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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
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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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Journal ArticleDOI

Detection of Security Attack in IoT using Received Signal Strength Indicator

TL;DR: RSSI values are used to find the location of sensor nodes in given various topologies using Contiki OS and its inbuilt Cooja simulator to achieve small-size and cost-effective solution.
Dissertation

Design and Analysis of Wireless-Based Technologies for Indoor Localization Systems

TL;DR: This work investigates a Wireless Sensor Network used for performing indoor localization under a variety of wireless technologies, localization techniques, and filtering algorithms and determined WiFi was determined to have the lowest error overall, while Bluetooth Low Energy consumed the lowest amount of power.
Journal ArticleDOI

Packet forwarding mechanism for mobile robots bounded by random walk model

TL;DR: This paper presents a packet forwarding mechanism for ZigBee based mobile wireless sensor network nodes and shows that the packet loss rate comes around to be 2 percent resulting in a 98 percent successful packet reception at the receiver end.
Journal ArticleDOI

RSSI study of wireless Internet of Things technologies

Diyan Dinev, +1 more
- 01 Sep 2022 - 
TL;DR: The RSSI values of sensor nodes in the BLE, ZigBee and LoRa networks for IoT were explore in this study and can be used to locate mobile sensor nodes for low-power IoT networks.
Journal ArticleDOI

Real-time robust and precise kernel learning for indoor localization under the internet of things

Carmen Mitidieri
- 01 Jul 2023 - 
TL;DR: Wang et al. as discussed by the authors proposed an online risk-sensitive localization technique named compositional online kernel indoor localization (COKIL), which further improves the performance and reduces the prediction variance under multi-path effects.
References
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Journal ArticleDOI

Internet of Things for Smart Cities

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Journal ArticleDOI

Survey of Wireless Indoor Positioning Techniques and Systems

TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Journal ArticleDOI

Smart objects as building blocks for the Internet of things

TL;DR: The authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity for smart objects, describing activity-, policy-, and process-aware smart objects and demonstrating how the respective architectural abstractions support increasingly complex application.
Journal ArticleDOI

A Survey of Indoor Localization Systems and Technologies

TL;DR: This paper aims to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time ofFlight (RTOF), and received signal strength (RSS) based on technologies that have been proposed in the literature.
Journal ArticleDOI

Location Fingerprinting With Bluetooth Low Energy Beacons

TL;DR: This work provides a detailed study of BLE fingerprinting using 19 beacons distributed around a ~600 m2 testbed to position a consumer device, and investigates the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency.
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