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2006 | Book

Particle Filters for Position Sensing with Asynchronous Ultrasonic Beacons Read chapter Read first chapter

Location- and Context-Awareness

Second International Workshop, LoCA 2006, Dublin, Ireland, May 10-11, 2006. Proceedings

Editors: Mike Hazas, John Krumm, Thomas Strang

Publisher: Springer Berlin Heidelberg

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

nd These proceedings contain the papers presented at the 2 International Workshop on Location- and Context-Awareness in May of 2006. As computing moves increasingly into the everyday world, the importance of location and context knowledge grows. The range of contexts encountered while sitting at a desk working on a computer is very limited compared to the large variety of situations experienced away from the desktop. For computing to be relevant and useful in these situations, the computers must have knowledge of the user’s activity, resources, state of mind, and goals, i.e., the user’s context, of which location is an important indicator. This workshop was intended to present research aimed at sensing, inferring, and using location and context data in ways that help the user. Our call for papers resulted in 74 submissions, each of which was assigned to members of our Program Committee. After reviews and email discussion, we selected 18 papers for publication in these proceedings. Most of the accepted papers underwent a shepherding process by a reviewer or a member of the Program Co- ittee to ensure that the reviewers’ comments were accounted for in the published version. We feel our selective review process and shepherding phase have resulted in a high-quality set of published papers. We extend a sincere “thank you” to all the authors who submitted papers, to our hard-working Program Committee, our thoughtful reviewers, and our conscientious shepherds. May 2006 Mike Hazas and John Krumm, Program Co-chairs Thomas Strang, Workshop Chair

Table of Contents

Frontmatter

Location Sensing

Particle Filters for Position Sensing with Asynchronous Ultrasonic Beacons
Abstract
In this paper we present a user-centric position sensing system that is based on asynchronous, independent ultrasonic beacons. These stationary transmitter units are small, cheap to manufacture, and have power requirements low enough to run each from a small solar cell and a nearby light source. Each beacon is programmed to emit a short, 40 kHz ultrasonic signal with a unique transmission period. The mobile receiver unit first associates a received signal with a beacon based on the observed periodicity, then measures the Doppler shift in the periodicity that results from movements of the receiver. Using Doppler shifts from a number of different beacons, the receiver is able to estimate both its position and velocity by employing a particle filter. In this paper, we describe our positioning algorithm, the hardware, and proof-of-concept results.
Henk L. Muller, Michael McCarthy, Cliff Randell
Cluster Tagging: Robust Fiducial Tracking for Smart Environments
Abstract
Fiducial scene markers provide inexpensive vision-based location systems that are of increasing interest to the Pervasive Computing community. Already established in the Augmented Reality (AR) field, markers are cheap to print and straightforward to locate in three dimensions. When used as a component of a smart environment, however, there are issues of obscuration, insufficient camera resolution and limited numbers of unique markers.
This paper looks at the advantages of clustering multiple markers together to gain resilience to these real world problems. It treats the visual channel as an erasure channel and relevant coding schemes are applied to decode data that is distributed across the marker cluster using an algorithm that does not require each tag to be individually numbered. The advantages of clustering are determined to be a resilience to obscuration, more robust position and pose determination, better performance when attached to inconvenient shapes, and an ability to encode more than a database key into the environment. A real world example comparing the positioning capabilities of a cluster of tags with that of a single tag is presented. It is apparent that clustering provides a position estimate that is more robust, without requiring external definition of a co-ordinate frame using a database.
Robert Harle, Andy Hopper
Automatic Mitigation of Sensor Variations for Signal Strength Based Location Systems
Abstract
In the area of pervasive computing a key concept is context-awareness. One type of context information is location information of wireless network clients. Research in indoor localization of wireless network clients based on signal strength is receiving a lot of attention. However, not much of this research is directed towards handling the issue of adapting a signal strength based indoor localization system to the hardware and software of a specific wireless network client, be it a tag, PDA or laptop. Therefore current indoor localization systems need to be manually adapted to work optimally with specific hardware and software. A second problem is that for a specific hardware there will be more than one driver available and they will have different properties when used for localization. Therefore the contribution of this paper is twofold. First, an automatic system for evaluating the fitness of a specific combination of hardware and software is proposed. Second, an automatic system for adapting an indoor localization system based on signal strength to the specific hardware and software of a wireless network client is proposed. The two contributions can then be used together to either classify a specific hardware and software as unusable for localization or to classify them as usable and then adapt them to the signal strength based indoor localization system.
Mikkel Baun Kjærgaard

