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Proceedings of Pervasive 2012: International Conference on Pervasive Computing

Fullname:Pervasive 2012: Pervasive Computing - 10th International Conference
Editors:Judy Kay; Paul Lukowicz; Hideyuki Tokuda; Patrick Olivier; Antonio Krüger
Location:Newcastle, United Kingdom
Dates:2012-Jun-18 to 2012-Jun-22
Publisher:Springer-Verlag
Series:Lecture Notes in Computer Science 7319 Springer 2012
Standard No:ISBN 978-3-642-31204-5; hcibib: Pervasive12
Papers:28
Pages:477
Links:Online Proceedings | Conference Home Page
  1. Activity Capturing
  2. Urban Mobility and Computing
  3. Home and Energy
  4. HCI
  5. Development Tools and Devices
  6. Indoor Location and Positioning
  7. Social Computing and Games
  8. Privacy
  9. Public Displays and Services

Activity Capturing

Personalized Driving Behavior Monitoring and Analysis for Emerging Hybrid Vehicles BIBAFull-Text 1-19
  Kun Li; Man Lu; Fenglong Lu; Qin Lv; Li Shang; Dragan Maksimovic
Emerging electric-drive vehicles, such as hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs), hold the potential for substantial reduction of fuel consumption and greenhouse gas emissions. User driving behavior, which varies from person to person, can significantly affect (P)HEV operation and the corresponding energy and environmental impacts. Although some studies exist that investigate vehicle performance under different driving behaviors, either directed by vehicle manufacturers or via on-board diagnostic (OBD) devices, they are typically vehicle-specific and require extra device/effort. Moreover, there is no or very limited feedback to an individual driver regarding how his/her personalized driving behavior affects (P)HEV performance.
   This paper presents a personalized driving behavior monitoring and analysis system for emerging hybrid vehicles. Our design is fully automated and non-intrusive. We propose phone-based multi-modality sensing that captures precise driver-vehicle information through de-noise, calibration, synchronization, and disorientation compensation. We also provide quantitative driver-specific (P)HEV analysis through operation mode classification, energy use and fuel use modeling. The proposed system has been deployed and evaluated with real-world user studies. System evaluation demonstrates highly-accurate (0.88-0.996 correlation and low error) driving behavior sensing, mode classification, energy use and fuel use modeling.
Mimic Sensors: Battery-Shaped Sensor Node for Detecting Electrical Events of Handheld Devices BIBAKFull-Text 20-38
  Takuya Maekawa; Yasue Kishino; Yutaka Yanagisawa; Yasushi Sakurai
In this paper we propose and implement a battery-shaped sensor node that can monitor the use of an electrical device into which it is inserted by sensing the electrical current passing through the device. We live surrounded by large numbers of electrical devices and frequently use them in our daily lives, and so we can estimate high-level daily activities by recognizing their use. Therefore, many ubiquitous and wearable sensing studies have attempted to recognize the use of electrical devices by attaching sensor nodes to the devices directly or by attaching multiple sensors to a user. With our node, we can easily monitor the use of an electrical device simply by inserting the node into the battery case of the device. We also propose a method that automatically identifies into which electrical device the sensor node is inserted and recognizes electrical events related to the device by analyzing the current sensor data. We evaluated our method by using sensor data obtained from three real houses and achieved very high identification and recognition accuracies.
Keywords: Sensors; Electrical devices; Battery
Leveraging Children's Behavioral Distribution and Singularities in New Interactive Environments: Study in Kindergarten Field Trips BIBAKFull-Text 39-56
  Inseok Hwang; Hyukjae Jang; Taiwoo Park; Aram Choi; Youngki Lee; Chanyou Hwang; Yanggui Choi; Lama Nachman; Junehwa Song
The behavior observations on young children in new, first-in-the-life environments have significant implications. We can often uniquely observe a child's unforeseen interaction with the environment and peer-children. It would be not only a piece of discovery but a beginning of an open quest worth exploring. Out-of-classroom activities like kindergarten's field trips are perfect opportunities, but those are quite different from regular classroom activities where the teachers' conventional observation methods are hardly practical. This paper proposes a novel approach to extend the teachers' awareness on the children's field trip behaviors by means of mobile and sensor technology. We adopt the notion of behavioral distribution and singularities. We estimate the children's representative behavioral state in a given context, and study the effect of focusing on the behaviors which are unlikely in this context. We discuss our 14-month collaborative study and various qualitative benefits through multiple deployments on actual kindergarten field trips.
Keywords: Behavior; distribution; singularity; children; kindergarten; field trip; smartphone; sensor

