Electronics 2021, 10, 3016. https://doi.org/10.3390/electronics10233016 www.mdpi.com/journal/electronics Article Proposal for a Localization System for an IoT Ecosystem Juraj Machaj 1, *, Peter Brida 1 and Slavomir Matuska 2 1 Department of Multimedia and Information‐Communication Technology, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia; peter.brida@feit.uniza.sk 2 Research Centre, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia; slavomir.matuska@feit.uniza.sk * Correspondence: juraj.machaj@feit.uniza.sk Abstract: In the last decade, positioning using wireless signals has gained a lot of attention since it could open new opportunities for service providers. Localization is important, especially in indoor environments, where the widely used global navigation satellite systems (GNSS) signals suffer from high signal attenuation and multipath propagation, resulting in poor accuracy or a loss of positioning service. Moreover, in an Internet of things (IoT) environment, the implementation of GNSS receivers into devices may result in higher demands on battery capacity, as well as increased cost of the hardware itself. Therefore, alternative localization systems that are based on wireless signals for the communication of IoT devices are gaining a lot of attention. In this paper, we provide a design of an IoT localization system, which consists of multiple localization modules that can be utilized for the positioning of IoT devices that are connected thru various wireless technologies. The proposed system can currently perform localization based on received signals from LoRaWAN, ZigBee, Wi‐Fi, UWB and cellular technologies. The implemented pedestrian dead reckoning algorithm can process the data measured by a mobile device that is equipped with inertial sensors to construct a radio map and thus help with the deployment of the positioning services based on a fingerprinting approach. Keywords: localization; positioning; IoT; Wi‐Fi; ZigBee; LoRaWAN; UWB 1. Introduction In recent years, a lot of research has been focused on novel smart solutions for smarter cities, smart transport and Industry 4.0 [1,2]. Most of these solutions rely on a vast amount of data that are collected by sensors and devices connected to the Internet, which is sometimes referred to as the Internet of everything (IoE) or the Internet of things (IoT) [3]. The connection of a large number of sensors and devices can be realized using heterogeneous wireless technologies since IoT devices may have different requirements on bandwidth and energy consumption [4,5]. There is a large number of different IoT applications and services; however, some of them require positioning information that is linked to the data from devices in order to be meaningful for the service provided to the user. The positioning information can be easily extracted from the global navigation satellite systems (GNSS) receiver; however, the implementation of such a receiver into the device not only increases its price but also has a negative impact on energy consumption. Moreover, if devices are deployed in dense urban or indoor environments, both the availability and reliability of GNSS‐based positioning are very low due to signal blockage and strong multipath propagation [6]. Therefore, alternative solutions for position estimation have been intensively studied in the last couple of years. Various technologies have attracted attention in the area of position estimation, including camera‐based systems with image processing [7], measurements of magnetic field fluctuations [8], the use of inertial measurements units implemented in devices [9] Citation: Machaj, J.; Brida, P.; Matuska, S. Proposal for a Localization System for an IoT Ecosystem. Electronics 2021, 10, 3016. https://doi.org/10.3390/ electronics10233016 Academic Editors: Jaime Lloret, Joel J. P. C. Rodrigues and Juan‐Carlos Cano Received: 6 October 2021 Accepted: 1 December 2021 Published: 2 December 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses /by/4.0/).