Evaluating Data Fusion Methodologies for Redundant Positioning

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ISBN: 6202093862
ISBN 13: 9786202093866
Autor: Elmesiry, Ahmed
Verlag: LAP LAMBERT Academic Publishing
Umfang: 152 S.
Erscheinungsdatum: 03.06.2020
Auflage: 1/2020
Format: 1 x 22 x 15
Gewicht: 244 g
Produktform: Kartoniert
Einband: KT
Artikelnummer: 9428388 Kategorie:

Beschreibung

Since the beginning of time, Man, by nature, has sought safety and well being for both himself and his kin. This instinct has obviously led him to develop an inquisitive, questioning disposition. He seeks information about his environs, but his cautious mind also demands reassurance that the data he receives is accurate, timely and not fraudulent or misleading. In striving to make modern pervasive technology systems as useful and as secure as possible, researchers aim to develop systems that can rely on similar guarantees. Ubiquitous computing is growing and emerging as an increasingly significant part of our everyday lives. Context awareness will play a substantial role in achieving this. Location is a major part of context but many factors have contrived to prevent the widespread deployment of location-aware technologies outside of a few niche areas. A Redundant Positioning Architecture will go a long way to combating the drawbacks that currently inhibit pervasive usage and this research endeavour aims to evaluate data fusion techniques which might be applicable for deployment within such a framework.

Autorenporträt

Ahmed M. Elmesiry has received his Ph.D. in Computing Information Security & Assurance from Waterford Institute of Technology, Ireland, and M.Sc. Degree in Computer Science from the Arab Academy for Science and Technology, Egypt. His research interests include Cryptography, Privacy Enhancing Technologies, Machine Learning and IoT Security.

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