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Proceedings of Pervasive 2008: International Conference on Pervasive Computing

Fullname:Pervasive 2008: Pervasive Computing, 6th International Conference
Editors:Jadwiga Indulska; Donald J. Patterson; Tom Rodden; Max Ott
Location:Sydney, Australia
Dates:2008-May-19 to 2008-May-22
Publisher:Springer-Verlag
Series:Lecture Notes in Computer Science 5013 Springer 2008
Standard No:ISBN 978-3-540-79575-9; hcibib: Pervasive08
Papers:18
Pages:314
Links:Online Proceedings
  1. Sensing and Activity Recognition
  2. Applications for Mobile Devices
  3. Location in Pervasive Systems
  4. Platforms for Pervasive Computing
  5. Lessons Learned from Displays, Games and Health Applications
  6. Privacy and Security

Sensing and Activity Recognition

Detecting Human Movement by Differential Air Pressure Sensing in HVAC System Ductwork: An Exploration in Infrastructure Mediated Sensing BIBAFull-Text 1-18
  Shwetak N. Patel; Matthew S. Reynolds; Gregory D. Abowd
We have developed an approach for whole-house gross movement and room transition detection through sensing at only one point in the home. We consider this system to be one member of an important new class of human activity monitoring approaches based on what we call infrastructure mediated sensing, or "home bus snooping." Our solution leverages the existing ductwork infrastructure of central heating, ventilation, and air conditioning (HVAC) systems found in many homes. Disruptions in airflow, caused by human inter-room movement, result in static pressure changes in the HVAC air handler unit. This is particularly apparent for room-to-room transitions and door open/close events involving full or partial blockage of doorways and thresholds. We detect and record this pressure variation from sensors mounted on the air filter and classify where certain movement events are occurring in the house, such as an adult walking through a particular doorway or the opening and closing of a particular door. In contrast to more complex distributed sensing approaches for motion detection in the home, our method requires the installation of only a single sensing unit (i.e., an instrumented air filter) connected to an embedded or personal computer that performs the classification function. Preliminary results show we can classify unique transition events with up to 75-80% accuracy.
Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography BIBAFull-Text 19-37
  Andreas Bulling; Jamie A. Ward; Hans Gellersen; Gerhard Tröster
In this work we analyse the eye movements of people in transit in an everyday environment using a wearable electrooculographic (EOG) system. We compare three approaches for continuous recognition of reading activities: a string matching algorithm which exploits typical characteristics of reading signals, such as saccades and fixations; and two variants of Hidden Markov Models (HMMs) -- mixed Gaussian and discrete. The recognition algorithms are evaluated in an experiment performed with eight subjects reading freely chosen text without pictures while sitting at a desk, standing, walking indoors and outdoors, and riding a tram. A total dataset of roughly 6 hours was collected with reading activity accounting for about half of the time. We were able to detect reading activities over all subjects with a top recognition rate of 80.2% (71.0% recall, 11.6% false positives) using string matching. We show that EOG is a potentially robust technique for reading recognition across a number of typical daily situations.
Pressing the Flesh: Sensing Multiple Touch and Finger Pressure on Arbitrary Surfaces BIBAFull-Text 38-55
  Joe Marshall; Tony P. Pridmore; Mike Pound; Steve Benford; Boriana Koleva
This paper identifies a new physical correlate of finger pressure that can be detected and measured visually in a wide variety of situations. When a human finger is pressed onto a hard object the flesh is compressed between two rigid surfaces: the surface of the target object and the fingernail. This forces blood out of the vessels in the fingertip, changing its colour slightly, but systematically. The effect is visible to the naked eye and can be measured using techniques from computer vision. As measurements are made of properties of the hand, and not the target surface, multiple-touch and pressure sensing can be added to a range of surfaces -- including opaque, transparent, smooth, textured and non-planar examples -- without modification of the underlying physical object. The proposed approach allows touch sensing to be fitted to surfaces unsuitable for previous technologies, and objects which cannot be altered, without forfeiting the extra range of expression of pressure sensitivity. The methods involved are simple to set up and low cost, requiring only a domestic-quality camera and a typical computer in order to augment a surface. Two systems which exploit this cue to generate a response to pressure are presented, along with a case study of an interactive art installation constructed using the resulting technology. Initial experiments are reported which suggest that visual monitoring of finger colour will support recognition of push events.

