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AI, IOT AND MACHINE LEARNING BASICS

Dr Aadam Quraishi MD,.MBA has research and development roles involving some combination of NLP, deep learning, reinforcement learning, computer vision, predictive modeling. He is actively leading team of data scientists, ML researchers and engineers, taking research across full machine learning life cycle – data access, infrastructure, model R&D, systems design and deployment.

Dr. Brajesh Kumar Singh, Received the B. Tech in Electronics and Communication Engineering from Delhi Technological University, New Delhi (Formerly DCE, Delhi University) and, M. Tech and P. hD. both completed from Guru Gobind Singh Indraprastha University, New Delhi. He is working as Associate Professor in Galgotia College of Engineering and Technology (GCET), Greater Noida, Utter Pradesh, India. He has more than 14 years of teaching experience He has published more than 17 research papers in international Journals, 8 International Conferences, 5 Patents in the field of Image processing, Biometrics, Machine Learning, Communication Technology and IoT.

Ismail Keshta received his B.Sc. and the M.Sc. degrees in computer engineering and his Ph.D. in computer science and engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, in 2009, 2011, and 2016, respectively. He was a lecturer in the Computer Engineering Department of KFUPM from 2012 to 2016. Prior to that, in 2011, he was a lecturer in Princess Nourah bint Abdulrahman University and Imam Muhammad ibn Saud Islamic University, Riyadh, Saudi Arabia. He is currently an assistant professor in the computer science and information systems department of AlMaarefa University, Riyadh, Saudi Arabia. His research interests include software process improvement, modeling, and intelligent systems.

Dr. Haewon Byeon received the Dr. degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AI-medicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 343 articles and 19 books.

 

 

Description

A revolutionary change in technology is being brought about by the confluence of Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML). This transition is altering industries as well as everyday lives. The purpose of this article is to offer an introduction to the key concepts, features, and linkages that are associated with our three technologies. Artificial intelligence, capable of imitating human intelligence, is the foundation upon which decision-making and predictive analytics are created. The Internet of Things (IoT) connects physical objects, which enables data exchange and communication that is seamless. ML, which is a subset of AI, gives computers the ability to learn and improve based on data without the need for conscious programming. Incorporating artificial intelligence and machine learning into the Internet of Things ecosystems provides intelligent automation, real-time analytics, and improved user experiences. There are a wide variety of applications, ranging from personalized consumer technology and industrial automation to smart cities and revolutionary healthcare advancements. The obstacles that are involved in deploying these technologies are also brought to light by this study. These challenges include concerns regarding data privacy, issues with scalability, and ethical considerations. The purpose of this article is to give a basic knowledge of the revolutionary potential of artificial intelligence, the Internet of Things, and machine learning by emphasizing the synergy between these three technologies

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