Urban Mobility and Computing

Urban Traffic Modelling and Prediction Using Large Scale Taxi GPS Traces BIBAFull-Text 57-72
  Pablo Samuel Castro; Daqing Zhang; Shijian Li
Monitoring, predicting and understanding traffic conditions in a city is an important problem for city planning and environmental monitoring. GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces produced allow us to have a unique view of the underlying dynamics of a city's road network. In this paper, we propose a method to construct a model of traffic density based on large scale taxi traces. This model can be used to predict future traffic conditions and estimate the effect of emissions on the city's air quality. We argue that considering traffic density on its own is insufficient for a deep understanding of the underlying traffic dynamics, and hence propose a novel method for automatically determining the capacity of each road segment. We evaluate our methods on a large scale database of taxi GPS logs and demonstrate their outstanding performance.
A Unified Framework for Modeling and Predicting Going-Out Behavior BIBAKFull-Text 73-90
  Shoji Tominaga; Masamichi Shimosaka; Rui Fukui; Tomomasa Sato
Living in society, to go out is almost inevitable for healthy life. There is increasing attention to it in many fields, including pervasive computing, medical science, etc. There are various factors affecting the daily going-out behavior such as the day of the week, the condition of one's health, and weather. We assume that a person has one's own rhythm or patterns of going out as a result of the factors. In this paper, we propose a non-parametric clustering method to extract one's rhythm of the daily going-out behavior and a prediction method of one's future presence using the extracted models. We collect time histories of going out/coming home (6 subjects, total 827 days). Experimental results show that our method copes with the complexity of patterns and flexibly adapts to unknown observation.
Keywords: Methodology; Activity recognition; Location representation
The Hidden Image of the City: Sensing Community Well-Being from Urban Mobility BIBAKFull-Text 91-98
  Neal Lathia; Daniele Quercia; Jon Crowcroft
A key facet of urban design, planning, and monitoring is measuring communities' well-being. Historically, researchers have established a link between well-being and visibility of city neighbourhoods and have measured visibility via quantitative studies with willing participants, a process that is invariably manual and cumbersome. However, the influx of the world's population into urban centres now calls for methods that can easily be implemented, scaled, and analysed. We propose that one such method is offered by pervasive technology: we test whether urban mobility -- as measured by public transport fare collection sensors -- is a viable proxy for the visibility of a city's communities. We validate this hypothesis by examining the correlation between London urban flow of public transport and census-based indices of the well-being of London's census areas. We find that not only are the two correlated, but a number of insights into the flow between areas of varying social standing can be uncovered with readily available transport data. For example, we find that deprived areas tend to preferentially attract people living in other deprived areas, suggesting a segregation effect.
Keywords: Mobility; Urban Analysis; Sensors; Well-Being
Scalable Mining of Common Routes in Mobile Communication Network Traffic Data BIBAKFull-Text 99-106
  Olof Görnerup
A probabilistic method for inferring common routes from mobile communication network traffic data is presented. Besides providing mobility information, valuable in a multitude of application areas, the method has the dual purpose of enabling efficient coarse-graining as well as anonymisation by mapping individual sequences onto common routes. The approach is to represent spatial trajectories by Cell ID sequences that are grouped into routes using locality-sensitive hashing and graph clustering. The method is demonstrated to be scalable, and to accurately group sequences using an evaluation set of GPS tagged data.
Keywords: Cellular networks; mobility; data mining; location privacy