Applications for Mobile Devices

MakeIt: Integrate User Interaction Times in the Design Process of Mobile Applications BIBAFull-Text 56-74
  Paul Holleis; Albrecht Schmidt
Besides key presses and text input, modern mobile devices support advanced interactions like taking pictures, gesturing, reading NFC-tags, as well as supporting physiological and environmental sensors. Implementing applications that benefit of this variety of interactions is still difficult. Support for developers and interaction designers remains basic and tools and frameworks are rare. This paper presents a prototyping environment that allows quickly and easily creating fully functional, high-fidelity prototypes deployable on the actual devices. With this work, we target the gap between paper prototyping and integrated development environments. Additionally, new interaction techniques can be significantly faster or slower to use than conventional mobile user interfaces. Hence it is essential to assess the impact of interface design decisions on interaction time. Additionally, the presented tool supports implicit and explicit user performance evaluations during all phases of prototyping. This approach builds on the original as well as extensions of the Keystroke-Level Model (KLM) which allows estimating interaction times in early phases of the development with a simulated prototype. An underlying state graph structure enables automatic checks of the application logic. This tool helps user interface designers and developers to create efficient and consistent novel applications.
Cooperative Techniques Supporting Sensor-Based People-Centric Inferencing BIBAFull-Text 75-92
  Nicholas D. Lane; Hong Lu; Shane B. Eisenman; Andrew T. Campbell
People-centric sensor-based applications targeting mobile device users offer enormous potential. However, learning inference models in this setting is hampered by the lack of labeled training data and appropriate feature inputs. Data features that lead to better classification models are not available at all devices due to device heterogeneity. Even for devices that provide superior data features, models require sufficient training data, perhaps manually labeled by users, before they work well. We propose opportunistic feature vector merging, and the social-network-driven sharing of training data and models between users. Model and training data sharing within social circles combine to reduce the user effort and time involved in collecting training data to attain the maximum classification accuracy possible for a given model, while feature vector merging can enable a higher maximum classification accuracy by enabling better performing models even for more resource-constrained devices. We evaluate our proposed techniques with a significant places classifier that infers and tags locations of importance to a user based on data gathered from cell phones.
Microsearch: When Search Engines Meet Small Devices BIBAFull-Text 93-110
  Chiu Chiang Tan; Bo Sheng; Haodong Wang; Qun Li
In this paper, we present Microsearch, a search system suitable for small devices used in ubiquitous computing environments. Akin to a desktop search engine, Microsearch indexes the information inside a small device, and accurately resolves user queries. Given the very limited hardware resources, conventional search engine designs and algorithms cannot be used. We adopt information retrieval techniques for query resolution, and propose a space efficient algorithm to perform top-k query on limited hardware resources. Finally, we present a theoretical model of Microsearch to better understand the tradeoffs in system design parameters. By implementing Microsearch on actual hardware for evaluation, we demonstrate the feasibility of scaling down information retrieval systems onto very small devices.

