Swati Hira
Biography
Dr. Swati Hira is an Assistant Professor at IIIT Nagpur with over a decade of teaching and research experience. She earned her Ph.D. in Data Mining from VNIT Nagpur in 2017. Her research interests span Hyperspectral Imaging, Machine Learning, Medical Imaging, Deep Learning, Time Series Modeling, and Spatial Data Mining. She has led major government-funded projects, including initiatives on coal quality exploration and the development of an indigenous NIR spectroscope in collaboration with CIMFR. With more than 30 publications and a patent to her credit, Dr. Hira continues to make significant contributions to applied AI and interdisciplinary research.
Research Interest
Her research expertise covers a wide range of domains, including Hyperspectral Imaging, Machine Learning, Medical Imaging, Deep Learning, Time Series Modeling, Spatial Data Mining, and Multidimensional Modeling.
Abstract
Development of coal quality exploration technique based on convolutional neural network and hyperspectral imaging"
Abstract:Coal is India?s prime energy source, contributing about 60% of total electricity production. Coal India,a major coal-producing public sector unit,has produced a record 703.2 million tons of coal during the year 2022?2023.Therefore, this paper proposes an idea of instant prediction of coal quality parameters using hyperspectral imaging and deep neural network. We have collected coal samples from 35 different coal mines of all areas of Western Coalfields Ltd (WCL), and 257 different types of samples have been generated.
All 257 coal samples were imaged using camera PIKA NIR 320. The RegNet model was applied to predict coal quality based on moisture, ash, volatile matter, gross calorific value, fixed carbon, and sulphur. The results were validated through chemical analysis results received from the lab. The proposed
approach achieved good prediction accuracy, nearly 96% for coal quality parameters. Moisture showed the highest accuracy, 96.09% in quality prediction
