous and diverse sensors in these environments can record users’ contextual information, leading to users unwittingly leaving “digital footprints.” Users must thus be allowed to control how their digital footprints are reported to third parties. While a significant amount of prior work has focused on location privacy, location is only one type of footprint, and we expect most users to be incapable of specifying fine-grained policies for a multitude of footprints. In this paper we present a policy language based on the metaphor of physical walls, and posit that users will find this abstraction to be an intuitive way to control access to their digital footprints. For example, users understand the privacy implications of meeting in a room enclosed by physical walls. By allowing users to deploy “virtual walls,” they can control the privacy of their digital footprints much in the same way they control their privacy in the physical world. We present a policy framework and model for virtual walls with three levels of transparency that correspond to intuitive levels of privacy, and the results of a user study that indicates that our model is easy to understand and use.