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2014 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Indoor Location-Based Services

Prerequisites and Foundations

verfasst von: Martin Werner

Verlag: Springer International Publishing

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book delivers concise coverage of classical methods and new developments related to indoor location-based services. It collects results from isolated domains including geometry, artificial intelligence, statistics, cooperative algorithms, and distributed systems and thus provides an accessible overview of fundamental methods and technologies. This makes it an ideal starting point for researchers, students, and professionals in pervasive computing.

Location-based services are services using the location of a mobile computing device as their primary input. While such services are fairly easy to implement outside buildings thanks to accessible global positioning systems and high-quality environmental information, the situation inside buildings is fundamentally different. In general, there is no simple way of determining the position of a moving target inside a building without an additional dedicated infrastructure.

The book’s structure is learning oriented, starting with a short introduction to wireless communication systems and basic positioning techniques and ending with advanced features like event detection, simultaneous localization and mapping, and privacy aspects. Readers who are not familiar with the individual topics will be able to work through the book from start to finish. At the same time all chapters are self-contained to support readers who are already familiar with some of the content and only want to pick selected topics that are of particular interest.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
This chapter covers the main influences for the book, especially the different domains, which made serious contributions to indoor location-based services. Examples are geology and geographic information systems, data mining and especially time series data mining, context awareness and activity recognition, robotics, computer vision, mobile computing, and ubiquitous computing. Furthermore, a quick overview of application domains of indoor location-based services is given. These examples intend to describe the various requirements, which motivate different algorithms and systems covered in the main part of the book. Finally, the structure of the book gets explained.
Martin Werner
Chapter 2. Prerequisites
Abstract
This chapter introduces mobile communication systems and the fundamental technical principles including signals, capacity theorems, and modulation. It contains a detailed section on signal propagation and statistical models for signal propagation, which are behind several indoor positioning approaches. It further introduces the most important sensor systems, which can be used to infer the position of a mobile device in buildings.
Martin Werner
Chapter 3. Basic Positioning Techniques
Abstract
Positioning technology can be organized by the underlying geometric principles such as triangulation, dead reckoning, or presence detection which can be further subdivided. Alternatively, the algorithms can be organized along observable variables (time, time difference, angle-of-arrival, angle-of-emission, signal strength, acceleration, rotation, etc.). This chapter provides basic algorithms for positioning organized along the underlying geometric principles. After explaining the basic algorithms, a description of real-world approaches is given, organized by the employed sensor technology and observable variables.
Martin Werner
Chapter 4. Building Modeling
Abstract
Indoor positioning systems often have expected errors of a few meters. While these values are quite good, the indoor environment often changes within this scale. Two rooms can be quite far from each other while the distance between the nearest points in both rooms is smaller than 1 m. Hence, a multitude of information (building, rooms, hallways, etc.) about buildings is typically needed to provide sensible location information for successful services. This chapter, therefore, explains building modeling and integrates basic algorithms for vector graphics and raster graphics, environmental models, navigation graphs, and location modeling. Furthermore, two approaches to standardization of environmental information for indoor location-based services are outlined: City GML and IndoorOSM.
Martin Werner
Chapter 5. Position Refinement
Abstract
There is a lot of possibility to improve service quality by extending the notion of a positioning system. Basic positioning systems assign locations to measurements. Advanced systems can use time-series information for refinement including Weighted Least Squares, Recursive Least Squares, Kalman filtering, and particle filtering. The main results and algorithms get a closed explanation in this chapter.
Martin Werner
Chapter 6. Trajectory Computing
Abstract
As the position refinement methodology showed, the time domain can add valuable information to positioning systems. A more general point of view is to further generalize positioning systems to assign location trajectories (sequences of locations) to measurement trajectories (sequences of measurements). This chapter will provide basic and advanced algorithms and results from this domain and explain their impact for indoor location-based services, which might not rely on the position of a user alone.
Martin Werner
Chapter 7. Event Detection for Indoor LBS
Abstract
While outdoors the position as well as a trajectory is often enough to determine most location events (corners, turns, arrivals at points-of-interest, etc.), inside buildings much more events can become relevant and many applications have to rely on a different technology to find these events. The most prevalent example is that the performance of Wi-Fi localization is pretty good in two-dimensional space, but can have difficulties to determine the right floor. These systems can be supported for example by using a barometer indicating reliably floor changes. This chapter first explains how indoor routes can be explained to a user and which events can be relevant for this explanation. Then, this chapter collects events that have been shown useful for indoor location-based services.
Martin Werner
Chapter 8. Simultaneous Localization and Mapping in Buildings
Abstract
Simultaneous localization and mapping (SLAM) is a family of algorithms to generate map information while positioning the moving target at the same time. SLAM algorithms rely on many elementary algorithms such as feature point tracking, loop detection, random sample consensus, surface simplification, and more. This chapter aims to bring together a closed exposition of these algorithms and their application inside buildings.
Martin Werner
Chapter 9. Privacy and Security Considerations
Abstract
This chapter discusses privacy in location systems and the impact for indoor location-based services. It introduces the main approaches for providing privacy including multiparty computation, k-anonymity, l-diversity, spatial and temporal cloaking, differential privacy, and private information retrieval.
Martin Werner
Chapter 10. Open Problem Spaces
Abstract
This chapter provides a critical conclusion about indoor location-based services and highlights the main problem spaces from a technical point of view. These include the reduction of computational complexity, building mapping in a crowd-sourcing manner, indoor navigation without maps, database drift compensation, deployment issues, and the need for distributed, local algorithms.
Martin Werner
Backmatter
Metadaten
Titel
Indoor Location-Based Services
verfasst von
Martin Werner
Copyright-Jahr
2014
Electronic ISBN
978-3-319-10699-1
Print ISBN
978-3-319-10698-4
DOI
https://doi.org/10.1007/978-3-319-10699-1

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