ETH - Indoor Positioning & Indoor Navigation


08:15 - 08:45	Frank Koehler (presenting author, at RheinMain University of Applied Sciences), Marcus Thoß, Alexander Aring: An Energy-Aware Indoor Positioning System for AAL Environments Ambient Assisted Living (AAL) is a field of research activities focusing on IT support for healthcare, comfort and control applications for private home environments and seniors that has gained importance over the last years. AAL facilities often require positioning services, and generally need to offer easy installation and low energy consumption. We present an approach based on a ultrasound and RF system for three dimensional indoor positioning and tracking using wall-mounted anchor nodes and a mobile positioning target. The target is a multifunctional customised handheld display and input device connected to the AAL context by ZigBee low-rate wireless personal networking technology. Positioning is achieved using TDoA distance measurement and a multilateration algorithm. To fulfil the low energy requirement, wall nodes are woken up only for positioning cycles by an ultrasonic pulse decoded by a custom electronic circuit and RF traffic is modelled with a small protocol footprint.

08:45 - 09:15	Paolo Barsocchi at ISTI-CNR, Stefano Chessa, Francesco Furfari, Francesco Potortì (presenting author, at ISTI-CNR): Using Context Information to Improve Indoor Localization Context aware applications (in particular AAL applications) collect a number of information (called context information) about the users. We observed that some of these information can be used to refine the localization of a user. For example, when the user turns on the light in a room, this fact can be use to infer that the user is in that room (or, even better, in front of the light switch). We exploit such an information showing that the use of the restriction significantly improves existing RSSI based localization algorithms, such as those based on multilateration and Least Mean Square (LMS).

09:15 - 09:45	Davide Merico (presenting author), Roberto Bisiani: Situation-Aware Indoor Tracking with High-Density, Large-Scale Wireless Sensor Networks Given the continuous technological advances in computing and communication, it seems that we are rapidly heading towards the realization of paradigms commonly described as ubiquitous computing, pervasive computing, ambient intelligence, Internet of things or, more recently, "everyware". In this paper we propose an innovative approach to the problem of indoor position estimation that aims at extending tracking to a new level of “awareness” bringing to bear new ambient data and opening the possibility of “reasoning” not only on simple positioning but also on the situation at hand. The approach is based on: (i) a low-cost and energy-aware localization infrastructure, (ii) multi-sensor, statistically-based, localization algorithms, (iii) logic-based situation assessment techniques. We evaluate the SAIT system in comparison with several commercial systems. The evaluation highlighted interesting results, showing that exploiting the movement data and situation assessment techniques can really improve the accuracy of indoor positioning systems.

Oral Presentations (Poster Teasers)

09:45 - 09:47

Uta Christoph (presenting author, at RWTH Aachen University), Karl-Heinz Krempels, Janno von Stülpnagel, Christoph Terwelp: Automatic Context Detection of a Mobile User
Mobile devices have obtained a significant role in our life providing a large variety of useful functionalities and features. It is desirable to have an automated adaptation of the behavior of a mobile device depending on a change of user context to fulfill expectations towards practical usefulness. To enable mobile devices to adapt their behavior automatically there is a need to determine the mobile user’s context. In this paper we introduce an integrated approach for the automatic detection of a user’s context. Therefore, we summarize and discuss existing approaches and technologies and describe a service architecture that takes into account information from the interaction of the mobile device with communication networks and positioning systems, from integrated sensors, and planned behavior of the user from e.g. his calendar or activity list. Additionally the architecture considers the social network of the user to derive further information about his context and finally it takes into account the user’s customs through a behavior model.