Mapping

KOTOHIRAGU NAVIGATOR: An Open Experiment of Location-Aware Service for Popular Mobile Phones
Abstract
We have developed a location-aware sightseeing support system for visitors to KOTOHIRAGU Shrine, using only popular mobile phones employing the gpsOne system. Its design is not a map-based navigation system, but a shared virtual world system like multi-player online role-playing games. We conducted an experiment recruiting 29 subjects from real tourists visiting the shrine, who had their own compatible GPS-phones. From the survey, we have found that location-aware sightseeing support system using mobile phones can be accepted by young people, but the generation gap is wider than expected.
Hiroyuki Tarumi, Yuko Tsurumi, Kazuya Matsubara, Yusuke Hayashi, Yuki Mizukubo, Makoto Yoshida, Fusako Kusunoki
A Wearable Interface for Topological Mapping and Localization in Indoor Environments
Abstract
We present a novel method for mapping and localization in indoor environments using a wearable gesture interface. The ear-mounted FreeDigiter device consists of an infrared proximity sensor and a dual axis accelerometer. A user builds a topological map of a new environment by walking through the environment wearing our device. The accelerometer is used to identify footsteps while the proximity sensor detects doorways. While mapping an environment, finger gestures are used to label detected doorways. Once a map is constructed, a particle filter is employed to track a user walking through the mapped environment while wearing the device. In this tracking mode, the device can be used as a context-aware gesture interface by responding to finger gestures differently according to which room the user occupies. We present experimental results for both mapping and localization in a home environment.
Grant Schindler, Christian Metzger, Thad Starner
Taking Location Modelling to New Levels: A Map Modelling Toolkit for Intelligent Environments
Abstract
We present a map modelling toolkit that meets the special requirements of pedestrian navigation in intelligent environments. Its central component is a graphical editor, which supports geometric modelling of architectural ground plans through polygon meshes. Multiple levels and their interconnections, such as ramps and staircases, can be represented through the aid of layers. In order to support a full range of activities, from travelling to interacting with pervasive user interfaces, coarse models on an outdoor scale can be hierarchically refined by submodels on building and room scales. The XML-encoded models can be useful for positioning systems, referencing spatial context and for route finding through multi-story buildings. Besides the editor, the toolkit provides a routing module for pedestrian navigation.
Christoph Stahl, Jens Haupert

Privacy and Access

Harvesting of Location-Specific Information Through WiFi Networks
Abstract
Ubiquitous computing requires ready access to information that is relevant to users’ context – especially information relevant to their current location. Applications on our personal devices should be able to autonomously and continuously harvest the information provided at that location and interrupt us only when it is important to do so. Currently, client devices are designed for explicit querying for information rather than continuous background harvesting of relevant information. To enable ubiquitous access to location-specific information, we can take advantage of the widespread deployment of WiFi networks. There is a wealth of location-specific information that network providers are willing to make publicly available to any users. However, today’s models for accessing wireless networks do not easily support this due primarily to concerns over security and bandwidth utilization. In this paper, we present and compare the different methods that can be applied to solve the problem of continuous background access to location-specific information. Specifically, we compare client-pull and server-push models and show how tradeoffs can be made involving privacy, power consumption on devices, and utilization of wireless bandwidth. We also present three applications and discuss how the tradeoffs affect their design.
Jong Hee Kang, Gaetano Borriello
Re-identifying Anonymous Nodes
Abstract
In mobile scenarios, privacy is an aspect of growing importance. In order to avoid the creation of movement profiles, participating nodes change their identifying properties on a regular basis in order to hide their identities and stay anonymous. The drawback of this action is that nodes which previously had a connection have no means to recognise this fact. A complete re-authentication would be necessary – if possible at all.
This paper discusses this new problem and proposes two possible solutions for re-identification of anonymous nodes, one based on symmetric encryption and one based on secure hashes.
Stefan Schlott, Frank Kargl, Michael Weber
Anonymous User Tracking for Location-Based Community Services
Abstract
In location-based community services (LBCSs), the positions of several targets are interrelated. Users can be notified when targets approach or separate from each other. Typical application areas are instant messaging, mobile gaming, dating, fleet management and logistics, as well as child tracking. Finding appropriate anonymization techniques for LBCSs is a hard problem since (i) the targets are continuously monitored and (ii) identifiers of the targets must not change in order to maintain coherence within a community. LBCSs are inherently stateful. Therefore, existing anonymization techniques for location-based services are not suited for LBCSs. In this paper, we present an anonymization technique for LBCSs, which employs distance-preserving coordinate transformations in conjunction with pseudonyms. It is based on the idea that for determining the distance between targets only relative positions are needed. It supports target anonymity, either with respect to the location provider, which collects the position fixes, or the LBS provider. The paper also presents the results of simulations, which we have performed in order to evaluate the proposed mechanism.
Peter Ruppel, Georg Treu, Axel Küpper, Claudia Linnhoff-Popien