Home and Energy

Accounting for Energy-Reliant Services within Everyday Life at Home BIBAFull-Text 107-124
  Oliver Bates; Adrian K. Clear; Adrian Friday; Mike Hazas; Janine Morley
Researchers in pervasive and ubiquitous computing have produced much work on new sensing technologies for disaggregating domestic resource consumption, and on designs for energy-centric interventions at home. In a departure from this, we employ a service-oriented approach, where we account for not only the amount of resources that specific appliances draw upon, but also how the associated services may be characterised in the context of everyday life. We undertook a formative study in four student flats over a twenty-day period, collecting data using interviews with eleven participants and over two hundred in-home sensors. Following an in-depth description of observations and findings from our study, we argue that our approach provides a more inclusive range of understandings of resources and everyday life than has been shown from energy-centric approaches.
Smart Blueprints: Automatically Generated Maps of Homes and the Devices Within Them BIBAFull-Text 125-142
  Jiakang Lu; Kamin Whitehouse
Off-the-shelf home automation technology is making it easier than ever for people to convert their own homes into "smart homes". However, manual configuration is tedious and error-prone. In this paper, we present a system that automatically generates a map of the home and the devices within it. It requires no specialized deployment tools, 3D scanners, or localization hardware, and infers the floor plan directly from the smart home sensors themselves, e.g. light and motion sensors. The system can be used to automatically configure home automation systems or to automatically produce an intuitive map-like interface for visualizing sensor data and interacting with controllers. We call this system Smart Blueprints because it is automatically customized to the unique configuration of each home. We evaluate this system by deploying in four different houses. Our results indicate that, for three out of the four home deployments, our system can automatically narrow the layout down to 2-4 candidates per home using only one week of collected data.
Hacking the Natural Habitat: An In-the-Wild Study of Smart Homes, Their Development, and the People Who Live in Them BIBAKFull-Text 143-160
  Sarah Mennicken; Elaine M. Huang
Commercial home automation systems are becoming increasingly common, affording the opportunity to study technology-augmented homes in real world contexts. In order to understand how these technologies are being integrated into homes and their effects on inhabitants, we conducted a qualitative study involving smart home professionals who provide such technology, people currently in the process of planning or building smart homes, and people currently living in smart homes. We identified motivations for bringing smart technology into homes, and the phases involved in making a home smart. We also explored the varied roles of the smart home inhabitants that emerged during these phases, and several of the challenges and benefits that arise while living in a smart home. Based on these findings we propose open areas and new directions for smart home research.
Keywords: Home automation; smart homes; domestic technologies

HCI

The Design of a Segway AR-Tactile Navigation System BIBAKFull-Text 161-178
  Ming Li; Lars Mahnkopf; Leif Kobbelt
A Segway is often used to transport a user across mid range distances in urban environments. It has more degrees of freedom than car/bike and is faster than pedestrian. However a navigation system designed for it has not been researched. The existing navigation systems are adapted for car drivers or pedestrians. Using such systems on the Segway can increase the driver's cognitive workload and generate safety risks. In this paper, we present a Segway AR-Tactile navigation system, in which we visualize the route through an Augmented Reality interface displayed by a mobile phone. The turning instructions are presented to the driver via vibro-tactile actuators attached to the handlebar. Multiple vibro-tactile patterns provide navigation instructions. We evaluate the system in real traffic and an artificial environment. Our results show the AR interface reduces users' subjective workload significantly. The vibro-tactile patterns can be perceived correctly and greatly improve the driving performance.
Keywords: Segway; Navigation; Augmented Reality; Vibro-Tactile; Feedback modalities; Real Traffic; Evaluation
Route Guidance Modality for Elder Driver Navigation BIBAKFull-Text 179-196
  Seungjun Kim; Jin-Hyuk Hong; Kevin A. Li; Jodi Forlizzi; Anind K. Dey
Differences in perceptual and cognitive abilities between the young and elderly have implications for in-car tasks. As a primary example, although in-car navigation systems enhance situational awareness, this comes at the cost of increasing visual distraction and cognitive load. To address these shortcomings, this paper explores the efficacy of multi-modal cues for providing route guidance information. We present the results of a study evaluating the impact of multi-modal feedback on driving performance and cognitive load. We found that the full combination of visual, auditory, and haptic feedback was generally most useful to reduce way-finding errors. However, our study highlighted a number of differences between elder and younger drivers for their safer navigation. Adding more modalities strained the already high workload of elder drivers. In contrast, adding haptic feedback to traditional audio and visual feedback led to more attentive driving by younger drivers. Therefore, for elder drivers, navigation systems need to be personalized to enhance the benefit of auditory feedback without increasing the number of sensory feedbacks. For younger drivers, it is necessary to incorporate new non-visual feedback to minimize distractions caused by visual feedback. We demonstrate these results through task performance-based measures, subjective workload measures and through objective workload measures that use psychophysiological responses of participants to predict a driver's cognitive load in near real-time.
Keywords: Elderly driver; Car navigation; Cognitive load; Divided attention; Haptics; Psycho-physiological measurement
Interactive Environment-Aware Handheld Projectors for Pervasive Computing Spaces BIBAKFull-Text 197-215
  David Molyneaux; Shahram Izadi; David Kim; Otmar Hilliges; Steve Hodges; Xiang Cao; Alex Butler; Hans Gellersen
This paper presents two novel handheld projector systems for indoor pervasive computing spaces. These projection-based devices are "aware" of their environment in ways not demonstrated previously. They offer both spatial awareness, where the system infers location and orientation of the device in 3D space, and geometry awareness, where the system constructs the 3D structure of the world around it, which can encompass the user as well as other physical objects, such as furniture and walls. Previous work in this area has predominantly focused on infrastructure-based spatial-aware handheld projection and interaction. Our prototypes offer greater levels of environment awareness, but achieve this using two opposing approaches; the first infrastructure-based and the other infrastructure-less sensing. We highlight a series of interactions including direct touch, as well as in-air gestures, which leverage the shadow of the user for interaction. We describe the technical challenges in realizing these novel systems; and compare them directly by quantifying their location tracking and input sensing capabilities.
Keywords: Handheld projection; geometry and spatial awareness; interaction

