Mobile Entity Localization and Tracking in GPS-less Environnments

Mobile Entity Localization and Tracking in GPS-less Environnments PDF Author: Richard Fuller
Publisher: Springer Science & Business Media
ISBN: 364204378X
Category : Computers
Languages : en
Pages : 275

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Book Description
This book constitutes the refereed proceedings of the second International Workshop on Mobile Entity Localization and Tracking in GPS-less Environnments, MELT, held in Orlando, Florida, USA, in September 2009 in conjunction with the 11th International Conference on Ubiquitous Computing (Ubicomp 2009). MELT is a forum for the state-of-the-art technologies in mobile localization and tracking and novel applications of location-based services. The research contributions in these proceedings cover significant aspects of localization and tracking of mobile devices that include techniques suitable for smart phones and mobile sensor networks in both outdoor and indoor environments using diverse sensors and radio signals. Novel theoretical methods, algorithmic design and analysis, application development, and experimental studies are presented in 14 papers that were reviewed carefully by the program committee. In addition, three invited papers, with topics on location determination using RF systems, Cramer-Rao-Bound analysis for indoor localization and approaches targeting mobile sensor networks, are also included in the proceedings.

Mobile Entity Localization and Tracking in GPS-less Environnments

Mobile Entity Localization and Tracking in GPS-less Environnments PDF Author: Richard Fuller
Publisher: Springer Science & Business Media
ISBN: 364204378X
Category : Computers
Languages : en
Pages : 275

Get Book Here

Book Description
This book constitutes the refereed proceedings of the second International Workshop on Mobile Entity Localization and Tracking in GPS-less Environnments, MELT, held in Orlando, Florida, USA, in September 2009 in conjunction with the 11th International Conference on Ubiquitous Computing (Ubicomp 2009). MELT is a forum for the state-of-the-art technologies in mobile localization and tracking and novel applications of location-based services. The research contributions in these proceedings cover significant aspects of localization and tracking of mobile devices that include techniques suitable for smart phones and mobile sensor networks in both outdoor and indoor environments using diverse sensors and radio signals. Novel theoretical methods, algorithmic design and analysis, application development, and experimental studies are presented in 14 papers that were reviewed carefully by the program committee. In addition, three invited papers, with topics on location determination using RF systems, Cramer-Rao-Bound analysis for indoor localization and approaches targeting mobile sensor networks, are also included in the proceedings.

Mobile Entity Localization and Tracking in GPS-less Environnments

Mobile Entity Localization and Tracking in GPS-less Environnments PDF Author: Richard Fuller
Publisher: Springer
ISBN: 3642043852
Category : Computers
Languages : en
Pages : 275

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Book Description
This volume contains the proceedings of the Second International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments (MELT 2009), held in Orlando, Florida on September 30, 2009 in conjunction with the 11th International Conference on Ubiquitous Computing (Ubicomp 2009). MELT provides a forum for the presentation of state-of-the-art technologies in mobile localization and tracking and novel applications of location-based s- vices. MELT 2009 continued the success of the ?rst workshop in the series (MELT 2008), which was held is San Francisco, California on September 19, 2008 in conjunction with Mobicom. Location-awareness is a key component for achieving context-awareness. - cent years have witnessed an increasing trend towards location-based services and applications. In most cases, however, location information is limited by the accessibility to GPS, which is unavailable for indoor or underground fac- ities and unreliable in urban environments. Much research has been done, in both the sensor network community and the ubiquitous computing community, to provide techniques for localization and tracking in GPS-less environments. Novel applications based on ad-hoc localization and real-time tracking of - bile entities are growing as a result of these technologies. MELT brings together leaders from both the academic and industrial research communities to discuss challenging and open problems, to evaluate pros and cons of various approaches, to bridge the gap between theory and applications, and to envision new research opportunities.

Mobile Entity Localization and Tracking in GPS-less Environments

Mobile Entity Localization and Tracking in GPS-less Environments PDF Author:
Publisher:
ISBN: 9781282635265
Category : Location-based services
Languages : en
Pages : 266

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Book Description


Opportunstic Seamless Localization

Opportunstic Seamless Localization PDF Author: Maarten Weyn
Publisher: Lulu.com
ISBN: 1447775287
Category :
Languages : en
Pages : 179

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Book Description


Progress in Location-Based Services

Progress in Location-Based Services PDF Author: Jukka M. Krisp
Publisher: Springer Science & Business Media
ISBN: 3642342035
Category : Science
Languages : en
Pages : 506

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Book Description
The book consists of peer-reviewed papers from the 9th symposium on Location Based Services (LBS) which is targeted to researchers, industry/market operators and students of different backgrounds (scientific, engineering and humanistic). As the research field is developing and changing fast, this book follows up on current trends and gives suggestions and guidance to further research. This book offers a common ground bringing together various disciplines and practice, knowledge, experiences, plans and ideas on how LBS can and could be improved and on how it will influence both science and society. The book comprises front-end publications organized into sections on: spatial-temporal data acquisition, processing & analysis; positioning / indoor positioning; way-finding / navigation (indoor / outdoor) & smart mobile phone navigation; interactions, user studies and evaluations; innovative LBS systems & applications.

