Overview

The rapid convergence of material science, electronics, and wearable technology has catalyzed the emergence of electronic textiles and conductive materials as foundational elements in the next generation of smart wearables. These innovative fabrics go beyond traditional clothing, integrating sensing, communication, and energy management capabilities to transform how we interact with the digital world. As demand grows for flexible, durable, and comfortable wearable systems that can monitor physiological signals, support remote healthcare, and enhance human-machine interaction, electronic textiles are poised to redefine both consumer applications and industrial solutions. Next-Generation Electronic Textiles and Conductive Materials for Smart Wearables brings together interdisciplinary research and innovation across smart materials, nanoengineering, textile manufacturing, and biomedical integration. It highlights the latest advances in conductive polymers, graphene-infused fabrics, flexible printed electronics, and fiber-based sensors, while addressing critical challenges such as washability, signal fidelity, and data security. Covering topics such as 3D printing, nanomaterials, and wireless communications, this book is an excellent resource for researchers, engineers, academicians, healthcare professionals, product developers, innovators, and more.

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9798337342870

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Pranshu Saxena received the B. E. in (2010), M. Tech. (2013), and PhD in 2023. He is currently an Assistant Professor in the School of Computer Science Engineering and Technology at the Bennett University, Greater Noida, India. He has published 24 research articles which include 6-SCI, 6-Scopus, and 12 peer-review journals/conferences. His research interests include medical image processing, automated image segmentation, Image texture analysis, intelligent system and Pattern Classification. He has been a designated reviewer (ISIEA 2012-2013, IJERT) and committee member (IJACR) for many international conferences and journals in image processing and medical imaging. He has published one book published by LAP Lambert Academic Publishing, USA. Mandeep Singh is an accomplished academician and Assistant Professor in the School of Computer Science, Engineering, and Technology (SCSET) at Bennett University, Greater Noida, India. He holds a Master's degree with Distinction in Information Security from Ambedkar Institute of Advanced Communication Technologies and Research (AIACTR) (now NSUT East Campus). With over nine years of teaching experience, he is currently pursuing a Ph.D. in Computer Science & Engineering from Dr. B.R. Ambedkar National Institute of Technology (NIT) Jalandhar, where he completed his coursework with Distinction (8.00 CGPA). Mr. Singh's expertise spans Computer Networks, Mobile Ad Hoc Networks (MANETs), Machine Learning, and Deep Learning. His research contributions include book chapters, international journals, and conference proceedings, alongside a notable track record of patent publications. Some of his patents address cybersecurity in email communication, AI-powered agricultural robotics, and intelligent machine vision systems. Additionally, he actively reviews papers for international conferences and journals and has held special sessions at prestigious events, including the International Conference on Computing and Communication Networks (ICCCNet). His dedication to excellence has earned him awards and recognition from the Institute of Industrial Development (IID) and MSME, Government of India for contributions to research and entrepreneurship. Sanjay Kumar Singh is currently working as an assistant professor in university school of automation and Robotics, Guru Gobind Singh Indraprastha University, East Delhi campus, Delhi. He has more than 12 years of experience in teaching and received integrated post graduate (B. Tech + M. Tech) degree from ABV-Indian Institute of Information Technology & Management, Gwalior and Ph. D. degree from IKG-Punjab Technical University. He has published more than 50 papers in reputed journals and international conferences. His area of research in the field of machine learning, deep learning, soft computing and intelligent systems.

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