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Öğe 3D Printed Capacitive Pressure Sensor with Corrugated Surface(IEEE, 2017) Tuna, Ahmet; Erden, Oguz K.; Gokdel, Y. Daghan; Sarioglu, BaykalIn this work a novel 3D printed capacitive pressure sensor with a corrugated surface is presented. The design composed of top and bottom plates. The sensor is 3D printed using a commercially available polymer material and then coated with Cr and Au with sputtering process. The dimensions of produced structure that designed is 11x11x4.6mm(3). Due to the corrugated surface, the area of the plates is increased 19.46% compared to a standard flat surface parallel plate capacitive sensor in the same bulk area. The design process of the sensor, simulation and the experimental results are given and explained in detail. The performance of the sensor is tested with various pressure levels between 0 Pa and 8.88 kPa. The experimental results show that the capacitance range of the sensor is 2.7 pF-4.3 pF. The maximum sensitivity of the sensor is obtained as 0.14 pF / kPa. The results confirm that the presented capacitive sensor can be utilized for carrying out pressure measurements.Öğe 3D Printed Microplatform for Fiber-Coupled Optical Microsystems(IEEE, 2017) Kizilcabel, Hilal; Sarioglu, BaykalIn this paper, a 3D printed microplatform for realization of fiber-coupling between a light source and an optical microsystems is proposed. The micro-platform is designed in a CAD software and printed using additive manufacturing fusing technology. The performance of the proposed microplatform is tested successfully by coupling an integrated CMOS photodiode with an area of 500 x 500 mu m(2) to a pig tail laser that is attached to a 62.5 mu m/125 mu m multimode fiber optic cable. Experiment results show that the proposed microplatform presents a cost-effective alternative to the silicon-processed microplatforms.Öğe A Mathematical Programming Approach for IoT-Enabled, Energy-Efficient Heterogeneous Wireless Sensor Network Design and Implementation(Mdpi, 2024) Taparci, Ertugrul; Olcay, Kardelen; Akmandor, Melike Ozlem; Kabakulak, Banu; Sarioglu, Baykal; Gokdel, Yigit DaghanThe Internet of Things (IoT) is playing a pivotal role in transforming various industries, and Wireless Sensor Networks (WSNs) are emerging as the key drivers of this innovation. This research explores the utilization of a heterogeneous network model to optimize the deployment of sensors in agricultural settings. The primary objective is to strategically position sensor nodes for efficient energy consumption, prolonged network lifetime, and dependable data transmission. The proposed strategy incorporates an offline model for placing sensor nodes within the target region, taking into account the coverage requirements and network connectivity. We propose a two-stage centralized control model that ensures cohesive decision making, grouping sensor nodes into protective boxes. This grouping facilitates shared resource utilization, including batteries and bandwidth, while minimizing box number for cost-effectiveness. Noteworthy contributions of this research encompass addressing connectivity and coverage challenges through an offline deployment model in the first stage, and resolving real-time adaptability concerns using an online energy optimization model in the second stage. Emphasis is placed on the energy efficiency, achieved through the sensor consolidation within boxes, minimizing data transmission hops, and considering energy expenditures in sensing, transmitting, and active/sleep modes. Our simulations on an agricultural farmland highlights its practicality, particularly focusing on the sensor placement for measuring soil temperature and humidity. Hardware tests validate the proposed model, incorporating parameters from the real-world implementation to enhance calculation accuracy. This study provides not only theoretical insights but also extends its relevance to smart farming practices, illustrating the potential of WSNs in revolutionizing sustainable agriculture.