Development Tools and Devices

.NET Gadgeteer: A Platform for Custom Devices BIBAFull-Text 216-233
  Nicolas Villar; James Scott; Steve Hodges; Kerry Hammil; Colin Miller
.NET Gadgeteer is a new platform conceived to make it easier to design and build custom electronic devices and systems for a range of ubiquitous and mobile computing scenarios. It consists of three main elements: solder-less modular electronic hardware; object-oriented managed software libraries accessed using a high-level programming language and established development environment; and 3D design and construction tools designed to facilitate a great deal of control over the form factor of the resulting electronic devices. Each of these elements is designed to be accessible to a wide range of people with varying backgrounds and levels of experience and at the same time provide enough flexibility to allow experts to build relatively sophisticated devices and complex systems in less time than they are used to. In this paper we describe the .NET Gadgeteer system in detail for the first time, explaining a number of key design decisions and reporting on its use by new users and experts alike.
Recognizing Handheld Electrical Device Usage with Hand-Worn Coil of Wire BIBAKFull-Text 234-252
  Takuya Maekawa; Yasue Kishino; Yutaka Yanagisawa; Yasushi Sakurai
This paper describes the development of a new finger-ring shaped sensor device with a coil of wire for recognizing the use of handheld electrical devices such as digital cameras, cellphones, electric toothbrushes, and hair dryers by sensing time-varying magnetic fields emitted by the devices. Recently, sensing the usage of home electrical devices has emerged as a promising area for activity recognition studies because we can estimate high-level daily activities by recognizing the use of electrical devices that exist ubiquitously in our daily lives. A feature of our approach is that we can recognize the use of electrical devices that are not connected to the home infrastructure without the need to equip them with sensors. We evaluated the performance of our approach by using sensor data obtained from real houses. We also investigated the portability of training data between different users.
Keywords: Activity sensing; Electrical devices; Wearable sensors
Self-calibration of RFID Reader Probabilities in a Smart Real-Time Factory BIBAKFull-Text 253-270
  Bilal Hameed; Farhan Rashid; Frank Dürr; Kurt Rothermel
RFID technology is now widely used to identify, locate, track and monitor physical objects. However, the use of RFID technology in modern manufacturing has been limited because of the unreliability of RFID devices. In addition to this, where it is used, the technology is mostly deployed to be a substitute for manual inventory management. In this paper we present the Smart Factory, a modern factory infrastructure capable of monitoring each and every product part that moves across the factory during the entire production process. In order to overcome the reliability issues in RFID devices, we have built up a probabilistic model to assign probabilities to the RFID readers and to the product part detections. We also present a probability self-calibration algorithm that automatically adapts the probabilities of RFID readers to better reflect their performance at current instance of time.
Keywords: RFID; Self-Configuration; Middleware; Smart Factory

