Convergence of Artificial Intelligence, Machine Learning, and the Internet of Things in Industry 4.0 Applications

Amrita Rai received her B. Tech (Electronics) degree from the College of Engineering Chandpur, affiliated with Nagpur University, in 1998. She earned her M.Tech degree from Maharishi Dayanand University, Rohtak, where she was the university topper, in 2007, and her PhD in Signal Processing from Thapar University, Patiala (previously Thapar Institute of Engineering and Technology), in 2015. With over 21 years of experience in teaching, research, and administration, Dr. Rai has published several papers in reputed international journals and has attended various national and international IEEE conferences. She has guided more than 20 postgraduate (PG) and 100 undergraduate (UG) theses. Additionally, she is the author of the book "Principles of VLSI and CMOS Integrated Circuits" and has written six book chapters. Dr. Rai serves as a reviewer for several prestigious journals and conferences. She has filed six patents and delivered expert lectures on topics such as Smart Sensors, IoT and sensors, and Adaptive Signal Processing at various universities and colleges. She has also chaired sessions at numerous national and international conferences. Dr. Rai was a senior member of the IEEE Delhi Section Society and has contributed to many international/SCI journals and conferences. She has published 13 national and international patents and received grants for two of her patents. Dinesh Kumar Singh earned his B.E. in Electronics and Communication Engineering from Kumaon Engineering College in Dwarahat, Almora, in 2003. He holds an M.Tech in Digital Communication from RGPV University, Bhopal, India, and a Ph.D. from the Indian Institute of Technology (ISM), Dhanbad, Jharkhand. His research interests include microwave engineering, particularly designing high-gain, compact, reconfigurable, fractal-shaped, circularly polarized microstrip antennas, substrate integrated waveguides (SIW), and magneto-electric (ME) dipole antennas for modern communication systems. Currently, he is a Professor in the Department of Electronics and Communication Engineering at G L Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India. He has published more than 20 papers in various reputed international journals and conferences and serves as a reviewer for the AEU International Journal of Electronics and Communication and Electronics Letters, among others. Rupali Singh obtained her BE degree from Nagpur University in 2001, her M.Tech degree from Shobhit University, Meerut, in 2009, and her Ph.D. from the SRM Institute of Science and Technology, Ghaziabad, in 2021. Her research focuses on reversible logic circuits, quantum dot cellular automata, and nano-circuits. Dr. Singh possesses extensive teaching and research experience and has a good number of national and international publications to her name. She currently works at the School of Electronics and Communication Engineering at the SRM Institute of Science and Technology, Ghaziabad, India. She has published three patents and has received a grant for one of her patents. Korhan Cengiz is an Assistant Professor who completed his Ph.D. in the Department of Electronics Engineering at Kadir Has University. He is the author of more than 40 papers in the field of communications and has participated as a keynote speaker at several conferences. Dr. Cengiz holds various referee and editor positions in several IEEE journals and conferences and is a Senior Member of IEEE. He serves as an Associate Editor for IET Electronics Letters.

• Artificial Intelligence – An Overview.- VLSI and Neural Networks Integration in Industry 4.0: A Comprehensive Approach.- AI/ML-Based Approaches in Healthcare: Transforming Diagnosis, Treatment, and Beyond.- Maintaining Electronic Health Records using ML and IoT techniques.- Sentiment Analysis During Covid-19 using Machine Learning Techniques.- Transforming Industry 4.0 with AI, ML, and IoT: An Overview of Emerging Trends.- Synergizing VLSI and Neural Networks: Unveiling the Nexus of Innovation in Industry 4.0.- Securing E-Learning in the Era of Industry 4.0: A Data Mining Approach.- Channel Estimation in Beyond-5G Massive MIMO System Using Machine Learning.- Supervised Machine Learning Algorithms for Retinal vessel detection in the Retinal Images-A Comprehensive Approach.- Signal Processing techniques and Data Collection through Sensors in Industry 4.0Application.- Design a Photonic Crystal Fiber based Biosensor using a thin metals layer for Industry 4.0.- Detection and diagnosis of cervical cancer using machine learning models.- AI/ML based approaches in healthcare Industry.- Artificial Intelligence Techniques for Sentimental analysis during pandemic.- Precision Oncology: Innovations in Computational intelligent for Cancer Detection.