Distributed and adaptive location identification system for mobile devices
Abstract Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into...
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doaj-8b560fe9d15c47c0bebb2d2a8f85c7202020-11-24T21:26:35ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802018-09-012018112010.1186/s13634-018-0583-3Distributed and adaptive location identification system for mobile devicesFahed Awad0Aisha Al-Sadi1Fida’a Al-Quran2Abdulsalam Alsmady3Department of Network Engineering and Security, Jordan University of Science and TechnologyDepartment of Computer Science, Jordan University of Science and TechnologyDepartment of Network Engineering and Security, Jordan University of Science and TechnologyDepartment of Computer Engineering, Jordan University of Science and TechnologyAbstract Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments.http://link.springer.com/article/10.1186/s13634-018-0583-3Location identificationIndoor navigationLocation-based servicesCalibration-freeModel-basedRSS-based |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fahed Awad Aisha Al-Sadi Fida’a Al-Quran Abdulsalam Alsmady |
spellingShingle |
Fahed Awad Aisha Al-Sadi Fida’a Al-Quran Abdulsalam Alsmady Distributed and adaptive location identification system for mobile devices EURASIP Journal on Advances in Signal Processing Location identification Indoor navigation Location-based services Calibration-free Model-based RSS-based |
author_facet |
Fahed Awad Aisha Al-Sadi Fida’a Al-Quran Abdulsalam Alsmady |
author_sort |
Fahed Awad |
title |
Distributed and adaptive location identification system for mobile devices |
title_short |
Distributed and adaptive location identification system for mobile devices |
title_full |
Distributed and adaptive location identification system for mobile devices |
title_fullStr |
Distributed and adaptive location identification system for mobile devices |
title_full_unstemmed |
Distributed and adaptive location identification system for mobile devices |
title_sort |
distributed and adaptive location identification system for mobile devices |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6180 |
publishDate |
2018-09-01 |
description |
Abstract Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments. |
topic |
Location identification Indoor navigation Location-based services Calibration-free Model-based RSS-based |
url |
http://link.springer.com/article/10.1186/s13634-018-0583-3 |
work_keys_str_mv |
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