Context Sensing

Towards Personalized Mobile Interruptibility Estimation
Abstract
The automatic estimation of the user’s current interruptibility is important to seamlessly adapt a device’s behaviour to the user’s situation. Different people differ in the way they rate their interruptibility. In this paper we investigate three options how to adapt an interruptibility estimation system to a particular user: by finding prototypical users, using experience sampling, or using knowledge of prototypical situations. We have experimentally tested all three approaches on a data set of 94 situations that have been annotated by 24 different users.
Nicky Kern, Bernt Schiele
Unsupervised Discovery of Structure in Activity Data Using Multiple Eigenspaces
Abstract
In this paper we propose a novel scheme for unsupervised detection of structure in activity data. Our method is based upon an algorithm that represents data in terms of multiple low-dimensional eigenspaces. We describe the algorithm and propose an extension that allows to handle multiple time scales. The validity of the approach is demonstrated on several data sets and using two types of acceleration features. Finally, we report on experiments that indicate that our approach can yield recognition rates comparable to other, supervised approaches.
Tâm Huỳnh, Bernt Schiele
Toward Scalable Activity Recognition for Sensor Networks
Abstract
Sensor networks hold the promise of truly intelligent buildings: buildings that adapt to the behavior of their occupants to improve productivity, efficiency, safety, and security. To be practical, such a network must be economical to manufacture, install and maintain. Similarly, the methodology must be efficient and must scale well to very large spaces. Finally, be be widely acceptable, it must be inherently privacy-sensitive. We propose to address these requirements by employing networks of passive infrared (PIR) motion detectors. PIR sensors are inexpensive, reliable, and require very little bandwidth. They also protect privacy since they are neither capable of directly identifying individuals nor of capturing identifiable imagery or audio. However, with an appropriate analysis methodology, we show that they are capable of providing useful contextual information. The methodology we propose supports scalability by adopting a hierarchical framework that splits computation into localized, distributed tasks. To support our methodology we provide theoretical justification for the method that grounds it in the action recognition literature. We also present quantitative results on a dataset that we have recorded from a 400 square meter wing of our laboratory. Specifically, we report quantitative results that show better than 90% recognition performance for low-level activities such as walking, loitering, and turning. We also present experimental results for mid-level activities such as visiting and meeting.
Christopher R. Wren, Emmanuel Munguia Tapia

