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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.
This book is essential for anyone interested in understanding how smart agriculture, utilizing information and technology such as computer vision and deep learning, can revolutionize agriculture productivity, resolve ongoing concerns, and enhance economic and general effectiveness in farming. The need for a reliable food supply has driven the development of smart agriculture, which leverages technology to assist farmers, especially in remote areas. A key component is computer vision (CV) technology, which, combined with deep learning, can manage agricultural productivity and enhance automation systems for improved efficiency and cost-effectiveness. Automation in agriculture ensures benefits like reduced costs, high performance, and accuracy. Aerial imaging and high-throughput research enable effective crop monitoring and management. Computer vision and AI models aid in detecting plant health, impurities, and pests, supporting sustainable farming. This book explores using CV and AI to develop smart agriculture through deep learning, data mining, and intelligent applications.
This proceedings book presents a comprehensive view of “smart” technologies and perspectives of their application in various areas of economic activity. The authors of the book combined the results of the cutting-edge research on the topic of “smart” technologies in the digital economy and Industry 4.0 and developed a unified scientific concept. The current experience has been considered, and the prospects for the application of “smart” technologies in society to promote social advance have been identified. “Smart” technologies in public administration and law, as well as the experience in development of e-government, have been examined. “Smart” technologies in business activity have been studied, and the transition from digital business to business 4.0 has been justified. The book contains the collection of the best works following the results of the 13th International Research-to-Practice Conference “Smart Technologies” for society, state and economy which was run by the Institute of Scientific Communications (ISC) and was held on July 2–3, 2020. The target audience of this book includes researchers investigating fundamental and applied problems of development of “smart” technologies, as well as concerned parties outside the academic community, in particular, representatives of the digital society, high-tech business entities and officials regulating the digital economy and Industry 4.0.
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
An AI-International Law Handbook: Part 1,
Carbon markets involve complex governance challenges, such as ensuring transparency of emissions, facilitating as well as recording transactions, overseeing market activity and preventing abuse. Conventionally, these have been addressed with a combination of regulatory, procedural and technical structures that impose significant burdens on market participants and administrators while remaining vulnerable to system shocks and illicit practices. Distributed Ledger Technology (DLT) has the potential to address these problems. This volume offers the first book-length exploration of how carbon markets can be governed using DLT, offering conceptual and theoretical analysis, practical case studies, and a roadmap for implementation of a DLT-based architecture in major existing and emerging carbon markets. It surveys existing expertise on distributed ledger technology, provides progress updates from industry professionals, and shows how this technology could offer a cost-effective and sustainable solution to double-counting and other governance concerns identified as major challenges in the implementation of carbon markets.
This book highlights recent findings in civil and environmental engineering and urban planning, and provides an overview of the state of the art in these fields, mainly in Russia and Eastern Europe. A broad range of topics and issues in modern engineering are discussed, including construction, buildings and structures, advanced materials, innovative technology, methods and techniques in civil engineering, heating, gas supply, water supply and sewerage, foundation engineering, BIM, structural reliability, durability and monitoring, special and unique structures construction (bridge, tunnel, road, railway engineering), design and construction of hydraulic structures, concrete engineering, urban regeneration and sustainable development, urban transport system, engineering structure safety and disaster prevention, water resources engineering, water and wastewater treatment, recycling and reuse of wastewater, etc. The volume gathers selected papers from the 6th International Conference on Construction, Architecture and Technosphere Safety (ICCATS), held in Sochi, Russia in September 2022. The authors are experts in various fields of engineering, and all papers have been carefully reviewed.
Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.
Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.