IoT, Big Data and AI for Improving Quality of Everyday Life: Present and Future Challenges: IOT, Data Science and Artificial Intelligence Technologies (Studies in Computational Intelligence, 1104). Cet article n’est pas disponible.IoT, Big Data and AI for Improving Quality of Everyday Life: Present and Future Challenges: IOT, Data Science and Artificial Intelligence Technologies (Studies in Computational Intelligence, 1104)

This book focuses mainly on the usages of three key technologies: IoT, big data, and AI for various day to day applications. Further, it explores the possibilities of future research based on the usages of latest information systems.

This book explores the current research and challenges to be faced by different researchers for building intelligent information solutions using key technologies; IoT, big data, and AI in improving quality of lives in smart cities and explores the limitations and capabilities of these three key computing technologies. The book is organized into three major parts; each part includes chapters exploring a specific topic, and there are: PART-1: IoT for Real World Solutions, (ii) Part-2: Big Data And Cloud Computing for Innovative Solutions For Day to Day Lives, and (iii) Part-3 Artificial Intelligence for Everyday Lives. This book may be useful to the scientists, scholars, and researchers who are working in the field of computer science and engineering, and communication engineering, along with the students in these subjects who are working or willing to work on IoT, big data, and AI technologies for improving quality of everyday life. Specialists as well as student readers find the book chapters encouraging and helpful.

IoT, data science & cloud, and AI all are the undergraduate (UG/ bachelor) subjects. Use of these three key technologies for building new applications for better world is helpful for UG and postgraduate (PG/ MS) Programmes students (as an elective and core course). This book may also be very useful for the Ph.D. (research scholars) during their course work and may be used as an instrument to identify the different challenges associated with information systems.