Context Detection & Awareness, Part 2

Session Chair: Prof. Roberto Bisiani, University of Milano-Bicocca

10:15 - 10:30	Uta Christoph, Karl-Heinz Krempels, Janno von Stülpnagel, Christoph Terwelp (presenting author, at RWTH Aachen University): Indoor-Navigation with Landmarks The complexity of large buildings, like airports, and the omnipresence of mobile devices ask for the ability to navigate people through these buildings with help of their mobile device. Mobile indoor positioning systems do not provide the accuracy required by common navigation systems, since they determine the geographical position based on trilateration of radio signals, e.g. from WiFi or GSM (Global System for Mobile Communication). Also, GPS (Global Positioning System) is not usable in indoor scenarios because buildings absorb the signals. So there is a need for navigation systems, which do not require precise or even any signal based positioning system. Most people tend to express navigation information as a sequence of waypoints and navigation commands enriched by using landmarks. Therefore, we introduce an approach for indoor navigation, which implements the use of landmarks in an automatic navigation system. The system provides the ability to determine a user’s position and guides her to a selected target.

10:30 - 10:45	Ory Chowaw-Liebman, Uta Christoph, Karl-Heinz Krempels (presenting author, RWTH Aachen University), Christoph Terwelp: Indoor Navigation Approach Based on Approximate Positions Until now navigation aids have primarily focused on outdoor scenarios, whether driving on highways or, more recently, walking through cities. These systems use the Global Positioning System (GPS) for position information. Indoor navigation however cannot rely on GPS data, as the signals do not penetrate building structure. Thus other techniques were developed to provide position information indoors, but most of them lack the precision of GPS. In this article the approach of an indoor navigation system based on imprecise position information is presented. To compensate the deficit of precision the position information is combined with a movement model. This movement model is automatically generated from the maps which are already required for navigation.

10:45 - 11:15	Karolina Baras (presenting author, at University of Madeira), Adriano Moreira (at University of Minho), Filipe Meneses: Navigation Based on Symbolic Space Models Existing navigation systems are very appropriate for car navigation, but lack support for convenient pedestrian navigation and cannot be used indoors due to GPS limitations. In addition, the creation and the maintenance of the required models are costly and time consuming, and usually based on proprietary data structures. In this paper we describe a navigation system based on a human inspired symbolic space model. We argue that symbolic space models are much easier to create and to maintain, and that they can support routing applications based on self-locating through the recognition of nearby features. Our symbolic space model is supported by a federation of servers where the spatial descriptions are stored, and which provide interfaces for feeding and querying the model. Local models residing in different servers may be connected between them, thus contributing to the system scalability.

11:15 - 11:30	Róbert Schulcz, Gábor Varga, László Tóth (presenting author, at BME): Indoor Location Services and Context-Sensitive Applications in Wireless Networks As a university research project at the Budapest University of Technology, this project aims to provide a complete solution for Wi-Fi based indoor location services, including client, central infrastructure and location algorithm, with context-sensitive navigation services built on the top. Lifting the constant need to re-survey building data, the developed system offers a hybrid approach, utilizing both radio fingerprint technologies and empirical propagation models in 3D multi-level buildings, borrowing ideas from both the Motley–Keenan Model and the New Empirical Model. It integrates the location service with a semantic map of the environment and a database of preferences and attributes applied to persons and devices, all these information are combined in a geometry model that can be used to infer special knowledge, thus allowing client applications to perform context-sensitive queries and provide more valuable functions to their users.

11:30 - 11:45	Thore Fechner (presenting author), Mareike Kritzler, Antonio Krüger: Geolocation Server – Coordinates become context aware This extended abstract describes a geolocation server for indoor environments. Most of the available tracking or localisation technologies use a coordinate based approach. They describe the current location through a set of coordinates. Although the position is described sufficiently with this set of coordinates, the circumjacent context is not. This work describes an approach to overcome this lack of contextual awareness for an industrial indoor localization. It introduces a service layer which enriches given coordinates based on existing blueprints with context information. The identified entities of the circumjacent context of the coordinates are communicated via a machine readable interface. The interface provides the logical entities’ geometry and a set of attributes which can be used to obtain further information like electrical or mechanical connections.

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