Öğe A self-tuning resonance-locking method for polymer MEMS microscanners(Iop Publishing Ltd, 2026) Alcicek, Berkay; Arseven, Aysin; Sarioglu, Baykal; Gokdel, Y. DaghanThis study presents a self-tuning optical MEMS microscanner based on a low-cost polyimide structure integrated with a piezoresistive feedback mechanism. The system automatically detects and tracks the torsional resonance frequency (approximate to 81 Hz), compensating for spring softening effects that otherwise degrade scan performance. A custom frequency sweep algorithm, combined with a closed-loop control, dynamically adjusts the actuation signal to maintain resonance-locked operation, enabling stable mechanical scan angles of 10-12 degrees ( approximate to 42 degrees total optical scan angle (TOSA)) at drive levels of 8-10 Vpp and 60-80 mA ( approximate to 0.5z-0.8W). This approach ensures stable displacement and total optical scan angle over time, even under frequency drift. In high-power characterization sweeps, the device demonstrates optical scan angles up to 100 degrees TOSA. The proposed architecture offers a practical and scalable solution for energy-efficient, high-resolution optical scanning using inexpensive and easily manufacturable polymer-based MEMS devices.Öğe An Electronic Control and Image Acquisition System for Laser Scanning Microscopy(IEEE, 2015) Gumus, Gokhan; Sarioglu, Baykal; Gokdel, Yigit DaghanThis paper presents an electronic system that controls the entire operation of a laser scanning microscopy system through a DAQ card. Proposed system does not only create the required electro-coil driving signal peculiar to magnetically actuated micro-scanner that enables the raster-scanning movement, but also is responsible from the image acquisition part by both serially gathering the laser intensity data and using it to construct a meaningful microscopy image. Micro-scanner which is fabricated using Ni as the structural material is utilized in the system. The microscanner's slow and fast scan frequencies are measured to be 250 Hz and 1560 Hz, respectively. Model of the DAQ card used in the system is NI-6356 which has maximum 5 mA current and 10 V voltage outputs. A power amplifier circuit with LM 386 is designed and added to the system for increasing field-of-view of the micro-scanner. The operation of the proposed system is demonstrated by acquiring data and constructing images from the USAF resolution target.Öğe An Optoelectrical, Standard CMOS-Based Active Catheter Tracking System for MRI(Elsevier Science Bv, 2014) Camli, Berk; Sarioglu, Baykal; Yalcinkaya, Arda D.A fully optical active catheter tracking system compatible with 3T MRI environment is presented. It replaces conducting cables with optical fibers to reduce RF-induced heating problem. Proposed system consists of a MEMS-based microstructure array and an IC driving it. The IC houses an RF receiver block and an optoelectrical power supply. A prototype IC was fabricated in UMC 0.18 mu m CMOS process. Measurements indicate that the supply unit is able to provide 2.18mA at 1.2V supply, when a laser beam of 80mW power at its source is applied to IC. The system is operational at laser source power levels above 40mW. (C) 2014 The Authors. Published by Elsevier Ltd.Öğe CMOS Optical Receiver for Low Power Biomedical Microsystems(IEEE, 2017) Yelkenci, Asli; Sarioglu, BaykalIn this paper, an integrated CMOS optical receiver in which optical power delivery and optical communication realized on a single channel is proposed. Pulse Width Modulation (PWM) method is applied on the light source for transmission of the signals. Clock, data and power signals are obtained by various filtering methods. The proposed receiver is designed in 180 nm UMC Standard CMOS technology and can operate with single integrated CMOS photodiode.Öğe Cryptographically strong random number generation using integrated CMOS photodiodes for low-cost microcontroller based applications(Tubitak Scientific & Technological Research Council Turkey, 2022) Sarioglu, BaykalIn this work, we propose a method to generate random numbers for low-cost, low-power, resource-limited low data-rate microcontrollers using integrated CMOS photodiodes. The proposed method utilizes an integrated CMOS photodiode in the photovoltaic mode as the entropy source. The method is based on serially capturing analog values derived from the integrated CMOS photodiode. The entropy of these values increased by a custom algorithm. The proposed random number generator is devised using an integrated CMOS photodiode manufactured in 180 nm standard CMOS technology. The wide applicably of the random number generator is demonstrated by realizing it on a low-cost Arduino UNO board placed in a typical room environment. The implemented random number generator passes NIST-SP800-22 and AIS31 randomness tests at high scores. The proposed method achieved 5.4 Kbps throughput and 7.2% total significance level without any postprocessing. The test results show the high cryptographical strength of the proposed method makes it a promising alternative to the currently used random number generation algorithms in low-cost, low-resources, low-data rate microcontroller-based applications.