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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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Journal ArticleDOI

Robust Localization System Using Vector Combination in Wireless Sensor Networks

Insung Kang, +1 more
- 01 Jan 2022 - 
TL;DR: This paper proposes a vector-based localization system that uses both distance and angle information and has up to 70% higher positioning accuracy compared to the existing iterative range-based algorithm such as MDS-MAP(C,R).
Proceedings ArticleDOI

Intelligent Luminaire based Real-time Indoor Positioning for Assisted Living.

TL;DR: An experimental evaluation on the accuracy of indoor localisation of a configurable cyber-physical system that enables indoor localization and monitoring of older adults living at home or in residential buildings to ascertain whether room-level localization is feasible in real time.
Proceedings ArticleDOI

Recent Breakthroughs in Cognitive Informatics and Cognitive Computing towards Autonomous AI (Plenary Panel Report-I of IEEE ICCI*CC'22)

TL;DR: A summary of the plenary panel (Part I) on the “Recent Breakthroughs in Cognitive Informatics and Cognitive Computing towards Autonomous AI (AAI)” in the 21st IEEE International ICCI*CC Conference (ICCI*CC'22) is presented in this article .
Proceedings ArticleDOI

Unsupervised Manifold Alignment for Wifi RSSI Indoor Localization

TL;DR: Results in this paper show how well the Manifold Alignment Algorithm is beneficial for a localization problem where it is implemented inside a machine learning model that computes the manifold of these datasets.
Proceedings ArticleDOI

Novel ZigBee-Based Smart Anti-Theft System for Electric Bikes for Vietnam

TL;DR: The developed solution herein provides the capability to perform the basic queries to determine the current location of the electric bike using Received Signal Strength Indicator of the Radio Frequency modules which gives the user ability to track the bike in the indoor and outdoor environments, improving personal security with the reduced power consumption in comparison with the existing technologies.
References
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Journal ArticleDOI

Internet of Things for Smart Cities

TL;DR: This paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
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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