Location in Pervasive Systems

Identifying Meaningful Places: The Non-parametric Way BIBAFull-Text 111-127
  Petteri Nurmi; Sourav Bhattacharya
Gathering and analyzing location data is an important part of many ubiquitous computing applications. The most common way to represent location information is to use numerical coordinates, e.g., latitudes and longitudes. A problem with this approach is that numerical coordinates are usually meaningless to a user and they contrast with the way humans refer to locations in daily communication. Instead of using coordinates, humans tend to use descriptive statements about their location; for example, "I'm home" or "I'm at Starbucks." Locations, to which a user can attach meaningful and descriptive semantics, are often called places. In this paper we focus on the automatic extraction of places from discontinuous GPS measurements. We describe and evaluate a non-parametric Bayesian approach for identifying places from this kind of data. The main novelty of our approach is that the algorithm is fully automated and does not require any parameter tuning. Another novel aspect of our algorithm is that it can accurately identify places without temporal information. We evaluate our approach using data that has been gathered from different users and different geographic areas. The traces that we use exhibit different characteristics and contain data from daily life as well as from traveling abroad. We also compare our algorithm against the popular k-means algorithm. The results indicate that our method can accurately identify meaningful places from a variety of location traces and that the algorithm is robust against noise.
An Integrated Platform for the Management of Mobile Location-Aware Information Systems BIBAFull-Text 128-145
  Anthony Savidis; Manolis Zidianakis; Nikolaos Kazepis; Stephanos Dubulakis; Dimitris Grammenos; Constantine Stephanidis
We present an integrated platform comprising a set of authoring and management tools for mobile location-aware information systems. The development of the platform was targeted in supporting large-scale systems with very crowded use sessions, at the scale of hundreds of simultaneous visitors, addressing information delivery for exhibits with proximity down to a couple few meters. The key platform features are: (i) spatial content editing with mixed-mode administration, either mobile (on-site with a PDA) or non-mobile (off-site, using a PC); (ii) system-initiated location-triggered information delivery combined with free user-initiated data exploration; (iii) applicable both indoors and outdoors; (iv) very efficient device renting processes through barcode readers; and (v) multiple location sensing technologies, prioritized according to precision trust (includes WLAN, GPS, and infrared beacons). Currently, the platform is being installed at the fifteen main museums and archeological sites of Greece (including Acropolis, Olympia, Delphi, Knossos and Mycenae), encompassing a total of five thousands mobile devices (see acknowledgements).
Calibree: Calibration-Free Localization Using Relative Distance Estimations BIBAFull-Text 146-161
  Alex Varshavsky; Denis Pankratov; John Krumm; Eyal de Lara
Existing localization algorithms, such as centroid or fingerprinting, compute the location of a mobile device based on measurements of signal strengths from radio base stations. Unfortunately, these algorithms require tedious and expensive off-line calibration in the target deployment area before they can be used for localization. In this paper, we present Calibree, a novel localization algorithm that does not require off-line calibration. The algorithm starts by computing relative distances between pairs of mobile phones based on signatures of their radio environment. It then combines these distances with the known locations of a small number of GPS-equipped phones to estimate absolute locations of all phones, effectively spreading location measurements from phones with GPS to those without. Our evaluation results show that Calibree performs better than the conventional centroid algorithm and only slightly worse than fingerprinting, without requiring off-line calibration. Moreover, when no phones report their absolute locations, Calibree can be used to estimate relative distances between phones.
Location Conflict Resolution with an Ontology BIBAKFull-Text 162-179
  William T. Niu; Judy Kay
Location modelling is central for many pervasive applications and is a key challenge in this area. One major difficulty in location modelling is due to the nature of evidence about a person's location; the evidence is commonly noisy, uncertain and conflicting. Ontological reasoning is intuitively appealing to help address this problem, as reflected in several previous proposals for its use.
   This paper makes several important contributions to the exploration of the potential power of ontologies for improving reasoning about people's location from the available evidence. We describe ONCOR, our lightweight ontology framework: it has the notable and important property that it can be semi-automatically constructed, making new uses of it practical. This paper provides a comprehensive evaluation on how ontological reasoning can support location modelling: we introduce three algorithms for such reasoning and their evaluation based on a study of 8 people over 10-13 days. The results indicate the power of the approach, with mean error rates dropping from 55% with a naive algorithm to 16% with the best of the ontologically based algorithms. This work provides the first implementation of such an approach with a range of ontological reasoning approaches explored and evaluated.
Keywords: Ontological reasoning; location conflict resolution; ontological algorithms

Platforms for Pervasive Computing

Evaluation and Analysis of a Common Model for Ubiquitous Systems Interoperability BIBAFull-Text 180-196
  Michael Blackstock; Rodger Lea; Charles Krasic
To support the deployment of ubicomp systems, the ubiquitous computing research community has developed a variety of middleware platforms, meta-operating systems and toolkits. While there is evidence that these systems share certain abstractions, it is not realistic to use the same platform in all environments; systems and applications specialized for specific environments and applications will always be required. In this paper we present a methodology for interoperability that allows developers to innovate and evolve their platforms while allowing others to build interoperable applications. Our approach is based on our design of the Ubicomp Common Model (UCM) and an implementation of this model called the Ubicomp Integration Framework (UIF). Our aim in this work is to provide clear evidence that the UCM unifies the capabilities of ubicomp systems based on an evaluation and analysis of its use in integrating several existing systems into a composite campus environment.
A Context-Aware System that Changes Sensor Combinations Considering Energy Consumption BIBAKFull-Text 197-212
  Kazuya Murao; Tsutomu Terada; Yoshinari Takegawa; Shojiro Nishio
In wearable computing environments, a wearable computer runs various applications using various sensors (wearable sensors). In the area of context awareness, though various systems using accelerometers have been proposed to recognize very minute motions and states, energy consumption was not taken into consideration. We propose a context-aware system that reduces energy consumption. In life, the granularity of required contexts differs according to the situation. Therefore, the proposed system changes the granularity of cognitive contexts of a user's situation and supplies power on the basis of the optimal sensor combination. Higher accuracy is achieved with fewer sensors. In addition, in proportion to the remainder of power resources, the proposed system reduces the number of sensors within the tolerance of accuracy. Moreover, the accuracy is improved by considering context transition. Even if the number of sensors changes, no extra classifiers or training data are required because the data for shutting off sensors is complemented by our proposed algorithm. By using our system, power consumption can be reduced without large losses in accuracy.
Keywords: Wearable computing; wearable sensors; context awareness; power consumption
Providing an Integrated User Experience of Networked Media, Devices, and Services through End-User Composition BIBAKFull-Text 213-227
  Mark W. Newman; Ame Elliott; Trevor F. Smith
Networked devices for the storage and rendering of digital media are rapidly becoming ubiquitous in homes throughout the industrialized world. Existing approaches to home media control will not suffice for the new capabilities offered by these digitally networked media devices. In particular, the piecemeal interaction provided by current devices, services, and applications will continue to engender frustration among users and will slow adoption of these technologies and the more sophisticated pervasive technologies that will surely follow them into the domestic environment. To address this challenge, we present OSCAR, an application that supports flexible and generic control of devices and services in near-future home media networks. It allows monitoring and manipulation of connections between devices, and allows users to construct reusable configurations to streamline frequently performed activities. A lab-based user study with 9 users of varied backgrounds showed that people could use OSCAR to configure and control a realistic and fully operational home media network, but that they struggled when constructing certain types of reusable configurations. The results of the study show that users were enthusiastic about adopting a system like OSCAR into their own media-related practices, but that further research and development is needed to make such systems truly useful.
Keywords: End-user composition; domestic technology; universal remote control; home media network

