Electrical and Electronic Engineering, Electrical and Electronic Engineering
15
Scopus Publications
Scopus Publications
Design and Implementation of an IoT-Based Heart Rate and Temperature Monitoring System Using ThingSpeak Mariyala Rajesh, I Adum Babu, K Manikanta 2025 International Conference on Emerging Trends in Signal Processing and Computational Intelligence Iccspci 2025, 2025 A crucial component of preventive healthcare nowadays is health monitoring, particularly in settings with limited resources and in rural areas. In order to provide realtime health information, this paper describes the design and implementation of a heart rate monitoring system that makes use of temperature and pulse sensors. The system is designed to record body temperature and heart rate, process the signals with a microcontroller, and send the information to the cloudbased ThingSpeak platform for remote monitoring and analysis. The suggested system guarantees ongoing health monitoring, facilitating early anomaly detection and prompt medical attention. The system offers an affordable, portable, and effective solution that can be used for remote medical care as well as personal health care applications by utilizing IoT connectivity. According to experimental results, the system detects vital signs with dependable accuracy while remaining easy to use and reasonably priced. This research aids in the creation of easily accessible digital health solutions that can help medical professionals keep an eye on patients and people in real time.
A Machine Learning Framework for Early Detection of Sleep Apnea and Insomnia G. Siva Sankar Varma, K. Manikanta, Nalla Chandana, Kavali Shireesha 2025 5th International Conference on Artificial Intelligence and Signal Processing Aisp 2025, 2025 Sleep apnea, insomnia and other sleep disorders have a major influence on public health, necessitating efficient and accurate early detection mechanisms. This study presents a Machine Learning (ML) based framework for identifying these disorders using health and lifestyle indicators. The predictive performance of several categorization models, such as AdaBoost (AB), k-Nearest Neighbors (KNN), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), Logistic Regression (LR), and Light Gradient Boosting Machine (LGBM), was assessed. According to experimental results, the XGB model outperformed with 92.55% of accuracy, 89.83% of precision, 92.49% of recall, 91.04% of F1-score and 94.71% of ROC-AUC. While LR provided a fair compromise between interpretability and accuracy, KNN and LGBM also showed competitive ROC-AUC values of 95.19% and 95.05% respectively among the other models. The results demonstrate how combining behavioral and health data with cutting-edge machine learning methods might facilitate early sleep disorder screening, facilitating prompt intervention and better patient outcomes.
Study of Digital Circuit Characteristics using GAA-Nanowire FET Mounika Sreeram, Manikanta Kurivella, Umakanta Nanda, Niroj Kumar Patra 2025 2nd International Conference on Circuits Power and Intelligent Systems Ccpis 2025, 2025 The continuous scaling of CMOS technology has introduced significant challenges such as increased leakage power, short-channel effects, and degraded subthreshold performance. To overcome these limitations, advanced transistor architectures like Gate-All-Around Nanowire Field-Effect Transistors (GAA-NWFETs) have emerged as promising alternatives due to their superior electrostatic control and scalability. This paper presents a comprehensive study on the digital circuit characteristics of GAA-NWFETs, focusing on their electrical performance and suitability for logic design. Key device metrics such as ON-current (I<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</inf>), OFF-current (I<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OFF</inf>), subthreshold slope (SS), drain-induced barrier lowering (DIBL), and I<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</inf>/I<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OFF</inf> ratio are extracted using TCAD simulations. The results demonstrate enhanced switching behavior and reduced leakage, confirming the potential of GAA-NWFETs in high-performance, low-power digital circuits. Furthermore, digital building blocks like inverter circuits are analyzed to evaluate their static and dynamic performance using the proposed device structure. The findings validate the feasibility of GAA-NWFET-based circuits for next-generation integrated systems, offering a pathway toward energy-efficient nanoelectronics design.
Performance-Centric Design and Physical Verification of Asynchronous FIFO for Low-Latency Applications Kurivella Manikanta, G Siva Sankar Varma, Jangili Anjali, Devarla Shashidhar, Mallem Shivamani 2025 5th International Conference on Artificial Intelligence and Signal Processing Aisp 2025, 2025 This manuscript focuses on the ASIC Design and Verification of an Asynchronous FIFO, with the primary goal of improving timing performance for efficient data transfer between asynchronous clock domains. The FIFO is implemented in System Verilog, incorporating dual-port memory, gray code pointer synchronization, and reliable full/empty flag logic. Verification is carried out using System Verilog and Universal Verification Methodology (UVM), with comprehensive test bench components. The entire design flow, including simulation (Xcelium), synthesis (Genus), and physical design (Innovus), is performed using Cadence tools. Results validate the design’s robustness, low power operation, and effectiveness for ASIC implementation in modern digital systems.
TFET Based Biosensor Using Dielectric Modulation Technique Manikanta Kurivella, Umakanta Nanda, Chandan Kumar Pandey IEEE Region 10 Annual International Conference Proceedings TENCON, 2024 In this era of fast-growing low-power semiconductor technology, there is a need for a best-in-the-market health monitoring system using transistor-based devices. Different semi-conductor technologies are used in our health monitoring system. However, this paper is concentrating on the Bio-FETs. Using Bio-FETs, detecting biomolecules is very effortless and has superior detection capability, less power, less cost, and label-less detection. When compared to MOSFETs, the properties of the TFET-based Bio-FETs have made them more sustainable as MOSFETs have some major issues like short channel effects (SCEs) and leakage current caused by the thermionic emission of electrons. A theoretical restriction on the subthreshold slope (SS greater than 60 mv/Dec) of the FET limits device performance in terms of sensitivity and increases power consumption. To overcome these effects, TFET is becoming the workhorse in manufacturing transistor-based biosensors. This paper demonstrates the TFET-based biosensor by using dielectric modulating technique including various structures, and the underlying mechanisms covering interpretative and quasi-experimental research parameters anal-ysis such as sensitivity parameters and distinct factors influencing the sensitivity parameter.
Impact of Dielectric Materials in an Asymmetrical Shaped Band to Band TFET Manikanta Kurivella, Umakanta Nanda, Sreeram Mounika, Chandan Kumar Pandey IEEE Region 10 Annual International Conference Proceedings TENCON, 2024 In this manuscript, the band-to-band tunnel field effect transistor TFET has an asymmetrical structure and is named a T-shaped channel TFET. The TFET drain current and transconductance parameters are analyzed at different dielectric materials and doping concentrations. Here observed that the ON current of the TEFT is high for HfO2 gate dielectric compared to other materials. Also, the switching ratio of the TFET is higher than other material combinations. All these analyses are carried out in the TCAD-Sentaurus software. Due to double gate TFET, the device is better immune to the short channel variations. Because the device drives controllability more towards the gates. The doping concentration of the TFET also changes the drain current of the device.
