Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Book Part Citation - Scopus: 12Realizing the Wireless Technology in Internet of Things (IoT)(Springer Singapore, 2018) Κogias, DImitrios G.; Michailidis, Emmanouel T.; Tuna, Gürkan; Güngör, Vehbi Çağrı; Kogias, Dimitrios G.The evolution of the Internet of Things (IoT) has been highly based on the advances on wireless communications and sensing capabilities of smart devices, along with a, still increasing, number of applications that are being developed which manage to cover various small and more important aspects of every people's life. This chapter aims at presenting the wireless technologies and protocols that are used for the IoT communications, along with the main architectures and middleware that have been proposed to serve and enhance the IoT capabilities and increase its efficiency. Finally, since the generated data that are spread in an IoT ecosystem might include sensitive information (e.g., personal medical data by sensors), we will also discuss the security and privacy hazards that are introduced from the advances in the development and application of an IoT environment. © 2019 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 7Citation - Scopus: 10PI-Controlled ANN-Based Energy Consumption Forecasting for Smart Grids(SciTePress, 2015) Gezer, Gülsüm; Tuna, Gürkan; Κogias, DImitrios G.; Gülez, Kayhan; Güngör, Vehbi Çağrı; Kogias, DimitrisAlthough Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities must comply with new expectations for their operations, and address new challenges such as energy efficiency regulations and guidelines, possibility of economic recessions, volatility of fuel prices, new user profiles and demands of regulators. In order to meet all these emerging economic and regulatory realities, the electric utilities operating SGs must be able to determine and meet load, implement new technologies that can effect energy sales and interact with their customers for their purchases of electricity. In this respect, load forecasting which has traditionally been done mostly at city or country level can address such issues vital to the electric utilities. In this paper, an artificial neural network based energy consumption forecasting system is proposed and the efficiency of the proposed system is shown with the results of a set of simulation studies. The proposed system can provide valuable inputs to smart grid applications. © 2022 Elsevier B.V., All rights reserved.Book Part Cognitive Radio Networks for Smart Grid Communications: Potential Applications, Protocols, and Research Challenges(CRC Press, 2017-12-19) Κogias, DImitrios G.; Tuna, Gürkan; Güngör, Vehbi ÇağrıA smart grid (SG) is the next generation of power grid, where transmission, distribution, power generation, utilization, and management are fully upgraded to improve efficiency, agility, environmental friendliness, economy, security, and reliability [1-4]. It offers two-way communication between the base stations and power generation sites [2-5], and optimizes the overall system performance by taking the advantage of wireless sensor networks (WSNs) [6-13], using smart sensor devices, and implementing renewable energy solutions. Since SG consists of many different applications with different communication and quality of service (QoS) requirements, it involves heterogeneous communication technologies based on a multitier communication infrastructure. © 2019 Elsevier B.V., All rights reserved.