Lessons Learned from Displays, Games and Health Applications

Overcoming Assumptions and Uncovering Practices: When Does the Public Really Look at Public Displays? BIBAKFull-Text 228-243
  Elaine M. Huang; Anna Koster; Jan Borchers
This work reports on the findings of a field study examining the current use practices of large ambient information displays in public settings. Such displays are often assumed to be inherently eye-catching and appealing to people nearby, but our research shows that glancing and attention at large displays is complex and dependent on many factors. By understanding how such displays are being used in current, public, non-research settings and the factors that impact usage, we offer concrete, ecologically valid knowledge and design implications about these technologies to researchers and designers who are employing large ambient displays in their work.
Keywords: Large displays; ambient displays; public settings; qualitative studies
Gaming Tourism: Lessons from Evaluating REXplorer, a Pervasive Game for Tourists BIBAFull-Text 244-261
  Rafael Ballagas; André Kuntze; Steffen P. Walz
REXplorer is a mobile, pervasive spell-casting game designed for tourists of Regensburg, Germany. The game creates player encounters with spirits (historical figures) that are associated with significant buildings in an urban setting. A novel mobile interaction mechanism of "casting a spell" (making a gesture by waving a mobile phone through the air) allows the player to awaken and communicate with a spirit to continue playing the game. The game is designed to inform visitors about history in a fun manner. The results of a formative evaluation are explored to inform the design of future serious pervasive games.
Opportunities for Pervasive Computing in Chronic Cancer Care BIBAKFull-Text 262-279
  Gillian R. Hayes; Gregory D. Abowd; John S. Davis; Marion Blount; Maria Ebling; Elizabeth D. Mynatt
While changing from a predominantly terminal to an increasingly chronic condition, cancer is still a growing concern. Accompanying this change are new opportunities for technologies to support patients, their caregivers, and clinicians. In this paper, we present an in-depth study of cancer communities. From this exploration, we define and describe the concept of a personal cancer journey. We examine lessons and design opportunities across this journey for sensing and context-awareness and capture and access applications.
Keywords: Healthcare; cancer; qualitative methods; sensing; applications

Privacy and Security

AnonySense: Opportunistic and Privacy-Preserving Context Collection BIBAFull-Text 280-297
  Apu Kapadia; Nikos Triandopoulos; Cory Cornelius; Daniel Peebles; David Kotz
Opportunistic sensing allows applications to "task" mobile devices to measure context in a target region. For example, one could leverage sensor-equipped vehicles to measure traffic or pollution levels on a particular street, or users' mobile phones to locate (Bluetooth-enabled) objects in their neighborhood. In most proposed applications, context reports include the time and location of the event, putting the privacy of users at increased risk -- even if a report has been anonymized, the accompanying time and location can reveal sufficient information to deanonymize the user whose device sent the report.
   We propose AnonySense, a general-purpose architecture for leveraging users' mobile devices for measuring context, while maintaining the privacy of the users. AnonySense features multiple layers of privacy protection -- a framework for nodes to receive tasks anonymously, a novel blurring mechanism based on tessellation and clustering to protect users' privacy against the system while reporting context, and k-anonymous report aggregation to improve the users' privacy against applications receiving the context. We outline the architecture and security properties of AnonySense, and focus on evaluating our tessellation and clustering algorithm against real mobility traces.
Privacy Protection for RFID with Hidden Subset Identifiers BIBAFull-Text 298-314
  Jacek Cichon; Marek Klonowski; Miroslaw Kutylowski
We propose very simple and cheap but nevertheless effective protection against privacy threats for RFID-tags. For the hidden subset RFID-tags proposed in this paper, the ID string presented by an RFID-tag evolves rapidly. It is not the bit value that enables one to recognize a tag. Instead, a reader detects some invariant properties that are hard to be recognized by a curious illegitimate reader.
   The solution is not based on any cryptographic primitive, it relies only on properties of random sets and on linear mappings between vector spaces. The solution proposed is well suited for low-end devices, since all mechanisms can be easily implemented by circuits of a small size.