Öğe Embedded System Design and Implementation For a Miniaturized Laser Projection Display(IEEE, 2019) Kucuk, Elif; Arseven, Aysin; Sarioglu, Baykal; Gokdel, Y. DaghanIn this work, a low power compact embedded system for steel scanner based miniaturized projection displays is presented. The proposed system is composed of a steel micro scanner, a microcontroller unit, a power amplifier, a 5mW laser with 650nm wavelength and a transistor-based laser driver. The proposed embedded system generates two actuation signals for vertical and horizontal movements of the scanner. The embedded system also generates laser pulses in synchronization with the actuation signals to form a stable and undistorted image. The steel scanner's total optical scanning angles (TOSA) are 5.415 and 3.2729 in slow-scan and fast-scan directions, respectively. Slow scan frequency is 264 Hz, while the fast scan frequency is 2640 Hz. The proposed device can deliver sufficient torque to allow non-resonant operation. Sample images generated using the proposed system are also given.Öğe EMRES: A New EMotional RESpondent Robot(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Sonmez, Elena Battini; Han, Hasan; Karadeniz, Oguzcan; Dalyan, Tugba; Sarioglu, BaykalThe aim of this work is to design an artificial empathetic system and to implement it into an EMotional RESpondent (EMRES) robot, called EMRES. Rather than mimic the expression detected in the human partner, the proposed system achieves a coherent and consistent emotional trajectory resulting in a more credible human-agent interaction. Inspired by developmental robotics theory, EMRES has an internal state and a mood, which contribute in the evolution of the flow of emotions; at every episode, the next emotional state of the agent is affected by its internal state, mood, current emotion, and the expression read in the human partner. As a result, EMRES does not imitate, but it synchronizes to the emotion expressed by the human companion. The agent has been trained to recognize expressive faces of the FER2013 database and it is capable of achieving 78.3% performance with wild images. Our first prototype has been implemented into a robot, which has been created for this purpose. An empirical study run with university students judged in a positive way the newly proposed artificial empathetic system.Öğe FPGA implementation of an optimized neural network for CFD acceleration(Elsevier Gmbh, 2025) Cevik, Gokalp; Sarioglu, Baykal; Aka, Ibrahim BazarIn this work, an evaluation of FPGAs as the central computation platform in domain-specific AI-accelerated CFD simulations is performed. This evaluation is performed in three categories: power efficiency, speed, and accuracy. The specific domain in the study is the FDA nozzle benchmark, which is simulated using SimpleFoam, a laminar solver that is a component of the OpenFOAM CFD toolbox. The proposed AI model is a low-parameter feed-forward neural network with three fully connected layers, trained using steadystate solutions distinguished by various Reynolds numbers, all of which are computed by the OpenFOAM framework. The proposed model can then generate the steady-state CFD simulation result given the initial few iterations generated by the solver. Moreover, this paper introduces a hardware implementation for inference of the simulation results using an SoC chip with minimal hardware resource utilization. The suggested hardware design is developed from scratch for Zynq-7000 System-on-Chip, using only VHDL, and requiring no dependencies on third-party commercial AI frameworks or costly FPGA boards designed for AI-related applications. The proposed workflow in the test case study achieves a 98% reduction in simulation time while maintaining relatively high accuracy and a 95.6% reduction in energy consumption compared with the regular CFD workflow.Öğe NeuralTimer: Configuration-Based Neural Network Approach to Hardware Timer-Based Applications(Ieee-Inst Electrical Electronics Engineers Inc, 2026) Akmandor, Melike Ozlem; Sarioglu, BaykalHardware timers are fundamental components in time-critical embedded systems, where precise and deterministic timing control is essential for operations such as real-time signal processing, task scheduling, sensor data acquisition, and synchronization. Even small timing inaccuracies can lead to degraded performance or system malfunction. This paper presents a novel NeuralTimer architecture that replaces conventional register-based timer logic with a compact neural network implemented on the Xilinx Zybo Z7-20 FPGA platform. The design operates at the board's native 125 MHz clock frequency and realizes an 8-bit threshold-based timing mechanism capable of adaptive and high-level timing control. Unlike traditional timers that require hardware-dependent configuration through prescalers and registers, the proposed approach enables reconfiguration simply by updating the neural network weights. Experimental validation demonstrates stable real-time performance confirming that neural-network-driven timers can serve as flexible, resource-efficient, and reconfigurable control primitives for next-generation embedded systems.