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Open AccessJournal ArticleDOI

RSSI-Based Indoor Localization With the Internet of Things

Sebastian Sadowski, +1 more
- 04 Jun 2018 - 
- Vol. 6, pp 30149-30161
TLDR
Four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network are compared in terms of localization accuracy and power consumption when IoT devices are used.
Abstract
In the era of smart cities, there are a plethora of applications where the localization of indoor environments is important, from monitoring and tracking in smart buildings to proximity marketing and advertising in shopping malls. The success of these applications is based on the development of a cost-efficient and robust real-time system capable of accurately localizing objects. In most outdoor localization systems, global positioning system (GPS) is used due to its ease of implementation and accuracy up to five meters. However, due to the limited space that comes with performing localization of indoor environments and the large number of obstacles found indoors, GPS is not a suitable option. Hence, accurately and efficiently locating objects is a major challenge in indoor environments. Recent advancements in the Internet of Things (IoT) along with novel wireless technologies can alleviate the problem. Small-size and cost-efficient IoT devices which use wireless protocols can provide an attractive solution. In this paper, we compare four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network. These technologies are compared in terms of localization accuracy and power consumption when IoT devices are used. The received signal strength indicator (RSSI) values from each modality were used and trilateration was performed for localization. The RSSI data set is available online. The experimental results can be used as an indicator in the selection of a wireless technology for an indoor localization system following application requirements.

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Citations
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A Survey of Indoor Localization Systems and Technologies

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A Meta-Review of Indoor Positioning Systems.

TL;DR: This paper provides an introduction to IPS and the different technologies, techniques, and some methods commonly employed and serves as a guide for the reader to easily find further details on each technology used in IPS.
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Assistant Vehicle Localization Based on Three Collaborative Base Stations via SBL-Based Robust DOA Estimation

TL;DR: An assistant vehicle localization method based on direction-of-arrival (DOA) estimation based on a sparse Bayesian learning (SBL)-based robust DOA estimation approach is proposed, which shows the effectiveness and superiority of the proposed method.
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BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum

TL;DR: Experimental results on distance estimation, location, and detection accuracy show that BLE beacon is a promising solution for an interactive smart museum.
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A Survey of Machine Learning for Indoor Positioning

TL;DR: A comprehensive survey of ML enabled localization techniques using most common wireless technologies for accurate indoor positioning and how the ML algorithms can be effectively used for fusing different technologies and algorithms to achieve a comprehensive IPS is provided.
References
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Proceedings ArticleDOI

Distance measurement and error estimation scheme for RSSI based localization in Wireless Sensor Networks

TL;DR: The estimated distances can be further used for locating the position of deployed sensor nodes using RSS measurements and the working model has been realised in TinyOs and RSS measurements are made using Telosb nodes.
Journal ArticleDOI

Real-Time Locating Systems Using Active RFID for Internet of Things

TL;DR: This paper proposes a newly fashioned RTLS using active RFID for the IoT, iLocate, which locates objects at high levels of accuracy up to 30 cm with ultralong distance transmission and leverages the ZigBee to achieve fine-grained localization accuracy.
Journal ArticleDOI

Localization Techniques in Wireless Sensor Networks

TL;DR: In this paper, sensor node architecture and its applications, different localization techniques, and few possible future research directions are discussed.
Proceedings Article

Does BTLE measure up against WiFi? A comparison of indoor location performance

TL;DR: It is demonstrated in experiments that BTLE propagation model can better relate RSSI to range than WiFi, which indicates that BTle can be more accurate when used in localization scenarios.
Journal ArticleDOI

Generalized Rao Test for Decentralized Detection of an Uncooperative Target

TL;DR: A novel fusion rule corresponding to a generalized Rao test is developed and a rationale for threshold-optimization is proposed and confirmed by simulations to reduce the computational complexity of distributed detection of a noncooperative target with a wireless sensor network.
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