Department of Electrical Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

In 5G and beyond cellular networks, the typical cell size has been reducing to provide higher data rates and meet the low latency requirements. Such ultra-dense deployments of base stations results in frequent handovers (HOs) of the user equipment. In this poster, we utilize the state-of-the-art double deep reinforcement learning (DDRL) framework to enhance the performance with respect to handover failure, radio link failure, and ping pong effect. Through extensive simulation results, we show that the proposed off-policy DDRL based handover scheme performs better than state-of-the-art handover schemes. © 2023 IEEE.

World University root node

2023 15th International Conference on COMmunication Systems and NETworkS, COMSNETS 2023

Double Deep Reinforcement Learning assisted Handovers in 5G and Beyond Cellular Networks

It is still challenging to accurately localize unmanned aerial vehicles (UAVs) from a ground control station (GCS) using various sensors. The mmWave frequency-modulated continuous wave (FMCW) radars offer excellent performance for target detection and localization in harsh environments and low lighting conditions. However, the estimated angle of arrival (AoA) of targets in the captured scene is quite poor. This article focuses on improving AoA estimation by combining the cutting-edge machine learning (ML) algorithms with a mechanical radar rotor setup. An mmWave FMCW radar system is mounted on a programmable rotor to capture range-angle maps of targets at various locations. The range-angle images are then labeled and trained further with the Yolov3 algorithm. Subsequent testing reveals that for detected target objects, the centroid of the bounding boxes from the detected objects provides accurate AoA estimation with very low root mean square error (RMSE). The results show that the proposed approach outperforms traditional methods in terms of performance and estimation accuracy. © 2001-2012 IEEE.

IEEE Sensors Journal

Multitarget Angle of Arrival Estimation Using Rotating mmWave FMCW Radar and Yolov3

This paper presents a novel technique for mitigation of flange effect and antenna transmit to receive isolation improvement methodology using RF choke for the bistatic radars of aerospace vehicles. The presence of flange causes variation in antenna radiation pattern, by an increase in sidelobe level, decrease in gain and dip in roll pattern, thereby degradation in the performance of the antenna. An RF choke adjacent to the waveguide wall is introduced to nullify the undesirable effects of the flange. This Paper demonstrates through simulation and experimentation that this choke effectively suppresses the surface wave and can be applied in many types of antennas to improve the radiation pattern deteriorated by parasitic elements. It is also demonstrated through measurements that the isolation from transmit to receive antenna is improved by introducing choke, with this technique antenna isolation is enhanced by 23 dB with 11 dB antenna gain. The gain and sidelobe improvement of the antenna with RF choke is 2 dB, and 6 dB, respectively. The proposed array antenna is fabricated with and without choke, measurements are performed and test results are presented. The isolation test between transmit & receive antenna is performed in an anechoic chamber and test results are presented. © 2022 Elsevier GmbH

AEU - International Journal of Electronics and Communications

RF choke based methodology for flange effect mitigation and antenna isolation improvement in bistatic radars of aerospace vehicles

Multimodal (RGB and thermal) applications are swiftly gaining importance in the computer vision community with advancements in self-driving cars, robotics, Internet of Things, and surveillance applications. Both the modalities have complementary performance depending on illumination constraints. Hence, a judicious combination of both modalities will result in robust RGBT systems capable of all-day all-weather applications. Several studies have been proposed in the literature for integrating the multimodal sensor data for object tracking applications. Most of the proposed networks try to delineate the information into modality-specific and modality shared features and attempt to exploit the modality shared features in enhancing the modality specific information. In this work, we propose a novel perspective to this problem using a Siamese inspired network architecture. We design a custom Siamese cross-domain tracker architecture and fuse it with a mean shift tracker to drastically reduce the computational complexity. We also propose a constant false alarm rate inspired coasting architecture to cater for real-time track loss scenarios. The proposed method presents a complete and robust solution for object tracking across domains with seamless track handover for all-day all-weather operation. The algorithm is successfully implemented on a Jetson-Nano, the smallest graphics processing unit (GPU) board offered by NVIDIA Corporation. © 2022 IEEE.

