A Low Cost Indoor Positioning & Intelligent Path Finding System - Gunagwera, Alex;Kiani, Farzad
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Despite the rapid improvement in mobile devices, overall gradual growth in the ubiquitous computing field, the wide applicability, more usefulness of location based services in general and indoor navigation. The Global Positioning System (GPS) has undergone tremendous improvement since the 1900s and it, indeed is considered one of the most successful navigation systems known to date. However, it is still inefficient for sufficiently accurate positioning in both indoor environments and environments with many tall buildings such as skyscrapers since such buildings block or interfere with its…mehr

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Produktbeschreibung
Despite the rapid improvement in mobile devices, overall gradual growth in the ubiquitous computing field, the wide applicability, more usefulness of location based services in general and indoor navigation. The Global Positioning System (GPS) has undergone tremendous improvement since the 1900s and it, indeed is considered one of the most successful navigation systems known to date. However, it is still inefficient for sufficiently accurate positioning in both indoor environments and environments with many tall buildings such as skyscrapers since such buildings block or interfere with its signal transmissions. In particular, building a sufficiently accurate, efficient and relatively cheap indoor navigation system in a GPS-free environment is still a challenging task with a lot of trade offs and constraints to put into consideration. In this study, a simple yet robust, low cost, context-aware user-interactive, user-friendly hybrid of fingerprinting and dead reckoning indoor navigation system suitable for both the visually and the physically disabled as well that takes advantage of the results yielded by sensor fusion is proposed.
Autorenporträt
Gunagwera, Alex
Alex Gunagwera received undergraduate and master degree in computer engineering from Fatih and Istanbul Sabahattin Zaim (IZU) Universities in 2015 and 2017 respectively. He is a PhD candidate in IZU. His interest research interests are robotics, ML, algorithm, computer networks and ubiquitous computing. He is the corresponding author of this study.