Emerging Trends in Microelectronics, Communication and Intelligent Systems: Proceedings of the International Conference, ETMCIS 2024

by Samaresh Das (Editor), Dhairya S. Arya (Editor), Dipti Y. Sakhare (Editor)

Overview

This book comprises select proceedings from the International Conference on Emerging Trends in Microelectronics, Communication and Intelligent Systems (ETMCIS 2024). It explores the synergies and intersections between engineering, artificial intelligence, microelectronics, communication, and signal processing. The book showcases the forefront areas of research in engineering, presenting readers with up-to-date insights and breakthrough discoveries. It highlights the latest studies, methodologies, and experimental findings, ensuring readers stay at the forefront of knowledge in these rapidly evolving fields. The book emphasizes real-world examples and implementation strategies to help readers grasp how these technologies can be leveraged to solve complex problems and improve existing systems.

Product Details

ISBN-13:	9789819664054
Publisher:	Springer Nature Singapore
Publication date:	11/04/2025
Series:	Lecture Notes in Electrical Engineering , #1420
Pages:	557
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

Samaresh Das is a Professor and Head of the Department at the Centre for Applied Research in Electronics (CARE) at the Indian Institute of Technology (IIT) Delhi, India. He earned his M.Sc. and Ph.D. degrees from the Indian Institute of Technology Kharagpur in 2005 and 2011, respectively. His doctoral research focused on Ge quantum dot-based floating gates, light emitters, and photodetectors on silicon substrates. After completing his Ph.D., Dr. Das joined the Ultimate Silicon Device Group at Tyndall National Institute in Ireland, under the leadership of Prof. Jean-Pierre Colinge. There, he worked on the fabrication and characterization of junctionless nanowire trigate MOSFETs. He later served as a research scientist at the Hitachi Cambridge Laboratory—Cavendish Laboratory at the University of Cambridge, contributing to the Quantum Information Project aimed at developing scalable silicon charge qubits. In September 2014, Dr. Das joined the Centre for Applied Research in Electronics at IIT Delhi as an assistant professor.

Dhairya Singh Arya is a scientist at CSIR-Central Scientific Instruments Organisation (CSIO) in Chandigarh, India. He received his B.Tech. and M.Tech. degrees in Electronics and Communication Engineering from Kurukshetra University, India, in 2012 and 2015, respectively. During his M.Tech. thesis, he collaborated with the Central Electronics Engineering Research Institute (CEERI) in Pilani, where he worked on piezoelectric-based MEMS acoustic sensors and MEMS hotplates. Dr. Arya earned his Ph.D. from the Indian Institute of Technology Delhi in 2022, with his doctoral research focused on "Bistable MEMS/NEMS-Based Switches for Rugged Embedded Applications: Non-Volatile Memory." His research expertise includes low-power MEMS/NEMS, micro-optoelectromechanical systems (MOEMS)-based devices, piezoelectric sensors and transducers, and NEMS terahertz detectors. His contributions to the field of micro- and nanoelectronics continue to drive advancements in sensor technology and energy-efficient device applications.

Dipti Y. Sakhare is a distinguished academician and researcher in Electronics Engineering, with over 20 years of teaching experience at MIT Academy of Engineering. She holds a Ph.D. in Electronics Engineering from Bharati Vidyapeeth Deemed University in Pune and specializes in digital design, VLSI, and embedded systems. Dr. Sakhare has received several prestigious accolades, including the MAAER’s Ideal Teacher Award, departmental honors for excellence in teaching, and the IUCEE Award for Best Practices in Teaching and Learning. She has been instrumental in securing significant research grants from AICTE and SPPU. Her scholarly contributions include an extensive publication record with numerous research papers and book chapters. Her research interests encompass text summarization, neural networks, and innovative VLSI designs, reflecting her dedication to technological advancements and academic excellence.

Table of Contents

An Efficient Method for Early Detection System for Cardiovascular Disease using Ensemble Machine Learning Techniques.- Word Recognition Using DTW.- Classroom Activity Detection using TinyML.- Analysis of Different Antenna Array Patterns for Hybrid Beamforming in Massive MIMO.- Design and Implementation of Cyclic Redundancy Check for Downlink Transmission in NB-IoT.- Performance Evaluation of CPU and GPU Processors Using Advanced Data Analysis Techniques.- A Survey on Skin Disease Detection Techniques through Deep Learning.- Fatigue and Drowsiness Detection using CNN.- Neuromorphic Computing Using RRAM.- Development of wearable beat-to-beat blood pressure variability monitor using differential pulse arrival time.- Machine Learning Based Sleep Pattern Analysis Using Linear Regression Algorithm.- ViD-Vision in Dark: Object Detection in Low-Light Images.- Intelligent Energy Management Systems for Future Smart Cities.- Design and Implementation of Vedic BCD Multiplier on Artix 7 FPGA Board.- Optimizing Sentiment Analysis in Airline Feedback: Feature Selection Impact on Machine Learning Models.- Sentiment Analysis on Medical Discharge Summaries.- Navigation and Control of SCARA Robot using Automation Studio.- APP BASED LEAF DISEASE DETECTION USING IMAGE PRE PROCESSING AND DEEP LEARNING.- Voice Command Enabled Robotic Arm: Enhancing in Human-Robot Interaction.- Comparative Analysis of NLP using various Machine Learning Methods.- Diabetes Prediction Using Machine Learning Algorithms with Different Feature Scaling Techniques.- Face Recognition-Based Smart Attendance Monitoring System Using Liveness Check and Geofencing.- Nonlinear Autoregressive with exogenous input (NARX) Neural Network based Machine Learning model for Time-series Application.- An L-Band Log-Periodic Dipole antenna for Future Moroccan CubeSat Projects.- Anaemia Prediction from Conjunctiva Images: Leveraging Pre-trained CNNs for Feature Extraction and Traditional ML for Classification.- Segmentation and Classification of Pulmonary diseases using Artificial Neural Networks and Otsu-Region Based Method from Chest Radiographs.- Recent Advances in Routing Techniques for IoT-Based Networks: A Comparative Analysis.- Performance Analysis of Hybrid Metal-Graphene THz MIMO Antenna with Equivalent ECM.- Manufacturing Setup for 4nm Semiconductor Integrated Circuits in India: Current Scenario and Opportunities.- Ambulance Relocation Using Deep Reinforcement Learning.- A Graph Based Hybrid Approach for Abstractive Text Summarization using Fastformers to Study Different Performance Matrices.- Image Inpainting using Two Stage Generative Inpainting Network with Contextual Attention.- Maharashtra Engineering College Admission Prediction - A Solution Using Ensemble Machine Learning Model.- Design and Development of an Energy and Power Management Strategy for Dual Energy Storage System for E-Bicycle.- Influence of Micro Cavity Fill Factor on Sensitivity Performance of MOS-HEMT device based Biomolecule Detector.- Temporal Evaluation of SPI and RDI for Agricultural Drought Analysis in Ahmednagar from 1981-2021.- EEG-based Cognitive load detection using pre-trained CNN.- ARTIFICIAL INTELLIGENCE BASED TRUST EVALUATION FOR ATTACKS DETECTION IN THE HEALTH-CARE DOMAIN.- Harvest Insight: Crop Yield Prediction Using Machine Learning Approach.- Averaged State Space Analysis of Single Phase Vienna Rectifier.- Performance Enhancement of Multiband Terahertz Patch Antennas Using Complementary Split Ring Reso-nators.- An Automated Approach for the Detection of Synthetic and Deepfake Media using Deep Learning.