Indoor Location and Positioning

AWESOM: Automatic Discrete Partitioning of Indoor Spaces for WiFi Fingerprinting BIBAFull-Text 271-288
  Teemu Pulkkinen; Petteri Nurmi
WiFi fingerprinting is currently one of the most popular techniques for indoor localization as it provides reasonable positioning accuracy while at the same time being able to exploit existing wireless infrastructure. To facilitate calibration efforts and to overcome fluctuations in location measurements, many indoor WiFi positioning systems utilize a discrete partitioning, e.g., a grid or a topological map, of the space where the positioning is being deployed. A major limitation of this approach, however, is that instead of considering spatial similarities in the signal environment, the partitioning is typically based on an uniform division of the space or topological constraints (e.g., rooms and walls). This can significantly decrease positioning accuracy when the signal environment is not sufficiently stable across all partitions. Moreover, current solutions provide no support for identifying partitions that are not compatible with the current wireless deployment. To overcome these limitations, we propose AWESOM (Activations Weighted by the Euclidean-distance using Self-Organizing Maps), a novel measure for automatically creating a discrete partitioning of the space where the WiFi positioning is being deployed. In addition to enabling automatic construction of a discrete partitioning, AWESOM provides a measure for evaluating the goodness of a given partitioning for a particular access point deployment. AWESOM also enables identifying partitions where additional access points should be deployed. We demonstrate the usefulness of AWESOM using data collected from two large scale deployments of a proprietary wireless positioning system in a hypermarket environment.
Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling BIBAFull-Text 289-306
  Kari Rye Schougaard; Kaj Grønbæk; Tejs Scharling
This paper introduces methods and services called PerPosNav for development of custom indoor pedestrian navigation applications to be deployed on a variety of platforms. PerPosNav is built on top of the PerPos positioning middleware [8] that fusions GPS, WiFi and inertial tracking into indoor positioning with high accuracy in many types of buildings. The challenges of indoor navigation are discussed and the PerPosNav services are introduced. PerPosNav combines symbolic and geometry based modeling of buildings, and in turn combines graph-based and geometric route computation. The paper argues why these hybrid approaches are necessary to handle the challenges of indoor pedestrian navigation. Furthermore, a fluent navigation is maintained via route tracking and navigation services that generate instructions based on how the user moves in relation to the prescribed route. The viability of PerPosNav has been proven by implementation of support for multiple modes of pedestrian indoor navigation: 1) augmented signs, 2) map based navigation on smartphones, 3) auditory navigation on smartphones solely via earbuds, and 4) augmented reality navigation. Experiences from the use of the PerPosNav services are discussed and compared to other indoor pedestrian navigation approaches.
Estimating Position Relation between Two Pedestrians Using Mobile Phones BIBAKFull-Text 307-324
  Daisuke Kamisaka; Takafumi Watanabe; Shigeki Muramatsu; Arei Kobayashi; Hiroyuki Yokoyama
In a complex indoor environment such as a huge station in an urban area, sometimes the direction and distance relative to another person are more important for pedestrians than their absolute positions, e.g. to search for a lost child. We define this information as the position relation. Our goal is to develop a position relation estimation method on a mobile phone with built-in motion sensors. In literature, methods of cooperative navigation using two pedestrians' positions estimated by pedestrian dead reckoning and a range sensor have been proposed. However, these methods cannot be applied to a mobile phone because pedestrian dead reckoning does not work well when a mobile phone is in a bag, and because there is no range sensor in a phone. In fact, no Bluetooth is reliable as a substitute range sensor. This paper proposes another approach to estimate the position relation of pedestrians. Our method finds the timing when two pedestrians are in close proximity to each other and walk together by using Bluetooth as a proximity sensor and corrects the parameters of position updates dynamically, even if absolute positions are unknown. The algorithm and evaluation results are presented in this paper.
Keywords: relative position; pedestrian dead reckoning; cooperative navigation; indoor positioning; gait analysis; accelerometer; magnetometer; mobile phone
Clearing a Crowd: Context-Supported Neighbor Positioning for People-Centric Navigation BIBAFull-Text 325-342
  Takamasa Higuchi; Hirozumi Yamaguchi; Teruo Higashino
This paper presents a positioning system for "people-centric" navigation, which estimates relative positions of surrounding people to help users to find a target person in a crowd of neighbors. Our system, called PCN, employs pedestrian dead reckoning (PDR) and proximity sensing with Bluetooth only using off-the-shelf mobile phones. Utilizing the feature of "group activity" where people naturally form groups moving similarly and together in exhibitions, parties and so on, PCN corrects deviation of distance and direction in PDR. The group information is also helpful to identify the surrounding people in the navigation. A field experiment in a real exhibition with 20 examinees carrying Google Android phones was conducted to show its effectiveness.

