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Article Citation - WoS: 18Citation - Scopus: 24Use of the Iqrf Technology in Internet-Of Smart Cities(Ieee-inst Electrical Electronics Engineers inc, 2020) Bouzidi, Mohammed; Dalveren, Yaser; Cheikh, Faouzi Alaya; Derawi, MohammadIn 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 Gj & x00F8;vik Municipality, Norway, are conceptually introduced. Finally, the future research directions are addressed.Conference Object Security Requirements in Iot Environments(Springer Science and Business Media Deutschland GmbH, 2022) Binglaw,F.; Koyuncu,M.; Pusatlı,T.The Internet of Things (IoT) is a relatively new concept as it connects things (or objects) that do not have high computational power. The IoT helps these things see, listen, and take action by interoperating with minimal human intervention to make people’s lives easier. However, these systems are vulnerable to attacks and security threats that could potentially undermine consumer confidence in them. For this reason, it is critical to understand the characteristics of IoT security and their requirements before starting to discuss how to protect them. In this scope, the present work reviews the importance of security in IoT applications, factors that restrict the use of traditional security methods to protect IoTs, and the basic requirements necessary to judge them as secure environments. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.Review Citation - WoS: 75Citation - Scopus: 120Hybrid Blockchain Platforms for the Internet of Things (iot): a Systematic Literature Review(Mdpi, 2022) Alkhateeb, Ahmed; Catal, Cagatay; Kar, Gorkem; Mishra, AlokIn recent years, research into blockchain technology and the Internet of Things (IoT) has grown rapidly due to an increase in media coverage. Many different blockchain applications and platforms have been developed for different purposes, such as food safety monitoring, cryptocurrency exchange, and secure medical data sharing. However, blockchain platforms cannot store all the generated data. Therefore, they are supported with data warehouses, which in turn is called a hybrid blockchain platform. While several systems have been developed based on this idea, a current state-of-the-art systematic overview on the use of hybrid blockchain platforms is lacking. Therefore, a systematic literature review (SLR) study has been carried out by us to investigate the motivations for adopting them, the domains at which they were used, the adopted technologies that made this integration effective, and, finally, the challenges and possible solutions. This study shows that security, transparency, and efficiency are the top three motivations for adopting these platforms. The energy, agriculture, health, construction, manufacturing, and supply chain domains are the top domains. The most adopted technologies are cloud computing, fog computing, telecommunications, and edge computing. While there are several benefits of using hybrid blockchains, there are also several challenges reported in this study.Article Citation - WoS: 4Citation - Scopus: 6A Conceptual Design of Smart Management System for Flooding Disaster(Mdpi, 2021) Ibrahim, Thaer; Mishra, AlokDisasters pose a real threat to the lives and property of citizens; therefore, it is necessary to reduce their impact to the minimum possible. In order to achieve this goal, a framework for enhancing the current disaster management system was proposed, called the smart disaster management system. The smart aspect of this system is due to the application of the principles of information and communication technology, especially the Internet of Things. All participants and activities of the proposed system were clarified by preparing a conceptual design by using The Unified Modeling Language diagrams. This effort was made to overcome the lack of citizens' readiness towards the use of information and communication technology as well as increase their readiness towards disasters. This study aims to develop conceptual design that can facilitate in development of smart management system for flooding disaster. This will assist in the design process of the Internet of Things systems in this regard.Article Citation - Scopus: 1From Street Canyons To Corridors: Adapting Urban Propagation Models for an Indoor IQRF Network(MDPI, 2025) Doyan, Talip Eren; Yalcinkaya, Bengisu; Dogan, Deren; Dalveren, Yaser; Derawi, MohammadAmong wireless communication technologies underlying Internet of Things (IoT)-based smart buildings, IQRF (Intelligent Connectivity Using Radio Frequency) technology is a promising candidate due to its low power consumption, cost-effectiveness, and wide coverage. However, effectively modeling the propagation characteristics of IQRF in complex indoor environments for simple and accurate network deployment remains challenging, as