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Positioning and Localization in the Internet of Things

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 7716

Special Issue Editors


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Guest Editor
Department of Electronics, Polytechnic School, University of Alcalá, Campus Universitario, 28871 Madrid, Spain
Interests: intelligent sensors; location; positioning systems; optoelectronic sensors; sensor networks; electronic designs; electronic instrumentation; signal treatment

E-Mail Website
Guest Editor
Department of Electronics, Polytechnic School Office O-334, University of Alcalá, Campus Universitario, 28871 – Alcalá, Madrid, Spain
Interests: intelligent sensors; indoor positioning systems; visible light positioning; optical sensorial systems; sensor networks; electronic design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few years, the problem of indoor location and positioning has been a subject of intense study and research. The objective is to achieve the implementation and applicability obtained by outdoor positioning and navigation systems in indoor environments.

This Special Issue will address contributions to improve, correct and/or assist the development and advancement of indoor positioning systems, as well as new implementations and positioning system strategies for any of the existing technologies. It also covers the different applications of indoor positioning systems themselves, such as pedestrian tracking; location-based services in public and commercial centers; assistance services in daily activities; ambient assistant living; location and tracking of users in geriatric and hospital centers; location and tracking of emergency intervention agents (e.g., police/firefighters); location and guidance of autonomous vehicles in industrial environments and automated car parks; tracking of high value goods during storage; and extra information for users via augmented reality, Internet of Things (IoT), etc.

Dr. Álvaro De-La-Llana-Calvo
Prof. Dr. José Luis Lázaro-Galilea
Guest Editors

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Keywords

  • indoor location
  • indoor positioning
  • indoor navigation
  • applications of IPS
  • AoA-DoA
  • PoA
  • ToA
  • RSS

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Published Papers (3 papers)

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Research

11 pages, 3346 KiB  
Communication
Context-Aware Statistical Dead Reckoning for Localization in IoT Scenarios
by David Munoz-Rodriguez, Rafaela Villalpando-Hernandez and Cesar Vargas-Rosales
Sensors 2023, 23(13), 5987; https://doi.org/10.3390/s23135987 - 28 Jun 2023
Viewed by 1158
Abstract
The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. [...] Read more.
The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. In addition, the new generation of smart industries and the energy of things (EoT) context demand novel, reliable, energy-efficient network protocols involving massive sensor cooperation. Such scenarios impose new demands and opportunities to cope with the ever-growing cooperative dense ad hoc environments. Position location information (PLI) plays a crucial role as an enabler of several location-aware network protocols and applications. In this paper, we have proposed a novel context-aware statistical dead reckoning localization technique suitable for high dense cooperative sensor networks, where direct angle and distance estimations between peers are not required along the route, as in other dead reckoning-based localization approaches, but they are obtainable from the node’s context information. Validation of the proposed technique was assessed in several scenarios through simulations, achieving localization errors as low as 0.072 m for the worst case analyzed. Full article
(This article belongs to the Special Issue Positioning and Localization in the Internet of Things)
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27 pages, 34223 KiB  
Article
Fast Deployment of a UWB-Based IPS for Emergency Response Operations
by Toni Adame, Julia Igual and Marisa Catalan
Sensors 2023, 23(9), 4193; https://doi.org/10.3390/s23094193 - 22 Apr 2023
Cited by 5 | Viewed by 3122
Abstract
A wide range of applications from multiple sectors already use ultra-wideband (UWB) technology to locate and track assets precisely. This is not the case, however, for first responder localization during emergency response (ER) operations, which are highly conditioned by procedural and environmental constraints. [...] Read more.
A wide range of applications from multiple sectors already use ultra-wideband (UWB) technology to locate and track assets precisely. This is not the case, however, for first responder localization during emergency response (ER) operations, which are highly conditioned by procedural and environmental constraints. After analyzing these limitations and reviewing the current state-of-the-art solutions, this work presents a UWB-based indoor positioning system (IPS) that relies on the global navigation satellite system real-time kinematic (GNSS-RTK) technology to quickly, accurately, and safely deploy its required infrastructure on site. A set of tests conducted on a two-story building prove the suitability of such a system, providing an average accuracy of less than 1 meter for static targets and the ability to faithfully reproduce the path followed by a mobile target inside the building. The obtained results strengthen the presented approach and pave the way for more sophisticated UWB-based IPSs that would include unmanned aerial vehicles (UAVs) and/or mobile robots to speed up network deployment even more while offering additional ER services. Full article
(This article belongs to the Special Issue Positioning and Localization in the Internet of Things)
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20 pages, 4287 KiB  
Article
An Indoor UWB 3D Positioning Method for Coplanar Base Stations
by Ning Zhou, Minghao Si, Dehai Li, Chee Kiat Seow and Jinzhong Mi
Sensors 2022, 22(24), 9634; https://doi.org/10.3390/s22249634 - 8 Dec 2022
Cited by 7 | Viewed by 2719
Abstract
As an indispensable type of information, location data are used in various industries. Ultrawideband (UWB) technology has been used for indoor location estimation due to its excellent ranging performance. However, the accuracy of the location estimation results is heavily affected by the deployment [...] Read more.
As an indispensable type of information, location data are used in various industries. Ultrawideband (UWB) technology has been used for indoor location estimation due to its excellent ranging performance. However, the accuracy of the location estimation results is heavily affected by the deployment of base stations; in particular, the base station deployment space is limited in certain scenarios. In underground mines, base stations must be placed on the roof to ensure signal coverage, which is almost coplanar in nature. Existing indoor positioning solutions suffer from both difficulties in the correct convergence of results and poor positioning accuracy under coplanar base-station conditions. To correctly estimate position in coplanar base-station scenarios, this paper proposes a novel iterative method. Based on the Newton iteration method, a selection range for the initial value and iterative convergence control conditions were derived to improve the convergence performance of the algorithm. In this paper, we mathematically analyze the impact of the localization solution for coplanar base stations and derive the expression for the localization accuracy performance. The proposed method demonstrated a positioning accuracy of 5 cm in the experimental campaign for the comparative analysis, with the multi-epoch observation results being stable within 10 cm. Furthermore, it was found that, when base stations are coplanar, the test point accuracy can be improved by an average of 63.54% compared to the conventional positioning algorithm. In the base-station coplanar deployment scenario, the upper bound of the CDF convergence in the proposed method outperformed the conventional positioning algorithm by about 30%. Full article
(This article belongs to the Special Issue Positioning and Localization in the Internet of Things)
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