Sarper Ozharar is a Senior Researcher in the Optical Sensing & Solutions Department at NEC Laboratories America, where he works on advanced distributed fiber-optic sensing technologies that transform standard communication fibers into highly sensitive instruments capable of detecting vibrations, acoustic signals, and environmental changes. Dr. Ozharar earned his B.S. in Physics from Koç University and later completed his Ph.D. in Optics and Photonics at the University of Central Florida. His academic and research background spans photonics, nonlinear optics, and sensing systems, providing the foundation for his work developing scalable fiber-optic sensing platforms. In recognition of his achievements in science and technology, he received the Achievement Award from Koç University, highlighting the impact of his research and his continued contributions to advancing optical sensing technologies.
His research focuses on distributed acoustic sensing (DAS), which enables fiber-optic cables to serve as large-scale sensor networks for applications such as infrastructure monitoring, transportation systems, environmental observation, and critical infrastructure security. By combining optical physics, signal processing, and system design, his work helps expand the role of fiber networks beyond communications into real-time sensing platforms. He has contributed to projects that demonstrate how fiber-optic sensing can reveal previously hidden patterns in natural and built environments, including innovative experiments showing that underground fiber-optic cables can detect biological and environmental phenomena, such as cicada activity. These efforts illustrate the growing potential of distributed sensing technologies to monitor ecosystems, detect infrastructure disturbances, and provide new sources of environmental data.
Posts
Vector beams are spatial modes that have spatially inhomogeneous states of polarization. Any light beam is a linear combination of vector beams, the coefficients of which comprise a vector beam spectrum. In this work, through numerical calculations, a novel method of free-space optical sensing is demonstrated using vector beam spectra, which are shown to be experimentally measurable via Stokes polarimetry. As proof of concept, vector beam spectra are numerically calculated for various beams and beam obstructions.
For the first time, we demonstrate remote sensing of pole-mounted fuse-cutout blowing in a power grid setup using telecom fiber cable. The proposed frequency-based AI model achieves over 98% detection accuracy using distributed fiber sensing data.
Our optical networking & sending team has arrived in Frankfurt for the 2024 European Conference on Optical Communication (ECOC) and is excited to present many papers and tutorials this week. Please follow this page and on our social media channels for updates.
The various sensing technologies such as cameras LiDAR radar and satellites with advanced machine learning models offers a comprehensive approach to environmental perception and understanding. This paper introduces an innovative Distributed Fiber Optic Sensing (DFOS) technology utilizing the existing telecommunication infrastructure networks for rain intensity monitoring. DFOS enables a novel way to monitor weather condition and environmental changes provides real-time continuous and precise measurements over large areas and delivers comprehensive insights beyond the visible spectrum. We use rain intensity as an example to demonstrate the sensing capabilities of DFOS system. To enhance the rain sensing performance we introduce a Deep Phase-Magnitude Network (DFMN) divide the raw sensing data into phase and magnitude component allowing targeted feature learning on each component independently. Furthermore we propose a Phase Frequency learnable filter (PFLF) for the phase component filtering and conduct standard convolution layers on the magnitude component leveraging the inherent physical properties of optical fiber sensing. We formulate the phase-magnitude channel into a parallel network and subsequently fuse the features for a comprehensive analysis in the end. Experimental results on the collected fiber sensing data show that the proposed method performs favorably against the state-of-the-art approaches.
Our team will be attending CVPR 2024 (The IEEE /CVF Conference on Computer Vision & Pattern Recognition) from June 17-21! See you there at the NEC Labs America Booth 1716! Stay tuned for more information about our participation.
Falling trees or their limbs can cause power lines to break or sag, sometimes resulting in devastating wildfires. Conventional protections such as circuit breakers, overcurrent relays and automatic circuit reclosers may clear short circuits caused by tree contact, but they may not detect cases where the conductors remain intact or a conducting path is not sufficient to create a full short circuit. In this paper, we introduce a novel, non-intrusive monitoring technique that detects and locates fallen trees, even if a short circuit is not triggered. This method employs distributed fiber optic sensing (DFOS) to detect vibrations along the power distribution line where corresponding fiber cables are installed. A physics-informed ResNet model is then utilized to interpret this information and accurately locate fallen trees, which sets it apart from traditional black-box predictions of machine learning algorithms. Our real-scale lab tests demonstrate highly accurate and reliable fallen tree detection and localization.
Our Sarper Ozharar, Yue Tian and Yangmin Ding and Jessica L. Ware from the American Museum of Natural History have discovered that fiber optic cables equipped with distributed acoustic sensing (DAS) can pick up the sounds of Brood X cicadas. DAS technology, typically used to monitor seismic activity, can detect the vibrations caused by the loud sounds of cicadas, which live underground for years until they come up to mate.
Brood X is the largest of the 15 broods of periodical cicadas, and individuals from this brood emerged across the Eastern United States in spring 2021. Using distributed acoustic sensing (DAS) technology, the activity of Brood X cicadas was monitored in their natural environment in Princeton, NJ. Critical information regarding their acoustic signatures and activity level is collected and analyzed using standard outdoor-grade telecommunication fiber cables. We believe these results have the potential to be a quantitative baseline for regional Brood X activity and pave the way for more detailed monitoring of insect populations to combat global insect decline. We also show that it is possible to transform readily available fiber optic networks into environmental sensors with no additional installation costs. To our knowledge, this is the first reported use case of a distributed fiber optic sensing system for entomological sciences and environmental studies.
Sarper Ozharar was awarded an Achievement in Science and Technology Award from Koç University on their notable 30th anniversary. As an alumnus of this esteemed institution, Sarper shared that this recognition is especially meaningful to him, marking a significant milestone in his professional journey.
We present the field trial of an innovative neural network and DAS-based technique, employing a pre-trained CNN fine-tuning strategy for effective rain detection and classification within two practical scenarios.