architectural elements like walls and corners cause substantial signal attenuation and unpredictable propagation behavior. This study investigates the applicability of a site-specific modeling approach, originally developed for urban street canyons, to characterize peer-to-peer (P2P) IQRF links operating at 868 MHz in typical indoor scenarios, including line-of-sight (LoS), one-turn, and two-turn non-line-of-sight (NLoS) configurations. The received signal powers are compared with well-known empirical models, including international telecommunication union radio communication sector (ITU-R) P.1238-9 and WINNER II, and ray-tracing simulations. The results show that while ITU-R P.1238-9 achieves lower prediction error under LoS conditions with a root mean square error (RMSE) of 5.694 dB, the site-specific approach achieves substantially higher accuracy in NLoS scenarios, maintaining RMSE values below 3.9 dB for one- and two-turn links. Furthermore, ray-tracing simulations exhibited notably larger deviations, with RMSE values ranging from 7.522 dB to 16.267 dB and lower correlation with measurements. These results demonstrate the potential of site-specific modeling to provide practical, computationally efficient, and accurate insights for IQRF network deployment planning in smart building environments.Article Citation - WoS: 1Citation - Scopus: 1Internet of Things (iot) and Artificial Neural Networks Towards Water Pollution Forecasting(Middle Pomeranian Sci Soc Env Prot, 2020) Ibrahim, Thaer; Mishra, Alok; Software EngineeringWater could be some-times a source of danger on people's lives and property. Although it is one of the most important elements of life on this planet. This article define the threat of water pollution in Tigris River in Iraq. by collecting a data that generated by sensors that installed in a water pollution sensing project in Baghdad city, also this article aimed to detect and analyze the behavior of water environment. It is an effort to predict the threat of pollution by using advanced scientific methods like the technology of Internet of Things (IoT) and Machine learning in order to avoid the threat and/or minimize the possible damages. This can be used as a proactive service provided by E-governments towards their own citizens.Conference Object Citation - Scopus: 1Semantic Interoperability and Reusability in Iot: a Systematic Mapping Study(Institute of Electrical and Electronics Engineers Inc., 2024) Alsaeh, A.; Sezen, A.Internet of Things (IoT) enables different devices, sensors, or humans to connect via the Internet. However, various IoT devices generate heterogeneous data in different formats. This hinders IoT devices from integrating and exchanging data between them. Adding semantic web technologies to the Web of Things (WoT) has greatly enabled IoT devices to be semantically interoperable. Moreover, W3C has established a Semantic Sensor Network (SSN) ontology that can be reused in different IoT applications due to difficulties in developing new ontologies. Many systematic mapping reviews in the literature have addressed semantic interoperability in IoT. Although reusability can play a vital role in enhancing semantic interoperability, none of those studies has discussed reusability and semantic interoperability together in the IoT area. In this article, we are seeking to fill this gap in the current literature by conducting a systematic mapping review for 72 articles to point out semantic interoperability as well as reusability in IoT. Five research questions have been identified regarding challenges and possible solutions about both semantic interoperability and reusability. The reviewed articles are classified into four categories. There are 47 articles about semantic interoperability, 2 of which discuss reusability, 18 of which include semantic interoperability with reusability, and the last category includes surveys. Moreover, the research questions are also assigned to the related category that answers the questions. This article highlights important insights about semantic web techniques namely, RDF, ontology, SPARQL, and OWL. Additionally, this article concludes how these techniques are enhanced in diverse domains such as healthcare, smart cities, and the energy domain. On top of that, this systematic mapping shows how reused ontology plays a remarkable role in the IoT domain Finally, results that answer the research questions are figured out and deeply analyzed in the tables and graphs. © 2024 IEEE.Conference Object An Iot Application for Locating Victims Aftermath of an Earthquake(Ieee, 2017) Karakaya, Murat; Sengul, Gokhan; Gokcay, ErhanThis paper presents an Internet of Things (IoT) framework which is specially designed for assisting the research and rescue operations targeted to collapsed buildings aftermath of an earthquake. In general, an IoT network is used to collect