In recent years, there has been a growing interest in building smart cities based on the Internet of Things (IoT) technology. However, selecting a low-cost IoT wireless technology that enables low-power connectivity remains one of the key challenges in integrating IoT to smart cities. In this context, the IQRF technology offers promising opportunities to provide cost-effective solutions. Yet, in the literature, there are limited studies on utilizing IQRF technology for smart city applications. Therefore, this study is aimed at increasing the awareness about the use of IQRF technology in IoT-based smart city development. For this purpose, a review of smart city architectures along with challenges/requirements in adopting IoT for smart cities is provided. Then, some of the common cost-effective IoT wireless technologies that enable low-power consumption are briefly presented. Next, the benefits of IQRF technology over other technologies are discussed by making theoretical comparisons based on technical documentations and reports. Moreover, the research efforts currently being undertaken by the authors as a part of ongoing project on the development of IoT-based smart city system in Gjøvik Municipality, Norway, are conceptually introduced. Finally, the future research directions are addressed.
For the past few years, the Internet of Things (IoT) technology continues to not only gain popularity and importance, but also witnesses the true realization of everything being smart. With the advent of the concept of smart everything, IoT has emerged as an area of great potential and incredible growth. An IoT ecosystem centers around innovation perspective which is considered as its fundamental core. Accordingly, IoT enabling technologies such as hardware and software platforms as well as standards become the core of the IoT ecosystem. However, any large-scale technological integration such as the IoT development poses the challenge to ensure secure data transmission. Perhaps, the ubiquitous and the resource-constrained nature of IoT devices and the sensitive and private data being generated by IoT systems make them highly vulnerable to physical and cyber threats. In this paper, we re-define an IoT ecosystem from the core technologies view point. We propose a modified three layer IoT architecture by dividing the perception layer into elementary blocks based on their attributed functions. Enabling technologies, attacks and security countermeasures are classified under each layer of the proposed architecture. Additionally, to give the readers a broader perspective of the research area, we discuss the role of various state-of-the-art emerging technologies in the IoT security. We present the security aspects of the most prominent standards and other recently developed technologies for IoT which might have the potential to form the yet undefined IoT architecture. Among the technologies presented in this article, we give a special interest to one recent technology in IoT domain. This technology is named IQRF that stands for Intelligent Connectivity using Radio Frequency. It is an emerging technology for wireless packet-oriented communication that operates in sub-GHz ISM band (868 Mhz) and which is intended for general use where wireless connectivity is needed, either in a mesh network or pointto-point (P2P) configuration. We also highlighted the security aspects implemented in this technology and we compare it with the other already known technologies. Moreover, a detailed discussion on the possible attacks is presented. These attacks are projected on the IoT technologies presented in this article including IQRF. In addition, lightweight security solutions, implemented in these technologies, to counter these threats in the proposed IoT ecosystem architecture are also presented. Lastly, we summarize the survey by listing out some common challenges and the future research directions in this field.INDEX TERMS Cyber attacks, IoT architecture, Internet of Things (IoT) ecosystem, IQRF, Network security.
Recently, IQRF has emerged as a promising technology for the Internet of Things (IoT), owing to its ability to support short- and medium-range low-power communications. However, real world deployment of IQRF-based wireless sensor networks (WSNs) requires accurate path loss modelling to estimate network coverage and other performances. In the existing literature, extensive research on propagation modelling for IQRF network deployment in urban environments has not been provided yet. Therefore, this study proposes an empirical path loss model for the deployment of IQRF networks in a peer-to-peer configured system where the IQRF sensor nodes operate in the 868 MHz band. For this purpose, extensive measurement campaigns are conducted outdoor in an urban environment for Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) links. Furthermore, in order to evaluate the prediction accuracy of well-known empirical path loss models for urban environments, the measurements are compared with the predicted path loss values. The results show that the COST-231 Walfisch–Ikegami model has higher prediction accuracy and can be used for IQRF network planning in LoS links, while the COST-231 Hata model has better accuracy in NLoS links. On the other hand, the effects of antennas on the performance of IQRF transceivers (TRs) for LoS and NLoS links are also scrutinized. The use of IQRF TRs with a Straight-Line Dipole Antenna (SLDA) antenna is found to offer more stable results when compared to IQRF (TRs) with Meander Line Antenna (MLA) antenna. Therefore, it is believed that the findings presented in this article could offer useful insights for researchers interested in the development of IoT-based smart city applications.
Owing to its efficiency in the Internet of Things (IoT) applications in terms of low-power connectivity, IQRF (Intelligent Connectivity using Radio Frequency) technology appears to be one of the most reasonable IoT technologies in the commercial market. To realize emerging smart building applications using IQRF, it is necessary to study the propagation characteristics of IQRF technology in indoor environments. In this study, preliminary propagation measurements are conducted using IQRF transceivers that operate on the 868 MHz band in a peer-to-peer (P2P) configured system. The measurements are conducted both in a single corridor of a building in a Line-of-Sight (LoS) link and two perpendicular corridors in a Non-Line-of-Sight (NLoS) with one single knife-edge link. Moreover, the measured path loss values are compared with the predicted path loss values in order to comparatively assess the prediction accuracy of the well-known empirical models, such as log-distance, ITU, and WINNER II. According to the results, it is concluded that the ITU-1 path loss model agrees well with the measurements and could be used in the planning of an IQRF network deployment in a typical LoS corridor environment. For NLoS corridors, both ITU-3 and WINNERII-2 models could be used due to their higher prediction accuracy. We expect that the initial results achieved in this study could open new perspectives for future research on the development of smart building applications.
Low-power wide area network (LPWAN) technologies such as IQRF are becoming increasingly popular for a variety of Internet of Things (IoT) applications, including smart cities, industrial control, and home automation. However, LPWANs are vulnerable to cyber attacks that can disrupt the normal operation of the network or compromise sensitive information. Therefore, analyzing cybersecurity risks before deploying an LPWAN is essential, as it helps identify potential vulnerabilities and threats as well as allowing for proactive measures to be taken to secure the network and protect against potential attacks. In this paper, a security risk analysis of IQRF technology is conducted utilizing the failure mode effects analysis (FMEA) method. The results of this study indicate that the highest risk corresponds to four failure modes, namely compromised end nodes, a compromised coordinator, a compromised gateway and a compromised communication between nodes. Moreover, through this methodology, a qualitative risk evaluation is performed to identify potential security threats in the IQRF network and propose countermeasures to mitigate the risk of cyber attacks on IQRF networks.
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