RFID Technology Integration for Business Performance Improvement

RFID Technology Integration for Business Performance Improvement PDF Author: Lee, In
Publisher: IGI Global
ISBN: 146666309X
Category : Computers
Languages : en
Pages : 337

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Book Description
The development of radio-frequency electromagnetic fields for wireless data transmission has presented several new opportunities for sharing, tracking, and reading digital information in various industries. RFID Technology Integration for Business Performance Improvement presents emerging research surrounding the use and value of Radio Frequency Identification (RFID) technology for cost reduction, supply chain improvement, inventory management, and partner relationship management. This publication is ideal for use by business managers, researchers, academics, and advanced-level students seeking research on the management strategies, operational techniques, opportunities, and challenges of implementing and using this new technology in a business setting.

Advances in Electrical and Computer Technologies

Advances in Electrical and Computer Technologies PDF Author: Thangaprakash Sengodan
Publisher: Springer Nature
ISBN: 9811555583
Category : Computers
Languages : en
Pages : 1399

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Book Description
The book comprises select proceedings of the first International Conference on Advances in Electrical and Computer Technologies 2019 (ICAECT 2019). The papers presented in this book are peer reviewed and cover wide range of topics in Electrical and Computer Engineering fields. This book contains the papers presenting the latest developments in the areas of Electrical, Electronics, Communication systems and Computer Science such as smart grids, soft computing techniques in power systems, smart energy management systems, power electronics, feedback control systems, biomedical engineering, geo informative systems, grid computing, data mining, image and signal processing, video processing, computer vision, pattern recognition, cloud computing, pervasive computing, intelligent systems, artificial intelligence, neural network and fuzzy logic, broad band communication, mobile and optical communication, network security, VLSI, embedded systems, optical networks and wireless communication. This book will be of great use to the researchers and students in the areas of Electrical and Electronics Engineering, Communication systems and Computer Science.

Autonomous Indoor Localization Using Unsupervised Wi-Fi Fingerprinting

Autonomous Indoor Localization Using Unsupervised Wi-Fi Fingerprinting PDF Author: Yaqian Xu
Publisher: kassel university press GmbH
ISBN: 3737600708
Category :
Languages : en
Pages : 198

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Book Description
Indoor localization is a research domain that aims to locate mobile devices or users in the indoor environments. More and more research has investigated to acquire the location information based upon existing Wi-Fi infrastructure. A technique of using current Wi-Fi data and a fingerprint database containing Wi-Fi fingerprints of desired locations for localization is known as Wi-Fi fingerprinting. Most current approaches for Wi-Fi fingerprinting depend on labor-intensive and time-consuming site surveys by professional staff or users to generate a fingerprint database of desired locations. Moreover, these approaches are not satisfactory for long-term localization of mobile devices in practice due to the costly and continuous update of the fingerprint database. In this thesis, we propose an approach to the indoor localization problem, in which we combine the Wi-Fi fingerprinting technique and the place learning technique to learn and update the Wi-Fi fingerprints of significant locations in an unsupervised manner. Significant locations are locations a user spent at least for a while (e.g., 10 minutes) and are most important and highly frequented in people’s daily lives. The conventional approaches use labeled Wi-Fi data intentionally collected by professional staff or users and learn Wi-Fi fingerprints of desired locations. Instead, the proposed approach uses unlabeled Wi-Fi data collected in a user’s daily life and learns Wi-Fi fingerprints of significant locations related to user’s daily trajectory and activities. We implement an autonomous indoor localization system WHERE based on the proposed approach. The system can automatically learn and update Wi-Fi fingerprints of significant locations, and determine the location of the mobile device when it returns to the learned locations. Moreover, we evaluate various measures of performance, in term of the location accuracy, the computational time, the power consumption, the size of a fingerprint database, and the system reliability in a practical use. Performance evaluation shows that the proposed autonomous indoor localization system WHERE is a reliable system for efficient use – being very low-cost to set up and maintain, and showing satisfactory localization performance.

Artificial Neural Networks – ICANN 2009

Artificial Neural Networks – ICANN 2009 PDF Author: Cesare Alippi
Publisher: Springer
ISBN: 3642042775
Category : Computers
Languages : en
Pages : 1034

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Book Description
This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.

Machine Learning for Indoor Localization and Navigation

Machine Learning for Indoor Localization and Navigation PDF Author: Saideep Tiku
Publisher: Springer Nature
ISBN: 3031267125
Category : Technology & Engineering
Languages : en
Pages : 563

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Book Description
While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve the accuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book: Provides comprehensive coverage of the application of machine learning to the domain of indoor localization; Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization; Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.