IEEE Transactions on Artificial Intelligence

Siamese Cross-Domain Tracker Design for Seamless Tracking of Targets in RGB and Thermal Videos

The development of efficient H2O2 sensors is crucial because of their multiple functions inside and outside the biological system and the adverse effects that a higher concentration can cause. This work reports a highly sensitive and selective non-enzymatic electrochemical H2O2 sensor achieved through the hybridization of Co3S4 and graphitic carbon nitride nanosheets (GCNNS). The Co3S4 is synthesized via a hydrothermal method, and the bulk g-C3N4 (b-GCN) is prepared by the thermal polycondensation of melamine. The as-prepared b-GCN is exfoliated into nanosheets using solvent exfoliation, and the composite with Co3S4 is formed during nanosheet formation. Compared to the performances of pure components, the hybrid structure demonstrates excellent electroreduction towards H2O2. We investigate the H2O2-sensing performance of the composite by cyclic voltammetry, differential pulse voltammetry, and amperometry. As an amperometric sensor, the Co3S4/GCNNS exhibits high sensitivity over a broad linear range from 10 nM to 1.5 mM H2O2 with a high detection limit of 70 nM and fast response of 3 s. The excellent electrocatalytic properties of the composite strengthen its potential application as a sensor to monitor H2O2 in real samples. The remarkable enhancement of the electrocatalytic activity of the composite for H2O2 reduction is attributed to the synergistic effect between Co3S4 and GCNNS. © 2023 by the authors.

Department of Chemistry

Fulltext

Biosensors

Hybridization of Co3S4 and Graphitic Carbon Nitride Nanosheets for High-performance Nonenzymatic Sensing of H2O2

For the precise measurements of special nuclear materials (SNM) including Pu and Am isotopes, we have used phoswich detector combination of two single crystal scintillators of Gd3Ga3Al2O12:Ce and CsI:Tl. High detection efficiency and sensitivity along with high figure of merit for the discrimination of these phoswich detectors ensures the detection and discrimination of thermal neutrons and gammas from spontaneous fission of Pu and other isotopes in presence of high gamma background. Using this detector, the low energy gammas, which is stopped completely in 1mm thick disc of GGAG, can be also discriminated from high energies gamma and shows linearity in wide range of sample quantities. By changing only the appropriate shielding, the similar setup was used for thermal neutron detection and shows a very good linearity over wide range. The quantity of a test sample was also calculated accurately by using the measured calibrated plot. © 2023 Korean Nuclear Society

Nuclear Engineering and Technology

Assaying of SNM using Simultaneous Detection of Fission Neutrons and Gammas by Employing a Novel Phoswich Detector

A sensitive, non-invasive, and biomarker detection in tear fluids for inflammation in potentially blinding eye diseases could be of great significance as a rapid diagnostic tool for quick clinical decisions. In this work, we propose a tear-based MMP-9 antigen testing platform using hydrothermally synthesized vanadium disulfide nanowires. Also, various factors contributing to baseline drifts of the chemiresistive sensor including nanowire coverage on the interdigitated microelectrode of the sensor, sensor response duration, and effect of MMP-9 protein in different matrix solutions were identified. The drifts on the sensor baseline due to nanowire coverage on the sensor were corrected using substrate thermal treatment providing a more uniform distribution of nanowires on the electrode which brought the baseline drift to 18% (coefficient of variations, CV = 18%). This biosensor exhibited sub-femto level limits of detection (LODs) of 0.1344 fg/mL (0.4933 fmoL/l) and 0.2746 fg/mL (1.008 fmoL/l) in 10 mM phosphate buffer saline (PBS) and artificial tear solution, respectively. For a practical tear MMP-9 detection, the proposed biosensor response was validated with multiplex ELISA using tear samples from five healthy controls which showed excellent precision. This label-free and non-invasive platform can serve as an efficient diagnostic tool for the early detection and monitoring of various ocular inflammatory diseases. © 2023 Elsevier B.V.