Öğe Optical Communication System with Single Channel Power Delivery and Data Transmission for Digital Biomedical Applications(IEEE, 2016) Yelkenci, Asli; Sarioglu, BaykalIn this paper, a communication system model in which optical power delivery and optical data transmission realized on a single channel is proposed. In the proposed system, optical power, data, and clock pulse signals are transmitted together on a single channel by applying PulseWidth Modulation on the light source. System model and the components are described in detail. The presented architecture enables single light sources and single fiber optical cable utilization, and hence, it can be integrated to compact, low-power, optical biomedical microsystems.Öğe Optically Powered Battery-Free Portable Microsystem for WSN and IoT Applications(IEEE, 2019) Ehican, Ilyas; Sarioglu, BaykalThis paper presents an ultra low power all-optical portable battery-free embedded microsystem that can be powered and controlled by a smart mobile phone. The microsystem contains an ultra-low voltage microcontroller as the processing unit; and, it receives power via a mini-solar cell. The optically powered microcontroller reads the local sensor data and transmits it to the mobile phone via modulating the light of an LED. A custom optical communication protocol that is based on Pulse Period Modulation is designed for the system. An image processing based mobile application utilizing the built-in flash of the phone is also programmed for controlling the microsystem. The mobile phone application using the built-in rear-facing camera analyzes the modulated optical signal from the LED on the microsystem and extracts the transmitted data. Experimental results of various local temperature measurements are also given.Öğe Performance Analysis of Histogram-Threshold Method for Cancer Detection(IEEE, 2014) Koc, Gamze; Gokdel, Yigit Daghan; Sarioglu, BaykalIn this paper, histogram-threshold method developed for cancer detection using miniaturized confocal microscopy system and its related performance analysis are presented. While doing the performance analysis, the receiver operation characteristics are applied in a novel fashion. Additionally, noise performances of different method are investigated. The highest and lowest success rates with 91.67% and 27.08% are acquired using Entropy Method and Mean Method, respectively.Öğe Photodiodes for Monolithic CMOS Circuit Applications(IEEE-Inst Electrical Electronics Engineers Inc, 2014) Camli, Berk; Sarioglu, Baykal; Yalcinkaya, Arda D.An optoelectrical power supply unit compatible with standard CMOS processes designed for microscale applications is presented. The system is based on an earlier version consisting of a photodiode that converts optical power to electrical power, and a dc/dc converter that increases the photodiode anode voltage to desirable levels. It has the ability to operate continuously or intermittently. The latter operation mode employs additional system elements and requires the modulation of the input laser beam. A prototype was fabricated in UMC 0.18-mu m triple-well standard CMOS process along with a direct conversion self-mixing receiver block on a die of 1525 mu m x 1525 mu m area. Performance measurements were done using a laser source of 650-nm wavelength at different power levels. For an input laser power of 80 mW, the source can provide an output current of 2.18 mA at a supply voltage of 1.2 V. The proposed system can be used to power integrated digital and low-power analog communication and medical microsystems.