This book contains the proceedings of the 1st International Conference on Artificial Intelligence, Computing Technologies, Internet of Things, and Data Analytics AICTA 2023. The theme of the conference is Artificial Intelligence and Its Applications. It focuses on recent trends and innovative approaches across various domains of Computer Engineering, such as cloud computing, image processing and computer vision, machine learning and deep learning, IoT, analytics, and security. The book introduces new ideas in artificial intelligence and its subfields, including machine learning and deep neural networks. This volume will be valuable for researchers and practitioners in computer engineering and related fields.

Consists proceedings of the International Conference on AICTA 2023 Discusses research ideas and real-time experiences in the field of artificial intelligence and its applications Useful for researchers and practitioners working in the field of computer engineering

Autorentext

Badal Soni is an Assistant Professor in the Department of Computer Engineering at the National Institute of Technology (NIT) Silchar, India. He completed his B.Tech from Rajiv Gandhi Technical University (formerly RGPV) in Bhopal, India, and his M.Tech from the Indian Institute of Information Technology Design and Manufacturing (IIITDM) Jabalpur, India. Dr. Soni earned his Ph.D. from NIT Silchar. With over twelve years of teaching and research experience in computer science and information technology, he specializes in image processing, machine learning, and natural language processing. Dr. Soni has published over 95 papers in international journals and conference proceedings, 02 authored books, and 05 edited books. He is a senior member of IEEE and holds professional membership in various organizations, including IEEE, ACM, IAENG, and IACSIT.

Poonam Saini is an Associate Professor in the Department of Computer Science and Engineering at Punjab Engineering College, Chandigarh. She obtained her Ph.D. in Computer Engineering from the National Institute of Technology, Kurukshetra. Her research interests include fault-tolerant distributed computing systems, cloud computing, blockchain technology, big data analytics, and explainable AI. Dr. Saini has 16 years of teaching and research experience and has published over 60 articles in prestigious journals, conferences, edited volumes, and arXiv. She has been recognized as a Senior Member of IEEE for her significant contributions to research.

Gyanendra K. Verma is an Assistant Professor in the Department of Computer Engineering at the National Institute of Technology Kurukshetra, India. He earned his B.Tech from Harcourt Butler Technical University (formerly HBTI) Kanpur, India, and both his M.Tech and Ph.D. from the Indian Institute of Information Technology Allahabad (IIITA), India, with a focus on Information Technology. Dr. Verma has over six years of teaching and research experience in computer science and information technology, specializing in image processing, speech and language processing, and human-computer interaction. His work on affective computing and the application of wavelet transforms in medical imaging and computer vision has been extensively cited. He is a member of professional organizations such as IEEE, ACM, IAENG, and IACSIT.

Brij Bhooshan Gupta is a Distinguished Professor in the Department of Computer Science and Information Engineering (CSIE) at Asia University, Taiwan. He has published over 500 papers in journals and conferences, authored 30 books, and holds 10 patents. Dr. Gupta is an Indian scholar who received his Ph.D. from the Indian Institute of Technology (IIT) Roorkee. His research interests span a wide range of topics, including cybersecurity, cloud computing, artificial intelligence, intrusion detection, blockchain technologies, cyber-physical systems, social media, and networking.

Inhalt

Exploring the association between Mental Health and Efficacy using Student Dataset.- Enhancing Predictive Maintenance for Induction
Motors: A 3D Holography-Based Digital Twin Approach with Extended Kalman Filter.- YouTube Video Performance: Leveraging Data Analysis and Forecasting with ARIMA Modeling for Optimal Engagement.