Analytica Chimica Acta

Tear-based MMP-9 detection: A rapid antigen test for ocular inflammatory disorders using vanadium disulfide nanowires assisted chemi-resistive biosensor

Nitrogen (N) is one of the essential nutrients required for healthy crop growth. Field phenotyping for nitrogen stress symptoms is laborious and time-consuming, that way, it is a major bottleneck in nutrition-inclusive agricultural research. Recent advancements in sensors and image processing facilitate color-based quantification of crop greenness from high-resolution RGB images. In this paper, we present unmanned aerial vehicle (UAV)-based digital field phenotyping for the estimation of crop nitrogen content. For this, we conducted a field experiment during the post-rainy season of 2021 at International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Hyderabad, India with long-stature cereal model crop, sorghum (Sorghum bicolor L.) cultivated under three different regimes varying in moisture and soil nitrogen content. A high-resolution RGB sensor (XenmuseX5S) mounted on DJI Matric 210 quadcopter was used for capturing the spatiotemporal imagery. Five different RGB spectrum vegetation indices indicating crop greenness were correlated with ground truth values of crop N content using simple linear regression and stepwise backward regression. With a prediction potential of R2=0.65 and MAE=0.27 for an independent dataset, we present a stepwise backward linear regression model as a promising approach for real-time estimation of the N status of sorghum crop. © 2023 IEEE.

2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

UAV-based Digital Field Phenotyping for Crop Nitrogen Estimation using RGB Imagery

With the commitment to climate, globally many countries started reducing brownfield energy production and strongly opting towards green energy resources. However, the optimal allocation of distributed energy resources (DERs) in electrical distribution systems still pertains as a challenging issue to attain the maximum benefits. It happens due to the system’s complex behaviour and inappropriate integration of DERs that adversely affects the distribution grid. In this work, we propose a methodology for the optimal allocation of DERs with vulnerable node identification in active electrical distribution networks. A failure or extreme event at the vulnerable node would interrupt the power flow in the distribution network. Also, the power variation in these vulnerable nodes would significantly affect the operation of other linked nodes. Thus, these nodes are found suitable for the optimal placement of DERs. We demonstrate the proposed data-driven approach on a standard IEEE-123 bus test feeder. Initially, we partitioned the distribution system into optimal microgrids using graph theory and graph neural network architecture. Further, using Granger causality analysis, we identified vulnerable nodes in the partitioned microgrid, suitable for DERs integration. The placement of DERs on the vulnerable nodes enhanced network resilience. Improvement in resilience is validated by computing the percolation threshold for the microgrid networks. The results show a 37% improvement in the resilience of the system due to the optimal allocation of DERs. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

International Journal of Data Science and Analytics

Data-driven approach to form energy-resilient microgrids with identification of vulnerable nodes in active electrical distribution network

This article proposes a fully-integrated, error amplifier (EA)-less, reference-inbuilt, dual-loop low dropout regulator (LDO) working at a minimum input voltage of 0.7 V. The reference-integrated structure has a flipped-voltage-follower (FVF) as the output stage and provides an output voltage of 0.6 V. The dual-loop architecture provides high dc loop gain (<inline-formula> <tex-math notation="LaTeX">$\geq$</tex-math> </inline-formula>60 dB), a very small output impedance, along with the proposed load-adaptive-biasing (LAB), which results in excellent line and load regulation. The power supply rejection (PSR) of the proposed LDO is improved by <inline-formula> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula>30 dB at frequencies around 100 kHz, using the proposed replica-based supply noise cancellation (RSNC). The design is fabricated in 0.18 <inline-formula> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula>m CMOS technology and occupies an area of 0.074 mm<inline-formula> <tex-math notation="LaTeX">$^2$</tex-math> </inline-formula>. The measured load and line regulation are 0.35 mV/mA and 0.45 mV/V, respectively, which are the best in the literature for sub-1 V LDOs The minimum PSR till 1 MHz is <inline-formula> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula>41.2 dB, and the design achieves a transient figure of merit (FoM) of 35.82 fs considering the limitation of having a low input voltage at a higher technology. This LDO achieves a 2.78<inline-formula> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> better line regulation and a 1.43<inline-formula> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> better load regulation compared to state-of-the-art sub-1 V LDOs while assuring a strong PSR performance till 1 MHz. IEEE