Öğe Quantitative detection system for immunostrips in 180nm standard CMOS technology(Springer, 2021) Tekin, Engincan; Celikdemir, Caner; Ucar, Busra; Gul, Ozgur; Sarioglu, BaykalIn this work, a CMOS based optical read-out system for biomarker on immunostrips detection is presented. For the proposed system, a CMOS integrated circuit containing an on-chip photodiode is designed in standard 180 nm UMC CMOS Technology. The system also contains cost-effective 3D Printed structures for holding both IC and the sample immunostrip together. The proposed system can be operated in two modes (1) light reflectance and (2) light transmittance. In the system, a laser with a wavelength of 637 nm is applied to the CMOS IC through immunostrip. Photovoltaic and photoconductive measurements are carried out for each mode on a custom Gluten biomarker immunostrip. Sensing operation of the biomarker is successfully realized with optical powers from 5 mW to 8 mW. Biomaterial density on the immunostrip is sensed and images of the biomarker with varying intensities are constructed from the measurements. Feasibility of the system for low power biomarker sensing applications is demonstrated.Öğe Quantitative Measurement of Colorimetric Signals in 180nm Standard CMOS Technology(IEEE, 2019) Celikdemir, Caner; Tekin, Engincan; Ucar, Busra; Gul, Ozgur; Sarioglu, BaykalIn this work, a CMOS based optical read-out system for biomarker sensing is presented. An integrated circuit containing an on-chip photodiode is designed an manufactured in 180nm UMC CMOS Technology. A 3D Printed structure is designed for holding both IC and the marker paper together. Laser light with 637 nm wavelength is applied to the marker paper and the CMOS IC. Optical measurements carried-out are based on the light transmissivity of the marker paper. Both photovoltaic and photoconductive measurements are carried out. The markers are successfully detected with 5mW to 20mW optical power. Images of the marker lines with varying intensity are generated from the measurements. Lastly, theoretical equations are derived, and the feasibility of the system for low power biomarker sensing applications is shown.Öğe Real-Time Visual Navigation Framework for Edge-Level Systems Using Classical Vision Algorithms(Institute of Electrical and Electronics Engineers Inc., 2025) Kaya, Baris; Tekelioglu, Melih Ilter; Sarioglu, BaykalThis paper presents a novel real-time navigation assistance system that enhances driver awareness by visually embedding directional guidance directly into the roadway scene. Instead of displaying instructions on a separate map interface, our system renders navigational cues - such as arrows - within the actual road view captured by a forward-facing camera. These cues are aligned with the detected lane geometry, enabling drivers to follow directions more intuitively without shifting focus away from the road. The system relies on lightweight computer vision techniques using OpenCV, avoiding the need for complex neural networks or high-performance hardware. It operates efficiently on minimal CPU resources and requires only a simple camera. Real-time integration with Google Maps provides up-to-date route information, which is seamlessly transformed into visual overlays projected within the driving lane. This design significantly improves driver focus and reaction time, particularly at higher speeds or in unfamiliar environments. By bridging map data with on-road visual guidance, our method offers a practical step forward in intelligent driver assistance systems. The approach supports future extensions such as windshield-projected interfaces, but its current implementation already demonstrates how smart, vision-based systems can make navigation safer, more accessible, and more human-centered. © 2025 IEEE.Öğe Scalable Mesh Networking with Machine Learning for Real-Time Crop Yield Prediction in Resource-Constrained Agricultural Environments(Institute of Electrical and Electronics Engineers Inc., 2025) Agha, Janib; Wamiq, Shehzada; Sarioglu, BaykalThis paper presents a custom-developed, ultra-lowpower mesh network of sensor nodes designed to log environmental parameters such as temperature and humidity across agricultural fields. The system employs a self-organizing, energy-efficient communication framework optimized for long-term deployment in resource-constrained environments. Logged data is combined with historical agricultural datasets to train a Random Forest Regressor specifically tailored for crop yield prediction. The model demonstrates high accuracy and robustness, effectively translating environmental trends into actionable forecasts. This integrated approach offers a scalable, low-cost pathway toward data-informed agricultural planning, enabling farmers to better anticipate outcomes and adapt to evolving climate conditions. A Random Forest Regressor trained on both field and historical data achieved an R2 of 0.98 and MAE of 4770.27 Hg/ Ha, outperforming linear and decision tree models. Real-time sensor data from 2025 was used to generate accurate yield predictions, demonstrating the system's viability for scalable, data-driven precision agriculture. © 2025 IEEE.