and process data from different sources called things. According to the collected data, an IoT system can actuate different mechanisms to react the environment. In the problem at hand, we exploit the IoT capabilities to collect the data about the victims before the building collapses and when it falls down the collected data is processed to generate useful reports which will direct the search and rescue efforts. The proposed framework is tested by a pilot implementation with some simplifications. The initial results and experiences are promising. During the pilot implementation, we observed some issues which are addressed in the proposed IoT framework properly.Article Citation - WoS: 7Citation - Scopus: 8A Simplified Method Based on Rssi Fingerprinting for Iot Device Localization in Smart Cities(Ieee-inst Electrical Electronics Engineers inc, 2024) Dogan, Deren; Dalveren, Yaser; Kara, Ali; Derawi, MohammadThe Internet of Things (IoT) has significantly improved location-based services in smart cities, such as automated public transportation and traffic management. Estimating the location of connected devices is a critical problem. Low Power Wide Area Network (LPWAN) technologies are used for localization due to their low power consumption and long communication range. Recent advances in Machine Learning have made Received Signal Strength Indicator (RSSI) fingerprinting with LPWAN technologies effective. However, this requires a connection between devices and gateways or base stations, which can increase network deployment, maintenance, and installation costs. This study proposes a cost-effective RSSI fingerprinting solution using IQRF technology for IoT device localization. The region of interest is divided into grids to provide training locations, and measurements are conducted to create a training dataset containing RSSI fingerprints. Pattern matching is performed to localize the device by comparing the fingerprint of the end device with the fingerprints in the created database. To evaluate the efficiency of the proposed solution, measurements were conducted in a short-range local area ( $80\times 30$ m) at 868 MHz. In the measurements, four IQRF nodes were utilized to receive the RSSIs from a transmitting IQRF node. The performances of well-known ML classifiers on the created dataset are then comparatively assessed in terms of test accuracy, prediction speed, and training time. According to the results, the Bagged Trees classifier demonstrated the highest accuracy with 96.87%. However, with an accuracy of 95.69%, the Weighted k-NN could also be a reasonable option for real-world implementations due to its faster prediction speed (37615 obs/s) and lower training time (28.1 s). To the best of the authors' knowledge, this is the first attempt to explore the feasibility of the IQRF networks to develop a RSSI fingerprinting-based IoT device localization in the literature. The promising results suggest that the proposed method could be used as a low-cost alternative for IoT device localization in short-range location-based smart city applications.Master Thesis İnternet Nesneleri (IoT) Ortamında Makine Öğrenmesi Kullanılarak Saldırı Tespiti: Ton-ıot Veri Seti İle Ağ Katmanına Odaklanma(2025) Alawneh, Ahmad; Koyuncu, MuratNesnelerin İnterneti (IoT), modern ağ sistemlerini dönüştürürken, çeşitli ve kaynak kısıtlı mimarisi nedeniyle önemli güvenlik risklerini de ortaya çıkarmıştır. Geleneksel Saldırı Tespit Sistemleri (IDS), özellikle ağ katmanında IoT tehditlerinin gelişen özelliklerini yeterince karşılayamamaktadır. Bu tez, ToN-IoT veri kümesi için özel olarak tasarlanmış, özellik-iyileştirmeli makine öğrenimine dayalı bir Ağ Saldırı Tespit Sistemi (NIDS) sunmaktadır. Önerilen çok aşamalı çerçeve, boyutluluğu azaltmak, fazlalığı gidermek ve gerçek zamanlı performansı iyileştirmek amacıyla istatistiksel (Pearson, Spearman, Ki-Kare) ve gömülü (Random Forest) öznitelik seçimi yöntemlerini bütünleştirmektedir. İkili ve çok sınıflı saldırı tespiti görevleri için Lojistik Regresyon, En Yakın Komşular (KNN), Karar Ağacı, Rastgele Orman (RF), Gauss Naive Bayes, Yapay Sinir Ağları (ANN), XGBoost, Gradient Boosting, AdaBoost ve ExtraTrees dâhil olmak üzere geniş bir sınıflandırıcı kümesi üzerinde kapsamlı karşılaştırmalar gerçekleştirilmiştir. Değerlendirme metrikleri F1-skoru, AUC, MCC ve çıkarım gecikmesini içermektedir. Bulgular, özellik seçiminin verimli sınıflandırıcılarla entegrasyonunun tespit doğruluğunu ve kaynak kısıtlı ortamlardaki operasyonel uygulanabilirliği önemli ölçüde artırdığını göstermektedir. Bu tez, IoT güvenlik uzmanları için çoğaltılabilir bir çerçeve ve pratik içgörüler sunarak sınıflandırıcı karmaşıklığı, yorumlanabilirlik ve gerçek zamanlı uygulanabilirlik arasındaki dengeyi vurgular. Elde edilen sonuçlar, ölçeklenebilir ve gelişmiş IoT güvenlik mimarileri için pragmatik bir temel sağlamaktadır.
