| Detecting Human Movement by Differential Air Pressure Sensing in HVAC System Ductwork: An Exploration in Infrastructure Mediated Sensing | | BIBA | Full-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 | | BIBA | Full-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 | | BIBA | Full-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. | |||
| MakeIt: Integrate User Interaction Times in the Design Process of Mobile Applications | | BIBA | Full-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 | | BIBA | Full-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 | | BIBA | Full-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. | |||
| Identifying Meaningful Places: The Non-parametric Way | | BIBA | Full-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 | | BIBA | Full-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 | | BIBA | Full-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 | | BIBAK | Full-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 | |||
| Evaluation and Analysis of a Common Model for Ubiquitous Systems Interoperability | | BIBA | Full-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 | | BIBAK | Full-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 | | BIBAK | Full-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 | |||
| Overcoming Assumptions and Uncovering Practices: When Does the Public Really Look at Public Displays? | | BIBAK | Full-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 | | BIBA | Full-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 | | BIBAK | Full-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 | |||
| AnonySense: Opportunistic and Privacy-Preserving Context Collection | | BIBA | Full-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 | | BIBA | Full-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. | |||