Researcher:
Çetinkaya, Oktay

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Oktay

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Çetinkaya

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Çetinkaya, Oktay

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2015 - 2019132020 - 20236

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Now showing 1 - 10 of 19
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    Electric-field energy harvesting in wireless networks
    (Ieee-Inst Electrical Electronics Engineers Inc, 2017) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Çetinkaya, Oktay; Akan, Özgür Barış; Other; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; N/A; 6647
    Electric-field energy harvesting (EFEH) can be considered as an emerging and promising alternative for self-sustainable next-generation WSNs. Unlike conventional harvesting methods that rely on ambient variables, EFEH provides more reliable and durable operation as it is operable with any voltage-applied conductive material. Therefore, it is better suited for advanced throughput and applications requiring a certain QoS. In this article, we introduce this newly emerging WSN paradigm, and focus on enabling EFEH technology for smart grid architectures, such as home, building, and near area networks, where the field intensity is relatively low. To this end, a practical methodology and a general use implementation framework have been developed for low-voltage applications by regarding compelling design issues and challenging source scarcity. The proposed double-layer harvester model is experimentally evaluated. Its performance in terms of implementation flexibility, sensor lifetime, and communication throughput is investigated. In addition, current challenges, open issues, and future research directions are discussed for the design of more enhanced EFEH wireless networks.
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    Energy-harvesting cognitive radios in smart cities
    (John Wiley and Sons Ltd, 2019) N/A; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Özger, Mustafa; Çetinkaya, Oktay; Akan, Özgür Barış; PhD Student; Researcher; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 6647
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    Nanosensor networks for smart health care
    (Elsevier, 2020) Abbasi, Naveed A.; Department of Electrical and Electronics Engineering; N/A; N/A; Department of Electrical and Electronics Engineering; Akan, Özgür Barış; Khan, Tooba; Civaş, Meltem; Çetinkaya, Oktay; Faculty Member; PhD Student; PhD Student; Other; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; 6647; N/A; N/A; N/A
    Advent of nanoscale sensors has paved the way for countless applications envisioned in the concept of a Smart City. In this chapter, we are focusing on one of the most fundamental requirements of the smart city, that is, smart health care. Great advancements in personal health care are expected with the emergence of nanosensing devices; however, single nanosensor is limited in its processing power and storage; thus we need to form network of nanosensors for any health-care application. In this chapter, we first elaborate the communication paradigms for nanosensor network. Moreover, we discuss various smart health-care applications such as smart drug delivery, body area network, implantable devices to treat injuries or malfunctions, and Internet of Nano Things. In the end, we highlight the implementation challenges for the nanosensor network for biomedical applications.
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    Energy neutral internet of drones
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) Long, Teng; Akan, Özgür Barış; N/A; Department of Electrical and Electronics Engineering; Özger, Mustafa; Çetinkaya, Oktay; PhD Student; Researcher; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A
    Extensive use of amateur drones (ADrs) poses a threat to the public safety due to their possible misuse. Hence, surveillance drones (SDrs) are utilized to detect and eliminate potential threats. However, limited battery, and lack of efficient communication and networking solutions degrade the quality of surveillance. To this end, we conceptualize the Energy Neutral Internet of Drones (enIoD) to enable enhanced connectivity between drones by overcoming energy limitations for autonomous and continuous operation. Power provisioning with recharging stations is introduced by wireless power transfer to energize the drones. Renewable energy harvesting is utilized to realize energy neutrality, which is minimization of deficit in harvested and consumed energy in enIoD. Communication and networking architectures and protocols for realization of multi-dimensional objectives are presented. Finally, possible application areas are explained with a case study to show how enIoD operates.
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    Internet of energy harvesting cognitive radios
    (Springer Nature, 2020) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; N/A; Akan, Özgür Barış; Çetinkaya, Oktay; Özger, Mustafa; Faculty Member; Researcher; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 6647; N/A; N/A