Social Computing and Games

Paying in Kind for Crowdsourced Work in Developing Regions BIBAKFull-Text 343-360
  Navkar Samdaria; Akhil Mathur; Ravin Balakrishnan
In developing regions, the reach of crowdsourcing services such as Amazon Mechanical Turk (mTurk) has been limited by the lack of adequate payment mechanisms and low visibility amongst the crowd. In this paper, we present a commodity based model for crowdsourcing where crowd workers get paid in kind in the form of a commodity instead of money. Our model makes crowdsourcing services more visible to users in developing regions and also addresses the issue of payment. We conducted two field studies in urban India to evaluate the applicability of our proposed model. Our results show that the commodity based crowdsourcing model reached workers with very different demographics from the typical mTurk workers. We also found that users preferred to receive a commodity instead of money as remuneration.
Keywords: crowdsourcing; mobile phones; humans as pervasive computing resources; commodity exchange model; developing regions; Amazon Mechanical Turk; India
Tangible and Casual NFC-Enabled Mobile Games BIBAKFull-Text 361-369
  Luis F. G. Sarmenta
As Near-Field Communication (NFC) becomes a mainstream feature in today's smartphones, it opens up a new range of applications and games. In this paper, we introduce and explore the idea of tangible and casual NFC games. First, we show how we can use NFC not just for its conventional use cases of information lookup and exchange, but in novel interaction techniques that offer players the fun of manipulating physical objects as part of the gameplay. Further, we show how using the unique ID present in most NFC tags and cards enables us to create games that can be downloaded and played by users "on impulse" -- anytime, anywhere, without the need to distribute application-specific tags or install any infrastructure. To demonstrate these techniques, we present several NFC games we have implemented, including novel variations of popular traditional games and toys. We also present results from a public beta trial showing that users around the world are able to successfully play and enjoy our games using transit cards, ID cards, and other cards they already have.
Keywords: HCI; tangible user interfaces; RFID

Privacy

Big Brother Knows Your Friends: On Privacy of Social Communities in Pervasive Networks BIBAFull-Text 370-387
  Igor Bilogrevic; Murtuza Jadliwala; István Lám; Imad Aad; Philip Ginzboorg; Valtteri Niemi; Laurent Bindschaedler; Jean-Pierre Hubaux
Wireless network operators increasingly deploy WiFi hotspots and low-power, low-range base stations in order to satisfy users' growing demands for context-aware services and performance. In addition to providing better service, such capillary infrastructure deployment threatens users' privacy with respect to their social ties and communities, as it allows infrastructure owners to infer users' daily social encounters with increasing accuracy, much to the detriment of their privacy. Yet, to date, there are no evaluations of the privacy of communities in pervasive wireless networks. In this paper, we address the important issue of privacy in pervasive communities by experimentally evaluating the accuracy of an adversary-owned set of wireless sniffing stations in reconstructing the communities of mobile users. During a four-month trial, 80 participants carried mobile devices and were eavesdropped on by an adversarial wireless mesh network on a university campus. To the best of our knowledge, this is the first study that focuses on the privacy of communities in a deployed pervasive network and provides important empirical evidence on the accuracy and feasibility of community tracking in such networks.
Map-Aware Position Sharing for Location Privacy in Non-trusted Systems BIBAKFull-Text 388-405
  Pavel Skvortsov; Frank Dürr; Kurt Rothermel
Many current location-based applications (LBA) such as friend finder services use information about the positions of mobile users. So-called location services (LSs) have been proposed to manage these mobile user positions efficiently. However, managing user positions raises privacy issues, in particular, if the providers of LSs are only partially trusted. Therefore, we presented the concept of private position sharing for partially trusted systems in a previous paper [1]. The basic idea of position sharing is to split the precise user position into a set of position shares of well-defined limited precision and distribute these shares among LSs of different providers.
   The main contributions of this paper are two extended position sharing approaches that improve our previous approach in two ways: Firstly, we reduce the predictability of share generation that allows an attacker to gain further information from a sub-set of shares to further increase the position precision. Secondly, we present a position sharing algorithm for constrained movement scenarios whereas the existing approach was tailored to open space environments. However, open space approaches are vulnerable to map-based attacks. Therefore, we present a share generation algorithm that takes map knowledge into account.
Keywords: Location-based service; privacy; obfuscation; sharing; map-awareness
Sense and Sensibility in a Pervasive World BIBAFull-Text 406-424
  Christos Efstratiou; Ilias Leontiadis; Marco Picone; Kiran K. Rachuri; Cecilia Mascolo; Jon Crowcroft
The increasing popularity of location based social services such as Facebook Places, Foursquare and Google Latitude, solicits a new trend in fusing social networking with real-world sensing. The availability of a wide range of sensing technologies in our everyday environment presents an opportunity to further enrich social networking systems with fine-grained real-world sensing. However, the introduction of passive sensing into a social networking application disrupts the traditional, user-initiated input to social services, raising both privacy and acceptability concerns. In this work we present an empirical study of the introduction of a sensor-driven social sharing application within the working environment of a research institution. Our study is based on a real deployment of a system that involves location tracking, conversation monitoring, and interaction with physical objects. By utilizing surveys, interviews and experience sampling techniques, we report on our findings regarding privacy and user experience issues, and significant factors that can affect acceptability of such services by the users. Our results suggest that such systems deliver significant value in the form of self reflection and comparison with others, while privacy concerns are raised primarily by the limited control over the way individuals are projected to their peers.