Social Context

Nomatic: Location By, For, and Of Crowds
Abstract
In this paper we present a social and technical architecture which will enable the study of localization from the perspective of crowds. Our research agenda is to leverage new computing opportunities that arise when many people are simultaneously localizing themselves. By aggregating this and other types of context information we intend to develop a statistically powerful data set that can be used by urban planners, users and their software. This paper presents an end-to-end strategy, motivated with preliminary user studies, for lowering the social and technical barriers to sharing context information. The primary technology through which we motivate participation is an intelligent context-aware instant messaging client called Nomatic*Gaim. We investigate social barriers to participation with a small informal user study evaluating automatic privacy mechanisms which give people control over their context disclosure. We then analyze some preliminary data from an early deployment. Finally we show how leveraging these mass-collaborations could help to improve Nomatic*Gaim by allowing it to infer position to place mappings.
Donald J. Patterson, Xianghua Ding, Nicholas Noack
An Unsupervised Learning Paradigm for Peer-to-Peer Labeling and Naming of Locations and Contexts
Abstract
Several approaches to context awareness have been proposed ranging from unsupervised learning to ontologies. Independent of the type of context awareness used a consistent approach to naming contexts is required. A novel paradigm for labeling contexts is described based on close range wireless connections between devices and a very simple, unsupervised learning algorithm. It is shown by simulation analysis that it is possible to achieve a labeling of different contexts which allows context related information to be communicated in a consistent manner between devices. As the learning is unsupervised no user input is required for it to work. Furthermore this approach requires no extra infrastructure or resources to manage the names assigned to the contexts.
John A. Flanagan
Building Common Ground for Face to Face Interactions by Sharing Mobile Device Context
Abstract
We describe an application used to share context and build common ground between nearby users. Our application runs on mobile devices and allows users securely to exchange the contents of their address books. This exchange reveals only which entries are common to the two users. We explore the use of our application using both Bluetooth and NFC as an underlying technology. Finally, we present the results of a small user study we have conducted.
Vassilis Kostakos, Eamonn O’Neill, Anuroop Shahi

Representation and Programming

Evaluating Performance in Continuous Context Recognition Using Event-Driven Error Characterisation
Abstract
Evaluating the performance of a continuous activity recognition system can be a challenging problem. To-date there is no widely accepted standard for dealing with this, and in general methods and measures are adapted from related fields such as speech and vision. Much of the problem stems from the often imprecise and ambiguous nature of the real-world events that an activity recognition system has to deal with. A recognised event might have variable duration, or be shifted in time from the corresponding real-world event. Equally it might be broken up into smaller pieces, or joined together to form larger events. Most evaluation attempts tend to smooth over these issues, using “fuzzy” boundaries, or some other parameter based error decision, so as to make possible the use of standard performance measures (such as insertions and deletions.) However, we argue that reducing the various facets of a activity system into limited error categories – that were originally intended for different problem domains – can be overly restrictive. In this paper we attempt to identify and characterise the errors typical to continuous activity recognition, and develop a method for quantifying them in an unambiguous manner.
By way of an initial investigation, we apply the method to an example taken from previous work, and discuss the advantages that this provides over two of the most commonly used methods.
Jamie A. Ward, Paul Lukowicz, Gerhard Tröster
Location-Based Context Retrieval and Filtering
Abstract
Context-based applications are supposed to decrease human-machine interactions. To this end, they must interpret the meaning of context data. Ontologies are a commonly accepted approach of specifying data semantics and are thus considered a precondition for the implementation of context-based systems. Yet, experiences gained from the European project Daidalos evoke concerns that this approach has its flaws when the application domain can hardly be delimited. These concerns are raised by the human limitation in dealing with complex specifications.
This paper proposes a relaxation of the situation: Humans strength is the understating of natural languages, computers, however, possess superior pattern matching power. Therefore, it is suggested to enrich or even replace semantic specifications of context data items by free-text descriptions. For instance, rather than using an Ontology specification to describe an Italian restaurant the restaurant can simply be described by its menu card.
To facilitate this methodology, context documents are introduced and a novel information retrieval approach is elucidated, evaluated, and analysed with the help of Bose-Einstein statistics. It is demonstrated that the new approach clearly outperforms conventional information retrieval engines and is an excellent addition to context Ontologies.
Carsten Pils, Ioanna Roussaki, Maria Strimpakou
Scripting Your Home
Abstract
Our homes and lives are as individual as ourselves. Many aspects, such as technical equipment, furniture, and usage patterns in these surroundings differ. Thus, personalization of applications that operate in such environments is required. The challenge for tools and programming paradigms is to provide a powerful but yet easy-to-use platform. In this paper we illustrate how our visual scripting language puts these requirements for programming ubiquitous computing environments into action.
Mirko Knoll, Torben Weis, Andreas Ulbrich, Alexander Brändle
Backmatter
Metadata
Title
Location- and Context-Awareness
Editors
Mike Hazas
John Krumm
Thomas Strang
Copyright Year
2006
Publisher
Springer Berlin Heidelberg
Electronic ISBN
978-3-540-34151-2
Print ISBN
978-3-540-34150-5
DOI
https://doi.org/10.1007/11752967

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