    The Internet of Things (IoT) offers enhanced connectivity so that any system, being, or process can be reached from anywhere at any time by perpetual surveillance, which results in very large and complex data sets, i.e., Big Data. Despite numerous advantages, IoT technology comes with some unavoidable drawbacks. Considering the number of devices to be added to the current electromagnetic spectrum, it is a fact that wireless communications will severely suffer and eventually become inoperable. Furthermore, as wireless devices are equipped with limited capacity batteries, frequent replenishments and/or maintenance will be needed. However, this is neither practical nor achievable due to the excessive number of devices envisioned by the IoT paradigm. Here, the unification of Energy Harvesting (EH) and Cognitive Radio (CR) stands highly promising to alleviate the current drawbacks, enabling more efficient data generation, acquisition, and analysis. This chapter outlines a new vision, namely Internet of Energy Harvesting Cognitive Radios (IoEH-CRs), to take the IoT-enabled Big Data paradigm a step further. It discusses the basics of the EH-assisted spectrum-aware communications and their implications for the IoT, as well as the challenges posed by the unification of these techniques. An operational framework together with node and network architectures is also presented.
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    A ZigBee based reliable and efficient power metering system for energy management and controlling
    (Ieee, 2015) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Çetinkaya, Oktay; Akan, Özgür Barış; Other; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; N/A; 6647
    Planning and management of energy are among the most important topics nowadays due to the fact that the existing power plants and systems fail to satisfy the energy demand and keep up with the daily developing technologies. To maintain the energy need of the existing systems, researchers are aiming to improve usage and savings of available resources and systems. For example, power metering system has been proposed to decrease the energy wasting. The purpose of this system can be explained as limiting the energy consumption in some cases like stand-by or while switching programs or devices which the system is installed on. By blocking the unnecessary consumption of energy, profits and savings are targeted. In this work, a new power meter system based on ZigBee technology is designed and implemented to obtain a more efficient structure and reduce the number of disadvantages of the existing technologies. In SmartPlug, the MCU was moved into the plug from outer environment and shifting the host to a spectator to eliminate user based faults and/or problems. Moreover, the proposed structure enhances the safety by detecting the sudden voltage fluctuations and preventing the possible damages of end-devices. In addition to these, we prove that cutting of stand-by powers and limiting the energy consumption by arranging the working hours of devices based on energy unit prices provide efficient, right and cheap usage of the energy.
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    A DASH7-based power metering system
    (IEEE, 2015) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Çetinkaya, Oktay; Akan, Özgür Barış; Other; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; N/A; 6647
    Considering the inability of the existing energy resources to satisfy the current needs, the right and efficient. use of the energy has become compulsory. To make energy sustainability permanent, management and planning activities should be carried out by arranging the working hours and decreasing the energy wasting. For all these, power metering, managing and controlling systems or plugs has been proposed in recent efforts. Starting from this point, a new DASH7-based Smart Plug (D7SP) is designed and implemented to achieve a better structure compared to ZigBee equipped models and reduce the drawbacks of current applications. DASH7 technology reaches nearly 6 times farther distances in comparison with 2.4 GHz based protocols and provides multi-year battery life as a result of using limited energy during transmission. Performing in the 433 MHz band prevents the possible interference from overcrowded 2.4 GHz and the other frequencies which helps to gather a more reliable working environment. To shorten the single connection delays and human oriented failures, the MCU was shifted directly into the plug from the rear-end device. Working hours arrangement and standby power cutting off algorithms are implemented in addition to these energy saving targeted improvements to enhance more efficient systems. With the collaboration of the conducted hardware and software oriented adjustments and DASH7-based improvements, a more reliable, mobile and efficient system has been obtained in this work.
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    Harvesting-throughput trade-off for wireless-powered smart grid IoT applications: an experimental study