Public Displays and Services

From School Food to Skate Parks in a Few Clicks: Using Public Displays to Bootstrap Civic Engagement of the Young BIBAKFull-Text 425-442
  Simo Hosio; Vassilis Kostakos; Hannu Kukka; Marko Jurmu; Jukka Riekki; Timo Ojala
We present Ubinion, a service that utilizes large public interactive displays to enable young people to give personalized feedback on municipal issues to local youth workers. It also facilitates discussion and sharing the feedback online using modern social networking services. We present the motivation and rationale behind Ubinion and analyze the results from three large-scale user trials conducted in authentic settings. The evaluation shows that young users are positive about adopting Ubinion, and that they quickly appropriated its use to provide feedback outside the intended scope of the system, but still reflecting their concerns. We argue that Ubinion's design as a fun and informal tool is appropriate for its purpose, and discuss the versatility of public interactive displays as a municipal feedback medium and as content sources for online communities in general.
Keywords: Social computing; urban computing; public spaces; public displays; social networking; civic engagement; information interfaces
Increasing Brand Attractiveness and Sales through Social Media Comments on Public Displays -- Evidence from a Field Experiment in the Retail Industry BIBAKFull-Text 443-460
  Erica Dubach Spiegler; Christian Hildebrand; Florian Michahelles
Retailers and brands are just starting to utilize online social media to support their businesses. Simultaneously, public displays are becoming ubiquitous in public places, raising the question about how these two technologies could be used together to attract new and existing customers as well as strengthen the relationship toward a focal brand. Accordingly, in a field experiment we displayed brand- and product-related comments from the social network Facebook as pervasive advertising in small-space retail stores, known as kiosks. From interviews conducted with real customers during the experiment and the corresponding analysis of sales data we could conclude three findings. Showing social media comments resulted in (1) customers perceiving brands as more innovative and attractive, (2) a measurable, positive effect on sales on both the brand and the product in question and (3) customers wanting to see the comments of others, but not their own, creating a give-and-take paradox for using public displays to show social media comments.
Keywords: Public Displays; Digital Signage; Pervasive Advertising; Social Media; Social Networks; Field Experiment; Mixed Methods; Retail Industry
Automatic Description of Context-Altering Services through Observational Learning BIBAFull-Text 461-477
  Katharina Rasch; Fei Li; Sanjin Sehic; Rassul Ayani; Schahram Dustdar
Understanding the effect of pervasive services on user context is critical to many context-aware applications. Detailed descriptions of context-altering services are necessary, and manually adapting them to the local environment is a tedious and error-prone process. We present a method for automatically providing service descriptions by observing and learning from the behavior of a service with respect to its environment. By applying machine learning techniques on the observed behavior, our algorithms produce high quality localized service descriptions. In a series of experiments we show that our approach, which can be easily plugged into existing architectures, facilitates context-awareness without the need for manually added service descriptions.