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) Akan, Özgür Barış; N/A; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Pehlivanoğlu, Ecehan Berk; Özger, Mustafa; Çetinkaya, Oktay; PhD Student; PhD Student; Researcher; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; N/A; 6647
    Sensor nodes, one of the most crucial elements of Internet of Things (IoT), sense the environment and send their observations to a remote Access Point (AP). One drawback of sensor nodes in an IoT setting is their limited battery supply. Hereby, energy harvesting (EH) stands as a promising solution to reduce or even completely eliminate lifetime constraints of sensors with exploitation of available resources. In this paper, we propose an electric-field EH (EFEH) method to enable battery-less execution of sensor-based IoT services for Smart Grid (SG) context. For this purpose, for the first time in the literature, harvestable energy through EFEH method is investigated with a transformer room experimental set-up. Our experiments reveal that 40 mJ of energy can be harvested in a period of 900 sec with the proposed EFEH method. Building on this energy profile, we define a throughput objective function θ for a «harvest-then-transmit» type system model, to shed light on the harvesting- throughput trade-off specific to IoT-assisted SG applications. Numerical results disclose non- trivial relationships between optimal harvesting period T-H, optimal transmission period T-T and critical network parameters such as node-AP hop distance, path loss exponent and minimum reporting frequency requirement.
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    Cognitive radio sensor networks in smart grid
    (Crc Press-Taylor and Francis Group, 2016) N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Ergül, Özgür; Çetinkaya, Oktay; Akan, Özgür Barış; PhD Student; Researcher; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 156793; N/A; 6647
    Smart Grid: Networking, Data Management, and Business Models delivers a comprehensive overview of smart grid communications, discussing the latest advances in the technology, the related cyber security issues, and the best ways to manage user demand and pricing. delivers a comprehensive overview of smart grid communications, discussing the latest advances in the technology, the related cyber security issues, and the best ways to manage user demand and pricing. delivers a comprehensive overview of smart grid communications, discussing the latest advances in the technology, the related cyber security issues, and the best ways to manage user demand and pricing. 1- Delivers a comprehensive overview of smart grid communications, discussing the latest advances in the technology, the related cyber security issues, and the best ways to manage user demand and pricing. 2-Explores the space of attacks in the energy management process, the need for a smart grid simulator, and the management issues that arise around smart cities. 3-Explores the space of attacks in the energy management process, the need for a smart grid simulator, and the management issues that arise around smart cities. 4-Presents cutting-edge research on microgrids, electric vehicles, and energy trading in the smart grid. Thus, Smart Grid: Networking, Data Management, and Business Models provides a valuable reference for utility operators, telecom operators, communications engineers, power engineers, electric vehicle original equipment manufacturers (OEMs), electric vehicle service providers, university professors, researchers, and students.
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    Estimation and detection for molecular MIMO Communications in the internet of bio-nano things
    (IEEE, 2023) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; N/A; Akan, Özgür Barış; Çetinkaya, Oktay; Baydaş, O. Tansel; Faculty Member; Researcher; Other; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; N/A; 6647; N/A; N/A
    For the Internet of Bio-Nano Things (IoBNT) applications demanding high transmission rates, a well-modeled Molecular Communication (MC) channel is essential. The existing studies proposing multiple-input and multiple-output (MIMO) models for MC, however, often make the unrealistic assumption of using ideal receivers with perfect absorption. Hence, this paper proposes a molecular MIMO channel model with spherical transmitters and partially-absorbing ligand receptor-based receivers underpinned by four unique parameters. For the non-analytical nature of the MIMO channel, we use a supervised learning algorithm to estimate the number of molecules in the reception space. We evaluate the root mean square error (RMSE) of our solution, which returns consistent results. The estimation is used for ligand-receptor binding statistics, in which the intersymbol inference (ISI) and molecular interference are considered. We also propose two techniques based on convolutional and recurrent neural networks (CNN & RNN) as alternatives to the generic threshold-based detection. Our detectors outperform the threshold-based technique; specifically, the CNN-based method improves the mean bit error rate (BER) performance three times.